Networked Control Systems for Connected and Automated Vehicles: Volume 2 (Lecture Notes in Networks and Systems, 510) 3031110501, 9783031110504
Control of large-scale distributed energy systems over communication networks is an important topic with many applicatio
130 7 49MB
English Pages 2104 [2004] Year 2022
Contents
Proposals for Development of Piggyback Transportation in the South of Russia
1 Introduction
2 Research Method
3 Research Results
4 Discussion
References
Model of Atmospheric Effects Onto a Group of Unmanned Aerial Vehicles
1 Introduction
2 Representation of the Most Significant Atmospheric Impacts in the Form of Fuzzy Sets
3 Model for Determining the Probability of UAV Damage as a Result of Atmospheric Influences
4 Determining the Probability of UAV Damage as a Result of Environmental Factors
5 Conclusions
References
Reinforcement of the Railway Roadbed with Soil-Concrete for the Passage of Heavy Rolling Stock
1 Introduction
2 Research Method
3 Research Results
4 Results Discussion
5 Conclusion
References
Estimation of the Resource of Spiroid Transmissions by the Condition Maximum Wear and Tear
1 Introduction
2 Research Methods
3 The Results of the Study
4 Discussion of the Results
References
Principles of Designing Asymmetric Rail Profiles
1 Introduction
2 Problem Statement
3 Theoretical Research
4 Research Results
5 Main Conclusions
References
Mathematical Modeling Technique for Designing a Composite Technological Process for Machining Holes in Laminated Parts
1 Introduction
2 Research Methods
3 Research Results
4 Conclusion
References
Design Criteria for Variable Rigidity Sections of Approach Embankments to Bridges and Overhead Crossings
1 Introduction
2 Research Methods
3 Research Results
4 Conclusion
References
Definition Model of the Optimal Size of the Material Resources in Construction
1 Introduction
2 Research Methodology
3 Research Results
4 Conclusion
References
Rationale for the Machine Complex Performance
1 Introduction
2 Research Methods
3 Research Results
4 Results and Discussion
5 Conclusion
References
Experimental Studies of Fiber Concrete Samples Under Cyclic Load
1 Introduction
2 Research Methods
3 Research Results
4 Conclusions
References
Application Effectiveness Analysis of the Thin-Walled Building Components for Transport Infrastructure Facilities
1 Introduction
2 Research Methods
3 Research Results
4 Conclusion
References
Experimental Study of Dynamic Forces Acting on Wheel Pairs of Railway Rolling Stock in Operation
1 Introduction
2 Methods and Equipment of Strain Gauge Control
3 Strain Gauge Control Results
4 Main Conclusions and Results Analysis
References
Simulation of the Track Machinery Technical Condition to Ensure Safe Operation
1 Introduction
2 Problem Solution
3 Conclusion
References
Development of On-Board Systems of Predictive Diagnostics of Electric Rolling Stock Traction Motor
1 Introduction
2 Materials and Methods
2.1 Mathematical Method
2.2 Heat Technique
2.3 Development of Software for Presenting Statistical Data
2.4 Calculation of Statistical Data to Determine the Residual Life of Traction Electric Motor
3 Results
4 Discussion
References
Accident Prevention System at Unguarded Railway Crossings
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Analyzing the Movement of a Freight Train at Stops on Flat Sections of the Railway
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Computer Modeling of Repair Technological Systems in Design Practice
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Improvement of Methods of Energy Optimal Automatic Operation of Electric Freight Locomotives
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
The Improvement of On-Board Systems for Predictive Technical Diagnostics of Mainline Electric Freight Locomotives Based on Digital Models
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Influence of Changes in External Factors on the Energy Efficiency Parameters of Electric Locomotives
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Preventive Diagnostics of Technical Condition of Inter-Turn Insulation of Traction Electric Motors Anchor Windings
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Improvement of the Traction Resource Management System to Enhance the Performance of Electric Rolling Stock
1 Introduction
2 Materials and Methods
3 Results
4 Discussion and Conclusions
References
Optimization of the Technology of Electrolytic Zincing of Traction Mechanisms Parts
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Control of Mainline Freight Electric Locomotives with Adjustment of Operating Modes
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Determining Optimal Electrical Discharge Machining Modes for the Disc Tab Grooves of Small-Size By-Passengine
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Modelling of Heating Process of the High-Pressure Fuel Pipeline of the Fuel Equipment of Diesel Locomotives
1 Introduction
2 Research Objectives
3 Mathematical Model Development
4 Conclusions
References
Improvement Metrological Support of the Technological Process of Repair of the Auto-Couple Device of the Railway Carriage
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Influence of Freight Locomotive Modernization by Increasing of Diesel Generator Set Power on the Mechanical Strength of Traction Drive
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Identification of Wind Loads Through Train Statistical Analysis
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Improvement of Edge Cutting Machining of Materials with Fatigue and Thermomechanical Failures
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
The Impact of the Transport Factor on Regional Development
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Choosing a Method for Studying Rail Vehicles’ Oscillations with Nonlinear Suspension Characteristics
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
The Effect of Distributed Generation Plants’ Prognostic Controllers on Power Quality in Power Supply Systems of Non-traction Consumers
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Increasing the Reliability of Diagnosing Power Transformers by Using a Defect Simulator
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Energy Intensity and Energy Efficiency of Energy Saving Policy of Railway Transport
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Production of Au Nanoparticles by Laser Ablation in Liquids
1 Introduction
2 Materials and Methods
3 Results
3.1 Number of Pulses
3.2 Energy
3.3 Rate of Extinction Growth
3.4 Nanoparticle Sizes
4 Conclusion
References
Improving the Efficiency of the Locomotive Complex Through Modern Methods of Managing Traction Resources
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Additive Technologies Features for Manufacturing Metal Products from Powder Materials by Direct Laser Deposition
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Image Processing for Visual Inspection of Hollow Reinforced Concrete Supports’ Inside Surfaces
1 Introduction
2 Methods
3 Main Part
4 Results
5 Conclusion
References
The Use of Heat Pump Systems for Heat Supply to Consumers
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
References
Designing a 3D Application Based on Digital Models of Railway Infrastructure
1 Introduction
2 Methods
3 Results
3.1 Creating a 3D Railway Space in the Trainz Railway Simulator
3.2 Contact Network
3.3 Railway Tracks
3.4 Implemented Track Development
3.5 Industry Work
3.6 Control Unit Su DSP (zxPath)
3.7 Artificial Intelligence
4 Conclusions
References
Designing a 3D Application Based on Digital Models of Rolling Stock
1 Introduction
2 Methods
3 Results
4 Conclusions
References
Energy Efficiency Level Analysis of Train Traction in a Structural Unit
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Combined Heat Pump and Solar Collector Application
1 Introduction
2 Object and Methods of Research
3 Results
4 Conclusions
References
Selecting the Optimum Design Solution for Rolling Stock Repair Plants Under Multiple Preference Criteria
1 Introduction
2 Object and Methods of Research
3 Results
4 Conclusions
References
Improving the Efficiency of Center-to Center Spacing Control
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
The Linearization Method to Calculate the Equilibrium Composition of Combustion Products of Diesel Engine
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Energy Efficiency of the Innovative Fifth-Generation 2ES5S Electric Freight Locomotive and the Results of its Tests
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
The Role of Diesel Locomotives Operating Modes in Simulating the Operation of Fuel and Control Equipment of Diesel Locomotives
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
The Categorization of Methods and Means of Energy Optimized Control of Electric Railway Rolling Stock
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
References
Interval Estimation of Magnetotelluric Response Function and Quality Control During Registration of Data
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusions
References
Control Method for Mainline Freight Electric Locomotives with the Possibility of Adjusting Movement Modes
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
Modeling the Management of an Economic System Based on Random Processes
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
The Prospective Model of Organization of Freight Transportation on the North Caucasian Railway Range
1 Introduction
2 Materials and Methods
2.1 Basic Organizational and Technical Measures to Increase the Carrying Capacity
2.2 The Analysis of the Carrying Capacity of the Heavy Direction Kotelnikovo—Tikhoretskaya—Kozyr’ki—Raz’’yezd 9 km—Vyshestebliyevskaya
2.3 Calculation of Carrying Capacity in the Considered Direction
2.4 Strengthening the Carrying Capacity of the Studied Direction
3 Results and Discussion
4 Conclusions
References
Implementation of «Lean Manufacturing» in the Construction and Transport Construction Industry
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Summary
References
The Essence and Features of the Construction Management System in the Conditions of Uncertainty
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Summary
References
Innovative Forms of Investment in Housing and Communal Services Projects
1 Introduction
2 Methods and Materials
3 Results and Discussions
4 Summary
References
The Impact of the Competitiveness of the Transport and Construction Industry on the Stability of the Socio-Economic System (SES)
1 Introduction
2 Materials and Methods
2.1 Materials
2.2 Methods
3 Results
4 Discussion
5 Summary
References
Innovations, Labor Productivity, Human Capital in the Construction Industry
1 Introduction
2 Methods and Materials
3 Results and Discussions
4 Summary
References
Systems of Indicators for a Comprehensive Assessment of the Stability of the Functioning of Enterprises in the Construction and Transport Industry
1 Introduction
2 Methods and Techniques
3 Results and Discussion
4 Summary
References
Approaches to of the Effective Assessment of Transportation Professionals’ Skills in Terms of Concept of Human Capital in «New» Economy
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Summary
References
Comparative and Correlation Analysis of the Parameters of Digitalization and Innovation Activity of Business and Transport Organizations
1 Introduction
2 Methods and Materials
3 Results and Discussions
4 Summary
References
Design of a Project Office When the Implementation of Investment of it in Construction Including a Transport Field
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Summary
References
Methodic Approaches to the Assessment of Regional Investment Attractiveness in the Sphere of Tourism and Transport Infrastructure
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Summary
References
Differentiation of Regional Development as a Factor of Destabilization of the Development of Innovative Potential and Transport Infrastructure of the Constituent Entities of the Russian Federation
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
A Model for Optimizing Transaction Costs in the Implementation of Intellectual Entrepreneurship in the Digital Economy
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Discussions
5 Conclusion
References
Essence and Role of the Anti-crisis Strategy in Preventing the Bankruptcy of Transport Companies
1 Introduction
2 Methods
3 Results
4 Discussion
5 Summary
References
Russia Impact of Transport Accessibility of the Enterprise on the Cost of Delivery in E-Commerce
1 Introduction
2 Materials and Methods
3 Results
4 Summary
References
Multi-dimensional Assessment of Marketing Capability on the Example of Transport Business Organizations
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion
References
The Formation of an Investment and a Transport Investment Innovation System Model of the Region
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
Study of the Level of Digitalization of the Banking Sector of Russia in the Context of the Pandemic and the Development of Transport Technologies
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
On the Problem of Investment and Innovation Activity
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
Quality Management in Modern Business and Transport Business Activities
1 Introduction
2 Research Methodology
3 Results
3.1 Quality as the Basis of Business Competitiveness
3.2 The Quality Measure is Dictated by the Consumer
3.3 Compliance with the Standard as a Quality Measure
3.4 Enterprise Management by Quality Criteria
3.5 Managing Quality Means Managing a Business
3.6 Project Approach to Quality Management
3.7 Training Specialists for Quality Management
4 Discussion
5 Conclusion
References
Transport and Industrial Construction as a Driver of Commercialized Innovations in Regional Production Systems
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Express Assessment of Business and Marketing Environment of an Industrial and Transport Enterprise on the Basis of Probabilistic-Attributive Approach Assessment
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
COVID-19 and Its Impact on Construction and Transport Construction Economy: An Integrated Framework
1 Introduction
2 Materials and Methods
3 Results and Discussions
3.1 India Real Estate Sector: Changing Dynamics
4 Conclusion
References
Human Capital as the Market Value of a Geomarketing and Transport System
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
Diagnostics of the Depth of Digitalization of Industrial Enterprises of the Construction and Transport Construction Complex
1 Introduction
2 Materials and Methods
3 Results and Discussions
4 Conclusion
References
Impact of the Import Substitution Program on the Competitiveness of Industrial and Transport Enterprises
1 Introduction
2 Materials and Methods
2.1 Materials
2.2 Methods
3 Results and Discussions
4 Conclusion
References
Thermal and Economic Performance of a Solar Hot Water System in Tashkent
1 Introduction
2 Methods
2.1 System Configuration
2.2 Economic Analysis
3 Results and Discussion
4 Conclusions
References
Influence of Heat and Humidity Conditions on the Operation of the Pin Connections
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusions
References
Pattern of Distribution of Carbon Nanotubes in the Matrix of Polymer Compositions for Wood Stabilization
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
Application of Information Systems in the Technology of Servicing Energy Consumers
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Criteria for Measuring the Economic Efficiency of Projects Based on Reusable Information Models
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusions
References
Research and Selection of Rational Parameters of a Refrigerated Container Terminal
1 Introduction
2 Literature Review
3 Method. Structural and Parametric Description of a Refrigerated Container Terminal
4 Determination of the Capacity of the Terminal Storage Area
5 Results
6 Discussion
7 Conclusion
References
The Phenomenon of “Bias of Assessment” as the Basis of a Behavioral Model and a Potential Source of Problems
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Effect of Phubbing on Students’ Performance
1 Introduction
1.1 Literature Review
2 Methods and Materials
3 Results and Discussion
3.1 The Online Survey
3.2 The Interview
3.3 The Correlation Analysis
4 Conclusion
References
Improving Management Methods for the Formation and Use of Information Resources of Enterprises
1 Introduction
2 Methods and Materials
3 Results
4 Discussion
5 Conclusions
References
Influence of Changes in the Pavement Concrete Moisture on Its Water Resistance During Traffic Exploitation
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
The Freezing Zone Formation of the Probe Around the Vertical Ground Heat Pumps
1 Introduction
2 Formulation of the Problem
3 Numerical Solutions and Analysis of Results
4 Conclusions
References
The Limiting Rut Depth by Conditions Safety of Traffic
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
References
Investigation of the Conditions for the Occurrence of Rail-Ground Potentials on AC Railways
1 Introduction
2 Materials and Methods
3 Modeling
4 Experiment
5 Conclusions
References
Conditions for Compliance Lewis Relationship When Air Flow is Contact with Ice
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Approximate Solution of the Heat Transfer Equation as a Function of the Transfer Potential Coefficient
1 Introduction
2 Methods and Materials
3 The Results of the Studies
4 Conclusion
References
Method for BIM and GIS Databases Integration for CIM Creation Support
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Modeling Professional Risk
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Sino-Russian Experience in Smart Grid Development: Issues and Perspectives
1 Introduction
2 Materials and Methods
2.1 Chinese Smart Grid Concept Materials and Power Energy Methods
2.2 Chinese Management System of Smart Grid
3 Results and Discussion
4 Conclusions
References
Prediction of the Service Life of Hybrid Ceramic Bearings by Integrated Deep Learning and Particle Filter Methods
1 Introduction
2 Validation
2.1 Hybrid Ceramic Bearing Run-to-Failure Test Setup
2.2 Hybrid Ceramic Bearing RUL Prediction Results
3 Conclusions
References
Resource-Efficient Use of Hydrocarbon Raw Materials as a Factor in the Transition to a “Green” Economy
1 Introduction
2 Review of Literature
3 Methods
4 Conclusion
References
Long Wave Dynamics in Heavy Wave Gravitating Fluid in Vlasov Type Model
1 Introduction
2 Materials and Methods
2.1 Kinetic Equation for Describing Long-Wave Motions in a Swirling Fluid
2.2 Description of the Classical Shallow Water Theory and Their Vortex Generalizations
3 Results
3.1 Group Properties and Some Exact Solutions for the Theory of Shallow Water with Dispersion (k) = 1 + αk2
3.2 Landau Attenuation for Long Waves on Water in a Liquid with a Free Surface for Arbitrary Dispersion
3.3 Approximate Calculation of the Landau Attenuation Coefficient Near the Long-Wave Limit (k =0)
4 Discussion
5 Conclusion
References
The System for Modeling and Visualizing 3D Algebraic Functions
1 Introduction
2 Materials and Methods
2.1 Methodology: Description of Modeling Language
2.2 Calculation System
2.3 Visualization
3 Results
4 Conclusions
References
Predictive Assessment of Dynamics Intellectual Activity Index National Innovation-Oriented System
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Digital Simulators and Training Devices for Solving Geometric Problems
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
The Effect of Visual Information Contained in Digital Training Courses on the Renewal of Working Memory
1 Introduction
1.1 Positive and Negative Impact
1.2 Working Memory
2 Materials and Methods
3 Results and Discussion
3.1 Proportion of Correct Answers
3.2 False Alarm Rate
3.3 Response Time
4 Conclusion
References
Soft Skills Development by Means of Digital Pedagogical Cues
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Methodological Approaches to Modeling Dynamic Development of Regional Ecological and Socio-Economic Systems
1 Introduction
2 Methods
3 Discussions
References
Icebreaker Fleet Management in Simulation Models of the Arctic Marine Transport Systems
1 Introduction
2 Materials and Methods
2.1 “Greedy” Ad hoc Algorithms
2.2 Method for Determining Areas of Responsibility (Support) and Optimal Placement of Icebreakers
2.3 Usage of the External Combinatorial Optimization Solver OptaPlanner for the Simulation
3 Results
4 Conclusions
References
Forecasting Temperature Change in Mine Workings at Change in Air Flow
1 Introduction
2 Methods
3 Discussion of Results
4 Conclusion
References
Modeling a Repertoire of Pilots’ Professional Communication Skills for Meeting Flight Safety and Aviation Security Challenges
1 Introduction
2 Materials and Methods
3 Results and Discussion
3.1 Communication Skills in Civil Aviation: Psychological and Functional Aspects
3.2 Prerequisites for Pilots’ Professional Communication Skills Typology
3.3 Functional Aspects of Pilots’ Professional Communication
3.4 Written Communication
3.5 The Repertoire of Pilots’ Professional Communication Skills
4 Conclusions
References
Rational Use of Hydrocarbon Resources in the Context of Environmental Sustainability of the Country
1 Literature Review
2 Methods
3 Conclusion
References
E-Learning Online Platforms for Educational Approach
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Numerical Study of the Intake Chambers of a Cotton Picker
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Particular Features of Call Tracking Technologies Application in Certain Industries
1 Introduction
2 Materials and Methods
2.1 Customer Survey
2.2 Method of Promotional Codes
2.3 Hidden Number
2.4 Static or Classic Call Tracking
2.5 Dynamic Call Tracking
2.6 Combined Call Tracking
3 Results and Discussions
3.1 Marketing Agencies
3.2 Tourism and Hotel Business
3.3 Education
3.4 Private Medicine
3.5 Legal Services
3.6 Financial Products
3.7 Automotive Industry
3.8 Real Estate
3.9 Household Services
3.10 Business-to-Business
4 Results and Discussion
5 Conclusion
References
Improved Method and Algorithm of Railway Crossing Automatic Signaling System
1 Introduction
2 An Improved Method of Transmitting Data to a Railway Crossing Signaling System
3 Algorithm of Operation of Railway Crossing on the Improved Method of Data Transmission to the Railway Crossing Signaling System
4 Modeling of the Method of Control of Approach Sections of Railway Crossings
5 Conclusion
References
Formation a Sustainable Supply Chain Strategy
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Mathematical Model of the Radial Bearing with a Fusible Metal Porous Coating
1 Introduction
2 Problem Statement
3 Conclusion
References
Mathematical Model of a Radial Bearing with Increased Bearing Capacity Operating on Lubrication with Melt on Shaft Surface
1 Introduction
2 Results
3 Conclusion
References
Leadership Vision in Advanced Technology
1 Introduction
1.1 Leadership
1.2 Leadership Skills
2 Methods
2.1 Technology
2.2 Technological Management and Competitive Advantage
3 Results
3.1 Technology Management
3.2 Technological Management and Competitive Superiority Skills
4 Conclusion
References
Architecture of Software Complex for Multicriteria Synthesis of Composite Materials
1 Introduction
2 Research Methods and Principles
3 Results
4 Discussion
5 Conclusion
References
Assessment of Heavy Metal Pollution in the Roadside Area of Motorways
1 Introduction
2 Research Methods
3 Experiment and Calculations
4 Conclusion
References
Optimization of the Field Development Mode by the Criterion of Maximizing Economic Efficiency
1 Introduction
2 Materials and Methods
2.1 Materials
2.2 Methods
3 Results and Discussion
4 Conclusion
References
Models of Recognition Algorithms Based on Construction of Two-Dimensional Logical Classifiers
1 Introduction
2 Statement of the Problem
3 Proposed Solution of Method
4 Experiments and Results
5 Conclusions
References
Contour Extraction When Recognizing Numbers Presented as Images
1 Introduction
2 Literature Review
3 Formulation of the Problem for the Extraction of Contours
4 Solution Method
5 Experiments
6 Experimental Research Results
7 Discussion of the Results of Experimental Studies
8 Conclusion
References
The Method of the Real-Time Control of the Erect Inverted Pendulum
1 Fuzzy Control of the Erect Pendulum
2 Swing-Up Routine of the Inverted Pendulum with the Given Acceleration
3 Conclusions
References
The Method of Mutual Use of the Labour Intensity of Finishing Works of Different Countries
1 Introduction
2 Research Methodology
3 Main Part
3.1 The Equation of the Pair Regression
3.2 Parameters of the Regression Equation
4 Conclusions
References
Choosing Material and Method for Increasing the Wear Resistance of Elements of Transport and Handling Equipment
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Method for Obtaining Structures with a Given Degree of Dispersion in Low-Carbon and Low-Alloy Steels of Transport and Handling Equipment
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Modeling and Optimization of the Hitch System of the Harvesting Units of Cotton Harvesting Machine MX-1.8 Under Vertical Vibrations
1 Introduction
2 Main Part
3 Conclusions
References
Energy Efficiency of an Orthogonal Balanced Wind Turbine Blade
1 Introduction
2 Materials and Methods
3 Boundary and Initial Conditions
4 Results of the Study
5 Calculation of Energy Efficiency
6 Conclusions
References
Study of the Influence of Design and Technological Parameters of a Horizontal Mixer on Its Performance Indicators
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusions
References
The Effect of Environmental Factors and Institutional Pressures on Construction Firms’ Performance: A Proposed Model
1 Introduction and Background
2 Conceptual Model
3 Methodology
3.1 Instrument Design
4 Data Analysis and Results
4.1 Reliability and Validity Assessment
5 Discussion
6 Conclusion
References
Application of Ventilation Systems with Increased Efficiency
1 Introduction
2 Materials and Methods
3 Research Results
4 Conclusions
References
Socio-Psychological and Criminological Characteristics of Persons Prone to Reckless Driving
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Evaluation of Forestry Industry Agglomeration and Regional Different Analysis in China's Southern Collective Forest Region
1 Introduction
2 Overview of the Research Region and Data Resources
2.1 Overview of the Research Region
2.2 Data Resources
3 Methodology
3.1 Location Quotient Model
3.2 Growth Rate of Agglomeration
3.3 Competitive State Model
4 Results and Analysis
4.1 Contribution of Forest Industry in the Southern Collective Forest Region to GDP
4.2 Analysis on the Trends of the Forest Industry Agglomeration in the Southern Collective Forest Region
5 Conclusions and Outlook
5.1 Conclusions
5.2 Outlook
References
Statistical Measurement of SMEs’ Credit Risk from the Perspective of Financial Crisis
1 Introduction
2 Literature Review
3 Selection and Description of Credit Risk Indicators for SMEs
3.1 Selection of the Research Sample
3.2 Selection of Indicators
4 Factor Analysis and Model Construction of Credit Risk Indicators
4.1 Factor Analysis of Explanatory Variables
4.2 Construction of the Logistic Regression Model
4.3 Analysis of the Predictive Power of the Model
5 Conclusions and Recommendations
5.1 Conclusions
5.2 Recommendations
References
Assessment of the Quality of Customs Services
1 Introduction
2 Methods and Materials
3 Results
4 Discussion
5 Conclusion
References
Energy-Efficient Technologies and Their Role in the Development of the Innovation Economy
1 Introduction
2 Theoretical Analysis
3 Discussion Results
4 Conclusions
References
Research on Topology Generation and Fault Prediction Technology of Low Voltage Distribution Network Based on State Perception
1 Introduction
2 Topology Generation and Verification Scheme
3 Fault Prediction Technology of Distribution Network Equipment
3.1 Mathematical Method of Equipment State Description Based on Historical Data
3.2 Device Fault Catastrophe Model Based on State-Aware Data
3.3 Fault Prediction Model for Equipment in Distribution Network
4 Verification and Analysis
4.1 Topology Generation Technology of Low-Voltage Distribution Network Based on State-Aware Unit
4.2 Implementation Method of Failure Prediction for Low-Voltage Distribution Network Equipment
5 Conclusion
References
Research on Target Customer Sales Strategy of Electric Vehicles Based on Machine Learning
1 Introduction
2 Implementation Steps
2.1 Overview
2.2 The Establishment of LR Model
2.3 The Establishment of LASSO Model
2.4 The Establishment of SVM Model
2.5 The Establishment of LightGBM Model
2.6 The Establishment of Random Forest Model
2.7 Feature Selection Results Based on Tree Model Feature Method
2.8 Summary
3 Conclusion
References
Automatic Recognition of Draft Marks on a Ship’s Board Using Deep Learning System
1 Introduction
2 Computer Vision Algorithm
3 Training a Model for Mark Detection
4 Synthesis of Linear Filter
5 Implementation of Algorithm
6 Possible Problems of Implementaiom and Methotds to Fix Them
7 Conclusion
References
Creation and Verification of a Simulation Model of the Flotation Process of Copper-Nickel Ore Enrichment on the Example of Inter-cycle Flotation
1 Introduction
2 Study of Factors Affecting the Process of Inter-cycle Flotation of Coper-Nicel Ore
3 Study of the Dependence of the Distribution of Nickel in the Fineness Classes of Flotation Products on the Content of the Fineness Class -0.071 mm in the Feed
References
Technological Control of the Granulometric Composition of Active Materials of Chemical Current Sources
1 Introduction
2 Problem Statement
3 Theoretical Part
4 Conclusion
References
Economic Security: A Critical Approach to Assessing the Effectiveness of the Resource Potential of Business
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Spectral Response Characteristic of Local Earthquakes According to Instrumentation Readings of the Engineering-Seismometrical Service
1 Introduction
2 Method and Subject of Research
3 Results
4 The Discussion of the Results
5 Conclusion
References
Consolidation of Powder Materials During the Production of Products by Hot Isostatic Pressing
1 Introduction
2 The Main Part
3 Pressing
4 Sintering
5 Extrusion
6 Conclusion
References
Research of Early Structure Formation Process of Concrete Where Concrete Waste is Used as Crushed Stone
1 Introduction
2 Methods
3 Results
References
Design of Energy-Saving Heat Pump Heat Supply Systems in Residential and Non-residential Premises
1 Introduction
2 Materials and Methods
3 Main Part
4 Conclusions
References
Influence of Temperature on the Energy Consumption for Pressure Pipelines
1 Introduction
2 Materials and Methods of Research
3 Results and Discussions
4 Conclusions
References
Discrete-Continuous Approach to the Moisture Transfer in Building Enclosures
1 Introduction
1.1 Moisture Regime of Enclosing Structures in the Construction Industry
1.2 Theoretical Studies in the Field of Humidity Regime of the Enclosing Structure
1.3 The Problem
2 Methods
2.1 Derivating the Moisture Transfer Equation and Formulating the Mathematical Model of Heat-Moisture Transfer Using the Moisture Potential Theory
2.2 Solving the Non-stationary Moisture Transfer Equation Using the Discrete-Continuous Approach
3 Results
4 Discussion
5 Conclusions
References
Object Trajectory Tracking in Industrial Building: Coupling of Building Information Modeling and Microwave Radar Technologies
1 Introduction
2 Method
3 Results
4 Conclusion
References
Evaluation of the Location for the Construction of Windfarm
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Research on Purification of Natural Water to Drinking Quality by Electrocoagulation
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Comparative Assessment of Acoustic Baffles
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Technological System Reliability as the Basis for Quality Indicators Stability Produced Machine Parts
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
Bypass Bends Deformability of CuZn5 Brass, X10CrNiTi18-9 and C22 Steel at Forming by Euler-Mode Buckling
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusions
References
Computerized Hardware and Software System for Investigation of Welding Defects of High-Strength Steel Based on a Subminiature Eddy-Current Transducer
1 Introduction
2 Experimental Technique
3 Research Results and Their Discussion
4 Summary
References
The Problem of High Humidity in the Ice Arena and Ways to Solve It
1 Introduction
2 Methods and Materials
3 Results and Discussion
4 Conclusion
References
The Use of Various Compositions of Borate Mixtures in the Development of Hardening Boride Coatings
1 Introduction
2 Materials and Method
3 Results and Discussion
4 Conclusions
References
Nanotechnologies in the Field of Concrete Production
1 Introduction
2 Nanotechnology in Construction
3 Concrete Nanotechnology
4 Discussion
5 Conclusions
References
Assessment of Porosity and Fracturing of Rocks Using Digital Photographs of Core Thin Sections
1 Introduction
2 Overview of Available Solutions
3 Materials and Methods
4 Results
5 Discussions and Conclusions
6 Conclusion
References
Bulk Cargo Pressure Acting on Vehicle Body Walls
1 Introduction
2 Methods and Results
3 Conclusion
References
Solving the Problem of Using Laser Levels in Low-Light Conditions
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusions
References
Quality Control of Welded Joints During Construction and Technical Expertise
1 Introduction
2 Methods
3 Results
4 Discussion
References
Reduction of Permeability of Fine-Grained Concrete
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusions
References
Strength and Deformability of Bent Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) Using a New Technology
1 Introduction
2 Materials and Methods
3 Research Results
4 Discussion
5 Conclusion
References
Creation of the Strength Design Methodology for Eccentrically Compressed Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) in the Longitudinal and Transverse Directions
1 Introduction
2 Materials and Methods
3 Research Results
4 Discussion
5 Conclusion
References
Optimization of Cargo Transportation Resource Allocation Based on Lean Manufacturing
1 Introduction
2 Methods
3 Results
4 Conclusion
5 Discussion
References
Automation of the Transfer Department of a Premier League Football Club
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Influence of Technological Factors of Cement Mechanical Activation on the Strength Properties of Fine-Grained Concrete
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
On the Specifics of Investigation for the Dynamic Problems of Cracked Layer by the Gradient Elasticity Theory
1 Introduction
2 Methods
2.1 Formulation of the Model Problem
2.2 The problem’s Investigation by the General Theory
3 Conclusion
References
Improving the Quality of the Surfaces of Reinforced Concrete Products During the Transition to a Two-Stage Production Technology
1 Introduction
2 Materials and Methods
3 Results
4 Discussions
5 Conclusion
References
Preconditions for the Development and Production of Wall Materials in the Northern Ethiopia
1 Introduction
2 Methods and Materials
3 Results and Discussion
4 Conclusion
References
Rational Methods of Reinforcement of Monolithic Flat Slabs in Frame Buildings
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
Influence of Various Factors on the Strength of Oblique Section of Beams Reinforced with Double-Sided Composite Clamps
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
Optimization of Structure Parameters of Semi-trailer-tank for Hydraulic Fracturing of Formation
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References
Development of Methods for Controlling the Chip Form via Intensified Chip Curling in the Cross-Sectional Plane
1 Introduction
2 Methods
3 Discussion
4 Conclusion
References
Development and Industrial Testing of a Method for Assessing the Deformation Properties of a Fixed Soil Massif
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
References
The Main Approaches to Defining the Boundaries of Agglomerations of Large Cities (Including Using the Capabilities of Big Data Mobile Network Operators)
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Warehouse Buildings Made of Wood
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusion
References
Methodology of Comparative Analysis of the Use of Leasing and Net Lending in the Technical Re-equipment of the Machine and Tractor Fleet
1 Introduction
2 Materials and Methods
3 Results of Scientific Research
4 Conclusion
References
Choosing the Communication Technologies and Technical Means
1 Introduction
2 Rationale for the Broadband Internet Access Technology Selection Approach
2.1 Analysis of Russia’s Position in the Global Digital Space
2.2 Analysis of the Regions’ Position in the Global Digital Space
2.3 Broadband Access Technology Selection by Russian Regions
3 Choosing the Way to Organize a Broadband Internet Access Subscriber Network, Given the Peculiarities of the Region
3.1 Analyzing the Population Structure by Region in the Russian Federation
3.2 Analysis of the Broadband Subscriber Network Organization in the Regions
4 Selecting the Node Access Point Antenna Design
4.1 Regulatory Restrictions on the VSAT Station Design Parameters
4.2 Design Parameter Restrictions for the VSAT Station Due to Climatic Factors
5 Conclusion
References
Use of Crushed Materials for Decorative Self-compacting Concrete
1 Introduction
2 Materials and Methods
3 Discussion and Results
4 Conclusions
References
Experimental Study of the Technology of Splicing Steel Rope on Machines with Rope Traction
1 Introduction
2 Methods and Materials
3 Results and Discussion
References
Improving the Safety of Operation of Handling Equipment During Container Transportation
1 Introduction
2 Methods and Results
3 Conclusion
References
Calculation of Resistance Due the Destruction of Soil by a Cutter
1 Introduction
2 Theoretical Part
3 Results
4 Conclusions
References
Efficiency Analysis for Mechanical Mixing Systems of Cementing Units
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References
Application of the Aggregated Approach to the Development of the Strategy of Technical Re-equipment of the Machine and Tractor Fleet of an Agricultural Enterprise
1 Introduction
2 Materials and Methods
3 Results of Scientific Research
3.1 Model Example
4 Conclusion
References
Truck Maintenance Frequency Optimization, Taking into Account an Increase in Its Operational Reliability
1 Introduction
2 Selection of the Object of Research of Operational Reliability
3 Frame Maintenance Frequency Optimization Taking into Account Its Operational Reliability
4 Practical Results of the Study
5 Conclusions
References
Vibroacoustic Characteristics of Flat Workpieces Hardening in Transport Engineering
1 Introduction
2 Results of Experimental Studies of Noise and Vibrations During Ball-And-Stick Hardening of Flat Parts
3 Conclusion
References
Method of Student Individuality Identification for Adapting and Intelligent Training Module Based on Soft Models
1 Introduction
2 Materials and Methods
2.1 Problem of Adaptation to the Trainees’ Intelligence Properties
2.2 Problem of ITM Adaptation to the Trainees’ Mental and Physiological Properties
2.3 Features of the Thought Experiment
3 Results
4 Conclusion
References
Energy Saving in Hydraulic Testing Systems
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
5 Conclusions
References
Tillage Device of Precision Pocessing with Pulsed Blows of Compressed Air
1 Introduction
2 The Purpose of the Research
3 Conclusions
References
Calculation and Optimization of Parameters of Standard Size Range of Unified Sections for Water Aluminum Radiators of Autotractor Engines
1 Introduction
2 Purpose of the Study
3 Materials and Methods
4 Results and Discussions
5 Conclusions
References
Effective Options for Strengthening Reinforced Concrete Compressed Columns in Terms of Technical and Economic Indicators
1 Introduction
2 Materials and Methods
3 Research Results
4 Discussion
5 Conclusion
References
Effective Options for Composite Strengthening of Eccentric-Compressed Reinforced Concrete Poles with Small Eccentricities of Load Application
1 Introduction
2 Materials and Methods
3 Research Results
4 Discussion
5 Conclusion
References
Investigation of the Mechanical Effect of Machinery on the Soil
1 Introduction
2 Research Methodology
3 Conclusion
References
On Determining the Elasticity Modulus of Moso Bamboo Based on the Static Bend Test Results by Analogy with Wood and Engineering Plastics
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Study of the Predicted Rate of Energy Resources Consumption on the Old Airport Renovation Area in Rostov-on-Don
1 Introduction
2 Methods
3 Results and Discussion
4 Conclusion
References
Applying Logistics Technology to the Transport of Consolidated Agricultural Cargo
1 Introduction
2 Improving the Quality and Competitiveness of Transport Services Through Logistics
3 Applying the Principles of Consolidation and Routing of Agricultural Freight
4 Electronic Document Management as a Tool to Improve the Competitiveness of the Transport of Agricultural Goods
5 The Role of Transport Logistics in Improving the Efficiency of Agribusiness Operators
References
Digital Freight Management in Transport Hubs in China
1 Introduction
2 Characteristics of the State of the Russian Market for International Road Transport of Goods
3 Development of the Transport Corridor “The New Silk Road” in China
4 Organisation of Intermodal Freight Transport in Transport Hubs
5 Digital Freight Management in Transport Hubs in China
References
The Analysis of Russian Railway Transport Enterprises Economic State in Terms of Market Transformation
1 Introduction
2 Materials and Methods
3 Results
4 Discussion
References
Investigation of the Energy-Saving Hydraulic Drive Dynamics of the Arrow Lifting Mechanism of the Forestry Manipulator
1 Introduction
2 Materials and Methods
3 Results
4 Conclusion
References
Features of the Block-Modular Cooling System of Traction Vehicles
1 Introduction
2 Purpose of the Study
3 Materials and Methods
4 Research Results and Discussions
5 Conclusion
References
Evaluation of the Functional Characteristics of the Elastic-Damping Mechanism of the Tractor Power Transmission Based on Statistical Analysis
1 Introduction
2 Purpose of Research
3 Materials and Methods
4 Discussion Results
5 Conclusions
References
Analysis of the Operation of Sowing Units Based on DMC Seeders in the Siberian Federal District Farms
1 Introduction
2 Research Methods
3 Results and Analysis
4 Conclusions
References
Hydraulic Actuator of Reciprocating Motion
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References
Reducing the Dynamic Loading of the Links of the Machine-Tractor Unit Aggregated by the Mobile Power Vehicle of the 1.4 Drawbar Category
1 Introduction
2 Methods of Research
3 Results of the Research
4 Conclusion
References
Paradox of the Image in Digital Communications
1 Introduction
2 Materials and Methods
3 Results
3.1 The Concept of a “Visual Turn” in the Understanding of Modern Culture
3.2 The Status of the Visual Image in Today’s Digital Environment
4 Discussion
5 Conclusions
References
Knowledge Base Applied Usage Operating on the Basis of Network Structure
1 On the Issue of Distance Learning as a Necessity
2 The Use of Cloud Technologies for Organizing the Work of Distance Learning Systems
3 Recommended Technology for Distance Automated Learning
4 Scheme of the Organization of the Work of Software, Technically Implementing the Process of Obtaining Answers to the Students’ Questions
5 On the Possibility of Creating a Multilingual Distance Learning System
6 Summary
References
Impact of the Digitalization Trend on the Management of Production Systems and Processes
1 Introduction
2 Materials and Methods
3 Results
4 Conclusions
References
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Lecture Notes in Networks and Systems 510
Alexander Guda Editor
Networked Control Systems for Connected and Automated Vehicles Volume 2
Lecture Notes in Networks and Systems Volume 510
Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Fernando Gomide, Department of Computer Engineering and Automation—DCA, School of Electrical and Computer Engineering—FEEC, University of Campinas—UNICAMP, São Paulo, Brazil Okyay Kaynak, Department of Electrical and Electronic Engineering, Bogazici University, Istanbul, Turkey Derong Liu, Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, USA Institute of Automation, Chinese Academy of Sciences, Beijing, China Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Alberta, Canada Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Marios M. Polycarpou, Department of Electrical and Computer Engineering, KIOS Research Center for Intelligent Systems and Networks, University of Cyprus, Nicosia, Cyprus Imre J. Rudas, Óbuda University, Budapest, Hungary Jun Wang, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
The series “Lecture Notes in Networks and Systems” publishes the latest developments in Networks and Systems—quickly, informally and with high quality. Original research reported in proceedings and post-proceedings represents the core of LNNS. Volumes published in LNNS embrace all aspects and subfields of, as well as new challenges in, Networks and Systems. The series contains proceedings and edited volumes in systems and networks, spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output. The series covers the theory, applications, and perspectives on the state of the art and future developments relevant to systems and networks, decision making, control, complex processes and related areas, as embedded in the fields of interdisciplinary and applied sciences, engineering, computer science, physics, economics, social, and life sciences, as well as the paradigms and methodologies behind them. Indexed by SCOPUS, INSPEC, WTI Frankfurt eG, zbMATH, SCImago. All books published in the series are submitted for consideration in Web of Science. For proposals from Asia please contact Aninda Bose ([email protected]).
Alexander Guda Editor
Networked Control Systems for Connected and Automated Vehicles Volume 2
Editor Alexander Guda Rostovskogo Strelkovogo Polka Narodnogo Rostov State Transport University Rostov-on-Don, Russia
ISSN 2367-3370 ISSN 2367-3389 (electronic) Lecture Notes in Networks and Systems ISBN 978-3-031-11050-4 ISBN 978-3-031-11051-1 (eBook) https://doi.org/10.1007/978-3-031-11051-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Contents
Proposals for Development of Piggyback Transportation in the South of Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Victor Zubkov, Ekaterina Ryazanova, Nikolay Ryazanov, and Nina Musienko Model of Atmospheric Effects Onto a Group of Unmanned Aerial Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmitry Belonozhko, Igor Korolev, Yury Chernyshev, and Nikolay Ventsov Reinforcement of the Railway Roadbed with Soil-Concrete for the Passage of Heavy Rolling Stock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Kosenko, Sergey Shkurnikov, Gennadiy Akkerman, and Sergey Akimov Estimation of the Resource of Spiroid Transmissions by the Condition Maximum Wear and Tear . . . . . . . . . . . . . . . . . . . . . . . . . Alexander Zaitsev Principles of Designing Asymmetric Rail Profiles . . . . . . . . . . . . . . . . . . . . Andrey Ilinykh, Andrey Romanov, and Inna Parahnenko
1
17
29
41 51
Mathematical Modeling Technique for Designing a Composite Technological Process for Machining Holes in Laminated Parts . . . . . . . Tatiana Tyunyukova and Anton Kirpichnikov
61
Design Criteria for Variable Rigidity Sections of Approach Embankments to Bridges and Overhead Crossings . . . . . . . . . . . . . . . . . . Alexey Lanis, Denis Razuvaev, and Petr Lomov
73
Definition Model of the Optimal Size of the Material Resources in Construction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Kuznetsov and Olga Demidenko
83
v
vi
Contents
Rationale for the Machine Complex Performance . . . . . . . . . . . . . . . . . . . . Sergey Kuznetsov, Ksenia Bogomolova, and Natalya Shipilova Experimental Studies of Fiber Concrete Samples Under Cyclic Load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Natalia Pichkurova and Maria Novitskaya Application Effectiveness Analysis of the Thin-Walled Building Components for Transport Infrastructure Facilities . . . . . . . . . . . . . . . . . . Natalya Pichkurova, Boris Prosyanikov, Sergey Kolankov, and Tatiana Pimshina Experimental Study of Dynamic Forces Acting on Wheel Pairs of Railway Rolling Stock in Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Bekher, Dmitry Kononov, and Aleksandr Buynosov Simulation of the Track Machinery Technical Condition to Ensure Safe Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alexey Loktev, Petr Sychev, Vladimir Aksenov, Alexander Pikalov, and Vyacheslav Sychev Development of On-Board Systems of Predictive Diagnostics of Electric Rolling Stock Traction Motor . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kirill Pastukhov, Stanislav Istomin, and Oleg Yrasov Accident Prevention System at Unguarded Railway Crossings . . . . . . . . Gayaz Akhmedzyanov, Vladimir Dremin, and Artem Litvinov
93
105
115
125
137
147 157
Analyzing the Movement of a Freight Train at Stops on Flat Sections of the Railway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Oleg Ablyalimov, Sergey Petrochenko, and Nozimjon Kodirov
165
Computer Modeling of Repair Technological Systems in Design Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Viktor Smirnov
173
Improvement of Methods of Energy Optimal Automatic Operation of Electric Freight Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . Egor Avdienko and Evgeniy Tretyakov
183
The Improvement of On-Board Systems for Predictive Technical Diagnostics of Mainline Electric Freight Locomotives Based on Digital Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Evgeniy Tretyakov, Dmitry Solovyov, and Mikhail Kudinov Influence of Changes in External Factors on the Energy Efficiency Parameters of Electric Locomotives . . . . . . . . . . . . . . . . . . . . . . Alexey Plaksin and Semen Shvetsov
193
203
Contents
vii
Preventive Diagnostics of Technical Condition of Inter-Turn Insulation of Traction Electric Motors Anchor Windings . . . . . . . . . . . . . Pavel Shkodun
217
Improvement of the Traction Resource Management System to Enhance the Performance of Electric Rolling Stock . . . . . . . . . . . . . . . . Alexander Vilgelm, Aleksandr Komyakov, and Alexander Strauchman
227
Optimization of the Technology of Electrolytic Zincing of Traction Mechanisms Parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmitry Muravyov and Ekaterina Izmest’eva
239
Control of Mainline Freight Electric Locomotives with Adjustment of Operating Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Stanislav Istomin, Artem Perestenko, and Sergey Shantarenko
251
Determining Optimal Electrical Discharge Machining Modes for the Disc Tab Grooves of Small-Size By-Passengine . . . . . . . . . . . . . . . . Sergei Petrochenko, Oleg Ablyalimov, Nozimjon Kodirov, and Rakhimzhan Rakhmaev
261
Modelling of Heating Process of the High-Pressure Fuel Pipeline of the Fuel Equipment of Diesel Locomotives . . . . . . . . . . . . . . . . . . . . . . . . Sergei Ovcharenko, Oleg Balagin, and Dmitrii Balagin
271
Improvement Metrological Support of the Technological Process of Repair of the Auto-Couple Device of the Railway Carriage . . . . . . . . . Dmitry Belan and Lyubov Kofanova
281
Influence of Freight Locomotive Modernization by Increasing of Diesel Generator Set Power on the Mechanical Strength of Traction Drive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Oleg Pudovikov, Eugeny Rybnikov, Elena Loginova, Tatiana Vakhromeeva, and Sergey Volodin
291
Identification of Wind Loads Through Train Statistical Analysis . . . . . . Ivan Grebnev, Natalia Sidorova, and Oleg Pudovikov Improvement of Edge Cutting Machining of Materials with Fatigue and Thermomechanical Failures . . . . . . . . . . . . . . . . . . . . . . . Michael Biserikan and Anastasia Kashbulina The Impact of the Transport Factor on Regional Development . . . . . . . . Tatiana Tselykh, Evgeniia Shtele, and Tatiana Kuvaldina Choosing a Method for Studying Rail Vehicles’ Oscillations with Nonlinear Suspension Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . Anatoly Savoskin and Natalia Lavlinskaya
299
309 317
329
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Contents
The Effect of Distributed Generation Plants’ Prognostic Controllers on Power Quality in Power Supply Systems of Non-traction Consumers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yuri Bulatov, Andrey Kryukov, and Konstantin Suslov Increasing the Reliability of Diagnosing Power Transformers by Using a Defect Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrey Kuznetsov, Viktor Harlamov, Maria Volchanina, and Anton Gorlov Energy Intensity and Energy Efficiency of Energy Saving Policy of Railway Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dmitry Rozhitsky, Alexey Rybak, Irina Krasnova, Aleksandr Komyakov, and Mikhail Nikiforov Production of Au Nanoparticles by Laser Ablation in Liquids . . . . . . . . Dmitry Melnikov, Olga Lutikova, Polina Gubareva, Maria Melnikova, and Kirill Fomichenko Improving the Efficiency of the Locomotive Complex Through Modern Methods of Managing Traction Resources . . . . . . . . . . . . . . . . . . Alexander Vilgelm, Alexander Komyakov, and Alexey Kashtanov Additive Technologies Features for Manufacturing Metal Products from Powder Materials by Direct Laser Deposition . . . . . . . . . Oleg Supchinsky, Maria Melnikova, Andrei Kholopov, Dmitriy Melnikov, and Alexandr Bogdanov Image Processing for Visual Inspection of Hollow Reinforced Concrete Supports’ Inside Surfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrey Kuznetsov, Anton Ponomarev, Georgy Volchanin, Kirill Fomichenko, and Andrey Gritcutenko The Use of Heat Pump Systems for Heat Supply to Consumers . . . . . . . Aleksandra Finichenko, Maria Glukhova, and Sergey Glukhov
339
351
359
369
379
393
403
411
Designing a 3D Application Based on Digital Models of Railway Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kirill Bogunov and Stanislav Istomin
419
Designing a 3D Application Based on Digital Models of Rolling Stock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kirill Bogunov and Stanislav Istomin
429
Energy Efficiency Level Analysis of Train Traction in a Structural Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alexey Davydov
437
Combined Heat Pump and Solar Collector Application . . . . . . . . . . . . . . Aleksandra Finichenko and Anastasia Polozkova
447
Contents
Selecting the Optimum Design Solution for Rolling Stock Repair Plants Under Multiple Preference Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . Viktor Smirnov Improving the Efficiency of Center-to Center Spacing Control . . . . . . . . Aleksey Obryvalin, Oleg Supchinsky, and Olga Sutkovay The Linearization Method to Calculate the Equilibrium Composition of Combustion Products of Diesel Engine . . . . . . . . . . . . . . . Alexandr Anisimov and Igor Chernyshkov Energy Efficiency of the Innovative Fifth-Generation 2ES5S Electric Freight Locomotive and the Results of its Tests . . . . . . . . . . . . . . Alexandr Baklanov, Andrey Shatohin, Andrey Shilyakov, Kiril Domanov, and Nikolay Esin The Role of Diesel Locomotives Operating Modes in Simulating the Operation of Fuel and Control Equipment of Diesel Locomotives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pavel Blinov and Alexander Blinov The Categorization of Methods and Means of Energy Optimized Control of Electric Railway Rolling Stock . . . . . . . . . . . . . . . . . . . . . . . . . . . Stanislav Istomin, Egor Avdienko, Kirill Domanov, and Andrey Shatohin Interval Estimation of Magnetotelluric Response Function and Quality Control During Registration of Data . . . . . . . . . . . . . . . . . . . . Andrey Lavrukhin, Alena Tukanova, Aleksandr Onufriev, and Andrey Malyutin Control Method for Mainline Freight Electric Locomotives with the Possibility of Adjusting Movement Modes . . . . . . . . . . . . . . . . . . Stanislav Istomin, Artem Perestenko, and Sergey Shantarenko Modeling the Management of an Economic System Based on Random Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Schislyaeva, Natalia Vasileva, Vladimir Grigoriev-Golubev, Irina Evgrafova, and Vladimir Belopolsky
ix
455 467
477
485
493
503
513
523
533
The Prospective Model of Organization of Freight Transportation on the North Caucasian Railway Range . . . . . . . . . . . . . . Viktor Zubkov, Nina Musienko, and Kirill Anoshkin
543
Implementation of «Lean Manufacturing» in the Construction and Transport Construction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Arskaya and Lyudmila Usatova
555
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The Essence and Features of the Construction Management System in the Conditions of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yulia Tkachenko and Irina Slabinskaya
563
Innovative Forms of Investment in Housing and Communal Services Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Galina Grinenko
571
The Impact of the Competitiveness of the Transport and Construction Industry on the Stability of the Socio-Economic System (SES) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tatyana Dubrovina and Evgenia Denisova Innovations, Labor Productivity, Human Capital in the Construction Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gulnara Balabanova, Tatyana Davydenko, Elena Dubinina, and Larisa Zhuravleva Systems of Indicators for a Comprehensive Assessment of the Stability of the Functioning of Enterprises in the Construction and Transport Industry . . . . . . . . . . . . . . . . . . . . . . . . . Irina Slabinskaya and Olga Benderskaya Approaches to of the Effective Assessment of Transportation Professionals’ Skills in Terms of Concept of Human Capital in «New» Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Dubinina, Zlata Stolyarova, and Elena Chizhova Comparative and Correlation Analysis of the Parameters of Digitalization and Innovation Activity of Business and Transport Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Irina Somina and Angelika Falko Design of a Project Office When the Implementation of Investment of it in Construction Including a Transport Field . . . . . . . Sergey Chyuev, Alexandra Bukovtsova, and Natalia Kozhukhova Methodic Approaches to the Assessment of Regional Investment Attractiveness in the Sphere of Tourism and Transport Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alexander Troshin, Vera Stolyarova, and Zlata Stolyarova Differentiation of Regional Development as a Factor of Destabilization of the Development of Innovative Potential and Transport Infrastructure of the Constituent Entities of the Russian Federation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anastasia Inozemtseva and Irina Pavlova
581
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A Model for Optimizing Transaction Costs in the Implementation of Intellectual Entrepreneurship in the Digital Economy . . . . . . . . . . . . . Daria Kadatskaya and Yulia Lavrova
649
Essence and Role of the Anti-crisis Strategy in Preventing the Bankruptcy of Transport Companies . . . . . . . . . . . . . . . . . . . . . . . . . . . Aleksandr Popov and Elena Lapteva
659
Russia Impact of Transport Accessibility of the Enterprise on the Cost of Delivery in E-Commerce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Lapteva and Elena Ogorodnikova
669
Multi-dimensional Assessment of Marketing Capability on the Example of Transport Business Organizations . . . . . . . . . . . . . . . . Tatyana Ponomareva, Elena Shchetinina, and Irina Rozdolskaya
679
The Formation of an Investment and a Transport Investment Innovation System Model of the Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anna Zhdanova
691
Study of the Level of Digitalization of the Banking Sector of Russia in the Context of the Pandemic and the Development of Transport Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sofia Bukhonova and Anna Yablonskaya On the Problem of Investment and Innovation Activity . . . . . . . . . . . . . . . Tatiana Kovaleva and Elena Atabieva Quality Management in Modern Business and Transport Business Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Anatoly Stepanov and Natalya Mityakina Transport and Industrial Construction as a Driver of Commercialized Innovations in Regional Production Systems . . . . . . Maria Starikova, Alexander Troshin, Stephanie Togba, and Larisa Denike Express Assessment of Business and Marketing Environment of an Industrial and Transport Enterprise on the Basis of Probabilistic-Attributive Approach Assessment . . . . . . . . . . . . . . . . . . . Ekaterina Schetinina, Elena Krasnoperova, Elena Schetinina, and Yuri Bogkov COVID-19 and Its Impact on Construction and Transport Construction Economy: An Integrated Framework . . . . . . . . . . . . . . . . . . Kumar Shalender, Babita Singla, Sandhir Sharma, and Marina Oberemok
703 711
719
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Human Capital as the Market Value of a Geomarketing and Transport System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vladimir Moiseev, Zhanna Avilova, Olga Gerasimenko, Ludmila Polovneva, and Tatyana Tselyutina Diagnostics of the Depth of Digitalization of Industrial Enterprises of the Construction and Transport Construction Complex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ekaterina Schetinina, Anatoly Rudychev, and Svetlana Kochina Impact of the Import Substitution Program on the Competitiveness of Industrial and Transport Enterprises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Mikalyt, Tatiana Dubrovina, and Stanislav Ignatov Thermal and Economic Performance of a Solar Hot Water System in Tashkent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Petros Axaopoulos, Alisher Shaislamov, Nodirbek Abdullaev, and Abzalkhon Akxrorkhodjaev Influence of Heat and Humidity Conditions on the Operation of the Pin Connections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sergey Fedosov, Vitaly Kotlov, Anatoly Pozdeev, Anatoly Aktuganov, Yulia Kuznetsova, Oleg Aktuganov, and Tatyana Pugacheva Pattern of Distribution of Carbon Nanotubes in the Matrix of Polymer Compositions for Wood Stabilization . . . . . . . . . . . . . . . . . . . . Mikhail Lisyatnikov, Mikhail Sergeev, Danila Chibrikin, and Mikhail Lukin Application of Information Systems in the Technology of Servicing Energy Consumers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Valerii Zubkov and Nina Sirina Criteria for Measuring the Economic Efficiency of Projects Based on Reusable Information Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vladislava Aliulova, Marina Petrochenko, Maria Vrublevskaya, and Anna Gorodishenina Research and Selection of Rational Parameters of a Refrigerated Container Terminal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Daurenbek Ilesaliev, Jamshid Kobulov, Rashida Tursunkhodjaeva, and Mukaddas Tashmatova The Phenomenon of “Bias of Assessment” as the Basis of a Behavioral Model and a Potential Source of Problems . . . . . . . . . . . . Oleg Tikhanychev
755
763
773
781
791
799
809
819
829
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Effect of Phubbing on Students’ Performance . . . . . . . . . . . . . . . . . . . . . . . Tatiana Baranova, Aleksandra Kobicheva, and Elena Tokareva
xiii
849
Improving Management Methods for the Formation and Use of Information Resources of Enterprises . . . . . . . . . . . . . . . . . . . . . . . . . . . . Svetlana Ovchinnikova, Aleksandr Borovkov, and Elena Schneider
857
Influence of Changes in the Pavement Concrete Moisture on Its Water Resistance During Traffic Exploitation . . . . . . . . . . . . . . . . . . . . . . . Ashot Arthur Antonyan
867
The Freezing Zone Formation of the Probe Around the Vertical Ground Heat Pumps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nikolay Rudenko, Irina Fursova, Darya Belyaeva, Sofya Popoudina, and Elena Dokhoyan The Limiting Rut Depth by Conditions Safety of Traffic . . . . . . . . . . . . . . Anatoly Aleksandrov and Tatyana Semenova Investigation of the Conditions for the Occurrence of Rail-Ground Potentials on AC Railways . . . . . . . . . . . . . . . . . . . . . . . . . . Evgeniy Tryapkin, Ivan Ignatenko, Sergey Vlasenko, Alexander Onischenko, and Natalia Shurova Conditions for Compliance Lewis Relationship When Air Flow is Contact with Ice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Tarasova, Vladimir Chernenkov, and Anton Eskin Approximate Solution of the Heat Transfer Equation as a Function of the Transfer Potential Coefficient . . . . . . . . . . . . . . . . . . . Natalia Parfentieva, Marina Panfilova, Vladimir Konovalov, and Soniya Efremova Method for BIM and GIS Databases Integration for CIM Creation Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mohamad Roumyeh, Vladimir Badenko, and Yulia Volkova Modeling Professional Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Smirnova and Nadejda Subbotina
875
883
893
903
913
923 933
Sino-Russian Experience in Smart Grid Development: Issues and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maksim Bikalenko and Valentina Burtseva
945
Prediction of the Service Life of Hybrid Ceramic Bearings by Integrated Deep Learning and Particle Filter Methods . . . . . . . . . . . . Xingyu Chen, Miao Dong, Longping Yi, and Zhiyun Wang
953
Resource-Efficient Use of Hydrocarbon Raw Materials as a Factor in the Transition to a “Green” Economy . . . . . . . . . . . . . . . . . Oleg Andreev
963
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Long Wave Dynamics in Heavy Wave Gravitating Fluid in Vlasov Type Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tatyana Krasnoslobodzeva and Maria Skvortsova The System for Modeling and Visualizing 3D Algebraic Functions . . . . Andrei Beiresh and Alexei Razumowsky Predictive Assessment of Dynamics Intellectual Activity Index National Innovation-Oriented System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elena Golovchanskaya and Svetlana Kirilchuk
975 985
995
Digital Simulators and Training Devices for Solving Geometric Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1005 Elmira Galyamova, Semen Matveev, and Boris Kiselev The Effect of Visual Information Contained in Digital Training Courses on the Renewal of Working Memory . . . . . . . . . . . . . . . . . . . . . . . 1017 Elena Romanova and Dariana Romanova Soft Skills Development by Means of Digital Pedagogical Cues . . . . . . . . 1027 Elena Chirkova, Elena Zorina, and Abram Maron Methodological Approaches to Modeling Dynamic Development of Regional Ecological and Socio-Economic Systems . . . . . . . . . . . . . . . . . 1037 Natalia Ivanova Icebreaker Fleet Management in Simulation Models of the Arctic Marine Transport Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1049 Alex Topaj, Alexander Buyanov, Alexander Karpenko, and Andrey Malykhanov Forecasting Temperature Change in Mine Workings at Change in Air Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1061 Aleksandr Galkin and Vladimir Pankov Modeling a Repertoire of Pilots’ Professional Communication Skills for Meeting Flight Safety and Aviation Security Challenges . . . . . 1069 Olena Kovtun, Anzhelika Kokarieva, and Nataliia Khaidari Rational Use of Hydrocarbon Resources in the Context of Environmental Sustainability of the Country . . . . . . . . . . . . . . . . . . . . . 1079 Oleg Andreev E-Learning Online Platforms for Educational Approach . . . . . . . . . . . . . 1089 Anna Kononenko, Mikhail Kravchenko, Larisa Nedospasova, and Ekaterina Fedorovich Numerical Study of the Intake Chambers of a Cotton Picker . . . . . . . . . 1097 Zafar Malikov, Abdurahim Yuldashev, Davronbek Kuldoshev, and Bekhzod Malikov
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Particular Features of Call Tracking Technologies Application in Certain Industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1109 Elena Torosyan, Tatyana Feiling, Aleksandr Khan, and Alisa Torosyan Improved Method and Algorithm of Railway Crossing Automatic Signaling System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 Sohibjamol Valiyev, Qamara Kosimova, Sunnatillo Boltayev, and Bekhruz Ergashov Formation a Sustainable Supply Chain Strategy . . . . . . . . . . . . . . . . . . . . . 1131 Svetlana Suvorova, Oksana Kulikova, Tatyana Kirillova, Galina Fedotova, and Evgenya Melikova Mathematical Model of the Radial Bearing with a Fusible Metal Porous Coating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1143 Murman Mukutadze and Aleksandr Mukutadze Mathematical Model of a Radial Bearing with Increased Bearing Capacity Operating on Lubrication with Melt on Shaft Surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1153 Murman Mukutadze and Aleksandr Mukutadze Leadership Vision in Advanced Technology . . . . . . . . . . . . . . . . . . . . . . . . . 1161 Mustafa Günay Architecture of Software Complex for Multicriteria Synthesis of Composite Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1173 Alexei Bormotov Assessment of Heavy Metal Pollution in the Roadside Area of Motorways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1181 Margarita Zhuravleva, Soniya Efremova, Vladimir Konovalov, Nikolai Zubrev, Marina Panfilova, and Anna Goryacheva Optimization of the Field Development Mode by the Criterion of Maximizing Economic Efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1189 Irina Filimonova, Anastasia Ivershin, and Irina Provornaya Models of Recognition Algorithms Based on Construction of Two-Dimensional Logical Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1199 Gulmira Mirzaeva Contour Extraction When Recognizing Numbers Presented as Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1209 Ergash Saliev, Olimjon Mirzaev, Makhamadaziz Rasulmukhamedov, and Sayyora Ibragimova The Method of the Real-Time Control of the Erect Inverted Pendulum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1219 Djavanshir Gadjiev, Aligadzhi Rustanov, and Ivan Kochetkov
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The Method of Mutual Use of the Labour Intensity of Finishing Works of Different Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1231 Rustam Fatullaev and Tembot Bidov Choosing Material and Method for Increasing the Wear Resistance of Elements of Transport and Handling Equipment . . . . . . . 1241 Alexander Scherbakov, Andrey Misailov, Denis Shavelkin, and Natalya Verbova Method for Obtaining Structures with a Given Degree of Dispersion in Low-Carbon and Low-Alloy Steels of Transport and Handling Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 Alexander Scherbakov, Maxim Aleksandrovskiy, Denis Shavelkin, and Natalya Verbova Modeling and Optimization of the Hitch System of the Harvesting Units of Cotton Harvesting Machine MX-1.8 Under Vertical Vibrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1265 Bakhtiyor Azimov, Anvar Rizaev, Dilfuza Yakubjanova, and Saidazim Kubaev Energy Efficiency of an Orthogonal Balanced Wind Turbine Blade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1277 Valery Prokopiev and Andrey Proskurin Study of the Influence of Design and Technological Parameters of a Horizontal Mixer on Its Performance Indicators . . . . . . . . . . . . . . . . . 1285 Petr Savinykh, Nikolay Turubanov, and Fedor Kipriyanov The Effect of Environmental Factors and Institutional Pressures on Construction Firms’ Performance: A Proposed Model . . . . . . . . . . . . 1293 Hassan Fehan and Osaro Aigbogun Application of Ventilation Systems with Increased Efficiency . . . . . . . . . 1303 Olga Malikova Socio-Psychological and Criminological Characteristics of Persons Prone to Reckless Driving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1313 Ivan Tretyakov Evaluation of Forestry Industry Agglomeration and Regional Different Analysis in China’s Southern Collective Forest Region . . . . . . 1325 Fang Liu and Hongxun Li Statistical Measurement of SMEs’ Credit Risk from the Perspective of Financial Crisis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1341 Chenyao Zhang and Jinsong Zhang Assessment of the Quality of Customs Services . . . . . . . . . . . . . . . . . . . . . . 1351 Alexander Shtrikov, Natalia Persteneva, and Darya Shtrikova
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Energy-Efficient Technologies and Their Role in the Development of the Innovation Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1363 Daria Kichikova, Nikolai Zakirov, and Yuri Katanov Research on Topology Generation and Fault Prediction Technology of Low Voltage Distribution Network Based on State Perception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1371 Ying Yao, Dalong Ji, and Wenjin Fu Research on Target Customer Sales Strategy of Electric Vehicles Based on Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1385 Zhiyuan Wang, Uchani Omar, and Menglin Lv Automatic Recognition of Draft Marks on a Ship’s Board Using Deep Learning System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1393 Yaroslav Kirilenko and Ignat Epifantsev Creation and Verification of a Simulation Model of the Flotation Process of Copper-Nickel Ore Enrichment on the Example of Inter-cycle Flotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1403 Roman Nikitin, Sergey Lukichev, Valery Biryukov, Yulia Kameneva, and Irina Vishnyakova Technological Control of the Granulometric Composition of Active Materials of Chemical Current Sources . . . . . . . . . . . . . . . . . . . . 1417 Dmitry Fugarov Economic Security: A Critical Approach to Assessing the Effectiveness of the Resource Potential of Business . . . . . . . . . . . . . . . 1425 Guzaliya Klychova, Gamlet Ostaev, Alsou Zakirova, Albert Iskhakov, Elena Konina, and Ekaterina Gainutdinova Spectral Response Characteristic of Local Earthquakes According to Instrumentation Readings of the Engineering-Seismometrical Service . . . . . . . . . . . . . . . . . . . . . . . . . . 1437 Vladimir Lapin, Nurakhmet Makish, Kamadiyar Kassenov, Zhassulan Omarov, and Dauren Kassenov Consolidation of Powder Materials During the Production of Products by Hot Isostatic Pressing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1447 Vladimir Makarov, Yuri Molev, and Alexey Markov Research of Early Structure Formation Process of Concrete Where Concrete Waste is Used as Crushed Stone . . . . . . . . . . . . . . . . . . . . 1455 Ivan Pulyaev and Sergey Pulyaev Design of Energy-Saving Heat Pump Heat Supply Systems in Residential and Non-residential Premises . . . . . . . . . . . . . . . . . . . . . . . . . 1461 Sergey Fedosov, Vadim Fedoseev, and Svetlana Loginova
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Influence of Temperature on the Energy Consumption for Pressure Pipelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1471 Vladimir Orlov and Dmitry Peterburgsky Discrete-Continuous Approach to the Moisture Transfer in Building Enclosures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1481 Kirill Zubarev Research on Purification of Natural Water to Drinking Quality by Electrocoagulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1491 Yuriy Bebikhov and Alexander Semenov Object Trajectory Tracking in Industrial Building: Coupling of Building Information Modeling and Microwave Radar Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1501 Vladimir Badenko, Vladimir Kuptsov, Sergey Ivanov, Alexander Fedotov, Yulia Volkova, and Galina Badenko Evaluation of the Location for the Construction of Windfarm . . . . . . . . 1509 Nail Timerbaev, Fouad Alhajj Hassan, Leysan Gainullina, Farida Filippova, and Safin Rushan Comparative Assessment of Acoustic Baffles . . . . . . . . . . . . . . . . . . . . . . . . 1517 Vadim Bespalov and Natalya Samarskaya Technological System Reliability as the Basis for Quality Indicators Stability Produced Machine Parts . . . . . . . . . . . . . . . . . . . . . . . . 1525 Galina Prokopets, Anatoly Prokopets, and Svetlana Vozhakova Bypass Bends Deformability of CuZn5 Brass, X10CrNiTi18-9 and C22 Steel at Forming by Euler-Mode Buckling . . . . . . . . . . . . . . . . . . 1533 Volodymyr Kukhar, Oleksandr Hrushko, Oleg Markov, Oleksandr Anishchenko, and Andrii Prysiazhnyi Computerized Hardware and Software System for Investigation of Welding Defects of High-Strength Steel Based on a Subminiature Eddy-Current Transducer . . . . . . . . . . . . . . . . . . . . . . . 1543 Vladimir Malikov, Alexander Katasonov, Nikolay Tihonskiy, Viktorya Kozlova, Ekaterina Valulina, Anatoly Sagalakov, Sergey Dmitriev, and Alexey Ishkov The Problem of High Humidity in the Ice Arena and Ways to Solve It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1555 Evgeniy Neverov, Igor Korotkiy, Dmitry Goleshov, Maxim Mokrushin, and Pavel Korotkih The Use of Various Compositions of Borate Mixtures in the Development of Hardening Boride Coatings . . . . . . . . . . . . . . . . . . . 1563 Vladimir Malikov, Nickolay Tihonskii, Victoria Kozlova, and Alexey Ishkov
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Nanotechnologies in the Field of Concrete Production . . . . . . . . . . . . . . . . 1573 Anatoly Lastovka, Tamara Danchenko, Inna Petukhova, and Ilya Polyakov Assessment of Porosity and Fracturing of Rocks Using Digital Photographs of Core Thin Sections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1583 Galina Prozorova and Elena Slinkina Bulk Cargo Pressure Acting on Vehicle Body Walls . . . . . . . . . . . . . . . . . . 1593 Andrew Nikitchenko, Viktor Artiukh, Sergey Kargin, Valentina Kashintseva, and Asiiat Mottaeva Solving the Problem of Using Laser Levels in Low-Light Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1603 Yanis Olekhnovich, Maksim Kuznetsov, Anna Zanina, and Andrey Ivashchenko Quality Control of Welded Joints During Construction and Technical Expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1615 Irina Serebryanaya and Alexandra Nalimova Reduction of Permeability of Fine-Grained Concrete . . . . . . . . . . . . . . . . 1623 Inna Egorochkina and Elena Shlyakhova Strength and Deformability of Bent Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) Using a New Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1633 Sergey Georgiev, Dmitry Mailian, and Elnar Huseynov Creation of the Strength Design Methodology for Eccentrically Compressed Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) in the Longitudinal and Transverse Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1643 Sergey Georgiev, Dmitry Mailian, and Alik Blagoz Optimization of Cargo Transportation Resource Allocation Based on Lean Manufacturing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1653 Elena Pinevich, Aleksandr Volokhov, Karina Mekhantseva, Vladimir Zinovev, and Diana Ganzhenko Automation of the Transfer Department of a Premier League Football Club . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1663 Tatiana Grober and Oleg Grober Influence of Technological Factors of Cement Mechanical Activation on the Strength Properties of Fine-Grained Concrete . . . . . . 1671 Sergei Stel’makh, Levon Mailyan, Alexey Beskopylny, Evgenii Shcherban’, and Anatolii Shuiskii
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On the Specifics of Investigation for the Dynamic Problems of Cracked Layer by the Gradient Elasticity Theory . . . . . . . . . . . . . . . . . 1681 Oksana Yavruyan and Khungianos Yavruyan Improving the Quality of the Surfaces of Reinforced Concrete Products During the Transition to a Two-Stage Production Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1689 Khungianos Yavruyan, Evgeniy Gaishun, Ekaterina Dementieva, Evgeniy Staritskiy, and Stanislav Shahaliev Preconditions for the Development and Production of Wall Materials in the Northern Ethiopia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1699 Berhane Gebru, Vladimir Kotlyar, Svetlana Kurilova, and Andrey Tolstorebrov Rational Methods of Reinforcement of Monolithic Flat Slabs in Frame Buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1709 Viktor Muradyan and Petr Polskoy Influence of Various Factors on the Strength of Oblique Section of Beams Reinforced with Double-Sided Composite Clamps . . . . . . . . . . 1717 Petr Polskoy Optimization of Structure Parameters of Semi-trailer-tank for Hydraulic Fracturing of Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1727 Alexey Lebedev, Sergey Kireev, Marina Korchagina, and Andrey Efimov Development of Methods for Controlling the Chip Form via Intensified Chip Curling in the Cross-Sectional Plane . . . . . . . . . . . . . 1737 Stanislav Mikhailov and Nikolai Kovelenov Development and Industrial Testing of a Method for Assessing the Deformation Properties of a Fixed Soil Massif . . . . . . . . . . . . . . . . . . . 1747 Albert Prokopov and Ilya Sychev The Main Approaches to Defining the Boundaries of Agglomerations of Large Cities (Including Using the Capabilities of Big Data Mobile Network Operators) . . . . . . . . . . . . . 1757 Dmitry Chebotarev Warehouse Buildings Made of Wood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1767 Gennadiy Verzhbovsky and Filipp Chervyakov Methodology of Comparative Analysis of the Use of Leasing and Net Lending in the Technical Re-equipment of the Machine and Tractor Fleet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1777 Arthur Alukhanyan and Olga Panfilova
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Choosing the Communication Technologies and Technical Means for the Transport Infrastructure in Rural Areas . . . . . . . . . . . . . . 1787 Marina Zvezdina, Yuliya Shokova, and Alexandr Eliseev Use of Crushed Materials for Decorative Self-compacting Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1799 Lyubov Kastornykh, Vera Kosenko, Alexander Kaklyugin, Mikhail Kholodnyak, and Vladimir Khartanovich Experimental Study of the Technology of Splicing Steel Rope on Machines with Rope Traction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1811 Edward Marchenko, Sergey Popov, Andrey Izyumov, Julianna Marchenko, and Evgeny Kosenko Improving the Safety of Operation of Handling Equipment During Container Transportation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1823 Aleksey Demyanov, Sergey Popov, Nikolay Dontsov, Julianna Marchenko, and Irina Pavlova Calculation of Resistance Due the Destruction of Soil by a Cutter . . . . . 1833 Sergey Kuren, Sergey Popov, Nikolay Dontsov, Julianna Marchenko, and Nikolay Ryzhkin Efficiency Analysis for Mechanical Mixing Systems of Cementing Units . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1843 Valentin Stepanov and Sergey Kireev Application of the Aggregated Approach to the Development of the Strategy of Technical Re-equipment of the Machine and Tractor Fleet of an Agricultural Enterprise . . . . . . . . . . . . . . . . . . . . . 1853 Lyudmila Borisova and Arthur Alukhanyan Truck Maintenance Frequency Optimization, Taking into Account an Increase in Its Operational Reliability . . . . . . . . . . . . . . . 1863 Marina Zaitseva, Sergey Popov, Julianna Marchenko, Nikolay Dontsov, and Elena Nemtseva Vibroacoustic Characteristics of Flat Workpieces Hardening in Transport Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1873 Alexander Isaev, Sergey Popov, Julianna Marchenko, Nikolay Dontsov, and Evgeny Kosenko Method of Student Individuality Identification for Adapting and Intelligent Training Module Based on Soft Models . . . . . . . . . . . . . . . 1881 Ilgar Alekperov, Gurru Akperov, Yuri Prus, Vladimir Khramov, and Safura Muradova Energy Saving in Hydraulic Testing Systems . . . . . . . . . . . . . . . . . . . . . . . . 1889 Alexey Pelipenko, Alexander Rybak, Natalya Vyborova, Sergey Zolotov, Vladislav Zubtsov, and Dmitry Lugantsev
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Tillage Device of Precision Pocessing with Pulsed Blows of Compressed Air . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1897 Yuri Lachuga, Badri Akhalaya, Yuri Shogenov, Besarion Meskhi, and Dmitry Rudoy Calculation and Optimization of Parameters of Standard Size Range of Unified Sections for Water Aluminum Radiators of Autotractor Engines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1905 Yekaterina Parluk and Otari Didmanidze Effective Options for Strengthening Reinforced Concrete Compressed Columns in Terms of Technical and Economic Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1913 Sergey Georgiev, Dmitry Mailian, and Valerii Chubarov Effective Options for Composite Strengthening of Eccentric-Compressed Reinforced Concrete Poles with Small Eccentricities of Load Application . . . . . . . . . . . . . . . . . . . . . . . 1923 Petr Polsky, Sergey Georgiev, and Dmitry Mailian Investigation of the Mechanical Effect of Machinery on the Soil . . . . . . . 1933 Galia Kokieva, Varvara Druzynova, Senge Yampilov, Daba Radnaev, Stanislav Shukhanov, and Akulina Popova On Determining the Elasticity Modulus of Moso Bamboo Based on the Static Bend Test Results by Analogy with Wood and Engineering Plastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1941 Gennadiy Verzhbovsky, Sergey Skuratov, and Sergey Shutskiy Study of the Predicted Rate of Energy Resources Consumption on the Old Airport Renovation Area in Rostov-on-Don . . . . . . . . . . . . . . . 1949 Svetlana Sheina, Eduard Tumanyan, Evgenia Minenko, and Polina Fedyaeva Applying Logistics Technology to the Transport of Consolidated Agricultural Cargo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1961 Luba Eremina and Nikolay Negrov Digital Freight Management in Transport Hubs in China . . . . . . . . . . . . 1971 Li Bingzhang and Vladimir Zirianov The Analysis of Russian Railway Transport Enterprises Economic State in Terms of Market Transformation . . . . . . . . . . . . . . . . . 1985 Natalya Magomedova, Maria Khlebnikova, and Viktoriya Razhina Investigation of the Energy-Saving Hydraulic Drive Dynamics of the Arrow Lifting Mechanism of the Forestry Manipulator . . . . . . . . . 1995 Alexander Rybak, Petr Popikov, Dmitry Bogdanov, and Andrey Konyukhov
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Features of the Block-Modular Cooling System of Traction Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2005 Yekaterina Parluk and Otari Didmanidze Evaluation of the Functional Characteristics of the Elastic-Damping Mechanism of the Tractor Power Transmission Based on Statistical Analysis . . . . . . . . . . . . . . . . . . . 2013 Zakhid Godzaev, Veronika Duryagina, Sergey Senkevich, Vladimir Kravchenko, and Irina Gamolina Analysis of the Operation of Sowing Units Based on DMC Seeders in the Siberian Federal District Farms . . . . . . . . . . . . . . . . . . . . . . 2023 Vladimir Belyaev, Viktor Buxmann, Besarion Meskhi, Dmitry Rudoy, Anastasiya Olshevskaya, and Ruslan Kastsiukevich Hydraulic Actuator of Reciprocating Motion . . . . . . . . . . . . . . . . . . . . . . . . 2033 Olesya Golubeva, Alina Pogorelova, and Viktor Mirniy Reducing the Dynamic Loading of the Links of the Machine-Tractor Unit Aggregated by the Mobile Power Vehicle of the 1.4 Drawbar Category . . . . . . . . . . . . . . . . . . . . . . . . . 2043 Vladimir Kravchenko, Lyudmila Kravchenko, Victor Zhurba, Sergey Senkevich, and Veronika Duryagina Paradox of the Image in Digital Communications . . . . . . . . . . . . . . . . . . . . 2053 Diana Volkova and Inna Topchiy Knowledge Base Applied Usage Operating on the Basis of Network Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2063 Anush Melikyan, Ani Babloyan, Eduard Manukyan, and Ovsanna Manukyan Impact of the Digitalization Trend on the Management of Production Systems and Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2073 Tatiana Tukhkanen, Alexandra Voronina, Alexander Okhotnikov, and Svetlana Goncharova
Proposals for Development of Piggyback Transportation in the South of Russia Victor Zubkov , Ekaterina Ryazanova , Nikolay Ryazanov , and Nina Musienko
Abstract The paper proposes a methodology for the effective organization of piggyback transportation, starting with the establishment of the required number of trains, determining the optimal track development of the piggyback terminal and ending with the assessment of piggyback trains’ passage along the route. The initial approved scheme for piggyback transportation on the territory of Russia is being revised, and new directions are being established that have potential for their development. The article presents the procedure for establishing the piggyback trains’ number that can turn on the selected direction after creating attractive conditions for transition to piggyback transportation. The calculated number of piggyback trains was taken as the initial information for choosing the optimal piggyback terminal technology. The paper substantiates a methodology choice for modeling of the terminal operation, which application is considered by the example of developing an optimal technology for a piggyback terminal in the South of Russia and establishing the necessary track development for it. To assess the passage of the calculated number of piggyback trains in the direction, the work considers the organization of their movement along the schedule fixed lines. The necessary measures are being established to increase sections’ capacity to create conditions for the development of potential flow of piggyback trains. Keywords Piggyback routes · Piggyback terminals · Technology · Modeling · Track development · Schedule fixed lines · Throughput capacity
1 Introduction The advantages of piggyback transportation have been repeatedly confirmed by foreign authors considering the issue in their papers [1–13]. V. Zubkov · E. Ryazanova (B) · N. Ryazanov · N. Musienko Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Square, Rostov-on-Don 344038, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_1
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Currently piggyback transportation has become widespread in Europe, the USA, and Australia and is called the “running highway”. This is because the current level of economic development, its globalization impose ever-higher demands on transport sector. Speed, efficiency of delivery, as well as the safety of goods are of primary importance. An important factor is environmental safety of cargo transportation. All these requests are fully met by a new method of cargo delivery for our country— piggyback transportation. In the article of A.N. Kryazhev is said, that since 2010, numerous attempts have been made in Russia to organize regular piggyback traffic on certain routes. Basically, the initiator of such projects was JSC «Russian Railways» company. However, there is a number of unresolved problems, which are pointed in the works of A.V. Fedorina, A.V. Cyganov, E.A. Mamaev, M.YU. Skorchenko. Its have led to a lack of demand for this type of service in the Russian market. We can enumerate them as follows: lack of piggyback terminals, service infrastructure, specialized rolling stock, lack of government support for the piggybacking program, which would make it possible to create attractive tariffs competing with road transport. No less important are lack of conditions ensuring demand for this type of transport, that include introduction of more stringent environmental requirements, restrictions on the vehicle axle load and restriction of vehicle movement on holidays. As a result, current investments in piggyback technology development are associated with high risks. Due to the high costs of piggyback terminals organizing, the development of piggyback transportation should take place primarily in areas of high demand. One of the factors determining their demand is the significant volumes of passenger traffic, the speed of which is growing. Under these conditions, the organization of a significant amount of freight traffic is impossible. The number of freight trains needs to be reduced, and those that remain will need to move at higher speeds. According to the European Agreement on the Most Important Lines of International Combined Transport, a permissible speed of 120 km/h with a load of less than 22.5 tons/axle should be provided, which will become possible after putting platform cars into operation for piggyback-container transportation for the 1520 mm gauge. In this regard, the movement of piggyback trains on fixed lines of the schedule will be a way out of this situation. One of these destinations is the southern direction from Moscow to Rostov-onDon, the road infrastructure of which is overloaded due to the implementation of huge volumes of road transport. At the same time, it will be impossible to implement the transition from road to rail transport in the future, even if the cargo owners are interested in this, since this direction will specialize for passenger trains passing to the southern resorts of Russia, and the number of freight trains will be reduced to a minimum. However, if the movement of freight trains is organized at an increased speed, the number of freight lines can be increased, and their occupancy can be improved by the service quality. In order to reorient the freight traffic to rail transport, it is proposed to develop piggyback transportation, the uniqueness of which lies in the fact that road and rail transport become partners but not competitors. For this purpose, it is necessary to design terminals location, their technology and proposals on the sequence from loading to unloading.
Proposals for Development of Piggyback Transportation …
3
2 Research Method To select a route for piggyback trains and, accordingly, to determine the location of piggyback terminals, it is necessary to collect information about existing freight flows and those ones which can potentially be involved in rail transportation in future. Initially, the development of piggyback transportation on 1520 mm gauge was planned in accordance with the General Scheme for the Development of piggyback transportation, approved by the Senior Vice-President of JSC “Russian Railways” V. A. Gapanovich and presented on the website http://xn--c1akhbnbahv.xn--p1ai/. According to it, it was planned to organize 13 routes on the gauge of 1520 mm. In the South of Russia, the network covers only Krasnodar. However, in our opinion in conditions of a dynamic transportation market, the originally approved piggyback transportation network should be revised from time to time. So, according to the studies presented in the work of M.N. Prokof’ev, a cartogram of the distribution of freight traffic flows from the direction of St. Petersburg—Moscow to the European part of Russia was formed (Fig. 1). Obviously, the greatest potential for organizing piggyback transportation belongs to the most loaded road transport routes. Accordingly, the choice of optimal piggyback routes should be based on an assessment of the existing traffic intensity and take into account the prospective change in the traffic situation presented in Table 1 based on information from the website http://xn--c1akhbnbahv.xn--p1ai/. In accordance with this, decisions are made on the location of piggyback terminals. However, the authors R. R. Gusejnov and M. YU. Skorchenko who studied this issue in their works, in connection with high capital costs, argue for construction of piggyback terminals on the basis of existing railway stations on the territory of freight yards after their certain revision, namely: increasing the useful length of lowered tracks. Meanwhile, the feasibility of this proposal will be ensured in case when freight yards are not limited by residential buildings and there is room for lengthening tracks and expanding parking areas for automobiles waiting to be loaded onto platforms. If one of the restrictions is not met, that is maximum annual capacity of a station with a piggyback terminal must be no less (P max ), than its required annual capacity (P n ): m i=1
Pimax ≥ P n ,
(1)
It will require the construction of a new terminal with capacity reserve to handle piggyback trains in future. In this regard, in order to define the variant for creating a piggyback terminal, it is necessary to set its required power. The analysis of the park structure, presented on the website http://xn--c1akhb nbahv.xn--p1ai/, shows that about 25% of vehicles participate in goods transportation that make up the target market segment for piggyback technologies (truck tractors and vans).
4
V. Zubkov et al. Murmansk Petrozavodsk
Helsinki
Symbols:
Kotla
Car flows in both sides St. Petersburg
7000, track Е105/М10 301 - 600 201 - 300 101 - 200 35 - 100
Moscow Nizhny Novgorod Ryazan
Kazan
Orel Kursk Penza Voronezh
Belgorod
Samara
Saratov
Volgograd Rostov-on-Don Astrakhan
Krasnodar
Fig. 1 Distribution of freight traffic flows in the direction of St. Petersburg–Moscow in the European part of Russia Table 1 Potential traffic volume on domestic routes №
Destination
Travel time, days
Automotive vehicles Per day
Per year
1
2
3
4
5
1
St. Petersburg–Yekaterinburg
5
900
300 000
2
St. Petersburg–Mockva
1,5
300
1 000 000
3
Moscow–Vologda
1
2 300
800 000
4
Moscow–Nizhny Novgorod–Kazan–Yekaterinburg
4
3 000
1 000 000
5
Moscow–Samara
3
1700
600 000
6
Moscow–Astrakhan
4
1400
500 000
7
Moscow–Krasnodar
4
1400
500 000
8
Yekaterinburg–Astrakhan
5
900
300 000
9
Moscow East–West
0,5
700
2 500 000
10
Moscow South–North
0,5
700
2 500 000
Total
10 000 000
Proposals for Development of Piggyback Transportation …
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Then the potential flow of cars that can be converted to intermodal piggyback traffic is determined by the formula (2): vehical = Nsum · 0.25, Nrvehical ollst
(2)
vehical —total vehicles flow in the direction under study (Fig. 1 and Table 1); where Nsum 0.25—share of vehicles for piggyback transportation (this share may change in future). The calculated number determines the expected intensity of trains arriving at the piggyback terminal, the service efficiency of which depends on the selected optimal terminal operation technology. Since the operation of a piggyback terminal can be represented as a process, the most obvious approach to choosing the optimal technology is discrete-event modeling [14], which is used in production modeling, as queuing systems, at a medium and high level of detail. The use of this method as optimal for solving the problem is also explained by the fact that discrete-event modeling allows changing the main variables of the system, experiment with the queue length, the intensity and number of requests received by the system, the duration of service, and monitor the system’s response in terms of queue length, average service time, canal occupancy, etc.. That is especially important when choosing the optimal technology for the existing potential flow of piggyback trains and in future. In the work of D.V. Kuz’min, it is also emphasized that if a system contains a large number of objects with different behaviors, the construction of an adequate model is impossible without the joint use of the agent approach. This approach is a simulation method that studies behavior of decentralized agents and how this behavior determines the behavior of the entire system as a whole. But if we take into account that the conditions for using piggyback trains are limited in Russia, for example, due to long distances, the most acceptable are unaccompanied transportation, then the number of blocks in the model will be in acceptable sizes for using only discrete-event modeling. An example of a discrete-event model for working with a piggyback train at a terminal is shown in Fig. 2. In parallel, a model is being built for working with the flow of cars arriving at the piggyback terminal, which is combined with the flow of trains in the “Unloading/Loading” block. Due to the low level of detail of the model for calculating indicators, one can use analytical formulas of the queuing systems theory. Based on the simulation results, the necessary track development for servicing piggyback trains, the size of the parking area, the number of locomotives, tractors, teams for inspection, etc. are established for different flow rates. For convenience, calculations are made in an Excel table, if the results are not satisfied, then, changing one of the parameters, one can immediately see what this will lead to and draw conclusions about the adoption of new results or the need for further parameters variation. Another important issue that needs to be resolved for the efficiency of transportation by piggyback trains is the order of their movement between terminals. According to the “Operating Model of Piggyback Transportation” developed in 2014 by Russian
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shipping yard train locomotive uncoupling operation
rolling stock fixing operation
operation of technical inspection on arrival
hitching operation of a shunting locomotive
driving up onto the way of unloading
loading and unloading yard acceptance and delivery operations
unloading / loading
acceptance and delivery operations
departure from the way of unloading
operation of technical inspection on departure
Fig. 2 The structure of the discrete-event operation model of a piggyback terminal with a train of low level detailing
Railways, presented on the website https://jd-doc.ru/2014, it is proposed to base regular piggyback transportation on the principles of passenger traffic (scheduled traffic) regardless of the train load. However, the problem is that the movement of piggyback trains is organized mainly in directions that already have the capacity of above the permissible limits, and, as it is said in the work of V.A. Sharov, A.F. Borodin, the movement of trains on a schedule requires capacity reserve, which includes: – time reservation for schedule overtaking, which implies travel time increase in the section by 3–5% and 2–4 min addition on the last stage before the technical station trf r. + 0, 05 trf r. + 4 min (3) ( trf r. ), = – time reservation to exclude delays transmission to other trains, implying an increase in the train interval by 1–2 min I = I + 2 min
(4)
In order to lay the required reserves in the lines for piggyback trains passage, it is necessary to implement technical and technological measures, assessment of which we have carried out in our work [15]. One of the measures considered to increase capacity is the use of new train locomotives and innovative railcars. The introduction of new types of railcars, specially designed for piggyback transport in the gauge of 1520 mm, capable of moving at a speed of 120 km/h, corresponds to these measures. As a result, the travel time of freight trains on the stages will decrease, and even if a reserve is laid (formula 3), the total travel time of freight trains on the section will not change. As a result, the parameter , calculated according to the Instructions for calculating the railway capacity according to the formula (5), will not decrease, the removal coefficients εpas
Proposals for Development of Piggyback Transportation …
7
i εas , calculated according to formulas (6) and (7) will not increase, and the required capacity of the section determined according to formula (8) will not increase as well.
ε pass
pass
tr Δ = fr ; tr t f r (1 − ) · 0.8 − 0.005 · n pass + 1.3; = I
(5)
(6)
εas = (Sas + 1) · (1 − 0.02 · N pass · (2 − av )) > 1
(7)
train , Nr eq = N f r + N pass · ε pass + Nas (εas − 1) · βr es , day
(8)
pass where tr —sum of net travel time of a passenger train on the section under consideration; t f r —travel time of a freight train on a limiting haul; N pass —total number of passenger trains on the section; I—calculated inter-train interval on the section; Sas —number of intermediate stations served by a modular train; N f r —total number of freight trains on the section; Nas —modular trains number; βr es —section capacity reserve for a double-track section, (βr es =1.1–1.15). If the sections for piggyback trains are equipped with an automatic locomotive signaling system (ALSS) with mobile block sections, the inter-train interval for piggyback trains is allowed at 6 min, like for passenger trains. Then, in case a reserve is set according to the formula (4), the travel interval for piggyback trains will not exceed the interval for freight trains, which is 8 min. This arrangement will not reduce the available capacity (formula 9) when piggyback trains move along schedule fixed lines, in contrast to the option when movement along schedule fixed lines is organized for trains traveling at a freight speed. Nn =
(1440 − ttech ) · αr el , α pass · I pass + β f r · I f r
(9)
where α pass , β fr —the share of passenger and freight traffic volume on the section, respectively; I pass , I fr —the inter-train interval between passenger and freight trains, respectively; ttech —duration of the technological window on the section, (ttech = 150 min); αr el —coefficient considering influence of failures in the operation of technical means (tracks, signaling, centralization and blocking devices, contact network), (αr el = 0.9–0.96).
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The evaluation of the proposed methodology for developing an effective organization of piggyback transport in the South of Russia is considered on the Moscow– Rostov-on-Don route, which is one of the busiest and requires measures to solve this problem. The study results are shown below.
3 Research Results On the basis of the cartogram presented in Fig. 1, significant amounts of freight traffic have been established at amount of 301 to 600 vehicles per day, which originate in Moscow and are extinguished in Rostov-on-Don. This fact substantiates the proposal to adjust the initial development plan for piggyback transportation and introduction of a new piggyback terminal near Rostov-on-Don. The proposal for the location of a piggyback terminal in Rostov agglomeration may become attractive to cargo owners if the necessary conditions for the development of piggyback transportation are met. In this case, a piggyback terminal can be both transit and final. In the case of organizing a transit piggyback terminal as an exchange transit freight traffic, one can consider the freight traffic destined for Krasnodar, Sochi and vice versa. According to the formula (2), potential number of vehicles that can be used for piggyback trains between the terminals in Moscow and Rostov-on-Don is equal to = 600 · 0.25 = 150 vehicles. Nrvehical ollst In future, if we expect the implementation of optimistic forecasts for freight traffic increase in the considered direction (Table 2), the number of such vehicles will be equal to Nrvehical = 1400 · 0.25 = 350 vehicles. ollst Depending on the adopted length of piggyback trains, their number is established, which is necessary for the transportation of the calculated number of cars. For pilot projects, a length of 44 cars was assumed. Based on this, the number of formed trains train is assumed to be Nrtrain ollst = 4 within the existing volumes and Nr ollst = 8 in future. These values determine the intensity of the flow λ entering the elements of the train processing model at the piggyback terminal (Fig. 2). Further results depend on the adopted technology and performance standards. These parameters can be controlled until the desired indicators are achieved. One of the options is shown in Table 2. Using analytical formulas of the queuing systems theory for the given parameters, the loading of service canals is established, which is the initial information for calculating the number of trains in each model element and the downtime duration taking into account the unevenness of the transport process (Table 3).
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Table 2 Distribution variant of work volumes between the elements of the terminal model serving the train № Element
Train numbers/before
Serving canal
Current volume Volume in future
1
Operation of technical inspection on arrival
4
8
2
Operation of technical inspection on departure
4
8
3
Driving up
4
8
4
Driving out
4
8
5
Acceptance and 4 delivery operations before driving up
8
6
Acceptance and delivery operations after cleaning
4
8
7
Unloading
4
8
8
Loading
4
8
Processing time considering unevenness, min M(Top )
Maintenance system (1 team of wagon drivers, 4 inspectors each)
61.04
1 Shunting locomotive
65.72
Acceptance and delivery workers (1 brigade)
48.32
61.92 40.16
40.16
Tractor units (4 pcs)
481.92 562.24
Due to the fact that Excel tables were used for calculations, changing one of the parameters, in this example—the rate of receipt, all values are automatically recalculated (in Table 3 are shown in fractions), by which it is possible to assess the consequences of the change and the need for revision path development or technology. Therefore, in Table 3, you can see that an increase in the trains flow leads to loading of tractors above the permissible norm, therefore, in case of the flow increase, it is necessary to change the technology—to introduce an additional number of tractors. With the help of Excel tables, increasing the number of tractors by 1, the permissible load volume is checked. The recalculation is done until the load reaches the permissible size. According to the results obtained, the minimum number of tractors at which the load does not exceed the permissible dimensions (0.85) should be 7 (Table 4). Considering this data, the rest of the indicators are recalculated, the values of which are presented in Table 4. Based on the established number of trains in the system of each model element (column 6 in Tables 3 and 4), the required number of tracks is determined for efficient processing of piggyback trains at the terminal. The obtained results of calculating the necessary track development for a piggyback terminal allow us to make a conclusion about the possibility of their creation
0.21/0.54
0.22/0.54
8
0.59/–
6
7
0.55/–
5
0.13/0.29
4
0.13 (0.7 p for each element)/0.47 (0.23 p for each element)
Cleaning
Driving up
Loading
Unloading
Acceptance and delivery operations after cleaning
0.19 (0.10 p for each element)/0.86 (0.43 p for each element)
0.06 (0.03 p for each element)/–
0.32/1.42
0.31/1.41
0.62/–
0.58/–
0.16/0.47
0.16/0.47
0.26/0.93
0.23/0.88
Ls, number of trains in Lk, number of queue trains in the system
Acceptance and 0.06 (0.03 p for each delivery operations element)/0.18 (0.09 p before driving up for each element)
Operation of technical inspection on departure
Operation of technical inspection on arrival
Element
0.58 (0.29 h for each element)/2.59 (1.3 h for each element)
0.17 (0.09 h for each element)/–
0.19 (0.10 h for each element)/0.54 (0.27 h for each element)
0.40 (0.20 h for each element)/1.41(0.71 h for each element)
Ws, downtime in queue, hour
83.25/143.51
79.45/139.71
567.42/–
487.10/–
45.93/56.34
45.93/56.34
72.97/103.37
60.25/90.65
Wk, downtime in the system, min
Note in columns 5 and 7, the values are equally distributed among the elements that are served by one canal, based on the assumption that there are no priorities in performing operations
Shunting locomotives (1 pc)
Tractor units (4 pcs)
0.13/0.29
3
0.20/0.46
2
Acceptance and delivery workers (1 brigade)
0.16/0.41
1
Maintenance system (1 brigade)
System loading, ρi
№
Serving canal
Table 3 Calculation of the trains’ number in the system and their downtime duration
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Table 4 Calculation of trains’ number in the elements served by tractors after their increase Serving canal
№
System loading, ρi
Element
Ls, number of trains in queue
Lk, number of trains in the system
Ws, downtime in queue, hour
Tractor units (7 pcs)
5
0.69
Unloading
0.72
Loading
0.01 (0.005 p for each element)
0.69
6
0.73
0.01 (0.005 h for each element)
Wk, downtime in the system, min 482.17 562.49
based on existing railway stations on the territory of freight yards or about the need to build a new terminal. If we focus on the promising volumes, then the construction of a new terminal is the best solution. Moreover, choosing a location it is necessary to exclude the creation of an additional load on the main highways and to ensure proximity to the repair base in case of the flatcars repair need. If we consider the agglomeration of Rostov-on-Don, then as the location of the piggyback terminal, we can discuss the territory between Bataysk and Azov, which has a railway connection, possibility of providing the entrance of trucks to bypass the busy M4-Don highway, as well as the proximity to the railroad car repair depot of Bataysk station. The final decision is made on the basis of design and survey work. In addition, comparisons with the option of the length of the tracks in the loading and unloading yard equal to the length of half of the train. An assessment of the possibility of organizing the movement of piggyback trains along fixed lines of the schedule on the Moscow–Rostov-on-Don route was carried out at one of the busiest sections of Rostov–Likhaya. As mentioned earlier, thanks to the use of a new type of rolling stock, piggyback trains will be able to move at a passenger speed of 120 km/h. Placing a reserve of 2 min in an inter-train interval when organizing their movement along fixed lines will lead to the fact that the minimum interval between the schedule lines will be no more than between freight trains. Therefore, introduction of piggyback trains, following a fixed schedule, instead of conventional freight trains, will not change the available capacity in any way. If in future the section will provide for the passage of 90 passenger, 20 freight trains, and 4 piggyback trains, then α pass = 0.82 and β fr = 0.17. Then the available throughput will be: Nn =
(1440 − 150) · 0, 96 ≈ 197 train pairs 0, 82 · 6 + 0, 17 · 8
To determine the required throughput and its correspondence to the current one, the following initial data were collected: passeven t =115 min; rpassodd =122 min; t rf r even =171 min; tr
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f r odd
tr =174 min; t f r = 23 min; N pass = 90 train pairs in future; N f r = 20 freight train pairs in the section; Nr ollst = 4 piggyback train pairs in the section; Nas = 2 modular trains; Sas = 5 intermediate stations served by a modular train; βr es = 1.1. For piggyback trains, according to the formula (3), an increased travel time along the section is established, taking into account the laid down reserve (trr ollst.even ) = 124.75 min; (trr ollst.even ) = 132.1 min. According to formula (5), the parameter is calculated for passenger and piggyback trains: pass = 0.68; ravollst = 0.68. av pass
As the parameter ravollst for piggyback trains has not changed compared to av for passenger trains, then the removal coefficient is considered to be common for passenger and piggyback trains, only in the formula (6) N pass is summed up with Nr ollst . ε pass =
23 · (1 − 0.68) · (0.8 − 0.005 · (90 + 4)) + 1.3 = 1.6; 8
The removal coefficient of the schedule lines by a modular train is determined by the number of stations served, εas = 5. Then the required capacity for the trains flow in future will be: Nr eq = [20 + (90 + 4) · 1.6 + 2(5 − 1)] · 1.1 ≈ 197 train pairs. As a result, the condition is fulfilled Nr eq ≤ Nn . However, if the demand for piggyback trains increases, the throughput capacity will no longer be enough. Then, to increase the capacity, it is necessary to reduce the number of freight trains due to the fact that some of them are formed with an increased weight. The method of determining the number of trains of increased weight is considered by the authors in [16].
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4 Discussion To assess the proposal for the development of piggyback transportation in the southern region of Russia, the authors proposed a methodology, the difference of which is the inclusion of all planning stages, starting with the establishment of the required number of trains, determining the optimal track development of the piggyback terminal and ending with the assessment of the passage of piggyback trains along the route. The paper proposes not to be limited to the approved General Scheme for the development of piggyback transportation in Russia, but to adjust it based on the analysis of the vehicles flows that are target for piggyback transportation. So, based on the analysis of the cartogram of the cars flow distribution, it was proposed to organize a piggyback terminal in the area of Rostov-on-Don, where there is repayment of a significant flow of vehicles. On this basis the possible number of piggyback trains is also established which will be in demand if attractive conditions are created for the transition to this transportation type alongside with the current traffic flows of road transport and in future. The calculated number of piggyback trains is used to simulate the optimal technology of a piggyback terminal in order to establish its track development. At the same time, considering the limited conditions for the piggyback trains use in Russia, in contrast to the diversity that exists abroad, choosing a modeling method, it is proposed to limit ourselves to discrete-event modeling. This method, at a low detail level, allows using analytical formulas to calculate the main indicators necessary to establish the required path development. The proposed minimum level of automation in the form of Excel spreadsheets makes it possible to vary the input data until the results meet the given constraints. This technique was considered on the example of establishing a track development for placing a piggyback terminal in the district of Rostov-on-Don. The results obtained also influence the decision to create piggyback terminals based on existing railway stations on the freight yards territory or the need to build a new terminal. Therefore, for the example under consideration, in the case of attracting a promising volume of automobile traffic for piggyback transportation, it will be necessary to build a new terminal. One of the variants of the track development scheme is proposed in the work based on the calculated optimal number of tracks. When assessing the possibility of effectively organizing of the piggyback trains movement along schedule fixed lines of Moscow–Rostov-on-Don route, which is characterized by a high level of workload, it was found that, in addition to the construction of the piggyback terminals themselves, it was necessary to implement technical and technological measures to increase traffic throughput capacity. Using the example of the busiest section of the considered direction, it is shown that with the volume of traffic in future passenger traffic will prevail over freight. After a new type of rolling stock with speed of 120 km/h will be put into operation and the sections will be equipped with an automatic locomotive signaling system (ALSS) with moving block sections, allowing reducing the interval between trains in the section, it will
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be possible to pass a minimum number of piggyback trains. For piggyback trains passage in future, in addition to the above measures, it will be necessary to increase the weight of freight trains in order to master a larger traffic flow with a smaller number of trains. As a result, the paper proposes a methodology for the effective organization of piggyback transportation, the use of which will make this transportation type popular in Russia after creating attractive conditions for the transition to piggyback transportation. This will raise up the quality of services in rail transport to world standards and make the passage of goods through Russia competitive in the network of international transport corridors.
References ˇ 1. Kurhan M, Cerniauskait˙ e L, Kurhan D (2020) Use of container and piggyback services in international railway traffic. In: Gopalakrishnan K, Prentkovskis O, Jackiva I, Juneviˇcius R (eds) TRANSBALTICA XI: transportation science and technology. Lecture notes in intelligent transportation and infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-386665_55 2. Macharis C et al (2010) A decision analysis framework for intermodal transport: comparing fuel price increases and the internalisation of external costs. Transp Res Part A 44(7):550–561. https://doi.org/10.1016/j.tra.2010.04.006 3. Mai Y, Liu J, Sun X (2015) Key problems of the development of piggyback transport in China. In: Fifth international conference on transportation engineering. https://doi.org/10.1061/978 0784479384.049 4. Materials of CargoBeamer Company’s Website. CargoBeamer takes combined freight across Europe. http://www.cargobeamer.eu/CargoBeamer-takes-Combined-Freight-acrossEurope795324.html 5. Materials of CargoBeamer Company’s Website. On track, no cranes. http://www.cargobeamer. eu/Terminal-795564.html 6. Materials of Flexiwaggon Company’s Website. Section environmental benefits. Flexiwaggon – the Fastest Route to an Eco-Friendly Future. http://www.flexiwaggon.se/advantages/enviro nment/74-environmental-benefits.html 7. Raitasuo P et al (2019) Sustainable intermodal train transport: new research perspectives. Oper Manage Sustain. https://doi.org/10.1007/978-3-319-93212-5_11 8. Seidelmann C (2010) 40 years of road-rail combined transport in Europe – from piggypack traffic to the intermodal transport system. International Union of Combined Road-Rail Transport Companies UIRR. 9. Skorchenko MY (2018) International experience in organising regular piggyback service. Transp Syst Technol 4(1):19–42. https://doi.org/10.17816/transsyst2018041019-042 10. Smolyanivov A et al (2019) Transport infrastructure condition for organizing piggyback traffic. IOP Conf Ser Earth Environ Sci 403:012200. https://doi.org/10.1088/1755-1315/403/1/012200 11. Spychalski JC, Thomchick E (2009) Drivers of intermodal rail freight growth in North America. EJTIR 9(1):63–82 12. Tsyganov A (2019) Loads of road vehicles during piggyback transportation. MATEC Web Conf 298(38):00109. https://doi.org/10.1051/matecconf/201929800109 13. Wang H, Liu Z (2016) The analysis of economic effect of railway piggyback transportation in China. In: 4th international conference on mechanical materials and manufacturing engineering (MMME 2016)
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14. Chislov O, Bogachev V, Zadorozhniy V et al (2019) Modeling of the rail freight traffic by the method of economic-geographical delimitation in the region of the south-easter coast of the Baltic Sea. Transp Probl 14:2. https://doi.org/10.20858/tp.2019.14.2.7 15. Zubkov V, Ryazanova E, Chebotareva E et al (2019) Capacity and traffic management on a heavy-traffic railway line. In: TransSiberia 2019: VIII international scientific Siberian transport forum, pp 934–949. https://doi.org/10.1007/978-3-030-37919-3_92 16. Kim NS (2021) Assessment of CO2 emissions for truck-only and rail-based intermodal reight systems in Europe. Transp Plan Technol 44(4):313–333. https://doi.org/10.1080/030810609 03119584
Model of Atmospheric Effects Onto a Group of Unmanned Aerial Vehicles Dmitry Belonozhko , Igor Korolev , Yury Chernyshev , and Nikolay Ventsov
Abstract Known approaches to the analysis of the reliability of a swarm of unmanned aerial vehicles (UAVs) are implemented on the basis of graph models. As a rule, a UAV swarm is modeled by a graph that displays information about the equipment installed on the aircraft, the topology of the swarm, and the connections between the equipment. Destructive effects on the UAV swarm are modeled by removing vertices from the graph. The feasibility of the tasks of the UAV swarm is determined on the basis of estimates of the connectedness of the vertices, the modified graph, corresponding to the necessary equipment. The advantage of such approaches is the possibility of obtaining the reliability characteristics of the UAV swarm equipment of a given configuration when performing the assigned tasks. But, at the same time, the computational complexity of such approaches significantly depends on the topology of the graph, including the number of vertices and the connections between them. The article considers the issue of building a model of the effects of atmospheric influences (environmental factors) on UAVs based on fuzzy sets. Atmospheric influences of the external environment include wind loads, atmospheric precipitation and temperature conditions of the external environment, which are presented as fuzzy numbers with triangular membership functions. The models take into account possible atmospheric impacts and make it possible to determine the probability of damage to a group of UAVs. The computational complexity of the proposed approach significantly depends on the number of qualitative estimates of atmospheric impacts on a group of UAVs. Based on the developed models, the values of the probability of damage to a group of UAVs as a result of various atmospheric influences are calculated. Keywords Unmanned aerial vehicle · Control system · Fuzzy sets · Mathematical model · Control · Atmospheric actions D. Belonozhko · I. Korolev S.M. Shtemenko Krasnodar Higher Military School, Street Krasina, 4, Krasnodar, Krasnodar Region 350035, Russia Y. Chernyshev · N. Ventsov (B) Don State Technical University, Gagarin Square, 1, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_2
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1 Introduction Aircraft are actively used in agriculture. In [1], three horizons are defined that predict the future of aircraft: the first horizon is the leading role of manned aviation and the secondary role of unmanned aerial systems; the second horizon is innovation and synergy between manned and unmanned aircraft; third horizon (research)— the leading role of unmanned systems. The perspective of the leadership of UAVs determines the development of a large number of subsystems that intellectualize their operation and functioning. The paper [2] proposes an algorithm for generating an optimal flight route in difficult conditions caused by the presence of obstacles. In [3], an adaptive control strategy is studied for tracking the UAV trajectory in gusty winds. In [4], the problem of UAV control under conditions of drive failure and wind exposure is solved. In [5], an approach was proposed for predicting the service life of an unmanned system operating on solar energy. The paper [6] presents an algorithm that optimizes UAV trajectories in models of a three-dimensional urban environment. In [7], a method is proposed for making coordinated combat decisions by a UAV swarm based on a consensus threat assessment. In [8], a method for modeling and assessing the reliability of a UAV swarm flight under conditions of random and targeted attacks is proposed. The reliability of the mission (the degree of feasibility of the task by a swarm of UAVs) is assessed by two indicators: vulnerability and connectivity. A vulnerability determines whether a system can easily lose its ability to perform a particular task due to external factors. The mission network of the UAV swarm can only complete its task if each payload type exists and they are connected in the specified order, the required payload types form a complete mission chain. In the context of the competitive development of unmanned systems, the main problem is that maintaining a qualitative advantage inevitably entails ever higher costs for development, production and operation, which threaten the strategic usefulness of the system, since they lead to a shortage of the actual number of available air platforms [1]. For this reason, it is necessary to pay special attention to the issues of a priori identification of situations in which the operation of UAVs may be associated with an increased accident rate. The reasons for the occurrence of such situations, in many cases, are difficult weather conditions. The influence of environmental factors on a group of UAVs can significantly reduce the quality of the task, and under certain values of the parameters of external influences, it can completely exclude the possibility of using a group of UAVs due to the high probability of their damage. Solving problems related to maintaining the effective functioning of a group of UAVs in various climatic conditions is an important step in drawing up requirements for UAV onboard equipment that ensures flight safety in emergency situations arising under the influence of various weather phenomena.
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As the impact of environmental factors in [9–12], meteorological conditions such as precipitation, wind loads, air temperature, humidity, air pressure are considered. Some of the listed parameters must be continuously monitored and evaluated during the flight for effective management of the UAV group. For classes of short-range and short-range UAVs, the wind speed is in the range from 20 to 50% of the air speed [13]. It is obvious that exceeding the permissible values of wind speed and precipitation intensity can lead to damage to the UAV. Depending on the design features [14], UAV flight may be unacceptable in conditions of complex atmospheric phenomena such as a snowstorm, storm, squall, hail, thunderstorm, heavy rain, etc. Information about the characteristics of the atmosphere is fuzzy, since on board some UAVs there is no way to accurately measure and represent the atmospheric effects of the external environment in the form of clear numbers [15]. In addition, during the flight, the effects on a group of UAVs can be different. However, when developing the model, only the most significant atmospheric phenomena on the UAV flight route were taken into account—wind speed and precipitation intensity.
2 Representation of the Most Significant Atmospheric Impacts in the Form of Fuzzy Sets Let’s define K = {{E˜ x }, {G˜ y }, {T˜v }}—the universal fuzzy set of atmospheric influences. Since wind speed, precipitation intensity and air temperature are considered as factors of external influences, we introduce fuzzy sets to describe them [16]. The fuzzy set of effects of wind loads on the UAV group will be denoted by E˜ x , fuzzy set of precipitation impacts on a group of UAVs—G˜ y , and the fuzzy set of temperature influences—T˜v . In [17], to study the complex interaction of a UAV group, the aircraft system is considered as consisting of three interdependent network levels: the communication level, the structural level, and the mission level. It is obvious that wind loads have a greater effect on the structural level, as it changes the distances between the UAVs, and precipitation affects the mission and communication levels, since they can make it difficult for the equipment (payload) located on the UAV to implement its functions, as well as to implement some types of communication. Temperature effects, which in some cases cause UAV icing, can affect both the structural level (loss of UAV controllability) and the mission and communication levels (impossibility of operation of UAV suspension equipment in current atmospheric conditions). A clear formalization of the impact of the external environment on each layer can significantly complicate the model, for this reason we will consider fuzzy means of formalizing the impact of one environmental factor on all layers of the UAV group. The composition of the flight and navigation equipment of the UAV includes means for determining air parameters. Thus, the direction and speed of the wind is measured on board using sensors of the static and dynamic pressure system. By
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analogy with the Beaufort scale, we formulate linguistic statements that vaguely characterize the wind loads on the UAV group: “weak wind” (about 3 m/s), “medium wind” (about 7 m/s), “strong wind” (about 11 m/s), “hard wind” (about 15 m/s), “squall” (about 20 m/s). To simplify further reasoning, we denote: E˜ 1 = “weak wind”, E˜ 2 = “medium wind”, E˜ 3 = “strong wind”, E˜ 4 = “hard wind”, E˜ 5 = “squall”. Denote the clear set containing the exact values of the wind speed by E. Then the expression “weak wind” can be interpreted as a fuzzy set E˜ 1 = µ E˜ 1 (e), e|e ∈ E . estimate of the wind speed, it can be argued that E˜ x = Similarly, for any qualitative µ E˜ x (e), e|e ∈ E , x = 1, 5. We use triangular membership functions of elements to fuzzy sets of wind load effects E˜ x [18]: ⎧ 0, e ≤ ax ; ⎪ ⎪ ⎨ (e − ax )/(bx − a x ), ax < e ≤ bx ; µ E˜ x (e, ax , bx , cx ) = ⎪ (c − e)/(cx − b x ), bx < e ≤ cx ; ⎪ ⎩ x 0, e ≥ cx .
(1)
where e—actual clear value of wind speed, ax , cx —bases, bx —vertices of membership functions of wind speed values e to the corresponding fuzzy sets. From formula (1) it follows that the degree of belonging of the wind speed to the values of linguistic variables on the segments [a x ; bx ] and [bx ; cx ] changes linearly. If it is necessary to take into account a more complex effect of uncertainties, for example, due to the imperfection of the UAV control system, or less directional stability due to the lightness of the UAV, it is advisable to use more complex forms of membership functions [19–21]. For a group of UAVs, an indirect method of measuring the intensity of precipitation by the meteorological line-of-sight range between the side and the ground can be used. In the proposed model, the initial data, criteria and limitations are defined, while the definition of membership functions is based on the following characteristics of the effects of atmospheric precipitation of the external environment: G˜ 1 —drizzling precipitation (drizzle)—low precipitation intensity of about 0.5 mm/h—visibility about 5 km; G˜ 2 —snow grains—the average intensity of precipitation is about 1.5 mm/h— visibility about 3 km; G˜ 3 —heavy precipitation (rain, snow)—high precipitation intensity of about 3 mm/h—visibility about 1 km; G˜ 4 —heavy precipitation (rain shower, heavy snow, hail)—critical intensity of precipitation is about 4.5 mm/h—visibility less than 500 m. A clear set containing the exact values of precipitation G. Fuzzy sets describing the intensity of precipitation, we write in the form: G˜ y = µG˜ y (g), g|g ∈ G , y = 1, 4.
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The triangular functions of membership of the amount of atmospheric precipitation g to fuzzy sets characterizing the intensity of precipitation are determined by the formula [18]: ⎧ ⎪ 0, g ≤ a y ; ⎪ ⎪
⎨ (g − a y )/(b y − a y ), a y < g ≤ b y ; µG˜ y g, a y , b y , c y = (2) ⎪ ⎪ (c y − g)/(c y − b y ), b y < g ≤ c y ; ⎪ ⎩ 0, g ≥ c y . where g—precipitation intensity, a y , c y —bases, b y —vertices of membership functions of atmospheric precipitation intensities g to the corresponding fuzzy sets. From formula (2) it follows that the degree of belonging of atmospheric precipitation to the values of linguistic variables on the segments [a y ; b y ] and [b y ; c y ] changes linearly. If it is necessary to take into account a more complex effect of uncertainties, for example, due to the greater exposure of the equipment installed on the UAV to the effects of precipitation, it is advisable to use more complex forms of membership functions [19–21]. For aircraft-type UAVs (light UAVs with short range and low-altitude UAVs with long flight duration, as well as short-range mini UAVs), icing on surfaces can cause changes in aerodynamic parameters and lead to a fall. A high probability of icing is observed in the temperature range from –16° to +2° in conditions of high humidity, as well as under such atmospheric phenomena as fog, rain, sleet. The definition of membership functions is based on the following temperature characteristics of the environment: T˜1 —moderate icing intensity—ambient temperature about –2 °C; T˜2 —high icing intensity—ambient temperature about –7 °C; T˜2 —low icing intensity—ambient temperature about –12 °C. A clear set containing the exact values of precipitation G. Fuzzy sets describing the temperature conditions of the environment, we write in the form: T˜z = µT˜z (t), t|t ∈ T , z = 1, 3. The triangular functions of membership of the amount of atmospheric precipitation g to fuzzy sets characterizing the intensity of precipitation are determined by the formula [18]: ⎧ 0, t ≤ az ; ⎪ ⎪ ⎨ (t − az )/(bz − a z ), az < t ≤ bz ; µT˜z (t, az , bz , cz ) = ⎪ (c − t)/(cz − b z ), bz < t ≤ cz ; ⎪ ⎩ z 0, t ≥ cz .
(3)
where t—temperature conditions of the environment, az , cz —bases, bz —vertices of the membership functions of the temperature conditions of the environment t to the corresponding fuzzy sets.
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From formula (3) it follows that the degree of belonging of the temperature conditions of the external environment to the values of linguistic variables on the segments [a z ; bz ] and [bz ; cz ] changes linearly. If it is necessary to take into account a more complex effect of uncertainties, for example, if chemical anti-icing agents are used before launching the UAV, it is advisable to use more complex forms of membership functions [19–21].
3 Model for Determining the Probability of UAV Damage as a Result of Atmospheric Influences When constructing a model for determining the probability of damage (equipment failure) of UAVs as a result of atmospheric influences of the external environment, we consider the following damage probabilities: I˜1 = low probability of UAV damage (approximately 0.1); I˜2 = average probability of damage to the UAV (approximately 0.475); I˜3 = high probability of damage to the UAV (approximately 0.85). Let us set a clear set I containing the probabilities of damage to the UAV. Let us write the fuzzy sets of UAV damage probability values as a result of atmospheric influences of the environment in the form: I˜v = µ I˜v (PN N ), PN N |PN N ∈ I , v = 1, 3. Triangular membership functions of fuzzy sets I˜v on the values of the probability of damage to the UAV as a result of atmospheric influences of the external environment PN N , are defined [18]: ⎧ 0, PN N ≤ av ; ⎪ ⎪ ⎨ (PN N − av )/(bv − a v ), av < PN N ≤ bv ; µ I˜v (PN N , av , bv , cv ) = ⎪ (c − PN N )/(cv − bv ), bv < PN N ≤ cv ; ⎪ ⎩ v 0, PN N ≥ cv .
(4)
where PN N —UAV damage probability, av , cv —bases, bv —vertices of triangular membership functions of the UAV damage probability PN N to the corresponding fuzzy sets. It is required to determine the probability of damage to the UAV by transforming the input fuzzy situation describing the impact of identifiable natural phenomena (wind, precipitation, temperature) according to a number of features (quantitative and qualitative).
Model of Atmospheric Effects …
23
4 Determining the Probability of UAV Damage as a Result of Environmental Factors It is proposed to use fuzzy estimates of the impact of the external environment on a swarm of UAVs. To logically link qualitative assessments of the intensity of environmental impacts (wind, precipitation, and air temperature) with qualitative assessments of the probability of UAV damage, a series of experiments was carried out to launch light UAVs with a short flight range and low-altitude UAVs with a long flight duration under the influence of environmental factors. Based on expert assessments of statistical data, bases of rules have been developed for various temperature characteristics of the external environment, presented in Tables 1, 2, 3 and 4. Table 1 describes the rules for determining the fuzzy probability of UAV damage in situations where temperature conditions do not significantly affect the UAV performance. Table 1 Rules for determining the probability of UAV damage when t ∈ / T˜z , z = 1, 3 G˜ y
E˜ x E˜ 1
E˜ 2
E˜ 3
E˜ 4
E˜ 5
G˜ 1 G˜ 2
I˜1 I˜1
I˜1 I˜1
I˜1 I˜2
I˜2 I˜2
I˜3 I˜3
G˜ 3 G˜ 4
I˜1 I˜2
I˜2 I˜3
I˜2 I˜3
I˜3 I˜3
I˜3 I˜3
Table 2 Rules for determining the probability of UAV damage when t ∈ T˜1 G˜ y
E˜ x E˜ 1
E˜ 2
E˜ 3
E˜ 4
E˜ 5
G˜ 1 G˜ 2
I˜1 I˜1
I˜2 I˜3
I˜2 I˜3
I˜1 I˜2
I˜3 I˜3
G˜ 3 G˜ 4
I˜1 I˜2
I˜3 I˜3
I˜3 I˜3
I˜3 I˜3
I˜3 I˜3
Table 3 Rules for determining the probability of UAV damage when t ∈ T˜2 G˜ y
E˜ x E˜ 1
E˜ 2
E˜ 3
E˜ 4
E˜ 5
G˜ 1 G˜ 2
I˜1 I˜1
I˜3 I˜3
I˜3 I˜3
I˜1 I˜2
I˜3 I˜3
G˜ 3 G˜ 4
I˜1 I˜2
I˜3 I˜3
I˜3 I˜3
I˜3 I˜3
I˜3 I˜3
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D. Belonozhko et al.
Table 4 Rules for determining the probability of UAV damage when t ∈ T˜3 G˜ y
E˜ x E˜ 1
E˜ 2
E˜ 3
E˜ 4
E˜ 5
G˜ 1 G˜ 2
I˜1 I˜1
I˜2 I˜2
I˜2 I˜2
I˜1 I˜2
I˜3 I˜3
G˜ 3 G˜ 4
I˜1 I˜2
I˜2 I˜3
I˜2 I˜3
I˜3 I˜3
I˜3 I˜3
Table 2 describes the rules for determining the fuzzy probability of damage to the UAV in situations where the temperature conditions contribute to a moderate intensity of UAV icing. Table 3 describes the rules for determining the fuzzy probability of damage to the UAV in situations where the temperature conditions contribute to the high intensity of UAV icing. Table 4 describes the rules for determining the fuzzy probability of UAV damage in situations where temperature conditions contribute to low UAV icing intensity. Tables 1, 2, 3 and 4 present the base of rules for determining qualitative estimates of the probability of UAV damage as a result of atmospheric influences of the external environment, formalized using fuzzy sets. Inference mechanism (solution of the problem related to the determination of the resulting membership function µr es (P˜ N N )), is carried out in the following order: 1) The degrees of fulfillment of each rule are calculated separately, i.e. “cut-off” levels are found for the conditions of each rule of Tables 1, 2, 3 and 4, characterizing the degrees of truth (belonging) of the atmospheric effects of the external environment in the form of wind loads and precipitation corresponding to each current condition (state) of the external environment. Aggregation of the conditions [18, 22] of the described rules is carried out separately for each state of the external environment:
µx yz (e∗ , g ∗ , t ∗ ) = µ E˜ x (e∗ ) ∧ µG˜ y (g ∗ ) ∧ µT˜z (t ∗ ),
(5)
where µx yz (e∗ , g ∗ , t ∗ )—degree of fulfillment (truth value) of the conditions of each individual rule K x yz , corresponding to the parameters of atmospheric influences of the external environment of the database of Tables 1, 2, 3 and 4; µ E˜ x (e∗ ), µG˜ y (g ∗ ), µT˜z (t ∗ )—calculated membership degrees of clear numerical values of wind speed e∗ , precipitation intensity g ∗ , ambient temperature t ∗ of the corresponding fuzzy sets E˜ x , x = 1, 5, G˜ y , y = 1, 4, T˜z , z = 1, 3. The activation membership functions of each rule are calculated using the Mamdani implication operator [23], i.e.—truncated membership functions are found according to the values in the tables of rules corresponding to the degrees of truth of elementary membership functions P˜N N the probability of UAV damage as a result
Model of Atmospheric Effects …
25
of atmospheric influences of the external environment: µ K x yz ( P˜N N ) = µx yz (e∗ , g ∗ , t ∗ ) ∧ µ I˜v ( P˜N N ),
(6)
where µ K x yz P˜N N —activated membership functions of conclusions of each rule K x yz ;
µ I˜ P˜N N —membership functions for the output variable P˜N N . v
2) The probabilities of damage to the UAV as a result of atmospheric influences of the external environment are determined. First, the membership function (accumulation) of the probability of damage to the UAV as a result of atmospheric influences of the external environment is calculated. Then the resulting fuzzy subsets (“truncated in height” membership functions) are combined together to form one fuzzy subset (the resulting membership function) [18]: µr es ( P˜N N ) = µ K 111 ( P˜N N ) ∨ µ K 121 ( P˜N N ) ∨ . . . ∨ µ K x yz ( P˜N N ),
(7)
where µr es P˜N N —the resulting membership function of the output of all rules included in the base of Tables 1, 2, 3 and 4; µ K x yz P˜N N —activated membership functions of conclusions of each rule K x yz .
As a result of the output, the membership function is obtained µr es P˜N N of the fuzzy set I˜v , representing the general conclusion (conclusion) from the rule base. For a clear value PN N of the probability of damage to the UAV as a result of atmospheric influences of the external environment, it is necessary to defuzzify the corresponding fuzzy result. 3) Bringing to clarity (defuzzification). The calculation of the probability of damage to the UAV as a result of atmospheric influences of the external environment is carried out by determining the center of gravity of the plane of the resulting figure, which lies under the graph of the resulting membership
function—as the ˜ ratio of the moment of the figure under the curve µr es PN N about the vertical
axis µ P˜N N to the area of this figure [18]: 1 PN∗ N
=
0
P˜N N µpe3 ( P˜N N )d P˜N N , 1 µpe3 ( P˜N N )d P˜N N
(8)
0
where PN∗ N —a clear value of the probability of damage to the UAV as a result of atmospheric influences of the external environment. At values of the probability of damage to the UAV as a result of atmospheric influences of the environment PN N ≥ 0.4 area of space will be classified as dangerous.
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Depending on the control method, this information is taken into account by the on-board computer to form the control corresponding to the current situation, or recommendations are developed for the operator to make decisions.
5 Conclusions 1. Mathematical models of atmospheric influences of the external environment on a group of UAVs based on the mathematical apparatus of fuzzy sets have been built. With their help, the values of the probability of damage to a group of UAVs under various conditions of atmospheric influences of the external environment were obtained. 2. Fuzzy qualitative estimates can significantly expand the traditional methods of mathematical modeling that require accurate information about the input quantities. The use of this model makes it possible to estimate the probability of damage to a group of UAVs when the outcomes of alternatives are not known exactly and the probabilities of their occurrence are estimated using membership functions. 3. Using the proposed models, the values of the probability of damage to the group of UAVs as a result of atmospheric influences of the external environment are determined. Acknowledgements The reported study was funded by RFBR according to the research project № 19-01-00357.
References 1. Jordan J (2021) The future of unmanned combat aerial vehicles: an analysis using the Three Horizons framework. Futures 134:102848 2. Jiang Y, Wu Q et al (2021) A diversified group teaching optimization algorithm with segmentbased fitness strategy for unmanned aerial vehicle route planning. Expert Syst Appl 185:115690 3. Cui L et al (2021) Adaptive super-twisting trajectory tracking control for an unmanned aerial vehicle under gust winds. Aerosp Sci Technol 115:106833 4. Yu Z et al (2021) Fractional order PID-based adaptive fault-tolerant cooperative control of networked unmanned aerial vehicles against actuator faults and wind effects with hardwarein-the-loop experimental validation. Control Eng Pract 114:104861 5. Wang J et al (2017) Modeling of BN lifetime prediction of a system based on integrated multi-level information. Sensors 17:2123. https://doi.org/10.3390/s17092123 6. Lin X et al (2021) Trajectory planning for unmanned aerial vehicles in complicated urban environments: a control network approach. Transp Res Part C 128:103120 7. Gao Y, Li D (2019) Consensus evaluation method of multi-ground-target threat for unmanned aerial vehicle swarm based on heterogeneous group decision making. Comput Electr Eng 74:223–232 8. Wang L et al (2021) Unmanned aerial vehicle swarm mission reliability modeling and evaluation method oriented to systematic and networked mission. Chin J Aeronaut 34(2):466–478
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9. Biradar Ash (2014) Wind estimation and effects of wind on waypoint navigation of UAVs. A thesis presented in partial fulfillment of the requirements for the degree master of science. Arizona State University 10. Stojcsics D, Molnar A (2013) Autonomous takeoff and landing control for small size unmanned aerial vehicles. Comput Inform 32:1117–1130 11. Sele M et al (2012) Wind corrections in flight path planning. Int J Adv Robot Syst 12. Langelaan JW, et al (2010) Wind field estimation for small unmanned aerial vehicles. In: AIAA guidance, navigation and control conference, Toronto, Canada. American Institute of Aeronautics and Astronautics. Paper 2010-8177 13. Beard RW, McLain TW (2012) Small unmanned aircraft: theory and practice. Princeton University Press, Woodstock, p 300 14. Liu C, Chen WH (2016) Disturbance rejection flight control for small fixed-wing unmanned aerial vehicles. J Guid Control Dyn 2810–2819 15. Kuznetsov IE et al (2018) The mathematical model of characteristics of the convective unstable atmosphere taking into account microphysical processes in clouds. J Phys Conf Ser Electron Edn 012170. https://doi.org/10.1088/1742-6596/1096/1/012170 16. Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353 17. Wang LZ, Lu DW, Zhang Y et al (2018) A complex network theory based modeling framework for unmanned aerial vehicle swarms. Sensors 18(10):1–24 18. Piegat A (2001) Fuzzy modeling and control. Springer 19. Pathinathan T, Ponnivalavan K (2015) Diamond fuzzy numbers. J Fuzzy Set Valued An 1:36–44 20. Pathinathan T, Ponnivalavan K (2015) Reverse order triangular, trapezoidal and pentagonal fuzzy numbers. Ann Pure Appl Math 9(1):107–117 21. Pathinathan T, Mike Dison E (2018) Similarity measures of pentagonal fuzzy numbers. Int J Pure Appl Math 119(9):165–175 22. Kaufmann A (1975) Introduction to the theory of fuzzy sets: fundamental theoretical elements, vol 1. Academic Press, New York 23. Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with fuzzy logic controller. Int J Man-Machine Stud 7(1):1–13
Reinforcement of the Railway Roadbed with Soil-Concrete for the Passage of Heavy Rolling Stock Sergey Kosenko , Sergey Shkurnikov , Gennadiy Akkerman , and Sergey Akimov
Abstract The purpose of the work is a comprehensive study of the influence of the structural reinforcement of the main platform with a soil-concrete layer on the operability of the roadbed under operating conditions of heavy rolling stock. The graphs of vertical stresses in the roadbed, the coefficients of the stability reserve of high embankments from the impact of heavy rolling stock with axial loads up to 294 kN/axis, the graphs of freezing–thawing of the earthen cavity before and after strengthening it with a soil-concrete layer are obtained. The results of the study of the stress–strain state of railway path models showed that the values of vertical stresses in the models before and after reinforcement with a soil-concrete layer differ in the range of 5–7%. The soil-concrete layer contributes to an increase in the bearing capacity of the main platform by more than 7 times. The vertical stresses in the area of the soil-concrete layer are on average 15% lower than in the models of the path without reinforcement. Strengthening of the main platform of the roadbed with a soil-concrete layer increases the stability of the embankment slopes by 6.5–7.4%. The presence of a soil-concrete layer contributes to a slight increase in the depth of freezing and at the same time reduces the maximum possible calculated height of frost heaving up to 27%. Keywords Railway path · Roadbed · Heavy train traffic · Soil-concrete layer · Recycling
S. Kosenko (B) · S. Akimov Siberian Transport University, Dusi Kovalchuk 191, Novosibirsk 630049, Russia e-mail: [email protected] S. Shkurnikov Emperor Alexander I St. Petersburg State Transport University, 9 Moskovskiy Avenue, St. Petersburg 190031, Russia G. Akkerman Ural State University of Railway Transport, Kolmogorov Street 66, Yekaterinburg 620034, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_3
29
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S. Kosenko et al.
1 Introduction The railway path and the rolling stock passing through it are a single mechanical system. The forces transmitted from the wheels of the rolling stock to the rails [1] affect various elements of the path, including the roadbed. There are stresses, elastic deformations and vibrations [2]. Many factors have a significant impact on the working condition of the roadbed [3]. The main ones include the design of the upper structure of the path, the type of rolling stock, their condition, as well as operational factors (axial loads of cars, traffic speeds, weight and length of trains). Currently, a concept for the development of a heavy train traffic polygon on the railway network of the Russian Federation with a length of 13.8 thousand km has been developed [4–6]. Increasing the weight standards of trains and axial loads is a priority direction that allows to ensure promising volumes of cargo transportation [7]. More intensive vibrodynamic loading of the roadbed raises a number of new and complex questions [8]. The experience of operating many railways under conditions of constant increase in axial loads has shown a steady increase in the number of sections with deformations of the roadbed (primarily the main platform) [7, 9, 10]. In addition, the increased dynamic effects of the rolling stock under certain conditions lead to the appearance of depths, bulging of the soil, as well as to the movements of the embankment slopes. It is proposed to strengthen the main platform of the roadbed by installing a soil-concrete layer [11, 12] on its surface using the technology of cold soil regeneration (recycling). Cold recycling is a technology for strengthening soils with various binders by preliminary milling and mixing of local soil on the road. When strengthening weak soils, a wide range of various additives (stabilizers) and binders are used, from industrial to production waste [13–15]. At the same time, the soils treated with a strengthening composition acquire high strength characteristics [16], hydrophobicity, their crack resistance and frost resistance increase [15], the heaving properties decrease or disappear [17]. The purpose of the work is to study of the influence of the structural reinforcement of the main platform with a soil-concrete layer on the operability of the roadbed under operating conditions of heavy rolling stock.
2 Research Method The studies were carried out according to the algorithm shown in Fig. 1. The research was carried out on numerical models. The calculated characteristics of the elements and layers of the models are given in Table 1. The stress state studies were performed by the finite element method in the Midas GTS NX software package. For this part of the study, three-dimensional models of a single-track railway path were created. The models consisted of the upper structure of the path of a standard structure and roadbed with a height of 3.0 m.
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31
Creating path models. Setting the characteristics of the elements and layers of the path models (γ, ρ, E, ν, φ, с, λ, w). Determination and assignment of loads from rolling stock
Calculations of the stress-strain state
σ ≤ [σ0]; τ ≤ [τ];
NO
YES Calculations of the stability of embankments. Definition Kdyn
NO
Kdyn ≥ [K] YES Heat engineering calculations. Definition hheave
NO
hheave ≤ [hheave]
YES Assignment of the required thickness of the soil-concrete layer
Fig. 1 Algorithm of complex studies of the influence of the soil-concrete layer on the operability of the roadbed under conditions of increased loads Table 1 The characteristics of the path elements taken for calculating the stress state Name of the layer
γ, kN/m3
E elas , MPa
c, MPa
ϕ, degrees
ν
Rails
76.52
210,000
–
–
0.30
Sleepers
24.53
36,000
–
–
0.20
Crushed stone ballast
17.56
150
0.02
45.0
0.30
Sand cushion
19.62
110
0.05
37.0
0.30
Soil-concrete layer
19.81
248
0.30
53.7
0.20
Roadbed: heavy loam of semi-solid consistency
19.23
30
0.028
19.4
0.30
Base: heavy loam of a refractory consistency
19.26
20
0.025
21.0
0.30
Note γ—is the specific gravity of the soil; E elas —is the modulus of elasticity; c—is the specific adhesion; ϕ—is the angle of internal friction; ν—is the Poisson’s ratio
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To assess the impact on the path of freight cars with increased axial loads, freight cars with an axial load of 245, 265 and 294 kN were accepted. The calculated load transmitted by heavy freight cars is the dynamic maximum probable value and was determined by the formula Pmax = Pavg. + λS,
(1)
where Pavg. and S—are the average value and the average square deviation of the design load, respectively; λ—a normalizing multiplier that determines the probability of the appearance of the maximum vertical load (assumed to be equal to 2.5). The obtained values of the maximum probable vertical loads are shown in Table 2, the scheme of action of the loads is shown in Fig. 2. The assessment of the impact of rolling stock on the roadbed is determined by the condition of ensuring the bearing capacity of the soil of the roadbed under the main platform. At the same time, the working area is taken as a zone of the roadbed with a depth of up to 2 m from the surface of the main platform. The load-bearing capacity of the main platform is checked by comparing the calculated normal σ z and tangential τ stresses with the permissible [σ0 ] and [τ ] ones according to the formulas: σz ≤ [σ0 ];
(2)
τ ≤ [τ ]
(3)
Table 2 Values of the most probable vertical loads from freight cars Speed, km/h
The value of the average and maximum vertical loads of the wheel on the rail, N, from cars with axial loads 245 kN
90
265 kN
294 kN
Pavg.
Pmax
Pavg.
Pmax
Pavg.
Pmax
160,668
189,136
164,745
194,451
183,383
216,176
1.85 m
Pavg
Pmax
x z
Fig. 2 The scheme of action of loads
1.85 m
Reinforcement of the Railway Roadbed with Soil-Concrete …
33
Studies of the stability of the roadbed were also carried out by the finite element method in the PLAXIS software package. The essence of the method is to determine the coefficient of safety K st , the calculated structure (in this case, the embankment). The resistance of the soil to shear is estimated by the coefficient of stability of the embankment at the dynamic state of the soil K dyn , which must be at least the permissible value [K], regulated by the requirements K dyn =
K st ≥ [K ], adyn
(4)
where adyn —dynamics coefficient. The dynamics coefficients depend on the height of the embankment, the intensity of the train load and the type of soil. The standard coefficient of stability of the embankment of a specially loaded railway line is 1.25. For this part of the research, flat models of embankments of a single-track railway path with a height of 10–16 m were created. The width of the main platform of the roadbed for a single-track section of the railway was assumed to be 7.6 m. The upper 6 m of the height of the embankments were planned with slopes with a slope of 1:1.5, the lower part—with slopes with a slope of 1:1.75. The pressures on the main platform in the form of rectangular strip loads from the rolling stock and the upper structure of the path are accepted as loads. The train load diagram is assumed to be rectangular, 2.7 m wide and 90 kPa. Such a load is assumed based on the operating stresses at the level of the main platform, determined for the calculation unit of the rolling stock (a four-axle freight car with an axle load of 294 kN). The diagram of the load from the upper structure of the path is taken of a rectangular shape with a width of 4.6 m and a value of 17 kPa. The study of the influence of the soil-concrete layer on the heat and humidity regime of the roadbed was carried out in the “Freeze-1” software package. The basis of the thermal engineering calculation is the solution of the problem of determining the one-dimensional non-stationary temperature field of the roadbed with obtaining estimates of the depth of seasonal freezing and the zone of intense frost heaving of the soil. In this case, a closed ground freezing system is adopted. The criterion for the admissibility of deformations of the roadbed in the winter period is the condition h fr. heave ≤ [h fr. heave ],
(5)
where hfr ·heave —the maximum possible height of uniform frost heaving of the soil of the roadbed, mm; [hfr ·heave ]—the permissible value of the height of uniform frost heaving, determined by the category of the road, mm. For the conditions of heavy train traffic, the permissible value of the height of uniform frost heaving is 15 mm. In the studies, two basic versions of the roadbed, composed of light and heavy loam, were taken. Both variants of the soil have a tough-plastic consistency. Sub-ballast layers obtained by regeneration of the initial soil were applied to the basic variants.
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S. Kosenko et al.
3 Research Results As a result of the study of the stress–strain state of railway path models, graphs of vertical stresses were obtained at the level of the main platform of the roadbed (Fig. 3) and at the depth under the most loaded sleeper directly under the car wheel (Fig. 4). The values of calculated and permissible tangential stresses were obtained (Table 3). As a result of the performed calculations of the stability of railway embankments with a height of 10–16 m, graphs of the dependences of the change in the coefficient of stability of the slope parts of the embankments before and after the reinforcement of the main platform with a soil-concrete layer are constructed (Fig. 5). As a result of thermal engineering calculations for the climatic conditions of the south of Western Siberia, graphs of the depth of freezing–thawing of the roadbed were obtained (Figs. 6 and 7). Figure 6 shows the graphs of freezing–thawing of models with a typical design of the roadbed (without a protective layer). The level of the main platform is shown by a thick (purple) line. The blue line shows the graph of the freezing of the ballast layer and the soil of the roadbed in time (isotherm T = T phase ), the red line shows the thawing graph (isotherm T = 0). The shaded area in turquoise color characterizes the zone of intense frost heaving, the depth of which is designated as H heave , the depth of freezing is designated as H phase.
-3.0
-2.0
Distance from the track axis, m -1.0 0.0 1.0 0.00
2.0
3.0
0.01
Vertical stresses, kPa
0.02
0.03 0.04 0.05
0.06 0.07 0.08
0.09 0.10 without soil-conc.
soil-conc. 0.2 m
soil-conc. 0.4 m
soil-conc. 0.5 m
soil-conc. 0.3 m
Fig. 3 Vertical stresses in the level of the main platform of the roadbed from the impact of a freight car with an axial load of 294 kN/axis
Reinforcement of the Railway Roadbed with Soil-Concrete …
35
-0.09
-0.08
-0.07
-0.06
-0.05
-0.04
-0.03
-0.02 -0.6 -0.8 -1.0 -1.2 -1.4 -1.6 -1.8 -2.0 -2.2 -2.4 -2.6 -2.8 -3.0
Distance from the sleeper, m
Vertical stresses, MPa -0.10
σy (265 kN/axle) σy (245 kN/axle, soil-conc. σy (294 kN/axle, soil-conc.
σy (245 kN/axle) σy (294 kN/axle) σy (265 kN/axle, soil-conc.
Fig. 4 Vertical stresses under the sole of the busiest sleeper, depending on the depth Table 3 The obtained values of the calculated and permissible tangential stresses Depth from the sleeper, m
Tangential stresses τ, kPa
Bearing capacity of the initial soil [τ], kPa
Bearing capacity of the roadbed with ground concrete [τ], kPa
0.60
−40.7
−59.4
−421.4
0.70
−48.5
−56.5
−410.2
0.80
−47.1
−52.7
−395.5
0.90
−43.1
−50.4
−386.7
0.10
−26.4
−49.5
−49.5
0.12
−23.8
−48.9
−48.9
0.13
−23.0
−48.2
−48.2
0.14
−22.4
−47.7
−47.7
0.16
−21.7
−47.2
−47.2
0.17
−21.1
−46.7
−46.7
0.19
−20.5
−46.2
−46.2
0.20
−19.9
−45.9
−45.9
36
S. Kosenko et al. 1.35
1.34
Stability coefficient
1.30
1.31
1.32
1.30 1.25 1.25
Kdyn =[1. 25]
1.22
1.24 1.20 Theembenkment slope stability is ensuredKdyn ≥ [1.25]
Theembenkment slope stability is unensuredKdyn < [1.25]
1.15 10
12
14 Embankment height, m without soil-concrete layer with soil-concrete layer
16
Fig. 5 Dependence of the change in the coefficient of stability margin when the main platform is reinforced with a soil-concrete layer
а) X XI XII I
II III IV V
b) VI VII VIII IX
h fr. heave=18 mm
decades
X XI XII I
II
III IV V
h fr. heave=26 mm
VI VII VIII IX decades
loam
Tfr. heave ≤ -0.8 ºC
Tfr. heave ≤ -1.1 ºC
loam
Tphase = -0.5 ºС 2.0 m
Tphase = -0.8 ºС 2.0 m Hfr. heave =1.32 m Hphase=1.40 m
Hfr. heave =1.20 m Hphase=1.28 m
Fig. 6 The graph of freezing–thawing of a typical construction of a loam roadbed: a light (I p = 8%, W = 20%); b heavy (I p = 12%, W = 25%)
4 Results Discussion The results of the study of the stress–strain state of railway path models showed that the vertical stresses on the main platform of the roadbed are equal to those allowed when exposed to rolling stock with an axial load of 265 kN/axis and exceed them when exposed to rolling stock with a load of 294 kN/axis (Figs. 3 and 4). The values of vertical stresses in the models before and after reinforcement with a soil-concrete layer differ in the range from 5 to 7% (Fig. 3). Vertical stresses in the area of the soil-concrete layer are on average 15% lower than in the models of the path without reinforcement (Fig. 4). The obtained values of tangential stresses showed that the use of a soil-concrete layer makes it possible to increase the bearing capacity of the
Reinforcement of the Railway Roadbed with Soil-Concrete …
37
a) X XI XII I
II
III IV V
hfr. heave=13 mm
b) VI VII VIII IX decades
II III IV V
hfr. heave=19 mm
VI VII VIII IX decades
soil-concrete
soil-concrete
loam
loam
Tphase = -0.8 ºС
Tphase = -0.5 ºС
3.0 m
X XI XII I
Hfr. heave =1.36 m Hphase=1.44 m
3.0 m
Hfr. heave =1.24 m Hphase=1.32 m
Fig. 7 The graph of freezing–thawing of models with a soil-concrete layer with a thickness of 0.4 m and the soil of the earth bed made of loam: a light (I p = 8%, W = 20%); b heavy (I p = 12%, W = 25%)
main platform of roadbed several times. In this study, the load-bearing capacity was increased by more than 7 times (Table 3). The obtained calculation results (Fig. 5) show that the reinforcement of the main platform of the roadbed with a soil-concrete layer thick contributes to the stability of the embankment slopes with a height of 12–16 m. The values of the coefficients of the stability margin of embankments with a height of 12–16 m increased by 6.5–7.4%. Calculations have shown that the obtained values of the coefficients of the stability margin of embankments with a height of 12 m or more are lower than the standard value [1.25] for railway lines with heavy freight trains. From the calculated data obtained, it is obvious that the reinforcement of the main platform of the roadbed with a soil-concrete layer has a concomitant positive effect on the stability of the embankment. The obtained results of thermal engineering calculations showed the following. In the model with an roadbed of a typical design made of light loam (I p = 8%, W = 20%), the depth of freezing of the soil under the main platform was 1.40 m. The zone of intense heaving of soils, determined by the depth of the H heave , was 1.32 m. At the same time, the maximum possible calculated height of the heave hheave , reaches 18 mm (Fig. 6). In the second model with roadbed of a typical design made of heavy loam (I p = 12%, W = 25%), the maximum depth of frost heaving of the H phase was 1.28 m, the zone of intense frost heaving was H heave = 1.20 m, and the height of frost heaving was hheave = 26 mm (Figs. 3 and 7). In models with a reinforced roadbed with a soil-concrete layer (Fig. 7), there is a slight increase in the depth of freezing and the zone of intense frost heaving (4 cm). However, the maximum possible calculated height of frost heaving decreased by 27% and amounted to 13 mm in the model of roadbed made of light loam, 19 mm from heavy loam. The lower values of the maximum possible height of frost heaving in models
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with a soil-concrete layer (with relatively identical values of H phase and H heave ) are explained by a much lower pre-winter humidity of the soil-concrete layer (W = 5%) due to its hydrophobic properties. For the model of a path made of light loam with the presence of a soil-concrete layer, the criterion of the admissibility of deformations of the roadbed in winter is fulfilled (13 ≤ [15]). For a model of a path made of heavy loam with a soil-concrete layer, it will be necessary to develop anti-heaving measures (for example, a coating made of expanded polystyrene).
5 Conclusion The obtained results of the influence of the soil-concrete layer on the operability of the roadbed allow us to recommend its use as a solution to the problem of increasing the bearing capacity of the soils of the main platform of the roadbed. Reinforcement of the roadbed with a soil-concrete layer must first be provided for on railway lines with heavy freight traffic. Acknowledgements This study was carried out with the financial support of “Russian Railways” JSC grant project No 3704995 dated 10.12.2019. “Anti-deformation strengthening of the main platform of the railway roadbed by the method of cold regeneration (recycling) in the areas of heavy trains traffic”.
References 1. Kosenko S, Akimov S (2017) Performance characteristics of differentially quenched rails. Mag Civil Eng 75(7):94–105. https://doi.org/10.18720/MCE.75.9 2. Manakov A, Kolarzh S, Mashkov A (2018) Organization of railway track tamping work using the software and hardware complex SMTC. Matec Web Conf 239:04002. https://doi.org/10. 1051/matecconf/201823904002 3. Le THM, Lee S-H, Park D-W (2020) Evaluation on full-scale testbed performance of cement asphalt mortar for ballasted track stabilization. Constr Build Mater 254:119249. https://doi. org/10.1016/j.conbuildmat.2020.119249 4. Kakhrimanova D, Belozerov V, Kapustina N, Pokrovskaya O, Orekhov S (2019) “Silk Road”: new projects and opportunities for revival. IOP Conf Ser Mater Sci Eng 698:066058. https:// doi.org/10.1088/1757-899X/698/6/066058 5. Anisimov V, Bogdanova L, Morozova O, Shkurnikov S, Nesterova N (2020) Multimodal transport network of the far eastern federal district of Russia. Lect Notes Civ Eng 130:459–468. https://doi.org/10.1007/978-981-33-6208-6_45 6. Kurenkov P, Pokrovskaya O, Anastasov M, Sokolov M, Bochkov A (2019) Study of the current state of the transport infrastructure of road and rail transport of the Russian Federation. IOP Conf Ser Mater Sci Eng 698:066064. https://doi.org/10.1088/1757-899X/698/6/066064 7. Zhao X, Yang J, An B, Liu C, Cao Y, Wen Z, Jin X (2016) Determination of dynamic amplification factors for heavy haul railways. J Rail Rapid Transit 232(2):514–528. https://doi.org/ 10.1177/0954409716679203
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8. Nie R, Leng W, Yang Q, Chen YF, Xu F (2016) Comparison and evaluation of railway subgrade quality detection methods. J Rail and Rapid Transit 232(2):356–368. https://doi.org/10.1177/ 0954409716671551 9. Kolos A, Romanov A, Shekhtman E, Konon A, Kiselev A (2020) Bearing capacity of high embankment clay soils in terms of heavy axle load operation. In: Lecture notes in civil engineering, vol 49, pp 403–412. https://doi.org/10.1007/978-981-15-0450-1_42 10. Blazhko L, Shtykov V, Chernyaev E (2017) Enhancement of subgrade’s bearing capacity in low water permeable (clay) soils. Proc Eng 189:710–715. https://doi.org/10.1016/j.proeng. 2017.05.112 11. Akimov S, Kosenko S, Bogdanovich S (2020) Stability of the supporting subgrade on the tracks with heavy train movement. Adv Intell Syst Comput 1116:228–236. https://doi.org/10.1007/ 978-3-030-37919-3_22 12. Akimov S, Kosenko S (2021) Stress state of roadbed reinforced with soil-concrete layer under the impact of heavy-tonnage trains. Transp Res Procedia 54:495–502. https://doi.org/10.1016/ j.trpro.2021.02.100 13. Rimal S, Poudel RK, Gautam D (2019) Experimental study on properties of natura soils treated with cement kiln dust. Case Stud Constr Mater 10:e00223. https://doi.org/10.1016/j.cscm.2019. e00223 14. Ahmed A (2013) Recycled bassanite for enhancing the stability of poor subgrades clay soil in road construction projects. Constr Build Mater 48:151–159. https://doi.org/10.1016/j.conbui ldmat.2013.05.089 15. Saygili A, Dayan M (2019) Freeze-thaw behavior of lime stabilized clay reinforced with silica fume and synthetic fibers. Cold Reg Sci Technol 161:107–114. https://doi.org/10.1016/j.coldre gions.2019.03.010 16. Celauroa B, Bevilacqua A, Lo Boscob D, Celauro C (2012) Design procedures for soil-lime stabilization for road and railway embankments. part 1 - review of design methods. Procedia Soc Behav Sci 53:754–763. https://doi.org/10.1016/j.sbspro.2012.09.925 17. Behnood A (2018) Soil and clay stabilization with calcium-and non-calcium-based additives: a state-of-the-art review of challenges, approaches and techniques. Transp Geotech 17, Part A:14–32. https://doi.org/10.1016/j.trgeo.2018.08.002
Estimation of the Resource of Spiroid Transmissions by the Condition Maximum Wear and Tear Alexander Zaitsev
Abstract The paper provides a brief description of the reasons for the failure of machine drives based on meshing, as well as worm gears, as a result of their operation and contact loads on the active surfaces of gear wheels, which leads to malfunctions, breakdowns, failures in the form of wear, scuffing, abrasion. The existing method for calculating endurance, taking into account the variability of loads and the number of cycles of their action on contact endurance and endurance of cogs in bending, used in strength calculations of spur and helical cylindrical gears, is described, and an analysis of methods for assessing the resource of gears is presented. The necessity of creating a method for estimating the resource according to the condition of the maximum wear of spiroid gears, taking into account the stepped mode of action of loads on the output shaft of the gearbox, is justified. The presented method for predicting spiroid gears by wear makes it possible to take into account the stepwise loading mode of the drives of lifting and transport machines. While using the experimentally obtained dependence of the wear intensity of the cogs of the spiroid wheel on the values of the torque on the output shaft of the spiroid gearbox, it is possible to calculate the resource of the spiroid gear taking into account the equivalent torque. Keywords Wear · Wear intensity · Spiroid gear · Equivalent torque
1 Introduction The destruction of the active surfaces of the links in the form of wear, scuffing on the side surfaces of the cogs and fractures formed during the operation of the mechanisms of lifting, construction, road machines with constant or variable loads during the time in the meshing of cog gears leads to premature failure of the mechanisms of this type of machines [1]. For cog gears, the main cause of failure is wear and jamming of the cogs (Fig. 1). A. Zaitsev (B) Siberian Transport University, Dusi Kovalchuk 191, Novosibirsk 630049, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_4
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Fig. 1 Cogs of spiroid wheels: a cog wear; b teasing on the surfaces of the cogs
To calculate the fatigue strength of straight-cogs and oblique cylindrical gears with steel wheels, according to GOST 21,354-87 (ST SEV 5744-86), a graph is used (Fig. 2) that takes into account the effect of the maximum load Ft(1) on contact endurance and on the endurance of the cogs during bending. A feature of the operation of the drives of lifting and transport machines is a stepby-step (variable) loading mode with a change in the values of the torques on the output shaft of the gearbox for the duration of the working cycle time. The working conditions of the machines themselves under these conditions lead to a change in the circumferential speed and loads, as well as to an increase in contact voltage, which results in the destruction of the cogs surface of the contacting links and wear [2].
Fig. 2 The graph describing the mode of operation of the cog pair
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Table 1 presents an analysis of methods for estimating the service life of cog gears, as well as the results of experimental studies conducted by researchers in the field of meshing gears. Table 1 Analysis of methods for estimating the service life of cog gears [3–8] Source number
Name of cog gear and elements
Evaluation criterion
Result
[3]
Cog straight cylindrical gear
Wear limit [h]
The service life of the cog gear using typical values of its parameters and loading conditions was 3453 h. When choosing more wear-resistant materials of the gear teeth and wheels with a wear rate of 10–11 . The resource was 3,453,000 h
Cog cylindrical bevel gear
Wear limit [h]
With the experimentally established value of the wear rate of the gear and wheel cogs Jh1 = Jh2 = 4.9 · 10–8 , the service life in accordance with the calculated formula was 1375 h
Slip-on screw-nut gear
Wear limit [h]
The service life of the gear is equal to: at σH = 1 MPa N = 106,376 working strokes; at σH = 5 MPa N = 5000 working strokes; with σH = 10 MPa N = 1341 working stroke
[4]
[5, 6]
Cog gear mechanisms of Wear limit [h] electro-mechanical drives
The experimental value of the wear rate for cog wheels made of steel 30HGSA (with lubrication) for the steady-state wear mode at 200 h of testing was 0.8 · 10–8 …20 · 10–8
Conical orthogonal spur gear
With the experimental value of the wear rate J h1 = J h2 = 5.0 · 10–8. The service life of the cog gear is 765 h (assuming that the normal load along the line of engagement is transmitted by one pair of cogs)
Wear limit [h]
(continued)
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Table 1 (continued) Source number
Name of cog gear and elements
Evaluation criterion
Result
Worm-gear
Wear limit [h]
For gears with worm wheels made of tin bronze Br.06F1.5 HB2 = 100HB and polished worms made of case-hardened steel 18HGT HRC1 = 57 … 64HRC, using a lubricant: mineral transmission oil TM6-18 (foreign analogue SAE85W_90) the experimental value of the wear rate of the worm wheel cogs was 0.5 · 10–9 …10 · 10–9
[7]
Worm-gear
Wear rate vw Weight loss m
Oils with Kluber additives, the wear rate was 0.0001… 0.012 μm/h, the weight loss was 0.0001… 1.25 g; for oils based on polyglucol, the wear rate was 0.055 … 2.1 μm/h, the weight loss was 1.25 … 21.06 g for 300 h of testing
[8]
Cog gear of aviation and maritime communication systems
Wear limit [h]
It follows from Table 1 that the main criterion for evaluating the resource of cog gears is the maximum permissible wear [h], and the parameter that particularly affects the calculation of the resource is the intensity of wear Jh of the gear cogs and the wheel. The table also shows that to increase the service life of meshing gears, certain technologies are used to strengthen the surface layers of the gear and wheel cogs, as well as the use of additives to gear oils on a mineral basis. Along with worm gears, spiroid gears, which belong to the worm type, have found application in various fields of technology (Fig. 3 [9, 10]). They have become widely used in the drives of mechanisms of lifting machines and transporting equipment operating both under constant loading mode and under modes with changing values of torques. For a significant number of drives of mechanisms of lifting, construction and road machines, the operation of which is carried out under conditions of step loading on the working equipment during the cycle, the creation of a method for estimating the resource of the spiroid gear by wear, that takes into account the variability of the action of the torque values at the output link of the gearbox, is an urgent task.
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Fig. 3 Worm and spiroid gear wheel
2 Research Methods Figure 4 shows the experimental dependences of the intensity of wear J hcp and of the cogs resource L of the spiroid wheel on the values of the torque on the output shaft of the gearbox T i of the traction winch of the laying crane for replacing the elements of the railway track. The traction winch is characterized by heavy operating modes, in which the useful resistances on the output shaft of the spiroid gearbox and the duration of their action during the operation cycle significantly change. This is due to changes in the conditions and organization of work on pulling packages of links of the rail-sleeper grid, in particular, from the slope of the track, the presence of curves and straight sections, as well as the type of sleepers. Experimental studies were carried out on the stand of the disc-roller analogy method [11]. The stand allows to simulate the following necessary parameters of the spiroid meshing in a wide range: sliding speed, contact line length, specific load, reduced radius of curvature, contact voltage, operating properties and parameters of the lubricating oil, the temperature of the lubricating oil, the materials of the pair links, the hardness of the surfaces of the worm turn and the wheel cog, the state parameters of the surfaces of the worm turn and the wheel cog [12]. These dependences J hcp = F(T i ) and L = F(T i ) allow finding the wear intensity of the cog of the spiroid wheel for the corresponding value of the equivalent torque T HE , as well as determining the resource of the established schedule of variable loading to the shaft of the traction winch gearbox.
3 The Results of the Study Calculation of the resource of the spiroid gearbox in the winch drive for pulling packages of rail-sleeper grid links.
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Fig. 4 Experimental graphs of the dependence of the wear intensity and the resource of the spiroid wheel on the values of the torque on the output shaft of the gearbox of the RS-160-25 traction winch. Used transmission oil CAT TDTO SAE 30 API GL-3 (TM-3-9 GOST 17,479.2-85). Worm Material: Steel 45; wheel material: bronze BrA9ZH4. Oil temperature in the gearbox Tm = 70 °C
1. Equivalent torque on the output shaft of the spiroid gearbox:
TH E
n Ti 3 Ni 3 = Tmax · , Tmax N i=1
(1)
where T max = 3280 N m is the maximum operating torque; T i /T max —is the relative value of the torque at the i-th stage of loading the output shaft of the gearbox (see Fig. 5); N i /N —is the relative number of cycles of the relative value of the torque at the i-th stage of loading the output shaft of the gearbox (see Fig. 5); n—is the number of loading stages of the output shaft of the gearbox. TH E = 3280 ·
3
13 · 0.226 + 0.6673 · 0.487 + 0.3333 · 0.287 = 2378 N m
2. Specific design force in meshing corresponding to the equivalent torque T HE : wH E =
TH E w H Emax , Tmax
(2)
where wHEmax = 389 N/mm—is the specific design force in the meshing corresponding to the maximum working torque T max . wH E =
2378 · 389 = 282.025 N/mm 3280
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Fig. 5 Graph of step loading of the output shaft of the spiroid gearbox of the traction winch
3. The maximum permissible wear of the cogs of the spiroid wheel for machines of this type is calculated: [h 2 ] = 0.125 · 3.14 · 8 · cos 8◦ = 3.11mm
(3)
where m = 8 mm—is the calculated axial modulus of the worm turn; αxR = 8° —is the right dividing axial angle of the profile of the worm turns. [h 2 ] = 0.125 · 3.14 · 8 · cos 8◦ = 3.11mm 4. Predicted resource of the spiroid gearbox [12, 13]: L=
[h 2 ]
SY 2 60 · 2.25 · J H E w H E η(ρr ed1,2 ) R VVFY n2i 2
,
(4)
where [h2 ] = 3.11 mm—the maximum permissible wear of the cogs of the spiroid wheel; J HE = 1.6 · 10–8 —an experimentally determined value of the wear intensity of the material of the spiroid wheel corresponding to the equivalent torque T HE (determined according to the graph of Fig. 4); η = 1.4 · 10–5 mm2 /N— the elastic constant of the contacting links; (ρred12 )R = 91.2 mm—the reduced radius of curvature at the calculated point of contact of the cogs of the wheel for the right dividing axial angle of the profile of the turns; n2 = 37 rpm—rated speed of the output shaft; V SY2 = 4037 mm/s—sliding speed at the calculated points of the profile of the cogs of the wheel; V FY2 = 962 mm/s—the circumferential speed at the calculated points of the profile of the wheel cogs; i = 1—the number of pairs of meshing with the gear wheel under consideration.
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L=
3.11 √ 60 · 2.25 · 1.6 · 10 282.025 · 1.4 · 10−5 · 91.2 · −8
4037 962
· 37
= 15453 h
4 Discussion of the Results 1. The experimental dependence of the wear intensity J h of the spiroid wheel cogs on the values of the torque on the output shaft of the spiroid gearbox T i , obtained using the results of a study on the stand of the disc-roller analogy method, allows determining the value of the wear intensity J HE corresponding to the equivalent torque T HE and estimating the resource of the spiroid gearbox under the conditions of a step loading mode. 2. An algorithm for estimating the resource of a spiroid gear according to the condition of the maximum wear of the cog of a spiroid wheel is developed on the basis of the experimental dependence J h = F(T i ) taking into account the equivalent torque. The prospect of further development of the study may be: the study of the effect of the wear intensity on the service life of the spiroid gear, depending on the load on the output shaft of the spiroid gearbox with various combinations of structural, lubricants and temperature operating modes.
References 1. Yunin PA, Drozdov YN (2018) How to distinguish between opposite faces of an a-plane sapphire wafer. J Appl Crystallogr 51(2):549–551. https://doi.org/10.1107/S16005767180 01383 2. Zaitsev A (2019) Calculation of the resource of spiroid transmissions from wear in the step of loading mode. IOP Conf Ser Earth Environ Sci 403:012221. https://doi.org/10.1088/17551315/403/1/012221 3. Kuksenova LI, Polyakov SA, Alekseeva MS, Rubtsov SV (2019) Increasing the service life of gears based on the choice of technologies for hardening the working surfaces of the teeth. Bull Sci Tech Develop 3:24–36. https://doi.org/10.18411/vntr2019-139-3 4. Polyakov SA, Kuleshova EM, Kuksenova LI, Medovshchikov AV (2020) Evaluation of the influence of lubricant quality on dynamic performance and resource of involute gears. IOP Conf Ser Mater Sci Eng 996:012020. https://doi.org/10.1088/1757-899X/996/1/012020 5. Andrienko LA, Vyaznikov VA (2011) Operation life of worm-gears according to wear criterion. BMSTU J Mech Eng 4:3–6. https://doi.org/10.18698/0536-1044-2011-4-3-6 6. Polyakov SA, Goncharov SY, Zakharov MN, Lychagin VV (2016) Influence of film-forming lubricants on the adaptability of worm gears. Russ Eng Res 36:93–95. https://doi.org/10.3103/ S1068798X16020179 7. Siebert H (2011) Worm gears-higher energy efficiency and less strain on resources. Int J Sci Eng Res 9(6):103–108 8. Petrov N, Staneva L, Petrov Y, Edrev S (2018) Study on the determination of the technical resources for toothed gear mechanisms of marine and aviation communication systems. Int J Sci Eng Res 9(6):603–610
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9. Goldfarb V, Trubachev E, Pushkareva T, Savelyeva T (2019) Comparative investigation of worm and spiroid gears with cylindrical worms. Mech Mach Sci 73:925–935. https://doi.org/ 10.1007/978-3-030-20131-9_92 10. Trubachev E, Savelyeva T, Pushkareva T (2018) Practice of design and production of worm gears with localized contact. Mech Mach Sci 51:45–72. https://doi.org/10.1007/978-3-31960399-5_16 11. Anferov VN, Kovalenko RK (2018) Load-bearing capacity of spiroid gears of mining machine drives under peak loads. J Min Sci 53(4):686–693. https://doi.org/10.1134/S10627391170 42679 12. Zaitsev A (2020) Resource assessment of spiroid gears under variable loading conditions. E3S Web Conf Key Trends Transp Innov 157:01007. https://doi.org/10.1051/e3sconf/202015 701007 13. Zaitsev AV (2020) Method of calculating of spiroid gear resource by wear at step loading mode. IOP Conf Ser Mater Sci Eng 795:012017. https://doi.org/10.1088/1757-899X/795/1/012017
Principles of Designing Asymmetric Rail Profiles Andrey Ilinykh , Andrey Romanov , and Inna Parahnenko
Abstract The article considers rail head wear mechanisms in curved sections of the railway track. Based on various schemes of interaction between the wheel and the rail, determined by railway track operating conditions, the advantages and disadvantages of various contact schemes are revealed. The necessity of forming asymmetric rails profiles is indicated and the concept of conformal wheel-rail contact is considered. The conformal contact occurs when the running rail fillet and the wheel flange wear down to common profile due to intense flange contact at the curves. Due to the conformal contact, the relative slip expands the contact zone, the specific pressure decreases, meanwhile the rail and wheel profiles, worn to the corresponding configuration, successfully show good performance in terms of fatigue endurance. Thus, it is recommended that the wheel and rail profiles are conformal. Such a profile can be given to wheels and rails during current maintenance; the rails can be tramped or profiled immediately after railing. It is noted that this profile is approximately the same under various conditions of flange contact on different railways. Recommendations are given to reduce the intensity of rail wear in curved track sections based on the formation of asymmetric profiles of inner and outer rail faces. Based on the proposed recommendations for reducing the rail head wear, general principles of designing repair profiles have been developed in order to reduce their defects. The requirements for repair profile design are developed, taking into account the structural and operational characteristics of the railway track. Keywords Rail · Cross-section profile · Asymmetric profile · Wheel-Rail contact · Rail wear A. Ilinykh (B) Siberian Transport University, Dusi Kovalchuk 191, Novosibirsk 630049, Russia e-mail: [email protected] A. Romanov Emperor Alexander I St. Petersburg State Transport University, 9 Moskovskiy Avenue, St. Petersburg 190031, Russian Federation I. Parahnenko Ural State University of Railway Transport, Kolmogorov Street 66, Yekaterinburg 620034, Russian Federation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_5
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1 Introduction In the curved sections of the railway track, due to the complex interaction with the rolling stock wheels, the rail head is subjected not only to physical and mechanical, but also to geometric changes. The smaller the radius of the curve, the more intensely the wheel affects the rail. The main changes in geometry of the rail crosssection profile are due to both wear and plastic deformations such as metal distortion and yielding. The predominance of a particular process of changing the rail shape is determined primarily by its operating conditions. Depending on the rail operating conditions, these changes may be different. The changes in rail shape vary significantly depending on where the rail is located: at a curve of medium, large or small radii. It is also significant if the rail lies on the inner or outer face in the curve. Consequently, the dynamics of changing the rail geometry will be different. To ensure optimal rail-wheel interaction during operation, the geometry of the rail cross-section must be corrected. For this purpose, so-called repair profiles are used [1]. Their shaping can be provided by rail grinding or milling technologies in accordance with the instructions for rail grinding and milling in transit and stationary conditions, approved by JSC “Russian Railways” regulation No. 3185r of 29.12.2014. Notably, universal asymmetric profiles do not exist. It is necessary to design and develop an appropriate special profile for certain operating conditions of the track and its structural features. With the correct designation and development of a specific profile, the rail capacity can be extended up to 60%, which determines the relevance of this task. It is necessary to develop rail profiles for differentiated operating conditions (curves of different radii, track sections with different loads, different rolling stock speeds) based on optimization criteria. The main ones are the following: – optimization of the cross-section geometric characteristics, considering the evolution of rail and wheel damage, in order to reduce the wear rate of the wheel-rail set; – improving the contact interaction of rail and wheel running surfaces with a decrease in contact stresses and rail damage caused by contact-fatigue defects; – timely implementation of technical measures to prevent the development of contact-fatigue defects. The limiting factor in solving this problem is the lack of a unified approach in the design of asymmetric rail profiles. First of all, it is explained by a currently unsolved scientific problem in determining the kinetics of rail profile change in various operating conditions.
Principles of Designing Asymmetric Rail Profiles
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2 Problem Statement During the wheel-rail interaction, the contact does not extend over the entire surface of the wheel and the rail. The geometry of the rail and wheel profiles prevents full contact. The contact is limited to the areas highlighted in Fig. 1, and implies a change in the outlines of the rail and wheel profile [2, 3] during their operation. In this case, a very important aspect is the consequence of these changes, in particular: what rail head outlines they result in, how they affect the distribution of contact loads, and consequently, the deterioration, occurrence and development of contact-fatigue defects. There are models that predict wheel and rail shape changes. These models take into account not only the removal of material due to the impact of friction forces, but also the movement of material along the profile. In accordance with these models [4], the rail and wheel profiles can be functionally divided into the following areas (Fig. 2): area A—the contact between the middle part of the rail head and the wheel rim; area B—the contact between the rail head and flange throat at the base; area C is the contact between the outer wheel and rail zones. To determine the optimal rail head geometry, it is necessary to assess the significance of each presented area in the overall structure of the rail-wheel interaction. To this end, it is necessary to structure the existing scientific and production experience and find out how deterioration processes occur in defined rail head areas with the wear intensity determination in various operating conditions. Based on previous facts, it is possible to predict the most optimal scheme of rail-wheel interaction and determine the optimal wheel and rail contact zones and their sizes.
Fig. 1 Possible wheel-rail contact zones
Fig. 2 Functional contact areas of the rail-wheel system
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3 Theoretical Research Based on the analysis of foreign and domestic research results, it is possible to present a generalized characterization of the areas indicated in Fig. 2, as well as to assess the intensity and nature of their changes during operation. In region A, contact often occurs when rolling stock moves straight and in curves of a relatively large radius. In curves of a small radius, such contact is significantly less seen, usually as a result of a combination of certain factors and rail-wheel contact geometry. This contact area accounts mainly for stability optimization of the rolling stock movement, ensuring a difference in the rolling wheel diameters sufficient to fit into the curves of a relatively large radius (for non-adjustable bogies) and a smaller radius (for self-adjustable bogies). In order to reduce wear intensity in this area, the conicity here should be minimal, in compliance with the fitting requirements, which provide contact extension to as much of the wheel rim width as possible. The rail head in this area is rounded in radius, and profiled wheels are preferred. In area B as a result of the small interaction area, the contact is often characterized by an extremely complex stress state. The two-point contact is accompanied by high rates of material wear and flow. In case of a single-point contact, high contact stresses prevail along with rotational and intense longitudinal slippage. The contact in the rail operational area is inextricably aligned with large angles of striking and transverse slippage. There are three possible cases that should be considered for the flange contact. A two-point contact, a single-point contact and a conformal contact (Fig. 3). Two-point contact. With an increased rail head bulge, a two-point contact is formed, where contact depth and the flange pre-touch (the point of flange contact ahead of the contact point of the tyre with the rail head) are quite significant. Thus, the speed of flange sliding along the head is high, and lateral wear quickly accumulates. Fluting forms more intensively on the running surface. This type of contact is characterized by intense slippage and wear, if lateral flange forces and transverse slippage take place, as it happens in curves. Under these conditions wheel flange wear accelerates until the flange outline matches the rail outline. This contact is often so intense that the plastic flow of flange material occurs. Experience indicates that the flange is often undercut with any lube layer put into the contact zone. During operation, the two-point contact is converted into a single-point contact. Single-point contact on the rail fillet. This type of contact possibly causes the greatest damage to the rolling stock and the track. High contact stresses that occur
Fig. 3 The main flange contact models in track curved sections a two-point contact; b single-point contact; c conformal contact
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in conditions of intense slippage cause fatigue damage on operational fillet. Singlepoint contact on the fillet is not a typical phenomenon and occurs rarely in cases when the wheel and rail profiles were incorrectly calculated or the rail head was flattened during operation. Conformal flange contact. The conformal contact occurs when the rolling rail edge and the wheel flange wear down to common profile due to intense flange contact at the curves. It is noted that this profile is approximately the same under various conditions of flange contact on different railways. Due to the conformal contact, relative slip expands the contact zone, specific pressure decreases and some flow of the rail metal probably occurs. Whatever the conformal contact mechanism, the rail and wheel profiles, worn to consistent configuration, successfully preserve it and show good performance in terms of fatigue endurance. This type of profile has a number of advantages, such as: – this type of profile retains its geometry for a relatively long time; – the fillet surface layer fatigue remains under control within the range of prevailing axial loads; – due to low specific pressure, the lube film applied to the surface is preserved; – Conicity is neutral, i.e. the wheels do not acquire a large taper, as in the case of a single-point contact. In comparison with a non-conformal profile, with use of conformal profile in curves contact stress level can be reduced. However, it should be noted that the mutual wear of the conformal profiles occurs in such a way that the pressure profile tends to concentrate in the area of the instantaneous rotation axis of the wheel set (fillet area and the base of the flange) and thereby boosts plastic metal flow [5]. It is believed that the rail and wheel wear rate is proportional to the energy spent on overcoming the rolling resistance with the wheel slippage along the rail. The rail and wheel wear is determined by relative slippage λ and pressure at the contact areas p. Then relative slippage and pressure depend on the dynamic parameters of the rail-wheel interaction. Moreover, wear is largely determined by the properties of the third body, which depend on lube and sand application, environmental conditions (humidity, rain, snow) [2]. There are three main wear types: normal, intense and catastrophic. The wear types are characterized by different intensity, surface condition, shape and size of wear particles. The normal wear type is characterized by light surfaces of the friction pair and relatively large metal particles with a length of about 1000 μ and a thickness of about 3 μ formed during the wear process. The intensive type of wear is characterized by a rougher surface. The wear rate increases rapidly. The wear particles are light flakes with a size of 500 μ and a thickness of 15 … 30 μ. With a catastrophic wear type, both friction surfaces become very rough, with seizure traces visible on them. Large wear particles have a size of about 300 μ and a thickness of about 50 μ. Smaller wear particles with a size of 10 μ have a spherical shape. There are two wear areas of the wheels and rails. The first area is the rail running surface and the wheel rim. The second area is the rail head side gauge and the wheel flange. The maximum wheel and rail wear rates for each area are given in the corresponding regulatory and technical documentation. The running surfaces are subjected to high contact stresses (1300…1700 MPa, depending on the
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axial load) at reasonably low (less than 0.01…0.015) levels of relative slippage. In this case, the values of the parameter pλ are in the range of 13 … 25, and a normal wear type occurs, mainly of an oxidative nature. The wear particles are mixed with various types of environmental pollution and form a layer of the third body on the running surface. The wear intensity depends on the composition of this layer and the frequency of surface clearing. The convex running surface eventually leads to rolling of the trough-shaped wheel. The wheel with a large mileage or high wear intensity acquires this type of shape. In return, the running surface becomes flatter, which also changes the rail-wheel interaction system. In this case, the wheel raceway is displaced along the rail from the center of the track curve, which ultimately leads to deterioration of conditions for bogie performance on the curve, relative slip increase and probability escalation of fluting. Gauge face wear occurs mainly with bogie performance on the curve. When a standard three-element bogie is moving in curves of a small radius under conditions of dry friction between the flange and gauge face, a catastrophic type of high-intensity wear occurs forming a significant number of wear particles, remaining on the track, and a rapid rail profile change. Since the relative slip λ depends on the angle of the wheel on the rail, which for a standard three-element bogie depends on the radius of the curve, the smaller the radius, the greater the wear of the flange and the gauge face. Depending on whether the wheel and rail have a new or worn profile, different contact pressures and relative slips may occur, which may lead to different wear types and rates. In case of unfavorable combinations, the contact pressure can reach 3000 MPa, and the relative slip—0.06…0.1. Under these conditions, the parameter pλ can reach up to 300 and catastrophic type of high-intensity wear and plastic deformation will occur. In addition, wear in the rail head fillet area is accompanied by significant plastic deformation. The latter occurs when the maximum contact pressures reach a critical level, which depends on the properties of the materials, in particular, on hardness, that changes due to operational hardening. Plastic deformation depends on tangential forces, which are generally determined by friction coefficient. Thus, if the friction coefficient is equal to 0.6, plastic deformation occurs on the surface with significantly lower contact stresses than when the friction coefficient is small. It is assumed that if the average contact stress exceeds 1/3 of the surface hardness measured in MPa, wear already occurs with a large proportion of plastic deformation, which accelerates rapidly with increasing contact stress. Along with wear and plastic deformation, it should be noted that one of the main types of rail damage are surface defects of a contact-fatigue nature, and consequently, longitudinal and transverse cracks on the head [3]. It is established that a plastic deformation zone is detected on the skin layer of the worn surface. Zone width is not stable and varies not only for different rails, but also within the same rail. The deformation zone usually consists of two parts, the boundary between them is not always clear. The first part, closer to the surface, is a zone of banding, where distinguishing grains and sometimes even individual stripes (by optical microscopy) is impossible. The deformed layers of this zone are
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stretched along the rail surface. The second part is the transition zone, in which strongly deformed grains are visible, stretched along the rail surface [5]. Thus, the wear of the gauge face middle part in the curved track sections is accompanied by two processes: the formation and growth of fatigue cracks deep into the material and material stratification as a result of shatter crack fusion. The prevailing mechanism of gauge face wear in curved track sections of a small radius is a contact-fatigue wear, in combination with a molecular-mechanical mechanism that prevails in rail fillet area. In many studies, optimal intensity of rail wear is noted, at which contact-fatigue damage occurrence and deterioration are in balance. The optimal wear intensity is achieved if the material surface wears out quickly enough so that small contactfatigue surface cracks do not develop into the rail depth and their development does not lead to destruction. The optimal wear rate depends on the railway track operating conditions, rail material, track curvature, but on average it is about 0.02 mm per 1 million GRT traffic load [6].
4 Research Results There are three fundamentally different points of view regarding the creation of repair profiles. The first one is based on the idea of keeping the rail bulge out of contact with the wheel for a certain period of time, as a result a two-point rail-wheel contact is provided, in which the vertical pressure is transmitted to the running surface at points located between the rail axis and the lateral radius, whereas lateral pressure is transferred to the gauge face [7]. The second point of view is to obtain minimal transverse movement of the wheel along the rail, which is one of the reasons for defect No. 11.1-2. formation. In some cases, with this profile, rail head radius does not contact the wheel [7]. And, finally, there is an opinion that the best rail profile is the one that is obtained in operation with wear of 2…3 mm (the run-in rail head profile). In this case, the most dense (over a larger area) rail-wheel contact is ensured, as a result, the contact stresses in the rail are reduced [2, 7, 8]. Each of these methods has its own advantages and is effective for certain situations. The proposed approach to cross-section rail profile formation combines all three design directions, which are applied depending on the operational conditions which determine a particular repair profile use. Thus, it is possible to formulate general principles of designing repair profiles: – cross-section rail profile formation, which allows minimal, but necessary metal removal to dispose contact-fatigue damage on the rail head surface; – to reduce defect growth rate, it is necessary to create optimal conditions for rail-wheel contact under various operating conditions, the type of rail-wheel contact before profiling and the contact conditions that are planned for rail-wheel interaction after grinding.
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Fig. 4 The scheme of forming the profile of rails laid on the outer face of curves
Based on the analysis, it is possible to formulate recommendations for reducing rail wear intensity in curved track sections based on the formation of asymmetric rail profiles of inner and outer rail faces: 1. To ensure better bogie performance on the curve and thereby reduce the wear intensity, it is necessary to carry out asymmetric grinding of the rails. 2. The main task of asymmetric rail grinding is to form rail profiles separately for inner and outer face in order to ensure the necessary taper and displacement of the inner and outer rail running face to the center of the curve to provide an optimal difference in the wheel rolling diameters, which enables wheel set movement along the curve without slipping. 3. For rails laid on the outer face of the curve, it is necessary to ensure conformal contact with the wheel taking into account the characteristics shown in Fig. 4. 4. In case of conformal contact on the outer face of the curve, in order to ensure the correct taper and prevent an increase in the relative slip of the running surface and the flange, it is necessary to prevent an expansion in the contact line width AB over 50 mm. To do so, when designing a repair profile, it is necessary to lay a stronger non-running rail face radius to avoid contact of the wheel tread with the rail surface outside of point A. 5. For rails laid on the inner face of the curves, a single-point contact with the wheel is provided taking into account the characteristics shown in Fig. 5. 6. For rails laid on the inner face of curves in order to reduce the influence of the formed flatness and AB zone expansion caused by plastic deformation and vertical wear of the rail, it is necessary to restore roundness of the running surface and remove the flow on the rolling and non-rolling rail faces. In this case, the coordinate xA will increase and the coordinate xB will decrease to the recommended values and the running track AB will shift to the non-rolling fillet (to the curve center). This increases the difference in the rolling inner and outer wheel diameters and, as a result, reduces the relative slip of the wheels and vertical rail wear. These recommendations are the basis for the methodology development on formation of asymmetric rail profiles in curved sections of a small radius track.
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Fig. 5 The scheme of forming the profile of rails laid on the inner face of curves
5 Main Conclusions The analysis of the domestic and foreign research results allowed us to draw the following conclusions: 1. During operation in curved track sections, the rail head surface is subjected to a complex effect of negative factors leading to wear, plastic deformations and occurrence of contact-fatigue defects. 2. The design of the repair profile should be carried out in a comprehensive manner in order to eliminate or at least minimize all negative factors leading to wear, plastic deformations and the occurrence of contact-fatigue defects. 3. The main parameters that determine wear processes and the occurrence of contact-fatigue defects of the wheel-rail pair in the curves include: contact stresses, relative slip, the difference in the rolling radii of the inner and outer wheels and the conditions for bogie performance on the curve. 4. The operating conditions of rails and wheels in curved track sections, due to design features, do not allow to completely eliminate wheel-rail pair wear, but at the same time the correct outline of contacting surfaces will significantly reduce wear intensity. 5. The optimal wear rate of the rail surface will allow timely removal of contactfatigue defects arising in the skin layer of metal, preventing their development into the rail depth. 6. In curved sections, conformal profiles are preferred as they reduce contact pressure and wear intensity. 7. The problem of creating a conformal rail-wheel contact is the lack of specific geometry of the wheel cross-section profile. Wheels with different geometry and wear rates pass along the track section, so the creation of a conformal rail profile can only be carried out on the basis of an average statistically worn wheel. 8. To reduce the defects and wear intensity in the curved track sections, it is necessary to carry out preventive work on grinding the rails in accordance with the established frequency, considering outlined recommendations.
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9. The design of the repair profile must be carried out considering railway track design parameters and the actual wear of the rails.
References 1. Karpushchenko N, Trukhanov P (2018) Mechanical and mathematical model for estimating the wear rate of the side face of rails. MATEC Web Conf 239:05007 2. Harris WJ, Zaharov S, Lundgren J, Tournay H, Ebersöhn W (2002) Guidelines to best practices for heavy haul railway operations: wheel and rail interface issues. International Heavy Haul Association, p 23454 3. Ilinykh A, Matafonov A, Yurkova E (2020) Efficiency of the production process of grinding rails on the basis of optimizing the periodicity of works. Adv Intell Syst Comput 1116:672–681 4. Smith RE, Kalousek J (1990) A design methodology for wheel and rail profiles on steered railway vehicles. In: Proceedings of the 3rd international symposium on contact mechanics and wear of rail-wheel systems, Cambridge, UK, pp 334–338 5. Reddy V (2004) Modelling and Analysis of rail grinding & lubrication strategies for controlling rolling contact fatigue (RCF) and rail wear. Queensland University of Technology 6. Kalousek J, Magel E (1997) Achieving a balance: the «Magic» wear rate. Railway Track Struct 7. Kosenko SA, Akimov SS (2017) Performance characteristics of differentially quenched rails. Mag Civil Eng 75(7):94–105 8. Magel E, Kalousek J (2002) The application of contact mechanics to rail profile design and rail grinding. Wear 253:308–316
Mathematical Modeling Technique for Designing a Composite Technological Process for Machining Holes in Laminated Parts Tatiana Tyunyukova
and Anton Kirpichnikov
Abstract The aim of the research presented in this article is to develop a new technological process for manufacturing and machining of laminated parts consisting of heterogeneous materials by combined methods. The basis of this process is the processing of holes in a pre-assembled package of sheet materials with different physical and mechanical properties. Regardless of the laminated parts’ design, the need to make holes in them during their production or assembly, as well as during repair work, is obvious. It is the heterogeneity of materials that creates difficulties when using traditional machining methods for laminated parts, such as drilling or the use of punching dies. In order to achieve the set goal, strength and plasticity of materials were brought together into a single quantitative parameter—the coefficient of machinability of sheet materials by cutting, which is the basis for modeling the technological process and further development of cutting tools. A mathematical model of the technological process was also developed, on the basis of which analytical dependences and quantitative relationships between the main parameters of the technological process were revealed. In the course of the experimental studies, the adequacy of the mathematical model to the real technological process has been confirmed, thus the possibility of its use for the processing of laminated parts has been established. The results of the conducted work are the basis for the special cutting tools and technological equipment development, necessary for the proposed technological process implementation for the laminated parts machining. The application of such equipment and implementation of the new technological process in the production of laminated parts can give a significant economic effect and expand the existing possibilities of processing such products under operational conditions. Keywords Laminated parts · Composite panels · Technological process of obtaining holes in laminated panels · Mathematical modeling of the technological process of cutting
T. Tyunyukova (B) · A. Kirpichnikov Siberian Transport University, 191 Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_6
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1 Introduction In various branches of the material production sphere, which include transport engineering, industrial, civil and transport construction, layered parts are used, which are unclosed envelopes with smooth gentle or flat surfaces, limited by contours of arbitrary outlines and containing the sheet materials composed in a certain sequence, which have different physical and mechanical properties [1–3]. Assembled from heterogeneous elements, layered parts are used as load-bearing planes of structures, and can also perform the role of protection against chemically aggressive environments, thermal, electrical and other influences, being decorative or a combination of these or other properties [4]. Thus, as a result of combining certain selected structural materials, composites are created, the mechanical characteristics of which cannot be obtained by using homogeneous materials. Fabrication and assembly of laminated parts involves the need to perform a number of technological operations, which include: obtaining blanks of sheet elements; formation of holes in them; installation and assembly in packages; installation of bolted, riveted or other connections. But from the point of view of feasibility in small-scale production, when modernizing equipment or performing repair work for the formation of holes in laminated parts, the only acceptable technology is the one that involves cutting holes in the pre-assembled package of sheet elements. However, drilling holes is not possible in some cases due to the following circumstances. Laminated parts can be made of heterogeneous materials, including non-metallic ones. Therefore, cutting modes and existing tooling designed for one of the materials can be inappropriate for the others. When manufacturing laminated parts, thin sheet materials can be used. But drilling holes in them, especially large diameter ones, will inevitably lead to material fractures in the area adjacent to the hole, and their location in the layered package precludes the use of special conductors, which could allow to exclude their appearance. In mass or serial production, punching of holes in each of the individual sheet elements can be performed using punching dies containing dies and punches. But in production conditions, performance of this operation is an inefficient method, since in already assembled protective housings, casings and other structures of complex shape the possibility of orientation of a die relative to a punch is excluded or installation of a die is impossible at all. In this regard, there is a need to develop a technological process for manufacturing and assembly of laminated parts, the greatest efficiency of which can be achieved by combining several operations of processing heterogeneous sheet materials. The article presents the ways to improve the efficiency of manufacturing processes of laminated parts on the basis of the combined methods of processing materials with the use of specialized forming tools and equipment. For this purpose, a mathematical model of the technological process of layered parts processing is developed, allowing optimizing cutting modes by minimum power consumption.
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A new technological process for manufacturing laminated parts that includes the formation of technologically necessary hole of minimum dimensions with its subsequent dimensional machining is proposed.
2 Research Methods Laminated parts can contain any number of layers of metallic and non-metallic materials. A typical structural element of a layered part can be represented as consisting of a system of layers stacked on a flat or curvilinear surface that defines the configuration of the component. An appropriate set of layers provides the necessary combination of mechanical, thermal, and other characteristics. When manufacturing, assembling and installing laminated parts, it is necessary to make holes in them in advance in order to install connecting elements. But during repair works and modernization of equipment, processing of holes, for example, by drilling thin-sheet, heterogeneous materials, assembled into packages and significantly different in machinability, causes certain difficulties [5, 6]. Therefore, it is necessary to develop a technology for manufacturing and assembling laminated parts, which would allow performing these works on machines and structures in operation. The problem under consideration can be solved on the basis of developing a new combined technological process for machining holes in laminated parts and creating special tools and small-size tooling for its implementation. The method of mathematical modeling served as a basis for developing the technological process. The cutting process in this case is studied as a process of material deformation with the help of discrete mechanical models [7]. Analyzing the technological operation of machining a hole in a single-layer thin sheet part—plate, it is possible to present it as a combination of three consecutive transitions, performed with the use of specialized tools. Figure 1 shows a scheme of the designed technological operation. At the first transition shown in Fig. 1, a tool 1 at its forward motion is machining technologically necessary (leading) hole. z
z
h
h
x
x 2
3
y
y a)
b)
Fig. 1 Scheme of machining a hole in the plate: a forward stroke; b reverse stroke: 1—special tool; 2—plate; 3—cylindrical conductor with cutting edges
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At the second transition, the tool moves in the formed hole. At the same time, it performs a progressive movement along the z axis to the value of 0.5 step of the tool belt twist and turn around the z axis. The third transition shown in Fig. 1, b is carried out in the reverse stroke of the tool, which performs only a reciprocal motion without rotation around the z-axis. In this case, the hole is cut by the side edge of the tool moving relative to the cylindrical conductor with cutting edges. The conductor is mounted on a manual fixture that is pressed by the operator to the workpiece. An electromagnetic actuator with a reciprocating motion of the electromagnet armature can be used as a fixture. Laminated parts can be made of heterogeneous materials, including non-metallic materials. Therefore, cutting modes and tools designed for machining one of the materials may not be suitable for the others. In addition, individual elements may be made of the materials that are poorly machinable, such as high-carbon and alloyed steels, titanium alloys, brittle nonmetallic materials, etc. [8–10]. In general, layered parts can contain any number of layers of materials with different physical and mechanical characteristics. These include, first of all, tensile strength σts or cut σc and plasticity, characterized by the degree of relative stretching of the material δ%, which determines the ability to cut sheet materials. At the same time, a ductile material such as soft aluminum with σts =75 MPa with asbestos-cement is easy to cut, and asbestos-cement with σts =70 MPadue to its brittleness, should be classified as a difficult to process material. Therefore, mechanical strength cannot fully characterize the machinability of sheet materials by cutting. In order to obtain a unified quantitative assessment of the physical and mechanical properties of materials, the strength and ductility indicators using the generalized Harrington function are convolved into a single parameter-coefficient of machinability of sheet materials by cutting, the variation range of which is shown in Table 1. Evaluation of the material machinability at random alternation of layers is the basis for modeling the technological process and developing the design of a cutting tool [11]. The task of the research is to determine the cutting forces during forward and reverse working strokes of the tool, and its loading can be carried out in one cycle or a number of repeated cycles. For laminated components it is not possible to construct the actual σ-ε diagrams used to calculate the load required to initiate the plastic flow of the material [12]. Table 1 Coefficient of sheet metal machinability Group no.
Machinability
The machinability factor, K Numeric value
Designation
1
High
1.00–0.63
K1
2
Average
0.63–0.37
K2
3
Low
0.37 and below
K3
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Fig. 2 Model a and load response b of an elastoplasticstrengthening body
Therefore, the force loading F-x characteristics, which establish the relationship between the applied load F and the absolute value of the settlement x, are used in the calculations. The mathematical model of the layered part is based on the elastic–plastic body model shown in Fig. 2, a. It represents a weightless cylindrical envelope of diameter d and height h, immersed in a homogeneous isotropic medium of height H ≤ hunder the impact of mass m moving with the speed υ0 . The elastic properties of a deformable body are modeled by a spring with stiffness c1 , set between the envelope and the moving mass. The resistance of the medium to the beginning of the envelope introduction is indicated by the dry friction damper and is characterized by the resistance force FR , arising at its end part: FE = c2 h k
(1)
where c2 is a conditional stiffness of the medium in the ductile zone; Fk is the value of the envelope displacement in k cycles of dynamic loading. The F-x characteristic corresponding to the model is shown in Fig. 2, b. At the initial conditions 0 ≤ hk ≤ h, material deformation has an elastoplastic strengthening character, with H≥ hk ≥ h, there is no strengthening and, finally, at H ≤ hk ≤ h, there is a softening of the elastic–plastic body. As it can be seen from Fig. 2, b, the initial segment of the load static characteristic 0. A represents the behavior of the body in the elastic deformation zone, and c1 ≡ tgα with α1 = α2 = ... = upalphak . Beyond the inflection point of the load characteristic A, the plastic flow of the deformed body is initiated, and c2 ≡ tgβ. The unit loading cycle is shown by lines 0A and AB, and line BC corresponds to the unloading of the model when the envelope is stopped. Re-loading occurs along line CB in the elastic zone and line BD in the plastic zone. The beginning of the (k + 1)-th cycle of deformation in the elastic zone, assuming that it was preceded by k cycles, will be described by the equation: m x¨ + c1 x1 = 0
(2)
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which will be true as long as the condition is satisfied: c1 x1 ≤ c1 h k FT
(3)
At t = t*, where t* corresponds to the moment of the plastic deformation initiation, it follows from (3): x1∗ =
c2 hk + FT c1
(4)
where x∗1 —is the value of strain in the elastic zone. At t ≥ t* the envelope starts to immerse (the obvious condition for the immersion of the envelope mυ02 > c1 (x1∗ )2 ). And in this case, we can write down a system of equations for the “mass-envelope» system motion in the area of plastic deformation:
m x¨ 1 + c1 (x1 − x2 ) = 0 c2 (hk + x2 ) + FT = c1 (x1 − x2 )
(5)
where the second equation is the coupling equation between the resistance forces in the elastic and plastic zones. The solution of Eq. (5), taking into account the finite conditions corresponding to the stopping of the envelope, provides a partial difference equation and determines the amount of strain of the elastic–plastic body for an arbitrary number of cycles of dynamic loading: 2 k k 2 FT c c mυ c FT 1 1 1 0 hk = + 1− − c2 c1 + c2 c1 + c2 c2 c22
(6)
For an elastoplastic non-strengthening body, the Eq. (6) has the form: hk =
mυ20 c1 − 2FT2 k 2FT c1
(7)
and in case of unstrengthening 2 k k FT c1 FT mυ20 c1 c1 hk = − + 1− c2 c2 c1 + c2 c1 + c2 c22
(8)
For a rigid plastic strengthening body, an unstrengthened body and a body with perfect plasticity, the formulas (6)–(8) can be transformed.
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A rigid plastic strengthening body:
hk =
FT c2
2 +
mυ20 FT k− c2 c2
(9)
Unstrengthened body: hk =
mυ20 k 2FT
(10)
A strengthening body with perfect ductility:
hk =
mυ20 c2
(11)
The problem of dynamic deformation of composite bodies with a complex structure, whose static load F characteristics are essentially nonlinear, appears more complicated. In this case, the problem of dynamic deformation can be solved using composite models, which enable the load characteristics to be approximated by piecewise linear functions. The model of a deformable solid body establishes the relationship between forces and displacements and can serve as the basis for modeling the combined technological process of machining layered parts. In this case, the envelope may consist of several layers I, II…N, and its elastoplastic properties (c1 , c2 , FT ) will be an integral estimate of the resistance forces to tool movement, determined by the static load F-characteristic of the real part. The model shown in Fig. 3 shows the combination of technological operations— machining the technologically necessary hole (1st transition), moving the tool in it to a given depth (2nd transition), dimensional machining of the hole with the return stroke of the tool (3rd transition). At the first transition shown in Fig. 3, a), the layered part consisting of two bonded envelopes I and II, with machinability coefficients K1 and K2 , acts as an elastic– plastic strengthening body. The part of the load characteristic corresponding to the first transition is shown in Fig. 4 and is shown by the OAB line with an offset ξmax in the elastic zone. At point B the gradual withdrawal of the tool from the underside of the part begins—the unloading line BC. Point C corresponds to the beginning of the second transition—the movement of the tool with simultaneous rotation in the pre-formed hole. The load characteristic is modeled by the 2nd envelope connected to the envelope 1 via an elastic element with stiffness c12 (CD line) or without (CD line). After the tool has moved in the lead hole to the specified depth, the tool begins its return stroke—the third transition.
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Fig. 3 Model of combined technological process: a first transition; b second transition; c third transition
F В Е
F F
А
N
D С
F
D′ 0 ξ 1st transition
x
x
x
h
h
h
2nd transition
x h
3rd transition
Fig. 4 Load characteristics of the combined process
Since the cutting force remains constant during the dimensional machining of the hole, the load characteristic DEN is modeled by the third envelope moving under the influence of the second envelope. The latter moves without resistance forces on the lateral face.
3 Research Results As a result, the experimental studies were carried out in order to assess the adequacy of the mathematical model to real technological processes, the influence of the end cutting edges of the tool on the cutting modes was investigated, the energy intensity of combined methods of processing layered parts was evaluated. In order to remove static load F-characteristics, sheet materials significantly differing in their physical and mechanical properties were used: steel, aluminum, asbestos-cement, and polystyrene foam. To exclude the influence of elastic properties of a layered part on the character of loading, which depends on the alternation of layers, its size, method of fastening,
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curvature of the surface and other factors, square samples with a side of 10 cm were installed in a special container. It is a hollow cylinder, in the inner part of which a very plastic material is placed. Relatively elastic materials in the form of sheets or packages were placed on the end part of the cylinder and rigidly fixed with a pressure washer. Static loading of the samples was carried out on mechanical and hydraulic presses. The experimental dependence F = f(x) was obtained. After the static characteristic was taken, the test specimen, mounted in a container, was subjected to dynamic loading on a copra. Regulation of single impact energy was performed by changing the drop height of the striker with mass of 1 kg. The value of pre-impact velocity of the striker was recorded by a device using photo-optical method of measurement with single interruption of laser beam by the striker. Figure 5 shows the static load characteristic, obtained while processing the component, consisting of carbon steel sheet with thickness of 0.6 mm and polystyrene foam with thickness of 20 mm. The 18 mm diameter hole was machined with a spiral strip (twisted) tool, the end part of which is made with two cutting edges. Figure 5 shows only the first transition and the beginning of the second transition. Since in the second and third transitions, the part behaves as a rigid plastic body, the loading lines in the static characteristic are not shown. Table 2 shows the parameters of the piecewise linear characteristic that approximates the dependence F = f(x) obtained experimentally. It is divided into intervals from 0 to hk5 , i.e., the values that should be determined to calculate the dynamic modes, and hki = xi . In intervals 1 and 3, the deformed body behaves as a body with perfect plasticity, and the energy is calculated by the formula (11). In intervals 2, 4, 5, with rigid-plastic behavior of the body, the calculation is performed according to the formula (10). From the table above, it is evident that with an energy value of T = 10 J transferred to the tool per load cycle, the total number of cycles required for machining the hole is k = 2.33. Consequently, the machining of a hole for three cycles of tool loading requires a single cycle energy of 7.8 J, whereas for a single cycle it will increase to 23.3 J. The value of energy of a single loading cycle obtained in the experiment is
Fig. 5 Load characteristic of the combined technological machining process of the laminated part “steel-foam-polystyrene”
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Table 2 Experimental data hki , FTi , c1i and results of loading cycles calculation Transition no.
Interval no.
Interval
Measuring range hk · 10−3 , m
1
1
0 − hk1
0–3.7
2 3 2 3
Value hki · 10−3 , m
Cutting strength FTi · 102 , N
Conditional stiffness c1i · 105 , N/m
Number of strokes ki
3.7
0
3.0
0.205
hk1 − hk2 3.7–5.0
1.3
11.0
–
0.143
hk2 − hk3 5.0–6.8
1.8
11.0
4.5
0.157
4
hk3 − hk4 6.8–27.1
20.3
3.0
–
0.609
5
hk4 − hk5 27.1–0
27.1
4.5
–
1.220
9.0 J, and the discrepancy between the calculation and experiment does not exceed 13.3%, which is a quite satisfactory result for the calculation of dynamic modes.
4 Conclusion As a result of the conducted research, the possibility of creating a new technological process for manufacturing laminated parts by combined methods, including cutting out a technologically necessary hole with its subsequent dimensional machining in one stroke of the tool is substantiated. The concept of machinability coefficient by cutting of sheet metal and nonmetal materials, taking into account tensile strength of materials and their brittleness, is introduced. Mathematical models of layered part and combined technological process which establish the connection between the main parameters of technological process—mechanical energy, cutting depth and the number of cycles of dynamic loading of tool in analytical form are developed. The results of the conducted work are the basis for the special development of cutting tools and technological equipment necessary for the implementation of the proposed technological process for the processing of laminated parts. The application of such equipment and implementation of the new technological process in the production of laminated components can give a significant economic effect and expand the existing possibilities of machining such products under operational conditions.
References 1. Ning H, Janowski GM, Vaidya UK, Husman G (2007) Compos Struct 80(1):82–91. https://doi. org/10.1016/j.compstruct.2006.04.090 2. Novikov M, Polushin V, Zimin S (2015) Sandwich panel as a structural element of overlap. Paper presented at the international scientific conference “Week of Science in SPBPU – Civil
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Design Criteria for Variable Rigidity Sections of Approach Embankments to Bridges and Overhead Crossings Alexey Lanis , Denis Razuvaev , and Petr Lomov
Abstract The development of rail transport involves the elimination of barrier places, which include the transition sections from the artificial structures to the subgrade. The existing normative solutions on the arrangement of transitional sections with variable rigidity refer mainly to the new construction. And during development of new types of crossing sites which allow performing works on their arrangement without movement restrictions, there are questions of design and estimation of nonuniformity of approach embankment settlement on crossing sites. To solve the emerging issues, it was proposed to evaluate the transition sections “smooth approach”—the pattern of change in the longitudinal slope on the section of variable rigidity, which does not cause significant dynamic effects on the track structures and rolling stock when the latter approaches the railway bridge structure. In order to obtain the criteria for assessing the "smooth approach”, the nonuniformity of approach embankment settlement in the area of its interface with the bridge for the known structures of the transition sections has been investigated. Functional dependences of changes in the vertical deformation of the main site on the length of the section with variable rigidity were obtained. Differentiation of the obtained functional dependences by the length of the section of variable rigidity allowed revealing the law of change in the increment of vertical deformation by the length of the approach embankment section. In other words, the assessment criteria of "smooth approach" to the railway bridge construction in the form of the law of change in the nonuniformity of the slope angle of the main platform on the section with variable rigidity has been obtained. The principle of designing new types of variable rigidity sections using the developed criteria has been proposed. Keywords Rail transport · Transition sections from the artificial structures to the subgrade · Bridge · Overhead crossings
A. Lanis · D. Razuvaev · P. Lomov (B) Siberian Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_7
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1 Introduction The Strategy for the Development of Rail Transport in the Russian Federation until 2030 provides for an increase in carrying capacity through the gradual introduction of heavy traffic with increased axle loads. The increase in axle loads involves the elimination of barrier places, which include the transition sections from artificial structures to the subgrade [1]. There is a sharp transition in the rigidity and deformability of the slab track at these sections, which in practice leads to the occurrence of track subsidence in this place and the need for frequent repairs [2, 3]. Considering the vast geography of the Russian railroad network, the construction of artificial structures was carried out at different times and using different designs of sections with variable rigidity. Many of such sections nowadays no longer fulfill their functions. Bridge structures on railway lines were built on deep foundations, and the track superstructure was laid on the approach embankments, poured with soil on the natural base. There are also railway facilities where variable rigidity is provided only by the work of the track superstructure (increase of sleeper density on the approaches to the artificial structures), which in conditions of increasing axial loads can affect the reliability of the structure. Solving the problem of ensuring the operational reliability of sections with variable rigidity of the operated railroad track and increasing the economic efficiency of their reinforcement is very relevant to the transport industry. According to industry standards and regulatory documents, technical literature, as well as scientific research [4–7], the following principal types of devices are used in the practice of construction and operation of interfaces of artificial structures and approach embankments: – laying of reinforced concrete slab; – arrangement of reinforced concrete boxes filled with crushed stone with variable depth; – arrangement of crushed stone cushion of variable thickness; – installation of the cushion reinforced with geosynthetic materials in layers; – construction of an approach embankment with higher density; – embankment reinforcement in the section with variable rigidity, etc. These solutions are more relevant to new construction, since in case of their application during reconstruction or maintenance of the operated railroad track, long process windows will be required, organization of which on the sections with high freight intensity is extremely difficult. Smooth change of rigidity in conditions of operated railroad track can be achieved by reinforcement of soils of the main ground bed on approaches to bridges by injection methods. Injection of solid solutions along the weakened cavities and cracks in the massif leads to the formation of reinforcing structure with compaction of the surrounding soil, which together can increase the rigidity of strengthened soils [8, 9]. Such methods can be provided without prolonged interruptions in train traffic.
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In this connection, there is a question of designing new types of variable rigidity sections, providing the required nonuniformity of the approach embankment settlement in the zone of its interface with the bridge, as for the known solutions. The standard published as a result of the meeting of experts of the Commission on Infrastructure and Rolling Stock (Warsaw, 2005) proposes to evaluate the nonuniformity of settlement in the area of approach embankment to the bridge by a reference value of unevenness—track bend angle. The authors of the article propose to use not only the average slope of the section, but also the regularity of its change along the length (the distance from a man-made facility), as well as the maximum value of this parameter on the approach section as a criterion of settlement nonuniformity on the transitional sections. Thus, the nonuniformity of the slope on the transition sections is proposed to be evaluated by the “smooth approach” to the railway bridge structure. This term means the regularity of change in the longitudinal gradient on the section of variable rigidity, in which significant dynamic impacts on the track structures and rolling stock do not occur when the latter enters the railway bridge structure. The purpose of this work is to develop the criteria for “smooth approach” of the main platform within the sections of variable rigidity and the conditions of its application.
2 Research Methods To achieve this goal, the authors investigated the nonuniformity of the main site settlement within a section of variable rigidity when using regulatory solutions. For this purpose, models of approach embankments reflecting application of normative solutions for arrangement of sections with variable rigidity have been made up. For each model, functional dependences of the change in the vertical deformation of the main site on the section length with variable rigidity were obtained. Differentiation of the obtained functional dependence on the length of the section with variable rigidity enabled to reveal the law of change in the increase in vertical deformation in relation to the length of the approach embankment section. The above-mentioned normative solutions used in new construction for arrangement of variable rigidity sections differ in technical peculiarities of their arrangement and technological execution. However, despite the differences in their design and in the materials used in the solutions, three characteristic models reflecting all the above-mentioned normative designs can be distinguished, which include: – a model with a wedge-shaped array device with a uniform change in power from crushed stone; – the model with the device of wedge-shaped array with a step change in power from reinforced concrete boxes filled with rubble; – a model with a plate element (reinforced concrete slab).
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The models of the variable rigidity section involved in the survey are shown in Fig. 1. In general, all the solutions are aimed at creating in the body of the high embankment (within the working zone) a wedge-shaped array with increased characteristics. And depending on the design used, such a zone can be formed both with uniform change in the depth of the array with increased characteristics, and with a step change in the depth of the array (see Fig. 1, a, b). a)
b)
c)
Fig. 1 Models of the section with variable rigidity: a with a wedge-shaped array of crushed stone with uniform power change; b with a wedge-shaped array of crushed stone boxes with staggered power change; c with the formation of a slab element
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According to S. I. Klinov’s research materials, the modulus of elasticity of the slab track on bridges and pipes, taking into account the work of man-made structures and the base, reaches 100 MPa. Consequently, in the models under development, it is reasonable to apply 100 MPa modulus of the wedge-shaped masses. The model with a reinforced concrete slab device should be singled out separately, because in this case a slab element with strength and rigidity parameters significantly exceeding similar parameters for soil medium is formed in the model (see Fig. 1, c). Investigations on the mathematical model were carried out for typical cases— embankments with elastic modulus of 50 and 80 MPa. These values are conditioned by the requirements to ensure the corresponding modulus of elasticity of embankment soils in new construction depending on the track category. The general sequence of investigation for each model is as follows: – formation of variable rigidity section models; – loading the models with constant load from the track superstructure and operational load from prospective heavy-weight traffic; – determination of vertical deformation of the main site within the approach embankment section to the bridge for each model (an example of the vertical deformation diagram is shown in Fig. 2); – construction of the vertical deformation of the basic site within the section of the approach embankment to the bridge, depending on the section length for each model; – statistical processing of the study results with the definition of the functional dependence of the change in the tangent of the vertical deformation graph slope angle.
Fig. 2 Deformed model of the approach embankment to the bridge using the standard solution of the variable rigidity section device
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3 Research Results As a result of modeling the standard structures of 15 and 25 m long sections of variable rigidity, characteristic vertical deformation diagrams were obtained for each typical case—embankments with elastic moduli of 50 and 80 MPa. An example of the vertical deformation diagram for a section of variable rigidity is shown in Fig. 2. Statistical processing of the obtained array for vertical deformation values enabled for each typical case (for embankments with elastic moduli of 50 and 80 MPa, and sections of variable rigidity of 15 and 25 m in length) to derive a functional dependence of the change in the vertical deformation of the main site on the distance to the artificial structure. An example of vertical deformation change graphs from the distance to the artificial structure and the derived functional dependence is shown in Fig. 3. For demonstration purposes, Table 1 shows the values of the tangent angle tangent to the vertical deformation graph, converted to the slope (in ppm) of the soil mass within the transition section at different distances from the barrier site (interface with man-made structures). The data are given for a 15 m long section of the approach embankment to the bridge in embankment body soils with an elastic modulus of 50 MPa, averaged for three models. Figure 4 shows the averaged graph of the change in the slope i of the deforming soil mass within the section of the approach embankment to the bridge from the distance to the barrier site (interface with man-made structure) for the existing solutions for the sections of variable rigidity. Length of the variable rigidity section L, m
Vertical deformation S·10-3, m
Fig. 3 Graphical dependence of the vertical deformation of the main site (within the section of the approach embankment to the bridge) as a function of the distance to the man-made structures
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 0 y = (–0.5·10-3·x4 + 0.00171x3 – 0.256*x2 + 2.9295x + 1 2 3 4 5 6 Transition 7 section with a 8 9 10 11 Transition section 12 13 in the form of boxes filled with 14 15 crushed stone 16 Transition section 17 in the form of a 18 "wedge" of crushed 19 stone 20 21 22 23 24
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Table 1 Values of the slope i of the deforming soil mass within the section of the approach embankment to the bridge at different distances to the barrier place (conjunction with man-made structures) Parameter
Distance to the barrier place (interface with a man-made structure), m 0.1
1
2
3
4
5
6
7
15
Slope i, ppm
2.9
2.5
2.1
1.8
1.6
1.4
1.3
1.2
0.04
3.2 Slope of the deforming soil mass within a section of variable rigidity, ‰
Fig. 4 Diagram of the change in slope i of the deforming soil mass within a section of variable rigidity as a function of the distance to the barrier place (conjunction with a man-made structure)
2.8 f(х) = (–2·10-3·x3 + 0.00513x2 – 0.512x +
2.4 2.0 1.6 1.2 0.8 0.4 0.0 0
1
2
3
4 5 6 7 8 9 10 11 12 13 14 15 Distance to the barrier place, m
As it can be seen from Table 1 and Fig. 4, the maximum slope equal to 2.9 ‰ is recorded at the beginning of the section with variable rigidity, directly at the barrier site. By the end of the simulated section of the approach embankment to the bridge, the curve flattens out and is characterized by the threshold slope value of 0.04 ‰. At the same time within the limits of approach embankment section to the bridge the average slope equals iav = 1.5 ‰. It is recommended to use these threshold values of slope as criteria of «smooth approach” for the sections of approach embankment to bridges. In accordance with algorithm described above, “smooth approach” criterions have been determined for portions of approach embankments to bridges with length of 15 and 25 m in soils with modulus of elasticity of 50 and 80 MPa. These criteria are shown in Table 2. The identified criteria should be used when assigning design solutions for arrangement of variable rigidity sections depending on the track category characterized by the elastic modulus of embankment soils and on the length of the approach embankment section to the bridge.
80 Table 2 Criteria for “smooth approach” for the sections of approach embankments to bridges
A. Lanis et al. Criterion
Threshold value
A 15 m long section with variable rigidity in soils with modulus of elasticity E = 50 MPa Regularity of slope change i
i ≈ f (x) = (– 2 · 10–3 x3 + 0.00513x2 – 0.512x + 2.9295)10–3 (± 0.5 ‰)
Maximum slope imax
3‰
Average slope iav
1.5 ‰
A 15 m long section with variable rigidity in soils with modulus of elasticity E = 80 MPa Regularity of slope change i
i ≈ f (x) = ( – 0.0844x + 1.612)10–3 (± 0.5 ‰)
Maximum slope imax
1.6 ‰
Average slope iav
1.1 ‰
A 25 m long section with variable rigidity in soils with modulus of elasticity E = 50 MPa Regularity of slope change i
i ≈ f (x) = ( – 0.488x3 + 25.04x2 + 460.14x + 3220.9)10–6 (± 0.5 ‰)
Maximum slope imax
3.2 ‰
Average slope iav
0.8 ‰
Criterion
Threshold value
A 25 m long section with variable rigidity in soils with modulus of elasticity E = 80 MPa Regularity of slope change i
i ≈ f (x) = (– 0.49658x2 + 20.19x + 211.15)10–5 (± 0.5 ‰)
Maximum slope imax
2.1 ‰
Average slope iav
0.7 ‰
4 Conclusion The results of this survey will provide an opportunity to design the new types of sections with variable rigidity. The general principle of design can be described as follows: 1. A digital model of an approach embankment with a section of variable rigidity is created in a software package in which FEM is implemented. 2. The vertical deformations of the main site within the approach embankment and the curvature of the transition section (under the action of operating loads) are determined for the model.
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3. For the obtained curvature, the functional dependence of the vertical deformation on the section length is determined and its derivative (by the section length l) is taken. 4. The derivative of the function is compared with the criterion presented in Table 2. The slope thresholds specified in Table 2 should be observed. In case one of the criteria is not met for the developed section of the approach embankment to the bridge, adjustments should be made to the design. The obtained criteria of “smooth approach” are valid for the sections with variable rigidity formed by reinforcement of soils of the main site of the earth bed. It is reasonable to consider reinforcement of the working zone by injecting solid mortars or packed piles as methods of soil reinforcement providing the developed criteria [9, 10]. It should be noted that while forming digital models, it is necessary to take into consideration stress damping in working zone level of an earth bed by means of input of corresponding boundary conditions into the model or to form a model of transition section with worked out man-made structures and considering compressible thickness of the structure. Thus, the main conclusions of the performed study may be formulated as follows: 1. The concept of «smooth approach” on the railway bridge structure within the section with variable rigidity has been introduced. 2. A number of criteria for “smooth approach” has been defined and justified, including the pattern of slope change, maximum and average slope (Table 2). The criteria are substantiated for 15 and 25 m long sections with variable rigidity with modulus of elasticity of soils on the approach embankment of 50 and 80 MPa. 3. The principle of design and calculation of sections with variable rigidity with achievement of necessary «smooth approach” is offered.
References 1. Aziman M, Saifulnaz MR, Hejazi F, Azarkerdar A (2019) IOP Conf Ser Earth Environ Sci 357(1):012013 2. Hu P, Zhang C, Chen SJ et al (2018) Eng Struct 175:565–576 3. Yasrobi SY, Ng KW, Edgar TV, Menghini M (2016) Transp Geotech 6:1–15. https://doi.org/ 10.1016/j.trgeo.2015.12.002 4. Helwany SM, Wu JT, Froessl B (2003) Geotext Geomembr 21(3):177–196 5. Lichtberger B (2005) Track compendium: formation, permanent way, maintenance, economics. Eurailpress. ISBN 3777103209, 9783777103204 6. Chen Q, Abu-Farsakh M (2016) Geotext Geomembr 44(1):39–50 (2016). https://doi.org/10. 1016/j.geotexmem.2015.07.001 7. Shen SL, Hong ZS, Xu YS (2008) Civil Eng Innov 2(2):71–86 8. Lanis AL (2018) MATEC Web Conf Siberian Transp Forum 239:05006
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9. Lanis A, Razuvaev D, Lomov P (2018) Paper presented at the 10th international scientific and technical conference «Polytransport Systems». MATEC Web Conf 216:01006 10. Saride S, Archeewa E, Puppala AJ et al (2010) Deep soil mixing (DSM) columns to improve foundation support for bridge approach embankments. Paper presented at the GeoFlorida 2010: advances in analysis, modeling & design, pp 1866–1875
Definition Model of the Optimal Size of the Material Resources in Construction Sergey Kuznetsov
and Olga Demidenko
Abstract The problem of determining the minimum required sufficient amount of material resources reserves to ensure the continuity of construction and installation works has been solved in the article. The review of modern publications on determining the level of the current stock of material resources of construction production is presented. The practice of material resources organization of construction objects requires coordination of the processes of their supply and consumption. The probabilistic nature of material and technical supply of building production complicates the use of methods for determining the reserves based on the use of average values. The deviation of the average delivery interval from the planned one, as well as the standard deviation do not allow determining the size of the reserve, as they do not take into account conformity of the total volume of deliveries to the demands in the given type of material resources. To adequately reflect the dynamics of consumption and material resources supply, it is proposed to use the method of statistical modeling. Application of the statistical modeling method implies establishing the nature of random values distribution of the elements of material and technical support—intensity of supply and consumption volumes, intervals of supply and consumption. The work with the model consists in changing the input parameters and evaluating the behavior of the system according to the criterion adopted. The criterion for selecting the optimal inventory level is the minimum value of the costs associated with storage and downtime of construction crews during the planned calendar period. The choice of the optimal size of the stockpile is reduced to the calculation of costs depending on the size of the initial stockpile. The developed calculation algorithm is demonstrated by a numerical example. The method presented by the authors allows solving the problem of optimizing the size of the material resources production stock, increasing the uniformity of supply of complex and specialized teams’ workers, reducing the amount of circulating assets in construction. S. Kuznetsov (B) Siberian Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] O. Demidenko Siberian State Automobile and Highway University, 5, Mira Avenue, Omsk 644080, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_8
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Keywords Material and technical supply · Construction production · Material resources · Interval and volume of supply · Production inventories · Statistical modeling method
1 Introduction Production inventories of material resources are to ensure the continuity and rhythm of the construction process. The production inventory includes material resources that have come into the possession of the construction organizations, but have not yet been used directly in the production. Providing continuity in the production of construction and installation works, the amount of material resources should be minimal, as resources in stock, are no longer mobile and are excluded from the production process. Determining the minimum of the required, but sufficient amount of stocks is the task of their calculation. The minimum necessary size of production inventories is related to the level of organization and planning of logistics. Timely drawing up of supply plans, their conformity with production plans are the most important conditions of quality planning of material reserves. Simultaneous consumption of a significant type of material resources dictates the requirement for stocks completeness. Completeness of stock is characterized by certain quantitative and assortment ratio of available building materials, products and designs that are simultaneously consumed in the production process. In the construction companies, material inventories are formed in accordance with the features of the adopted technology and the organization of the construction process at the objects of construction, based on their assumption of the possibility of logistics support any of the adopted options for production work. In practice, this leads to intra-shift downtime due to ill-timed and incomplete logistics. The main part of the production stock—the current stock can be set in different ways. The choice depends on the availability of data needed for calculation. The current inventory rate can be calculated using the analytical relationship between demand and average inventory levels. This relationship is established on the basis of a considerable amount of data on stock levels by the methods of mathematical statistics and probability theory. If it is not possible to use the aforesaid method, the rate of current stock can be determined on the basis of the statistical data analysis on the size and interval of material and technical resources supply. The size of the current inventory can be determined based on the size q0 of the optimal delivery volume: q = 0
2K α h
(1)
where K is transportation and procurement costs; α is the total need for material resources in the planning period; h is the cost of material resources storage.
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Taking into account that the current stock is a variable value, it is necessary to establish that part of it, which should act during the formation of the production stock as a whole. The authors in [1] recommend defining this part of the stock at the level of half of the delivery interval. However, fluctuations in the intervals and supply volumes can lead in this approach either to a shortage of material resources, or to their excess. Therefore, in [2], when calculating the average value of the current inventory, it is recommended to take into account the fluctuations of the volumes and supply intervals using the following formula ⎡ 3ci =
1⎣ tav + 2
(tac − tav 2
)2
+
(qac −qav )2 n
P
⎤ ⎦
(2)
where tav is an average delivery interval in days; tac defines actual delivery intervals in days; qac is the actual size of deliveries in physical units; qav is anaverage delivery size in physical units; P is anaverage daily consumption in natural units; n is a number of supplies taken into account. As the analysis [3–5] shows, the average current supply of material resources, calculated by the formula (2), cannot ensure the production of works in the case of a break in supplies, exceeding the average interval. In addition, significant deviations in the volume of supply, in the intensity of consumption of material resources can be recorded. To eliminate the effect of these deviations on the rhythm of construction work production it is necessary to create an insurance stock of material and technical resources. In accordance with the sources [6–10], it is recommended that the size of the reserve based on the deviation from the intervals of supply only in the larger side. In [11] it is proposed to determine the size of the insurance stock by the method of standard deviations. The standard deviation makes it possible to find deviations from the average value with different signs. It is proposed to use it to calculate the deviation of the current stock size from the average, rather than the deviation of supply intervals. Using the rule of “three sigmas”, it is possible to establish the categories of insurance stock, which determine the reliability of supply of material and technical resources in the process of construction and installation works. Insurance stock in the amount of one standard deviation provides 68.3% of the reliability of uninterrupted supply in all cases of supply. It is recommended to use this value for rationing stocks of interchangeable material resources. An insurance stock in the amount of two standard deviations provides reliability of uninterrupted supply of 95.5%. For the construction industry, this value of the reliability of the resources logistics is sufficient. An insurance margin of three standard deviations provides 99.7% of logistics reliability. This category is recommended for the construction enterprises with a continuous technological process.
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2 Research Methodology The size of the necessary production inventory is determined by norms and standards. The stock norm defines the relative size of the stock in days of average daily consumption. Stock standard is an absolute size in kind or in value terms. With the help of norms and standards the maximum allowable planned volume of material resources (in excess of current consumption), which is necessary to ensure the smooth operation of the construction organization, is set. Stock standards in kind are used for planning and distribution of material resources, determining the capacity of storage facilities. Inventory standards in value terms are used to determine the amount of working capital and bank credit. The norms and standards of production inventories are determined by: – conditions of consumption—the range of material resources, the frequency of consumption, the size of incoming deliveries; – terms of supply—the form of supply and the volume of deliveries; – transportation conditions—by road, rail, water or other means of transport. These factors determine the need for a specific approach to rationing stocks in each case. Rationing stocks of structures, parts and other semi-finished products in the production of construction and installation work is extremely difficult. The dynamics of the construction process and probabilistic parameters, which characterize this process, do not allow us to use the well-known methodology of determining the reserves, which is based on the principle of “average” values. The application of average values to characterize processes is based on the fact that the average value is always the mean value for many different individual values of the same kind. It characterizes the level of the studied attribute for the unit of qualitatively homogeneous totality. If the totality does not have the property of homogeneity with respect to the averaged attribute, then the average values calculated for it are often fictitious and do not reflect any regularities. The characteristic of the average demand presented in [12–15] confirms the impossibility of using the average values in the conditions of the construction process. Material consumption in construction is related to the structure of construction work performed in the corresponding calendar periods. At that, the intensity of consumption of a certain type of material resources in a construction organization depends on the number and composition of specialized or complex teams, the level of their technical equipment, availability of sufficient work front, etc. In addition, the current methodology of determining the degree of uneven logistics is based on the use: the distribution and comparative methods, indicators of the weighted average delivery interval, the indicators of the root-mean-square deviation of the volumes of deliveries.
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Distributional and comparative methods of determining the degree of the uneven supply process are based on determining the volumes of supply in different periods (quarters, months, decades) and their comparison. The main disadvantage of these methods is that they do not provide quantitative indicators of the unevenness degree of supply. Both the deviation of the weighted average supply interval from the planned one and the standard deviation do not allow making certain conclusions about the size of inventories, because they do not take into account the degree to which the total supply volume corresponds to the need for this type of material. If the volumes of all batches are increased or decreased by the same number of times, the weighted average supply interval will not change, while the total supply for the period in question will increase or decrease. The specified reasons have demanded search of methods of calculation which would adequately display dynamics of consumption and deliveries of material resources in the conditions of building production. At the analysis of complex systems, to which the system of maintenance of building production with prefabricated details and constructions should be referred, method of statistical modeling (Monte-Carlo method) can be used. The application of this method leads to savings in the number of calculations, which are quite significant when modeling complex systems. The use of the method has been promoted by such important properties of the method as its rather simple computational scheme and universality. Many problems with probabilistic parameters are solved with the help of statistical modeling method. Particularly good results are achieved when it is possible to use approximate solutions. The calculation error of this method is proportional to the square root of the inverse to the number of experiments. If the number of observations is increased by a factor of four, the calculation error is reduced by a factor of two. In addition, the results of each test are independent of each other. Successful application of the statistical modeling method presupposes a preliminary analysis of statistical characteristics of all elements of the process of forming and using stocks (intervals of demand and supply, sizes of demand and supply, frequency of these values in the total volume of used statistics). The method under consideration is of great interest from the point of view of possibilities for analyzing and optimizing the size of material resources inventories for construction production. Let us consider the method of developing a model for solving the problem of determining the optimal stock of the nomenclature group of prefabricated reinforced concrete products. The purpose of modeling is to determine the economically justified volume of the stockpile taking into account the random fluctuations of the defining parameters. The development of these parameters and the establishment of the relationship between them is determined by the modeling criterion. The quantities characterizing incoming and consumption of prefabricated structures for the corresponding calendar periods are the parameters of stock management. The character of these values change in time makes it necessary to coordinate the modes of supply and consumption.
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Modeling the problems of managing the stock of prefabricated structures and parts required quantitative determination of the costs associated with the shortage of this type of resource. Losses of the construction organization in case of material resources deficit consist of the payment for idle time of workers, depreciation charges on the active part of production assets used for this type of work, losses of the conditionally constant part related to overhead costs. Losses associated with the payment of workers’ idle time can be determined by the formula Π1 = tid 2/3H
(3)
where tid is the duration of idle time due to the lack of material resources, h; H—is the average hourly tariff rate of the installation crew, rubles. In the case of rental of construction machines used in installation work, the loss of the construction company from their idle time is set at the rate of rental cost, reduced to one machine hour. If the construction machines are on the balance sheet of the construction company, losses from the downtime are added from depreciation deductions. 2 =
k i=1
Oi mi 100
(4)
where O is the book value of machines, rubles; m is the depreciation charges on this type of machines, %; k is the number of machines involved in the production process. Losses of the conditionally constant part of the overhead costs constitute 40% of the overhead costs for the construction organization Π3 = 0.4H C
(5)
where H is the amount of overhead costs for this type of construction and installation work; C is the estimated cost of works using a unit of missing material resources, rubles. In addition to losses from the lack of material resources at the construction site of the construction organization has losses from the storage of material resources inventories. These losses consist of the cost of current assets invested in inventories and the cost of the storage space maintenance. According to the expert estimates, the costs of maintaining storage areas are determined to be 0.4–0.5% of the cost of stored material resources [16]. Organization of material and technical support should completely exclude interruptions in the work of specialized and complex teams due to the lack of material resources and prevent their excessive stocks at the construction site. In this case, managerial decisions should be aimed not at the issue of replenishing the warehouse
Definition Model of the Optimal Size of the Material Resources …
89
of material resources, but at the issue of ensuring the continuous construction production. For this purpose, it is necessary to define probabilistic characteristics of process of material and technical support of construction to establish regularities of material resources consumption and supply change in time. The size of the material resources production stock depends on the progress of delivery schedules and the intensity of construction and installation works. The task of determining the optimum stock of material resources can be formulated as follows: to determine at the beginning of the calendar period an economically viable size of the stock of the nomenclature group of material resources, which achieves a minimum of losses from the storage of resources and downtime of construction teams consuming this group of resources for construction and installation work. The studies have shown that the optimal size of the stockpile depends mainly on the following factors: – The intensity of supply V1 of material resources in accordance with the supply plan; – intensity of consumption (demand) V2 in accordance with the plan of construction and installation works; – delivery intervals (disruptions in operations of transport or the manufacturing plant) J1 ; – consumption intervals (breaks in consumption of organizational and technological nature) J2 . To implement the developed algorithm, a program was compiled. Work with the model consists in changing the input parameters and evaluating the behavior of the system according to the adopted criterion.
3 Research Results The distribution of random variables (supply intensity V1 and supply intervals J1 , consumption intensity V2 and demand intervals J2 ) and their corresponding probabilities P are given in Tables 1, 2, 3 and 4. These tables present the data on the consumption and supply of reinforced concrete piles. Table 1 Supply volume distribution Supplyintensity P V1 , m3
Supplyintensity P V1 , m3
Supplyintensity P V1 , m3
Supplyintensity P V1 , m3
10
0.085 50
0.078 55
0.078 75
–
15
0.042 30
0.078 60
0.054 80
0.030
20
0.114 35
0.126 65
0.078 90
0.060
25
0.120 40
0.048 70
0.030 95
0.018
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Table 2 Consumption distribution Consumption intensity V2 , m3
P
Consumption intensity V2 , m3
P
Consumption intensity V2 , m3
P
Consumption intensity V2 , m3
P
10
0.034
25
0.064
40
0.140
55
0.059
15
0.038
30
0.144
45
0.131
60
0.038
20
0.144
35
0.110
50
0.081
65
0.013
Table 3 Delivery interval distribution Supply intervals J1 , days
P
Supply intervals J1 , days
P
Supply intervals J1 , days
P
Supply intervals J1 , days
P
1
0.644
3
0.103
5
0.034
7
0.07
2
0.123
4
0.082
6
0.007
8
–
Table 4 Consumption interval distribution Consumption intervals J2 , days
P
Consumption intervals J2 , days
P
Consumption intervals J2 , days
P
Consumption intervals J2 , days
P
1
0.773
3
0.116
5
0.009
7
–
2
0.076
4
0.013
6
0.018
8
–
A stock (volume) of material resources at arbitrary time t is considered. A random volume of material resources B is requested. If at time t the stock X is sufficient, the request is satisfied in full. If the stock is insufficient, the request is partially satisfied. In this case there is a shortage of material resources, the size of which is proportional to the cost of the volume of undelivered constructions: Z = C ∗ (B − X )
(6)
where C is the cost estimate of the material resource shortage per unit of products. Replenishment of constructions occurs at a random moment τ in a random volume y. It is required to find such an initial level of structural stock x0 , at which the costs associated with storage, immobilization of funds in stock and shortage, over the planned calendar period T will be minimal. The condition should be fulfilled: y≥ B (7) x0 + τ
t
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Table 5 Modeling results Initialstock, m3
0
50
100
150
200
250
300
0
0
Losses from the lack of structures, rubles 56,100 25,900 8500
2050 0
Losses from storage, rubles
0
4050 5400 6750 8100
Total losses, rubles
56,100 27,250 11,200 6100 5400 6750 8100
1350
2700
60000 40000 20000 0
0
100
200
300
400
Fig. 1 Change in the value of the total cost depending on the initial stock value of building structures
When formalizing the model, we introduce the notations V i —time interval between i + 1 and i requests for designs, μ—time interval between j + 1 and j deliveries. After establishing the nature of the random variables distribution, it is necessary to simulate the process for different values of the initial stock (from the minimum to the maximum possible) of the adopted planning period T and to determine the dependence of the costs on the stock size. Calculation, taking into account the adopted criteria and constraints, allowed to determine the optimal value of the stockpile. The data received as a result of modeling for the volume of monthly consumption of reinforced concrete piles 650 m3 are presented in Table 5. The dependence of total costs on the value of the initial stock of building structures is shown in Fig. 1. The size of the optimal stock of reinforced concrete piles is 200m3 . Preliminary calculations show that the use of the considered method of stock definition allows to reduce their size by 25–35% compared with the current level with a significant increase of the reliability of construction and installation works.
4 Conclusion The task of material and technical support of construction is to ensure uninterrupted and complete supply of construction in accordance with the approved production program and the projected schedule of construction and installation works. The model suggested by the authors enables to solve the problem of optimizing the size of material resources production stock, raising the uniformity of supplying
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working integrated and specialized teams, reducing the amounts of circulating assets in construction. In the future, the necessity of approbation of the algorithm developed by the authors on the regional capital construction sites is considered. Thus, the presented results of the study can predict the state of construction production in the studied time period and optimize the management decisions by choosing the most rational strategy of material and technical supply with material resources.
References 1. Sokolnikov V, Osipenkova I, Stupakova O, Nurgalina R (2020) IOP Conf Ser Mater Sci Eng 918(1):012015. https://doi.org/10.1088/1757-899X/918/1/012015 2. Siu MFF (2019) Facilities 37(5/6):292–312. https://doi.org/10.1108/F-04-2018-0057 3. Ardila F, Francis A (2020). Front Built Environ. https://doi.org/10.3389/fbuil.2020.00128 4. Bozejko W, Hejducki Z, Wodecki M (2019) Arch Civil Mech Eng 19(1):194–204. https://doi. org/10.1016/j.acme.2018.09.010 5. Xu X, Wang J, Li CZ, W. Huang, Xia N (2018) Autom Constr 95:20–34. https://doi.org/10. 1016/j.autcon.2018.07.026 6. Kasaev BS, Razakov AA (2015) Stud Eng Technol 2(1):111–123. https://doi.org/10.11114/set. v2i1.992 7. Tabrizi BH, Ghaderi SF, Haji-Yakhchali S (2017) Int J Simul Process Model 28(2):67–82. https://doi.org/10.6186/IJIMS.2017.28.2.1 8. Hosseini MR, Chileshe N, Rameezdeen R, Lehmann S (2014) Int J Constr Eng Manage 3(3):75– 90. https://doi.org/10.1177/0734242X15584842 9. Koulinas KG, Xanthopoulos SA, Tsilipiras TT, Koulouriotis DE (2020) Buildings 10(8):134. https://doi.org/10.3390/Buildings10080134 10. Siu M-FF, Lu M, Abourizk S (2016) J Constr Eng Manage 142(1). https://doi.org/10.1061/ (ASCE)CO.1943-7862.0001027 11. Demidenko O, Alekseev NE (2016) Vestnik SibADI 6(52):61–66 12. Vitvitskiy EE, Fedoseenkova ES (2018) IOP Conf Ser Earth Environ Sci 7:072013. https://doi. org/10.1088/1755-1315/194/7/072013 13. Yudina A, Sychov S, Gaido A (2020) Archit Eng 5(2):32–37. https://doi.org/10.23968/25000055-2020-5-2-32-37 14. Vorobyov V, Manakov A, Yanshina I, Repina I (2020) Adv Intell Syst Comput 1116:691–706. https://doi.org/10.1007/978-3-030-37919-3_69 15. Abramov AD, Ilinykh AS, Galay MS, Sidorov JS (2017) Mater Sci Forum 906:50–55. https:// doi.org/10.4028/www.scientific.net/MSF.906.50 16. Sergeyev VI (2016) Transp Telecommun 17(2):100–110. https://doi.org/10.1515/ttj-2016-0009
Rationale for the Machine Complex Performance Sergey Kuznetsov , Ksenia Bogomolova , and Natalya Shipilova
Abstract While analyzing the hydro-transport complexes operation, the data on the working time losses duration in real working conditions have been collected. The logical and mathematical processing of the statistical information is accomplished. The parameters of working time losses caused by: dredger malfunction; power outrage; dredger moving; anchor relaying; professional repair; other reasons; work on the map; work on the main pipeline; work on the floating pipeline; repair of auxiliary equipment; maintenance of the dredger; and dredger cleaning are studied. To estimate the significance of factors, it was proposed to use the model of the coefficient of complexes’ use in terms of time. This model enables assessment of significance of indices of complexes, kits and separate machines under any operation conditions. This will make it possible to predict the duration and cost of production at the design stage. The article determines the indicators of hydro transport complexes operation losses. A comprehensive assessment of the dredge operation in real production conditions is considered using the indicators of loss of working time, which makes it possible to predict their performance. More precise definition of working time under real conditions will allow planning rhythmical equipment operation with more substantiation and decreasing operation cost of machines. A method for assessing the losses of working time of systems, complexes, sets, individual machines, and devices is proposed. Keywords Database · Loss of working time · Dredgers
S. Kuznetsov (B) Siberian Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] K. Bogomolova JSC “Sibgiprotrans”, 15, Vokzalnaya Magistral, Novosibirsk 630099, Russia N. Shipilova Kuban State Technological University, 2, Moskovskaya Street, Krasnodar 350072, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_9
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1 Introduction Databases of full-scale testing of systems, complexes, kits and individual machines contribute to optimization of organizational and technological solutions during construction, reconstruction and repair of facilities under real production conditions [1–4]. In the Siberian State University of Railway Transport, a database of the results of field observations of hydro-transport complexes operation is created. In this base the data on exploitation years of dredgers are stored. Table 1 illustrates the indicators of hydro-transport complexes operation [1]. These data with the help of regression analysis can determine the importance of loss of working time of each factor. The proposed method makes it possible to determine the relative importance of each factor when using the samples of complexes’ performance indicators obtained with the help of: – – – –
process models; models of machines, kits and complexes operation; the results of field operation tests at actual objects; models of complexes performance.
At creation of databases mathematical and logical check of series was carried out [5, 6]. Application of “Model” program [5, 6] allowed to build models, make analysis of model residuals and check significance of models. Table 1 Complex performance Indicator
Factor
Coefficient
Calendar labor time reserve
Tf
Operation time to failure
Tn
Operation time
Tp
K t = T p /T f
Idle time
Tl
K l = Td /T f
Dredger cleaning
T l01
K l01 = Tl01 /T f
Chart work
T l02
K l02 = Tl02 /T f
Professional repair
T l03
K l03 = Tl03 /T f
Anchor relocation
T l04
K l04 = Tl04 /T f
Power outrage
T l05
K l05 = Tl05 /T f
Auxiliary equipment repair
T l06
K l06 = Tl06 /T f
Work on a floating slurry line
T l07
K l07 = Tl07 /T f
Work on the main slurry line
T l08
K l08 = Tl08 /T f
Dredger movement
T l09
K l09 = Tl09 /T f
Dredger maintenance
T l10
K l10 = Tl10 /T f
Dredger malfunction
T l11
K l11 = Tl11 /T f
Other causes
T l12
K l12 = Tl12 /T f
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2 Research Methods To establish the relative importance of factors, we used the samples of performance indicators for machines, sets and complexes of machines obtained with the help of: – probabilistic models of technological processes; – the results of field tests of machines operation; – model for calculating the performance of machines, sets, complexes and systems. The use of normalization coefficients of the model in comparing the influence of factors and establishing the relative importance of each of them was made by the formula: bi = ai
Sxi S yi
where bi is the regression equation coefficient after normalization; ai is theregression equation coefficient before normalization; S xi is the root mean square error of the variable on the axis X; S yi is the root mean square error of the Y-axis variable. The coefficient of relative loss of the complex working time was determined by the formula: K li =
Tli Tc
where T c is the operating time of the complex. Checking the inadequacy of the model assuming that the model is correct was performed using the mean square error S 2 , as estimates of the magnitude σ 2 . If these values differed by an order of magnitude or more, it was concluded that the model was inadequate [7–9]. General F-criterion enables to determine the statistical significance of the model. It is defined as follows: F=
Mean square due to regression Mean square due to residual
The significance of the regression model was checked by comparing the total F-criterion to a pre-selected percentage point of the tabulated value of the total Fcriterion. The regression model is statistically significant when the value of the total F-criterion of the model is greater than the tabulated value [10, 11]. The database of field tests enabled us to build a model of dredger utilization factor by time and calculate the importance of each factor in the model. Then calculate probability density distribution of factors and determine their belonging to the appropriate distribution law. Out of 12 considered indicators of working time losses of the dredger, 9 are subject to the normal distribution law. Table 3 gives indices of working time losses of hydraulic transport complexes.
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3 Research Results Significance of each factor in the multifactor model of the time use factor of the complex (Kt = 1 – Kl04 – Kl05 – Kl08 – Kl07 – Kl12 – Kl10 – Kl03 – Kl09 – Kl06 – Kl02 – Kl11 – Kl01 ) is presented in Table 2 [1]. Table 3 shows the significance of the factors of working time losses in the operation of hydraulic transport complexes in the real production conditions of Western Siberia. Table 2 Model of complex usage rate by time Model
Significance of the factor %
Factor
Kt = 1
Time utilization rate
−K l04
2.01
Anchor relocation
−K l05
2.56
Power outrage
−K l08
2.26
Work on the main slurry line
−K l07
7.43
Work on a floating slurry line
−K l12
7.16
Other causes
−K l10
3.85
Dredger maintenance
−K l03
6.41
Professional repair
−K l09
4.82
Dredger movement
−K l06
5.73
Auxiliary equipment repair
−K l02
20.89
Chart work
−K l11
23.64
Dredger malfunction
−K l01
13.23
Dredger cleaning
Table 3 Idle time indicators of the complexes Indicator
Significance of the factor, %
Anchor relocation
2.01
Work on the main slurry line
2.26
Power outrage
2.56
Dredger maintenance
3.85
Dredger movement
4.82
Auxiliary equipment repair
5.73
Professional repair
6.41
Other causes
7.16
Work on a floating slurry line
7.43
Dredger cleaning
13.23
Chart work
20.89
Dredger malfunction
23.64
Rationale for the Machine Complex Performance
97
The data are derived from a multifactor mathematical model of the dredge time use factor. Tables 4 and 5 show the parameters of working time losses sampling. Loss ratios of hydro-transport complexes are shown in Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12. Losses of work time of the complexes are caused by: cleaning (Fig. 1); chart work (Fig. 2); professional repairs (Fig. 3); work on the floating slurry pipeline (Fig. 4); work on the main slurry line (Fig. 5); dredge movement (Fig. 6); anchor relocation (Fig. 7); lack of power (Fig. 8); auxiliary equipment repairs (Fig. 9); dredge maintenance (Fig. 10); dredge failure (Fig. 11) and other causes (Fig. 12). Table 4 Parameters of working time losses sampling of complexes: cleaning (Kl01); chart work (Kl02); professional repair (Kl03); work on a floating slurry line (Kl04); work on the main slurry line (Kl05); dredger movement (Kl06) Indicator
K l01
K l02
K l03
K l04
K l05
K l06
Minimum factor value
0.015
0.057
Maximum factor value
0.100
0.120
0.016
0.007
0.009
0.010
0.040
0.010
0.013
0.040
Mode
0.059
0.085
Median
0.057
0.088
0.025
0.009
0.010
0.022
0.027
0.0085
0.011
0.023
Sampling asymmetry
−0.09
−0.12
0.16
0.00
0.20
0.0076
−0.56
Sampling excess
−0.20
−0.45
−0.60
−1.13
−1.14
Sample mean value of the factor
0.056
0.089
0.027
0.0086
0.011
0.024
Mean square deviation of the factor
0.017
0.013
0.0053
0.0007
0.0013
0.0087
Deviation risk from the average value
0.013
0.011
0.0043
0.0005
0.0012
0.0074
Variation coefficient
29.21
15
27,942
11,293
35.5
Calculated value of the Pearson criterion
0.048
0.025
0.06
0.107
0.103
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 0.28 criterion
0.30
0.43
0.42
0.79
0.66
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
0.025
0.018
0.06
0.107
0.106
19.2
Normal distribution
1.36
0.019
Logarithmically normal distribution Calculated value of the Pearson criterion
0.048
(continued)
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Table 4 (continued) Indicator
K l01
K l02
K l03
K l04
K l05
K l06
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 0.27 criterion
0.36
0.41
0.41
0.78
0.68
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
1.36
Calculated value of the Pearson criterion
0.453
0.28
0.234
0.23
0.11
0.071
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 1.93 criterion
1.60
1.52
1.53
0.96
0.68
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
1.36
Calculated value of the Pearson criterion
1,875,214
0.441
1.256
2.38
1.63
20,506
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 2.169 criterion
1.13
1.26
1.36
2.00
2.97
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
Uniform distribution
The Weibull distribution
1.36
Table 5 Selected loss of working time of the complexes: anchor relocation (Kl07); power outrage (Kl08); auxiliary repair (Kl09); dredge maintenance (Kl10); dredge malfunction (Kl11); other causes (Kl12) Indicator
K l07
K l11
K l12
Minimum factor value
0.028
K l08 0.0063
0.0098
K l09
K l10 0.0075
0.066
0.023
Maximum factor value
0.036
0.012
0.033
0.026
0.129
0.037
Mode
0.029
0.009
0.020
0.017
0.101
0.031
Median
0.032
0.010
0.020
0.017
0.100
0.030
Sampling asymmetry
0.048
−0.18
0.17
Sampling excesses
−1.29
−1.21
−0.65
Sample mean value of the factor
0.032
0.010
0.021
Mean square deviation of the factor
0.0024
0.0018
0.0055
0.06
−0.21
−0.26
−0.34
−0.51
−0.50
0.016
0.101
0.031
0.0036
0.014
0.0032 (continued)
Rationale for the Machine Complex Performance
99
Table 5 (continued) Indicator
K l07
Risk of deviation from the average value
0.0021
Variation coefficient
21,732
K l08 0.0016 18.9
K l09 0.0044 26.8
K l10 0.0029 21.7
K l11
K l12
0.011
0.0026
44,241
15,980
0.01
0,056
Normal distribution Calculated value of the Pearson criterion
0.17
0.15
0.037
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11,02
Komogorov-Smirnov criterion of 1.17 agreement
0.98
0.50
0.43
0.37
0,50
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
0.042
0.011
0.056
1.36
0.042
Logarithmically normal distribution Calculated value of the Pearson criterion
0.17
0.15
0.037
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 1.15 criterion
0.98
0.52
0.42
0.42
0.52
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
1.36
Calculated value of the Pearson criterion
0.079
0.087
0.16
0.43
0.24
0.28
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Kolmogorov–Smirnov agreement 0.73 criterion
0.98
1.44
1.78
2.02
1.86
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
1.36
Calculated value of the Pearson criterion
1.54
0.73
1823
20.9
0.28
0.22
Tabular value of the Pearson criterion
11.02
11.02
11.02
11.02
11.02
11.02
Komogorov-Smirnov criterion of 2.21 agreement
1.92
2.03
1.54
1.06
1.13
Critical values of the criterion of agreement K-C
1.36
1.36
1.36
1.36
1.36
Uniform distribution
The Weibull distribution
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Fig. 1 Probability distribution density of dredger cleaning duration
Fig. 2 Probability density distribution of the working time on the floating slurry line
Fig. 3 Probability density distribution of the working time on the chart
Rationale for the Machine Complex Performance
Fig. 4 Probability distribution density of working time on the main slurry line
Fig. 5 Probability distribution density of dredger repair duration
Fig. 6 Probability density distribution of the dredge movement duration
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Fig. 7 Probability density distribution of anchor relocation duration
Fig. 8 Probability density distribution of dredger maintenance duration
Fig. 9 Probability density distribution of power outage duration
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Fig. 10 Probability distribution density of dredger failure duration
Fig. 11 Probability density distribution of auxiliary equipment repair duration
Fig. 12 Probability density distribution of other causes duration
4 Results and Discussion The studies have shown that out of 12 considered indicators of working time losses of the dredger, 9 correspond to the law of normal distribution.
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5 Conclusion 1. The models for estimation of significance of working time losses in hydraulic transport complexes, which allowed us to carry out forecasting of the hydro transport complexes’ main performance indicators, are proposed. 2. The proposed toolkit for constructing models of loss of working time when justifying the performance of hydro-transport complexes to make management decisions with reasonable, obtains real reliability. 3. The conducted research of confidence intervals allowed establishing the limits of models’ application. This universal method can be used when assessing the specific area of models of complexes, sets and machines’ application.
References 1. Kuznetsov SM (2015) Theory and practice of forming sets and systems of machines in construction. Direct-Media, Moscow, Berlin, p 271. https://doi.org/10.23681/375250 2. Zaitsev AV (2021) Actual Probl Modern Econ 1:144–155. https://doi.org/10.34755/IROK. 2021.72.43.020 3. Glotov VA, Kuznetsov SM, Zaitsev AV (2019) Substantiation of performance indicators for straightening and tamping machines of cyclic and continuous action. Direct-Media, Moscow, Berlin, p 169. https://doi.org/10.23681/567509 4. Kuznetsov SM, Kuznetsova KS (2020) Justification of the reliability of machinery and equipment, textbook. Direct-Media, Moscow, Berlin, p 164. https://doi.org/10.23681/595966 5. Anferov, VN (2015) Design of drives of hoisting-and-transport machines based on spiroid gears with a guaranteed wear resource. Direct-Media, Moscow, Berlin, p 214. https://doi.org/ 10.23681/429387 6. Anferov VN, Zaitsev AV (2020) Vestnik IzhSTU, pp 31–37. https://doi.org/10.22213/24131172-2020-2-31-37 7. Anferov VN, Tkachuk AP, Shishlova IV (2019) Modern technologies. Syst Anal Model 51–57. https://doi.org/10.26731/1813-9108.2019.4(64).51-57 8. Anferov VN, Tkachuk AP, Zaitsev AV (2017) Calculation of the resource of the spiroid gear in the drive of the cable assembly mechanism of the electric forklift. Vestnik IzhSTU 20(20):24– 28. https://doi.org/10.22213/2413-1172-2017-2-24-28 9. Kuzmin AV, Anferov VN (2018) Computational and experimental evaluation of self-braking in the design of worm-type gears. Direct-Media, Moscow, Berlin, p 78. https://doi.org/10.23681/ 494232 10. Glotov VA, Glotov NV, Trescheva ED, Legalova IV (2020) Issues Sustain Develop Soc 8:247– 253. https://doi.org/10.34755/IROK.2020.92.11.054 11. Glotov VA, Glotov NV, Trescheva ED, Legalova IV (2020) Actual Probl Modern Econ 9:405– 410. https://doi.org/10.34755/IROK.2020.20.76.055
Experimental Studies of Fiber Concrete Samples Under Cyclic Load Natalia Pichkurova
and Maria Novitskaya
Abstract Concrete and reinforced concrete structures have been the basis of construction all over the world for many decades. However, concrete is an elastic– plastic (brittle) material and cracking occurs when its fibers are stretched. The results of the extensive research of Russian and foreign specialists have shown that the problem of early cracking of concrete can be solved by reinforcing its stretched fibers with steel rebar or dispersed reinforcement. At the same time, fiber concrete (dispersed reinforced concrete) opens up the possibility of creating structures with predetermined properties. Analysis of numerous studies has shown that fiber concrete structures are designed for both static and dynamic loads. However, the question of the fiber concrete behavior under cyclic load (which is typical for the majority of railway infrastructure structures) has not been fully studied. In the presented article, the behavior of fiber concrete specimens under cyclic load is investigated. The specimens are reinforced with steel, polypropylene and basalt fiber. The results of tests are plotted as a function of cycles’ number for load, fatigue curves in each series. Experimental tests have shown that the sample reinforced with steel fiber has the highest strength characteristics under cyclic loading. The sample reinforced with polypropylene fiber has the lowest strength characteristics. Keywords Dispersion-reinforced concrete · Steel fiber · Basalt fiber · Polypropylene fiber · Cyclic loads
1 Introduction Many load-bearing structures of railway infrastructure facilities are in a complex stress–strain state. In addition to static loads, they are often subjected to dynamic N. Pichkurova (B) Siberian State Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] M. Novitskaya “Sibgiprotransput” - Affiliate JSC “Roszheldorproekt”, 8 D., Shamshurin Street, Novosibirsk 630004, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_10
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(including impact) or cyclic loads. Therefore, such structures should have high operational characteristics—wear resistance, tensile and compression strength, crack resistance, corrosion resistance, frost resistance, etc. This problem can be eliminated by using fiber concrete—dispersion-reinforced concrete. The experience of fiber concrete application in Russian and foreign construction industries [1–7] indicates its significant advantages: – reduction of construction costs when using fiber for reinforcement instead of wire mesh or framework; – consumption of concrete using fiber is much lower; – fiber concrete does not lose its technical characteristics, as due to the fiber the material becomes viscous; – fiber can be used in both gas and foam concrete structures; – fiber concrete is resistant to temperature influences, moisture-resistant and frostresistant; – fiber concrete has good adhesive qualities; – fiber concrete has less weight compared with conventional concrete. At present there is the following classification of fibers used for fiber concrete reinforcement [8, 9]: 1. by elastic modulus: – High-modulus fibers: steel, carbon, glass, etc., – Low-modulus fibers: polypropylene, viscose, etc.; 2. according to their origin: – natural fibers: basalt, asbestos, wool, etc., – Artificial fibers: polyamide, viscose, etc.; 3. according to the basic material: – metallic fibers: steel, – 3. basic material: metallic fibers: steel, non-metallic fibers: mineral, synthetic. Fibre concrete has a high structural toughness, thereby acquires a significant resistance to dynamic loads, including impact [10, 11]. For example, in the USA, the state of Nevada, a research on the production of fiber concrete pavements of airfield runway and comparison of these pavements with reinforced concrete pavements was conducted. The thickness of conventional concrete was 25.4 cm, and fiber concrete— 15.2 cm, which is 40% less. It was noted that after 700 cycles of loading, i.e., take-offs and landings, the concrete coating was out of service, while the fiber concrete coating withstood about 4500 cycles. Thus, it can be concluded that the durability of fiber concrete coating is 6.4 times higher than the conventional concrete coating durability. However, the analysis of the studies dedicated to the fiber-crete structures’ behavior under cyclic loads showed that this question hadn’t been studied sufficiently. Below the experimental research results of fiber-concrete specimens under cyclic loading are given.
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2 Research Methods The following materials were used to perform the experimental studies: 1. Portland cement CEM I 42,5H, producer JSC “Achinsk cement”. 2. Fine aggregate—Obskoy sand (cement-sand ratio C/S = 1/2). Total percentage residue by weight on a sieve No. 0.315 was 60%, on a sieve 0.16–40%. 3. Water. 4. Crushed stone with a fraction size—5–10 mm. 5. High-performance superplasticizer DR8200 (concentration 0.4%)—to improve the adhesion of the mixture. 6. Slag 7. Fibers: a) steel fiber with a length of 35 mm and a thickness of 0.7 mm (Fig. 1); b) polypropylene fiber with length of 12–15 mm (Fig. 2); c) basalt fiber with length from 6 to 24 mm (Fig. 3). Research scope: Series No. 1—6 prisms containing steel fiber. Series No. 2—6 prisms containing polypropylene fiber. Series No. 3—6 prisms containing basalt fiber. To determine the cube strength of concrete, 3 cubes of size 10 × 10 × 10 cm were poured (according to the test results, the class of concrete in terms of compressive strength B40). The dimensions of the samples: fiber concrete prisms—40 × 40 × 160 mm (Fig. 4). The consumption of materials for each batch was determined during the preparation of the fiber concrete mixture. The volume of each mix was 5 kg. As a basis was taken the control composition of the heavy concrete without adding fiber: 376 kg/m3
Fig. 1 Steel fiber
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Fig. 2 Polypropylene fiber
Fig. 3 Basalt fiber
Fig. 4 Forms for three sample-prisms
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cement, 94 kg/m3 slag, 783 kg/m3 sand, 1050 kg/m3 crushed stone, 1.9 kg/m3 additive (concentration of 0.4%), 115 l/m3 water. Steel fiber was introduced into the concrete mix in an amount of 20 g per mix, polypropylene fiber—26 g per mix; basalt fiber—6 g per mix. Cement and aggregates were mixed dry until a homogeneous mixture, then fibers were added, mixing with the required amount of water and stirring until a homogeneous mass was formed. After making, the samples were stored in molds for 24 h. Further the samples were unmolded at the expiration of time and laid in a chamber with water for curing within 14 days. Curing conditions were ensured at a temperature of 20 ± 2° C and a humidity of 95 ± 5%. The technological scheme of dispersion-reinforced concrete preparation depending on the type of different fibers is shown in Fig. 5.
Fibers Steel
Polypropylene
Dispensing
Dispensing
Water mixing
Water mixing
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Stirring dry
Basalt
Stirring 1. Cement 2. Water
Dispensing Dispensing
3 Crushed stone
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6 Superplasticizer
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The fiber concrete samples were tested with a tensile testing machine. Before cyclic loading tests, the destructive load of prism samples with dispersed reinforcement was determined, for this purpose three samples from each series were tested. Specimen-prism was placed between the press supports, centered along the geometrical axis, and then the load was applied until destruction at a constant rate of load rise (0.05 ± 0.01) MPa/s.
3 Research Results As a result of processing the experimental data, graphs of cyclic loading for sampleprisms reinforced with steel, polypropylene and basalt fiber were plotted (Figs. 6, 7 and 8). The graph of Fig. 6 shows the cyclic load test of series No. 1 specimens. One cycle consists of loading and unloading the specimen. The load at which the specimens fail ranges from 1.3 to 2.2 kN. The test results of series No. 1 show that when the maximum load is equal to 0.7 of the destructive loads, the number of cycles was 100. When the maximum load was reduced by 10–15% the sample withstood the number of cycles 1.4 times more (sample No. 3). The sample No. 2 was loaded in steps, the load was increased every 20 cycles. After 40 cycles, fatigue failure occurred.
Fig. 6 Dependence of the number of cycles on the load for samples-prisms series No. 1
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Fig. 7 Dependence of the number of cycles on the load for specimens-prism series No. 2
Fig. 8 Dependence of the number of cycles on the load for prism samples’ series No. 3
The graph in Fig. 7 shows the test of the series No. 2 specimen. Compared to the graph in Fig. 7, it should be noted that the specimens of series No. 2 have lower strength characteristics. The load at which the specimens failed was from 0.8 to 1.5 kN, which is 2.5 times less than the failure load of specimens of series No. 1. It should also be noted that specimen No. 3 withstood 60 load-unload cycles, but it was loaded with 0.8 kN.
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The second sample was loaded-unloaded with loads of 1.0–0.5 kN. The specimen withstood 12 cycles, indicating that it was either unevenly reinforced or insufficiently reinforced. The third sample was loaded in steps, and the load was increased every 20 cycles. When the load was increased after 40 cycles, fatigue failure occurred, similar to specimen No. 2 of series No. 1 (only at a lower load). Figure 8 shows the test of specimen series No. 3. Comparing the research results, it should be noted that the samples reinforced with basalt fiber are more resistant to the action of cyclic load (samples of series No. 3). The load at which the failure of the samples was from 1.2 to 2.5 kN, which is 1.1 times higher than the failure load of steel fiber-reinforced samples and 2 times higher than the failure load of polypropylene fiber-reinforced samples. Therefore, further comparison of specimens of series No. 3 was carried out with specimens of series No. 1. The first sample of series No.3 withstood 120 cycles, of which 110 cycles the sample was loaded with 1.5–1.0 kN, further the load was reduced by 10% and made 1.0–0.5 kN. The specimen endured another 10 cycles and then fatigue failure occurred. The second sample was loaded in stages, and the load was increased every 20 cycles. Increasing the loading after 60 cycles to 2.5 kN, the specimen endured one cycle, and then a crack appeared. Comparing the results of tests with the results of tests of specimen No. 2 of series No. 1, it should be noted that the number of cycles the specimen reinforced with basalt fiber endured was 1.5 times more. The third specimen was loaded-unloaded with loads of 1.0–0.5 kN. The sample endured 8 cycles; then, at increase of the load up to 2.2 kN brittle (sudden) destruction happened. Stresses (MPa) were determined in order to plot the fatigue curve on the basis of the obtained results of the loads. Figures 9, 10 and 11 show fatigue curves for sample series No. 1 (reinforced with steel fiber), No. 2 (reinforced with polypropylene fiber) and No. 3 (reinforced with basalt fiber). The fatigue curves show that the maximum stress at which the specimens fail decreases significantly as the number of cycles increases. Steel fiber reinforced specimens withstand the highest number of cycles; therefore, they are more enduring compared to specimens of series No. 2 and No. 3. The samples of series No. 2 have low endurance limit, even at low stresses. The samples of series No. 3 are of intermediate position as they endure less cycles than the samples of series No. 1, but the failure occurs at higher stress (37.89 MPa) than the samples of series No. 1 (34.8 MPa).
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Fig. 9 Fatigue curve for No. 1 sample series
Fig. 10 Fatigue curve for No. 2 sample series
Fig. 11 Fatigue curve for No. 3 sample series
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4 Conclusions The conducted experimental studies showed that high strength characteristics and endurance under cyclic loads have specimens made with steel and basalt fibers. The fatigue curves show that the maximum stress, at which the specimens fail, decreases significantly with increasing cycle number. The samples reinforced with steel fibers withstand the highest number of load cycles.
References 1. Klyuev SV (2012) Eng Constr J 8:6–10. https://doi.org/10.5862/MCE.34.9 2. Klyuev AV (2011) Bulletin of BSTU named after V.G. Shukhov 2:60–63. http://dspace.bstu. ru/handle/123456789/1 3. Haktanir T, Ari K, Altun F, Atis CD, Karahan O (2006) Cement Concr Compos 28(9):811–816. https://doi.org/10.1016/j.cemconcomp.2006.06.002 4. Hoff CC (1986) Use of steel fiber reinforced concrete in bridge ducts and pavements. In: Steel fiber concrete. Elsevier Applied Science Publishers Ltd., England, pp 67–108 5. Savastano JH, Santos SF, Radonjic M, Soboyejob WO (2009) Cement Concr Comp 31(4):232– 243. https://doi.org/10.1016/j.cemconcomp.2009.02.006 6. Naser MZ, Hawileh RA, Abdalla JA (2019) Eng Struct 198:109542. https://doi.org/10.1016/j. engstruct.2019.109542 7. Travush VI, Konin DV, Krylov AS (2018) Mag Civil Eng 1:90–100. https://doi.org/10.18720/ MCE.77.8 8. Talantova KV, Mikheev NM, Polzunovsky Vestnik 1:194–199. https://polzvestnik.altstu.ru/arc hive_polz_vestnik/ 9. Rasheed MHF, Agha AZS (2012) Eng Tech J 30(6):974–987. https://scholar.google.com/citati ons?user=7WZefRQAAAAJ&hl=fil 10. Morozov VI, Pukharenko YV (2014) Vestnik MGSU 3:189–196. https://doi.org/10.22227/ 1997-0935.2014.3.189-196 11. Do TMD, Lam TQK (2021) Mag Civil Eng 102(2):10207. https://doi.org/10.34910/MCE.102.7
Application Effectiveness Analysis of the Thin-Walled Building Components for Transport Infrastructure Facilities Natalya Pichkurova , Boris Prosyanikov , Sergey Kolankov, and Tatiana Pimshina
Abstract At the present time, light steel thin-walled structures are widely used in the world practice. Due to the availability of production, application of high-strength steel and aluminum alloys, installation speed and reduction of construction costs, starting from the zero cycle, such structures can be used both for low-rise and production facilities, in particular for transport infrastructure facilities (overpasses, bridges, service and technological facilities, etc.). However, the connections of elements of the thin-walled structures’ elements require more in-depth study. This paper presents some studies on the effectiveness of thin-walled structures due to the use of tongue and groove joints of metal profiles. This type of connection presupposes the use of special fasteners, which provide a receiving recession on one side of the overlapping sheet elements. On the opposite side, the fastener has a thickening, through which the tension of the bolt is made by punching the connecting metal. The bearing capacity of dowel-bolt connections is determined by the inclusion of an additional factor in the work of the connection (bearing stress—shear key), which does not participate in the work of conventional bolt junctions. Model experiments carried out with the Ansys Ls-Dyna PC have shown that the keyed-bolt junction is a promising method for increasing the reliability of steel structures in general due to an increased safety margin and deformability. Keywords Light steel thin-walled structures · Key-bolt junction · Model experiment
N. Pichkurova (B) · B. Prosyanikov Siberian Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] S. Kolankov Emperor Alexander I St. Petersburg State Transport University, 9, Moskovsky Avenue, Saint-Petersburg 190031, Russia T. Pimshina Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Square, Rostov-on-Don 344038, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_11
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1 Introduction Light steel thin-walled structures are currently one of the most progressive trends in construction. Technology of light steel thin-walled structures belongs to energyefficient methods of construction and has been used for many decades in Europe, Japan and the USA—the countries which experienced a boom of fast construction of low-rise buildings in the postwar period [1–6]. The main advantages of using light steel thin-walled structures are: 1. Construction speed. One of the main advantages of this technology. High speed of project assembly is due to the use of lightweight structures made of durable steel. 2. Economic efficiency. According to the rough estimates, the cost of construction and finishing materials is 10–15%. Moreover, the technology of light steel thinwalled structures requires less steel consumption (25–50%), which noticeably reduces the total amount of construction costs. 3. Strength. Thin-walled galvanized profiles have a unique combination of strength and are easy to use. 4. “Dry” type of construction. No liquid materials relieve the construction from moisture problems and the accompanying dampness and mold. 5. Lightness. Low weight of constructions allows to reduce loads on the base, that in general influences on the choice of foundations of low-loaded types. 6. Environmental friendliness. Construction of buildings practically does not have negative impact on the environment. The above-mentioned advantages of thin-wall structures are especially important when designing transport infrastructure facilities (various service buildings and structures, bridges, overpasses, crossings, etc.). The most suitable field of application for such structures is determined on the basis of structural conditions (manufacturing, corrosion protection, etc.), strength properties and static conditions (span size, load, etc.), economic indicators, operating conditions and aesthetic perception (Fig. 1). The types of element connections for light steel thin-walled structures [7] are as follows:
Fig. 1 Frame structure made of light steel thin-walled structures
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by welding; by means of gluing; by means of self-tapping screws, rivets and bolts [8, 9]; combined types (glue-bolt connections, welded adhesives, etc.).
Welded joints for thin-walled structures are rarely used in Russia despite the fact that the types of possible welded joints are highlighted in the domestic regulatory documents. Rare use is connected with the fact that in most cases the thickness of metal profiles does not exceed 2.5–3 mm, which significantly increases the risk of through “weld-through” of the structure. The analysis of foreign studies [7] showed that in Europe such connections are used quite widely. Nevertheless, for joining thin sheet metal there should be an appropriate technique and technology. In most cases, screw connection provides non-disassembled section. In Russia this connection is considered to be one of the most widespread, but the use of self-tapping screws is limited by their location in the nodes of the sections. As a consequence, with an insufficient number of screws in the node connection, its load-carrying capacity is low, which limits the use of such connection for large spans. It is possible to increase the carrying capacity of node connections by using bolted friction shear-resistant connections and bolted friction connections with a distribution pad. A promising way to increase the load-carrying capacity of the sheet steel element connection is a bolted junction, which is made with metal punching near the bolted area [10]. In this type of connection special fasteners are used, which provide an acceptance recess on one side of the overlapping sheet elements being connected. On the opposite side the fastening element has a thickening, by means of which at bolt tensioning pushing of connected metal into receiving cavity is performed. Thus, the bolt connection additionally includes a mechanical engagement of the bent edges of the pierced metal area, resulting in a keyed-bolt junction.
2 Research Methods According to the results of the studies carried out in the field of key-bolt connections, it can be concluded about the multistage nature of their work. The increase in the resistance to buckling is due to the compression stress arising on the opposite side of the crumpled edge of the hole as a result of the shear resistance of the punched metal mechanical adhesion area. Thus, a more uniform distribution of stresses on the holes edges is achieved, which leads instead of destruction to the section ovalization (displacement of the crumpled hole in this case can reach 12–14 mm instead of 3– 5 mm). Such a conclusion is extremely important for increasing the reliability of joints, especially for the objects operated in seismically hazardous areas or requiring calculation on the progressive destruction. Experimental (model) research was carried out in the Ansys Ls-Dyna program complex using the finite-element method. The purpose of the study was to analyze
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the effect of punching in the keyed-bolted connection (Experiment 1) on the structural reliability improvement in comparison with a conventional bolted connection (Experiment 2). Figure 2 shows the keyed-bolt junction. The same elements were used for the conventional connection except for the washer package, which was replaced by two flat washers on the top and bottom. Referring to Fig. 3, the washers included in the package have the following purpose: 1. The inner washer (5)—provides the pushing of the profiles into the inside of the package;
Fig. 2 Model of a key-bolt junction: 1—elements to be connected; 2—bolt head with bolt rod; 3—nut; 4—levelling washer; 5—inner washer; 6—power washer package; 7—outer washer
Fig. 3 Partitioning of the key-bolt junction model into finite elements
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2. The outer washer (7)—provides the necessary receiving recess for the metal being punched through; 3. Power washer package (6)—provides the force required for punching through to the profile metal; 4. Leveling washer (4)—serves as a criterion for correctness of connection assembly (full contact of washer edge with profile surface indicates uniform piercing); it prevents from premature temptation of inner washer position in the process of connection operation. When specifying the material properties, the elements were divided into 2 groups. The first group included bolt, nut and washers. For this group of materials, the model—“bilinear isotropic” was selected, in order to exclude the fracture of the finite elements. The second group included destructible materials—bottom sheet and top sheet. When assigning the properties to these elements, the “plastic kinematic” model was adopted, which allows the finite elements to collapse when they reach their maximum deformations. When the first finite element in the upper or lower sheet was turned off, the maximum total deformations of the joint were determined. The general model and the bolt model are shown in Figs. 3, 4 and 5. The metal punching in the experiment was modeled from the bolt pre-tensioning. The sheets in the experiment were given a thickness of 1.5 mm. The steel of the sheets was C255 with a standard resistance Ryn = 255 N/mm2 . The washers were modeled M12 with a thickness of 3 mm with different outer diameters, except for the outer M30 with a thickness of 4 mm, to provide an acceptance recess. The standard resistance of the washers is Ryn = 315 N/mm2 . High-strength M12 bolt, accuracy
Fig. 4 Partitioning of a bolt into finite elements
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Fig. 5 Partitioning sheets into finite elements
class B, strength class 12.9. Friction coefficient is taken as µ = 0.25. Modulus of steel elasticity E = 2.1 · 105 . The experiment was conducted in two stages. The first stage was to load the model along the bolt axis in order to obtain the penetration of metal near the bolt area (Fig. 6). After the first stage, all loads were removed while maintaining the intermediate results of the model. In the second stage, the load was applied evenly to the sheet end nodes. To eliminate dynamic effects, the model was loaded gradually for 4 s. The maximum value of applied force was 3750 kg. In the second experiment, a conventional LSTWC bolted junction with bolt pretensioning was assembled. The characteristics of this model are the same as the previous one, only there is no washer package for pushing through the hole edges. The experiment was also conducted in two stages. But in the first stage, loading of the
Fig. 6 Result of the experiment (first stage)
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model along the bolt axis was created in order to obtain a friction-cutting connection with the same friction coefficient as in the previous case for maximum similarity with the first model.
3 Research Results Dependencies of total deformations (Fig. 7) and ovalization deformations (Fig. 8) on the applied load were plotted according to the results of the experiment. Analyzing the first experiment plots it is possible to note a big enough elastic zone of connection work, further we can see a jump of deformations which can be connected with washers tearing off, after that we observe the meshing effect due to which connection is deformed, but not destructed. And only when the ovalization of
15 mm; 3150 kg
Key-bolt juncƟon
N, kg
3500 3000 2500 2000 1500 1000 500 0 -5
0
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10
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4000
N, kg
3000 2000 1000 0 0
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Fig. 8 The dependence of ovalization strains on the applied load of the key-bolt junction
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the hole 6.4 mm and the load 3150 kg is reached, the first finite element is “turned off” and the connection collapses. According to the second experiment results, plots of total deformations (Fig. 9) and ovalization deformations (Fig. 10) were plotted against the applied load. Analyzing the second experiment’s plots, we can note a less “smooth” character of the joint’s work. There is still a visible zone of elastic deformations, but with a large deformation of the hole in this zone. Further, we can see almost horizontal jump of deformations, which can be associated with disruption of the washers up to the moment of the bolt contacting with the hole edge. It is also possible to observe a short elastic stage of plate deformation, followed by a short stage of plastic deformations of the plates and destruction of the connection at deformations of 2.86 mm in the hole at a load of 2250 kg.
Common joint
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Fig. 9 The dependence of the total deformation on the applied load of a conventional bolted connection
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Fig. 10 Ovalization strains dependence on the conventional bolted joint’s applied load
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4 Conclusion Model experiments have confirmed that the meshing effect of the punched metal area bent edges affects the hole deformation and, consequently, the load-bearing capacity and reliability of the connection. Currently, the key-bolt junction of thin-walled profiles is one of the effective methods of increasing reliability due to the increased safety margin and deformability due to the possibility of greater deformation than a conventional connection.
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Experimental Study of Dynamic Forces Acting on Wheel Pairs of Railway Rolling Stock in Operation Sergey Bekher , Dmitry Kononov , and Aleksandr Buynosov
Abstract The efficiency of rail transport directly depends on train speeds and axle loads of rolling stock, the increase in which causes an increase in the level of dynamic forces acting on wheel sets and rails. As a result of the wheels interaction with defects in the rolling surface and rails in the process of operation, the dynamic forces increase significantly, which negatively affects both the probability of formation and the rate of defects development in the parts of wheel sets and axlebox units. The research purpose is to create a technique and experimental determination of statistical distribution parameters of vertical dynamic forces arising in real operating conditions in the system of wheel and rail using dynamic tensometry. The equipment for vertical forces control, acting from the wheels of the rolling stock on reinforced concrete sleepers, is installed on the existing section of a straight railroad track on the rails. A methodology of strain-gauge control, based on measuring vertical deformations of rail necks above the sleepers and the software for determining the vertical forces in the “wheel-rail” system have been developed. The equipment was created and the strain gauge control section was calibrated under static (hydraulic jack) and dynamic (impact) loading. In the process of repeated tests with train load and in real operating conditions, the distribution of vertical dynamic forces arising in the “wheel-rail” system when the train moves were obtained. It is shown that the presence of even permissible defects of the rolling surface increases the dynamic forces by 2–3 times, the distribution of these forces is approximated by the exponential dependence and the probabilities of their occurrence in the train are calculated.
S. Bekher (B) Siberian Transport University, 191, Dusi Kovalchuk Street, Novosibirsk 630049, Russia e-mail: [email protected] D. Kononov Emperor Alexander I St. Petersburg State Transport University, 9, Moskovsky Avenue, Saint Petersburg 190031, Russia A. Buynosov Ural State University of Railway Transport, 66, Kolmogorov Street, Yekaterinburg 620024, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_12
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Keywords Dynamic forces · “wheel-rail” system · Wheel surface defects · Reliability of railcars running parts · Dynamic tensometry · Control of wheels in motion
1 Introduction The efficiency of rail transport is directly related to the maximum permissible speed and the maximum axle load of the rolling stock on the rails. The share of innovative cars with axle load of 25 and 27 t/axis is constantly increasing on the Russian railroads. The share of these cars currently exceeds 10%. In the recent years the “shoulders” between the maintenance of the freight cars have increased significantly, which in the modern conditions reaches 1000–1200 km. When increasing the efficiency of transport industry, the fundamental problem, without the solution of which the further development is not possible, is the traffic safety. The priority directions of research and development work [1–8] on the railway transport include the measures aimed at reducing the number of failures of technical means and, first of all, the responsible ones, which determine the transport safety. As compared to 2000, the number of cases of destruction of unsprung running gear in freight trains on the railroads of the Russian Federation has increased by 5–10 times, despite the fact that a comprehensive approach is used to ensure failurefree operation of rolling stock. During manufacturing and repair non-destructive control of the parts and units of the cars is performed and in the process of operation their technical condition is monitored. In car repair depots the details of wheel pairs are controlled [9] by ultrasonic, eddy current and magnetoporous methods in order to detect fatigue defects, and at the maintenance points the visual and measuring inspection is carried out. The improvement of car manufacturing [10], repair and operation system should be based on the use of automated [11] control and monitoring systems. Obligatory condition of this complex system functioning is the presence of feedback between the results of technical condition assessment in operation [12] and the criteria of limit state during manufacturing and repair. Changes of operating conditions of objects and or repair technologies must be compensated by operative changes of methods and criteria of rejection, which is especially important for active methods of control. In these conditions it is promising to use passive methods of control and monitoring (strain-gauge, acoustic-emission, vibro-diagnostic), the primary signals of which are related to the parameters of processes occurring in the control object, which allows classifying the detected defects by their influence on the serviceability of the controlled object. Passive [13, 14] methods of rolling stock control in the process of train movement [15–17] are sufficiently developed and have found wide application in the railroads of many countries. Further improvement of these methods can be connected with their integration with control systems of car repair and car building complexes. The
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increase in reliability of unsprung running gears after repair can only be guaranteed if the dynamic loads in operation do not exceed the design values. Currently, railroads use floor rolling stock diagnostic systems [18–23], based on a wide class of physical effects and phenomena: vibrodiagnostic, strain gauge, dynamometer, optical, acoustic-emission and others. These technologies and equipment allow to register indicators of interaction dynamics of wheels and rails and identify a wheel pair and transfer information about it to transportation process participants when limit values are exceeded. Despite the significant advantages arising from the introduction of these systems, the positive effect of their use is limited by the definition of the object’s technical condition. In these conditions the actual task is to create the monitoring systems of the real dynamic forces in the wheel and rail system, the statistical analysis of the data received from these systems will allow using them for the control processes at all stages of the car life: manufacturing, repair, operation. The purpose of the work is to create a methodology and experimental determination of statistical parameters of vertical dynamic forces arising in the railway wheel and rail system, including with rolling surface defects, using dynamic tensometry.
2 Methods and Equipment of Strain Gauge Control The tests were carried out on the testing ground of the STU and on the operating section of a straight track with the rails of R65 type according to GOST R 51,6852013, laid on reinforced concrete sleepers according to GOST 33,320-2015 with a frequency of 2000 pcs/km. Primary strain transducers—strain gauges PKS-12-200 with nominal resistance of 200 and strain sensitivity coefficient k g = 2.12 were glued over the sleepers at a height of h = 83 mm in pairs on opposite sides of the rail web (Fig. 1). The axis of the transducers was oriented vertically to register transverse deformations εZ . Signals from strain gauges were recorded by the fastacting “Dynamics-3” system [24] with a maximum sampling rate of the analog-todigital converter of 64 kHz per channel and the price of the smallest digit ε = 0.5 · 10– 6 . Developed software, using signals from load cells on the inside of the rail relative to the rail track εin and from the outside—εout , calculated the symmetrical ε S and asymmetrical ε A components of rail web deformations: εS =
εout + εin 2
(1)
εA =
εout − εin 2
(2)
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Fig. 1 Scheme of installing strain gauges on the rails of the measuring track section
Symmetrical vertical deformations εSare associated with the action on the rail of a vertical force Q, which vector is located in the symmetry plane of the rail, and antisymmetric vertical deformations εA depend on the bending moment M associated with the eccentricity e of the application of force Q and the action of the lateral force B (Fig. 2): εS = k Q · Q
(3)
εA = kM · M
(4)
where k Q , k M are the aspect ratios, N–1 . Under the influence of forces from the wheel, the rail is deformed according to three main schemes (Fig. 2, b): compression of the neck from the vertical force of the wheel and/or the sleeper reaction; torsion, caused by the bending moment M; bending in the vertical plane, associated with the finite rigidity of the subrail base. The used scheme of strain measurement (see Fig. 1) allows reducing the influence of torsional and bending strains (Fig. 2, b), due to the location of strain gauges in the neutral plane of the rail and exclusion of deformation antisymmetric component. The developed software of strain gauge system to control wheels in motion is based on the isolation and mathematical analysis of two components of strain gauge system signals. The high-frequency component of the signal is associated with local deformations under the wheel in the zone of (160–180) mm in length and provides an estimate of the average vertical force from the wheel on the rail with an error of no more than 5%. Determination of the impulse component parameters of the force caused by the impact of the rolling surface defect outside the zone with extension (180–1200) mm is based on the calculation of the amplitude ratio of the impulse component to the average level of deformations.
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Fig. 2 Scheme of application of forces from the wheel on the rail (a) and deformed states of the rail (b)
Calibration [25] of the strain gauge system to determine the proportional coefficients k Q (3) for each pair of load cells was carried out by dynamic and static forces. Dynamic loading was carried out by impact load (Fig. 3, a), a striker weighing 10 kg, loosely falling from a height of 1.0 m. The impact time was fixed by duration of electric contact between the striker and the rail and varied in the tests from 0.3 to 0.5 ms. According to the results of dynamic tests, the proportionality coefficient k Q was taken as equal to the relation of integral of the registered deformations on impact time to the change of striker impulse. The static force calibration was carried out using the designed and manufactured loading device providing lateral and vertical impact on the rail (Fig. 3, b). The horizontal force up to 110 kN was reproduced by a rod 1 resting against the opposite rail and a hydraulic cylinder 2 with a stop 3. Vertical force up to 218 kN was exerted by rod 4 and jack 6 with a stop in the longitudinal beam of the freight car. The jacks
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Fig. 3 Diagram and device for measuring section calibration by dynamic force under shock loading (a) and static force by hydraulic device (b): reproduced by bar 1—horizontal bar, 2—horizontal hydraulic cylinder, 3—arrest stop, 4—vertical bar, 5—hydraulic hoses, 6—jack
Table 1 Mean values and RMS of the proportionality coefficient k Q , determined in the process of calibration by static and dynamic forces Load method
Proportionality factor, k Q , 10−6 · N−1 Average value
RMS
Static force
2.05
0.03
Dynamic force
1.98
0.04
were supplied with hydraulic fluid through hoses 5 by a hand pump with a maximum pressure of 70 MPa. The conversion coefficient was determined as the ratio of the registered symmetric deformations to the value of vertical force reproduced by the jack. The results of static and dynamic force calibration for 10 measurements are shown in Table 1. Taking into account the random uncertainty in the reproduction of the vertical force, estimated by the root mean square deviation (RMS), the values of the dynamic and static coefficients of proportionality coincide.
3 Strain Gauge Control Results To study the uncertainty of vertical forces under repeatability conditions, multiple tests were conducted, in which one freight train made 77 passes over the measuring
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Fig. 4 Experimental distribution of vertical dynamic forces from wheel to rail and normal distribution
section at speeds (15.3 ± 1.4) m/s. The distributions of vertical forces from defect-free wheels on the rails are satisfactorily described by the normal law of distribution. The characteristic type of distribution—the dependence of the number of measurements on the registered vertical force is shown in Fig. 4. Experimental data were checked for belonging to normal distribution with mathematical expectation equal to 107.5 kN and standard deviation of 2.8 kN. The value χ2 = 2.5 does not exceed the quantile of the distribution χ2 0.05,4 = 9.5 with the level of significance q = 0.05 and the number of degrees of freedom n = 4. The cars in the train had different axle loads and, consequently, the average vertical dynamic force from the wheel to the rail, which ranged from 76 to 138 kN. The mean square deviation of the force contains two components: multiplicative δ S = 2% and the additive component of 1.86 kN, which does not depend on the weight of the car and is determined by the dynamic processes of interaction between the running parts with the track superstructure during the train movement. Rolling surface defects [26], such as sliders, potholes and uneven rolling (Fig. 5), have a significant influence on the dynamic forces arising in the process of interaction between the wheel and the rail. Currently, on Russian railroads, sliders up to 1 mm deep, potholes (metal pitting) up to 10 mm deep and up to 50 mm long along the rolling surface are allowed for operation. Measurements of defect parameters are carried out at train stops at car inspection points: depth with a gauge with a division value of 0.1 mm, length with a ruler—1 mm. Performed measurements of dimensions of more than 20 permissible defects of the rolling surface have shown that the defect profile is satisfactorily described by a flat area of depth R and length l. The surface of the central part of the slider is uneven with signs of metal wrenching, while the pitted part has spalling. The depth of the defect, measured relative to the top of the wheel crest, is from 0.2 to 0.6 mm. The outer part of the defects has a smooth surface
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Fig. 5 Slider with a chamfer on the wheel rolling surface
with traces of riveting, which appear in the process of movement and associated with increased loads from the impact of the wheel on the rail. For the wheel with a defect, shown in Fig. 5, the average force on the rail was Fmean = 118 kN, and the amplitude value of the force arising from the rolling of the wheel by the defective area, Fmax = 246 kN. The defect results in dynamic forces that exceed the average force by 2.1 times (by 108%). The experimental wheel detection frequencies for different values of relative vertical force excesses over the average are shown in Fig. 6. All wheels with forces exceeding the average by more than 200% are assigned to the point with abscissa 208 kN. As an example, the data for 4 trains that have passed the measuring section at a speed of (50 ± 10) km/h, and simultaneously the average data and the result of approximation by the least-squares exponential dependence of the “tail” of the distribution with excesses greater than 50%: n = n 0 · exp(−δ P /α)
(5)
where n 0 = 3.7% and α = 63% are the approximation coefficients set by the least mean ) · 100%—the squares’ method, n is a relative number of wheels, δ P = (PmaxP−P mean relative excess of the vertical force over the average value. As part of the train (item 1 in Fig. 6), 48% of wheel pairs of the train when passing the measuring section in the strain gauge signals have a pulse component associated with the influence of rolling surface defects. Amplitude value of dynamic force exceeds average value by 50 for 10% of all wheel pairs, by 100% for 4% and by 200% for the number of wheels less than 1%. According to the level of significance q = 5%, the confidence limit of the maximum value of excess force is 78%. The smallest number of wheel pairs with rolling surface defects was found in the train made up of new cars (Fig. 6, item 2). For all wheels the forces do not exceed
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Fig. 6 Experimental frequency of wheel detection as a function of exceeding the average dynamic force on the rails (1, 2, 3, 4—serial numbers of trains, 5—average values, 6—approximation of the exponential function)
the average value by more than 64%. However, trains made up of used cars are characterized by defects that cause an increase in dynamic force compared to static force by a factor of 2 and 3 or by 100 and 200%, respectively. For example, the train, test results of which are given in Fig. 6 item. 4, two wheels with a force of 2 times and one wheel with a force of 3 times the average force were found. On average for all trains, the maximum dynamic force is 2 times the average force from the wheel in 2% of the wheels of the freight train. The highest relative number of such wheels in one train was 4% (item 3 in Fig. 6). Similarly, the proportion of wheels with the maximum force of 3 times the average force recorded varied from train to train in the range from 0 to 2.5%.
4 Main Conclusions and Results Analysis The strain-measuring control section on the operating trackless track is equipped with primary converters—wire strain gauges and measuring equipment—dynamic strainmeasuring complex “Dynamics-3” with a sampling frequency of 64 kHz and the lowest digit value of deformation 0.5 · 10–6 . Software for automated control of vertical dynamic forces transmitted from car wheels to rails was developed and implemented. Calibration of the section with dynamic and static forces was performed using an impact device (average force value of 110 kN at impact time of 0.4 ms) and hydraulic loading device with maximum force of 218 kN. In the process of repeated tests with train load and under real operating conditions, the distribution of vertical dynamic forces arising in the “wheel-rail” system during the train movement at speeds of (50–60) km/h has been obtained. It is shown that
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in the absence of defects, the distribution of vertical dynamic forces belongs to the normal one according to the χ2 criterion with a significance level of 5%. The mean square deviation contains an additive component of 1.9 kN and a multiplicative one equal to 2% of the mean value of the vertical force. It is shown that the defects of the rolling surface, the dimensions of which correspond to the requirements of the normative documentation, are able to increase the peak values of the dynamic forces by 2 and more times. On average, 3% of wheels in the registered data contain defects that cause an increase in dynamic forces by a factor of 2 in relation to their average level, and 1% of wheels—by a factor of 3. The distributions of vertical dynamic forces with rolling surface defects are approximated by an exponential dependence with the parameter α = 63%. According to the approximation results, the probabilities of registration of forces in 2, 3, 4, 5 times of average force are 2.7, 0.6, 0.12 and 0.03%, respectively. In accordance with GOST 10791-2011, minimum allowable ratio of fatigue limit to static load from the wheel to the rail is 3.5 for 230.5 kN/axis axial load and 3.7 for 245 kN/axis when tested on the basis of 5 million cycles. Under these conditions, the operational reliability of solid rolled wheels, which are subjected to dynamic forces 4 times higher than average when the train is in motion, is at risk. The probability of occurrence of one such wheel is a significant value, so for a freight train of 70 four-axle cars, the probability exceeds 50%. The established patterns are particularly relevant for the wheels with a thin rim and technological defects. Due to the reduced rigidity of the rim, a high level of stress occurs in the area of its transition to the disc. The presence of technological defects creates conditions in which stresses are capable of exceeding the fatigue strength limit. This results in the formation of fatigue cracks, which, when visually inspected in operating depots, are the cause of component failures, accidents, derailments or derailments.
References 1. Bernal E, Spiryagin M, Cole C (2021) Wheel flat analogue fault detector verification study under dynamic testing conditions using a scaled bogie test rig. Int J Rail Transp. https://doi. org/10.1080/23248378.2021.1889407 2. Tao G, Wen Z, Chen G et al (2021) Locomotive wheel polygonisation due to discrete irregularities: simulation and mechanism. Veh Syst Dyn 59(6):872–889. https://doi.org/10.1080/004 23114.2020.1737148 3. Sta´skiewicz T, Firlik B, Kominowski J (2021) Out-of-round tram wheels – multibody simulation study based on measured wheel rim geometry. Proc Inst Mech Eng Part F J Rail Rapid Transit. https://doi.org/10.1177/0954409721994036 4. Manea I, Ene M, Girnita I et al (2021) Determination of wheel-rail interaction forces of railway vehicles for evaluation of safety against derailment at running on twisted tracks. In: Balthazar JM (ed) Vibration engineering and technology of machinery. Mechanisms and machine science, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-030-60694-7_11 5. Muravev VV, Tapkov KA, Lenkov SV (2019) In-production nondestructive testing of internal stresses in rails using acoustoelasticity method. Russ J Nondestr Test 55(1):8–14. https://doi. org/10.1134/S1061830919010078
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Simulation of the Track Machinery Technical Condition to Ensure Safe Operation Alexey Loktev , Petr Sychev , Vladimir Aksenov , Alexander Pikalov , and Vyacheslav Sychev
Abstract The issues of safe operation of track machines integrated into machine complexes are considered in the context of the analysis of downtime causes in the system of peculiarities of their operation using mathematical modeling of their state, which is represented as multidimensional space generalizing ideas about the state of each track machine and fluctuations of these states in the machine complex. The results of processing the statistical data on the number and causes of downtime for individual SRS are generalized, which made it possible to identify the causes as control parameters in the system of differential equations for all probabilities of states of a closed system of mass maintenance of track machines with a given expectation. The model of controlling the state of track machines in the phase-space of machine complexes, is divided by a hyperplane into two subsets—serviceable and faulty (failure), in which the vector of its states in the process of repair works is subject to fluctuation. The process of incoming maintenance and repair demands is described by a probabilistic model and represents a flow of homogeneous events arriving at random intervals of time as the simplest, Poisson flow. It has been proved that one-dimensional density is not enough to describe the real process of track machine complexes operation, and it has been suggested to use two-dimensional probability density. Experimental calculations were performed using the proposed models. On the basis of different probability values, the number of requirements, which should be limited to the implemented model, was calculated in order to determine the parameters of location and possibilities of track machine operation on a given track section at the next stage of research.
A. Loktev · V. Aksenov · V. Sychev (B) Russian University of Transport (MIIT), 22/2, Chasovaya Street, Moscow 125190, Russia e-mail: [email protected] P. Sychev LLC “Vagonputmashproekt”, 9A, 1, Kulakov Lane, Moscow 129626, Russia A. Pikalov Sinara-Transport Machines JSC (“STM”), 51, R. Luxemburg Street, Ekaterinburg 620026, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_13
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Keywords Modeling · Safety · Labor protection · Track machine · Operation · Maintenance
1 Introduction Technical condition of track machines used in repair and maintenance of railroad track plays a decisive role in ensuring the safety of workers engaged in these processes [1]. The state of special rolling stock (SRS) is determined by a set of quality indicators of their functioning, which can be reduced to the indicators of SRS reliable operation, determined by the presence of failures in their work. For SRS operated on the railroad track, reaching the limit state, expressed in failures, is caused by the following reasons: scattered micro damages in units and parts, developing under loads into macroscopic cracks; excessive wear of rubbing parts and surfaces; natural impacts; uncontrollable gross errors in operation, which are the result of violations of operating and occupational safety conditions. This causes loss of SRS units and parts operability, determined by the intensity of their wear and dynamic forces at operation, which reduce the level of SRS safe operation. In particular, for hopper feeders, significant reasons causing failures are [2]: errors in operation during loading and unloading of ballast, development of cracks in the ridge and kingpin beams or places of their connections, excessive corrosion of main units and parts, metal fatigue damage and other failures, usually associated with hidden manufacturing defects. Failures can be divided into two groups: the first—failures that do not lead to dangerous interruptions in the SRS, eliminated during its scheduled repair; the second group of failures—the limit states of the main elements that limit the resource SRS, in which the resource is produced under normal operating conditions, and the physical processes in the development of the resource are irreversible. For the second group of failures it is necessary to define a probability Pp(t) [3, 4] that the limiting condition will not be reached on some interval [0, T]. Statement of the problem. A mathematical model of the state of these means can be represented as a multidimensional space generalizing ideas about its states and their fluctuations (X, Y, Z…). d X dY d Z ; ; dt dt dt
(1)
Let us represent the technical state of SRS by the area X in n-dimensional space. Let us evaluate the quality of SRS operation by the corresponding indicators E i = (x), which form the area of At states in M-dimensional space. Thus, in the first approximation, the technical state of technical means corresponds to the change of trajectory in the phase space (X, Am ) without taking into account the state fluctuation, first of all, the reliability function φ(x).
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2 Problem Solution The analysis of SRS downtime for an average of 7 years of operation shows the influence of the SRS reliability parameter on the functioning of the railroad maintenance system [5, 6]. The analysis showed that downtime of SRS and their complexes are caused by various reasons: cancellation of windows, weekends, transportation, absence of crews, commissioning works, maintenance, scheduled repairs, unscheduled repairs, etc. The results of statistical data processing in the form of dependence of relative number of outages for separate SRS has allowed distinguishing causes, which can be referred to controlled parameters in the system of differential equations for all probabilities of states of closed-loop mass service system with given expectation. The input of the system is a simple flow of requests with some density, the service time of one request is subject to a distribution law with a certain parameter. For binary states of “serviceable-faulty” type, the limits of function variation are defined by the following relation: 0 ≤ φ(x) < 1
(2)
Thus, the system state is characterized by the values of variables Cc = X ni , Akm φ e . The change in the system state [7, 8] can be represented by a phase trajectory in space (X, A). When designing SRS set, the standard service life of SRS, but in the process of operation individual resource is formed, which, generally speaking, can be managed. The most important indicators of complex indices of SRS reliability and serviceability in the system of maintenance of railroad track are the coefficients of availability CA and technical use Ctu : N CA =
i=1 i pi
N Top
N Ctu =
i=1 t pi
N TE
(3)
where t pi —total dwell time of machines in serviceable condition; T op , T E define the duration of SRS operation except for downtime in scheduled repairs and maintenance of the railroad track and time of SRS operation, respectively. We will consider such factors as wear and aging as perturbing factors aimed at changing the state of SRS. Let’s combine the controlling factors into the maintenance and repair system common to all types of SRS [8]. SRS, in the process of its operation, is in different states. The change of parameters characterizing these factors and depending on the course of processes in time and space is determined at the initial stage by three parameters-coordinates X 0 , Y 0 , Z 0 in three-dimensional space. However, the technology of SRS application and, first of all, the rate of change of SRS technical condition is not limited to these three parameters, but consists of p points which are described by the following parameters: X k0 , Yk0 , Z k0 , where k = 1, n.
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In the most general form, the technical state of the SRS in operation, at each point in time, is defined by the phase point X = (X 1 , X 2 , ..., X n ) [9]. The state trajectory will be influenced by the control parameter U = (U1 , U2 , ..., Un ). The change of U and X is a process from the control function U{t) and the phase trajectory X(t). A process will be considered completely defined if the control is given U(t) at t > t0 and the initial phase state X 0 = X (t0) . We represent the model of SRS state control in the phase space, divided by hyperplane G(x) into main subsets—serviceable and faulty (failure), in which the vector of its states during the operation of SRS, in particular during its repair work is subject to fluctuation. Then the position of this vector will change when the operating conditions change. Also, the period to reach the hyperplane will change. Then the control purpose will be to control the position of the vector trajectory by the indicator γ . In the absence of sharp perturbing influences, for example, a crack of the SRS supporting element, such as a frame, the state of the SRS will change monotonically, and the trajectory will gradually approach the hyperplane. At this point, it is necessary to apply a control that will prevent the state vector trajectory from getting into the area of failures. In this case the control U 2 should be performed at discrete moments of time Δt, and if the state vector passes into the area of failures, the control U 3 will provide intensive recovery. Thus, the control equation U Σ of the condition is described as: U = U1 (t) +
n 1
U2 (Δti ) +
k 1
U3 Δt j
(4)
where i, j are the discrete moments of applying the control actions that restoring the state; Δt are the sampling intervals. The dynamics of the SRS state change process can be described by the system of differential equations: d Xn = F(X, Y, U ) dt
(5)
Y 0 defines the SRS operating conditions accepted as normal. Then the provision of these conditions will be U 0 , and the process of state change in this case corresponds to the equation: d Xn = 1, dt
(6)
where I = f (Y0 , U0 ). The equation of unperturbed motion can be represented in another equivalent form: d Xi = γi , i = 1, ..., n. dt
(7)
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Influence of small deviations of conditions ΔY and ΔU from Y 0 and U 0 on the state change in the first approximation is described by the equation: dΔX i = k0 ΔX + K 1 ΔY + K 2 ΔU, dt
(8)
d fi where K 1 = is a gradient vector—line by Y; d fi dU j K2 = is a gradient vector—line by U; dU ⎛ j ⎞ ΔY1 ⎜ ΔY2 ⎟ ⎟ ΔY = ⎜ ⎝ · · · ⎠ is a vector column by Y; ΔYn ΔU is a vector column by U. Thus, management of individual SRS resource in the system of railroad track maintenance depends on the technology of controlling factors and technology of track works, the impact of which will depend on increasing the SRS output (actually, the speed of movement at work) and increasing their load capacity. Increasing the output is associated with limiting the dynamics of changes in track draft, and with increasing load capacity changes in stress and force in various elements of the railroad track [10, 11]. The model should take into account the elements of SRS maintenance system functioning under different modes of use on the railroad track with different types and values of faults of this track, as well as organizational parameters, such as the conditions of providing «track possesses». Each action occurring with during SRS operation can be extended to the SRS class based on the analysis of their operation under different weather conditions, technical conditions, qualification of track workers, etc. Let us represent the set of individual and related maintenance requirements by a random function ξ (t), determining the number of maintenance requirements for some time interval (0, t), which can only take integer values [12]. Then the random process ξ (t) is a set of implementations ξ (t) = {x(t)}, which is characterized by a distribution function. The distribution function can be n-dimensional (dependence on x n ) and m-momentum (dependence on t m ). However, for practical application we use the derivative of the distribution function, that is, the probability density function: w1 (x1 ; t1 ) = d F1 (x1 ; t1 )/d x1
(9)
But the one-dimensional density showing the fraction of realizations of a random process that falls within the corridor of values [x1 , x1 + d x1 ], is insufficient to describe the real process of track machine complexes operation, since it does not provide a description of the process change over time. Therefore, we will use a twodimensional probability density function, highlighting the moments of time t1 , t2 and some values x1 , x2 from the range of possible values of a random process ξ (t):
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w2 (x1 , x2 ; t1 , t2 ) = ∂ 2 F2 (x1 , x2 ; t1 , t2 )/∂ x1 ∂ x2
(10)
The n-dimensional and n-momentum probability density functions provide more complete information about the change in the process over time: wn (x1 , x2 , ..., xn ; t1 , t2 , ..., tn ) = ∂ n Fn (x1 , x2 , ..., xn ; t1 , t2 , ..., tn )/∂ x1 ∂ x2 ...∂ xn (11) The process of incoming demands for maintenance and repair is described by a probabilistic model and is a flow of homogeneous events arriving at random time intervals. The Poisson simplest flow will be considered, in which the probability of arrival of exactly “K” demands at time interval t is given by the Poisson formula:
(λt ) -λt е К! К
Рk(t) =
(12)
Here Pk (t) is the probability of exactly “K” demands in time t; λ is a number of claims per time unit; K is an estimated number of claims. Let us assume that the requirements A1 , A2 , A3 …… An appear on the time axis at intervals t 1 , t 2 , t 3 … t n − 1, t n . The value of time intervals t n − 1 − t n − 2 and t n − t n − 1 will be denoted by t and τ. Then, according to the probability multiplication theorem, the probability of the claims in the interval τ will be P(t + τ ) = P(t) [1 − P(τ )],
(13)
where P(t) is the probability that in the interval t no claims have been received. From (6) we define: P(τ ) = 1 −
P(t + τ ) P(t)
(14)
If we accept the indicative distribution law of the random intervals of time of incoming demands for maintenance, we get P(t + τ ) = e−λ(t+τ ) , P(t) = e−λt , P(τ ) = 1 − e−λτ .
(15)
From the expression (15) we see that the probability of the claim P(τ ) in the interval τ does not depend on the value of t, while the ratio (14) indicates that the appearance of the claim after the moment An−1 depends on the interval t. Thus, the flow of maintenance requests is better described by the model based on the exponential law of random variables distribution, and the value f (t) = λe−λt represents some density function.
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The definition of the requirements flow characteristics is not yet sufficient for a comprehensive description of the maintenance system under consideration. It is also necessary to describe such a parameter as the time of one maintenance, which characterizes the productivity of rolling stock, which maintenance of machines of different brands can vary, firstly, due to the fact that maintenance is required by track machines of different brands, amount of work and machine resources, and secondly, due to the condition of stationary and mobile workshops, with a significant role played by human factor and parameters of the “man–machine” interaction [13, 14]. The average labor intensity of one maintenance of track machines of the same brand or a group of machines of different brands can be determined with the help of the expression: n qi · n i q = i=1 ni
(16)
where qi is labor intensity of one service of the i-th brand machine; ni is the mathematical expectation of the number of service requirements for the i-th brand of machines arriving during the observed time interval. The labor intensity value in the general case is a random variable, which can be practically estimated for different machines from the experience of their operation and processing of statistical data. It is obtained that the maintenance of machines in man/hour is approximate for: Duomatic, Unimat almost 1500 man/hour, respectively: VPR-02, VPR-1200, VPR-02, VPR-500 almost 1000 man-hours; DSP, DSP-C, PB almost 800 man-hours; ELB almost 300 man-hours and DGKU, MPT only 150 manhours. This variation is caused by the design features of different SRS. Comparison of the relative quantitative characteristics of SRS downtime shows that a number of reasons can be attributed to the controllable parameters in the system of differential equations for all state probabilities of a closed-loop mass service system with expectation. In this case, they can be described not only in the time domain but also in the frequency domain using the Fourier transform. Using Fourier transform for probability density function w1 (x1 ; t1 ), we obtain the characteristic function θ1 (u 1 ; t1 ) =
∞ −∞
e ju 1 x1 w1 (x1 ; t1 )d x1
Since the minimum dimension that takes into account the specificity of the random process is 2, it makes sense to consider a two-dimensional characteristic function θ2 (u 1 , u 2 ; t1 , t2 ). Since downtime parameters have different effects on the final characteristics of the use of SRS, it is convenient to use the representation of the characteristic function, in each term of which at the next stage it is possible to allocate an appropriate coefficient, taking into account the influence of one or another parameter:
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∂θ2 ∂θ2 1 ∂ 2 θ2 2 1 ∂ 2 θ2 2 ∂ 2 θ2 u1 + u2 + u + u + u1u2 + . . . ∂u 1 ∂u 2 2 ∂u 2 1 2 ∂u 2 2 ∂u 1 ∂u 2 1 2 1 1 1 1 = 1 − m 1 (t1 )u 1 − m 1 (t2 )u 2 − m 2 (t1 )u 21 − m 2 (t2 )u 22 − m 11 (t1 , t2 )u 1 u 2 + . . . j j 2 2
θ2 (u 1 , u 2 ; t1 , t2 ) = 1 +
(17)
Here m k (t) is the initial moment one-dimensional function of k order. It is possible to set the value of SRS downtime or waiting time of the complex of machines for web repair and, on this basis, to select the values of control parameters for a particular distance. For this purpose, it is convenient to use probability of no-failure operation from the given value z: z 1 t2 ∫ e− 2 dt. Pop (z) = √ 2π −∞
(18)
It is also possible to operate with the probability of error depending on the normalized parameter Pop (z) = 1 − Pop (z)
(19)
Experimental calculations by the proposed models on the Microsoft Office Excel editor and MATLAB engineering computer complex were carried out. By setting different values of probability, the number of requirements, which should be limited to the implemented model, is obtained, that at the next stage of research becomes possible to determine with a given security the parameters of location and possibilities of operation of track machine at a given distance of track (Fig. 1). On Fig. 1 on an axis of ordinates the probability of occurrence of necessity of repair works at operation of the machine within the limits of the certain technological process, on an axis of abscissa the relation of time of work on a site of a way to the reduced time of idle time is laid. The curves 1, 2, 3 in Fig. 1 were obtained by using the traditional method of modeling, on the basis of experimental data and using the proposed approach, respectively. Some discrepancy between the curves obtained by using traditional methods and the proposed method for the interval of requirements from 4 to 12, is due to the fact that in approximating the average section of the exponent did not take into account all the terms of the series.
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Fig. 1 Probabilistic estimation of maintenance-free operation for track machinery, depending on the number of service requirements for the machine, taking into account various calculation methods
3 Conclusion Thus, the conducted analytical studies and the obtained graphical results showed that the proposed methods of mathematical modeling of SRS operation give good coincidence with the results of using the traditional methods of statistical data processing. At the same time, the methods proposed in this study allow separating at the initial stage of solving the problem the influence of individual factors of SRS functioning on the final characteristics of their use and providing an opportunity to observe the dynamics of the impact of individual operating conditions on the parameters of performance efficiency. The proposed methodology makes it possible to determine the real values of control parameters under certain conditions of use of SRS and their complexes by fixing some of the required functions. The developed mathematical model of life cycle assessment with regard to the conditions necessary to improve the level of safe SRS operation allowed formalizing the process of SRS maintenance and determining the main characteristics of SRS maintenance processes to assess the quality of the maintenance system functioning, including the requirements flow and directions of operating SRS complexes optimization, which will ensure the reduction of injuries when working with SRS in the production of track works.
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References 1. Loktev DA, Loktev AA (2020) Transportation soil engineering in cold regions, vol 1. Lecture notes in civil engineering, vol 49, pp 205–214 2. Loktev DA, Loktev AA, Salnikova AV (2020) Commun Sci Lett Univ Zilina 22(1):95–101 3. Loktev DA (2019) E3S Web Conf 135:02029. https://doi.org/10.1051/e3sconf/201913502029 4. Alfimtsev AN, Sakulin S, Loktev DA et al (2019) J Adv Res Dyn Control Syst 11(2):506–516 5. Loktev DA, Loktev AA (2018) Proc. global smart industry conference, pp 1–7 6. Loktev DA, Loktev AA, Stepanov R, Pevzner V, Alenov K (2018) An aggregated method for determining railway defects and obstacle parameters. Paper presented at the 4th international conference on advanced engineering and technology, ICAET 2017. IOP Conf Ser Mater Sci Eng 4:012021 7. Loktev AA, Sycheva AV, Vershinin VV (2014) Modeling of work of a railway track at the dynamic effects of a wheel pair. Paper presented at the 2014 international conference on theoretical mechanics and applied mechanics, Venice, Italy, 15–17 March 2014, pp 32–35 8. Alpem M (1957) Am J Ophthalmol 57:345–353 9. Bender C, Denker K, Friedrich M et al (2011) A Hand-held laser scanner based on multi-camera stereo-matching. Paper presented at the IRTG 1131 - visualization of large and unstructured data sets workshop, pp 123–133 10. Loktev AA, Sychev V, Gridasova E, Stepanov R (2017) Mathematical modeling of railway track structure under changing rigidity parameters. Nonlinearity Probl Sol Appl Theoret Appl Math 1:291–307 11. Devyatkov V, Alfimtsev A (2011) IGI Global 10:146–167, Hershey, USA 12. Ganin AN, Priorov AL (2002) Quantization of wavelet coefficients. Paper presented at the 1st IEEE int conf on circuits and systems for communications (ICCSC 2002), St. Petersburg, pp 202–205 13. Glusberg B, Savin A, Loktev A et al (2020) Adv Intell Syst Comput 982:556–570 14. Gould E, Verenikina I, Hasan H (1992) Activity theory as a basis for the design of a webbased system of inquiry for world war 1 data. Paper presented at the 23rd information systems research seminar in Scandinavia, pp 761–770
Development of On-Board Systems of Predictive Diagnostics of Electric Rolling Stock Traction Motor Kirill Pastukhov , Stanislav Istomin , and Oleg Yrasov
Abstract The article deals with the problem of providing diagnostics, monitoring and control of the residual life of traction electric motors of electric rolling stock. The analysis shows that the existing diagnostic systems of traction engines do not allow us to carry out diagnostics to make a decision on maintaining their operability and monitoring the residual resource. Due to the fact that the main cause of breakdowns and inter-turn closures of the insulation of the TED is its overheating, it is proposed to improve the method of temperature control of the armature winding, additional poles, compensation winding. The article proposes a system with an algorithm for analyzing the condition, comparing the current operating modes of the traction engine of a 2ES6 series locomotive for further calculation of its residual life, monitoring and control of its condition. The system under development will collect data from diagnostic sensors, save them and send all the accumulated data to the server. Data processing is carried out on the server using artificial intelligence and machine learning methods and a decision is made on the technical condition and residual resource of the traction motor. As a result, it becomes possible to assess the critical condition of the traction motor. Keywords Traction electric motor · Diagnostics · Residual resource · Locomotives · Temperature control · Armature winding · Monitoring
1 Introduction The design of new generation locomotives is becoming more complicated, which is due to the requirements of increasing power, reducing energy costs for train traction, improving traffic safety, automation of control with optimal modes options, etc. The condition of locomotives, their power units, assemblies and parts is monitored throughout the entire life of locomotives, both during their operation on the railway lines and during inspections and repair. K. Pastukhov (B) · S. Istomin · O. Yrasov Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_14
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Not only the electrical but also the mechanical components are becoming more complicated due to more complex suspension and transmission systems, brake and spring arrangements. In this regard, the extent of diagnostics for maintenance increases, and the requirements for their quality and effectiveness toughen. The analysis shows that more than 50% of the total number of maintenance operations is accounted for by diagnostics. At the same time, the analysis of the technological procedures of locomotives maintenance and repair, for instance, shows that until recently, almost 2/3 of the operation time was unproductive. About 20% of the time was spent on tracing the region of imperfections (identification of a faulty assembly or unit), about 40% was spent on detecting a defect inside this region, and only 35% was spent on repairing the faulty part. Therefore, it is important to develop the advanced methods and means of fault detection, control the condition of parts, assemblies and units of locomotives [1–4]. Diagnostics as a special procedure of maintenance inspection is determining the technical condition and predicting the operational capability of equipment according to diagnostic parameters functionally related to the operating parameters of the technical condition of this equipment. Diagnostic parameters can be the current consumption, electrical resistance, thermal conditions, jittering and transportation noise, degree of tightness, wear products of rubbing parts in lubricating oils, etc. One of the important directions in railway transport is automatization of monitoring the technical condition of rolling stock en route [5]. The data obtained are used for express analysis aimed at diagnosing the technical condition of the electric locomotive and evaluating the results of the trip. This information can be used for management decisions at the depot to optimize train operating modes, timetables and repair [6]. When the speed and weight of trains, through train run distances are increased, and the intervals between following trains are reduced, ensuring a high level of traffic safety becomes of primary importance. This problem cannot be solved without improving traditional and developing new methods of controlling locomotives during their movement along non-stop sections. Therefore, the authors will consider the prospects for the development of on-board systems for predictive diagnostics of the technical condition of electric rolling stock, in particular, its most crucial assembly— a traction electric motor [7].
2 Materials and Methods The object of the study is a 2ES6 series electric locomotive, which uses a microprocessor control and diagnostic system MPSU and D, etc. According to the statistics for 2020, the electrical equipment failures in 2ES6 series electric locomotives come first followed by traction electric motors failures. These factors make the problem under consideration one of interest (Fig. 1).
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Due to the fact that a significant number of locomotives uses the 810 series traction electric motor, the issues of improving on-board diagnostics and calculating the residual life of this traction electric motor are of immediate interest. Developing technical diagnostics systems is an integral part of the set of works to ensure the quality of operating machines and mechanisms. The main purpose of technical diagnostics is to properly determine the technical condition of traction rolling stock. Hardware or software, built-in or external facilities with a developed diagnostic algorithm are used depending on the locomotives diagnosis tasks. The next group includes the tasks related to the development of principles of construction, experimental testing and commercialization of diagnosis facilities. The classification of the main subjects of technical diagnostics research is shown in Fig. 2 [8]. In contrast to reliability theory, which studies average probability statistical indicators characterizing technical objects and uses them for calculations, technical diagnostics studies the methods that determine the actual state of technical objects. Various methods are used to diagnose the condition of the locomotive, its components and equipment. The choice of method depends on the complexity of the diagnosed assembly and equipment. Technical diagnostics The system
Physical objects
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Fig. 2 Block diagram of classification of the main tasks of technical diagnostics
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Fig. 3 Block diagram of classification of diagnostic methods
Methods of diagnosing locomotives differ depending on the combination of features as to the particular structure and interaction of the three main parts of the technical diagnostics system. These three parts include the object of diagnosis, the system for collecting, converting and transmitting information and the system for processing, accumulating and displaying diagnostic results (Fig. 3).
2.1 Mathematical Method The existing mathematical methods used in technical diagnostics are divided into two large classes: – mathematical modeling of diagnostic processes; – application of various theories (pattern recognition theory, theory of sets, etc.). Mathematical modeling makes it possible to limit and reduce the cost of the diagnostics, select the most informative diagnostic parameters, and accumulate information in an analytical form to predict the technical condition of the object. Analytical models allow for solving optimization problems and correlating object states with diagnostic parameters and quality indicators in an analytical form. During the operation of the object, the external and internal parameters change; therefore, the output parameters change. When analytical models of object technical condition are used, microprocessor devices look most promising [9].
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2.2 Heat Technique This method is based on the analysis of the heat radiation of parts, elements or devices in operation. Some parts and elements have increased intensity of their heat radiation associated with local overheating, which is due to the defects or inhomogeneities. Timely detection of these defects allows you to take measures to prevent the failure of parts and the device as a whole. By the method of obtaining information about the intensity of radiation, heat methods are divided into contact and non-contact. Methods based on the properties of the emulsions changing the development speed of the colour scheme depending on the temperature [10]. Non-contact methods of measuring the characteristics of the thermal field are based on the properties of bodies to emit electromagnetic energy proportional to their temperature. They are divided into methods with simultaneous and sequential recording of heat radiation. The proposed diagnostic system will include a set of components for taking data from a traction motor, transferring them to a data processing unit for calculation and data accumulation. The driver information system provides the values of the current consumed, the voltage of the contact network, the readings of the locomotive signal lights and other data coming from safety control system or from the recorder of the locomotive traffic situation, all these recorded on a single removable data storage device.
2.3 Development of Software for Presenting Statistical Data For the proposed system, the software based on a statistical analysis system (SSA, Statistical analysis systems, SA) designed for complex statistical data studies will be developed. These software products support analysis methods such as regression analysis, predictive analytics, time series analysis and statistical modeling. This system will allow for processing the data received from the sensors and provide statistical information about the operation of the traction electric motor, which will result in detecting the cause of its failure, the person responsible for it and more accurate data about the malfunction. Statistical data will be presented as tabular and graphical.
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2.4 Calculation of Statistical Data to Determine the Residual Life of Traction Electric Motor Predictive Analytics Predictive analytics is a class of data analysis methods that focuses on predicting the future behavior of objects and subjects in order to make optimal decisions (Fig. 4). Predictive analytics uses statistical methods, data mining methods, game theory, analyzes present and historical facts to make predictions about future events. Time Series Analysis Time series is the sequence of the recorded signal (the observed one). This approach is used when it is not possible to construct equations of motion (Fig. 5). Numerous applications of time series analysis are a rapidly developing field of science at present. The joint methods of analysis under consideration will make it possible to obtain data on the residual life of traction electric motor, which will help to prevent chance failures.
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Fig. 5 Time series analysis
3 Results The traction characteristics of a 2ES6 series locomotive were built on the basis of statistical methods. A 2ES6 series electric locomotive is equipped with 810 series traction motors. This electric locomotive uses 65 positions to gain power. The operation of the traction motor is influenced by many factors from temperature to humidity, which makes the calculation of the residual life a difficult task. Below is the dependence of the current on the travel time of 2ES6 series electric locomotive showing us the abrupt changes in the current load of the traction motor in operation (Fig. 6). This graph shows that the current is not stable changing abruptly, which can lead to overheating of the insulation. This mode has a significant impact on the reliability of a traction motor, which results in intensive insulation aging. In the existing on-board system, the resistance method is a classical method used to measure the temperature of traction electric motor. The proposed system considers two approaches. The first is opening the armature and installing temperature gauges; the second one is the use of an infrared pyrometer to measure the temperature of the traction motor winding. Next, all the information is transmitted to the electric locomotive, where it is processed; the temperature of the traction electric motor overheating is monitored, and the residual life of the traction electric motor is calculated for its further on-line repair. This approach will allow you to repair the traction electric motor when needed. The traction motor is subject to heavy loads due to the current changes, which results in overheating and reducing its residual life, thus making its failure probable.
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On the basis of the data obtained through the operation of the traction motor, the calculation of the winding residual life will be done as thermal control through Runge–Kutta method [11, 12]. ⎧ C1 + ⎪ ⎪ ⎪ ⎨ ⎪ ⎪ ⎪ ⎩
dθ1 dt
2 + θ1 (λ12 + λ15 + λ14 + λ19 ) − θ5 λ15 − θ2 λ12 − θ4 λ14 − θ9 λ19 = P1 (1 + β1 θ1 )kcl 2 C2 + dθdt1 + θ2 (λ23 + λ12 + λ29 ) − θ3 λ13 − θ1 λ12 − θ9 λ29 = P2 (1 + β1 θ2 )kcl , .............................. dθy 2 Cn + dt + θy λi,j + λi,j + λi,j − θy λi,j − θy λi,j − θy λi,j − θy λi,j = Pn (1 + β1 θy )kcl
where θ1 , θ2 , . . . , θ y is the temperature rise of the assemblies included in the traction electric motor design; λ1 , λ2 , . . . , λi, j -thermal conductivity between the assemblies; C1 , C2 , . . . , Cn -the heat capacity of the corresponding assemblies; P1, P2 , . . . , Pn losses in separate machine assemblies at ambient temperature; β1 -temperature resistance coefficient; kcl -current load ratio; I-motor armature current; Ir -rated motor armature current. The algorithm for solving this system of equations: θset = f (kload )θ = f (t)
(1)
The result of solving this system of equations is used to calculate the predicted residual life of traction motor winding insulation. A method for predicting the residual life for a specified class of insulating materials, chemical reactions in various materials under thermal influences proposed by J. van’t Hoff and S. Arrhenius. With regard to isolation, it is necessary to find not the rate of the chemical reaction but the time of aging reaching a critical state.
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Insulation service life Dθ at θ insulation heating temperature: Dθ = D0 ∗ e−θ/a
(2)
Next, the value of the residual life is found by the formula: Dr esid =
2 sh α2 α
∗ T ∗ eθavg/a D0
(3)
where D0 is the insulation service life at rated temperature, years.
4 Discussion Most existing diagnostic systems have a number of disadvantages: inability to monitor data in real time; to save statistics; present statistical data to determine the residual life of a traction electric motor. In this regard, the authors of the article propose to improve the existing diagnostic methods by introducing a system of data collection, monitoring, accumulation and presenting the statistics based on the data obtained. The data source of the diagnostic system is the readings taken from a traction electric motor. They indicate the electric power consumed by each traction motor in real time and allow you to more accurately adjust the operating modes using the data on the current, voltage, resistance, temperature, etc. The software package of the proposed system for recording, analysing and structuring the data on an electric motor involves presenting statistical data, which will provide us with the residual life of a traction electric motor. Moreover, the proposed system will help to save these statistics to identify the causes of malfunctions and ways of their elimination. The monitoring system can be used together with the autonomous driver information system, which will allow for transferring the data received from the traction electric motor in real time directly to the driver. This will make choosing the traction electric operation mode due to its condition easier. To achieve this, it is proposed to introduce into the control panel a system for monitoring the operation of a traction motor to notify the driver about the state of the motor. This will enable the driver to make an adequate choice of the operation mode due to the data obtained.
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References 1. Buynosov A, Vasilyev V, Erpalov A, Nitskiy A, Baitov A (2020) Analysis of electric noise at vibration based diagnostics of motor-coach stock assemblies. Transp Urals 2(65):10–15. https://doi.org/10.20291/1815-9400-2020-2-10-15 2. Da Y, Shi X, Krishnamurthy M (2011) Health monitoring, fault diagnosis and failure prognosis techniques for brushless permanent magnet machines. In: 2011 IEEE VPPC, Chicago, IL, pp 1–7. https://doi.org/10.1109/VPPC.2011.6043248 3. Abenoza RF, Cats O, Susilo YO (2017) Travel satisfaction with public transport: determinants. Regional disparities and their evolution. Transp Res Part A Policy Pract 95:64–84. https://doi. org/10.1016/j.tra.2016.11.011 4. Ebrahimi BM, Faiz J (2013) Demagnetization fault diagnosis in surface mounted permanent magnet synchronous motors. IEEE Trans Magn 49(3):1. https://doi.org/10.22436/jnsa.009. 05.10 5. Zykov YuV (2007) Theoretical framework of technical diagnostics of rolling stock: manual. Publishing House of USURT, Yekaterinburg 6. De Santiago J, Bernhoff H, Ekergård B, Eriksson S, Ferhatovic S, Waters R, Leijon M (2012) Electrical motor drivelines in commercial all-electric vehicles: a review. IEEE Trans Veh Technol 61(2):475–484. https://doi.org/10.1109/TVT.2011.2177873 7. Elyakin SV (2016) Locomotive traffic safety systems: manual (series of lectures). FSBEI Training center for education in railway transport, Moscow 8. Kolpakhchyan P, Zarifian A, Andruschenko A (2017) Systems approach to the analysis of electromechanical processes in the asynchronous traction drive of an electric locomotive. Stud Syst Decis Control 67:134. https://doi.org/10.1007/978-3-319-51502-1_3 9. Buynosov AP, Statsenko KA (2016) Technical diagnostics of electric rolling stock. Study guide on “Technical diagnostics of electric rolling stock” for students majoring in Electric railway transport, Yekaterinburg 10. Akimov P, Matasov A (2011) State estimation via l1-norm approximation: application to inertial navigation. In: IFAC world congress, Milan, vol 18, pp 14386–14391. https://doi.org/10.3182/ 20110828-6-IT-1002.00123 11. Cheng Y, Wang Z, Zhang W (2019) A novel condition-monitoring method for axle-box bearings of high-speed trains using temperature sensor signals. IEEE Sens J 19(1):205–213. https://doi. org/10.1109/jsen.2018.2875072 12. Chua TW, Tan WW, Wang ZX, Chang CS (2010) Hybrid time-frequency domain analysis for inverter-fed induction motors fault detection. In: IEEE international symposium on industrial electronics (ISIE), Italy, Bari
Accident Prevention System at Unguarded Railway Crossings Gayaz Akhmedzyanov , Vladimir Dremin , and Artem Litvinov
Abstract In the Russian Federation, most railway accidents take place at unguarded railway crossings. The majority of scientific papers on the topic of crossings deal with the improvement of guarded railway crossings operation. At present, there is no effective way to improve safety at unguarded railway crossings. The subject of the study is unguarded railway crossings. The aim of the paper is to develop a set of preventive measures to avoid accidents at unguarded railway crossings. The article describes the cases of traffic accidents at railway crossings of the West Siberian railway, studies the scheme of unguarded railway crossings and offers a schematic diagram of the accident prevention system at unguarded railway crossings. The work algorithm of the accident prevention system at unguarded railway crossings and the algorithm of giving the locomotive a notification of an emergency situation at unguarded railway crossings are presented. Using the existing coding scheme of the automatic continuous locomotive signaling as a transmission line for information about an emergency situation at a railway crossing allows simplifying significantly the scheme of the developed system. The paper also calculates the maximum permissible time of occupation of the crossing by motor vehicles and the time of coding change in the automatic locomotive signaling system of continuous type. The proposed accident prevention system at unguarded railway crossings does not require additional equipment to organize the communication channel and is cost-neutral. Equipping unguarded railway crossings with this system will improve train safety, reduce the number of accidents and increase the efficiency of the railway transport complex in general. Keywords Railway crossing · Traffic safety · Accident prevention system · Automatic locomotive signaling · Traffic accident G. Akhmedzyanov (B) · V. Dremin Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] A. Litvinov Omsk City Academy of the Ministry of Internal Affairs Russia, 7, Komarova Avenue, Omsk 644092, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_15
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1 Introduction Ensuring the safety of train traffic is an important task of JSC Russian Railways. Road traffic accidents (RTAs) at railway crossings account for a significant share of the total number of accidents on the railroad. The consequences of such accidents are: human casualties, damage to rolling stock and infrastructure facilities, disruption of train schedules. That is why the state and JSC Russian Railways are making a considerable effort to reduce the accident rate at railway crossings. This includes the following measures: construction of overpasses, equipment of railway crossings with crossing barriers, educational and propaganda work among drivers. But the main problem remains unsolved. The majority of accidents (81%) occur at unguarded railway crossings, where it is impossible to ensure the protection of the crossing area from road transport [1–3]. Unguarded crossings include railway crossings of the third and fourth categories. These crossings have only a warning in the form of road markings and warning signs, as well as crossing traffic lights (for crossings of the third category). Let us consider the accidents at railway crossings of the West Siberian railway. A total of 109 road traffic accidents (RTAs) were recorded from 2015 to 2020, including 105 of those (96%) at unguarded crossings. We can mention the accident on the Uryvaevo-Pankrushikha crossing. The locomotive crew of a freight train approaching a crossing (600 m before the crossing) saw a man standing on the side of the road and giving circular signals to stop the train. The driver applied emergency braking and saw a car at the crossing, which was in the oversize of the first track. Due to the short distance the collision could not be prevented. As a result of the accident, the locomotive, railway crossing and relay cabinet equipment were damaged. The train stop lasted 25 min. It is evident that in the case of early notification of the emergency situation at the railway crossings to the locomotive crew, the accident could have been avoided.
2 Materials and Methods To develop a way to warn the driver of an accident at an unguarded railroad crossing, let us consider the scheme of such a crossing (Fig. 1) [4–10]. In front of the crossing, road signs are installed and road markings are applied. Crossing lights, installed at a distance of at least 6 m from the outermost rail are used as signalization at the crossings of the third category. The scheme shows that the driver has no opportunity to assess the situation at a level crossing in advance and prevent a possible accident. There are various ways to control the situation at railway crossings [11–15]. The main methods include video surveillance cameras, GLONASS equipment, schemes of video broadcasting of the situation at the crossing and broadcasting of information from the crossing via radio channel. The common disadvantage of these methods is significant financial expenses
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ldim
lsig lconf
laxis lrail llin
lstop ltrans
Fig. 1 The scheme of an unguarded railway crossing
because of the necessity to equip all locomotives with video monitors, to equip crossings and locomotives with communication equipment, to equip crossings with video surveillance system. If we speak about modernization of unguarded crossings, these costs are unjustified due to the large number of such crossings. Let us consider the design of an accident prevention system at unguarded railway crossings. First of all it is necessary to choose the way to determine an emergency situation at a railway crossing. Since the crossing under study is unguarded, there is no person who could detect an emergency situation. Therefore, it is necessary to use technical sensors. The use of a camera as a sensor of a possible accident will make it possible to broadcast the picture from the crossing to the driver’s cab, and he himself will make decisions about the situation at the railway crossing. The disadvantages of video cameras are their high cost; interference due to atmospheric phenomena (rain, fog, snowstorms); the need for a communication channel to broadcast the image to the driver’s cab. The optimal variant is a radar sensor—similar to the sensor of the crossing area occupancy control, used at railway crossings with crossing barriers. The main advantage of the radar sensor is that it allows you to monitor each lane of the road separately. The second task in designing the system is to select the method of information transmission to the driver’s cab. There are technical solutions that use a radio channel to transmit information (Wi-Fi, Wi-Max, train radio communication). They allow transmitting a large flow of information, but their coverage range is limited and the quality of the signal is affected by atmospheric phenomena. Also, the radio channel requires expensive switching equipment both at the crossing and in the driver’s cab. The existing communication lines have been selected to be used in the project. To transmit information about an emergency situation on a railway crossing, a continuous automatic cab signaling (CACS) can be used. It transmits numerical code indications of floor traffic lights to the driver’s cab on the locomotive traffic lights. The advantage of using a CACS line is that it is possible not only to be transmit
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rs
rs
rs
Time meter
Control unit
Track circuit
Coding scheme
Car
Train
Fig. 2 The block scheme of the accident prevention system on an unguarded railway crossing
information to the train driver, but also to monitor his reaction and to force the train to brake. The block scheme of the accident prevention system on an unguarded railway crossing is shown in Fig. 2.
3 Results The system works as follows. Radar sensors (rs) monitor the zone of a railway crossing and record the occupation of the lane by motor transport. The information from the sensors is transmitted to the time meter, which measures the time of occupation of the crossing zone by an individual vehicle unit. If the time of occupation of the railway crossing zone is higher than the critical value, the information about the abnormal situation is transmitted to the control unit. A track circuit is connected to the second input of the control unit, which records the occupation of the approach section when a train appears. If a train is approaching the crossing and an abnormal situation has been detected at the railway crossing, the control unit activates the coding scheme. The coding scheme switches the code combination in the track circuit from permissive to prohibitive. Then the locomotive devices perceive the code combination and start the procedure of warning the driver and emergency train braking. The algorithm of the system is shown in Fig. 3. Let us consider the algorithm of notification of the driver about an emergency situation at a railway crossing (Fig. 4). If the system detects an abnormal situation at a railway crossing, it changes the CACS coding signals in such a way that first the code RY is transmitted, and then the coding is terminated. In this case the driver receives a command to brake, and if he does not comply with it, the brake control circuit triggers automatically. To prevent an accident at a crossing it is necessary for the train to stop before it enters the crossing. This requires not only the disappearance of the CACS code,
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Start
Is the train coming to the crossing?
Is the emergency situation eliminated
No
Yes
Yes
Train permission
Activation of the alarm system
To DTS
Has the train passed the crossing
Is the alarm system activated?
No
Yes Yes
Yes
Is there an emergency situation at the crossing?
No
Is the 2nd train coming to the crossing No
No Deactivate the alarm system
Yes Emergency train braking
End
Fig. 3 The algorithm of the accident prevention system at unguarded railway crossings
but also the execution of the algorithm shown in Fig. 4. Therefore, it is necessary to calculate the time of coding change in the CACS system. The code transmission period (t cod ) for the code track transmitter KPTSh-5 is 1,6 s, and for KPTSh-7— 1,86 s. Change of indications of a locomotive traffic light occurs after repetition of three transmission cycles. Then the time of start of braking (t stop ) of the train will be defined as: tstop = tr−y + t0 = 3tcod + 3tcod = 6tcod .
(1)
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ASC initial code Receiving code G
Yes Changing from code G to code RY
No Receiving code Y
Yes Changing from code Y to code RY
No
Receiving code RY
Yes Coding deactivation
No Audio visual notification to the driver Acknowledging No Forced operation of the brake line
Yes
Train braking
Train stop End
Fig. 4 The algorithm of notification to a locomotive about an emergency situation at an unguarded railway crossing
The time of the beginning of braking for KPTSh-5 is 9.6 s, and for KPTSh-7— 11.16 s. The train moving at a speed of 80 km/h, for this time will pass 215 m and 250 m respectively. Consequently, there is enough time for braking to prevent an accident. To accurately determine the emergency situation it is necessary to calculate the maximum permissible time of occupation of the crossing by vehicles. If this time is exceeded, the system will decide on the occurrence of an emergency situation at the crossing and will begin to transmit this information to the driver. Calculation will be performed on the basis of the crossing scheme shown in Fig. 1. Let us
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consider the case with the worst conditions: the minimum speed of vehicles vrans — 8 km/h, the maximum length of vehicles lrans —24 m, the most common type of crossing—two-lane, crossing a double-track railroad. The maximum time of vehicles in the conflict zone is equal: tmax = tcros + trans + tres .
(2)
Substituting the known distances and the speed of the car we get: tmax = (lcros + lrans )/0.28vrans + tres .
(3)
The length of a double-track crossing includes the distance from the stop line to the rail (llin = 10 m), the track width (lrail = 1.5 m), the distance between the track axes (laxis = 4.1 m), and the clearance distance (ldim = 2.5 m). Guaranteed reserve time is (t res = 10 c). Then: tmax = ( llin + lrail + laxis + ldim + lrans )/0.28vrans + tres .
(4)
Substituting the calculated value we obtain: tmax = (10 + 1, 5 + 4, 1 + 2, 5 + 24)/0.28 · 8 + 10 = 28, 8 ≈ 30. Thus, when the reading of the short-circuit sensor exceeds the time value of 30 s, the decision about an abnormal situation is made and the algorithm of notification of the notification of a train driver about this situation starts.
4 Conclusions The obtained system of accident prevention at unguarded railway crossings allows the driver to receive information about an emergency situation at unguarded crossings. The system is cost-neutral and does not require any additional equipment to organize a channel for communication. To estimate the performance characteristics and reliability of the system it is necessary to produce a prototype and equip the pilot area of the railroad with it. The improvement of traffic management at unguarded railway crossings makes it possible to increase the train safety and reduce the number of traffic accidents. Reducing train downtime due to accidents at railway crossings and schedule violations will increase the efficiency of the railway transport.
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References 1. Office of the National Rail Safety Regulator (2018) Rail safety report 2017–2018. ONRSR, Adelaide. https://nraspricms01.blob.core.windows.net/assets/documents/Publication/17789ONRSR-Safety-Report-Spreads.pdf 2. Office of Rail Regulation (2018) Business plan 2018–19. ORR, London. http://orr.gov.uk/__ data/assets/pdf_file/0006/27465/orr-business-plan-2018-19.pdf. Authored 13 Apr 2018 3. European Union Agency for Railways (2018) Railway safety in the European Union: safety overview 2017. Publications Office. https://data.europa.eu/doi/10.2821/813806 4. Bari´c D, Pilko H, Starˇcevi´c M (2018) Introducing experiment in pedestrian behavior and risk perception study at urban level crossing. Int J Injury Control Saf Promot 25(1):102–112. https:// doi.org/10.1080/17457300.2017.1341934 5. Beanland V, Grant E, Read GJ et al (2018) Challenging conventional rural rail level crossing design: evaluating three new systems thinking-based designs in a driving simulator. Saf Sci 110:100–114. https://doi.org/10.1015/j.ssci.2018.03.002 6. Larue GS, Wullems C (2015) Driving simulator evaluation of the failure of an audio invehicle warning for railway level crossings. Urban Rail Transit 1(3):139–148. https://doi.org/10.1007/ s40864-015-0018-5 7. Mulvihill CM, Salmon PM, Beanland V et al (2016) Using the decision ladder to understand road user decision making at actively controlled rail level crossings. Appl Ergon 56:1–10. https://doi.org/10.1016/j.apergo.2016.02.013 8. Stefanova T, Oviedo-Trespalacios O, Freeman J et al (2018) Contextual factors explaining risk-taking intentions at Australian level crossings. Saf Sci 110:145–161. https://doi.org/10. 1016/j.ssci.2018.03.004 9. Tjahjono T, Kusuma A, Pratiwi YY, Purnomo RY (2019) Identification determinant variables of the injury severity crashes at road-railway level crossing in Indonesia. Transp Res Procedia 37:211–218. https://doi.org/10.1016/j.trpro.2018.12.185 10. Haperen W, Sarmad Riaz M, Daniels S et al (2019) Observing the observation of (vulnerable) road user behavior and traffic safety: a scoping review. Accid Anal Prev 123:211–221. https:// doi.org/10.1016/j.aap.2018.11.021 11. Khattak A (2009) Comparison of driver behavior at highway–railroad crossings in two cities. Transp Res Rec J Transport Res Board 2122:72–77. https://doi.org/10.3141/2122-09 12. Larue GS, Naweed A, Rodwell D (2018) The road user, the pedestrian, and me: investigating the interactions, errors and escalating risks of users of fully protected level crossings. Saf Sci 110:80–88. https://doi.org/10.1016/j.ssci.2018.02.007 13. Liu J, Khattak AJ (2017) Gate-violation behavior at highway-rail grade crossings and the consequences: Using geo-spatial modeling integrated with path analysis. Accid Anal Prev 109:99–112. https://doi.org/10.1016/j.aap.2017.10.010 14. Rudin-Brown CM, Lenné MG, Edquist J, Navarro J (2012) Effectiveness of traffic light vs. boom barrier controls at road–rail level crossings: a simulator study. Accid Anal Prev 45:187– 194. https://doi.org/10.1016/j.aap.2011.06.019 15. Salmon PM, McClure R, Stanton NA (2012) Road transport in drift: applying contemporary systems thinking to road safety. Saf Sci 50:1829–1838. https://doi.org/10.1016/j.ssci.2012. 04.011
Analyzing the Movement of a Freight Train at Stops on Flat Sections of the Railway Oleg Ablyalimov , Sergey Petrochenko , and Nozimjon Kodirov
Abstract The article presents the results of the substantiation of the dynamics of kinematic parameters of the freight train movement on a virtual flat section of the railway organized by electric locomotives 3VL80C when stopping at an intermediate and final stations. The realization of this research goal was carried out using the methods of locomotive traction theory, taking into account the graphical solution of the equation of train motion and modeling of the transportation work of electric traction locomotives. The obtained kinematic parameters of the stopping process of freight trains of various weights and regression equations for determining the above-mentioned parameters on virtual and, identical to them, real sections of railways constitute the practical significance of this research and are recommended for implementation in the work of enterprises of the locomotive complex. Keywords Research · Result · Freight train · Electric locomotive · Railway · Parameter · Passing loop · Analysis · Station · Time · Speed · Plain · Virtual
1 Introduction Ensuring economical consumption of fuel and energy resources by traction electric and diesel rolling stock of railways is a well-known problem. In the study [1] shows that one of the essential components of the energy consumption rate in operation is the specified consumption associated with train stops, which also increases with increasing mass of the train. The research papers [2–4] provide an analysis and evaluation of the efficiency of the use of electric traction locomotives, in particular, electric locomotives 3VL80C on a virtual flat section of the railway. Moreover, [4] proposes a method of analytical and graphical calculation of the kinematic parameters O. Ablyalimov (B) · N. Kodirov Tashkent State Transport University, Street Adylkhodzhaeva, 1, 100067 Tashkent, Uzbekistan e-mail: [email protected] S. Petrochenko Omsk State Transport University, Prospekt Marksa, 35, 644046 Omsk, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_16
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of the freight train movement at stops at various stations. Thanks to this technique, study [5] obtained the values of some (two–ways of deceleration and acceleration, and the speed of movement during braking and acceleration) kinematic parameters of the movement of freight trains organized by 3VL80C electric locomotives, when stopping on a virtual flat section of the railway, depending on the mass of the train. However, for such a kinematic parameter as the train’s acceleration–deceleration time, a comparative analysis was not carried out in full. The authors of studies [6–8] propose to ensure high operational reliability of units, systems and assemblies of locomotives along the route not only through further improvement of service maintenance and repair of locomotives, but also in connection with the use of modern developments in the electrical industry and computer technologies in operating conditions. Studies [9, 10] are devoted to studying the possibilities of reducing the consumption of fuel and energy resources for train traction, in which it is proposed to save full-scale diesel fuel by diesel locomotives and electric energy by traction electric rolling stock by optimizing the operating modes of power power plants (systems) of diesel and electric traction locomotives. The process of transferring electrical energy from the contact wire to the equipment of the traction and power system of a moving electric rolling stock through a current collector (pantograph) with a sliding electrical contact in the area of insulators and neutral inserts of the contact network in relation to high-speed railways is devoted to works [11–13]. Here, the authors recommend improving (increasing) the qualitative component of the current collection process, both by optimizing the current collection modes by normalizing the upper and lower limits of contact pressure, and by using mechanical and electrical means of protection against the occurrence of any kind of resonant phenomena in this case. The authors of studies [14, 15] in case of a forced stop of a train under a neutral insert in order to remove it from this place, recommend using normally open sectional disconnectors with a manual drive and a grounding knife to temporarily supply voltage to the neutral insert from the direction of train movement. The results of studies [6–15] have a certain scientific interest and practical significance, but they are not at all interconnected with the substantiation of the parameters of the main indicators of the energy intensity of transportation work and the efficiency of the use of traction rolling stock in relation to the real conditions for organizing freight traffic on the railway sections (section) of the Uzbek railways taking into account the degree of complexity of their path profile. Therefore, the urgency of the technical problem related to the verification of all kinematic parameters of freight train movement at stops on railway sections of various complexity is obvious, and the solution of this problem, in our opinion, is of practical interest to specialists and researchers of the railway locomotive complex. The purpose of this study is to clarify the kinematic parameters pertaining to the path of movement and the speed of freight trains, taking into account the acceleration–deceleration time at the moment of the organization of stopping process at the intermediate and final stations of the virtual flat section of the railway, where organizational, technological and technical operating conditions are similar to real ones.
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2 Materials and Methods The present research is a logical continuation of the papers [2–4] and therefore the basis of the developed algorithm for implementing the research goal formulated above were the methods and techniques [1] of the theory of locomotive traction, the initial data [2, 5] on the material and technological conditions for organizing the transportation work of freight locomotives on the straightened track profile of the railway section under study, the object and subject of research. The object of the study are freight trains with different weights and the same number of axles of the rolling stock, three-section mainline (train) freight electric locomotives of the series 3VL80C and a straightened track profile of the first type of virtual flat section of the railway. The subject of the study is the kinematic parameters of the movement of a freight train, taking into account the analysis of its stopping at the intermediate and final stations of the specified railway section for three masses and a constant number of axles of the train. In the manual [16] and studies [2, 3], respectively, the design features, technical parameters, energy and operational indicators of the 3VL80C electric freight locomotive are covered in detail and a comprehensive description of the straightened track profile of the virtual flat section of the railway is provided. The analysis of the movement trajectory of a freight train with different masses of rolling stock [2–4] indicates that the transportation process of goods by railway occurs at a uniform speed, where the dynamics of fluctuation does not exceed the interval of the specified speed V = 10 km/h. Table 1 shows the factual numerical values of the movement speeds and travel time of a freight train when it stops at intermediate and terminal stations. Figure 1 shows the dynamics of changes in the factual length of the track that freight trains pass in case of stops at the intermediate and terminal stations, taking into account their travel time at the moment of braking and as acceleration is completed at these stations. Similarly [5], in Table 1 and in Fig. 1 the following notation is introduced: Vd and Vd —the speed of a freight train in early deceleration at the intermediate and terminal stations respectively; Va is the speed of a freight train at the time of regaining nonstop speed at an intermediate station; td and td is the deceleration time of a freight train in the intermediate and terminal stations respectively, in case of freight train braking; ta is the time of a freight train acceleration at an intermediate station when starting from a standstill; Sd and Sd is the path of freight train deceleration in the intermediate and terminal station respectively, in case of freight train braking; Sa is the acceleration path of a freight train at an intermediate station when starting. The interpretation (definition) of these kinematic parameters is given in studies [4, 5]. For better clarity of the graphical dependencies in Fig. 1, the deceleration time td and acceleration time ta of a freight train in case of its braking at an intermediate station are reduced, respectively, by 1.5 times and 2.0 times.
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Table 1 Kinematic parameters of the movement of a freight train when braking and starting from a place at an intermediate and terminal station, electric locomotive 3VL80C № n/p
1
Conditions of transportation work
Kinematic parameters of a freight train
weight of rolling stock Q, t
Number of axles m, axles
Speed of movement during braking and acceleration
Deceleration time
Station B, Vd
Station S, Vd
Station V, Va
Station V, Δtd
Station S, Δtd
Station V, Δta
2
3
4
5
6
7
8
9
With an increase in the weight of rolling stock 1
2500
200
96
98
98
1.40
1.40
1.80
2
3000
200
94
97
93
1.80
1.50
1.75
3
3500
200
92
95
89
1.90
1.70
1.95
4
Average values
94
96.7
93.3
1.70
1.53
1.83
With a decrease in the weight of rolling stock 1
3500
200
92
95
89
1.90
1.70
1.95
2
3000
200
94
97
93
1.80
1.50
1.75
3
2500
200
96
98
98
1.40
1.40
1.80
4
Average values
94
96.7
93.3
1.70
1.53
1.83
Fig. 1 Kinematic parameters of the stopping process of a freight train at the intermediate and terminal stations, electric locomotive 3VL80C
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3 Results Preliminary analysis of the research results indicated in Table 1 and in Fig. 1 shows that increasing the weight of the freight train rolling stock in case of its breaking at an intermediate and terminal station contributes to the increase in the deceleration time td , td and acceleration time ta and also the deceleration path Sd , Sd and acceleration path Sa with the decrease in their velocity Vd , Vd and Va . The dynamics of changes in kinematic parameters in terms of travel time, travel path and speed of the stopping process of a freight train within the given range of the freight train weight differentiation from Q1 = 2500 t to Q3 = 3500 t by Q = 500 t is described by the following regression equations. Deceleration time td of a freight train when braking at an intermediate station, km: td = 0.125Qi2−0.425Qi + 2.1, R2 = 1.0.
(1)
Deceleration time td of a freight train when braking at a terminal station, km: td = 0.05Qi2−0.05Qi + 1.4, R2 = 1.0.
(2)
Acceleration time ta when starting a freight train at an intermediate station, km: ta = −0.15Qi2 + 0.85Qi + 0.7, R2 = 1.0
(3)
Deceleration path Sd of a freight train when braking at an intermediate station, km: Sd = 0.075Qi2−0.175Qi + 2.45, R2 = 1.0.
(4)
Deceleration path Sd of a freight train when braking at a terminal station, km: Sd = 0.1Qi2−0.2Qi + 2.25, R2 = 1.0.
(5)
Acceleration path Sa when starting a freight train at an intermediate station, km: Sa = −0.1Qi2 + 0.55Qi + 2.5, R2 = 1.0.
(6)
Speed Vd at the beginning of braking of a freight train at an intermediate station, km/h: Vd = −2Qi + 98, R2 = 1.0.
(7)
Speed Vd at the beginning of braking of a freight train at a terminal station, km/h:
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Vd = −0.5Qi2 + 0.5Qi + 98, R2 = 1.0.
(8)
Speed Va at the end of the acceleration of the freight train at the intermediate station, km/h: Va = 0.5Qi2−6, Qi + 104, R2 = 1.0.
(9)
In formulas (1)–(9), the sufficient value of the approximation accuracy is R 2 = 1.0 (the necessary condition for reliability is R 2 ≥ 0.8), and the value Qi = 1, 2, 3 denotes the variants of the traction calculation.
4 Conclusions From the above-mentioned regression equations it can be seen that the dynamics of the mentioned kinematic parameters depending on the change in the weight of freight train rolling stock is described by a polynomial of the second degree. The exception is the movement speed Vd at the beginning of braking of a freight train at an intermediate station (linear dependence). As a result of our research, the kinematic parameters of the movement of freight trains and electric locomotives 3VL80C were substantiated in the form of tabular data and graphical dependencies, and regression equations were obtained to determine the main kinematic parameters of the transportation work of the electric traction locomotives under study, including the stopping process, on virtual and, identical to them, real flat sections of the railway. The obtained kinematic parameters can be implemented in the practice of the locomotive depots of the Uzbek railways for the real conditions of the organization of the operation of three-section mainline freight electric locomotives of the 3VL80C series on flat areas.
References 1. Ablyalimov OS (2020) The exploitation of the 3VL80S electric locomotives on the plain of railway district. J Univers Tech Sci 1(7)(76):59–67. https://doi.org/10.32743/UniTech.2020. 76.7-1 2. Ablyalimov OS (2021) Research of the efficiency of locomotive UzTE16M3 operation and tractive qualities of the rail track profile Marokand - Navoi line of Uzbek railway. J Modern Probl Russian Transp Complex 11(1):18–28. https://doi.org/10.18503/2222-9396-2021-11-118-28 3. Ablyalimov OS (2018) Analysis of the efficiency of transportation work of 3VL80S electric locomotives at the Kattakurgan - Navoi section of the Uzbek railway. J Modern Technol Syst Anal Model 4(60):70–79. https://doi.org/10.26731/1813-9108.2018.4(60).70-79
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4. Ablyalimov OS (2016) The effectiveness evaluation of the diesel locomotives 3T10M utilization between Marokand - Kattakurgan on the Uzbek railways. J Modern Probl Russian Transp Complex 6(2):16–22. https://doi.org/10.18503/2222-9396-2016-6-2-16-22 5. Ablyalimov OS (2020) Energy efficiency analysis of traction rolling stock of railways. J Univers Tech Sci 1(9)(78):85–87. https://doi.org/10.32743/UniTech.2020.78.9-1 6. Anand MD et al (2008) Fault diagnosis system for a robot manipulator through neuro-fuzzy approach. Int J Model Identif Control 3(2):181–192 7. Michal G, Huynh N, Shukla N, Munoz A, Barthelemy J (2017) RailNet: a simulation model for operational planning of rail freight. Transp Res Procedia 25:461–473. https://doi.org/10. 1016/j.trpro.2017.05.426 8. Li N (2010) Research on electromagnetic transient process of electric locomotive system. Beijing Jiaotong Univ, Beijing 9. Mulder M (2014) Transnet diesel locomotive fuel consumption tables. Transnet Freight Rail, Train Design Department, Pretoria 10. Mayet C et al (2014) Influence of an energy storage system on the energy consumption of a diesel-electric locomotive. IEEE Trans Veh Technol 63(3) 11. Liu YJ et al (2010) Mayr’s equation-based model for pantograph Arcof high-speed railway traction system. IEEE Trans Power Delivery 25(3):2025–2027 12. Fang ZG (2010) Application of transient overvoltage suppression technique for EMU autopassing the neutral section with on-board switch closed. Railway Tech Innov l(1):44–46 13. He ZY et al (2011) Research on the harmonic in high-speed railway traction power supply system and its transmission characteristic. Proc CSEE 31(16):55–62 14. Li S, Lv H, Xu C, Chen T, Zou C (2020) Optimized train path selection method for daily freight train scheduling 8:40777–40790 15. Wen JM et al (2011) Research and using on auto-passing phase separation control strategy of high-speed EMU. Railway Stand Des 4:104–108 16. Naidoo PN, Mulder JM (2017) Improved distributed power train handling strategies. In: 11th international heavy haul association conference, pp 765–773
Computer Modeling of Repair Technological Systems in Design Practice Viktor Smirnov
Abstract The paper deals with the creation of computer simulation models of technological systems for the repair production of rolling stock. The analysis of known methods of mathematical modeling is carried out. Their advantages and disadvantages are evaluated when used to solve optimization problems of design solutions. The requirements for computer models are formulated, the description of the modeling problem and its solution based on the modular principle of pattern networks are given. An elementary element of the model is the so-called Pattern, which has a set of certain properties, incoming and outgoing connections. By combining individual modules into a network, it becomes possible to create regular configurations, models of various technological equipment with continuity of algorithmic and information structure. According to the simulation experiment, a set of indicators characterizing the system performance, the use of equipment and means of delivery, and the quality of planning solutions are evaluated. The data of practical approbation of the proposed method in the design of objects of locomotive and car facilities are given. As a result of computational experiments, the calculated confirmation of the effect of the volume of work in progress on the performance of the technological system was obtained; the fact of the nonlinear dependence of the increase in the production capacity of the enterprise on the increase in the productivity of the main equipment was confirmed. Keywords Repair of rolling stock · Technological design · Mathematical modeling · Simulation model · Pattern networks
1 Introduction The design of technological repair systems is a complex multi-operational task, solved in several stages, including: goal setting, conceptual (preliminary) design, schematic design, technological design with the development of an executive project. Each of the stages is characterized by its own methods of checking and optimizing V. Smirnov (B) Omsk State Transport University, Prospekt Marksa, 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_17
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design solutions. The most difficult is the final stage—technological design, which is connected with a high degree of detail of the object representation, taking into account the functional relationships of its individual elements and subsystems [1, 2]. The basis for the development of design solutions are the classical design postulates—the direct flow principle, technological closure and others. However, it should be noted that the very observance of these principles does not imply obtaining a design solution in the form of a single option. Each individual design solution based on a set of operations and design procedures under conditions of uncertainty of the entire set of parameters of the technological system assumes the presence of several alternatives [3–7]. Thus, the task of optimizing a technological project is reduced to obtaining a certain set of rational options, choosing the best option, and then clarifying and correcting this option using special methods of project analysis based on the results of mathematical modeling. In the study of technological systems of enterprises and organizations, it is customary to distinguish several approaches based on a different representation and mathematical description of the target function of the object of research [8, 9]. System-Functional Approach. The most common, simple, and accessible approach based on the description of the target function of the production and technological system (F) in the form of a “black box”. A “black box” refers to a system with an unknown internal structure. The concept of “black box” was proposed by W. R. Ashby and assumes two types of models. The first type includes any models of production and technological systems considered as a finite or infinite automaton [10–13]. The use of models of this class allows us to study the behavior of technological systems, that is, their reactions to a variety of external influences and at the same time prescind from their internal structure. System-Structural Approach. In contrast to the general theory of systems, which is distinguished by the lack of a clear subject-material field of research, in the theory of organization, it is customary to refer to structure {S} as the composition of both the objects themselves and the set of stable technological connections between them, which ensure its integrity and the preservation of the basic properties of the system under various external and internal changes [8, 9]. The description of the production and technological structure of the enterprise as an isolated system can be represented in the form of corresponding graphs. According to the method of modeling, when implementing the modeling approaches described above, analytical, statistical and simulation models are distinguished. Analytical models. are some kind of mathematical relations linking the structural parameters of the system with the indicators of its functioning. Graphs, linear and nonlinear equations, mathematical series, polynomials of various degrees, artificial neural networks, etc. can be used to obtain ratios [8, 10]. For example, when assessing the production potential, the method of direct calculations is most often
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used, which involves calculating the direct impact of changes in the factor forming the production potential on the quantitative characteristics of the production capacity of the enterprise [14]. Factors that do not have direct quantitative measurement, as a rule, are taken into account by the expert method and are introduced in the form of appropriate correction coefficients. The expert method is based on the generalization of experience, knowledge, observations of specialists, allowing them to systematize and identify patterns. The experts’ assessment is taken into account by adjusting the measured parameters of the technological system according to the corresponding calculated coefficients of the time of technological operations at the workplace, indicators of internal return and repair program, the algorithm of the management and logistics system, additional restrictions on the availability of resources, and so on. Statistical research. methods allow us to identify certain stable patterns and dependencies between the significance of factors and the significance of indicators. For example, in practice, multivariate and univariate regression equations and correlation analysis equations are most often used to establish the forms of relationships between productivity and other parameters of processes and machines [15, 16]. In addition to multidimensional regression models, univariate correlation analysis equations are often used in practice to establish a relationship between performance and any single factor. Correlation coefficients and standard deviations of parameters are estimated for them, for example, according to the Pearson criterion [17]. Summarizing the above, it can be stated that the use of analytical models allows us to give only an approximate assessment of the work of the production and technological complex of the enterprise, which does not take into account a number of important factors related to the probabilistic nature of changes in the program and the volume of repairs for individual units and aggregates of rolling stock. Significant opportunities for the study of the processes of functioning of production systems are made available with the use of computer simulation methods, the methodology of which is described in sufficient detail in a number of recent scientific articles and monographs [18, 19]. Simulation modeling is most actively used primarily to solve problems of analyzing the dynamic behavior of production systems [20–22]. The peculiarity of creating simulation models used in the analysis of technological design solutions is the requirement for their high degree of detail. The use of traditional methods of creating simulation models described above entails considerable complexity and requires a lot of time to create models due to the lack of continuity of the algorithmic and information structure of individual elements of models, which practically excluded their practical use in scientific and engineering design practice.
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2 Materials and Methods Based on the basic principles of the “paradigm of modular thinking” [23, 24], with the participation of the author of the article, a methodology of the modular principle of creating simulation models of technological processes of repair and maintenance of railway rolling stock based on the theory of patterns and oriented pattern networks has been created and successfully implemented in practice for a number of years [25]. The modeling is based on the representation of the technological process of production in the form of a network, set on the basis of a formalized description of a real-operating or projected enterprise or one of its structural divisions. The basic concept of pattern theory is the concept of an abstract generator (pattern module) and its inseparable connections. Pattern networks are constructed from generators, by pairwise combining the connections of various generators into clusters. The set of all generators is called the composition of the network, and the set of all clusters is called the structure. The set G of the generators of the network is finite and the generators are numbered. Each generative g ∈ G is completely determined by the vector of its features: in in out , . . . , βim , βi1 , . . . , βirouti , a(g) = a i, γi1 , . . . , γil i , βi1 i
(1)
where i is the ordinal number of the generator; γik , k = 1, . . . , li —attributes of the in ,k = generator; m i and ri is the number of incoming and outgoing connections; βik out 1, . . . , m i and βik , k = 1, . . . , ri —indicators of the input and output connections of the generator. The attributes and indicators of the links of the generators are variables. Sets Dik , in out in and Dik of acceptable values of variables γik , βik and βikout determine the inforDik mation content of the generator and are called domains of the corresponding variables. For discrete pattern networks, the domains of all variables are finite or countable sets. The composition, structure and content determine the structural skeleton of the network. On each cluster of the pattern network, a binary relationship is established between two variables β out and β in , called the connections relation, which takes the value “true” (connected state) or “false” (disconnected). The structural connections of pattern networks are always true, and each cluster of the associated pattern network can be in two states—true or false. The state of the cluster depends on the values of the corresponding indicators of the connections. The generator can be visually represented in the form of a graphical diagram. The input and output connections of oriented generators depicted in the diagrams clearly represent the inputs and outputs of technological operations with a number k (Fig. 1). For a technological network, the generators are technological operations. The number of incoming and outgoing connections of the generator is determined by the type and relationships of the technological operation. The domains of the generators attributes contain possible values of the parameters of technological operations, the
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Fig. 1 Representation of the generator in the form of a graphic scheme
conditions for their execution and other necessary information. Technological positions and sections are standard fragments of a common network—regular configurations made up of combinations of pattern modules, the connections between which are completely determined by the technological process of repair. The pattern network is a medium for discrete dynamic modeling of technological processes of rolling stock repair. The operation of the model is based on the principle of modeling special states of the system—characteristic events occurring at the time of the application for transport services at the end of a technological operation. The event serves as a condition for connecting the clusters of the pattern network. Based on the results of simulation modeling, parameters and indicators reflecting the operation of the technological system are estimated: productivity, repair time, load coefficients of technological and lifting equipment during the working shift, queue length and waiting time for transport services, the number of parts in storage. The algorithm for simulating the operation of the technological system under study consists in a step-by-step change in the state of the model (Fig. 2). At the first step, the parameters of the model and computational experiment are set, as well as the initial values of the variables (block 1). The model implements the principle of dynamic formation of associated pattern networks with a discrete time step. The moment of the current time change is determined by the fact of execution of the application—a technological operation or an operation to transfer the repair object (block 2). At the initial moment of time, applications are received for transferring repair objects to the workshop. At each step, according to the set priorities, out of the many requests to transfer a repair object the most “important” one is selected and executed in whole or in part (block 3). The choice from the set of applications for transport services is made by the module in accordance with the algorithm of the production management system, the possible options of which were described earlier when presenting the object of modeling. The calculation of the model time is carried out as follows. If there are no applications with a receipt time less than or equal to the current value of the model time (block No. 4), then the current time increases to the nearest time of receipt of the application (block No. 5). If the application is executed, the application service time is added to the current model time (block No. 6).
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1 Start 2 Setting initial parameters 3 Formation of applications 4 Selecting a request for execution 5 Has the application
NO
9 Time increase by 1 minute YES
YES 6 Increasing the current time for the time of application execution 7 Changing position status parameters:
10 t < T NO 11 Report generation
1) queues in storage devices; 2) list of operations; 3) list of applications; 4) position status indicator; 5) list of external requirements.
END
8 Editing application parameters. Formation of internal applications Fig. 2 Algorithm for modeling the operation of a technological system
With the full or partial execution of the application, the current time, the position of lifting and transport mechanisms, the parameters of the state of the positions change, the queues of applications in the storage are updated, technological operations are performed when the necessary conditions are met (block No. 7), new applications are formed and existing applications are edited (block No. 8). If the current model time is t less than the estimated simulation time T (block No. 9), then the described algorithmic cycle is repeated, in the opposite case, the computational experiment is completed and the report is generated (block No. 10).
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3 Results
5
1,0
4
0,8 Crane load factor
Productivity, motor/day
The proposed methodology for creating simulation models was tested during the development of a model of the workshop for the repair of traction electric motors for the technological project of the Kinel locomotive repair depot of JSC “Russian Railways”. According to the technical specification for the design, the workshop should carry out repairs with disassembly of engines in the amount of 2,800 engines per year. The workshop’s working hours are 7 days a week for 12 h a day. The project provides for in-line organization of repair of electric motors according to the U-shaped flow scheme (Fig. 3). An overhead support crane with a control cabin is used to move repair objects. The execution of applications is carried out on the principle of a simple queue— “first come, first served”. The scope of technological operations was adopted in accordance with the Manual for Maintenance and current repair of electric locomotives. Figure 3 shows the results of a series of computational experiments to determine
3 2 1 0
0,4 0,2 0
5 10 15 20 25 30 Number of motors in the shop
5
30 25 15 10 20 Number of motors in the shop
7000 Average motor repair time, min
5 Average queue length
0,6
4 3 2 1
0
5
10
20
25 30 Number of motors in the shop 15
6000 5000 4000 3000 2000 1000 0
0
5
10 15 20 25 30 Number of motors in the shop
Fig. 3 Shop operation parameters based on simulation results with different volume of work in progress
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the optimal number of repair facilities simultaneously involved in the production process in order to achieve the highest system performance while maintaining the repair cycle time and queues in storage devices within acceptable limits. Thanks to simulation modeling, the boundaries of the optimal volume of workin-progress can be obtained to achieve maximum performance of the technological system under specified repair time constraints. For the example under consideration, these limits were 3 p and 1, 5 p respectively, where p is the performance of the limiting equipment (units per day). It is important to note the nonlinear nature of the dependence of the production capacity of the technological system on the performance of the main technological equipment. The nonlinearity is due to the limitations of the transport system and the progressive increase in non-manufacturing costs. In the example under consideration, with a doubling of equipment productivity, a 30% increase in workshop capacity was observed.
4 Conclusion As a result of computational experiments, the adequacy of the proposed modeling method was confirmed; the need to clarify the calculated performance values with simulation data was proved; the calculated confirmation of the effect of the volume of work in progress on the performance indicators of the technological system was obtained; the fact of the nonlinear dependence of the increase in the production capacity of the enterprise on the increase in the productivity of the main equipment was confirmed. The proposed methodology makes it possible to model the work of rolling stock repair enterprises with a high degree of detail, while the modular construction principle ensures the continuity of the algorithmic and information structure of the models of individual elements, which significantly reduces the time and complexity of their creation. Among the most important conclusions of these studies the following should be noted: 1. The necessity of clarifying the design performance data obtained analytically by the results of simulation modeling is proved. 2. The calculated confirmation of the influence of the volume of work-in-progress on the performance indicators of the technological system was obtained. The presented graphs clearly show: a zone of steady growth, then saturation, peak productivity, decline and stabilization. Hence the statement about the need for monitoring the receipt of repair objects in order to achieve maximum productivity. 3. The fact of the nonlinear dependence of the increase in the production capacity of the technological system on the increase in the productivity of the main technological equipment due to the increase in losses and the emergence of additional restrictions on the part of the transport system is confirmed.
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4. A real tool has been created to solve the problems of optimizing production logistics and, in particular, to solve the problem of optimal technological zoning of a multicomponent transport system. In addition to directly analyzing and optimizing design solutions, using the created models, a wide range of problems can be investigated to assess their impact on the performance of an enterprise, such as production logistics and procurement, the organization of a repair quality control system, methods of managing the production process.
References 1. Michael S, Siegfried W (2004) Fabrikplanung und Fabrikbetrieb: Methoden für die wandlungsfähige und vernetzte Fabrik. https://doi.org/10.1007/3-540-35046-2 2. Grundig C-G (2018) Fabrikplanung. Carl Hanser Verlag, München, Wien 3. David S, Cochran ER (2020) Sustainable enterprise Design 4.0: addressing Industry 4.0 technologies from the perspective of sustainability. Procedia Manuf 51:1237–1244. https://doi.org/ 10.1016/j.promfg.2020.10.173 4. Michael S, Siegfried W (2006) Planungsphasen, -objekte und -instrumente. https://doi.org/10. 1007/3-540-35046-2_4 5. Fridrikhson O, Mishkurov P, Bodnar O, Kornilov S, Say V (2021) Methodology for justification of the location of railcar repair complex enterprises. Transp Res Procedia 54:419–428. https:// doi.org/10.1016/j.trpro.2021.02.091 6. Abdallah T (2017) Chapter 2 - infrastructure, facilities and vehicles. In: Abdallah T (ed) Sustainable mass transit. Elsevier, pp 15–29. https://doi.org/10.1016/B978-0-12-811299-1.000 02-2 7. Mulder H (2006) Rapid enterprise design. https://doi.org/10.13140/RG.2.2.26057.95840 8. Bangsow S (2016) Modeling of production processes. https://doi.org/10.1007/978-3-319-195 03-2_3 9. Ashlock D (2006) Evolutionary computation for modeling and optimization. Springer, New York 10. Law A, Kelton D (2014) Simulation modeling and analysis 11. Novikov DA (2016) Cybernetics. Springer. https://doi.org/10.1007/978-3-319-27397-6 12. Guzzella L, Onder CH (2010) Introduction to modeling and control of internal combustion engine systems. Springer, Heidelberg, 354 p. ISBN 978-3-642-10774-0 13. Hanci A, Gokbay I (2020) Analysis of software test design techniques by mathematical modelling, pp 88–93. https://doi.org/10.1109/UBMK50275.2020.9219451 14. Karpichev V, Sergeev K, Bolotina A (2019) Modeling of technological processes of machinebuilding and repair manufacture. Commun Sci Lett Univ Zilina 21(4):59–62. https://doi.org/ 10.26552/com.C.2019.4.59-62 15. Doronina E, Skatkov A, Doronina Yu (2021) Modeling maintenance and repair intensity of production system based on variable structure process, pp 774–778. https://doi.org/10.1109/ ICIEAM51226.2021.9446413 16. Naab T (2017) Statistics, descriptive. In: The international encyclopedia of communication research methods. https://doi.org/10.1002/9781118901731.iecrm0241 17. Jay D, Kenneth B, Matthew C (2021) Chi-squared tests. https://doi.org/10.1007/978-3-03055156-8_13 18. Reyes-Álvarez L, Jaime F, Rodríguez-Muñiz L, Díaz I (2017) Towards an ontological model for technological systems structure representation. Int J Uncertain Fuzziness Knowl-Based Syst 25:37–55. https://doi.org/10.1142/S0218488517400104
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19. Orazbayev B, Ospanov Ye, Orazbayeva K, Makhatova V, Kurmangaziyeva L, Utenova B, Mailybayeva A, Mukatayev N, Toleuov T, Tukpatova A (2021) System concept for modelling of technological systems and decision making in their management: monograph. https://doi. org/10.15587/978-617-7319-34-3 20. Fox W, Burks R (2021) Simulation models. In: Advanced mathematical modeling with technology, pp 391–439. https://doi.org/10.15587/978-617-7319-34-3. https://doi.org/10.1201/978 1003046196-9 21. Kormin T, Ovchinnikova V, Tsumbu J-D (2021) Simulation modeling of manufacturing. IOP Conf Ser Mater Sci Eng 1047:012090. https://doi.org/10.1088/1757-899X/1047/1/012090 22. Jaeseok C, Kwang L (2021) Probabilistic production simulation model. https://doi.org/10.1002/ 9781119819042.ch5 23. Ulf G, Michael M (2007) Pattern theory: from representation to inference. ISBN 9780199297061 24. Grenander U, Miller M (2006) The canonical representations of general pattern theory. https:// doi.org/10.1093/oso/9780198505709.003.0007 25. Smirnov VA, Semenov AM (2012) Modular principle of rolling stock repair modeling. World Transp 3:158–163
Improvement of Methods of Energy Optimal Automatic Operation of Electric Freight Locomotives Egor Avdienko
and Evgeniy Tretyakov
Abstract The paper presents a comparative analysis of the existing methods, tools and technologies to improve the efficiency of operation of electric rolling stock through automatic operation on the level of current unmanned railway transport technologies established by the International Electrotechnical Commission Standard. The paper substantiates the requirements and operation features of automatic train operation systems when more advanced levels of electric locomotives automation are introduced within the framework of digital transformation of transport system. These include a complete rejection of simplified traction calculations with the determination of all necessary parameters based on actual data measured in real time including the limitations of the track and energy infrastructure, the statuses of the nearest traffic participants and other rapidly changing factors. The paper proposes the methods of energy optimal adaptive automatic train operation of electric freight locomotives with a significant amount of data based on artificial neural networks and digital twin aggregate. Keywords Electric motive power · Automatic train operation · Automation · Optimization methods
1 Introduction At present, JSC “Russian Railways” has developed a digital transformation strategy of the holding, which is fully integrated with the Decree of the President of the Russian Federation “On national goals and strategic objectives of the development of the Russian Federation for the period of up to 2024”, the program “Digital Economy of the Russian Federation” and the Long term development Program of JSC “Russian Railways” until 2025. As part of the implementation of the Long term Program, the integrated research and development project “Digital Railway” aims to increase the E. Avdienko · E. Tretyakov (B) Omsk State Transport University, Marksa pr. 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_18
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competitiveness and efficiency of the Russian Railways holding through the use of breakthrough information technologies: – technology “Industrial Internet of Things” and “Big Data” for automatic train operation with a given train schedule, infrastructure capacity, control centers teams, the technical condition of rolling stock and the status of the immediate traffic participants for constant collection of primary data on the state of the rolling stock and infrastructure with the subsequent formation of a complex object descriptions in order to manage their life cycle, monitoring the condition of rolling stock in operation, for digital infrastructure diagnostics and fast cooperation with the members of the production activities and suppliers; – the technology of “Imitation Modeling” (Simulation Modeling) for the control of cars and locomotives, which allows for determining the optimal mode of rolling stock operation considering its location, owner, status, operation plans and technical condition as well as reserving car spaces in order to increase the efficiency of rolling stock; – digital twin technology. Priority directions for the development of the transition to modern methods and means of rolling stock management according to are: – implementation of processes for infrastructure maintenance and arrangement of an “unmanned train movement” system based on a digital infrastructure model employing a geocentric coordinate system; – unification of commuter and metro train traffic control systems in large metropolitan areas; – creation of a new generation on-board security systems through computer technologies with elements of artificial intelligence; – development of a regulatory framework and technologies for collecting and processing information. Currently, the efficiency of the automatic rolling stock control system can be determined by the following criteria: – by increasing the handling capacity and the carrying capacity due to more accurate compliance with the traffic schedule; – improving traffic safety by reducing the probability of hazardous proximity of trains; – reduction of energy costs for train traction due to the choice of energy-optimal train control modes and regarding minimum energy consumption optimal distribution of travel time along the line for the running time along the hauls.
2 Materials and Methods With regard to system operation, the International Union of Public Transport considers five levels of automation of train operation management (from G0AO to
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G0A4) [6]. Level G0A4 implements automatic train operation management without any maintenance men on board of the rolling stock. To a greater extent, the term “unmanned control” corresponds to this situation. Table 1 shows the levels of automation of rolling stock operation management. Let us examine the current level of automation of G0A2 rolling stock management in Russia and describe the automation levels of G0A3 and G0A4. This will contribute to better understanding the principles of each separate level. Almost all trains running on the Russian Railways network are equipped with a safety device corresponding to automation level 1. Trains with automation level 2 have been successfully used on the Russian railway network for more than 20 years, several thousand locomotives have been equipped. This level is fulfilled due to the algorithms for traction control and braking of energy optimal train operation along the given route, with the schedule and indications of automatic locomotive signaling systems received via an inductive channel from rail circuits taken into account. At this level of automation, the driver is located in the front of the train cab, monitors the vacancy of the railway track and stops the train in case of a hazardous situation. Ensuring the safe departure of the train from the station platform is the responsibility of the operating crew (opening and closing doors can be done automatically). The use of level 2 reduces the fatigue of the driver and contributes to less energy consumption and more accuracy in following the traffic schedule. Automation level 3 (GOA3): Automatic control of rolling stock without a driver. At this level of automation, it is necessary to use additional measures in comparison with GOA2 since the driver is not in the head cabin, does not monitor the vacancy of the railway track and cannot stop the train in case of a hazardous situation. At this level of automation, the operating crew members on board are required. Ensuring the safety of the train departure from the station platform including closing the doors, can be the responsibility of operating crew, or actions can be performed automatically. Automation level 4 (GOA4). Fully automatic train management. Compared to GOA3, this level of automation requires additional measures since the train is controlled without operating crew on board. Ensuring the safety of the train departure from the station platform, including closing the doors, is automatic. More precisely, the system detects and takes an action in the event of hazardous and emergency situations such as the evacuation of passengers. In some hazardous or emergency situations such as a train derailment or the detection of smoke or fire, the prompt involvement of crew is provided. Let us consider the possibilities of automatic train operation system at the current level of automation of rolling stock management G0A2. According to this level, the automatic train operation system should perform the following functions: ensuring a safe route, ensuring safe interval traffic control, ensuring safe running speed, controlling traction and braking. Let us consider the automatic train operation system from the company “AVP Technology” USAVP, at present, it has the following functions: – calculation of the train running time rational in terms of electric power consumption – by separate hauls, based on the provided time schedule of
Identification of emergency situations and measures therein
Passenger boarding/disembarka-tion control
x
Ensuring the safe conditions for the start of the train (the doors control) x
x
Prevention of injuring the people between the cars or between the platform and the train
Detection of the source of fire/smoke, derailment, loss of train continuity, processing of passenger requests (call/evacuation, surveillance)
x
Control of doors for boarding/disembarking passengers
x
x
x
x
x
Preventing trains from hitting people x on the tracks
x x
x
x
System
System
GOA1
x
Traction and braking control
Crash avoidance
Control of the track vacancy
x
Ensuring safe speed
Train operation
x x
Ensuring safe interval regulation
Ensuring the safe movement of trains
Ensuring a safe route
GOA0
Basic train management functions
Table 1 The level of automation of rolling stock management
x
x
x
x
x
x
System
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control station tracking; determination of the actual speed of movement; calculation of the current astronomical time and the time remaining before the control station; comparison of the actual speed with the calculated speed and determination of the required speed of the train to meet the estimated running time including the sections of approaching traffic signals that require speed reduction, approaching the places having the speed limit; selection of the traction position of the train depending on the calculated value of speed; calculation of the coordinates of the track and the location of the train relative to the platforms accelerates the train to the design speed (energetically rational one); maintains movement at the estimated speed; reduces the speed of movement when approaching the action spots permanent or temporary speed limits; practices the signals of the locomotive traffic light; practices a signal about stalling reducing or disabling traction at stalling and recovering it after the termination of stalling. in case of manual operation, informs the driver about the recommended driving modes.
It can be concluded that the existing option for automatic train operation completely provides and performs the functions of rolling stock control on the current automation level. However, applying the third G0A3 level of automatic operation means expanded functions. The functions of preventing the train from colliding with obstacles and people are added. Thus, all these should be implemented through the introduction of a computer vision system by installing radars, lidars and various types of cameras. Therefore, due to the extension and addition of the new functions, the previous functions of the automatic train operation should be improved.
3 Results At the third level of automation, the technologies and methods should be changed in order to build an energy-optimal trajectory of movement in real time [1–13]. Moreover, the proposed automatic train operation will have to respond to a large number of changing factors in the process of movement, process big data and adjust the current trajectory of movement to these changing factors. It is proposed to take into account the data that will be sent to the automatic operation system every second, such as: the change in the resistance of the rolling stock, the moment of inertia, braking forces, the dynamic lengthway internal forces of the rolling stock, the current weight of the train, the limitations of the track and energy infrastructure, the statuses of the closest traffic participants, etc. Moreover, the system should become an adaptive
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automatic train opeartion system. It is planned to completely abandon the simplified traction calculations [14–16] limiting the possibilities of automatic operation system in order to move to the next level of automation [17] of rolling stock management. It is supposed to develop a method based on the abovementioned functions of the system. As it was stated above, it is planned to abandon the simplified traction calculations. It is assumed that traction calculations will be performed during the movement (the calculation unit is an artificial neural network), responding to all changing factors of the train situation. All the data for calculating and constructing an energy-optimal adaptive trajectory of movement will enter the calculation block from the memory block, where all information from the outside will be received and stored. On the basis of these data, an energy-efficient travel route will be built. In general, the optimal train control problem [13] can be considered as a problem of an optimization nonlinear mixed integer programming, which is solved by most authors through the methods presented in Fig. 1.
Optimization methods
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Some researchers [16] adhere to heuristic methods for solving the problem of optimal reconfiguration of the electrical network. These methods can significantly reduce computational and time resources; however, the obtained solutions are approximate. The optimization problem of combinatorial type is solved by the authors [16] through fireworks algorithms, neural networks, fuzzy sets mainly when initial data are limited. Heuristic methods for solving combinatorial optimization problems have proved their high efficiency in comparison with classical methods of iteration with a significant number of arguments of the objective function, when the determining factor is not the accuracy but the speed of calculations. However, the latter are not preferable for solving the problem. The method based on artificial intelligence, for instance, expert systems, fuzzy set theory, i.e. with elements of self-organization can be considered the most suitable method for automatic train operation from the point of view of energy-optimal operation with elements of adaptability. Expert self-organizing systems are based on the principles of implementing changes in the state of objects when certain conditions emerge. In most cases, this happens without a complete mathematical model of the control object. Selforganization of control objects is performed through determining the controlling actions on the basis of achieving optimal trajectories by local regulators in real time when the external and internal environment change.
4 Conclusion The existing methods and algorithms for improving the efficiency of rolling stock management within automatic train operation systems are based on classical approaches of direct optimization of explicitly specified mathematical models of train movement following the rules of traction calculations. The proposed approach is aimed at developing an adaptive energy-optimal automatic train operation system that will respond to most of the changing factors during movement in real time. This system should be described through intelligent methods of control objects self-organization (digital twin aggregate). The requirements and features of the functioning of automatic train operation systems are substantiated when advanced levels of automation of electric locomotives within digital transformation of the transport system: a complete rejection of simplified traction calculations for determining all the necessary parameters based on actual data measured in real time, including the limitations of the track and energy infrastructure, the statuses of the closest traffic participants and other dynamically changing factors are introduced. The paper proposes the methods of energy optimal adaptive automatic train operation of electric freight locomotives with a significant amount of data based on artificial neural networks and digital twin aggregate.
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References 1. Xiao Z, Wang Q, Sun P, You B, Feng X (2020) Modeling and energy-optimal control for highspeed trains. IEEE Trans Transp Electrif 6(2):797–807. https://doi.org/10.1109/TTE.2020.298 3855 2. D’Acierno L, Botte M (2019) The implementation of energy-saving strategies in the case of limitation in rolling stock availability. In: 2019 IEEE international conference on environment and electrical engineering and 2019 IEEE industrial and commercial power systems Europe (EEEIC/I&CPS Europe). https://doi.org/10.1109/EEEIC.2019.8783403 3. Chamaret A-P, Frugier D, Mannevy P, Galeb Y, Pichon G, Henry P (2018) Energy efficiency for rolling stock, from measuring to savings. In: 2018 IEEE international conference on electrical systems for aircraft, railway, ship propulsion and road vehicles & international transportation electrification conference (ESARS-ITEC). https://doi.org/10.1109/ESARS-ITEC.2018. 8607291 4. Aradi S, Bécsi T, Gáspár P (2013) A predictive optimization method for energy-optimal speed profile generation for trains. Published in: 2013 IEEE 14th international symposium on computational intelligence and informatics (CINTI). https://doi.org/10.1109/CINTI.2013. 6705179 5. Ma W, Li L, He S, Cheng J, Huang G, Zhou CQ (2012) Influencing factors on energy consumption of air conditioning system in railway passenger station based on orthogonal experiment. In: 2012 second international conference on intelligent system design and engineering application. https://doi.org/10.1109/ISdea.2012.703 6. Huang J, Deng Y, Yang Q, Sun J (2016) An energy-efficient train control framework for smart railway transportation. IEEE Trans Comput 65(5):1407–1417. https://doi.org/10.1109/ TC.2015.2500565 7. Pröhl L, Aschemann H (2019) Energy optimal trajectory planning for electrically driven railway vehicles with particle swarm optimization. In: 2019 IEEE 15th international conference on control and automation (ICCA). https://doi.org/10.1109/ICCA.2019.8900019 8. Pecharroman RR, Lopez-Lopez A, Cucala AP, Fernandez-Cardador A (2014) Riding the rails to DC power efficiency: energy efficiency in dc-electrified metropolitan railways. IEEE Electrif Mag 2(3):32–38. https://doi.org/10.1109/MELE.2014.2333684 9. Voron OA, Petrushin AD (2021) Improving the energy efficiency of electric machines for specialized railway rolling stock. In: 2021 XVIII international scientific technical conference alternating current electric drives (ACED). https://doi.org/10.1109/ACED50605.2021. 9462273 10. Eberhardinger B, Reif W, Wotawa F, Holvoet T (2014) Quality assurance for self-adaptive, selforganising systems (message from the workshop organisers). In: 2014 IEEE eighth international conference on self-adaptive and self-organizing systems workshops. https://doi.org/10.1109/ SASOW.2014.30 11. Cheng G, Liu T, Wang X, Huang Q (2006) Rapid training for self-organizing neural networks with incremental. In: Sixth international conference on intelligent systems design and applications. https://doi.org/10.1109/ISDA.2006.222 12. Renzi C, Leali F, Cavazzuti M, Andrisano AO (2014) A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems. Int J Adv Manuf Technol 72(1):403–418. https://doi.org/10.1007/s00170-014-5674-1 13. Sheridan ThB (2011) Adaptive automation, level of automation, allocation authority, supervisory control, and adaptive control: distinctions and modes of adaptation. IEEE Trans Syst Man Cybernet Part A Syst Hum. https://doi.org/10.1109/TSMCA.2010.2093888 14. Scheepmaker GM, Pudney PJ, Albrecht AR, Goverde RMP, Howlett PG (2020) Optimal running time supplement distribution in train schedules for energy-efficient train control. J Rail Transp Plan Manage 14:100180. https://doi.org/10.1016/j.jrtpm.2020.100180
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15. Madhusudan P, Rathankumar DB, Aishwarya K, Anitha GS (2018) Computationally efficient algorithms and high-speed ASIC design for railway gate automation. In: 2018 second international conference on computing methodologies and communication (ICCMC). https://doi.org/ 10.1109/ICCMC.2018.8488089 16. Venkateswaran KG, Nicholson GL, Roberts C, Stone R (2015) Impact of automation on the capacity of a mainline railway: a preliminary hypothesis and methodology. In: 2015 IEEE 18th international conference on intelligent transportation systems. https://doi.org/10.1109/ITSC. 2015.339 17. Nowakowski W, Bojarczak P, Łukasik Z (2018) Railway automation systems diagnosis based on Bayesian method. In: 2018 international conference on recent innovations in electrical, electronics & communication engineering (ICRIEECE). https://doi.org/10.1109/ICRIEECE4 4171.2018.9008871
The Improvement of On-Board Systems for Predictive Technical Diagnostics of Mainline Electric Freight Locomotives Based on Digital Models Evgeniy Tretyakov , Dmitry Solovyov , and Mikhail Kudinov
Abstract The paper presents the results of operational reliability of electric locomotives of 2ES6 series belonging to Omsk operating locomotive depot of the West Siberian railway in 2020 according to the types of equipment faults. There is a comparative analysis of domestic and foreign studies concerning on-board systems of predictive technical diagnostics of electric rolling stock, providing control and technical condition of locomotives in real time. It is shown that the main direction of the improvement of on-board systems for predictive technical diagnostics of mainline freight electric locomotives is forecasting of electrical equipment service life on the basis of digital mathematical models of real-time objects taking into account retrospective and predictive descriptions of their behavior. The paper deals with the results of data analysis from on-board measuring systems of electric rolling stock by means of KNIME machine learning tool. Keywords Electric locomotive · Analysis · Equipment faults · Technical diagnostics · Effectiveness · Digital model
1 Introduction In 2020, the Ural Locomotives plant produced and handed over to JSC Russian Railways 96 two-section DC freight electric locomotives of the 2ES6 series. However, despite the new technical solutions applied and improved characteristics of these electric locomotives, the problem of equipment failures remains acute. The main volume of failures falls on the share of electrical equipment and electrical machines. In order to solve this problem it is necessary to increase operational reliability of electric locomotives with the help of new digital technologies of technical diagnostics. In 2020, during the operation of 2ES6 series electric locomotives assigned to Omsk operating locomotive depot of the West Siberian railway, 2116 cases of locomotive E. Tretyakov (B) · D. Solovyov · M. Kudinov Omsk State Transport University, Marksa pr. 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_19
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failures were detected and, as a consequence, their transfer to the out-of-operation fleet (unscheduled repairs) took place. The distribution of locomotive malfunctions by the equipment type in 2020 compared to 2019 is shown in Fig. 1 (in number of cases). As follows from Fig. 1, the main share of faults in electric locomotives is electrical equipment, the second place is taken by electrical machines, the third place belongs to pneumatic equipment, and mechanical equipment occupies the fourth place. Let us take a closer look at the cases of 2ES6 electric locomotives failures due to electrical equipment and electrical machines malfunctions. The distribution of electrical equipment failures in 2020 compared to 2019 is shown in Fig. 2. As follows from Fig. 2, the main share of faults of electrical equipment is auxiliary converter (AC), control circuits, current collectors, power circuit contactors and protection devices.
Fig. 1 The distribution of locomotive malfunctions by the equipment type
Fig. 2 The distribution of electrical equipment failures
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Fig. 3 The distribution of electrical machines failures
The distribution of electrical machines failures in 2020 compared to 2019 is shown in Fig. 3. As follows from Fig. 3, the main share of electric machines failures is the damage of the collector-brush apparatus, armature and magnetic system of the skeleton. At present, in Russia and abroad, remote methods of traction rolling stock (TRS) diagnostics are widely used [1–4]. General Motors has developed the FIRE system, which provides real-time monitoring and technical condition of locomotives. Diagnostics is performed remotely, the FIRE system receives more than 800 signals that determine the main parameters of the technical condition of the locomotive. Analysis of technical condition trends, which allows forecasting its further development, is also an effective tool to implement the maintenance and repair system based on the actual condition of locomotives. This system also provides an opportunity to download archived information from the memory of the electronic control system of the locomotive in order to know about changes in the state of equipment over a relatively long time and with great reliability to predict potential failures indicating their possible causes [4]. In Germany, the ruDi system has been developed to monitor and manage the fleet of TRS. It provides registration of all operational data, technical diagnostics of the rolling stock in operative mode and determines its location within the European network [5]. In Russia, as the part of the informatization program of JSC Russian Railways, an automated system for recording, analyzing and investigating failures of technical facilities is being developed. As one of the sources of input information in this system the information from rolling stock diagnostics systems is used. The development of an automated system to manage the technical condition of locomotives is necessary to solve this problem. It is possible to distinguish the following
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subsystems in it: the subsystem of collecting and processing of diagnostic information; the subsystem of accumulating and analyzing of information about locomotive failures; the subsystem of analyzing and planning of preventive and repair works. Maintenance of the electronic passport allows including diagnostic information on failures and data on repairs carried out. The subsystem of accumulating and analyzing information on locomotive failures includes a set of workstations installed at locomotive depots. Technical condition logs and equipment replacement logs filled in during operation provide the bulk of information. At the end of 2016 the first electric locomotive technical condition monitoring centers were established at two service locomotive depots: “Sverdlovsk” and “The South Ural” in Chelyabinsk, managed by STM-Service, a member of Sinara—Transport Machines Holding. The modern equipment of the center makes it possible to decode the diagnostic information of the rolling stock control and diagnostics system, received to the servers via satellite and Internet communication from the diagnostic systems of modern locomotives through the use of the locomotive interaction system [6]. All the information received on locomotive diagnostics is thoroughly analyzed for correctness of fault detection. LSD “Sverdlovsk” monitoring center has developed an operation algorithm, according to which the processes of diagnosing equipment of 2ES6, 2ES10 electric locomotives during operation are continuously improved. All the data are generated in accordance with the laid down algorithms. The generated data make it possible to make quite specific conclusions concerning the technical condition of the unit. For example, in the case of line contactors, the number of the unit will be known, which facilitates repair work during service maintenance. At present, stationary and onboard diagnostic systems are used to assess the technical condition of the TRS, which ensure the operation quality of the rolling stock. However, the experience of TRS operation shows that the most reliable information will be obtained when the locomotive is in motion. Onboard tools allow checking the units and parts, the information on the technical condition of which is difficult to obtain in stationary conditions. As diagnostic parameters measured by the equipment installed directly on the locomotive, such parameters are chosen which characterize the power and economic qualities of the locomotive, traffic safety, and also allow carrying out operative search of faults and their elimination. Onboard means of working diagnostics are constantly in operation and instantly react to the slightest deviations from normal functioning of individual parts and units [7, 8]. Today JSC Russian Railways is actively developing the Smart Locomotive project [8]. Its key functionality is as follows: the information received from locomotives equipped with microprocessor control systems makes it possible to make decisions on the expediency of further locomotive operation. The system takes into account not only the existing database, but it is intended for continuous improvement of the processes of technical diagnostics and restoration of rolling stock using the so-called intelligent analysis platform. However, the calculation of probability of occurrence of locomotive failure at each specific incoming message showed that not all the information transmitted from onboard control and diagnostic systems correlates with the faultless operation of the locomotive, which leads to a large error in the area of determination of the searched
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node. To minimize these errors, it is necessary to increase the correlation coefficient, which, in its turn, will positively affect the reliability of work on determining the state of the locomotive, preceding the failure and identifying the predicted service life of the equipment.
2 Materials and Methods The authors propose to carry out prediction of electric equipment service life on the basis of digital mathematical models of real-time objects taking into account retrospective and predictive descriptions of their behavior as the main direction of improvement of onboard predictive technical diagnostics systems for mainline electric freight locomotives. On the basis of these digital models it is proposed not just to calculate the probability of failure of electric locomotive equipment, but to determine the service life before failure (in hours, km run). Main digital mathematical models are traction electric motor, electric locomotive power circuit for all positions and modes, traction converter, auxiliary converter, auxiliary electric machines, batteries. The following practical tasks are solved in the framework of the present study: – identification of faults in traction motors, uneven loading, as well as differences in electromechanical characteristics; – identification of deviations and outliers (anomalies) of measured values of electrical quantities associated with disturbances in the operating modes of electrical equipment, deviations of parameters of electric locomotive power circuit elements from the calculated ones, including those based on development of the mathematical model of the locomotive; – identification of cases of exceeding the actual operating parameters of electric locomotives over the design parameters set by the manufacturer; – identification of correlation between external perturbations of electrical values and deviations in operation, failures of electric locomotive equipment, etc. Analysis of data from onboard measuring systems of electric locomotives within the framework of the tasks being solved was performed using KNIME machine learning software [9]. Under various operating modes of the electric locomotive (traction mode, coasting, braking, changes in the power scheme, external forces and factors), the parameters monitored by the locomotive control and diagnostic microprocessor system (LCDMS) are dynamically changed, including in a random way. As mode models, for example, of traction motors (TM) we will consider the following: 1. Normal mode: all parameters of TM, power circuit in operation are within the values set by the manufacturer and other normative documents. 2. Prefaulty mode: violation of operation modes (as a rule, exceeding of admissible parameters) and pre-failure condition of TM.
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Fig. 4 The general identification order of traction motor modes
3. Faulty mode: associated with abnormal operation of electrical equipment, as a rule, its development leads to triggering of protection and (or) failure. Let us consider the proposed models of prefaulty and faulty modes in terms of criteria, principles of identification of these modes and identification of anomalies. Figure 4 shows the general order of identification of modes on the example of TM. By anomaly in this case we will understand the situation when the value of the measured (defined) parameter of TM operation significantly deviates from the predicted (expected, set) one for this mode of operation. The model identifies the mode as prefaulty in case the permissible measured electric parameters are exceeded and the pre-failure state of TM is detected on the basis of indirect assessments. Criteria of operation mode violation are exceeding of admissible parameters set by the manufacturer [10].
3 Results When exceeding of permissible modes of operation of electric equipment of electric locomotive of 2ES6 series the data from electric locomotive movement parameter recorders of 2ES6 series were processed according to KNIME program. Figure 5 shows a histogram of currents distribution over five intervals. Overcurrents were determined using the Row Filter node of KNIME program. It is known that the most common methods of data analysis, including the search for anomalies, are associated with the construction of regression models
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Fig. 5 The histogram of currents distribution over five intervals
(linear, logistic regressions, etc.), classification models (decision trees, ensembles of trees, support vectors method, multilayer perseptron, etc.), clustering (kmeans method, spatial and hierarchical clustering, etc.).), model estimation (crossvalidation, mismatch matrix, etc.), application of deep learning of neural networks, etc. [6]. Armature data clustering by k-means method is implemented in KNIME (Fig. 6). The main task to be solved by the mentioned clustering method is to find and study the deviations and outliers of the experimental measured data with respect to the hypotheses of their interrelation with each other (in the form of electric propulsion, electromechanical characteristics of TM and electric locomotives, characteristics
Fig. 6 KNIME operation area
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determined on the basis of Kirchhoff laws for the electric power circuit of an electric locomotive, etc.). For example, Fig. 7 shows the dependence of armature currents of groups 1–2 of TM on armature currents of groups 3–4. Cluster analysis allows detecting anomalous points with outliers—deviations from linear dependence or from typical characteristics. The cause of these outliers may be incorrect initial data, which should be additionally filtered, or malfunction of electric locomotive power circuit elements, leading, for example, to inadmissible variation of currents between branches 1–2 and 3–4.
Fig. 7 The armature current dependence of groups 1–2 TM on the armature current of groups 3–4 as points with two clusters
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Obtaining homogeneous groups of data allows building mathematical (numerical) models of electric rolling stock behavior to implement the “smart locomotive” concept. An important stage of data analysis from onboard locomotive systems is the prediction of failures of technical means and (or) maintenance and repair intervals, which will be reflected in the following publications of the authors.
4 Conclusion A comparative analysis of domestic and foreign research dealing with onboard predictive technical diagnostics systems for electric rolling stock, which provide real-time monitoring and technical condition of locomotives, has shown that the main direction of improvement of onboard predictive technical diagnostics systems for mainline freight electric locomotives is prediction of electrical equipment service life on the basis of digital mathematical models of real-time objects taking into account retrospective and predictive descriptions of their behaviour. The proposed approaches to data analysis from on-board measuring systems of electric rolling stock by means of KNIME machine learning tool have shown their effectiveness. It is proposed to carry out real-time prediction of the electric locomotives electrical service life on the basis of the digital mathematical models of the technical diagnostics objects (digital twins).
References 1. Garramiola F, Poza J, Madina P, Del Olmo J, Almandoz G (2018) A review in fault diagnosis and health assessment for railway traction drives. Appl Sci 8(12):2475. https://doi.org/10.3390/ app8122475 2. Wang H, Chai T-Y, Ding J-L, Brown M (2009) Data driven fault diagnosis and fault tolerant control: some advances and possible new directions. Acta Autom Sin 35:739–747 3. Li C, Luo S, Cole C, Spiryagin M (2017) An overview: modern techniques for railway vehicle on-board health monitoring systems. Veh Syst Dyn 55:1045–1070 4. Sa J, Choi Y, Chung Y, Kim H-Y, Park D, Yoon S (2017) Replacement condition detection of railway point machines using an electric current sensor. Sensors 17:263 5. D’Acierno L, Gallo M, Montella B, Placido A (2013) The definition of a model framework for managing rail systems in the case of breakdowns. In: Proceedings of the 16th international IEEE conference on intelligent transportation systems (IEEE ITSC 2013). https://doi.org/10. 1109/ITSC.2013.6728372 6. Khudoyarov DL, Tyushev IA (2018) Development of locomotive on-board diagnostics systems. Innotrans 4:43–48. https://doi.org/10.20291/2311-164X-2018-4-43-48 7. Goverde RM, Meng L (2011) Advanced monitoring and management information of railway operations. J Rail Transp Plan Manage 1(2):69–79. https://doi.org/10.1016/j.jrtpm.2012.05.001 8. Capolino G-A, Antonino-Daviu JA, Riera-Guasp M (2015) Modern diagnostics techniques for electrical machines, power electronics, and drives. IEEE Trans Ind Electron 62:1738–1745
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9. Information on: https://hub.knime.com/ process repository from the KNIME community 10. DC electric freight locomotive 2ES6 with collector traction motors. Operation manual part 3. Description and operation of control and measurement system 2ES6.00.000.000.RE2. Yekaterinburg: “Ural Locomotives2”, 123 p
Influence of Changes in External Factors on the Energy Efficiency Parameters of Electric Locomotives Alexey Plaksin and Semen Shvetsov
Abstract The article presents a technical and economic methodology for predicting the fuel and energy efficiency of a locomotive enterprise based on the assessment of the current situation with the consumption of fuel and energy resources (FER) by electric rolling stock, taking into account the optimization of the use of electric locomotives’ power and thereby increasing their energy indicators with the possibility of obtaining a quantitative and operational assessment of the degree of compliance with the nominal power and needs for it, as well as the use of power specifically for the stated operating domain, taking into account changes in basic parameters such as speed, track profile, weight of the locomotive and cars. The article aims to evaluate the impact of operational factors (indicators) on the use of electric locomotives’ power through the use of economic and mathematical modeling methods. Keywords Excess power · Energy efficiency · Elasticity of function · Coefficient of variation · Electric locomotive
1 Introduction Forecasting the consumption of fuel and energy efficiency of a locomotive enterprise is a difficult task due to the fact that it depends on a large number of indicators. Therefore, the determination of measures and ways to improve the energy efficiency of the locomotive enterprise as a whole should be based on an assessment of the current situation with the consumption of fuel and energy resources (FER) by electric rolling stock, taking into account the prospective growth. Currently, on the Russian railway network, there is an underutilization of power by electric locomotives at various sections, which is clearly seen by the example A. Plaksin (B) The West Siberian Railway—Branch of JSC «RZD», 4, Burlinsky Crossing, Novosibirsk 630132, Russia e-mail: [email protected] S. Shvetsov Omsk State Transport University, 35, Marksa pr., Omsk 644046, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_20
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of passenger electric locomotives that are operated on a large range of railways with different types of the track profile. At the same time, as studies show, electric locomotives with excess power are operated with low energy indicators in comparison with those that they could have had in case of optimal power use [1, 2]. When choosing the power of electric locomotives at the design stage, the calculation of the nominal power is made, as a rule, for one mode, that which is the most complex one. For freight electric locomotives, this mode is operation on a calculated grade, and for passenger locomotives, it is movement at maximum speed on a flat section of track [3]. There are also power selection methods which take into account the values of the starting speed and traction effort [4, 5]. As the conducted studies and the results of the operation of electric locomotives show, while the choice of power based on these methods is acceptable for sections with a complex path profile, in sections with a light profile the power value is overestimated (excessive) and there is an underutilization of power by electric locomotives, which affects their energy performance [1, 2, 6, 7]. Other disadvantages of these power selection methods include the inability to obtain a quantitative and operational assessment of the degree of compliance with the nominal power and the needs for it, as well as the use of power specifically for the stated operating domain, taking into account changes in basic parameters such as speed, track profile, weight of the locomotive and cars. The reason for this is to determine the actual power data without identifying the relationship between the parameters that affect the power of an electric locomotive. Thereby, the considered methods of selecting the power of electric locomotives do not take into account the essential parameters of their operation, and, consequently, the options for determining the power are largely conditional. In our opinion, in order to choose the optimal value of the nominal power of an electric locomotive, a more flexible approach should be applied. And this issue should be comprehensively investigated, which will help identify the so-called “bottlenecks” and increase the energy performance of electric locomotives in operation and those planned for production. Therefore, the purpose of this work is to evaluate the impact of operational factors (indicators) on the use of electric locomotives’ power. In this regard, the operating domain of the West Siberian Railway was considered. It has sections of different track profiles, ranging from plain to hilly-mountainous (type III according to the VNIIZHT classification), on which EP1 and EP2K passenger electric locomotives are operated with underutilization of structural capacity [8].
2 Materials and Methods Since these electric locomotives have an excessive value of structural power, we introduce the concept of excess power at the operating domain, which can be represented as follows:
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Pc.ex. =
Pc.n −
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I I Pc = 365 n i · Pc. n − 365 n i · Pc , i=1
i=1
(1)
where n i is the size of the movement; I —the number of sites on the railway operating domain; Pc. n —the value of the nominal power of the electric locomotive; Pc —the values of the power required to overcome the forces of resistance to the movement of the train, which can be defined as (2) where is the conversion factor; V —speed of movement; m l and m c —the weights of the locomotive and cars; /
//
w0 = a1 + b1 V + c1 V 2 and w0 = a2 + b2 V + c2 V 2 are the main specific resistances to the movement of the locomotive and cars, calculated according to [9, 10]; wug =
d V
and wi are additional specific resistances to movement from the undercar generators and from the grade i e , determined according to [9, 10]. In relation to one electric locomotive, when handling one site, formula (1) can be reduced to the following form (3) The occurrence of an excess power value is mainly due to the following factors— an overestimated value of the available power of electric locomotives and an underestimated value of the required power, which, in turn, depends on the weight of the train, the speed of movement and the profile of the track. The necessary condition for the minimum power consumption is that the excess power value is equal to zero or the required power is equal to the nominal power of the long-term operation mode. The main prerequisite for the use of economic and mathematical methods in the analysis of the presented model [11] is the assumption that when operating an electric locomotive with an optimal power value, almost all of its parameters for a given amount of work are nominal, normative and constant. Consequently, the function Pc.ex. can theoretically be decomposed into a Taylor series near these parameter values, which makes it possible to investigate small increments of the function from small and independent increments of its arguments (parameters). The mathematical conclusions given below are based on the use of the materials of the works [11–14]. The formula that takes into account the terms of the first order of smallness in the decomposition of the function has the form:
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(4) where A, … , M are numerical coefficients determined by partial derivatives of the corresponding arguments:
since the other terms are independent of x1 , their partial derivatives equal zero. Similarly for other arguments
The values of the coefficients where A, …, M must be constant, but provided that the arguments of the function are close to constant values, this requirement is fulfilled /
A = f x1 (a, . . . m) .................. M = f x/m (a, . . . m), then formula (4) will have the form.
(5) Corrections of higher orders determined by partial derivatives can be justifiably neglected in this case, in view of the absence of significant nonlinearity of the function Pc.ex. near the nominal values of the parameters. Let us define the partial increments of the function in order to further assess the degree of influence of the arguments independently of each other on the function.
Dividing the left and right parts of the expressions by the increment of the corresponding argument, in the limit with Δx1 → 0, we get
Influence of Changes in External Factors …
207
Δx1 f (x1 , ..., xm ) ∂ f (x1 , ..., xm ) = , Δx1 ∂ x1 .................................... ∂ f (x1 , ..., xm ) Δxm f (x1 , ..., xm ) = · Δxm ∂ xm Hence ∂ f (x1 , ..., xm ) · Δx1 ∂ x1 .................................... ∂ f (x1 , ..., xm ) Δxm f (x1 , ..., xm ) = · Δxm ∂ xm Δx1 f (x1 , ..., xm ) =
In this case, the total increment of the function is equal to the sum of the partial increments with the values of the other arguments unchanged Δf (x1 , ..., xm ) =
m ∂ f (x1 , ..., xm ) Δxi , i=1 ∂ xi
(6)
where Δf (x1 , ..., xm ) is the function increment; xi i-th argument, independent of the rest; m—the number of independent arguments. To estimate the degree of relative (percentage) change of a function with small relative changes (1%) of its parameters, one can use the elasticity of the function determined by the formulas [16, 17]: ε=
∂ f (x1 , ..., xm ) xi ∂ f xi (x1 , ..., xm ) ∂ xi ÷ = · f (x1 , ..., xm ) xi ∂ xi f (x1 , ..., xm )
(7)
∂ f xi (x1 , ..., xm ) ∂ xi ∂ln f (x1 , ..., xm ) ÷ = , f (x1 , ..., xm ) xi ∂lnxi
(8)
or ε= here τ=
∂ f (x1 , ..., xm ) ∂ xi
is the coefficient expressing the absolute sensitivity of the function to the change of the argument xi in units of measurement. Thus, after differentiating expression (3) by the arguments of interest, formulas for calculating absolute sensitivities will be obtained τi , and after multiplying them by
208
A. Plaksin and S. Shvetsov
xi f (x1 , ..., xm ) according to expression (7), formulas for determining the elasticity values of εi function (3) by these arguments will be obtained. According to formula (3), the excess power expression Pc. ex. . includes both normative Pc. n. and actual values of the variable parameters V , m l , m c and wi . Then, by alternately setting the actual value to any of the parameters, and the normative values to the rest, it is possible to assess the degree of influence of each factor on the required and excess power values. The reason Pc. ex. = 0 may be low (high) values of the speed of movement, the weight of the train, the profile of the track, the nominal power and others that are included in the expression Pc. ex . Using this expression, it is possible to analyze the parameters of excess power, which requires a respective monthly or annual analysis of the excess power of electric locomotives at the operating domain in question. Formulas for determining the values of sensitivity and elasticity of the function Pc. ex. depending on the parameters being changed were calculated as: from the weight of the locomotive m l
(9)
from the weight of the cars m c
(10)
from the speed of movement V
(11)
Influence of Changes in External Factors …
209
from the equivalent grade i e
(12)
In addition, it is of interest to determine the coefficients of variation of excess power values on railway sections based on known coefficients of parameter variation and corresponding elasticity coefficients. Formulas for estimating standard deviations and coefficients of variation in accordance with [13] have the form: σs =
Ds =
1 (xs j − x s )2 m k , j mk
Vs =
σi · 100%, xs
(13) (14)
where xs = 0 is the nominal value or weighted average value of the Sth argument, determined from the expression: xs =
1 xsr m k , r n
(15)
where xsr —the value of the S th argument of the middle of the intervals in the interval distribution; m k —the corresponding frequencies or weights of the attribute values, while m k = n; Ds —the average square of the deviation (variance) of the parameter; Vs —coefficient of variation, which expresses the ratio of the mean square deviation σs to the weighted average as a percentage (%). Then the variation coefficient of excess power will be equal to [18] V Pc. ex. =
M s=1
εs · Vs .
(16)
Using formulas (9–16), the elasticities and coefficients of variation of the parameters of the excess power function (3) were calculated for monthly averages Pc. ex. , based on the data given in [2, 8]. The calculation results are presented in Table 1. To obtain an objective picture of the energy efficiency of electric locomotives from value Pc.ex. , the dependences of the sensitivity and elasticity of the parameters of the required power of electric locomotives Pc were determined and a comparative assessment of the elasticity of the parameters Pc and Pc. ex. was carried out. The values of sensitivity and elasticity of the function Pc parameters were calculated in the same way as for the function Pc. ex. according to formulas (4–8).
10
9
8
7
6
5
4
70.1
65.8
Kamen na Obi-Karasuk
74.7
Cherepanovo-Karasuk
Karasuk-Kamen on Obi
69.1
73.1
Karasuk-Barnaul
Karasuk-Cherepanovo
69.6
63.5
Artyshta-Barnaul
Barnaul-Karasuk
62.3
Barnaul-Artyshta
58
60
Belovo-Novokuznetsk
Novokuznetsk-Belovo
65.5
65.6
Novosibirsk-Belovo
Belovo-Novosibirsk 0.696 0.856 0.328 0.579 0.406 0.507 1.138 2.523 0.608 0.467
−0.174
−0.183
−0.146
−0.151
−0.216
−0.242
−0.096
−0.114
−0.084
−0.074
1.208 0.691
2.825
−0.189
−0.230
2.308
−0.176
64
65.3
Barnaul-Cherepanovo
Cherepanovo-Barnaul
−0.232
2.025 2.238
−0.137
−0.154
Novosibirsk-Cherepanovo 53.1
Cherepanovo-Novosibirsk 57.8
3
80
86.1
1.223
Barabinsk-Omsk
2
0.781
Barabinsk-Novosibirsk
1
−0.392
V Elasticity Coefficient value, 1 V of km/h variation of parameter Vv
−0.357
№ Section of operation n/a
115
116
167
164
506
502
411
413
582
593
619
615
501
482
520
543
731
667
−0.028
−0.030
−0.048
−0.042
−0.155
−0.144
−0.102
−0.101
−0.141
−0.139
−0.170
−0.168
−0.132
−0.123
−0.119
−0.114
−0.223
−0.226
3.383
3.543
5.473
5.271
16.946
17.334
24.649
25.329
22.938
21.052
15.271
13.499
18.590
19.983
20.264
18.626
11.073
13.201
Value Elasticity Coefficient of m 1mc of v, variation tons of parameter Vmc
Table 1 Determination of excess power values on railway sections
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
1
1
−0.020
−0.021
−0.028
−0.025
−0.064
−0.059
−0.045
−0.044
−0.057
−0.056
−0.068
−0.067
−0.055
−0.052
−0.049
−0.046
−0.050
−0.050
135
135
135
135
135
135
135
135
135
135
135
135
135
135
135
135
135
135
−0.029
−0.032
−0.037
−0.032
−0.039
−0.036
−0.030
−0.029
−0.028
−0.027
−0.033
−0.033
−0.032
−0.031
−0.026
−0.023
−0.040
−0.046
−0.151
−0.168
−0.226
−0.196
−0.500
−0.455
−0.328
−0.320
−0.410
−0.396
−0.502
−0.498
−0.408
−0.382
−0.349
−0.320
−0.670
−0.713
4541
4517
4427
4467
4019
4069
4240
4250
4104
4118
3991
3997
4123
4159
4191
4222
3802
3775
The value of R ex, kW
(continued)
−0.128
−0.158
−0.550
−0.334
−2.756
−2.583
−2.610
−2.595
−3.394
−3.038
−2.749
−2.544
−2.991
−2.870
−2.755
−2.395
−2.746
−3.460
The Elasticity Value Elasticity The total Ratio of value 1 ie ml, elasticity variation 1ml of i tonn of all V rc.ex e, % parameters is 1 Pc.ex
210 A. Plaksin and S. Shvetsov
12
11
76.7
75.6
Irtyshskoye-Omsk
Omsk-Irtyshskoye
76.7
75.8
Irtyshskoe-Karasuk
0.373 0.785 1.270 1.057
−0.122
−0.118
−0.212
−0.212
V Elasticity Coefficient value, 1 V of km/h variation of parameter Vv
Karasuk-Irtysh
№ Section of operation n/a
Table 1 (continued)
398
383
168
170
−0.124
−0.121
−0.049
−0.050
16.370
16.175
6.732
7.496
Value Elasticity Coefficient of m 1mc of v, variation tons of parameter Vmc
2
2
2
2
−0.053
−0.052
−0.028
−0.029
135
135
135
135
−0.040
−0.041
−0.038
−0.038
−0.429
−0.426
−0.233
−0.240
−2.253
−2.229
−0.423
−0.423
The Elasticity Value Elasticity The total Ratio of value 1 ie ml, elasticity variation 1ml of i tonn of all V rc.ex e, % parameters is 1 Pc.ex
4124
4131
4418
4409
The value of R ex, kW
Influence of Changes in External Factors … 211
212
A. Plaksin and S. Shvetsov
As a result of the analysis and comparison of the parameters of the total elasticities of the functions, the dependence was obtained Pc. n − ε Pc = − 1, Pc ε Pc. ex
(17)
which made it possible to evaluate the energy efficiency of electric locomotives by the amount of power use Pc. n Pc It depends on the ratio of the total elasticities of the power parameters εP c ε Pc. ex and can be taken as a criterion for evaluating the ratio of electric locomotive power. Figure 1 shows the dependencies of power use by an electric locomotive from the ratio of the total elasticities of the parameters Pc and Pc. ex , obtained by the formula (17). As can be seen from Fig. 1, the optimal use of electric locomotive power (Pc. n = Pc ) would be observed with the ratio of the total elasticities of the parameters Pc and εP Pc. ex c εc.ex 10.00 9.00 8.00 7.00 6.00 5.00 Pс. n 4.00 Pc. 3.00 2.00 1.00 0.00 0.00 -1.00 -2.00 -3.00 -4.00 -5.00 -6.00 -7.00 -8.00 -9.00-10.00 ∑ ε Pc
∑ε
Pc. ex
Fig. 1 The dependencies of power use by an electric locomotive from the ratio of the total elasticities of the parameters Pc and Pc. ex
Influence of Changes in External Factors …
213
close to zero. Thus, it can be concluded that ideally, in order to reduce the consumption of fuel and energy resources, the ratio of the total elasticities of the parameters Pc and Pc. ex should tend to zero. Then the energy efficiency of excess power can be estimated using the coefficient of variation as: VE(Pc. ex ) =
M s=1
εs( pc ) · Vs . εs( pc.ex )
(18)
According to the formulas (4–8 and 17, 18), calculations were made and the coefficient of variation of the energy efficiency of electric locomotives VE(Pc. ex ) in the sections was determined. The calculation results are presented in Table 2. The analysis of the data in Table 2 showed that the coefficient of variation in the energy efficiency of the value Pc. ex due to changes in power parameters during operation on different sections of the railway differs by several times (the largest value is 3.7 times), which indicates a different energy efficiency of the electric locomotive during operation. At the same time, the greatest energy efficiency of electric locomotives is observed on the Novosibirsk-Omsk section (the lowest value VE(Pc. ex ) = −45, 148), Table 2 Determination of the energy efficiency of using excess power from excess power values on railway sections № Section of operation n/a
The ratio of elasticities of function ε Pcv ε Pc.exv
The ratio of elasticities of function ε Pcm c ε Pexm c
The ratio of elasticities of functions
Coefficient Value Value of Pc. ex , Pc. n Pc kW variation VE(Pc. ex )
εc ε Pc.ex
1
Barabinsk-Novosibirsk
−4.506
−48.633
−3.684
−53.139
3775
4.68
2
Barabinsk-Omsk
−2.975
−42.173
−3.809
−45.148
3802
4.81
3
Novosibirsk-Cherepanovo −14.782
−135.962 −7.300
−150.744
4222
8.30
4
Barnaul-Cherepanovo
−14.976
−129.666 −6.489
−144.642
4159
7.49
5
Novosibirsk-Belovo
−6.009
−67.151
−73.160
3997
5.97
6
Belovo-Novokuznetsk
−4.206
−127.204 −6.042
−131.410
4118
7.04
7
Barnaul-Artyshta
−2.533
−195.600 −7.722
−198.133
4250
8.72
8
Barnaul-Karasuk
−2.261
−96.519
−5.568
−98.780
4069
6.57
9
Karasuk-Cherepananovo
−15.250
−70.634
−13.400
−85.883
4467
14.40
10
Kamen na Obi-Karasuk
−8.173
−59.209
−17.502
−67.382
4541
18.50
11
Karasuk-Irtysh
−9.074
−77.814
−11.559
−86.887
4418
12.56
12
Irtyshskoye-Omsk
−7.836
−99.797
−6.170
−107.633
4131
7.17
−4.975
214
A. Plaksin and S. Shvetsov
and the lowest energy efficiency is on the Barnaul–Artyshta section (the highest value VE(Pc. ex ) = – 198,133).
3 Results The data in Table 2 show that it is practically impossible to achieve such a state of operation of electric locomotives, at which VE(Pc. ex ) will be zero, which corresponds to the most advantageous mode (minimum electricity consumption) and the principle of the least waste of effort and energy. The determination of the sensitivity and elasticity coefficients of the required and excess power, the coefficients of variation of the parameters of excess power and its energy efficiency should be carried out for each section of operation (locomotive series) separately and all the arguments constituting variable components of expression (3), including changing the profile of the track on the section (in this paper, an equivalent lift was adopted), as well as different types of electric locomotives, if they are operated on the sections under consideration should be considered. Based on the actual data, with the help of the above methodology, it is possible to perform an effective and thorough analysis of the power use and the choice of its rational value. Obviously, it is possible to use absolute sensitivity formulas instead of elasticity coefficients. In this case, the coefficient of variation of the values Pc. ex will be determined by the formula
M s=1 τs σs
V pc. ex =
Pc. ex
· 100%,
(19)
and the coefficient of variation of the energy efficiency of the values Pc. ex according to the formula VE( pc. ex ) =
M τs(Pc ) s=1 τs(Pc )
Pc. ex
· σs
· 100%.
(20)
4 Conclusions The developed mathematical model and methodology for the analysis of excess power can be used in the study of the locomotive economy of the railway, as well as objects of power traction of trains. In contrast to the existing methods of selecting electric locomotive power values, the above mathematical apparatus makes it possible to quantify the degree of compliance of the electric locomotive power as a whole and its parameters with the level of required power and to assess the stability or instability
Influence of Changes in External Factors …
215
of the electric locomotive power to changes in the environment at the given operating domain. The values of the coefficients of variation of the parameters of excess power and its energy efficiency determined for several sections of the railway allow us to assert that these values can be significant and influence the choice and use of electric locomotives’ power, which also affects the costs of fuel and energy complex. The situation is complicated by the fact that often an excessive power value can occur at one of the sections when the optimal (rational) power value is realized at the other sections. In such cases, a timely analysis with the identification of the causes of the disproportions will make it possible in real conditions to redistribute power between the sections of operating domain or the power parameters themselves (speeds or train weights) in order to achieve rational use of electric locomotives with minimal fuel and energy consumption. This corresponds, to a certain extent, to the principles of optimal management of the railway rolling stock. A regular analysis will help to adapt the power usage to the conditions of a constantly changing external environment and, through minimal and timely efforts, to transfer the system to a new state that meets modern requirements for this stage.
References 1. Aulov EV et al (2018) Accounting for the energy consumption of passenger electric locomotives in locomotive operating depots. Bull Res Inst Railway Transp 77(5):280–287. https://doi.org/ 10.21780/2223-9731-2018-77-5-280-287 2. Zarifyan AA (2020) Energy balance during freight electric locomotive operation. Bull Bryansk State Tech Univ 89(4):21–30. https://doi.org/10.30987/1999-8775-2020-4-21-30 3. Hetman HK, Marikutsa SL (2017) Selection of rational parameters of the nominal mode electric trains with asynchronous traction drive. Sci Transp Progr 69(3):56. https://doi.org/10.15802/ stp2017/104767 4. Hetman HK, Marikutsa SL (2017) The choice of rational parameters of the nominal mode of electric locomotives). Sci Transp Progr Dnipro 67(1):96–10. https://doi.org/10.15802/stp2017/ 92615 5. Fischer S (2015) Traction energy consumption of electric locomotives and electric multiple units at speed restrictions. Acta Technica Jauriensis 8(3):240–256. https://doi.org/10.14513/ actatechjaur.v8.n3.384 6. Kolpahchyan PG, Zarifyan AA (2015) Study of the asynchronous traction drive’s operating modes by computer simulation. Part 1: Problem formulation and computer model. Transp Probl 10(2):125–136. https://doi.org/10.21307/tp-2015-028 7. Kolpahchyan PG, Zarifyan AA (2015) Study of the asynchronous traction drive’s operating modes by computer simulation. Part 1: problem formulation and computer model. Transp Probl 10(3):5–15. https://doi.org/10.21307/tp-2015-029 8. Nikonchuk IN (2020) On the issue of increasing operational energy efficiency of eight-axle passenger DC electric locomotives. Russ Railw Sci J 79(6):373–382. https://doi.org/10.21780/ 2223-9731-2020-79-6-373-382 9. Sirong Y (2018) Principles of railway location and design. Academic Press, pp 73–157. https:// doi.org/10.1016/B978-0-12-813487-0.00002-0 10. Su R, Gu Q, Wen T (2014) Optimization of high-speed train control strategy for traction energy saving using an improved genetic algorithm. J Appl Math 1–7. https://doi.org/10.1155/2014/ 507308
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11. Cheremisin V, Istomin S, Perestenko A (2020) Artificial intelligence methods to control the energy efficiency of electric rolling stock online. E3S Web Conf 175:05046. https://doi.org/10. 1051/e3sconf/202017505046 12. Carmen C (2016) An invitation to applied mathematics: differential equations, modeling, and computation. Academic Press, p 878 13. Keller AA (2018) Mathematical optimization terminology. Academic Press, p 325 14. Korn G (2014) Handbook of mathematics for scientists and engineers: definitions, theorems, formulas, p 832 15. Nisbet R, Elder J, Miner G (2009) Handbook of statistical analysis and data mining applications. Academic Press, pp 285–312. https://doi.org/10.1016/B978-0-12-374765-5.00013-9 16. Schweinzer P (2011) Mathematical methods for economic analysis. Birkbeck College, University of London, p 245. https://www.researchgate.net/publication/228760692 17. Tsokos CP, Kandethody M, Ramachandran (2021) Mathematical statistics with applications. Academic Press, p 680. https://doi.org/10.1016/B978-0-12-817815-7.01001-0 18. Aerts S, Haesbroeck G, Ruwet C (2015) Multivariate coefficients of variation: comparison and influence functions. J Multivar Anal 142:183–198. https://doi.org/10.1016/j.jmva.2015.08.006
Preventive Diagnostics of Technical Condition of Inter-Turn Insulation of Traction Electric Motors Anchor Windings Pavel Shkodun
Abstract The aim of the article is to improve the methodology for monitoring the state of the turn-to-turn insulation of traction electric motors of rolling stock. The actual signal of the wave response obtained on the armature winding of the traction motor is considered. It is proposed to use the change in the parameters of the virtual standard of the wave response, describing the cold and hot state of the turn-toturn insulation of the traction motor armature winding. It is proposed to judge the degree of deviation of the virtual standard by the coefficients of deviation of the damping decrement and the angular frequency. The features of using the proposed technique in the process of maintenance during predictive diagnostics of the state of the turn-to-turn insulation of the traction motor armature winding are determined. Keywords Traction motor · Diagnostic parameter · Diagnostics · Wave response
1 Introduction The operability of DC traction electric motors (TEM) of rolling stock is laid at the stage of its design, it is determined by the quality of maintenance and repair, and also depends on the operating conditions. Currently, both new series of traction electric motors and old ones are operated on the railways of Russia, and malfunctions occur in both series of traction motors. The change in the technical condition of the inter-turn insulation of the traction electric motor of railway rolling stock occurs when the ambient temperature changes, including in autumn and spring. This process is caused by the ingress of water vapor into the insulation, which leads to its excessive moistening and the formation of voids during drying, which reduces the electrical resistance of the insulation. The study of statistical data shows that traction electric motors accounts for up to 14% of locomotive unit failures, while up to 80% of electric motors fail due to the deterioration of technical condition of the insulation. P. Shkodun (B) Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_21
217
218
P. Shkodun
Predictive identification of the beginning of the degradation process in the interturn insulation of the anchor winding of the rolling stock traction electric motor is an important scientific task aimed at reducing the cost of maintenance and repair of the TEM and locomotives in general. A review of the literature [1–12] confirms the absence in the literature of solving the problem of determining the degree of assessment of the technical condition of the DC motors armature winding inter-turn insulation. The analysis of the literature sources confirmed the effectiveness of the wave response method for solving the problem.
2 Materials and Methods Testing the condition of the TEM insulation primarily involves testing the hull and inter-turn insulation. Of the existing methods for testing the insulation of electric motors, it is possible to use methods that provide a comprehensive diagnosis of the state of the TEM insulation. The first group of methods is aimed at testing the state of the body insulation. This group includes the time/resistance method, the step voltage test method, the determination of the polarization and absorption coefficients. The use of these methods makes it possible to evaluate the quality of body insulation, determine the degree of its moisture content, and also indicate the need to take preventive measures to improve the quality of insulation even if its resistance value is satisfactory. To test the state of turn-to-turn insulation, it is proposed to apply the wave response method. The values of the criteria for assessing the quality of insulation based on the results of insulation tests are determined by state standards and regulations. To assess the quality of turn-to-turn insulation, it is proposed to use the wave response method. Currently, a method has been developed to assess the technical condition of the inter-turn insulation of the anchor winding of DC electric motors, using the analysis of parameters and waveform response. The method involves fixing the wave damping process that occurs in the armature winding of the TEM under the action of short diagnostic pulses at different angular positions of the armature. Impulses, acting on the conductors and insulation of the winding, cause the appearance of a damped oscillatory process in it, and changes in the technical condition of the insulation lead to a change in the parameters of the wave response. When the armature rotates slowly, the angular coordinate of the insulation damage site changes and the parameters of the wave response change. TED insulation functions in difficult conditions, therefore, perfect electrical insulating materials are used for its manufacture. The main characteristic of insulating materials is high temperature resistance. The basic requirements for TED, the classification of insulation in terms of resistance to high temperature and voltage are regulated by standards. The armature winding of traction motors consists of several sections that are placed in grooves formed by steel sheets from which the armature core is made. The ends of two sections of a two-layer winding are placed in one groove. The conclusions of the armature winding sections are connected to the
Preventive Diagnostics of Technical Condition …
219
contact plates of the collector in accordance with the selected connection scheme (loop, wave, combined). Sections of the anchor winding are fixed in the grooves with the help of special wedges. Conventionally, the insulation of the armature winding can be divided into turnto-turn and body. The insulation between the winding and the motor housing is additionally protected from mechanical damage by a layer of cover insulation. Sections of the armature winding, located in one groove, also have a common insulation. Winding end parts are most exposed to negative factors: winding end parts are not protected from external influences. The frontal parts of the windings are most often subjected to preventive and restorative operations: impregnation and drying. Winding insulation breakdown is one of the characteristic failures of rolling stock traction electric machines. The collector is one of the important structural elements of the traction motor armature. The insulation between adjacent collector plates is made of high quality insulating materials, and the collector design itself has a significant margin of safety. Failures of the collector-brush assembly in most cases are associated with the presence of a sliding contact, as well as with harsh operating conditions, but not with a violation of the integrity of the insulation. The following failures of the TED collector most often occur: unsatisfactory condition of the collector working surface; melting of solder from the junction of the winding with the collector plate. The most difficult in terms of diagnosis are latent injuries, since after the damage is detected, additional diagnostics are necessary to localize the damage site. The most important result when testing the state of insulation of electric motors can be achieved through the use of complex diagnostic methods. Identification and search for turn-to-turn short circuits is a complex technological operation. The technology for localizing turn-to-turn short circuits in the winding of the withdrawn armature has been worked out, patented and successfully used in production. There is a technique that allows you to fix the fact of the occurrence of an turn-to-turn short circuit in the armature winding of an electric motor without removing the armature. The study of the nature of the processes that cause the occurrence of a wave response and determine the nature of the reaction to the occurrence of insulation damage is an important task in the formation of a scientifically based approach to the application of the wave response method in practice. In this method, a simplified chain equivalent circuit of one parallel branch of the armature winding is considered. This mathematical model contains: u - voltage; x is the coordinate along the length of the winding; L, K, C - inductance, longitudinal turn-to-turn capacitance and winding capacitance per case, respectively, per unit length. A wave process occurs in the winding, the parameters of which depend both on the electrical and geometrical parameters of the tested winding. Oscillations in the armature winding occur as a result of the influence of a diagnosing pulse. Then these fluctuations die out, since the stored energy is spent on the formation of eddy currents, a small part of the energy is dissipated in the active resistance of the winding.
220
P. Shkodun
i u
Сdx
L/dx
i+
∂i dx ∂x
ik
L/dx ∂i ik + k dx ∂x
K/dx Сdx
K/dx Сdx
dx x Fig. 1 Element of the winding equivalent circuit
Figure 1 shows chain equivalent circuit of the winding, taking into account the losses that occur in a real winding, contains: inductance L dx , capacitance on the case C dx , resistance Rdx (losses in copper and eddy currents) and longitudinal capacitance Kdx.
When analyzing the processes occurring in the armature winding of a TED, it is convenient to use the winding section as a structural element of a chain equivalent circuit. Taking into account the damped nature of the wave responses, we can describe the damped wave process that occurs during testing by the following expression: U (t, x) = U0 e−βt sin(ωt + φ)sin(αx)
(1)
where U 0 is the amplitude of the wave response, V; β is damping factor, rad/s; ω is angular frequency, rad/s; ϕ is initial phase of oscillation, rad; α is spatial oscillation phase factor, rad/m; x is coordinate along the length of the winding, m. Experimental studies have shown that half the period of the spatial component of the wave damping process fits along the length of the armature winding parallel branch. This simplification is valid only for the fundamental harmonic of the spatial and temporal components of the damped wave process. In the process of experimental studies, no significant effect of higher harmonics on the test results was revealed. The series circuit resistance includes the active resistance of the winding under test, the resistance of the control resistor, and the internal resistance of the power supply. The occurrence of an turn-to-turn short circuit in the winding leads to a change in the nature of the damped wave process amplitude distribution along the length of the winding. Thus, the winding is divided into two parts with proportional lengths (Fig. 2). The deviation of the parameters of the wave response calculated realizations from the experimental realizations does not exceed 7%. The presence of deviations in
Preventive Diagnostics of Technical Condition …
221
I0/2 I0/4 0 - I0/4 - I0/2 I
-3I0/2 I0 0 x l/5
2l/5
3l/5
4l/5
l
0
T/5 t
2T/5
3T/5
4T/5
T
Fig. 2 Visual representation of the wave response in a healthy winding
the calculation results is due to the presence of mutual induction between the turns of the sections lying in the same groove, which is not taken into account by the mathematical model. The shape of the tested electric motor wave responses on the brushes depends on the nature of the interaction of physical processes in the healthy and damaged parallel branches of the tested armature winding. The change in the shape of the wave response in the process of armature changing the angular position is caused by physical processes that occur in the armature winding. To register the wave response, a mobile device for diagnosing the state of interturn isolation of commutator electric machines WRM Tester was used [13]. The device was created on the basis of the STM32F746G-DISCO debugging module by employees of the Department of Electrical Machines and General Electrical Engineering of OSTU. The microcontroller controls the supply of a short rectangular pulse, registers the wave response, saves the measured values to an SD card in the form of instantaneous samples. The device has a galvanic separation and a power key, while the measuring channel is implemented on a differential amplifier INA159 Texas Instruments. The device can be used in locomotive depots and locomotive repair plants, it is portable and has a Li-ion battery with a charge-discharge controller. Based on the previously conducted studies using the WRM Tester mobile device, we have obtained the ranges of acceptable values of wave responses characterizing the operable state of the inter-turn insulation of the armature winding of the TEM. When performing these studies, it was found that it is advisable to use virtual standards that characterize the technical condition of the insulation of the armature winding of the TEM. The previously developed methodology does not contain information about the possibility of predictive assessment of the technical condition of insulation, but is
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aimed at finding defects in the form of a short circuit. If the inter-turn insulation of the TEM is in a serviceable condition, the wave response does not change at different angular positions of the TEM armature, but it has a difference at different temperatures. Thus, the task arises of supplementing the methodology with measurements of the armature winding wave response in cold and hot states, calculating the parameters of the wave response, which can diagnose changes in the technical condition of the inter-turn insulation of the armature winding. The degree of change in electric strength is associated with a change in resistance and inter-turn capacitance. It is possible to solve this problem by using a mathematical model of the wave response of the inter-turn insulation of the TEM armature winding in the form of a virtual standard for cold and hot states, which will allow predictive diagnostics of changes in the state of the inter-turn insulation of the armature winding of the TEM with an increase in its temperature, which is adequate to the processes occurring in operation. Figure 3 shows an oscillogram of the registered wave response signal received on the armature winding of the TEM on completion of the rectangular diagnostic pulse and that of the virtual standard. The given signal is described using a sinusoidal function exponentially decreasing in amplitude. This form of wave response is the same for different series of TEMs and can be represented by the mathematical expression: U (t) = U0 e−kδ δ0 t sin(kω ω0 t + α),
V
(2)
Virtual standard
mks
U
Actual wave response
t Fig. 3 Wave response of inter-turn insulation of the armature winding of the traction electric motor of locomotives
Preventive Diagnostics of Technical Condition …
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where U 0 is the amplitude of the wave response, V; k δ is the coefficient of deviation of the attenuation decrement; δ 0 is attenuation decrement, 1/s; k ω is the coefficient of deviation of the angular frequency; ω0 is angular frequency, rad/s; α is initial phase, rad. The presented mathematical model of the signal contains coefficients characterizing the wave response, these coefficients can be determined for cold and hot insulation conditions. The coefficient Δk δ is the factor of the change in the attenuation decrement of the oscillatory damping process, and the coefficient Δk ω is the factor of the change in the deviation of the angular frequency, while both coefficients are determined relative to the values of the attenuation decrement and angular frequency for the cold state of the inter-turn insulation of the armature winding. The calculation of these coefficients is carried out using the following mathematical expressions: Δkδ =
δhot , δcold
(3)
Δkω =
ωhot . ωcold
(4)
Figures 4, 5 and 6, as an example, show the results of measurements of the wave response of the inter-turn insulation for the EK810Ch type traction electric motors of the 2ES6 electric locomotives when a diagnostic pulse is applied.
V
U
mks
t Fig. 4 The wave response of the inter-turn insulation of the armature winding of the electric motor EK810Ch No 335 in cold and hot states
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V
U
mks
t Fig. 5 The wave response of the inter-turn insulation of the armature winding of the electric motor EK810Ch No 691 in cold and hot states
V
U
mks
t Fig. 6 The wave response of the inter-turn insulation of the armature winding of the electric motor EK810Ch No 1527 in cold and hot states
3 Results The analysis of the registered implementations of the TEM wave response was carried out, which made it possible to determine the diagnostic parameters of the wave response describing the cold (δ cold , ωcold ) and hot (δ hot , ωhot ) state of the inter-turn insulation of the TEM armature winding, as well as the factor of changes in the
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Table 1 The results of calculating the parameters of the wave response of traction motors δ cold , 1/s
δ hot , 1/s
ωcold , rad/s
ωhot , rad/s
k δ
k ω
335
120,760
130,215
288,218
283,000
1.078
0.982
692
92,500
86,542
145,000
138,020
0.936
0.952
1527
130,500
135,700
289,700
252,300
1.040
0.871
Parameter TEM number
diagnostic parameters Δk δ and Δk ω . Experimental data were processed, the values of the variation of the deviation coefficient of the attenuation decrement and the deviation coefficient of the angular frequency for the analyzed data are given in Table 1. The change in the diagnostic parameters of the wave response was no more than 10% for the entire sample of serviceable TEM. Thus, based on the analysis of the actual wave response signal obtained on the armature winding of the TEM in cold and hot states, diagnostic parameters were obtained in the form of the factor of change in the attenuation decrement Δk δ and the angular frequency Δk ω . The closer the value of these diagnostic parameters is to one, the smaller the change in insulation parameters as its temperature increases. At the same time, it is necessary to take into account the correspondence of the parameters of virtual standards to the serviceable state of isolation. Predictive diagnostics consists in assessing the values of diagnostic parameters, and the degree of change in the technical condition of the inter-turn insulation of the armature winding of the TEM can be evaluated by the calculated numerical values.
4 Conclusions The use of the presented methodology for assessing the technical condition of the inter-turn insulation of the armature winding of the TEM using the WRM Tester device has a number of features: – diagnostic parameters of changes in the attenuation decrement and the angular frequency of virtual standards can be used for qualitative comparison of the state of the inter-turn insulation of the armature winding of various traction motors when its temperature changes; – accumulation of an array of statistical data will make it possible to clarify the ranges of changes in the parameters of the virtual standard for a specific type of TEM in cold and hot states; – if a significant change in the wave response in the hot state is detected in terms of shape and parameters relative to the virtual standard in the cold state, further diagnosis of the armature winding of the TEM is required to identify the causes that caused such a deviation.
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References 1. Baranski M, Decner A, Polak A (2014) Selected diagnostic methods of electrical machines operating in industrial conditions. IEEE Trans Dielectr Electr Insul 21(5):2047–2054. https:// doi.org/10.1109/TDEI.2014.004602 2. Decner A, Glinka T, Polak A (2008) Diagnostic tests method of turn to turn insulation. Zeszyty Problemowe–Maszyny Elektryczne 79:103–106. https://doi.org/10.1109/ICELMACH.2010. 5608307 3. Decner A, Polak A (2010) Diagnostic tests of turn-to-turn insulation. Paper presented at the 19th international conference on Electrical Machines–ICEM, pp 1–3. https://doi.org/10.1109/ ICELMACH.2010.5608307 4. Fernando N, Romanazzi P, McCulloch MD (2017) Degradation of mechanical properties of class-H winding insulation. Paper presented at the IEEE international Electric Machines and Drives conference, pp 1–7. https://doi.org/10.1109/IEMDC.2017.8002411 5. Grubic S, Aller J, Lu B, Habetler T (2008) A survey on testing and monitoring methods for stator insulation systems of low-voltage induction machines focusing on turn insulation problems. IEEE Trans Ind Electron 12:4127–4136. https://doi.org/10.1109/TIE.2008.2004665 6. Grubic S, Restrepo J, Aller J, Bin L, Habetler T (2011) A new concept for online surge testing for the detection of winding insulation deterioration in low-voltage induction machines. IEEE Trans Ind Appl 47(5):2051–2058. https://doi.org/10.1109/TIA.2011.2161972 7. Gyftakis K, Kavanagh D, Sumislawska M et al (2015) Dielectric characteristics of electric vehicle traction motor winding insulation under thermal ageing. IEEE Trans Ind Appl 313–318. https://doi.org/10.1109/EEEIC.2015.7165179 8. Henao H, Capolino G, Fernandez-Cabanas M et al (2014) Trends in fault diagnosis for electrical machines: a review of diagnostic techniques. IEEE Ind Electron Mag 8(2):31–42. https://doi. org/10.1109/MIE.2013.2287651 9. Polak A (2013) The use of DC current to testing condition of the insulation of electrical machines. Przeglad Elektrotechniczny 1:123–131 10. Schemmel F, Bauer K, Kaufhold M (2009) Reliability and statistical lifetime-prognosis of motor winding insulation in low-voltage power drive systems. IEEE Electr Insul Mag 25(4):6–13. https://doi.org/10.1109/MEI.2009.5191411 11. Taylor CD, Grzybowski S (2009) Measurement of partial discharge in machine winding insulation during short-rise time pulse voltage. Paper presented at the IEEE Electric Ship Technologies Symposium, pp 529–532. https://doi.org/10.1109/ESTS.2009.4906562 12. Toliyat H, Nandi S, Choi S, Meshgin-Kelk H (2013) Electric Machines-Modeling Condition Monitoring and Fault Diagnosis, pp 117–118. CRC Press, Taylor & Francis Group, Boca Raton 13. Kharlamov V, Shkodun P, Shestakov I (2018) Improvement of the methodology for improvement of the turn-to-turn short circuit detection in the driving motor anchor winding. In: Murgul V, Popovic Z (eds) International Scientific Conference Energy Management of Municipal Transportation Facilities and Transport EMMFT 2017. EMMFT 2017. AISC, vol 692, pp 24–30. Springer, Cham. https://doi.org/10.1007/978-3-319-70987-1_3
Improvement of the Traction Resource Management System to Enhance the Performance of Electric Rolling Stock Alexander Vilgelm , Aleksandr Komyakov , and Alexander Strauchman
Abstract The paper deals with the energy efficiency management systems for train traction in JSC “Russian Railways”. The purpose of the long term development programme and energy strategy of JSC “Russian Railways” is outlined. The paper substantiates the significance of scientific research in this field. The current situation with traction rolling stock and modern traction resource management systems is analyzed. The paper also provides the current state of Russian and foreign scientific research in the field of energy efficiency. The purpose of this study is to test the possibility of enhancing the performance of electric rolling stock by improving the traction resource management system. A conceptual model describing the dependence of energy efficiency indicators on standard setting factors and operational indicators was created. The paper suggests the use of the proprietary methodology which is improved to meet the target objectives. The initial data are samples of the factor scores and indicators on which the energy efficiency and performance of locomotives and their corresponding scores of standard setting factors and operational indicators may hypothetically depend. A sequence of obtaining output data is provided to create computational models in “KORTES” (Complex of Calculations of Traction Power Supply). The functional flow diagram of the proposed system and its description are given. The paper proposes an approach to improve the traction resource management system. Keywords Energy efficiency · Train traction · Traction rolling stock · Electric rolling stock · Data analysis · Simulation modeling · KORTES · SimuLink
1 Introduction In accordance with the long term development program of JSC Russian Railways concerning the key area of efficiency improvement, it is planned to reduce the cost A. Vilgelm (B) · A. Komyakov · A. Strauchman Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_22
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of rail transportation in 2025 to that of 2018 for baseline and optimistic scenarios by 13 and 18%, respectively (for the prices in 2018). It is worth noting that one of the main objectives of the long term development program of JSC Russian Railways and the energy strategy of JSC Russian Railways holding is a significant increase in the energy efficiency of train traction. As noted in [1–3], this problem is also relevant for other major railways in the world. In order to increase the energy efficiency of transportation, enhance the performance of traction rolling stock (TRS) and replace the outdated locomotive fleet, in 2020 JSC Russian Railways purchased 328 mainline electric locomotives including 294 freight ones (2ES5K – 15 units, 3ES5K – 122 units, 4ES5K – 15 units, 2ES6 – 96 units, 3ES6 – 30 units, 2ES7 – 9 units, 3ES4K – 4 units, 3ES10 – 3 units) and 34 passenger ones (EP2C – 25 units, EP20 – 5 units, EP1M – 4 units). Great costs of JSC Russian Railways associated with the purchase of new rolling stock necessitate implementing modern engineering and methodological solutions aimed at improving the efficiency of rolling stock operation. On the one hand, the analysis of research has shown that improving the efficiency of locomotive operation including energy issue is widely discussed. Junhua Ren etc. in [4] and Zhang Chenchen etc. in [5] analyze the factors affecting the consumption of electricity for train traction. In [6] Pengling Wang and Rob M. P. Goverde consider multi-train trajectory optimization for energy efficiency and delay recovery. Also, energy-efficient train timetable problems are considered in [7–10]. The problems of increasing the efficiency of train traction using regenerative braking are considered in the works of Youneng Huang etc., Michał Urbaniak etc., Gabriel Réchard etc., Lilia Galaï-Dol etc., Nezevak V. L. and Cheremisin V. T [11–15]. On the other hand, S. I. Noskov etc. [16], A. Di Graziano etc. [17] exploring the impact of performance indicators of traction rolling stock on the operational characteristics of railway transport. To solve these problems, simulation modeling is widely used [18]. However, the current challenges facing railway transport, in particular, its increasing role of energy for total operating costs, the accelerating digital transformation of JSC Russian Railways necessitate further research related to the improvement of the traction resource management system in order to enhance the performance of electric rolling stock. At present, there is no thorough research of methods for evaluating the performance of locomotives to assess and predict changes in the energy efficiency indicators of train traction relative to the current values when operational indicators are changed, the technical characteristics of the new traction rolling stock and operational parameters of railway sections. The authors note the mutual influence of emerging trends and hypothesize that a promising direction for the development of the traction resource management system is the designing a methodology for assessing the optimal values of electric rolling stock performance indicators based on simulation and statistical models as to energy efficiency.
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2 Materials and Methods The purpose of this study is to analyze the possibility of enhancing the performance of electric rolling stock by improving the traction resource management system. The paper suggests the use of the proprietary methods [19, 20] which are improved to meet the target objectives. To develop simulation models, it is proposed to use the complex of traction computation programs “KORTES” and the process modelling system MATHLAB SimuLink. The subject of the study is the traction resource management system. The initial data are the retrieved values of energy efficiency indicators and the corresponding values of standard setting factors and operational indicators obtained through KORTES software package simulation modelling. Numerical methods of approximation and smoothing of experimental data, least square method, gradient descent method and machine learning methods are used to create statistical models. The model describing the dependence of energy efficiency indicators on standard setting factors and operational indicators has the following form E = f (x1 , x2 ...xn )
(1)
where E is an energy efficiency indicator, x—the factors affecting energy efficiency, n is the number of factors; Several approaches can be used for this sampling: – using the DRCP database–the system of centralized processing of the driver’s routes; – using the KORTES software package; – using the SimuLink simulation system. To assess the consumption of fuel and energy resources (hereinafter referred to as FER), JSC Russian Railways approved of a methodology for analyzing and forecasting fuel and energy consumption for train traction [9]. This methodology uses the main information–the consumption of fuel and energy resources and the values of operational factors presented in the data repository of JSC Russian Railways in “Locomotive fleets” in the form of THO-125 and the reference data on the performance of indicators of traction rolling stock operation; meteorological data on atmospheric air temperature (hereinafter referred to as temperature). According to this methodology, the analysis of the consumption of fuel and energy resources is made by comparing the actual change in the specific consumption of fuel and energy resources (the DRCP base) in the structural unit with the corresponding calculated value of the total change in the specific consumption of fuel and energy resources due to the impact of changes in operational factors in the reporting period
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Determining computaton model type depending on the calculated number of main tracks, current type, profile type
Computing total traction for various traffic (freight, passenger, suburban) with all possible input and output parameters
Statistical processing of the obtained sampling
Determining optimal values (the ranges of values) of operational indicators as to specific sections, conditions, lines of locomotives etc. Fig. 1 The sequence of constructing the simulation model
relative to the reference period and target indicators. When analyzing the consumption of fuel and energy resources, one should select the last calendar period similar to the reporting period as the base one. Collecting and processing the obtained empirical and theoretical data are done separately by types of traction rolling stock, types of traffic, lines of traction rolling stock and areas of work within the sites of locomotive crews. The main disadvantage of the data withdrawn from the DRCP is their insufficient reliability due to various equipment failures and the human factor. When computation models are created in KORTES, the following sequence of actions will be used (Fig. 1). It is important to create test samples different from each other due to the key parameters of the site. Thus, the type of track profile significantly affects the amount of energy consumption for train traction. It is also necessary to understand that, on the one hand, with the increasing non-uniformity of the track profile of the gage section, the mass of freight trains becomes the limiting factor. On the other hand, a non-uniform profile gives more possibility for using the kinetic energy of moving trains in terms of electricity recovery in the overall energy balance. Moreover, the type of current or the number of the main tracks of the gage section crucially affects the amount of energy loss in the traction supply system, the possibilities and specific use of regenerative braking and, as a consequence, the values of empirical coefficients and the final empirical expressions for calculating energy efficiency.
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To create computation models in KORTES, after the section parameters are selected, it is necessary to make a set of traction computation for freight, passenger and suburban types of traffic for each of the standard sections. In these computations, the input (changeable, i.e. independent) parameters of traction computation are the following: – – – – – –
the mass of the stock; the load on the axle of the train; a line of locomotives; the number of stops; operating speed; and others.
The output (computation results, i.e. dependent) parameters of traction computations are: – – – –
service speed and service speed coefficient; total electric power consumption according to electric rolling stock meters; energy recovery according to electric rolling stock meters; the time spent by the electric rolling stock in recovery mode of the total running time; – active energy consumption and power factor for AC sections; – and a number of other parameters. The next step will be computing traction and sampling with subsequent statistical processing of the computation results. The processing tool is a regression correlation analysis of data used to obtain optimal values or ranges of values for operational indicators. When traction is calculated, the obtained data are compared with the obtained mathematical models “Simulink” and the data of “DRCP”. Thus, it is necessary to follow a sequence of actions which are illustrated by the following algorithm (Fig. 2). The data source in this algorithm is the actual data, the results of simulation modelling in KORTES software package and MATHLAB SimuLink. The Computation Sampling subprogram is a combined base of the data obtained as the results of computation based on a constructed computation model. The Correlation Data Analysis subprogram is a statistical study of the obtained data and the identification of significant or insignificant factors and indicators that affect the operational characteristics of locomotives. The block Conducting Test Measurements includes a trial check of the statistical data obtained through the three approaches. The criterion Data Convergence Check is a comparison of the data obtained in each of the approaches. The output Optimal Factors and Indicator Values—obtaining optimal values of factors and indicators on which operational indicators depend. After receiving the functions (1), it is necessary to minimize the function. Minimizing a function or searching for the minimum of a function with several variables can be done in MATHCAD.
232
Fig. 2 The algorithm of the sequence of actions
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3 Results To test the algorithm (Fig. 2), a computation model was created, on the basis of which traction computations were carried out for a DC 2ES6 electric locomotive on a hypothetical section with a non-uniform track profile of about 150 km long. Train traffic is assumed as non-stop traffic. With the help of the KORTES software package, 100 traction computations were made based on the data of the computation model. All the data obtained during traction computations and the calculated data (specific power consumption) were summarized in an Excel table. A fragment of the obtained data is presented in Table 1. Due to the data obtained as a result of modelling, it is possible to construct the following graph of the dependence of the specific energy consumption on the mass of the stock and the running speed of the stock (Fig. 3). The graph shows that the extremum of function is within the mass ranging from 4000 to 4500 tonnes, the speed ranging from 35 to 45 km/h and specific power consumption ranging from 90 to 105 kWh/104 tonne kilometre gross. On the basis of the correlation and regression function in Statistica, the following values presented in Table 2 were obtained. The R-squared coefficient of determination is 0.846. This coefficient indicates that the calculated parameters of the obtained function, i.e., the model itself, explain the Table 1 Sampling of results Weight, m, kg
Speed, V, km/h
Power consumption, w, kWh
1500
39.8
2994.6
1500
45
1500
49.7
1500
54.9
1500 1500
Tonne kilometre operation A, 104 tonne kilometre gross
Specific energy consumption wp, kWh/104 tonne kilometre gross
21.7
137.8
3011.2
21.7
138.5
3037.9
21.7
139.8
3084.8
21.7
141.9
59.9
3155.6
21.7
145.2
65
3238.7
21.7
149.0
1500
69.9
3361.4
21.7
154.7
1500
74
3512.3
21.7
161.6
7000
27.4
13,606.5
101.4
134.1
7000
25.8
13,662
101.4
134.7
7000
27.7
13,677.6
101.4
134.8
7000
28
13,804.4
101.4
136.1
7000
28.4
14,191.1
101.4
139.9
7000
22.9
14,380.2
101.4
141.8
…
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Fig. 3 Three-dimensional graph of the dependence of the specific power consumption on the mass of the stock and the running speed
Table 2 Final values of correlation and regression analysis N = 96
Beta
Intercept Weight
Std. Err. of Beta
B
Std. Err. of B
t(91)
p-level
−
−
240.2614843
14.02691
17.1286
0.000000
−3.59678
0.305093
−0.0407855
0.0346
−11.7891
0.000000
Speed
−2.16498
0.475502
−2.5281257
0.55526
−4.5530
0.000016
Weight2
3.70309
0.323570
0.000005044
0.00000
11.4445
0.000000
Speed2
2.31946
0.453717
0.02731161
0.00534
5.1121
0.000002
dependence and changes in the studied parameter—the specific power consumption on the studied factors—the mass of the stock and the running speed. In the end, withdrawing the coefficients from Table 2, we get the following dependence: wp (V, m) = 240, 2613843 − 0, 0407855 · m − 2, 5281257 · V + 0, 000005044 · m 2 + 0, 0273116 · V 2
(2)
Specific power consumption, kWh/10 4 tonne kilometre gross
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180.0 160.0 140.0 120.0 100.0 80.0 60.0 40.0 20.0 0.0
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 Computation model number
Fig. 4 Graph of convergence of the values of the calculated wp (point) and the obtained values of wp as a result of traction computations
Applying the values of the stock mass and speed from Table 1 for the function (2), we obtain the following convergence graph (Fig. 4). Figure 4 shows that the convergence of the function graph (2) with the results of the numerical experiment is quite high (the average relative error was 6.1%). However, in the range of very small and very large train masses, there is a more significant discrepancy between the factual and simulated mass. This requires correcting the model (2) for the specified ranges through the use of other types of nonlinear functions or machine learning methods, for instance. Next, using MathCAD, we will construct a three-dimensional graph according to the function (2) (Fig. 5). Then we will construct a three-dimensional graph of wp(m, V) function and determine the minimum of this function equal to wp = 99, 311kW t ·h104 tkm gr oss, which corresponds to the value of the train mass m = 4043 T and speed V = 46, 283 km/h.
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w p, kWh/10 4 tkm gross
V, km/h m, tons
Fig. 5 Three-dimensional graph of the dependence of wp (m, V) on the basis of the obtained function
4 Discussion and Conclusions This paper proposes the approaches to the development of a traction resource management system through the assessment of optimal values of the performance indicators of electric rolling stock as to energy efficiency. To achieve this, an algorithm including the following steps: development of a simulation model, selection of an approximating function and its minimization has been developed. To confirm the efficiency of the approach, a numerical experiment has been carried out. The experiment has proved that the best energy efficiency indicators are achieved with a train weight of 4043 tonnes and a speed of 46.3 km/h. In this case, we had one extremum of the function, however, the authors do not exclude that variants with several local extremes are possible. For instance, one in the range characteristic of empty trains, the second–in the range of high mass trains. Using simulation modeling methods (KORTES or Matlab) to sample the source data in comparison with DRCP database has a number of advantages. They are the analysis of a wider range of operational indicators, increase in the reliability of data by eliminating errors associated with incorrect readings of metering devices, etc. The results obtained are in good agreement with the theory of train traction, but at the same time allow us to expand theoretical knowledge in terms of modeling energy efficiency indicators depending on operational indicators. In comparison with the methodology of analysis and forecasting of energy consumption for train traction currently used by JSC “Russian Railways”, the obtained results demonstrate a nonlinear dependence
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of specific electricity consumption on operational indicators, which increases the accuracy of calculations and allows for determining the range of optimal values of operational indicators. The proposed approaches can be used for: 1) improving the system of managing train traffic and traction resources by composition of trains with optimal performance indicators; 2) developing the methodology for analysis and planning of energy efficiency indicators of transportation. For further development of the proposed approaches, the authors advise the following: 1) increasing the sample size of the source data by leveling off changes in operational indicators, performing calculations for various types of track profiles, locomotives, etc.; 2) taking into account more impact factors; 3) improving simulation modelling methods due to more correct registering of the feed voltage level, air temperature, etc.; 4) improvement of regression models through the use of nonlinear functions of various types, machine learning methods.
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Optimization of the Technology of Electrolytic Zincing of Traction Mechanisms Parts Dmitry Muravyov
and Ekaterina Izmest’eva
Abstract The purpose of the article is to determine the optimal modes of hot-dip zincing of the parts to obtain a coating of increased strength and corrosion resistance in order to improve the operational reliability of the parts subject to negative environmental factors. The article presents the results of an experimental study of zinc coating of such part as a pull rod, which is included in the design of the elevator counterweight. In the course of the research based on the theory of experimental planning, a full factor experiment was conducted. In the experiment, the thickness of the zinc coating of the part and the impact of such factors as coating time and current density were considered as optimization parameters. The results of the experiment made it possible to determine the optimal values of the selected factors to ensure the thickness of the zinc coating required by the regulatory documentation for the manufacture of the pull rod in the conditions of existing production. Keywords Galvanizing · Corrosion · Current density · Coating · Thickness · Part · Temperature · Electrolyte · Experiment · Optimization · Technological process
1 Introduction The durability of parts combined into a single structure is determined not only by the quality of their manufacture but also by the operational properties of the working environment. Therefore, the reliability of parts largely depends on the corrosion rate. Being especially heavy at increased mechanical and thermal stresses, corrosion processes cause significant damage to steel structures. Due to corrosion, steel structures lose the required ductility, strength, tightness, thermal and electrical conductivity, reflectivity and other important properties [1]. D. Muravyov (B) Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] E. Izmest’eva PKF-Siblift LLC, 11, Industrialnaya Street, Omsk 644027, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_23
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Through the method of expert assessments, it was found that at least 15% of the annual volume of steel production is wasted on the replacement of corroded metal. At the same time, metal is irretrievably wasted in the form of products and structures, the cost of which significantly exceeds the cost of the original metal. Corrosion losses account for 5–10% of national income in all industrialized countries. Corrosion losses are increasing annually including those resulting from environmental pollution. The analysis of the consequences caused by waste polluting the environment shows that the same harmful substances that dangerously affect the ecological balance in the nature cause corrosion of metals. For instance, the atmosphere is highly polluted by the emission of various gases, dust, smoke. Along with the issues of rational use of material resources, the development of cost-effective technological processes, environmental protection remain the most important problems of our time. Thus, the analysis of information a priori helped to formulate the main purpose of the study, i.e. the necessity to improve the technology of applying zinc coatings in the manufacture of parts in order to reduce the corrosion rate. The object of the research is the zincing technology of such part as a pull rod included in the suspension unit for the cable of the elevator counterweight beam. The counterweight is designed to balance the weight of the cabin and partially the weight of the transported cargo, which reduces the power of the drive motor. The scientific novelty of the work lies in the fact that for the first time a study of zincing the pull rod of the manufacturer LLC “PKF Siblift” in Omsk was conducted with the help of methods of planning an industrial experiment in order to optimize the modes of zinc coating. The theoretical and practical significance of the research is the application of the obtained results to improve the zinc coating technology of the pull rod on the production facilities of the manufacturer. The parameters of the pull rod should comply with the norms during its service life when the part is exposed to such climatic factors as: • the effect of oxygen on the metal contributing to the metal oxidation; • high humidity leading to metal corrosion; • high air pollution leading to the destruction of metal. The material used for the manufacture of the considered part is steel 20, which has balanced chemical composition. However, nickel (up to 0.3%), chromium (up to 0.2%) and copper (up to 0.3%) contained in the steel composition generally having a positive effect on the mechanical properties of steel, do not significantly increase the corrosion resistance of the alloy due to their low concentration. Thus, in order to strengthen the resistance of steel 20 to corrosion, zinc coating is a part of the technological process of manufacturing the pull rod [2]. Zinc coating is anodic in relation to black alloys and protects steel from corrosion electrochemically at temperatures of up to 70 °C, and at higher temperatures – mechanically. Moreover, zinc in comparison with other metals is not toxic to humans [3, 4].
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The thickness of the zinc coating was chosen as a controlled parameter for optimizing the electrolytic zincing process. The thickness could be adjusted in the range from 3 to 40 µ by changing various technological parameters such as: • • • •
current force in amperes; current density; operating temperature of the electrolyte; concentration of active components of the working solution.
During the electrolytic zincing, the composition and temperature of the electrolyte at a given current density directly affect the deposition rate and the structure of the zinc coating [5]. The selection and provision of suboptimal values of the exposure time, the temperature of the working solution and the current density during zincing lead to the defects in the zinc coating, among which [6–8] are: 1. Insufficient adhesion on the surface of the pull rod (Fig. 1, a). The peeling and fragility of the zinc coating are mainly associated with the poor quality of the preparation of the greasy surface. In addition, the cause of lack of adhesion may be an inaccurate exposure time of the part in the electrolyte solution. 2. 3. 4. 5.
Pitting corrosion on the surface (Fig. 1, b). Roughness on the edges of the part. The diversity of the appearance of the coating. The fragility of the zinc coating.
Dark (mainly brownish or black) color - occurs when the electrolytic bath is contaminated and the permissible amount of waste is exceeded.
Fig. 1 Defects in the zinc coating of the pull rod: a insufficient adhesion; b pitting corrosion on the part
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Defects arise from various causes including: • drawbacks in surface preparation before applying zinc; • violations in the electrolyte technology; • non-compliance with the operating parameters of the zincing process. In addition to all of the above, the quality of electrolytic zincing is affected by the configuration and spatial orientation of the part in the electrolyte, as well as the placement and condition of the planes of the main and auxiliary anodes. Defects lead to the destruction of the continuity of the zinc coating of the pull rod, deterioration of the protective properties and final corrosion [9–11]. Due to the action of intercrystalline corrosion, metal parts lose the required strength, tightness, thermal and electrical conductivity, reflectivity and other important properties. The analysis of zinc coating defects arising in the course of manufacturing the pull rods revealed the need for experimental substantiation of optimal modes of zinc coating through electrolytic zinc coating, which contributes to improving the quality of the operation.
2 Materials and Methods In order to determine the optimal modes of hot zinc coating in production, an industrial full factorial experiment (FFE) of type N = 22 was planned and conducted aiming at the formulation of the four main experiments. The thickness of the zinc coating h, microns, was chosen as the optimization parameter y, and as factors affecting this parameter: x 1 —zinc coating time T, min; x 2 —operating current density j, A/dm2 were considered. On the basis of production conditions and the analysis of a priori information, the levels of factors x 1 and x 2 were determined for variation during the experiment. The values of the factors are given in Table 1. The optimization of the thickness of the zinc coating was performed through the evaluation of the parameters of the mathematical model of the technological process Table 1 Names of factors and levels of their variation Item N
Factors Zinc coating time T, min
Operating current density j, A/dm 2
Natural value
Natural value
Encoded value
Encoded value
x 1
1
x 2
The basic level
10
0
2
0
The upper level
15
+1
3
+1
The lower level
5
−1
1
−1
Variation interval
5
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Table 2 The planning matrix of a full factorial experiment of type N = 22 yj
S y2
Experiment No
x0
x1
x2
x1 x2
y1j
y2j
y3j
yj
1
+
+
+
+
17
18
19
18
1
18
2
+
–
+
−
11
11
12
11.3
0.335
11.3
3
+
+
−
−
10
12
15
12.3
6.335
12.3
4
+
–
−
+
10
11
12
11
1
11
b
b0
b1
b2
b12
13.15
2
1.5
1.35
under study. The model was developed on the basis of the results of a full factorial experiment for two factors x 1 and x 2 in coded values, and is an algebraic polynomial of the second degree: y = b0 + b1 x1 + b2 x2 + b12 x1 x2 ,
(1)
where b0 , b1 , b2 , b12 are the estimates of the coefficients of the first-order mathematical model (regression coefficients). To determine the numerical values of the coefficients of the desired mathematical model with the selected levels of the factors taken into account, a DFE planning matrix was compiled. The matrix presented in Table 2 contains the conditions for conducting experiments on the basis of which an experiment with all possible combinations of factor levels was conducted. The electrochemical process of zinc deposition on the pull rod connected to the negative pole of the power supply was carried out in a solution of zinc sulfate and chloride as well as zinc fluoroborate [12–15]. The thickness of the coating was measured with the changed parameters of the electrolytic process by the Etari ET555 thickness gauge, the principle of operation of which is based on both magnetic induction and Hall effect, which allows for measuring the density of the magnetic field. The pull rod without visual defects before and after experimental zinc coating is shown in Fig. 2. The reproducibility of the experiments was evaluated on the basis of the results of three parallel experiments y1j , y2j , y3j when the homogeneity of the variances S yj (2) was evaluated according to Cochran’s test. The estimate of the variance of n parallel experiments for each i-th point of the factor space was determined by the formula: 3 2 S yi
=
t=1
yti − y i n−1
2 ,
(2)
where yti is the value of the optimization parameter for the i-th vector row of the planning matrix in the t-th parallel experiment; t is the number of parallel experiment, t = 1, …, n; n is the number of parallel experiments.
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Fig. 2 The pull rod before and after zinc coating
The hypothesis of reproducibility of experiments is tested through Cochran’s criterion, the value of which was calculated by the formula: 2 S ymax G calc = 4 2 = 0, 731 i=1 S yi
(3)
A comparison of the calculated value of the Cochran’s Gcalc criterion with the tabular value of the Gcalc for the selected significance level equal to 0.77 confirmed the hypothesis of reproducibility of experiments, since the Gcalc < G tab . Thus, it was found that the choice of factors and the levels of their variation were done correctly. The calculation of the values of the desired coefficients b0 , b1 , b2 , b12 of the mathematical model was performed with the help of the formulas: b0 =
1 4 x0 j y j , j=1 4
(4)
bi =
1 4 xi j y j , j=1 4
(5)
1 4 x i j xl j y j , j=1 4
(6)
bil =
where x ij , x lj is the encoded value of the i-th and l-th factors in the j-th experiment; x 0j is the encoded value of the dummy-based factor corresponding to the coefficient b0 in the j-th experiment.
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As a result of the calculations (see Table 2) an intermediate mathematical model of the technological process under study was obtained in coded values of factors x 1 and x 2 y = 13, 15 + 2x1 + 1, 5x2 + 1, 35x12 .
(7)
The estimation of the variance of the reproducibility of the experiment (the variance of the optimization parameter) was calculated by the formula: 4 S y2
=
2 j=1 S y j
N
=
8, 67 = 2, 1675. 4
(8)
Verification of the significance of the coefficients of the obtained mathematical model was carried out according to Student’s t-test by constructing a confidence interval of the coefficients. First of all, the variance of the regression coefficient was calculated through S bi with the help of the following formula: 2 Sbi2 = Sbil =
S y2 n·N
=
2, 1675 = 0, 1806. 3·4
(9)
Next, the confidence interval of the coefficients bi and bil was constructed: bil = bil = ±ttab Sbi = ±2, 306 · 0, 425 = ±0, 9801.
(10)
where t is the tabular value of Student’s criterion and is selected depending on the number of degrees of freedom with which the value was determined and the selected significance level αS y ; S bi - the quadratic error of the regression coefficient. Sbi = + Sbi2 .
(11)
All coefficients of the regression Eq. (7) are considered significant because their absolute value is greater than the confidence interval. The adequacy of the obtained incomplete quadratic regression equation was checked through Fisher criterion: Fcalc =
2 Sad , S y2
(12)
2 where Sad are estimates of the variance of the adequacy of the obtained mathematical model. The estimation of the variance of the adequacy of the mathematical model was determined by the following formula:
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2 n y j − yˆ j N − (k + 1) j=1 3 (18 − 18)2 + (11, 3 − 11, 3)2 + (12, 3 − 12, 3)2 + (11 − 11)2 = 0, = 4 − (2 + 1) N
2 Sad =
where y j is the predicted value of the response function according to the mathematical model tested in each j-th vector row of the DFE matrix. By formula (12) it was found that Fcalc =
0 = 0. 2, 1675
Thus, the hypothesis about the adequacy of the mathematical model was accepted because F calc < F tab , where F tab = 4.46. After the mathematical model in the encoded values of factors × 1 and × 2 was calculated and constructed, a transition from the encoded to the natural form of factor recording was made in accordance with the expression xi =
x˜i − x˜i0 , x i
(13)
where xi is the encoded value of the i-th factor; x˜i - the natural value of the i-th factor (in units of measurement); x˜i0 -the natural value of the “zero” level of the i-th factor; Δx i is the variation interval of the natural value of the i-th factor setting the values of the upper and lower levels of the factor. Thus, formulas for the transition to the natural form of recording factors x 1 , x 2 affecting the value of the optimization parameter ywere obtained x1 =
T − x˜10 T − 10 ; = x 1 5
(14)
j − x˜20 j −2 . = x 2 1
(15)
x2 =
After the transformation, the mathematical model took the form h = 11, 55 − 0, 14T − 1, 2 j + 0, 27 j T.
(16)
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3 Results
The thickness of the zinc coating
The resulting mathematical model (17) made it possible to construct the graph of the thickness of the zinc coating h depending on the operating parameters of the zinc coating mode: the zincing time T and the operating current density j shown in Fig. 3. It also allowed us to predict the values of the coating thickness at the values of factors that have not been studied experimentally. The analysis of the graph allowed us to conclude that there is a direct dependence of the zinc coating thickness on the technological parameters of the electrolytic zincing of the pull rod. Metallographic studies of the zinc coating were carried out on the SIAMS800 Solid Microstructure Fragment Analyzer consisting of an OLYMPUS GX41 inverted metallographic microscope with a maximum magnification of x1000, equipped with a microscopic video camera and connected to a personal computer with innovative software for panoramic microscopy. Figure 4 shows the microstructure of steel 20 at the interface between the base metal and the applied zinc coating, a—at 500x magnification; Fig. 4, b—at 1000x magnification.
Fig. 3 Graph of the dependency of zinc coating thickness on the zincing time and the operating current density
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Fig. 4 Microstructure of the interface between steel 20 and zinc coating at 500x a 1000x magnification b
The ferrite-pearlite structure of the base metal of low-carbon steel 20 and a layer of zinc coating with rainbow shades are clearly traced. According to Fig. 4, it can be concluded that it was possible to obtain a homogeneous and uniform zinc coating, and there is a strong adhesion of the coating with the base metal.
4 Conclusions The results of the experiment allowed us to draw the following conclusions: • The established range of optimal values of the process parameters made it possible to adjust the zincing production modes in order to obtain a uniform coating with a thickness of 8–18 microns in accordance with the requirements of the design documentation. • An external inspection of the parts after zincing in the set modes showed on the surface of the pull rod no defects such as slag deposits, uncovered strips or spots and scratches reaching the base metal. • The operating current density in the range from 1 to 2 A/dm2 and the exposure time during zincing for 15–20 min are the sufficient values to obtain a coating with a thickness of 9–12 microns. However, according to the proposed technological process, with simultaneous zincing of 100 parts, it is necessary to increase the current force in order to achieve the required current density. Despite the fact that the full factor experiment allowed us to obtain only a limited range of optimal values of the zincing mode parameters, the further research based on the planning of the second-order experiment will be aimed at determining the exact optimal values of the zincing time and current density to achieve a certain coating thickness.
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References 1. Sharma SK (2012) Green Corrosion Chemistry and Engineering: Opportunities and Challenges. Wiley-VCH Verlag GmbH Co, KGaA, Hoboken. https://doi.org/10.1002/9783527641789 2. Oluwole OO et al (2008) Effect of zinc plating of low carbon steel on corrosion resistance in cocoa fluid environment. Mater Des 29(6):1266–1274. Elsevier Science Publishing Company, Inc. https://doi.org/10.1016/j.matdes.2007.05.002 3. Wing L et al (2009) A solution to reducing the cost of acid zinc plating. Metal Finish 107(4):26– 30. Elsevier Science Publishing Company, Inc. https://doi.org/10.1016/S0026-0576(09)000 18-X 4. T Nozawaa T, Nakagawa K (2021) Understanding diffusion layer agitation by cavitation in electroplating based on high-speed monitoring. Ultrasonics Sonochemistry 81:105856. Elsevier Science Publishing Company, Inc. https://doi.org/10.1016/j.ultsonch.2021.105856 5. He YQ, Jia T, Liu XJ (2014) Hot-dip galvanizing of carbon steel after cold rolling with oxide scale and hydrogen descaling. Iron Steel Res Int 21:222–226. https://doi.org/10.1016/S1006706X(14)60034-0 6. Kanani N (2008) Electroplating: Basic Principles, Processes and Practice. Elsevier Science Publishing Company, Inc., Germany, Berlin. https://doi.org/10.1016/B978-1-85617-451-0. X5000-3 7. Maaß P, Peißker P (2011) Handbook of Hot-Dip Galvanization. Wiley-VCH Verlag GmbH & Co, KGaA. https://onlinelibrary.wiley.com/doi/book/https://doi.org/10.1002/9783527636884 8. Gusev VM, Mordynskii VB, Frolova MG (2016) Improvement of dynamic thermal diffusion galvanizing production process efficiency. Chem Petrol Eng 52:563–566. https://doi.org/10. 1007/s10556-016-0233-2 9. Grodecki J (2010) Achieving maximum brightness in a zinc plating bath solution. Metal Finish 108(5):26. Elsevier Science Publishing Company, Inc. https://doi.org/10.1016/S00260576(10)80105-9 10. Grodecki J (2011) Dealing with plating bath contamination and poor adhesion in zinc plating. Metal Finish 109(7):34–35. Elsevier Science Publishing Company, Inc. https://doi.org/10.1016/ S0026-0576(13)70069-2 11. Cf K, Zw Z, Ml W (2017) Effect of hot-dip galvanizing processes on the microstructure and mechanical properties of 600-MPa hot-dip galvanized dual-phase steel. Miner Metall Mater 24:1379–1383. https://doi.org/10.1007/s12613-017-1530-2 12. Vislobokova SL, Marutyan SV (2012) Problems with mastering hot-galvanizing technology in Russia. Metallurgist 55:625–627. https://doi.org/10.1007/s11015-012-9477-z 13. Andersson Ö (2012) Experiment!: Planning, Implementing and Interpreting. Published by John Wiley & Sons Ltd., Hoboken. https://doi.org/10.1002/9781118311059 14. Coleman HW, Steele WG (2009) Experimentation, Validation, and Uncertainty Analysis for Engineers, Third Edition. Published by John Wiley & Sons, Inc., Hoboken. https://doi.org/10. 1002/9780470485682 15. Moffat RJ, Henk RW (2021) Planning and Executing Credible Experiments: A Guidebook for Engineering, Science, Industrial Processes, Agriculture, and Business, First Edition. Published by John Wiley & Sons Ltd., Hoboken. https://doi.org/10.1002/9781119532828
Control of Mainline Freight Electric Locomotives with Adjustment of Operating Modes Stanislav Istomin , Artem Perestenko , and Sergey Shantarenko
Abstract The paper raises the problem of insufficient quality control of the operating modes of electric locomotives, carried out by on-board systems. The problem of determining the recommended values of the traction forces is presented as an iterative determination of the setting of the traction force for several subsequent time steps on the basis of a dataset known in advance and describing the past states of the locomotive. To solve this problem, artificial recurrent neural networks (ARNN) of the long short-term memory (LSTM) architecture are used, which are insensitive to time gaps between events and the effect of forgetting. As a result of comparing the data accumulated in the course of experimental studies and comparing them with the results of simulation modeling, it was found that when the locomotive implements the recommended values of traction and braking forces, a decrease in the values of the specific energy consumption of traction of trains per trip is expected on average by 1%. Keywords Energy efficiency · Electric locomotives · Adaptive control of electricity · Electricity metering systems · Electricity rationing systems
1 Introduction At the moment, many methods have been developed for determining the optimal operating modes of locomotives [1–14]. Most of them are based on the application of the provisions of the thrust calculation for the search for energy-optimal trajectories of motion and use the Pontryagin maximum principle. These methods operate with approximate dependences obtained by generalizing experimental data and very limitedly take into account the actual values of the factors changing in the process of traction of trains by a locomotive, operating mainly only with the information available before the start of the trip. With significant deviations from the trajectories S. Istomin (B) · A. Perestenko · S. Shantarenko Omsk State Transport University, 35, Marksa Prospekt, 644046 Omsk, Russia e-mail: [email protected]
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_24
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proposed by these methods, it is required to rebuild them for the entire remaining trip, which in some cases is inappropriate due to the high algorithmic complexity of the calculations.
2 Materials and Methods In general, the data from the on-board automatic driving systems-Registrar of parameters of movement and automatic driving (RPMAD) - are the matrix X, which describes the process of operating the locomotive as a sequential change in n states, each of which is determined by m parameters (features): ⎛
x11 · · · ⎜ X = ⎝ ... . . . xn1 · · ·
⎞ x1m .. ⎟, . ⎠
(1)
xnm
where x—parameter value. This matrix can also be represented as a multidimensional time series, where each index t corresponds to a vector of parameters of dimension m: X = (X t : t ∈ T ) = (x1 , x2 , . . . , xn )
(2)
where x—vector of parameter values with dimension m; t—multidimensional index; T —index set, T = {1, 2, . . . , n}. In this case, the task of processing data on the parameters of the motion of an electric locomotive can be reduced to the task of predicting the recommended operating mode of an electric locomotive y, described by m p parameters, for subsequent n p steps, based on known data from on-board systems x, described by m h parameters and containing n p measurements, i.e. samples from time series X. The setting of the traction force is taken as the y parameters, since it has a significant effect on the amount of electrical energy consumption, determines the nature of the train movement, and is not connected to the design features of a particular series of electric locomotives. Considering the operation of a locomotive as a sequential change of states, one can describe the trip as a discrete multidimensional time series. In this case, the problem of determining the recommended values of traction forces can be represented as an iterative determination of the force setting for several subsequent time steps based on a dataset known in advance and describing the past states of the locomotive. To solve this problem, artificial recurrent neural networks (ARNN) of the architecture of long short-term memory (LSTM), insensitive to time gaps between events and the effect of forgetting, were used [15–21]. This approach made it possible to present the results of the development of an algorithm for processing data on the parameters of the movement of an electric locomotive, which makes it possible to calculate the values
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of the traction force settings from the data of on-board systems, and a method for controlling mainline freight electric locomotives, which makes it possible to correct the operating modes of the locomotive. The force F realized on the bogie is a generalization of the traction and braking forces:
F = F[F > 0] − B[B > 0]
(3)
where [ ]—Iverson bracket. Maximum permissible train speed: p vmaxt = min vt , vtt , v d
(4)
where vp , vt —permanent and temporary speed limits, respectively; vd —maximum design speed. Based on the matrix x containing observations of the parameters of the locomotive movement for the last nh = 30 s, the recommended values of the force F realized on the bogie are determined for the following np = 10 s:
F = Wd h t + bd , t = n h
(5)
According to the results of the calculation of F, the traction F and braking B forces recommended for implementation on the bogie are determined: F =F F >0
(6)
B=F F χ2 t = 11.1, it follows that the hypothesis about the consistency of the opinions among the interviewed specialists is accepted.
Determining Optimal Electrical Discharge Machining Modes …
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3 Results The results of a priori ranking of the factors are presented in a rank diagram (see Fig. 2). According to the rank diagram, as the most crucial factors should be recognized the following: current force (x 1 ), the space between the electrode and the rough material (x 2 ), wire pull broaching speed (x 3 ). To describe the impact of the parameters of the EDM mode on the surface roughness, mathematical modeling with a simplex-lattice design was used. An industrial experiment was carried out on a Sodick AG400L wire-cut EDM machine. The 0.3 mm diameter brass wire was used as a tool electrode. The factors for conducting an industrial experiment are the current force (x1), the space between the electrode and the rough material (x2), the wire pull broaching speed (x3). The regression equation is described through the following polynomial solution: yˆ = b0 +
1≤i≤k
bi xi +
1≤i≤ j≤k
bi j xi x j +
bi jk xi x j xk
(3)
1≤i≤ j≤k≤q
expressed in the form: yˆ = β1 x1 + β2 x2 + β3 x3 + β12 x1 x2 + β23 x2 x3 + β13 x1 x3 + β23 x2 x3 + + β11 x12 + β22 x22 + β33 x32
Fig. 2 Rank diagram
(4)
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Table 2 Second order simplex lattice design Experiment number
x1
x2
x3
y
1
1
0
0
y1
2
0
1
0
y2
3
0
0
1
y3
4
1/2
1/2
0
y12
5
1/2
0
1/2
y13
6
0
1/2
1/2
y23
Table 3 Experiment design matrix Experiment number
The space between Current force I, A the electrode and the rough material A, μm
Wire pull broaching speed V pull , m/min
Surface roughness Ra, mm
1
45
6
80
1.475
2
18
10
80
1.975
3
18
6
100
1.75
4
31.5
8
80
1.1
5
31.5
6
90
1
6
18
8
90
0.8
Tables 2 and 3 show the second-order simplex-lattice design (Scheffe’s simplexlattice design) and the experiment design matrix. Six experiments were sufficient for conducting an industrial experiment according to Scheffe’s simplex-lattice design. The mathematical relationship describing the impact of the mode parameters on the roughness of the herringbone pattern was obtained through the Statistica 6.0 software package and has the following form: y = 1.475x1 + 1.975x2 + 1.75x3 −2.5x1 x2 −2.45x1 x3 −4.25x2 x3
(5)
The adequacy of the obtained mathematical models was verified through comparing the calculated values of Student’s t-criterion. t pRa = 1.46 with a tabular value of t 0.05; 10 = 2.228 with 5% significance level. Since the calculated value of the t- criterion is less than the tabular one, the obtained regression equations should be considered adequate. The transition from coded factor values to natural values was done through the expressions: – the space between the electrode and the rough material - A = 18 + 27 x 1 ; – current force-I = 6 + 4 x 2 ; – wire pull broaching speed - V pul = 80 + 20 x 3 .
Determining Optimal Electrical Discharge Machining Modes …
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Fig. 3 Surface of equal response
To construct the surface of equal response, the Statistica 6.0 software package was used. Figure 3 shows the resulting surface of equal response. The optimal machining mode to achieve the roughness parameter Ra ≤ 1.5 μm was determined by solving the Eq. (5) by searching through all the values of the factors x 1 , x 2 , x 3 . The mode providing the maximum machining and allowing for achieving the required value of the roughness parameter Ra = 1.5 microns is the current force-9 A, the space between the electrode and the rough material-18 microns, wire pull broaching speed-82.5 m/min.
4 Conclusion 1. The following factors affecting the roughness of the herringbone pattern of the disk after electrical discharge machining are considered to be the most crucial ones. They are the current strength, the space between the electrode and the rough material, the wire pull broaching speed; 2. An industrial experiment with a simplex-lattice design resulted in a mathematical relationship describing the impact of the current force, the space between the
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electrode and the rough material, the wire pull-broaching speed on the roughness of the disc herringbone pattern after electrical discharge machining; 3. Solving the obtained relationship resulted in obtaining the parameters of the mode of electrical discharge machining of the disc herringbone pattern. These parametres ensured the maximum machining and allowed for achieving the value of the roughness parameter Ra = 1.5 μm: the current parameter (current) - 9 A, the space between the electrode and the rough material - 18 microns, wire pull broaching speed - 82.5 m/min.
References 1. Fawal S, Kodal A (2021) Overall and component basis performance evaluations for turbojet engines under various optimal operating conditions. Aerosp Sci Technol 117(2021):1–14. https://doi.org/10.1016/j.ast.2021.106943 2. Waligórski M, Batura K, Kucal K, Merkisz J (2020) Empirical assessment of thermodynamic processes of a turbojet engine in the process values field using vibration parameters. Measurement 158:107702. https://doi.org/10.1016/J.MEASUREMENT.2020.107702 3. Jones J (2022) Thermo-mechanical fatigue–in the gas turbine engine. Encyclopedia Mater Metals Allloys 476–484. https://doi.org/10.1016/B978-0-12-819726-4.00112-5 4. Zhu Sh-P, Liu Q, Lei Q et al. (2018) Probabilistic fatigue life prediction and reliability assessment of a high-pressure turbine disc considering load variations. Int J Damage Mech 27(10):1569–1588. https://doi.org/10.1177/1056789517737132 5. Ikpe AE, Owunna I, Ebunilo PO et al (2016) Material selection for high pressure (HP) turbine blade of conventional turbojet engines. Am J Mech Ind Eng 1(1):1–9. https://doi.org/10.11648/ j.ajmie.20160101.11 6. Aspinwall DK, Soo SL, Berrisford AE, Walder G (2008) Workpiece surface roughness and integrity after WEDM of Ti-6Al-4V and Inconel 718 using minimum damage generator technology. CIRP Ann Manuf Technol 57(1):187–190. https://doi.org/10.1016/j.cirp.2008. 03.054 7. Ayesta I, Izquierdo B, Flaño O, Sánchez JA, Albizuri J, Avilés R (2016) Influence of the WEDM process on the fatigue behavior of Inconel® 718. Int J Fatigue 92:220–233. https://doi.org/10. 1016/j.ijfatigue.2016.07.011 8. Naveen Babu K, Karthikeyan R, Punitha A (2019) An integrated ANN–PSO approach to optimize the material removal rate and surface roughness of wire cut EDM on INCONEL 750. Mater Today Proc 19:501–505. https://doi.org/10.1016/j.matpr.2019.07.643 9. Varol Ozkavak H, Sofu MM, Duman B, Bacak S (2021) Estimating surface roughness for different EDM processing parameters on Inconel 718 using GEP and ANN. CIRP J Manuf Sci Technol 33:306–314. https://doi.org/10.1016/j.cirpj.2021.04.007 10. Kneubühler F, Wiessner M, Wegener K (2020) Analysis of WEDM process with respect to wire wear and wire consumption. Procedia CIRP 95:313–318. https://doi.org/10.1016/j.procir. 2020.03.151 11. Gowthaman PS, Jeyakumar S (2019) A review on machining of high temperature aeronautics superalloys using WEDM. Mater Today Proc 18:4782–4791. https://doi.org/10.1016/j.matpr. 2019.07.466 12. Pavan C, Sateesh N, Subbiah R (2021) Taguchi analysis on machinability of Inconel 600 using Copper, Brass, and Copper tungsten electrodes in EDM. Mater Today Proc 46(2021):9281– 9286. https://doi.org/10.1016/j.matpr.2020.02.113 13. Maurya R, Porwal RK, Kumar V (2019) Experimental investigation & modelling of wire EDM process during machining of Nicrofer 5716. Mater Today Proc 26:1184–1190. https://doi.org/ 10.1016/j.matpr.2020.02.239
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14. Satyanarayana K, Mounika M, Kiran KR (2021) Optimization of machining parameters in wire cut electrical discharge machining Inconel 600 using untreated brass wire. Mater Today Proc 44:2411–2415. https://doi.org/10.1016/j.matpr.2020.12.463 15. Satyanarayana K, Mounika M, Raj Kiran K (2021) Experimental studies and optimization of WEDM process in machining of Inconel 600 using zinc wire. Mater Today Proc 44:2431–2434. https://doi.org/10.1016/j.matpr.2020.12.475
Modelling of Heating Process of the High-Pressure Fuel Pipeline of the Fuel Equipment of Diesel Locomotives Sergei Ovcharenko , Oleg Balagin , and Dmitrii Balagin
Abstract Mathematical model of heating process of fuel pipeline of high pressure of fuel equipment of diesel engines is presented. Temperature of its outer surface is calculated at different values of ambient air temperature and technical condition of fuel equipment. The simulation did not take into account the elastic fluctuations in the injection fuel line, and the pressure along the entire high pressure line during the process is assumed to be the same and changing only in time. Diagnostic parameter is proposed for evaluation of fuel equipment operability of diesel locomotives. A software package has been developed that allows you to quickly process the results of thermography with the formation of a conclusion on the technical condition of the object. Temperature values on the external surface of high-pressure fuel pipelines are presented depending on the technical state of the fuel equipment and ambient air temperature and a number of critical values, at which further operation of the diesel locomotive leads to a deterioration of its power, economic and environmental characteristics, to a possible failure in the path and to the necessary unplanned repair of the locomotive. The reliability of the simulation results was confirmed by a series of experiments in the diesel locomotive workshop of the Moskovka service locomotive depot. The comparison of the results of thermograms and the results of theoretical studies confirmed the sufficient accuracy of the developed mathematical model. The presented discrepancy of experimental and theoretical data does not exceed 4%. Keywords Diesel · Heat transfer coefficients · Mathematical model · Fuel equipment
1 Introduction The effective operation of diesel locomotives mostly depends on the reliability and efficiency of fuel equipment (FE). The number of failures of diesel locomotives in the Russian railroad network due to diesel failure runs to 41% of the total number S. Ovcharenko · O. Balagin · D. Balagin (B) Omsk State Transport University, Prospekt Marksa, 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_26
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of failures of the main units of diesel locomotives [1], including 12–15% of the total number of diesel locomotive failures due to the failure of the FE. It is possible to reduce the number of failures while operating diesel engine FE by the implementation of methods of non-disassembly and non-contact diagnostics for early failure detection [2–4]. The development of the methodology to monitor the performance of fuel equipment of diesel locomotives is an important component of technical measures aimed at improving the efficiency of diesel locomotive operation.
2 Research Objectives The research objective was to develop scientific approaches to assess the process of heat transfer from the surface of the high-pressure fuel pipeline of diesel engine FE that allows to determine the performance of fuel equipment (high-pressure fuel pump (HPFP), injector) by the temperature of the outer surface of high-pressure fuel pipelines, taking into account the ambient air temperature. The works [5–15] and a number of papers of other researchers study the efficiency of diesel locomotive FE in operation. The present work demonstrates the results of calculation of the outer surface temperature of high-pressure fuel pipelines in the initial and operational states, and suggests a diagnostic parameter to evaluate the performance of FE of diesel locomotives. The obtained results continue the previously performed studies [3, 6].
3 Mathematical Model Development To develop a mathematical model of the heating process of the high-pressure fuel pipeline of FE of a diesel engine, the computational scheme of direct-acting fuel system with a mechanical drive and a pressure pipe is proposed (see Fig. 1) [6]. At the first stage of the modelling the calculation of the injection process has been done to determine the characteristics of the change in fuel pressure per cycle for different technical condition of the fuel equipment (high pressure fuel pump (HPFP), injector). Changing the condition of the flow process in the inlet and outlet sections of the injection valve and injector needle, as well as the plunger closing and opening the suction and cut-off windows of the sleeve makes it necessary to divide the flow process into stages, the number of which is determined by the design of the «HPFPpipe-injector» system and the size ratio between its elements. The initial equation to calculate the balance of fuel flow rate is the following equation
Modelling of Heating Process of the High-Pressure Fuel …
273
Fig. 1 Computational scheme of the fuel system
(l) Z (l) 2 ja − jgo f pl p +Z n t − tgo − dp = dt. (1) υgo + jgo t − t go + βV 2t g fn where f pl —cross-sectional area of the plunger, m2 ; β—fuel compression coefficient, m2 /H; V —capacity of high-pressure fuel system, m3 ; υ go —velocity corresponding to the geometric beginning of the feed, i.e. time t gs , m/s; jgo —acceleration at the beginning of the geometric fuel supply; t—current time value, s; t go —geometric duration of fuel supply, s; ja —acceleration at the end of the geometric fuel supply with duration t g ; (l) 3 Z (l) p , Z n —fuel leakage through HPFP and the injector, respectively, m /s. The modelling does not take into account elastic vibrations in the injection fuel line, and the pressure along the entire high-pressure line during the process is considered to be the same and it varies only in time. Based on the equation used to determine the continuity of the flow rate through the injector needle seating cone and through the nozzles [3].
μne f ne
2 pn − pn = μnh f nh ρ
2 pn − pdcc , ρ
the basic equation of the fuel injection process is obtained:
(2)
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S. Ovcharenko et al.
dp f n υ = βV + μnh f nh dt
2 2 kne pυ 2 (l) + (Z (l) p − C − p n dcc p + Z n ), (3) 2 +1 ρ kne 2
where μne f ne —effective flow section under the injector needle; μnh f nh —effective section of the injector nozzles; pn —fuel pressure in the injector chamber, Pa; pn —pressure before the injector nozzles, Pa; pdcc —average pressure in the diesel combustion chamber during fuel injection, Pa; ρ—fuel density, kg/m3 . υ—fuel feed rate, i.e. corresponding to the time t m/s; k ne —proportion of effective flow section under the injector needle to the effective section of the injector nozzles; C—coefficient of change in the diameter of nozzles. Figure 2 presents an example of the dependence of the calculated fuel pressure in the fuel line of the diesel engine 1-PD4D on the crankshaft rotation angle ϕ, obtained from the results of the fuel supply process modelling. To determine the fuel flow rate Q through each element of the system, the high-pressure fuel system is looked upon as consisting of three node objects: HPFP, the pressure pipe and the injector (see Fig. 3) [10, 13–15]. As a result the basic equation of the fuel flow rate is obtained: 2 Pp − Pc Q=
ρ (μf1 )2 + 1 2 + v (μ f pl )
.
(4)
1 (μf n )2
where Rp —fuel pressure in the overplunger space of HPFP, Pa; Pc —gas pressure in the diesel cylinder, Pa; μf v , μf pl , μf n —effective flow section of the injection valve of HPFP, the pressure pipe and the injector. Fig. 2 Fuel pressure in the injection fuel line in diesel 1-PD4D
Modelling of Heating Process of the High-Pressure Fuel …
μfрl
μfn
PRESSURE PIPE
INJECTOR
μfv
HPFP
275
Рc
Pp(φ)
hpl(φ)
gсf Qpl
Qp
Qn
Fig. 3 Fuel system scheme of the high-pressure diesel engine
The modelling of the characteristic faults were carried by setting different values: cross-sectional area of the plunger (fpl); injection valve cross-sectional area by discharge belt (fv); flow section under the cone of the injector needle (fn1); total flow area of the injector nozzles (fn2); flow coefficient of the flow area under the valve cone (μv); flow coefficient of the flow area under the needle cone (μe); flow coefficient of the injector nozzles (μn). At the second stage of the research, the modelling results made it possible to introduce a parameter to assess the technical condition of fuel equipment of diesel locomotives. It is the temperature of the outer surface of high-pressure fuel pipelines, o C: ( f p) tes = tf −
Q f · Rλ , F
(5)
where t f —fuel temperature in the high-pressure pipeline (after the compression in the overplunger space), °K; Qf —quantity of the heat transferred from the fuel to the air, W; Rλ —thermal resistance of the wall, m2 · K/W; F—outer surface area of the fuel pipeline, m2 . To automate and improve the efficiency of calculations, a software package has been developed that allows processing the results of thermography obtained from infrared receivers of different manufacturers (TESTO, FLIR, FLUKE, IRTIS-2000 ME). As a result values of temperature on the outer surface of high pressure fuel pipelines depending on technical condition of fuel equipment and ambient air temper( f p) ature (from 0 to 30 °C) and a number of critical values tes , at which further operation of a locomotive diesel engine leads to deterioration of its performance, economic and environmental characteristics and possible failure on the way as well as to necessary emergency repair of a diesel locomotive, have been obtained. The results of the modelling are presented in Table 1.
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Table 1 The results of the modelling of outer surface temperature of the high-pressure fuel pipeline Ambient air temperature, °C, t sur
Outer surface temperature of the fuel pipeline, °C tc
25
j(fs)
51.6
tc
j(p)
45.9
tc
=
j ( f s)
tc
j ( p) −tc j( f s)
tc
,%
=
j ( f s)
tc
j (n) −tc j( f s)
tc
,%
j(n)
47.1
11.0
8.7
26
52.7
47.1
48.8
10.6
7.4
27
53.9
47.8
49.8
11.3
7.6
28
55.2
48.9
52.0
11.4
5.8
29
56.9
51.0
52.6
10.4
7.6
30
58.1
51.9
54.3
10.7
6.5
In Table 1 tcj(fs) is the calculated normative value of the surface temperature of the pipeline of fault-free fuel system at j temperature; tcj(p) is the calculated value of the surface temperature of the fuel system pipeline with faulty HPFP at j temperature; tcj(n) is the calculated value of the surface temperature of the fuel system pipeline with the faulty injector at j temperature. The modelling has resulted in the critical values of fuel system pipeline temperature deviation. It makes 5% with the faulty injector (with the minimum deviation of 5.8%, see Table 1), and 10% with the faulty HPFP (with the minimum deviation of 10.4%, see Table 1). To verify the reliability of the modelling results, a number of experiments have been carried out. The comparison of the results of thermogram processing (Fig. 4) and the results of theoretical studies confirms the sufficient accuracy of the developed mathematical model [7]. The discrepancy between the experimental and theoretical data does not exceed 4% Table 2). cylinder 3
+36.3 +36.2
+36.6
+33,3
+33.4
a
cylinder 2
cylinder
1
b
Fig. 4 Pressure pipes of cylinders 1–3 of diesel locomotive engine SLET18DM-747: a thermogram; b photo, a thermogram; b photo
36.5
36.2
37.1
36.1
38.1
3
4
5
6
37.5
1.6
3.7
1.1
3.5
2.7
3.7
37.6
36.5
36.8
31.1*
36.5
36.2
Note * − faulty HPFP of cylinder 3; ** − faulty injector of cylinder 1
36.1
2
37.5
37.5
37.5
30.5
37.5
37.5
Calculated value
0.3
2.7
1.9
2.0
2.7
3.5
Miscalculation , %
Experimental value
Experimental value
Miscalculation , %
Faulty HPFP (the plunger pair wear)
FE fault-free
Calculated value
Experiment №2
Experiment №1
1
№
Cylinder
Temperature of the pressure pipe of diesel engine 1-PD4D of diesel locomotive SLET18DM-747, t sur = 4 ºC
Table 2 Comparative analysis of modelling and thermography results
36.1
37.1
37.2
36.3
36.5
33.4**
Experimental value
37.5
37.5
37.5
37.5
37.5
32.5
Calculated value
3.7
1.1
0.8
3.2
2.7
2.8
Miscalculation , %
Faulty injector (leakage of the locking cone of the injector)
Experiment №3
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4 Conclusions As a result of the theoretical research: – a diagnostic parameter to control the technical condition of fuel equipment of locomotive diesels has been proposed, namely, the temperature of the outer surface of high-pressure fuel pipelines. – a number of boundary values of high-pressure fuel pipelines outer surface temperature, at which further operation of a locomotive diesel engine leads to deterioration of its performance, economic and environmental characteristics and possible failure on the way as well as to necessary emergency repair of a diesel locomotive, have been determined.
References 1. Ovcharenko S, Balagin O, Balagin D (2018) Integrated system of non-contact thermal control of the units of self-contained locomotives. In: MATEC Web of Conferences, vol 239, p 01002. https://doi.org/10.1051/matecconf/201823901002 2. Choi SW et al (2014) The effects of cooling rate and heat treatment on mechanical and thermal characteristics of Al-Si-Cu-Mg foundry alloys. J Alloy Compd 617:654–659. https://doi.org/ 10.1016/j.jallcom.2014.08.033 3. Ovcharenko S, Balagin O, Balagin D (2020). Modeling of heat exchange processes in the locomotive cooling system. In: Popovic Z, Manakov A, Breskich V (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. AISC, vol 1115, pp 463–472. Springer, Cham. https://doi.org/10.1007/978-3-030-37916-2_45 4. Barnes A (2014) Increased locomotive performance using condition based maintenance. PCMSEng UK, Unit 3A, Adwick Park, Manvers, Rotherham, United Kingdom. https://doi. org/10.1049/cp.2014.1011 5. Sumtsov A (2018) Thermal imaging diagnostics locomotives, Ukrainian State University of railway transport. In: MATEC Web of Conferences, vol 182, no 10, p 01004. https://doi.org/ 10.1051/matecconf/201818201004 6. Ovcharenko S, Balagin O, Balagin D (2017) Cooling system operation efficiency of locomotive diesel engine. In: IOP Conference Series: Earth and Environmental Science, vol 90, p 012011. https://doi.org/10.1088/1755-1315/90/1/012011 7. Johnson JE (2012) Characteristics of 3000 bar Diesel spray injection under non-vaporizing and vaporizing conditions. In: ICLASS 2012, 12th Triennial International Conference on Liquid Atomization and Spray Systems, Heidelberg, Germany, 2–6 September 2012 8. Tung S, Witherspoon SR, Roe LA, Silano A, Maynard DP, Ferraro N (2008) A MEMS-based flexible sensor and actuator system for space inflatable structures. https://doi.org/10.1088/09641726/10/6/312 9. Gubarev PV, Glazunov DV, Shapshal AS (2021) Refined collector thermal design for electric locomo-tive traction engine. In: Proceedings of the 6th International Conference on Industrial Engineering. https://doi.org/10.1007/978-3-030-54814-8_40 10. Wang JR, Min JC, Song YZ (2006) Forced convective cooling of a high power solid-state laser slab. Appl Therm Eng 26(5–6):549–558 11. Glock S et al (2009) Optical classification for quality and defect analysis of train brakes. In: SPIE Europe Optical Metrology. https://doi.org/10.1117/12.827457 12. Dec JE, Espey C (1998) Chemiluminescence imaging of autoignition in a DI diesel engine. In: SAE. https://doi.org/10.4271/982685
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13. Jakob M, Hülser T, Janssen A (2012) Simultaneous high-speed visualization of soot luminosity and OH chemiluminescence of alternative-fuel combustion in a HSDI diesel engine under realistic operating conditions. Combust Flame 159(7):2516–2529 14. Srna A, von Rotz B, Herrmann K, Boulouchos K (2019) Experimental investigation of pilot-fuel combustion in dual-fuel engines, part 1: thermodynamic analysis of combustion phenomena. Fuel 255:115642 15. Augusta R, Foster DE, Ghandhi JB, Eng J (2006) Chemiluminescence measurements of homogeneous charge compression ignition HCCI combustion SAE. https://doi.org/10.4271/200601-1520
Improvement Metrological Support of the Technological Process of Repair of the Auto-Couple Device of the Railway Carriage Dmitry Belan
and Lyubov Kofanova
Abstract The purpose of the article is to improve the existing technological process of auto-coupling equipment repair due to the developed system for monitoring malfunctions of the auto-coupling device of non-traction units of rolling stock and the use of the designed special tool “Template 8kl-5299” to control the lock of the autocoupling de-vice. As a result of the study of the technological process of repairing automatic coupling equipment, special attention was paid to statistical methods for monitoring and accounting for the presence of automatic coupling device malfunctions, as well as a new system for monitoring and accounting for the presence and malfunctions of automatic coupling devices and the development of new measuring devices for the operation of monitoring parts of the coupling mechanism of the automatic coupling device, as well as the design of the body of the automatic coupler, its possible defects during operation and the analysis of the existing technological process for repairing the lock of the closing part of the body of the automatic coupler. The statistics on the most common defects are given. The analysis of existing methods of restoration, the body of the automatic coupler was carried out, the most effective one was identified. To improve the quality of repair and reliability of rolling stock units, repair of locomotives and cars is of great importance. Therefore, it is planned to introduce new technological processes for restoration of parts and assembly units of cars at car repair enterprises. Keywords Depot · Automatic coupler · Repair process · Instrumentation · Automatic coupler body · Lock
1 Introduction Railway transport is one of the leading sectors of our country’s economy. Reliability of the rolling stock depends on the quality of its repair. Recently, the rolling stock hasn’t been fully updated. The demand for rolling stock is constantly growing due D. Belan (B) · L. Kofanova Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_27
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to increase in traffic flows. Therefore, repair companies of railway transport are entrusted to improve the technological process and increase repairs as well as their quality. According to “GOST 22,703-2012 Cast parts of coupling and automatic coupling devices of railway rolling stock. General technical conditions”, automatic coupling SA-3 (Fig. 1) is used for coupling units of rolling stock, as well as the transmission of traction and shock loads. The automatic coupling device of the car consists of five components: • • • • •
body and mechanism located in it; release drive; shock-centering device; harness device with absorbing apparatus; supporting parts.
When the couplers are coupled and are in operation, it is almost impossible to check all the dimensions which determine the reliability of the automatic coupling device. Therefore, during inspections on trains, only a general assessment of the
Fig. 1 Automatic coupling SA – 3
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operability and condition of the device as a whole is given. Methods of such inspection, developed by employees of a number of roads, are used at mass loading and unloading stations at marshalling and divisional yards. The SA-3 automatic coupling is a non-rigid traction-shock type. It consists of a body and parts of a clutch mechanism: lock, lock holder, fuse, lift, lift roller. The auto-coupler device refers to the shock-traction equipment of the car and is designed to couple the cars between themselves and the locomotive, keep them at a certain distance from each other, perceive, transfer and mitigate the effects of tensile and compressive forces arising during movement. Train traffic safety largely depends on the proper functioning of this equipment [1, 2]. The automatic coupling device of the rolling stock must be in good working order at all times. In order to timely detect and eliminate the malfunctions that have arisen, in addition to checking the device on trains, an external inspection was established without removing units and parts from the rolling stock and a complete inspection with removing removable components and parts from the rolling stock. To check the operability of the device as a whole as well as the interaction of its components and parts without specific assessment of the condition of each part, there is an external inspection of the automatic coupler device during the current uncoupling repair of cars, a unified technical revision of passenger cars, washing repair of steam locomotives, current repair of TR-1 diesel locomotives, electric locomotives and cars of electric and diesel trains [3]. A complete inspection of the automatic coupling device is carried out during major and depot repairs of cars, major repairs of locomotives and electric train cars, ongoing repairs of TR-2, TR-3 diesel locomotives, electric locomotives, electric train cars and diesel trains [3]. Before an external inspection, the auto-coupler is cleaned of dirt or snow to detect cracks on the parts or their bends and to check the conformity of components and parts with the standards established for this type of inspection. The mechanism and the state of the automatic coupling are checked with template 940p. Automatic coupling SA-3 provides: • automatic coupling in case of collision of rolling stock units with different maneuvering speeds; • automatic locking of the lock in the lower position at the coupled auto couplings, which eliminates spontaneous uncoupling on the train (self-release); • uncoupling of the rolling stock without a person entering between the end beams and holding the mechanism in the uncoupled position until the automatic couplings are separated; • automatic return of the mechanism to the ready-to-clutch position after the automatic couplings are separated; • restoration of the clutch at mistakenly uncoupled auto couplings without their dilution; • maneuvering work by thrusts (work “on the buffer”), when the auto-couplers do not interlock when they collide [4].
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JSC "RZD" Passenger Depot Form for recording malfunctions of automatic couplers Automatic coupler number
Date of receipt
Type
Parts to be checked
Numbers of templates
Coupler body
893p
Lock (before repair) Lock (after repair) Lock holder Fuse Lock lifter Lock lifter pin < >> 2021
Place of last repair
Manufacturer
Malfunctions
Type of repair required
Subject to/ not subject to repair
8kl-5299 841p 800r-1 847p 919p Signature______________________ (persons in charge of repair and inspection)
Fig. 2 Form for recording malfunctions of automatic couplers
2 Materials and Methods When considering the organizational and production structure of the depot LVChD1 Omsk, it became known that the enterprise does not have a form for recording malfunctions of automatic couplers. To improve service quality and simplify records management of malfunctions and defects of automatic coupling devices, a form for automatic coupling equipment was developed. It is presented in Fig. 2. According to the new form for recording malfunctions, the automatic coupler is registered by filling out the corresponding form columns, which indicate the date of receipt, the number of the automatic coupler, the manufacturer, and the place of the last repair. Each part of the automatic coupler is checked by the templates indicated in the form for malfunction [2, 3, 5]. Next, the locksmith determines whether the part is subject to repair, if it is, then malfunction is recorded in the appropriate column.
3 Results The main task of any control system is to identify defects and determine the limits of strength and reliability. Defects may arise as a result of errors in design, production
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or operation: casting defects, fatigue failure, atmospheric corrosion, wear of mated parts, defects in coating, defects in permanent metal joints. In each specific case, special techniques are used to determine the degree of influence of the defect on the quality of the product: how much reliability and performance characteristics will decrease, how the terms and conditions of operation will change, and whether the defect is critical and the item cannot be allowed to use. There are two main groups of tests: destructive and non-destructive testing [4, 6–8]. Based on the developed form for recording malfunctions of the automatic coupling device, various templates for checking the details of the automatic coupler equipment were analyzed. Template No. 800R-1 is used to check the lock fuse (Fig. 3). Template No. 841P is used to check the thickness of the automatic coupling lock holder (Fig. 4). Template No. 847P is used to check the lock lifter (Fig. 5).
Fig. 3 Template No. 800R-1
Fig. 4 Template No. 841P
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Fig. 5 Template No. 847P
Fig. 6 Template No. 852P
Template No. 852P is used to check the thickness of the lock and its closing part after repair (Fig. 6). Template No. 893P is used to check the length of the small tooth of the body and the distance between the impact wall of the throat and the traction surface of the large tooth during depot repair of the car (Fig. 7). Template No. 919P is used to check the lock lifter pin (Fig. 8). The specially designed tool template 8kl-5299 (Fig. 9) is a constructive combination of two templates 852p and 899p.
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Fig. 7 Template No. 893P
Fig. 8 Template No. 919P
Fig. 9 Template 8kl-5299
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Fig. 10 Template 8kl-5299
The thickness of the closing part of the lock along its entire height is checked before repair with a non-passable template 8kl-5299; The lock is qualified as serviceable after repair if its closing part does not fit into cut-out b of template 8kl-5299 and unserviceable if it fits into cut-out b of template 8kl-5299 (Fig. 10). The lock is checked with templates in accordance with Instruction No. CVVNIIZhT-494-97 [9]. At the same time, they check: • pass-through cut-out with template 8kl-5299; The lock is qualified as serviceable if it freely passes through the cut-out a of this template. Thus, the specially designed tool template 8kl-5299 allows to reduce the time for transportation and change of measuring instruments for monitoring automatic coupler CA-3.
4 Conclusions In this work, we improved the technological process of auto-coupling device repair, namely, we designed a system for monitoring malfunctions of the auto-coupling device of passenger cars, which made it possible to increase the quality of inspection, repair and control of the auto-coupling [10–15]. Also, we designed a special tool “Template 8kl-5299” to control the lock of the auto-coupling device.
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References 1. Kudryashov E, Stetsurin A (2008) More efficient repair of machine parts by a group method. Russ Eng Res 28(9):924–925. https://doi.org/10.3103/S1068798X08090232 2. Kheder M, Trigui M, Aifaoui N (2017) Optimization of disassembly sequence planning for preventive maintenance. Adv Manuf Technol 90(5–8):1337–1349 3. Datsun Y (2016) Determination of the degree of influence of repair processes on serviceability of units of the traction rolling stock East. Eur J Enterp Technol 7(79):56–61 4. Krasheninin OS, Klymenko OV, Ponomarenko OV (2016) Forecasting of performance evaluation of new vehicles. Sci Transp Progress Bull Dnipropetrovsk Natl Univ Railw Transp 66(6):78. https://doi.org/10.15802/stp2016/90478 5. Balyakin AV, Vdovin RA, Ispravnikova SS (2020) Application of additive technologies for manufacturing turbine stator parts in aircraft engines. J Phys Conf Ser 1515:042108. https:// doi.org/10.1088/1742-6596/1515/4/042108 6. Davydov YA, Plyaskin AK (2013) Comprehensive studies of elements of automatic coupling devices of locomotives. Transp Asia-Pac Reg 1:32–39 7. Gulyaev AV, Kozlov DP, Keino MY, Plyaskin AK (2012) Measuring complex for monitoring the operating modes of automatic couplers of an electric locomotive. Bulletin of the Institute of Traction and Rolling Stock. Paper presented at the scientific-practical conference of scientists of transport universities, engineering workers and representatives of academic science “Science of the university–innovations in production”, Stetsyuk AS and Gamolly YA (eds). Publishing House of the Far East State University of Transportation, Khabarovsk, pp 66–69 8. Kravchuk VV, Plyaskin AK, Keino MY (2012) Fundamentals of electric transport production technology. Publishing House of the Far East State University of Transportation, p 244 9. Kobishchanov VV, Antipin DY, Rasin DY, Manueva MV (2020) Methods development of strength and reliability analysis of rolling-stock bearing structure using mathematical modeling methods. Bull Bryansk State Tech Univ 88(3):29–37. https://doi.org/10.30987/1999-87752020-3-29-37 10. Krasheninin OS (2015) The effect of locomotive hours on adjusting periodicity of maintenance service and current repair. Sci Transp Progress Bull Dnipropetrovsk Natl Univ Railw Transp 55(1):148–154. https://doi.org/10.15802/stp2015/38265 11. Zhu C, He J, Peng J et al (2019) Failure mechanism analysis on railway wheel shaft of power locomotive. Eng Fail Anal 104:25–38. https://doi.org/10.1016/j.engfailanal.2019.05.013 12. Leite M, Infante V, Andrade AR (2021) Using expert judgement techniques to assess reliability for long service-life components: an application to railway wheelsets. Proc Inst Mech Eng Part O J Risk Reliab 1748006X2110346. https://doi.org/10.1177/1748006x211034650 13. Ponomarenko OV (2017) Prospects for improving the technical condition of rolling stock on the railways of Ukraine. Sci Transp Progress Bull Dnepropetrovsk Natl Univ Railw Transp 67(1):88. https://doi.org/10.15802/stp2017/93162 14. Oganyan ES, Kossov VS, Ovechnikov MN et al (2020) The modeling burden and resource of an automatic coupler body by techniques of numerical analysis. J Mach Manuf Reliab 49:408–411. https://doi.org/10.3103/S105261882005009X 15. Xiu R, Spiryagin S, Wu Q et al (2020) Fatigue life assessment methods for railway vehicle bogie frames. Eng Fail Anal 116:104725. https://doi.org/10.1016/j.engfailanal.2020.104725
Influence of Freight Locomotive Modernization by Increasing of Diesel Generator Set Power on the Mechanical Strength of Traction Drive Oleg Pudovikov , Eugeny Rybnikov , Elena Loginova , Tatiana Vakhromeeva , and Sergey Volodin Abstract There is considered the not common type of diesel-locomotive modernization: the influence on gear transmission strength of traction effort torque that arises in traction motor after modernization of diesel locomotive with diesel-generator set of increased power for drawing freight trains of higher weight. In case of slippage there will appear moments of rotating resistance in the mechanical part of traction drive that will cause driving gear bending and corresponding uneven loading of axle-motor bearings and their wear. The impact of moments after re-adhesion on the elements of mechanical part of modernized diesel locomotive traction drive was carried out by the method of mathematical 3D-modeling with the help of finite-element analysis. The calculations proved the one-side localization of the greatest stress on gear teeth, so the corresponding uneven teeth load may cause fatigue crack. Research led on 3D-model made it clear the flexibility of mechanical system of locomotive tractive drive. Bending of driving gear and traction motor shaft arised due to adhesion may cause uneven redistribution of stress along the axial motor bearings, so one of the bearings on the gear side will be overloaded. Keywords Mechanical part of traction drive · Traction motor shaft · Traction gearbox · Driving gear · Traction effort torque · Moment of resistance · Re-Adhesion · Finite-element analysis of locomotive traction drive
1 Introduction There appears logical decision to modernize the existing locomotive fleet [1, 2] in order to increase railway freight traffic in the absence of possibility and practicability of new modern locomotives acquiring [3]. The purpose of this study is to consider the effect of power increasing of diesel generator set installed on serial diesel locomotive without replacing of traction electrical equipment on safety margin of traction drive and traction motor shaft. The O. Pudovikov (B) · E. Rybnikov · E. Loginova · T. Vakhromeeva · S. Volodin Russian University of Transport (RUT (MIIT)), Obraztsova Street, 9b9, 127994 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_28
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increase of diesel-generator set power leads to enhancement of diesel locomotive tractive effort that permits to improve the carrying capacity due to increasing tonnage rating. Computational studies were carried out relating on diesel locomotive 2TE116. There was assumed that experimental diesel locomotive is equipped by dieselgenerator set with power 15% higher than that on the serial diesel locomotive 2TE116. The loads in traction drive were calculated during the movement of the serial and experimental diesel locomotives with full use of power and trains with maximum calculated weights on the section with specific gradient ip = +9‰ (according to the methodology for classifying railway lines of Russian Railways). There were calculated the maximum weights of trains for specific speed Vp = 24.5 km/h of 2TE116 diesel locomotive as: Q = 3500 tones for the serial diesel locomotive and Q = 4500 tones for the experimental diesel locomotive according to the Rules of traction calculation for train operation.
2 Materials and Methods The increase of traction force of experimental diesel locomotive in the entire range of speeds and maximum calculated weight of freight train is accompanied by augmentation of traction moments and moments of resistance forced on the elements of mechanical part of traction drive during the operation of diesel locomotive on adhesion curve. The traction moment as load arisen in traction drive is determined: MT D =
FK · D K . 2·k·u·η
(1)
FK —traction effort, N; D K = 1.050 m—wheel diameter; u = 4.4—ear reduction rate; k = 12—the number of locomotive driving axles; η = 0.97—fficiency of traction drive. According to calculations fulfilled the moment realized by traction drive of experimental diesel locomotive is: • 7900 Nm at the moment of locomotive start; • 5667 Nm for the continuous tractive effort 570 kN.
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Table 1 Parameters of traction drive manufacturing materials Part of traction drive
Manufacturing material
Yield stress σT , MPa
Stress limit σ B , MPa
Traction drive shaft
Steel 20KhN3A GOST 4543-71
685
835
Pinion
Steel 20Kh2N3A GOST 4543-71
830
1080
Gear
Steel 45 KhN GOST 4543-71
640
785
The moments realized by traction drive of the serial diesel locomotive are the following: • 7540 Nm at the moment of locomotive start; • 4673 Nm for the continuous tractive effort 469 kN that is 20% lower than the moment occurred on the traction motor shaft of the experimental diesel locomotive. The solid model of traction drive consists of traction electric motor armature and driving gear. The nature and consequences of increased loads impact on the mechanical part of traction drive were assessed using the built finite element model. The physical and mechanical properties of traction drive units which strength was studied were determined by the characteristics of the manufacturing material (Table 1). The following boundary conditions were set in the model: armature of electric motor rests and rotates in armature bearings-this condition is satisfied by setting boundary conditions on the corresponding surfaces of the armature shaft; gear is pressed on wheelset axle. It was decided not to include the wheelset itself in the model, but to replace it by boundary conditions on the corresponding surfaces of the model-displacement constraints were set on the inner part of the gear hub. In this statement of problem the model considers the traction drive operation as quasi-static, i.e. supposed resistance overcoming of motionless gear and transferring of traction moment on it at each time moment. Modeling of gearing was carried out on the assumption of ideal conditions of uniform contact along the entire length of gear teeth. When the maximum traction effort torque 7900 Nm is applied to the traction motor shaft at the moment when the experimental locomotive starts, a characteristic feature of one-way transmission appears-irregular loading of teeth along the length. In this case the greatest stress arises in the tooth close to the traction motor. In case of stable wheel-rail adhesion of experimental diesel locomotive there arises stress 247 Nm in driving gear that is 3 times less than the yield stress of the gear manufacturing material (Table 1).
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One of the most severe conditions for locomotive traction drive is the restoration of wheel-rail adhesion after slippage [4, 5]. Taking into account the variability of the adhesion coefficient and the increased weight of freight trains drawn by the experimental diesel locomotive, it can be assumed that the experimental diesel locomotive is set to slippage. At the moment of re-adhesion the traction electric motor of the experimental diesel locomotive experiences an instant increase of rotating resistance, equal to the mass of unsprung parts of traction drive: wheelset, traction electric motor and gearbox, which is about 5 tons in case of support-axial suspension of traction drive. The moment of rotating resistance in this case is defined as: MR = F ·
DK , 2
(2)
F is the force that causes rotating resistance of the traction motor, it is equal to the weight of unsprung parts. The traction calculations showed that when drawing a freight train of average mass by experimental diesel locomotive there occur the traction moment 4000 Nm in traction motor. For this value of tractive moment there was evaluated the influence of loss of adhesion on the strength of the mechanical part of traction drive.
3 Results As the result of calculations there was distinguished that the stress would be 1329 MPa in the gear tooth, which is 2 times higher than the yield stress and 1.7 times higher than the stress limit of the gear manufacturing material (Fig. 1) (Table 1). There could appear stress even higher after re-adhesion in the mechanical part of traction drive. In this case besides the specified moment of resistance (2) there will be additional resistance moment that occurs after re-adhesion from the mass of traction drive units. For further calculations there was taken the smaller value of the adhesion coefficient –0.2 that corresponds to the condition without adhesion. Similarly to the previous calculation, the effect of the increased moment of resistance on the gear strength after re-adhesion was evaluated for an average tractive effort moment 4000 Nm that occurs if experimental diesel locomotive draws freight trains of increased mass. In the case of greater moment of resistance occurred after re-adhesion there increases stress in the base of gear tooth and gear rim up to the value 1346 MPa that is over stress limit (Table 1) (Fig. 2).
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Fig. 1 The stress distribution of the loaded gear tooth
The localization of the greatest stress (Fig. 2) indicates that there is edge contact between teeth gears and it occurs at the moment of premature contact of the pinion tooth point with the gear root. This causes an additional dynamic load. At the same time, in the middle of the tooth there is stress that exceeds the yield stress and particularly equal to the strength stress of the gear manufacturing material (Table 1). That means if there would be some certain conditions and due to the gap between teeth of worn gears a median impact may occur. Gearing with such impact causes varying load in teeth. For a certain number of cycles in the aria of maximum local stress on the tensile side, a fatigue crack and tooth breaking may occur [6–8]. After re-adhesion there is moment of rotating resistance that causes torsion load of the wheelset which leads to driving gear bending [9] (Fig. 3). Such bending of driving gear and traction motor shaft may cause uneven redistribution of stress along the axial motor bearings [10], so one of the bearings on the gear side will be overloaded.
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Fig. 2 Stresses in gear rim if increased moment of resistance during slippage applied
Fig. 3 Bending of driving gear under the influence of rotating resistance moment after re-adhesion
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4 Conclusion The motor-axial bearings of the serial diesel locomotive 2TE116 are evenly loaded. Significant moments arising in the traction drive in case of slippage cause mutual displacements of traction drive parts with redistribution of loads. The irregular loading will increase wear rate of motor-axle bearings and wheelset axle as well, as the result of diesel-generator set power enhancement.
References 1. Liudvinaviˇciusa L, Jastremskasb V (2017) Modernization of diesel-electric locomotive 2M62 and TEP-70 locomotives with respect to electrical subsystem. Procedia Eng 187:272–280 2. Bogajevskiy A, Arhun S, Dvadnenko V, Ponikarovska S (2020) Determining the degree of increasing locomotive diesel economic efficiency by modernization of the speed controller. EAI Endorsed Trans Energy Web 7(28):e4 3. Lebedevas S, Dailydka S, Jastremskas V, Rapalis P (2015) The influence of locomotive diesel engine transient operating modes on energy usage. Transp Res Part D Transp Environ 34:219– 229 4. Koblov R, Novachuk I, Egorov P (2017) New interpretation of process of formation of tractive effort of the locomotive. Procedia Eng 187:803–808 5. Andrews HI (1959) The contact between a locomotive driving wheel and the rail. Wear 2(6):468–484 6. Jiang J, Chen Z, Zhai W, Zhang T, Li Y (2020) Vibration characteristics of railway locomotive induced by gear tooth root crack fault under transient conditions. Eng Fail Anal 108:104285 7. Wang J, He G, Zhang J, Zhao Y, Yao Y (2017) Nonlinear dynamics analysis of the spur gear system for railway locomotive. Mech Syst Signal Process 85:41–55 8. Chen Z, Zhai W, Wang K (2019) Vibration feature evolution of locomotive with tooth root crack propagation of gear transmission system. Mech Syst Signal Process 115:29–44 9. Chen Z, Zhai W, Wang K (2017) Dynamic investigation of a locomotive with effect of gear transmissions under tractive conditions. J Sound Vib 408:220–233 10. Shantarenko S, Kuznetsov V, Evseev A (2021) Modeling of dynamic behavior of wheel-motor block under conditions of locomotive moving. Transp Res Procedia 54:834–841
Identification of Wind Loads Through Train Statistical Analysis Ivan Grebnev , Natalia Sidorova , and Oleg Pudovikov
Abstract The article was written in order to substantiate the energy consumption rate for train traction and to determine how to reduce them. Wind load impacting train cars is one of the essential factors affecting energy consumption in traction. This is of particular relevance to the steppe regions where high speed winds prevail most of the year, which have a significant impact on an increase in fuel and energy consumption for train traction. The article analyzes the main factors affecting the consumption of fuel and electric power and the main methods of rationing fuel and energy resources. The study is based on Pallasovka-Verkhniy Baskunchak section of Privolzhskaya railway. Histograms of specific fuel consumption for trains with fixed minimum and maximum axle loads, based on the reported data of locomotive crews, were constructed and analyzed. Conclusions on the effect of wind loads on specific fuel consumption were drawn on the basis of the numerical characteristics of the obtained samples. Contributions of the wind loads to a significant increase in the specific fuel consumption has been proved in the article. Moreover, large consumption values were obtained for empty trains. Keywords Fuel and energy resources · Energy saving · Energy efficiency · Specific fuel consumption · Wind loads
1 Introduction Railway transport is one of the largest consumers of fuel and energy resources (FER) in the country. On the one hand, it consums about 5% of the total Russian electricity consumption and almost 11% of diesel fuel. On the other hand, the cost of diesel fuel in the overall costs of JSC Russian Railways is very significant and accounts for 8% of total company’s spending. The fuel and energy policy of JSC Russian Railways is based on saving diesel fuel. JSC Russian Railways aims to save 25 billion rubles a year on diesel fuel by I. Grebnev (B) · N. Sidorova · O. Pudovikov Russian University of Transport, Obrazcova Street, 9b9, 127994 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_29
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2024. It is possible to increase the energy efficiency of railway transport by using technical or organizational measures. As a rule, organizational measures require the least investment, they are applicable to the considered locomotive depot and are reduced to finding, identifying and diminishing the main factors affecting fuel consumption [1, 2]. The factors that affect the fuel consumption of trains running on each railway hall are divided into 3 main categories: – permanent, having insignificant changes over a long time of operation and which can be neglected. For example, the profile of a railway track. – conditionally constant, which do not change over a long period of time (for example, types of traction rolling stock and cars), or have sufficient stability in specific months of the year (for example, certain flows of freight trains or seasonal ambient temperatures); – variable ones that change for each specific trip (for example, all characteristics of freight trains) [3]. The last point also includes such factors that change in terms of time during the trip, and which must be taken into account in some cases. For example, temperature, wind speed and direction. The variable factor is the realized dependence of the speed along the way in each trip. Diesel fuel costs per trip largely depend on the degree of professionalism of the drivers. The normalization of fuel consumption for train traction, with the significant costs for train purchase taken into account, is of great importance for managing the efficient operation of railway transport. At present, there are 3 main methods of technical rate setting: – Technical rate setting based on the analytical calculations of fuel and energy resources consumption for train traction. Instructions on technical rate setting based on V.S. Molyarchuk’s works were and are widely used in the USSR and Russian railway system. The initial rate of specific consumption of fuel and energy resources for a trip was supposed to be determined through the equation of traction and energy in manufacturer’s certificate of origin passport of a certain range locomotive. Further, the value of the specific consumption was corrected through coefficients considering the influence of the main factors on the consumption [4]. – Rationing based on the automation of processing the data of the driver’s routes. At Russian Moscow State University of Railway Engineering (MIIT) and Omsk State Transport University, the methods for rationing the consumption of fuel and energy resources based on the statistical processing of the driver’s routes data were developed. In those studies, analyzing and rationing energy consumption were considered as problems of correlation regression analysis with pair or multivariable correlation methods, which make it possible to assess the impact on the specific fuel and energy consumption not only of one randomly changing factor versus certain other factors, but also a simultaneous effect of several random factors.
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– Determination of fuel and energy resources consumption for a trip based on the energy optimal traction calculation. For the energy optimal traction calculation, the speed characteristic of the train movement with the corresponding locomotive control modes - traction, running-out, braking ensuring a minimum of energy consumption is determined. The optimization problem is solved through the use of a mathematical instrument - Portnyagin’s maximum principle. The calculation is based on the integration of the train motion equation with the help of normative formulas of the Traction Calculation Rules considering the track profile, speed limits, travel time, type of locomotive, etc. [5, 6].
2 Materials and Methods The analysis was conducted on the basis of the drivers’ routes data. To collect statistical data, an electronic resource containing a complete database of electronic drivers’ routes was used to process the drivers’ routes by centralized driver’s route processing of JSC “Russian Railways” (According to the statistical data of JSC Russian Railways 2020). A sample of driver’s routes was collected from locomotive depot of TChE13 Ershov Privolzhskaya railway. The drivers operating on Pallasovka - Verkhniy Baskunchak and Verkhniy Baskunchak - Pallasovka sections were considered. The data were taken in such a way as to exclude or neglect the influence on the specific flow rate of the ambient air temperature. The data from March to May 2021 and from October to December 2020 were sampled. The average temperature in these months is approximately the same and varies from –10 to 10 °C [7]. Thus, the influence of high and low temperatures is excluded. A statistical analysis of the train traffic was conducted, and the block diagrams of the distribution density of the specific consumption were presented. Moreover, this resource considers wind effects for a trip on the basis of the data from a weather station and a driver’s report. This can be seen in the special column “Remarks”. When the driver’s routes were sampled from the original population, the routes having distorted data on actual fuel consumption were excluded. To discard statistical data, Grubb’s test was used [8, 9]. The study is based on Pallasovka - Verkhniy Baskunchak section of Privolzhskaya railway. The section was selected due to the terrain, weather and climate conditions. The other reason was that the locomotive depot “Ershov” responsible for this section additionally adjusts the fuel consumption rate on the basis of the field conditions. The section is located entirely on a flat steppe changing into semi-desert landscape [10]. Consequently, no air currents, except for wind ones, will have a significant effect here [11]. Numerical Characteristics of the Samples Under Consideration. A block diagram of the axle load distribution density in this direction was built on the basis on the driver’s route data. Since both directions have almost the same distributions with a
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slight degree of deviation, Fig. 1 shows a generalized block diagram of axle load distribution. From the block diagram, we can conclude that the predominant number of trains are either completely empty with a minimum average axle load, or fully loaded with a maximum load. Axle load is the main factor determining the specific fuel consumption. Therefore, when determining additional factors affecting the consumption, it is customary to consider the axle load as constant. A private sampling of the routes with the values satisfying the end columns of the block diagram was compiled. The numerical characteristics of the samples are presented in Tables 1, 2, 3 and 4. Block Diagrams of Specific Fuel Consumption Density Distribution. According to the parameter charts, Pallasovka-Verkhniy Baskunchak section is flat with an insignificant height. Therefore, it is advisable to combine the samples of specific fuel f, (axle / t) 0.14
0.12
0.1
0.08
0.06
0.04
0.02
0 5,9 - 7,7
7,7 - 9,6 9,6 - 11,4 11,4 - 13,3 13,3 - 15,1 15,1 - 17 17 - 18,8 18,8 - 20,7 20,7 - 22,5 22,5 - 24,4 q, (t / axle)
Fig. 1 Block diagram of the axle load density distribution of freight trains on the section under consideration
Table 1 Statistical parameters of the flow of total sampling trains weighing 2000 tons without wind effect for the total sampling for traction with 2TE25KM two-section diesel locomotives Parameters Train traffic
Parameters of statistical distribution characteristics Sample size
Mathematical expectation
Mean square deviation
Min. parameter value
Max. parameter value
Specific fuel consumption e kg /change
104
28.3
5.4
14.8
46
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Table 2 Statistical parameters of the flow of total sampling trains weighing 2000 tons with wind effect for the total sampling for traction with 2TE25KM two-section diesel locomotives Parameters Train traffic
Parameters of statistical distribution characteristics Sample size
Mathematical expectation
Mean square deviation
Min. parameter value
Max. parameter value
Specific fuel consumption e kg/change
132
30
7.1
14.8
55.6
Table 3 Statistical parameters of the flow of total sampling trains weighing 6000 tons without wind for the total sampling for traction with 2TE25KM two-section diesel locomotives Parameters Train traffic
Parameters of statistical distribution characteristics Sample size
Mathematical expectation
Mean square deviation
Min. parameter value
Max. parameter value
Specific fuel consumption e kg/change
113
15.02
1.88
11.2
19.7
Table 4 Statistical parameters of the flow of total sampling trains weighing 6000 t with wind effect for the total sampling for traction with 2TE25KM two-section diesel locomotives Parameters Train traffic
Parameters of statistical distribution characteristics Sample size
Mathematical expectation
Mean square deviation
Min. parameter value
Max. parameter value
Specific fuel consumption e kg/change
138
15.5
2.3
11.2
22.9
consumption with a fixed axle load from different directions into one generalized sample. The homogeneity check of the sought samples was carried out on the basis of the Student’s t-test [12]. Next, on the basis of the block diagram data presented in Figs. 1, 2, 3, 4 and 5 contained the block diagrams of the specific fuel consumption density distribution for trains with a fixed minimum and maximum axle load [13]. Statistical analysis of specific fuel consumption has shown that it is best described by the log-normal distribution law. This type of distribution is steady for any type of train traffic: with a predominance of both empty and loaded trains. This is due to the fact that the specific consumption does not always change linearly depending on the change in the standard-setting factors [14].
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f, (t ∙ km gross / kg) 0.09 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 14,8 - 19,3
19,3 - 23,7
23,7 - 28,2
28,2 - 32,6
32,6 - 37,1
37,1 - 41,5
41,5 - 46
е, (kg / t ∙ km gross)
Fig. 2 The block diagram of specific fuel consumption distribution density for a 2TE25KM diesel locomotive without wind effect for the total sampling and for a fixed minimum axle load f, (t ∙ km gross / kg)
0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01
0
14,8 - 20,7 20,7 - 26,5 26,5 - 32,3 32,3 - 38,1 38,1 - 43,9 43,9 - 49,7 49,7 - 55,6 е, (kg / t ∙ km gross)
Fig. 3 The block diagram of the specific fuel consumption distribution density for a 2TE25KM diesel locomotive with wind effect for the total sampling and for a fixed minimum axle load
Lower average, maximum and minimum values of specific fuel consumption were obtained for loaded trains both in the samples without and with the wind load. These are 15.02; 19.7; 11.2 and 28.27; 46; 14.8 (kg/t km gross), respectively, for the samples without the wind loads. The following results: 15.53; 22.9; 11.2 and 30.05; 55.6; 14.8 (kg/t km gross), respectively, were obtained for the samples with the wind loads.
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f (t ∙ km gross / kg) 0.22
0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 11,2 - 12,4
12,4 - 13,6
13,6 - 14,8
14,8 - 16
16 - 17,3
17,3 - 18,5
18,5 - 19,7
е, (kg / t ∙ km gross)
Fig. 4 The block diagram of the specific fuel consumption distribution density for a 2TE25KM diesel locomotive without wind effect for the total sampling and for a fixed maximum axle load
f (t ∙ km gross / kg) 0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 11,2 - 12,6 12,6 - 14,1 14,1 - 15,6 15,6 - 17
17 - 18,5
18,5 - 20
20 - 21,4 21,4 - 22,9
е, (kg / t ∙ km gross)
Fig. 5 The block diagram of the specific fuel consumption distribution density for a 2TE25KM diesel locomotive with wind effect for the total sampling and for a fixed maximum axle load
3 Results The obtained block diagrams clearly show an increase in the specific fuel consumption if there is a wind load. This is noticeable both in private sampling and in general sampling. The average specific fuel consumption increased by 6.3% for empty trains. The median of the sample with the wind loads shifted upward by 3.4%. An increase in asymmetry is also noticeable due to the presence in the sample a tail area biased towards an increase in specific fuel consumption. There is a big difference in the variance values. Moreover, the variance for the sampling with the wind loads is much higher than that for the sampling without wind loads. Such a scatter of variance values is quite possible due to different directions of wind loads. This can prove once again that the presence of wind loads significantly changes the pattern of specific fuel consumption. If we consider the kurtosis values, then we see a lesser value of the peak sharpness in the sampling under the influence of wind loads. This is due to the fact that the sampling without the influence of wind loads has more values close
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to the average specific fuel consumption. For the samples with a fixed maximum axle load, the average specific fuel consumption increased by 3.4%. The median of the sample with wind loads shifted upward by 3.2%. An increase in the value of the variance is also seen. Displacement of the asymmetry to the right is also traced. However, the resulting gain is less than for the trains with a fixed minimum axle load. The kurtosis values for the trains without the influence of wind loads have a negative value, which is typical for the samples of loaded distribution, where the values of specific fuel consumption have minimum values and slightly deviate from the average.
4 Conclusions The analysis of the two obtained independent samples for trains with a fixed minimum and fixed maximum axle load showed that under the influence of wind loads, the average value of specific fuel consumption increased more for trains with a fixed minimum axle load by 6.3% versus 3.4%. This is obvious as the trains with weight close to critical one for a diesel locomotive on a given section are in operation, the generated power and the generated energy accordingly, is almost totally consumed for traction and carrying capacity. It is also important that empty trains have greater specific resistance, in particular, due to the wind. This is the result of turbulence in open hatches, doors, intercar space and car bodies [15–17].
References 1. Romanova A, Luzhnov Y, Vygnanov A (2019) Resource-saving management on sections of high-speed railway lines. Procedia Comput Sci 149:297–300. https://doi.org/10.1016/j.procs. 2019.01.138 2. Scheepmaker GM, Pudney PJ, Albrecht AR et al (2020) Optimal running time supplement distribution in train schedules for energy-efficient train control. J Rail Transp Plan Manag 14:100180 3. Popov AN, Radionov IA, Mushenko AS (2015) Synergetic design of autopiloting systems with complex optimization of train traction. IFAC-PapersOnLine 48(11):457–462. https://doi.org/ 10.1016/j.ifacol.2015.09.228 4. Abramov A, Podorozkina A, Bilenko G et al (2022) Optimization of freight train speeds on railway transport. Transpn Res Procedia 61:371–375. https://doi.org/10.1016/j.trpro.2022. 01.060 5. Scheepmaker GM, Goverde RMP (2006) Output-based optimal timing control of switched systems. In: Proceedings of the International Workshop on Hybrid Systems: Computation and Control, LNCS, Santa Barbara, CA, USA, 29–31 March 2006 6. Wang P, Goverde RMP (2015) The interplay between energy-efficient train control and scheduled running time supplements. J Rail Transp Plan Manag 5(4):225–239 7. Sidorova E, Sitdikova L, Izotov V (2015) The major types of the weathering crust of the eastern Russian plate and its mineralogical and geochemical features. Procedia Earth Planet Sci 15:573–578. https://doi.org/10.1016/j.proeps.2015.08.105
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8. Caceres LT, de Castro M (2018) New estimation methods for the Grubbs model. Chemom Intell Lab Syst 176:119–125 9. Shah IA, Barakat HM, Khan AH (2020) Characterizations through generalized and dual generalized order statistics, with an application to statistical prediction problem. Statist Probab Lett 163:108872 10. Trivella A, Wang P, Corman F (2020) The impact of wind on energy-efficient train control. EURO J Transp Logistics 10:100013. https://doi.org/10.1016/j.ejtl.2020.100013 11. Ermolenko B, Ermolenko G, Fetisova Y et al (2017) Wind and solar PV technical potentials: measurement methodology and assessments for Russia. Energy 137(15):1001–1012. https:// doi.org/10.1016/j.energy.2017.02.050 12. Gmurman V (1977) Probability Theory and Mathematical Statistics, p 429. Higher School, Moscow 13. Kawai R (2017) Importance sampling Monte Carlo simulation for general multivariate probability laws. J Comput Appl Math 319:440–459 14. Junhua R, Qing Z, Feng L (2020) Analysis of factors affecting traction energy consumption of electric multiple unit trains based on data mining. J Clean Prod 262:121374. https://doi.org/ 10.1016/j.jclepro.2020.121374 15. Dongrun L, Gisella M et al (2020) Correlation of car-body vibration and train overturning under strong wind conditions. Mech Syst Signal Process. 142:106743. https://doi.org/10.1016/ j.ymssp.2020.106743 16. Yutao X, Tanghong L, Wenhui L (2021) Numerical comparisons of the aerodynamic performances of wind-tunnel train models with different inter-carriage gap spacings under crosswind. J Wind Eng Ind Aerodyn 214:104680 17. Onder A, O’Neill C et al (2016) Flying ballast resistance for composite materials in railway vehicle carbody shells. Transp Res Procedia 14:595–604. https://doi.org/10.1016/j.trpro.2016. 05.301
Improvement of Edge Cutting Machining of Materials with Fatigue and Thermomechanical Failures Michael Biserikan
and Anastasia Kashbulina
Abstract The article deals with the issue of increasing the efficiency of the machining operation of hard-to-treat steels with a heat-strengthened surface and contact fatigue failures on the case study of restoring the rolling surface of mounted wheels. The paper analyzes the statistical data and shows that the weakest point of the repair process and quality assurance is machining of wheel tread. A new machining flow chart based on the softening of the surface layer by a powerful local laser-based heating source is proposed. When the material was machined, the effect of hardness loss in the cutting zone during heating was used. The article analyzes the temperatures in hard-face plates when the latter are machined. Keywords Cutting tool · Lathe work · Mounted wheels · Cutting modes · Hard alloy · Fatigue failure · Fracture · Wear
1 Introduction The problem of edge cutting machining of hard-to-treat materials is one of the main ones [1–3]. Increased hardness and viscosity create problems with chip separation and durability of the cutting tool [4, 5]. Let us consider the problem of machining grade "T" steel with surface hardening. Such steel is used in the production of wagon wheels. After being in operation such steel has a hardened boundary layer of 1 mm deep with hardness ranging from 520 to 410 HV, and in some zones of up to 950 HV, while the regulations for hardness of the rim of solid-rolled wheels during production range from 320 to 360HB [6, 7]. The repair shop receives the parts with surface hardening and defects of fatigue and thermo mechanical character (TMC) which have a negative effect on the edge cutting machining [8]. The machining technology used aims to eliminate the existing defects from the rolling surface without the micro geometry of the resulting surface taken into account. At the same time, a layer of metal of proper quality is removed into the chips. Depending on the size of the TMC, M. Biserikan (B) · A. Kashbulina Omsk State Transport University, 35, Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_30
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the following machining modes are proposed: cutting depth t = 4–8 mm, feed s = 1–1.4 mm, cutting speed Vcut = 30–50 m/min. It is possible to significantly simplify the machining of materials with contact fatigue defects of thermo mechanical origin using temperature softening of the surface layer. It is known [4] that when steel is heated above 500 °C, hardness, resistance to rupture and limit of elasticity significantly decrease (twice as much or more). Therefore, in order to significantly reduce the hardness of the hardened material, improve the quality of the treated surface and reduce the failure of the cutting tool, heating of the cutting zone to a temperature above 500 °C is needed. At the same time, it is rational to heat the cutting zone up to 800–1000 °C since with an increase in temperature, the softening process quickens.
2 Materials and Methods Promising machining methods are plasma-assisted and laser-beam machining. The principle of both is to preheat the cut layer to a temperature at which the steel cutting is satisfactory. However, the implementation of plasma-assisted machining in remedial works has a number of significant disadvantages. Moreover, it does not allow for controlling temperature applications to the material and, finally its structure, therefore plasma-assisted machining is not used. During laser-beam machining, the heat accumulated in the cut layer cannot spread deep into the surface, which creates conditions for increasing productivity with a given tool life, the roughness and waviness of the machined surface decreases, wear resistance increases, there are no macro cracks. This effect can be achieved through high power lasers with continuous or repetitively pulsed radiation, which allow for heating the material in the chip zone to a temperature of more than 1250 °C. This system can be based on a TS912F3 machine and a ytterbium fiber laser. (Fig. 1). This type of lasers is characterized by high laser radiation power, operation in continuous, quasi-continuous or low mode operations, and high efficiency [9]. The main problem of laser machining is the choice of process parameters in such a way that the value of the contact temperature, on the one hand, does not exceed the temperature of structural transformations at a depth greater than the allowance, and on the other hand, the temperature in the cut layer should be sufficient to reduce the energy intensity of cutting [10]. Figure 2 shows the flow-chart of laser machining. The zone of laser heating is considered as a volume source of heat moving at a constant speed. This zone is described by the differential Eq. (1), the temperature pattern after the end of laser exposure is determined according to (2), the fusion penetration of the surface layer is determined according to (3) [11–14]. 1 ∂ ∂θ ∂ ∂θ ∂ ∂θ qb ∂θ = λ + λ + λ + , ∂τ cρ ∂ x ∂x ∂y ∂y ∂z ∂z cρ
(1)
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Fig. 1 Diagram of a TS912F3 wheel lathe machine equipped with a laser annealing device and a system for recognizing zones with contact fatigue and thermomechanical failures: 1—lathe machine wheel; 2—video surveillance system; 3—toolheads; 4—laser annealing device; 5—laser head
Fig. 2 The flow-chart of laser machining of a TMC wheel
2 ⎤ −y 2 −z ex p ex p 4ac τ 4ac (τ +τ0 ) 2AP ⎣ ⎦, T (y, z, τ ) = √ √ Vcut cρc 4πac (τ + τ0 ) 4πac τ ⎡
hLZ =
2AP
, πrn ρVcut cTk + L evap
(2)
(3)
where θ is the temperature, °C; τ—time, second; c is the mass heat capacity, J/(kg*°C); λ is the coefficient of thermal conductivity, W/m*°C; qb —heat flux density from internal sources, W/m2 ; p—density, kg/m2 ; τ—laser exposure time, s; τ0 is a time constant; V cut —cutting speed, m/s; ac is the thermal conductivity of the machined material, m2 /s; A is the surface absorption coefficient of laser radiation;
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Fig. 3 Temperature pattern in the laser exposure zone
T k is the boiling point of the machine-treated material, K; L evap. is the evaporation energy density of the machine-treated material, J/kg. Initial data for calculation: c = 465 J/(kg*°C); p = 7800 · kg/m3 ; λ = 47 W/(m*°C); Tk = 3000 °C; L evap. = 6.1 · 106 J/kg, V cut = 0.58 m/s; P = 7 · kW; r n = 1 · 10–4 m. Figure 3 shows the calculation results for half of the annealed area of the cut layer. When the part is being cut, a significant amount of heat is released at the point of contact of the tool with the machined part, which results in heating the tool, the part and the chips. The amount of heat released during machining depends on the parameters of the cutting modes and the geometry of the tool used. When rolling stock wheels are being repaired, a cutting tool equipped with tangential hard-face plates is used, the allowance is removed through the round-nose and liner parts of the main cutting edge. The cross section of the remnant relief on the machine-treated surface is formed by the round-nose sides of the plate (Fig. 4). When the rolling profile is recovered, the tool is chosen according to heat resistance, which is especially important the heated metal is machined since the surface of the tool is heated more intensively. The influence of temperature on the cutting process and the resulting forces is estimated by numerical methods based on the application of a thermo mechanical approach. √ t tr (2r − tr ) + r · ar c sin , (4) Pz = K ξ Sb st + (μ1 σb h 3 + 0.7Sb H0 ) sin ϕ r
tr Py = K V Sb s (t − tr ) cos ϕ + tr 1 − + σb h 3 (t − tr )ctan ϕ + tr 2r
2r −1 , tr
(5)
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Fig. 4 The flow chart of removing the allowance with the help of a tangential plate: ϕ—the main angle in the plan, °; ϕ1 —the auxiliary angle in the plan, °; s—feed, m/min; r is the radius at the top of the tool, m; t is the cutting depth, m; Rz —roughness of the treated surface, microns
where μ1 is the coefficient of friction on the back surface; ϕ is the main angle in the plan; λ is the dip angle of the front surface; σb is the conditional tensile strength, MPa; S b is the actual tensile strength, MPa; h3 —wear land height, m; H 0 —height of the built-up edge, m; K ξ , K V —specific forces of chip formation; ls is the length of the scarfing edge, m. The parameters of the section of the cut layer–thickness, width, length of the chip contact with the tool - are determined according to [5] with the following assumptions taken into account: a) on the front surface of the tool at a length AC = l, there are always two zones: the plastic contact zone with a length AM = l0 and the elastic contact zone MC = l0 , with l 0 = 0.5 l; b) in the zone of plastic contact, the tangential stresses are the same and equal τ p , and in the zone of elastic contact they are decreasing according to the law of the 3rd grade. The maximum temperature of primary plastic changes at the point A on the cutting edge is determined by: τp er f θA = cρ B
PeB 4
(6)
The maximum contact temperature on the front surface is at the point M(x = l 0), i.e. at the end of the plastic contact zone, and is expressed as: θ M = θ A (1 + ψ M ), ψM
√ 0.9675n PeB cos γ + sin γ − B(cos γ − sin γ ) = , cos γ + B sin γ er f PeB 4
(7)
(8)
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where M is the ratio of the maximum friction temperature M to the maximum temperature A; B—characterizes the degree of plastic changes of the removable allowance metal and the surface layer of the machined part; n is the part that the heat of friction of the chip on the front surface makes up of the total heat of friction. B=
m Pen , − sin γ )q
F k D p (1
(9)
Dimensionless groups Pe , F, D, coefficient m and exponents n, k, p and q are determined depending on the cutting conditions.
3 Results Thus, the total variable contact temperature on the front surface of the tool will be determined by the expression: 0.6 l0 x , 0 ≤ x ≤ l0 ; θn = θ A 1 + ψ M θn = θ A 1 + ψ M , x > l0 l0 x
(10)
When the material is laser heated, the layer removed into the chips results in an additional thermal load, thus changing the parameters determining the cutting process, and the front surface of the tool interacts with the heated metal. The relationship between the temperature on the surface of the cutting tool with additional heating and the temperature on the surface with no heating is expressed: θ = θn + (1 − pθn )θh ,
(11)
where p is the interaction factor, p = 0.001; h is the average temperature of the metal at the cutting edge of the tool during laser heating, °C. 2 b1 cρVcut k0 βW e[−k1 a1 ] · · er f θh = √ , 2 4λLk0 + cρVcut b1 π λLcρVcut
(12)
where W is the power of the laser installation, W; β is a coefficient that reflects some accumulated heat introduced by the laser beam in the machined part; k 0 is the concentration coefficient of the heat source, m-2; L is the length from the center of the heating point to the edge of the tool measured in the direction of the cutting speed, m; a 1, b 1—thickness and width of the cutout, m; λ is the thermal conductivity of the machined material, W/m *K; c is the heat capacity of the machined material, J/kg*K; ρ—the density of the machined material, kg/m3 . Calculation by formulas (6)–(12) allowed us to determine the temperature of the front surface of the hard-face plates of the cutting tool (Fig. 5).
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The temperature of the front surface,°C
°C
315
950
1
750
2
550 350 0
0.0005 0.001 0.0015 0.002 Distance from the top of the tool, m
0.0025
0.003
Fig. 5 Changing the temperature of the front surface of the tool: 1—laser heating; 2—without heating
Under these conditions, when the surface is annealed by a laser beam, the temperature above 500 °C does not extend to a depth of more than 2 mm. The structural changes occur only in the zone of the removed allowance for machining, and the base metal does not change its properties [15, 16].
4 Conclusion The use of laser heating of the cut layer in zones containing operational defects does not lead to the loss of tool cutting properties since the T14K8 hard alloy cutting plates of domestic production used for rolling surface reprofiling have a heat resistance of up to 1000 °C. The plates made of MS121 alloy (TU 48-19-308-80) manufactured by Sandvik, and TT1500 manufactured by TaeguTec have heat resistance up to 1100 °C. Thus, the use of laser machining for rolling surface zones with thermomechanical and fatigue defects ensures a reduction in cutting resistance. The chips take a significant part of the heat, and the tool does not overheat. The structure of the source metal does not change.
References 1. Arrazola PJ, Özel T, Umbrello D, Davies M, Jawahir IS (2013) Recent advances in modelling of metal machining processes. CIRP Ann Manuf Technol 62(2):695–718. https://doi.org/10. 1016/j.cirp.2013.05.006 2. Gutiérrez I, Altuna MA (2008) Work-hardening of ferrite and microstructure-based modelling of its mechanical behaviour under tension. J Mater 56(17):4682–4690. https://doi.org/10.1016/ j.actamat.2008.05.023 3. Abouridouanea M et al (2019) Microstructure-based approach to predict the machinability of the ferritic-pearlitic steel C60 by cutting operations. Procedia CIRP 82:107–112. https://doi. org/10.1016/j.procir.2019.04.013
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4. Abouridouane M, Klocke F, Lung D, Veselovac D (2015) The mechanics of cutting: insitu measurement and modelling. Procedia CIRP 31:246–251. https://doi.org/10.1016/j.pro cir.2015.03.048 5. Puls H, Klocke F, Lung D (2014) Experimental investigation on friction under metal cutting conditions. Wear 63–71. https://doi.org/10.1016/j.wear.2013.12.020 6. Neishi Y, Makino T, Matsui N, Matsumoto H, Higashida M, Ambai H (2013) Influence of the inclusion shape on the rolling contact fatigue life of carburized steels metall. Phys Metall Materials Sci 44(5):2131–2140. https://doi.org/10.1007/s11661-012-1344-9 7. Alley ES, Neu RW (2010) Microstructure-sensitive modeling of rolling contact fatigue. Int J Fatigue 32(5):841–850. https://doi.org/10.1016/j.ijfatigue.2009.07.012 8. Kabo E (2002) Material defects in rolling contact fatigue–influence of overloads and defect clusters. Int J Fatigue 24(8):887–894. https://doi.org/10.1016/S0142-1123(01)00193-1 9. Nigon GN, Isgor OB, Pasebani S (2021) The effect of annealing on the selective laser melting of 2205 duplex stainless steel: microstructure, grain orientation, and manufacturing challenges. Opt Laser Technol 134. https://doi.org/10.1016/j.optlastec.2020.106643 10. Sarkar S, Mukherjee S, Kumar CS, Kumar Nath A (2020) Effects of heat treatment on microstructure, mechanical and corrosion properties of 15–5 PH stainless steel parts built by selective laser melting process. J Manuf Process 50:279–294. https://doi.org/10.1016/j.jma pro.2019.12.048 11. Oh WJ, Son Y, Cho SY, Yang SW, Shin GY, Shim DS (2020) Solution annealing and precipitation hardening effect on the mechanical properties of 630 stainless steel fabricated via laser melting deposition. Mater Sci Eng 794. https://doi.org/10.1016/j.msea.2020.139999 12. Wang C, Shen XJ, An ZB, Zhou LC, Chai Y (2016) Effects of laser shock processing on microstructure and mechanical properties of K403 nickel-alloy. Mater Des 89:582–588. https:// doi.org/10.1016/j.matdes.2015.10.022 13. Kokawa H (2011) Potential of grain boundary engineering to suppress welding degradations of austenitic stainless steels. Sci Technol Weld Join 16(4):357–362. https://doi.org/10.1179/ 1362171811Y.0000000021 14. Zhang QK, Wang XM, Song ZL (2021) Effects of thin cladding layer and annealing treatments on mechanical properties of AISI4340 steel. Eng Fract Mech 256.https://doi.org/10.1016/j.eng fracmech.2021.107997 15. Sun SD, Liu QC, Brandt M, Luzin V, Cottam R, Janardhana M et al (2014) Effect of laser clad repair on the fatigue behavior of ultra-high strength AISI4340 steel. Mater Sci Eng A 606:46–57. https://doi.org/10.1016/j.msea.2014.03.077 16. Wen SF, Li S, Wei QS, Yan CZ, Zhang S, Shi YS (2014) Effect of molten pool boundaries on the mechanical properties of selective laser melting parts. J Mater Process Tech 214:2660–2667. https://doi.org/10.1016/j.jmatprotec.2014.06.002
The Impact of the Transport Factor on Regional Development Tatiana Tselykh , Evgeniia Shtele , and Tatiana Kuvaldina
Abstract Many scientists consider the role of transport infrastructure in the country’s economic development. Despite this, there is no precise definite conclusion about the presence or absence of a direct link in the current scientific literature. The article provides a review of the contemporary global and domestic literature, according to which the impact is considered reasonable and mathematically confirmed by some scientists, but at the same time denied by other researchers. The authors have proposed a hypothesis involving two assumptions, that transport factor in Russian conditions has a significant impact only on the development of certain regions depending on their type, and that the improvement of road infrastructure in certain types becomes an impetus for the emergence of small businesses. The research base is based on panel data for Russian regions from 2006 to 2018. As a result of dividing the RF subjects into groups and conducting regression analysis, the authors draw the following conclusions: the connection between infrastructure factors and GRP is confirmed only for underdeveloped regions; the connection between infrastructure development and small businesses is not identified. Keywords Transport infrastructure · Roads · Economic development · Regions · Small business · Econometric model
1 Introduction The development of transport infrastructure at the macro level of any country is an indicator of the state of its economic development because, on the one hand, transport meets the needs of freight and passenger transport, while on the other hand, transport is necessary to ensure the smooth functioning and expansion of industrial production. At the micro level, the rapidly developing processes of motorisation and mobility of society require managing them in order to avoid not only critical positions but T. Tselykh (B) · E. Shtele · T. Kuvaldina Omsk State Transport University, 35, Marx Street, Omsk 644046, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_31
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also to correctly direct efforts towards the formation of modern transport hubs in the Russian regions. The role of transport infrastructure as a means of regulating economic development is determined by the fact that it has some influence on the development level of all other components of the economic complex as they use transport services think [1]. Its influence and connection to the processes of individual regions’ economic development have been studied by scientists [2, 3], but there is no definite conclusion on this issue in economic science so far. There are many opinions on the role of transport infrastructure, but the authors of this article proceed from the fact that transport infrastructure and the location of economic entities are determined by the parameters of inter-system links and opportunities for economic development. It emphasizes the essence of transport infrastructure as an element of the economic entities’ development potential. On the one hand, advantageous location reduces transport costs; on the other hand, transport infrastructure components include road infrastructure characterised by road conditions and the transport process organisation. The first component can be assessed using different indicators such as road length, road density and quality (e.g., percentage of roads with paved surfaces, percentage of roads with improved surfaces etc.). The organisation of the transport process in this paper refers to the implementation algorithm of the transport system. This criterion is very complex and multifaceted and can be described by the following parameters: cargo safety, proportion of goods delivered on time, delivery time, etc. Spatial location (distance) also affects transport costs. The key question is whether investment in transport can increase aggregate factor productivity by stimulating investment activity. The main driver of sustainable economic growth is investment and productivity growth. If transport provision is to have a similar effect, it must work through these channels directly or indirectly by influencing the decisions taken by economic actors. There are a number of interesting studies by both domestic [4–10] authors in relevant articles.
2 Materials and Methods In order to assess the transport factor impact on regional development, the authors have put forward hypotheses: • the link between gross output and infrastructure is only possible for certain groups of regions, depending on the region type (in terms of economic development and the existing infrastructure level); • development of road infrastructure is a trigger for the emergence of small industries in regions with economies based only on large industrial facilities and far from the national level of socio-economic development.
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The hypotheses were tested by dividing all regions into several groups depending on the economic development level and the transport infrastructure development level and constructing regression equations (data analysis in Eviews) based on panel data for Russian regions from 2006 to 2018. The presence of a mathematical relationship was also confirmed (refuted) by the significance coefficients of the independent variables.
3 Results A total of 35 out of 85 Russian regions were studied. The remaining ones were not included in the sample, as they could have been assigned to different groups depending on the division subjectivity. Moreover, the purpose of this study was not to develop recommendations for all regions, but to confirm or refute the abovementioned hypotheses. The regions were classified into three groups according to their level of economic development in terms of GRP absolute value and GRP per capita (in order to avoid subjectivity of influence of one indicator): high, medium and low values. It should be noted that these indicators have been chosen as the most common and available in the regional statistics, which in dynamics reflect the presence or absence of economic growth in the territories. In order to generate the ranking, the authors used an integrated indicator that includes: • • • • •
density of paved roads; percentage of roads with improved pavement; number of transported freights; number of passengers; density of railways.
According to the authors, these characteristics directly or indirectly reflect the level of infrastructure development by assessing the saturation of the territory with networks. An indirect relationship can be traced through the volume of transported goods (the higher this indicator, the higher the economic incentives to saturate the infrastructure) and population mobility (which, among other things, depends on the quality of infrastructure). The assigned places of regions in the ratings are summarized, the rating is constructed in ascending order: from 57 conventional points for the city of Moscow and up to 361 for Yakutia. As a result, the authors identified 9 groups of regions (Table 1). Next, an analysis of the relationship between infrastructure indicators, as published in open regional statistics, and investment in transport and the GRP indicator was carried out. Namely: • density of paved public roads, roads per 1,000 m2 of territory; • road freight turnover, mln. t-km • proportion of roads with improved surface, %;
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Table 1 Division of Russian regions by transport infrastructure development and GRP GRP
Infrastructure development High
Average
Low
High
-1 Moscow region, Moscow, Saint Petersburg, Tatarstan
-2 Sverdlovsk region, Krasnoyarsk region, Leningrad region, Samara region
-3 Irkutsk region, Perm krai
Average
-4 -5 Novosibirsk region, Samara Volgograd region, Omsk region, Voronezh region region, Kemerovo region, Primorski Krai
-6 Kostroma region, Amur region, Astrakhan region, Vologda region
Low
-7 Stavropol Krai, Chuvashia, Bryansk Region, Penza
-9 Trans-Baikal region, Altai Republic, Tuva Republic, Buryatia
• • • •
-8 Dagestan, Kalmykia, Chechnya, Ingushetia, Kurgan region, Orel region
investment in transport per 1,000 inhabitants, thousand rub; length of public roads, kilometres investment in transport, mln. rub; density of public railways (km of railways per 1,000 km2 ) share of paved roads, %.
The analysis of various regression relationships revealed that most infrastructure indicators (e.g. the share of roads with hard surface, the share of roads with improved surface) are insignificant in the models. The railway track length indicators are constants throughout the study period in almost all constituent entities of the Russian Federation, so this criterion was excluded. It is important to pay attention to the results of regression analysis of the relationship between investment in transport, road density, road length and freight turnover in relation to the gross regional product. Thus, capital investment in transport, which is an important indicator of infrastructure development, is not related to GRP indicator (y) in any group of regions, as they do not depend on market factors, but are determined mainly by federal or regional funding programs. Their coefficients in the regression equations were found to be insignificant. Separate attention is paid to the indicators related to the density of paved roads (x1) and the length of roads (x2). The infrastructural indicators were taken with a lag of one year. Since the regions differ significantly in the magnitude of the indicators, the authors used absolute differences in GRP and road length for the analysis. In addition, the constant effects are included in the equation, which takes into account differences in the average influence of factors in the regions. δ(y it ) = β1 x 1it−1 + δβ2 (x 2it−1 ) + yeari + αi + εit
(1)
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where i is a region from the appropriate group, t is an observation period (year); year—time trend, α determines permanent effects for the regions, β is a regression coefficient, δ( f t ) = (ft −ft−1 )/(ft−1 )*100% In the groups of regions with a low level of economic and infrastructural development, the coefficients of the dependent variables were found to be significant. Since road density and length are similar indicators, only one indicator should be kept for further study. According to the authors, road density is more informative. Linear regression equations were constructed based on a dated panel of data collected over a number of years in the regions indicated. In order to refute or confirm the hypothesis about the significance of the factors, the authors included a trend in the equations, as in most cases GRP is determined by the trend. If infrastructure factors are found to be significant in the equation of a particular group, one should consider the hypothesis of significance of infrastructure trends to be confirmed. The results are presented in Tables 2 and 3. Next, another simplified regression was analysed on the dependence of GRP on the main factors: labour (value of wages), capital (value of fixed assets in the regions) and infrastructure (density of roads) (Table 4). δ(yit ) = b1 x1it + δb2 (x3it ) + δb3 (x4it ) + yeari + αi + ε
(2)
Table 2 Results of regression equations by regional group (paved road density (×1) and road length (×2)) 1 group Coefficients are not significant
2 group Coefficients are not significant
3 group Coefficients are not significant
4 group Coefficients are not significant
5 group Coefficients are not significant
6 group Coefficients are not significant or make no economic sense
7 group Coefficients are not significant
8 group Coefficients are significant, positive
9 group Coefficients are significant, positive
Table 3 Regression analysis results (1) Variable
Group 9 Coefficient
Group 8 P-value
Coefficient
P-value
x1(−1))
0.053
0.012
0.072
0.0416
δ(x3(−1))
0.145
0.045
0.123
0.0503
year
0.823
0.0000
0.8345
0.0000
C
1677.15
0.0000
23,458
0.0000
R-squared
0.25
0.32
Adjusted R-squared
0.24
0.31
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Table 4 Results of regression equations on regional groups (3) 1 group 2 group 3 group Coefficients are not significant Coefficients are not significant Coefficients are not significant 4 group 5 group 6 group Coefficients are not significant Coefficients are not significant Coefficients are not significant 7 group 8 group 9 group Coefficients are not significant Coefficients are not significant Coefficients are significant
where x3 is an average wage, x4 the size of the operating fixed assets in the respective regions, b regression coefficients. The only indicator describing infrastructure-road density-was chosen due to the insignificance of other variables and the lack of alternative data in regional statistics. As the available sample size associated with one region is too small (data for the period 2006–2018), a statistical analysis of each of them is not possible due to insufficient size. The regions vary considerably in size, so simply combining the data into one sample to build a regression model would not be correct. In order to construct regression equations that reflect the overall dependencies for the regional groups, a shift to increments was made. This resulted in the dimensionless rates in the large sample. The regression equations describing the dependence of GRP on the above-mentioned indicators turned out to be significant only for underdeveloped regions. The results are shown in Table 5. Mathematical correlation was found only for economically underdeveloped regions. In order to test the second hypothesis about the connection between infrastructure and small business development, regression equations were constructed by groups and a lag of one year was used for the research. Since the subjects of Russia differ significantly in the size of the indicators, the absolute differences in the turnover of small businesses and investment were used for the analysis (Tables 6 and 7).
Table 5 Regression results for group 9 (2) Variable
Group 9 Coefficient
P-value
X1 (−1)
0.245
0.052
δ(x3)
0.183
0.045
δ(x4)
0.054
0.000
YEAR
−1.278
0.000
C
2751.120
0.000
R-squared
0.242
Adjusted R-squared
0.238
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Table 6 Results of regression equations for regional groups on transport investment (x6), road density (x7) and small enterprise turnover (y2) 1 group Coefficients are of low significance, positive
2 group Coefficients are not significant
3 group Coefficients are not significant
4 group Coefficients are not significant
5 group 6 group Coefficients are not significant or Coefficients are not significant make no economic sense
7 group Coefficients are not significant
8 group Coefficients are not significant
9 group Coefficients are not significant
Table 7 Results of regression equations on regional groups (3) Variable
Group 9 Coefficient
P-value
δ(x5 (−1))
0.053
0.098
X1 (−1)
0.012
0.125
year
−12,547.561
0.000
C
−5245.230
0.000
R-squared
0.922
Adjusted R-squared
0.910
δ(z it ) = δa1 (x 1it−1 ) + a2 x5it−1 + a3 yeari + ε
(3)
where zi is small business turnover, ai defines regression coefficients, x5 defines transport investments. The maximum significant coefficients were obtained only for the first group. It was also decided to estimate the dependencies for the number of small enterprises (s) and the density of roads and investments in transport. Since the constituent entities of Russia differ significantly in the size of the indicators, the absolute differences for the number of small enterprises and the size of investments were used to estimate them. δ(s it ) = k1 x 1it−1 + δk 2 (x5it−1 ) + k3 yeari + αi + ε,
(4)
Having analysed all the equations, we did not obtain significant coefficients for any of the groups.
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4 Discussion Modern Western researchers [11] have repeatedly assessed the impact of infrastructure on the location of production and foreign trade in their work. Their study was continued by the models of Helpmen and Krugman [12]. The main conclusion reached by the scientists can be formulated as follows: a policy that finances domestic infrastructure in a backward country encourages firms to move to that country. As elements of infrastructure, the authors evaluated the development of transport and telecommunications in the region, the level of order and the legislation efficiency. At present, the model of symmetric reduction of import and export transaction costs in response to improved infrastructure has been criticised. Interesting results are contained in the work of a team of researchers led by Baldwin [13]. The authors, describing different policies using the spillover model (number of transfers to poorer regions, quality of transport infrastructure within a region, quality of transport infrastructure between regions and policies aimed at increasing technological spillover) argue that infrastructure that promotes inter-regional trade (transport and roads) increases spatial concentration, promotes economic growth and reduces regional income inequality. In other words, the authors claim that transport infrastructure can become an “engine” for economic development and acceleration of market transformations, facilitate development of inter- and intra-territorial, sectoral links and optimal use of resources. Current studies do not have a clear convergence of views on the magnitude of the infrastructure impact on economic growth and do not emphasise any general effects of this impact. More often it is emphasized that it depends on the timing, country and type of infrastructure in question. Only a few recent empirical studies find a positive relationship between infrastructure and growth. Kamps [14] analyses the impact of public capital on real GDP in 22 OECD countries from 1960 to 2001. In most cases, he finds a positive relationship with elasticities ranging from 0.41 to 0.84 across countries. Jong-A-Pin and Haan [15] find a positive relationship between public capital and output in France, Sweden and Finland, but a negative one in Belgium, Ireland and the UK. The results of the European Commission long-run econometric analysis (1950– 2012) show that in the long-term, both transport and electricity infrastructure are positively correlated with GDP. Short-term shocks in electricity and transport infrastructure seem to have a less significant impact on the current level of GDP. This suggests that the effects of investment in transport infrastructure take time to materialize [16–18]. In a study by Aschauer [19] on the relationship between GDP and investment in social infrastructure (e.g. hospitals) in the US from 1953–1985, the elasticity is about 0.06. Thus, a 10% increase in investment in social infrastructure would provide a 0.6% increase in GDP. Canning studied the World Infrastructure Database (1950–1995) and found that the impact of infrastructure varies across countries depending on population, GDP
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per capita, geographical location, and this relationship changes over time [20]. The same is argued by the OECD, where it is stated that many studies did not take into account the type of investment (new construction, modernisation) [21]. O’Fallon report a positive relationship, but it is less significant [22]. Nadiri and Mamuneas looked at inter-regional highways in the USA and adjusted elasticities on the order of 0.08% between 1950 and 1991 [23]. At the same time, the debate among academics on this issue has continued unabated in recent years. For example, reports from SACTRA [24] and the Department of Environment, Transport and the Regions report a weak evidence base for such studies. Eberts [25] concludes that there is no defined method for estimating the impact of infrastructure on GDP. Among domestic studies on this problem, one should highlight Semina’s monograph [26], where theoretical and methodological foundations for assessing the level of transport infrastructure in the Republic of Moldova are considered. A little earlier, Yakunin, Makarov et al. [4] describe the mechanism of non-inflationary GDP growth because of investment in transport. D. A. Manukyan [27] indicates a high correlation between GDP and the density of railways and roads in the USA, EU, Russia and Armenia in period 2004–2007. The study by E.I. Kolchinskaya [28] covered the transport infrastructure of the Russian regions and the level of industrial development. It is based on the principle of calculating integral indicators of transport and industrial development (availability of paved roads by regions of the Russian Federation, turnover of organizations, balanced financial result of organizations, investment volume and data on roads). Next, production functions were constructed using estimates of the level of infrastructure development. The working hypothesis of the relationship between the indicators has been rejected due to the insignificance of the obtained equations. This is due to both economic and historical reasons. First, the basis of the transport network of the Russian Federation, including the railway network, was established in the Soviet period, when decisions to build roads were made on the basis of the need to improve the defense capability, the need to address social objectives. The image and political aspects, rather than economic feasibility, were in the foreground. In addition, some regions have prospered in economic development due to the location of one or more large factories from the Soviet Union times. It is these large enterprises that have created their own transport infrastructure (e.g. railways, which are not part of public transport routes). At the same time, these regions may have low road densities, as the infrastructure is presented as access roads to such a giant. Therefore, there is no obvious statistical correlation mathematically between the level of development of industries and transport infrastructure in Russia as a whole. This makes it impossible to conclude that transport development will not contribute to the country’s economic growth. Russia is a country with highly differentiated regional development: the GRP (gross regional product) of Moscow is 357 times higher than that of Altai Territory, while the density of paved roads in Moscow Region is 746 times higher than in Chukotka (which of course is explained by the geographical position of the region).
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For this reason, it seems appropriate to conduct a study not for Russia as a whole, but for individual regions (groups of regions). Taking into account the facts mentioned above, the first hypothesis was confirmed: road efficiency indicators correlate with GDP in underdeveloped regions, where public infrastructure construction has a significant share in GRP. The equations are suitable for regression forecasting; this allows us to estimate that changes in road density along with some other elements will lead to changes in GRP. The mathematical relationship was found only for the economically underdeveloped regions. This may be due to the fact that in the well-developed regions other transport modes (air, rail, owned by large enterprises, waterways) play an important role. This is possible because of the placement of road construction orders with local firms. No significant mathematical relationship was found between the turnover of small businesses, investments in transport, and road density. The same is true for the other dependent variable-the number of small businesses. There are a number of possible reasons for this: imperfect regional statistics on small enterprises in the regions, an imperfect market mechanism, and significant administrative barriers hindering the operation of small enterprises in Russia. It is possible that these correlations can be explained by a better mechanism for small business operation in the developed regions. This research provides a basis for further development of recommendations, such as improvements in automotive infrastructure and small business mechanisms in Russian underdeveloped regions.
5 Conclusion As a result of dividing the RF subjects into groups and conducting regression analysis, the authors conclude that the relationship between infrastructure factors and GRP is confirmed only for underdeveloped regions, the relationship between infrastructure development and small business is not identified, namely: • the hypothesis of the link between the economic development level and transport infrastructure is confirmed for the regions of groups 8 and 9 with low level of infrastructure and economic development. • the hypothesis of the impact of transport infrastructure development on small business turnover in the regions was confirmed, i.e., for the regions with high level of gross regional development per capita and high and medium level of infrastructure development. • the hypothesis that there is a relationship between the number of small businesses, investment and infrastructure indicators has not been confirmed.
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References 1. Prus P, Sikora M (2021) The impact of transport infrastructure on the sustainable development of the region. Case study. Agriculture 11(4):279 2. Pereira AM et al (2013) On the economic effects of public infrastructure investment: a survey of the international evidence. J Econ Dev 38(4):1–37 3. Chen CL, Vickerman R (2017) Can transport infrastructure change regions’ economic fortunes? Some evidence from Europe and China. Reg Stud 51(1):144–160 4. Yakunin VI, Makarov VL, Bakhtizin AR (2007) State investment policy on transport and its economic consequences. Bull Russ Acad Sci 77(6):483–497 5. Pal S (2010) Public infrastructure, location of private schools and primary school attainment in an emerging economy. Econ Educ Rev 29(5):783–794 6. Mejia-Dorantes L, Paez A, Vassallo JM (2012) Transportation infrastructure impacts on firm location: the effect of a new metro line in the suburbs of Madrid. J Transp Geogr 22:236–250 7. Rietveld P, Bruinsma F (2012) Is Transport Infrastructure Effective? Transport Infrastructure and Accessibility: Impacts on the Space Economy. Springer Science & Business Media, Heidelberg. https://doi.org/10.1007/978-3-642-72232-5 8. Lakshmanan TR (2011) The broader economic consequences of transport infrastructure investments. J Transp Geogr 19(1):1–12 9. Hong J, Chu Z, Wang Q (2011) Transport infrastructure and regional economic growth: evidence from China. Transportation 38(5):737–752 10. Xueliang Z (2013) Has transport infrastructure promoted regional economic growth?—with an analysis of the spatial spillover effects of transport infrastructure. Soc Sci China 34(2):24–47 11. Martin P, Rogers C (1995) Industrial location and public infrastructure. J Int Econ 39:335–351 12. Krugman P (1991) Increasing returns and economic geography. J Polit Econ 99:483–499 13. Baldwin R, Forsli R, Martin P et al (2003) Economic Geography and Public Policy. Princeton University Press, Princeton 14. Kamps C (2005) Is there a lack of public capital in the European Union? EIB Work Pap 10(1):72–93 15. Jong-a Pin R, de Haan J (2008) Time-varying impact of public capital on output: new evidence based on VARs for OECD countries. EIB Pap 13(1):56–81 16. European Commission (2015) The 2015 Aging Report: Economic and budgetary projections for the 28 EU Member States (2013–2060). European Commission Directorate-General for Economic and Financial Affairs Publications 17. European Commission (2016) Next steps for a sustainable European future: European action for sustainability. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions 18. European Commission (2016) Synthesis report on the assessment of member states’ building renovation strategies. JRC Sci Policy Rep 19. Aschauer D (1993) Genuine economic returns to infrastructure investment. Policy Stud J 21(2):380–390 20. Canning D, Fay M (1993) The effect of transportation networks on economic growth. Columbia University 21. OECD (2003) The sources of economic growth in OECD countries. https://read.oecd-ili brary.org/economics/the-sources-of-economic-growth-inoecd-countries_9789264199460-en# page4.. . Accessed 10 June 2018 22. O’Fallon (2003) Linkages between infrastructure and economic growth. Ministry of Business. Innovation and Employment. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.184. 9839&rep=rep1&type=pdfAccessed 31 July 2017 23. Nadiri M, Mamuneas T (1998) The effects of public infrastructure and R&D capital on the cost structure and performance of US manufacturing industries. Natl Bureau of Econ Res Rev Econ Stat 76(1):22–37
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24. Standing Advisory Committee on Trunk Road Assessment (SACTRA) (2003) Transport investment, transport intensity and economic growth. http://www.roads.detr.gov.uk/roadnetwork/sac tra/report99/index.htm. Accessed 01 July 2014 25. Eberts R (2017) Valuing mature highway system: in search of the holly grail. TR News 309:24– 29 26. Semina I, Nosonov A, Loginova N (2014) Spatial analysis and assessment of the socioeconomic development of the region. Mordov Publishing House. University, Saransk 27. Manukyan DA (2009) Place of transport in the development of the Republic of Armenia. Bull St. Petersb Univ 5(3):177–182 28. Kolchinskaya E (2015) Influence of transport infrastructure on industrial development of Russian Regions. Actual Probl Econ Law 2:77–82
Choosing a Method for Studying Rail Vehicles’ Oscillations with Nonlinear Suspension Characteristics Anatoly Savoskin
and Natalia Lavlinskaya
Abstract On the case study of a dynamic system with one degree of freedom and a nonlinear restoring force the paper shows that a random white noise disturbance can be effectively used to identify the specific features of the oscillations of nonlinear systems. Within the framework of the considered case study, such a disturbance made it possible to easily distinguish the ultraharmonic (high-frequency) components of the oscillations of the nonlinear system under study. The performed check by calculating the oscillations of a nonlinear system with a sinusoidal disturbance of increased amplitude in comparison with the calculations of random oscillations of the same system showed a high adequacy of the results obtained. The used method for determining the probabilistic characteristics of random oscillations of a nonlinear system based on the procedure of averaging over a set of implementations can be used in the future for probabilistic calculation of more complex nonlinear systems with a finite number of degrees of freedom. Keywords Dynamics of rail vehicles · Oscillations of nonlinear systems · Non-stationary random processes · Ultraharmonic components · Fast Fourier transform · Two-dimensional autocorrelation function · Two-dimensional spectral density · White Gaussian noise
1 Introduction Methods of mathematical modeling are widely used to solve the problems of rolling stock dynamics. In this case, the models of real railway vehicles are complex nonlinear systems with many degrees of freedom. Therefore, the issues related to the methods of studying the oscillations of such nonlinear systems are relevant [1–5]. It is known that in the oscillations of nonlinear systems there are a number of features that significantly distinguish them from the oscillations of linear systems [1, 3]. In particular, in nonlinear systems, the amplitudes of forced oscillations A. Savoskin · N. Lavlinskaya (B) Russian University of Transport, Obrazcova Street, 9b9, 127994 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_32
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ambiguously depend on the frequency and amplitude of the disturbance; the emergence of subharmonic and superharmonic (ultraharmonic) oscillations, the emergence of self-oscillatory modes, etc. are possible. To identify such features, the special methods of studying oscillations are used. For instance, a fitting method for systems with piecewise linear characteristics, methods of harmonic balance, energy balance, etc. In [6–8] it was proposed to use for this purpose the method of numerical integration of systems of nonlinear differential equations under random perturbation. Since the random oscillations of nonlinear systems are unsteady, to find the numerical characteristics of these oscillations, we used averaging over a set of implementations. The purpose of this study is to test the applicability of this method based on comparing the results obtained in the study of oscillations of the simplest nonlinear systems with one degree of freedom with random and deterministic harmonic disturbances in effect.
2 Materials and Methods The object of research is the simplest single-mass model of a rail vehicle as a system with one degree of freedom under a kinematic disturbance (Fig. 1, a), the oscillation equations of which have the form: ˙ + F y = 0, m¨z + mg + β
(1)
Let us assume that the system has a linear dissipation β˙z and a nonlinear restoring force, described by a cubic parabola (Fig. 1, b): kN
c mg m
a)
b)
Fig. 1 Design scheme of the vehicle model with one degree of freedom a and nonlinear elastic characteristic of the restoring force b
Choosing a Method for Studying Rail Vehicles’ Oscillations …
F y = c + μ3 ,
331
(2)
where = z − η, a η—kinematic disturbance, which is taken as either a Gaussian white noise, or a deterministic harmonic function: η(t) = ηm sin 2π f t.
(3)
The equation of oscillations (1) with (2) taken into account can be written in the form: ˙ + c z − η + μ(z − η)3 = 0, m¨z + mg + β(˙z − η)
(4)
Bouncing oscillation z(t) of the adopted model was investigated with the following parameters: μ = 0.8; weight m = 23,000 Ns2 /m, hardness c = 2.200.000 N/m, damping coefficient of the equivalent hydraulic shock absorber β = 30.000 Ns/m. To determine the natural oscillation frequency of a linearized system equivalent to the original nonlinear one described by the Eqs. (1) and (2), it is necessary to find the quasi-elastic coefficient A0 , which is defined as the derivative of the nonlinear restoring force at the point of static deflection of an elastic element under the action of gravity (Fig. 1, b). The value of the static deflection of the elastic element is found from the equation: c st + μ3st = mg Next, we find the derivative of the nonlinear elastic force function at the point of static deflection: F y = c + 3cμ2 ; F y (st ) = A0 = 2200000 + 3 · 2200000 · 0.8 · 0.12 = 2252800 Then the natural frequency of oscillations of the linearized single-mass system is: 1 fc = 2π
A0 ≈ 1.6 H z. m
White Gaussian noise was used as a steady ergodic random disturbance η(t) for such a model [9, 10]. Since the oscillations of a nonlinear system are not ergodic or even unsteady, it is necessary to use an averaging algorithm over a set of implementations for their probabilistic analysis. In this regard, 211 = 4096 implementations of white noise were generated, each contained N = 20.000 values with a sampling step T = 0.001s. Some of the implementation fragments of the disturbance with a duration of 2 s are shown on Fig. 2, a.
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To study the oscillations of the adopted nonlinear system with a deterministic disturbance, the kinematic sinusoidal disturbance η(t), see (3), with a frequency equal to the natural oscillation frequency of the linearized system f c = 1.6 Hz was used. Oscillation amplitude ηm will be increased unless ultraharmonic components appear as part of the oscillations z(t). The solution of the nonlinear differential Eq. (4) was executed in the MatLabSimulink software package [11–14] by numerical integration through the DormandPrince method, which does not require lowering the order of the differential equation and reducing it to Cauchy’s form.
3 Results As a result of solving the equation with a random disturbance, 4096 implementations of the random process of vertical oscillations z(t) were obtained. Some of the fragments of these implementations (Fig. 2, b) with a duration of 4 s show that individual implementations z(t) significantly differ from each other, both in the range of random oscillations, i.e., in the variance and in the frequency composition, which confirms the non-ergodicity and even possible nonsteadiness of random oscillation processes. For a probabilistic description of a set of implementations of a non-ergodic random process z(t), a two-dimensional probability density was found f [z(t 1 ), z(t 2 )] (Fig. 3). The statistical distribution showed satisfactory convergence with the theoretical two-dimensional normal distribution law found by the formula: f [z(t 1 ), z(t 2 )] =
2 k=1
1 (z k − z k ) , √ exp − 2S2zk S zk 2 π
(5)
Fig. 2 Implementations of random processes: a disturbances; b oscillations of a nonlinear system
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333
where z k = 0 is mathematical expectation, S2zk is variance, and S zk is the standard deviation of k—th process z(t). In addition, a correlation-spectral analysis of the random process z(t) was performed [15]. Autocorrelation function R z (t 1 , t 2 ) are determined through the two-dimensional probability density with the matrix of values z(t) (Fig. 4):
mm
mm
a)
b)
Fig. 3 Two-dimensional probability density of oscillations of a nonlinear system a and its crosssection b at 0.5 S z ; 1.0 S z and 1.5 S z (solid line stands for statistical, dotted - for theoretical)
Fig. 4 Autocorrelation function of the bouncing nonlinear oscillation process of a single-mass nonlinear model
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∞ ∞ R z (t 1 , t 2 ) =
z(t 1 )z(t 2 ) f [z(t 1 ), z(t 2 ), t 1 , t 2 ]d z(t 1 )dz(t 2 )
(6)
−∞ −∞
The resulting autocorrelation function R z (t 1 , t 2 ) has a surface area (Fig. 4) in the inner function t 1 and t 2 . It should be noted that at t 1 = t 2 the autocorrelation function R z (t 1 , t 2 ) becomes the variance D z (t). As the autocorrelation function graph shows R z (t 1 , t 2 ), the variance D z (t) has some fluctuations in the diagonal plane (≈14%). Taking into account the regularity of the variance change process over time and a large number of processed implementations increasing the confidence of the correlation function estimate, we should consider a random process z(t) nonstationary. 2D spectral density G z f 1 , f 2 was obtained through the double fast Fourier transform (hereinafter - FFT) algorithm of the correlation function R z (t 1 , t 2 ) [10, 15]. Spectral density has a maximum at the fundamental frequency of 1.6 Hz, lying in the diagonal plane passing through the axis of symmetry and equal to the natural frequency, as well as a number of additional maxima lying on lines parallel to the axes O f 1 and O f 2 (Fig. 5). A more visual representation of the harmonics nature of the oscillations spectral density of a system with one degree of freedom can be obtained in the top view f , f 2 performed at different values (Fig. 6). Figure 6 shows the cross sections G z 1 G z f 1 , f 2 = const. The frequencies and amplitudes of all harmonics are shown in Table 1. As this table shows, the values of the harmonic frequencies are approximately two, three and four times higher than the fundamental oscillation frequency, which corresponds to the condition for the appearance of ultraharmonic oscillations in the system.
Fig. 5 Two-dimensional spectral density of a random process of bouncing oscillations of a singlemass nonlinear model
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Fig. 6 Top view of 2D spectral density
Table 1 Frequency and spectral density values for random disturbance Harmonics
Frequency, Hz
Spectral density, mm 2 s
The fundamental harmonic curve
1.6
2430
The first ultraharmonic curve
3.1
360
The second ultraharmonic curve
4.75
410
The third ultraharmonic curve
6.5
290
As a result of solving Eq. (4) with a deterministic sinusoidal disturbance η(t) = ηm sin 2π f t one implementation of the bouncing nonlinear oscillation process was obtained z(t) (Fig. 7). These graphs show that the implementation of the process of deterministic oscillations is periodic (curve 2) and differs significantly from the harmonic process of disturbance (curve 1). In addition, the average value of the process z(t) is not equal to zero due to the gravity mg and is z = 3.6 mm. Decomposition of one period of process oscillations z(t) in Fourier series made it possible to reveal the harmonic composition of this process (Fig. 8), the harmonic frequencies of which are shown on the axes f 1 and f 2 of this Figure. In this case, the frequency and amplitude of the fundamental harmonic curve are shown in the diagonal plane OAf . The values of the frequencies and amplitudes of these harmonics are presented in Table 2. As this table shows, all nine ultraharmonic components have frequencies that are multiples of the fundamental frequency of 1.6 Hz, which confirms the results obtained in the study of random oscillations of such a nonlinear system.
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Fig. 7 Implementations of the process of sinusoidal disturbance - curve 1 and the process of deterministic oscillations of a nonlinear system - curve 2
Fig. 8 Amplitude spectrum of nonlinear oscillation process under deterministic disturbance
4 Discussion 1. Oscillations of a nonlinear system under the action of Gaussian white noise with constant spectral density are a non-stationary random process, the probabilistic characteristics of which can be determined on the basis of averaging procedures over a set of implementations. 2. The two-dimensional distribution law of the instantaneous values of random oscillations of such a system complies with Gaussian distribution law. The correlation function and the spectral density of these oscillations are the functions of two arguments respectively t 1 and t 2 or f 1 and f 2 .
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Table 2 The value of the frequencies and amplitudes of the harmonic composition of nonlinear oscillations with sinusoidal disturbance Harmonics
Frequency, Hz
Amplitude, mm
The fundamental harmonic curve
1.6
The first ultraharmonic curve
3.2
103 1.383
The second ultraharmonic curve
4.8
1.108
The third ultraharmonic curve
6.4
1.083
The fourth ultraharmonic curve
8.0
0.6003
The fifth ultraharmonic curve
9.6
0.6562
The sixth ultraharmonic curve
11.2
0.5467
The seventh ultraharmonic curve
12.8
0.9751
The eighth ultraharmonic curve
14.4
1.184
The ninth ultraharmonic curve
16.0
0.5384
3. The composition of the spectral density of these random oscillations includes ultraharmonic components with the frequencies of 2, 3 and 4 times higher than the fundamental oscillation frequency, which at the adopted values of the system parameters was 1.6 Hz. 4. Oscillations of a nonlinear system with a harmonic disturbance with a fundamental frequency of 1.6 Hz are periodic and, in addition to the fundamental oscillation frequency, contain ultraharmonic components with a wider spectrum of frequencies including those having the same frequencies as in random oscillations. This testifies to the adequacy of the adopted technique for determining the probabilistic characteristics of random oscillations of a nonlinear system based on the procedure of averaging over a set of implementations.
5 Conclusions The study shows that the method of probabilistic analysis of random oscillations of a nonlinear system based on the averaging procedure over a set of implementations allows one to obtain sufficiently reliable characteristics of the random processes under study. The given method can be used in the future for probabilistic calculation of more complex nonlinear systems with a finite number of degrees of freedom.
References 1. Sayyaadi H, Shokouhi N (2009) A new model in rail–vehicles dynamics considering nonlinear suspension components behavior. Int J Mech Sci 51(3):222–232. https://doi.org/10.1016/j.ijm ecsci.2009.01.003
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2. Wang WL, Zhou ZR, Yu DS, Qin QH, IIwnick S (2017) Rail vehicle dynamic response to a nonlinear physical ‘in-service’ model of its secondary suspension hydraulic dampers. Mech Syst Signal Process 95:138–157. https://doi.org/10.1016/j.ymssp.2017.03.031 3. Strano S, Mario Terzo M (2018) On the real-time estimation of the wheel-rail contact force by means of a new nonlinear estimator design model. Mech Syst Signal Process 105:391–403. https://doi.org/10.1016/j.ymssp.2017.12.024 4. Kaiser I, Strano S, Mario Terzo M, Tordela C (2021) Anti-yaw damping monitoring of railway secondary suspension through a nonlinear constrained approach integrated with a randomly variable wheel-rail. Mech Syst Signal Process 146:107040. https://doi.org/10.1016/j.ymssp. 2020.107040 5. Keck A, Schwarz C, Meurer T, Heckmann A, Grether G (2021) Estimating the wheel lateral position of a mechatronic railway running gear with nonlinear wheel–rail geometry. Mechatronics 73:102457. https://doi.org/10.1016/j.mechatronics.2020.102457 6. Savoskin AN, Akishin AA (2014) The generation of multidimensional stochastic process of perturbation in the problems of railways rolling stock dynamics. In: Computer Modeling and Simulation. Proceedings of the International Research and Development Conference, pp 135– 141. https://doi.org/10.5862/JCSTCS.217-222.6 7. Savoskin AN, Akishin AA, Yurchenko D (2017) Dynamics and optimization of a new doubleaxle flexible bogie for high-speed trains. J Rail Rapid Transit Proc Inst Mech Eng 737879. https://doi.org/10.1177/0954409717737879 8. Savoskin AN, Akishin AA, Yurchenko D (2016) Design of a new two-axle bogie for a high speed train. In: Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance, p 85. https://doi.org/10.4203/ccp.110.85 9. Balakrishnan AV, Mazumdar RR (2010) On powers of Gaussian white noise. IEEE Trans Inf Theory 57(11). https://doi.org/10.1109/TIT.2011.2158062 10. Pulford GW (2011) The two-dimensional power spectral density: a connection between 2-D rational functions and linear systems. IEEE Trans Autom Control 56(7):1729–1734. https:// doi.org/10.1109/TAC.2011.2135170 11. Hamdi RTA, Abdul Hussein MA (2018) Using matlab-simulink for solving differential equations. J Sci Eng Res 5(5):307–314 12. Radionova LV, Chernyshev AD (2015) Mathematical model of the vehicle in MATLAB Simulink. Procedia Eng 129:825–831. https://doi.org/10.1016/j.proeng.2015.12.114 13. Hroncová D, Šarga P, Alexander Gmiterko A (2012) Simulation of mechanical system with two degrees of freedom with bond graphs and MATLAB/Simulink. Procedia Eng 48:223–232. https://doi.org/10.1016/j.proeng.2012.09.508 14. Sivák P, Hroncová D (2012) State-space model of a mechanical system in MATLAB/Simulink. Procedia Eng 48:629–635. https://doi.org/10.1016/j.proeng.2012.09.563 15. Pulford GW (2008) Derivation of the two-dimensional power spectral density of a nonstationary linear system with constant coefficients project: Two-dimensional (2-D) spectral density estimation, Report number: KF_V8.3
The Effect of Distributed Generation Plants’ Prognostic Controllers on Power Quality in Power Supply Systems of Non-traction Consumers Yuri Bulatov , Andrey Kryukov , and Konstantin Suslov
Abstract In power supply systems powered from mainline railroads’ traction substations, the problem of ensuring the electric power quality is acute. One of the effective ways to solve it is the use of smart grid technologies, an important segment of which are automatically controlled distributed generation plants. The article presents the results of computer simulation of transients during an increase in traction load, which leads to deterioration of power quality in non-traction consumers’ power supply systems. The purpose of the study was to determine the efficiency of using distributed generation plants to improve the power quality in power supply systems of on-site facilities powered from mainline railroads’ traction substations. Particular attention was paid to the setting and algorithms of the automatic controllers of the distributed generation plant synchronous generator and their influence on the indicators of the transient process and the power quality in the power supply system. The studies were conducted in the MATLAB development and simulation environment. Their results indicated that the presence of distributed generation plants allows to improve the power quality factors at the busbars of non-traction consumer; concordant setting of controllers provides the possibility for additional improvement of these indicators. The use of prognostic controllers ensures maintaining of power quality factors at a constant level when changing the generator load. The use of direct current link and prognostic controllers almost completely eliminates voltage asymmetry and harmonic distortions, significantly reduces the oscillability and value of voltage overshoot and generator rotor speed of the distributed generation plant. Y. Bulatov (B) Bratsk State University, 40, Makarenko Street, Bratsk 665709, Russian Federation e-mail: [email protected] A. Kryukov Irkutsk State Transport University, 15, Chernyshevskogo Street, Irkutsk 664074, Russian Federation A. Kryukov · K. Suslov Irkutsk National Research Technical University, 83, Lermontov Street, Irkutsk 664074, Russian Federation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_33
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Keywords Railroad power supply systems · Distributed generation plants · Synchronous generators · Automatic voltage controller · Automatic speed controller · Prognostic controllers · Power quality · Modeling
1 Introduction The problem of improving the electric power quality in power supply systems (PSS) supplied from traction substations is relevant for the contemporary transport power engineering [1, 2]. One of the most effective ways to solve it in the PSS of on-site facilities supplied from the district windings of 6–10–35 kV traction transformers is in the use of smart grid technologies, an important segment of which are automatically controlled distributed generation (DG) plants connected near the power consumers [3, 4]. Under the conditions of digitalization of the power engineering [5, 6], the design and implementation of DG plants should be based on computer models [7, 8]. DG plants operating on the basis of synchronous generators (SG) allow to develop a sufficiently high power. The efficiency of SG operation depends on the setting of rotor automatic voltage controllers (AVC) and automatic speed controllers (ASC). There are many methods of setting and algorithms of SG controllers functioning [9–15]. However, their impact on power quality factors (PQF) is not sufficiently studied. Below are the results of studies aimed at determining the effectiveness of using DG plants to improve the power in power supply systems, supplied from mainline railroads’ traction substations. At the same time, the influence of DG plants prognostic controllers on PQF and quality of control processes was evaluated.
2 Materials and Methods The simulation was performed in MATLAB environment for the railroad power supply system (RPSS), a fragment of which is provided in Fig. 1. Transient processes caused by connecting the traction load, which resulted in a deterioration of the PQF, were studied. The modes were simulated when the direct current link (DCL) was switched on and switched off with the connection of the DG plant with the traction substation through the bypass. In the course of simulation, special attention was paid to the influence of predictive algorithms [14] in AVC and ASC on the indicators of transient process and PQF in the PSS. The following were used as PQF: negative sequence asymmetry factor k 2U ; total harmonics coefficients k U .
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Fig. 1 The investigated power supply scheme: VT—voltage transformer; EW—excitation winding; SS—speed sensor; B—breaker
The schematic diagram of the PSS model under study in MATLAB is provided in Fig. 2. The turbogenerator model was used as the DG plant, the parameters of which are presented in the synchronous machine model setup window in Fig. 3. The steam turbine was simulated by the first-order aperiodic link with time constant of 0.2 s and a limiting unit. The model is defined with respect to the input signal of the shutter position and the output signal–mechanical power on the turbine shaft. Excitation thyristor system model (Excitation System unit in Fig. 2) was created based on equations describing thyristor converter and input amplifier. The corresponding Simulink-model scheme is shown in Fig. 4. The thyristor exciter is simulated by the first-order aperiodic link model with a coefficient Ke , a time constant Te and a voltage limiting unit (Fig. 4). The following numerical values of the parameters were accepted in modeling: Ke = 1; Te = 0.025 s. To control the DG plant, models of classical AVC and ASC [13], using the proportional-integral-differential (PID) control law, as well as prognostic AVC and auto prognostic ASC [14] were used.
Fig. 2 The schematic diagram of the PSS model under study in MATLAB
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Fig. 3 Parameter window of the synchronous turbogenerator model
1 Uare
1 Te.s+Ke Exciter
1 limit
Vf
Fig. 4 The generator excitation system model diagram of DG plant
3 Results The study was conducted for the mode of connection of an additional traction load on 27.5 kV busbars. In this case, the load power of the DG plant varied. Measurements of all PQFs were performed in network and the DG plant’s steady-state operating mode. Measurements were carried out for the most critical power quality indicators in the RPSS–total voltage harmonic factors k U and negative sequence asymmetry factor k 2U , %. The power of an additional traction load was increased from 2.76 to 25.15 MV · A. Such power changes are possible when heavy trains move along the mountain pass sections.
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The simulation results are presented in the form of oscillograms of rotor speed and generator voltage of the DG plant when using different controllers (Figs. 5 and 6), as well as in Table 1, which shows the change in power quality factors when varying DG plant load.
Fig. 5 Oscillograms of the DG plant’s generator rotor speed: 1—classical non-concordantly configured AVC and ASC; 2—classical concordantly configured ASC and AVC; 3—prognostic concordantly configured ASC and AVC
Fig. 6 Voltage oscillograms on non-traction consumer busbars when connecting an additional traction load: a classical non-concordantly configured AVC and ASC; b classical concordantly configured ASC and AVC; c prognostic concordantly configured ASC and AVC; d DG plant is shut down
3.62 3.41 10.87
k UBC , % k UCA , % k 2U , %
Prognostic concordantly configured AVC and ASC
Classical concordantly configured AVC and ASC
3.30
3.62 3.41 10.87
k UCA , % k 2U , %
10.87
k 2U , % k UBC , %
3.41
k UCA , % 3.30
3.62
k UBC , %
k UAB , %
3.30
k UAB , %
0 k UAB , %
Classical non-concordantly configured AVC and ASC
9.05
3.13
3.42
3.17
9.57
4.21
4.84
5.24
9.62
6.42
5.01
5.71
10
9.05
3.14
3.42
3.18
9.47
6.03
5.85
6.27
9.38
7.30
5.04
6.54
30
9.05
3.14
3.42
3.19
9.42
8.73
10.97
13.92
9.30
10.77
10.24
14.46
50
9.05
3.14
3.42
3.19
9.37
9.89
15.30
14.72
9.28
12.20
16.35
22.04
60
Loading of DG plant turbogenerator k load , %
Power quality factors
Types of adjustment systems of DG generator
Table 1 Power quality factors on 6 kV busbars of non-traction consumer 80
9.06
3.15
3.42
3.20
9.29
17.98
26.39
16.09
9.20
14.51
18.71
23.30
90
9.06
3.15
3.42
3.20
9.34
21.13
29.54
17.31
9.21
15.15
22.69
24.98
100
9.06
3.16
3.42
3.21
9.34
21.28
32.73
19.96
9.21
15.30
22.94
25.14
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The loading value was determined by the factor kload =
100P , Pnom
where P is the actual generation power; Pnom is DG plant rated power.
4 Discussion The simulation results allow to make the following inferences: 1. The use of prognostic AVC and auto prognostic ASC when an additional traction load is connected, can significantly reduce the transient time, oscillability and the value of voltage and rotor speed overshoot of DG plant’s generator rotor compared with the classical controllers (Figs. 5 and 6). 2. In the absence of DG plant and the connection of additional traction load, the voltage on the non-traction consumer’s busbars cannot be maintained at the rated level (Fig. 6, d). 3. Increasing the load of the DG plant turbogenerator reduces the negative sequence voltage asymmetry factor k 2U , but at the same time, it increases the total coefficients of voltage curve harmonics k U (Table 1, Fig. 7). It is explained by the fact that at a large voltage asymmetry in the mains, the turbogenerator connected to it starts to generate additional harmonics. As the load of the turbine generator increases, the power of these harmonics also increases. 4. The use of prognostic AVC and ASC makes it possible to keep the PQF practically unchanged at a significant voltage imbalance and changes in the load of the turbine generator (Table 1, Fig. 7). In this case, at the beginning of turbogenerator loading (in the range k load from 0 to 15%) reduction in voltage asymmetry coefficient of the negative phase-sequence k 2U and total voltage harmonic coefficients is noted k U . Further loading of turbogenerator leads to a slight increase in these coefficients which does not deflate previous inferences. Thus, under conditions of significant voltage asymmetry, when additional powerful traction load is connected, DG plant’s load should be decreased. Application of prognostic controllers allows to significantly decrease total coefficients of mains voltage harmonics. Further studies should help to develop the sophistication of the simulated system’s scheme while using various DG plants. In addition, simulation of the operating mode of the PSS under study was performed when connecting non-traction consumers and DG plants through a direct current link (DCL); at that, prognostic controllers were used at the turbogenerator [14]. The simulation results allow us to conclude that the use of DCL virtually completely eliminates voltage asymmetry and harmonic distortions of the voltage curve. Power quality factors in this case were (for any load of turbogenerator): k UAB = 0.18%; k UBC = 0.23%; k UCA = 0.27%; k 2U = 0.096%. The use of DCL and prognostic
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Fig. 7 Dependencies of power quality factors on generator load: a classical non-concordantly configured AVC and ASC; b classical concordantly configured AVC and ASC; c prognostic concordantly configured AVC and ASC; d dependences of voltage unbalance factors by the negative sequence
AVC and ASC significantly reduces the oscillability and the magnitude of voltage and generator rotor speed overshoot of DG plant. The corresponding oscillograms are provided in Fig. 8. In conditions of significant voltage asymmetry in power supply system, it is recommended to connect DG plants and non-traction consumers plants when connecting a powerful traction load, using DC link which will allow to additionally connect a solar power plant, DC generators, energy storage units and other equipment to DC busbars. In general, the simulation results allow us to speak about the efficiency of DG plants application with prognostic controllers in power supply systems, supplied from mainline railroads’ traction substations. This efficiency is achieved by improvement of power quality and control quality indicators.
Fig. 8 Oscillograms of voltages a and the generator rotor speed b of DG plant, connected through a DCL, with an increase in traction load
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5 Conclusions The developed power supply system model can be used to solve practical issues associated with power quality improvement on 6–10–35 kV traction substations busbars that supply transport, industrial and housing and utilities on-site facilities. Based on simulation results the following conclusions can be made as to the efficiency of the controlled DG plants used in power supply systems supplied from mainline railroads’ traction substations: 1. DG plants can be used to improve PQF in PSS of non-traction consumers; in which case a special influence is exerted by concordant setting of DG plant generator’s AVC and ASC: total harmonic coefficients of voltage is reduced from 21 to 14%. AVC and ASC prognostic algorithms produce an additional effect for PQF improvement. However, the main effect is observed in control quality improvement. These effects are manifested in different loading of DG plant generator. 2. The application of prognostic controllers in DG plants allows to maintain the power quality factors at a virtually unchanged level in case of changes in the generator loading. 3. The application of DC link and prognostic controllers virtually fully eliminates voltage asymmetry and harmonic distortions of the voltage curve, significantly reduces oscillability and voltage overshoot value and DG plant’s rotor rotational frequency. Acknowledgements The research was carried out with financial support from a grant from the state assignment of the Ministry of Science and Higher Education of Russian Federation (project No. FZZS-2020-0039).
References 1. Feng C, Gao Z, Sun Y, Chen P (2021) Electric railway smart microgrid system with integration of multiple energy systems and power-quality improvement. Electr Power Syst Res 199:107459. https://doi.org/10.1016/j.epsr.2021.107459 2. Ji X, Wang H, He L (2021) New energy grid-connected power quality management system based on internet of things. Sustain Comput Inform Syst 30:100460. https://doi.org/10.1016/j. suscom.2020.100460 3. Rugthaicharoencheep N, Auchariyamet S (2012) Technical and economic impacts of distributed generation on distribution system. Int J Electr Comput Energ Electron Commun Eng 6(4):385–389. https://doi.org/10.5281/zenodo.1327636 4. Sikorski T, Rezmer J (2015) Distributed generation and its impact on power quality in lowvoltage distribution networks. Power Quality Issues in Distributed Generation. IntechOpen. https://doi.org/10.5772/61172 5. Park C, Cho S, Heo W (2021) Study on the future sign detection in areas of academic interest related to the digitalization of the energy industry. J Clean Prod 313:127801. https://doi.org/ 10.1016/j.jclepro.2021.127801
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6. Burda YD, Volkova IO, Gavrikova EV, Kosygina AV (2019) Digitalization and ways for the development of the electric energy industry with the participation of consumers: new challenges for shaping the investment climate. J Siberian Fed Univ Humanit Soc Sci 12(4):545–564. https:// doi.org/10.17516/1997-1370-0408. 7. Liere-Netheler I, Schuldt F, Maydell K, Agert C (2020) Simulation of incidental distributed generation curtailment to maximize the integration of renewable energy generation in power systems. Energies 16(13):1–22. https://doi.org/10.3390/en13164173 8. Bulatov YN, Cherepanov AV, Kryukov AV, Suslov KV (2020) Distributed generation in railroad power supply systems. Paper presented at the 3rd International Colloquium on Intelligent Grid Metrology (SMAGRIMET), Cavtat, Dubrovnik, Croatia, pp 54–60. IEEE. https://doi.org/10. 23919/SMAGRIMET48809.2020.9264013 9. Zhang J, Zhuang J, Du H, Wang S (2009) Self-organizing genetic algorithm based tuning of PID controllers. Inf Sci 179:1007–1018. https://doi.org/10.1016/j.ins.2008.11.038 10. Pikina GA, Pashchenko FF, Pashchenko AF (2020) Synthesis, research and comparative analysis of predictive control algorithms. In: International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon, pp 1–5. https://doi.org/10.1109/FarEastCon50 210.2020.9271646 11. Sedhom EB, Magdi ME-S, Ahmed YH, Abdulaziz SA (2020) Hierarchical control techniquebased harmony search optimization algorithm versus model predictive control for autonomous smart microgrids. Int J Electr Power Energy Syst 115:105511. https://doi.org/10.1016/j.ijepes. 2019.105511 12. Bulatov YN, Kryukov AV (2016) Optimization of automatic regulator settings of the distributed generation plants on the basis of genetic algorithm. Paper presented at the 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), IEEE Conference Publications, pp 1–6. https://doi.org/10.1109/ICIEAM.2016.7911456 13. Pashchenko F, Pikina G, Rodomanova Y (2017) Universal Searchless Method for Parametric Optimization of Predictive Algorithms. Paper presented at the 13th IEEE International Conference on Control & Automation, Macedonia, Ohrid, pp 952–957. https://doi.org/10.1109/ICCA. 2017.8003189 14. Bulatov YN, Kryukov AV, Nguyen VH (2018) Automatic prognostic regulators of distributed generators. Paper presented at the International Multi-Conference on Industrial Engineering and Modern Technologies, pp 1–4. https://doi.org/10.1109/FarEastCon.2018.8602718 15. Chen Y, Ma Y, Yun W (2013) Application of improved genetic algorithm in PID controller parameters optimization. Telkomnika 11(3):1524–1530. https://doi.org/10.11591/telkomnika. v11i3.2301
Increasing the Reliability of Diagnosing Power Transformers by Using a Defect Simulator Andrey Kuznetsov , Viktor Harlamov , Maria Volchanina , and Anton Gorlov
Abstract The article deals with the issues of diagnosing electrical engineering complexes. Technical solutions are proposed for the determination of defects in the insulation of high-voltage transformers by the presence of partial discharges recorded by the acoustic method. To increase the reliability of the determination of defects, their development in time, the use of a defect simulator is proposed. Performing measurements at different times of the year (winter, spring, summer, autumn), accompanied by seasonal temperature changes, leads to additional errors associated with a change in the properties of the transformer oil. The main idea of the technical solution is to simultaneously measure signals on a power transformer and a defect simulator. If, when the temperature changes, the value of the reference voltage on the defect simulator does not change, therefore, the defect does not develop in time, and the increase in amplitude is associated with changes in the properties of the transformer oil. If, with a change in the parameters of the acoustic signal, an increase in the reference voltage on the defect simulator is observed with a seasonal temperature change, then a defect in the diagnosed power transformer develops. Keywords Power supply system · Power transformer · Acoustic control · Defect simulator · Reliability increase
1 Introduction Power transformers (PT) are the main element in the equipment of the railway power supply system. The service life of the PT depends on the condition of the insulation inside the oil-filled tank. Aging of the insulation inside the PT tank occurs due to electrical, mechanical and thermal stresses. The consequences of these loads lead to the occurrence of partial discharges (PD) inside the PT, which must be detected in a timely manner, preventing the occurrence of emergency conditions. A. Kuznetsov (B) · V. Harlamov · M. Volchanina · A. Gorlov Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_34
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When diagnosing power transformers in the railway power supply system, a fairly large number of methods of electrical and non-destructive testing are used. The use of acoustic methods makes it possible to determine the presence of insulation defects during the operation of power transformers and to locate the places of their occurrence [1]. The use of acoustic monitoring means significantly increases the reliability and speed of the currently used chromatographic method for monitoring dissolved gases in transformer oil. A feature of the railway transport power supply system is the location of traction substations along the railway track. Operation of power transformers is carried out in open conditions. It is shown that for diagnosing power transformers it is advisable to use portable systems based on acoustic monitoring of partial discharges due to their high mobility and relative ease of installation.
2 Materials and Methods The paper proposes a device for determining defects in the insulation of power transformers by the presence of partial discharges recorded by the acoustic method using a defect simulator. To increase the reliability of the determination of defects, their development in time, it is proposed to use a defect simulator. Performing measurements at different times of the year (winter, spring, summer, autumn), accompanied by seasonal temperature changes, leads to additional errors associated with changes in the properties of transformer oil [2–7]. The analysis of the literature revealed the presence of a large number of works devoted to acoustic control and methods for diagnosing power transformers [8–14]. The use of a defect simulator in the proposed device is associated with simultaneous measurements of signals on the PT and the defect simulator [15]. If, when the temperature changes, the value of the reference voltage on the defect simulator does not change, therefore, the defect does not develop in time, and the increase in amplitude is associated with changes in the properties of the transformer oil. If, with a change in the parameters of the acoustic signal, an increase in the reference voltage on the defect simulator is observed with a seasonal temperature change, then the development of a defect in the diagnosed PT is observed. When using a defect simulator, the reliability of diagnosing defects and the dynamics of their change by the method of registering PDs with seasonal temperature changes for STs in operation in the open air outside industrial premises is increased. The proposed device for monitoring PT contains a winding temperature measuring unit; digital acoustic diagnostics unit; acoustic measuring transducers, block of calculation models (BCM), block of visualization of the monitored parameters of the transformer (BVMP). To compensate for temperature errors caused by seasonal temperature changes, changes in viscosity and attenuation coefficient during the propagation of acoustic waves, and as a consequence of a decrease in amplitude, frequency characteristics, waveform, a defect simulator unit was additionally introduced, containing an
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15 3
BVMP PS
4
5
EC
CIG
14
9
6
ST
BCM
11
PT 10
12
8
12
7
BDAD 13 1
OT
DS
2
Fig. 1 Diagram of a device for recording the parameters of partial discharges on a power transformer using a defect simulator
regulated DC power supply, an electronic switch, a clock pulse generator, a step-up transformer, an oil-filled tank, an electric spark gap, defect simulator temperature control unit, block for maintaining temperature in an oil-filled tank. In Fig. 1 shows a diagram of a device for recording the parameters of partial discharges on a power transformer using a defect simulator. The proposed device for registering PD parameters on a PT using a defect simulator (Fig. 1) contains a power transformer (PT) 1, a defect simulator unit (DS) 2, consisting of an regulated DC power supply (PS) 3, an electronic switch (EC) 4, a clock impulse generator (CIG) 5, a step-up transformer (ST) 6; an oil-filled tank (OT) 7; an electric spark gap (ES) 11, a defect simulator temperature control unit 8; block for maintaining the temperature in an oil-filled tank 13, block for measuring the temperature of the windings PT 9; block of digital acoustic diagnostics (BDAD) 10; acoustic measuring transducers 12, block of calculation models (BCM) 14, block of visualization of the monitored parameters of the transformer (BVMP) 15. In Fig. 2 shows the layout of the electric spark gap in the oil-filled tank of the defect simulator. Maintaining the oil temperature in the DS equal to the oil temperature of the diagnosed PT is carried out by the block for maintaining the temperature in the oil-filled tank 13. The device for monitoring power transformers (Fig. 1) works as follows. All main operating parameters of a power transformer are measured and controlled using blocks of measurement of primary parameters.
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Fig. 2 The layout of the electric spark gap in oil-filled tank: 16 – bracket; 17, 18 – electrical spark gaps; 19 – transformer oil
The block of digital acoustic diagnostics BDAD 10 provides acoustic control and continuous recording of the intensity of partial discharges, as well as the amplitude, phase and spatial coordinates of each impulse. The block of calculation models 14 according to measurements in real time based on information from the primary transducers, the block for measuring the temperature of the windings PT 9; block of digital acoustic diagnostics (BDAD) 10 calculates the service life of the power transformer and the aging rate of the insulation. The block of visualization of the monitored parameters 15 provides the operator with the ability to conveniently work with the current, archived and calculated values of the operating parameters in the form of tables and/or graphs. Diagnostic information is stored for a long time and allows for the conclusions about the development of defects.
3 Results The proposed defect simulator 2 allows reproducing partial discharge (PD) pulses, similar to impulses recorded from defects of the diagnosed transformer with different amplitude, phase and repetition rate. When implementing the differential measurement method, at the first stage, partial discharge impulses are recorded on the diagnosed PT 1 using acoustic sensors 12, then these sensors are transferred to the oilfilled tank 7 as part of the DS, and partial discharges formed by the electric spark gap 11 are recorded. On the regulated DC power supply (PS) 3, a voltage is set corresponding to the threshold for the occurrence of partial discharges. This voltage is applied to the electronic switch 4, which is controlled by the clock impulse generator 5 with a frequency corresponding to the PD repetition rate on the diagnosed PT 1. From the output of the step-up transformer 6, high-voltage impulses are sent to the
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electric spark gap 11 causing PD. By regulating the reference voltage on the PS, the same PD amplitude recorded on the PT and DS is achieved, and this value is stored. With seasonal changes in temperature, the oil in power transformers used in the open air changes its properties. The viscosity of the oil changes [2], and, consequently, the phase and attenuation coefficients change during the propagation of acoustic waves [5], which in turn affects the parameters of acoustic impulses recorded by the measuring equipment. Real component of propagation constant [1/m]: k=
ω . Vl
(1)
Is the phase coefficient, allowing to calculate the change in wavelength, and the imaginary part is the attenuation coefficient, which can be calculated by the formula, [1/m]: α=
4 b ω2 ω2 1 1 η + η = + x − cv cp 2ρ0 Vl3 2ρ0 Vl3 3
(2)
where η—shear (transverse) viscosity coefficient [Pa · s]; η—volumetric viscosity coefficient [Pa · s]; x—heat conduction coefficient [W /( m · K)]; cv —gas specific heat at constant volume [J/(kg · K)]; c p —gas specific heat at constant pressure [J/(kg · K)]. The main reason for the attenuation of acoustic waves is the force of viscous resistance between neighboring particles of the medium with different rate, it is taken into account by the first term in expression (4). The article describes a defect simulator device, designed to generate signals similar to recorded acoustic signals in diagnostic systems for high-voltage oil-filled equipment using the example of power transformers. The proposed defect simulator is advisable to use with modern PT diagnostic systems, which include acoustic control units. Table 1 shows an example of diagnostic data for seasonal temperature changes from +20 to –10 °C. When diagnosing a power transformer using a defect simulator, the reference voltage of the power supply is recorded. In the second and third columns, an increase in the amplitude of partial discharges is observed with a seasonal temperature change from 100 to 150 units. ADC. Both values were recorded at the same value of Ur = 5.5 V, which allows us to assume that the energy of high-voltage pulses causing PD remains constant. Therefore, an increase in defects is not observed, and an increase in amplitude is associated with seasonal temperature changes and changes in the properties of transformer oil. In the second and fourth columns, an increase in the PD amplitude is also observed with seasonal temperature changes from 100 to 150 units. ADC, however, these values were recorded at different values of Ur1 = 5.5 V and Ur2 = 6.8 V, which suggests that the energy of high-voltage pulses causing PD increases, therefore, an
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Table 1 Comparison of signals on a power transformer and a defect simulator with seasonal temperature changes Power transformer Amplitude, units ADC
100
150
150
Frequency, kHz
200
150
150
Duration, μs
30
20
20
Temperature, °C
+20
−10
−10
Reference voltage, V
5,5
5,5
6,8
Amplitude, units ADC
100
150
150
Frequency, kHz
200
150
150
Duration, μs
30
20
20
Temperature, °C
+20
−10
−10
Defect simulator
increase in the insulation defect is observed, and the increase in amplitude is primarily associated with an increase in the defect and, to a lesser extent, with a change in the properties of the transformer oil.
4 Conclusion An increase in the reliability of monitoring the condition of the transformer is confirmed with seasonal temperature changes. Simultaneous measurements of signals on the PT and the defect simulator are performed. On the data of full-scale measurements, it was shown that if the value of the reference voltage on the defect simulator did not change with a change in temperature, it meant that the defect did not develop in time, and the increase in amplitude was associated with changes in the properties of the transformer oil. In the case when, with a change in the parameters of the acoustic signal, an increase in the reference voltage on the defect simulator was observed with a seasonal temperature change, this meant that a defect in the diagnosed ST was observed. Acknowledgments The study was carried out with the financial support of the Russian Foundation for Basic Research within the framework of the scientific project No. 20-38-90,231.
References 1. Karandaev AS, Evdokimov SA, Sarlybaev AA, Lednov RA (2013) Requirements to the monitoring system of ultrahigh power electric arc furnace transformer performance. Russ Internet J Ind Eng 2:58–68. https://doi.org/10.24892/RIJIE/20130209
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2. Karandaev AS, Evdokimov SA, Khramshin VR, Sarlybayev AA (2015) System for real-time monitoring of the technical state of a transformer on an ultrahigh-power electric-arc steelmaking furnace. Metallurgist 58(9–10):872–879. https://doi.org/10.1007/s11015-015-0010-z 3. Khramshin VR, Karandaev AS, Khramshin RR, Evdokimov SA, Sarlybaev AA, Nikolaev AA: Monitoring device for power transformers, RU Patent No. 2615790, Bull. Isobr. No. 1. pub. 11.04.2017 4. Gastelurrutia J, Ramos JC, Larraona GS, Rivas A, Izagirre J, Río L (2011) Numerical modelling of natural convection of oil inside distribution transformers. Appl Therm Eng 4(31):493–505. https://doi.org/10.1016/j.applthermaleng.2010.10.004 5. Taha Ibrahim BM, Dessouky Sobhy S, Ghaly Ramy NR, Ghoneim Sherif SM (2020) Enhanced partial discharge location determination for trans-former insulating oils considering allocations and uncertainties of acoustic measurements. Alex Eng J 6(59):4759–4769. https://doi.org/10. 1016/j.aej.2020.08.041 6. Cheremisin VT, Kuznetsov AA, Volchanina MA, Gorlov AV (2020) Measuring the acoustic signals parameters of the defect simulator of power transformers. Transp Syst Technol 6(4):161–171. https://doi.org/10.17816/transsyst202064161-171 7. Strachan SM, Rudd S, McArthur SDJ, Judd MD, Meijer S, Gulski E (2008) Knowledgebased diagnosis of partial discharges in power transformers. IEEE Trans Dielectr Electr Insul 15(1):259–268. https://doi.org/10.1109/T-DEI.2008.4446759 8. Markalous SM, Tenbohlen S, Feser K (2008) Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals. IEEE Trans Dielectr Electr Insul 15(6):1576–1583. https://doi.org/10.1109/TDEI.2008.4712660 9. Jitjinga P, Suwanasrib T, Suwanasrib C (2016) The design of electrode for partial discharge location simulation in oil insulated power transformer and the application of AE method. Procedia Comput Sci 86:289–292 10. Kunickia M, Boruckia S, Zmarzłya D, Frymusb J (2020) Data acquisition system for on-line temperature monitoring in power transformers. Measurement 161:107909 11. Liu H-L (2016) Acoustic partial discharge localization methodology in power transformers employing the quantum genetic algorithm. Appl Acoust 102:71–78. https://doi.org/10.1016/j. apacoust.2015.08.011 12. He X, Xie G, Jiang Y (2011) Online partial discharge detection and location system using wireless sensor network. Energy Procedia 12:420–428 13. Deshpande A, Mangalvedekar H, Cheeran A (2013) Partial discharge analysis using energy patterns. Electr Power Energy Syst 53(1):184–195 14. Hekmati A (2015) Proposed method of partial discharge allocation with acoustic emission sensors within power transformers. Appl Acoust 100:26–33 15. Karandaev AS, Evdokimov SA, Devyatov DK, Parsunkin BN, Sarlybayev AA (2012) Diagnostics of power transformers by the method of acoustic location of partial discharges. Vestnik MSTU 1:105–108. https://doi.org/10.24892/RIJIE/20130209
Energy Intensity and Energy Efficiency of Energy Saving Policy of Railway Transport Dmitry Rozhitsky , Alexey Rybak , Irina Krasnova , Aleksandr Komyakov , and Mikhail Nikiforov
Abstract The paper considers the possibility of using the method of analyzing the production energy intensity and specific energy efficiency of the Central Directorate for Heat and Water Supply on the example of one of its regional divisions. The proposed method makes it possible to calculate the key energy efficiency indicators for multifunctional industries in order to assess the effectiveness of the energy saving policy for a selected period of time without considering any individual measures. The proposed method consists of determining the energy efficiency indicators based on the main production indicators of the structural unit. They are the consumption of all types of consumed fuel and energy resources (boiler and furnace fuel, electric power, heat energy from external suppliers), water resources and the volume of received streamflow, payroll budget and some others. The calculation is made for each line of production activity. Gorky Directorate for Heat and Water Supply was chosen as a case study. The conducted analysis resulted in obtaining the necessary initial data and making calculations used for further assessment of the effectiveness of fuel and energy resources and a number of energy saving measures taken by the directorate from 2015 to 2019. The paper shows how the approach to determine the energy intensity and specific energy efficiency of multifunctional industries can be applied. Keywords Energy intensity · Energy efficiency · Heat supply · Water supply · Water discharge
D. Rozhitsky (B) · I. Krasnova Russian University of Transport, 22/2, Chasovaya Street, 125190 Moscow, Russia e-mail: [email protected] A. Rybak Railway Research Institute of JSC Russian Railways, 10 3rd Mytischinskaya Street, 129851 Moscow, Russia A. Komyakov · M. Nikiforov Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_35
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1 Introduction Improving energy efficiency is one of the country’s priorities caused by the high energy intensity of various industries. According to Energy Strategy of the Russian Federation, “the energy intensity of the Russian economy decreased by 9.3% from 2008 to 2018 (from 10.8 to 9.8 toe/mln. RUB of gross domestic product for the 2016 prices). The main factors of reducing energy intensity were the processing factor (the increase in energy efficiency of energy consuming equipment) and the operating rate. In order to reduce the energy intensity of their products, almost all Russian companies develop and implement energy saving and energy efficiency improvement programs. Global environmental trends make enhancing energy saving policies mandatory. Currently, mostly the low carbon footprint, i.e. minimal negative impact on the environment, makes the industry attractive for the investors. There are several ways to determine energy intensity at present. Thus, to assess the changes in the energy consumption of an industry as a result of introducing energy saving measures in Russia, it is recommended to use the approach mentioned in GOST R 56,743-2015: – isolation of the modernization zone: the measurement of the main parameter (energy conservation is determined by direct measurements of the main operation parameter, which impacts the consumption of energy resources); – the isolation of the modernization zone: measurement of all the parameters (this method measures the energy consumption of the system participating in the project); – the entire facility (the energy conservation is determined by measuring the consumption of energy resources on the entire facility or part of the facility); – computer modeling (the energy conservation is determined by simulating the consumption of energy resources by the entire facility or part of the facility). Methods for assessing industrial energy intensity based on the ISO 50001 standard are quite common. Yuhui Jin etc. in [1] and Bojana Jovanovi´c in [2] evaluate energy efficiency using maturity ratings. Giuliano Dall’O’ etc. in [3] and Alberto Fichera etc. in [4] proposed an equation for estimating the annual energy consumption of the heating system of buildings and regression equations for control charts. Bhaskaran Gopalakrishnan etc. proposed a structured approach for facilitating the implementation of ISO 50001 standard in the manufacturing sector using ISO 50001 Analyzer [5]. Libo Wu etc. proposed methods for assessing energy efficiency achievements in the transport sector [6]. Comparing changes in energy intensity allows you to promptly respond to negative trends and make appropriate engineering, organizational, technical and strategic management decisions. In this case, practice or external benchmarking methods can be used for analysis [7, 8]. JSC “Russian Railways” is one of the largest consumers of fuel and energy resources in the country. Railway transport units annually consume about 1300 thousand tons of boiler and furnace fuel by imputation only to meet non-traction needs
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such as generating thermal energy for both production and utility consumers of linear units. The structural divisions of the company’s specialized branch, i.e. the Central Directorate for Heat and Water Supply (hereinafter referred to as CDHWS), are the main consumers of this resource. Besides producing and transportating thermal energy, the CDHWS also provides water supply and water discharge. Within the “Energy Saving and Energy Efficiency Improvement Program of JSC “Russian Railways”, a number of energy saving measures are being taken for each functional area. Due to such versatile nature of production activities, the assessment of their effectiveness for the regional divisions of the CDHWS has always been hugely discussed since there was no unanimous approach to solving this problem for multifunctional units. The purpose of this article is to develop an approach providing an objective and reliable assessment of the energy intensity of CDHWS with the special character of its production taken into account.
2 Materials and Methods To solve this problem, “Methodology for determining the energy intensity and specific energy efficiency of the production activities of the Central Directorate for Heat and Water Supply” was developed. This methodology divides the production activity into separate lines thus calculating energy efficiency indicators separately for each of them. Calculations can be made at any level of management: linear, regional, the entire branch. The production energy intensity in terms of operation and providing such services to the consumers as heat supply (output and transportation of thermal energy) for reference (base) year, MJ/GCAL, is determined by the formula: 29, 31 · 103 · ( E IH S =
i
B H S i · E i + γ B H S oth ·
B H S i · E i ) + 3, 6 · (W H S + γ B H S oth · Woth )
i
Q gen
(1)
where B H S i is the volume of fuel and energy resources consumption of i-type (except for electric power) needed for the generation of heat; both the meter and the volume of consumption is determined by form ATE-1 “Report on heat supply and water discharge” approved by the Order of JSC “Russian Railways”; 29.31—conversion factor of the volume of fuel and energy resources consumption (kgoe) into the units of energy (MJ); W H S —the volume of consumption of electric power (with no loss) for the output and transportation of thermal energy, ths kWh; is determined by Form 4-fuel “Report on balances, delivery and consumption of fuel” approved by the Order of JSC “Russian Railways”; B H S i —the consumption of i-type motor fuel when maintaining and repairing the heat, water supply and water discharge (other consumption of fuel and energy resources) networks, t;
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Woth —the volume of consumption of electric power (with no loss) when maintaining heat, water supply and water discharge networks and other utility needs (other consumption of fuel and energy resources), ths kWh; is calculated as the difference between the overall consumption of electric power and the industrial electric power consumption; 3.6—the conversion factor of electric power consumption in physical units of measurement (kW · h) into units of energy (MJ); Q gen —the amount of domestic heat provided to the facilities of the structural divisions of JSC “Russian Railways” and to the third parties (including the loss at heat networks before the heat reaches the interface region of balance sheet attribution), and power-plant consumption, Gcal; γ B H S oth —the share in other consumption of fuel and energy resources conditionally attributed to the maintenance of the domestic facilities of heat supply; E i —the heat equivalent used to convert the units of i-type fuel and energy resources in physical units of measurement into the units of reference fuel; for certain types of fuel and energy resources and grades of coal it is taken as reference data. When several grades of coal are used, the weighted average value of its thermal equivalent is determined by the formula: E Coal av =
Bcoal j · E coal j
j
Bcoal j
(2)
j
where: Bcoal j —the volume of consumption of j-grade coal for all types of activities and use (excluding sales to external organizations and individuals as fuel for utility needs), t; E coal j —the thermal equivalent of j-grade coal. The share of fuel and energy consumption of all types conditionally attributed to the maintenance of heat supply facilities for the reference year is determined by the formula: γ B H S oth = PH S /(PH S + PW S + PW D )
(3)
where PH S , PW S , PW D is the amount of the payroll budget for the employees servicing heat supply, water supply and water discharge facilities, RU. The specific energy efficiency of production activities in terms of such services to the consumers as the output and transportation of thermal energy, Gcal/MJ is determined by the formula: E EHS =
29.31 · 103 · (
i
B H S i · E i + γ B H S oth ·
Q gen B H S i · E i ) + 3.6 · (W H S + γ B H S oth · Woth ) i
(4)
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The energy intensity of production activities in terms of such services provided to the consumers as the output and transportation of water, MJ/m3 is determined by the formula: Both i · E i 3.6 · (WW S + γ BW S oth · Woth i ) + 29.31 · 103 · i (5) E IW S = VW S where WW S —the consumption rate of electric power (with no loss) allocated to the output and transportation of water, ths kW · h; γ BW S oth —the share of fuel and energy resources consumption conditionally attributed to the maintenance of water supply facilities respectively, for the current or reference year; Woth i —the consumption rate of electric power (with no loss) when providing maintenance of networks of heat, water supply and water discharge and other utility needs (other consumption of fuel and energy resources), ths kWh; is calculated as the difference between the overall consumption of electric power and the electric power consumption for production operation; Both i —the consumption of i-type motor fuel used for maintenance and repair of networks of heat, water supply and water discharge (other consumption of fuel and energy resources), t; VW S —the volume of the water generated domestically and provided to the structural divisions of JSC “Russian Railways” and external consumers, and also consumed for internal purposes, m3 . The share of fuel and energy consumption of all types, conditionally attributed to the maintenance of water supply facilities is calculated by the formula: γ BW S oth = PW S /(PH S + PW S + PW D )
(6)
The specific energy efficiency of production activities in terms of such services provided to the consumers as the output and transportation of water, m3 /MJ, is determined by the formula: E EW S =
3.6 · (WW S + γ BW S oth
VW S · Woth i ) + 29.31 · 103 · Bothi · E i
(7)
i
The energy intensity of production activities in terms of such services to the consumers as the transportation and treatment of wastewater, MJ/m3 is determined by the formula: 3.6 · (WW D + γ BW D oth · Woth i ) + 29.31 · 103 · E IW D =
i
VW D
Bothi · E i (8)
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where WW D is electric power consumption rate (with no loss) attributed to the transportation and treatment of wastewater, ths kWh; γ BW D oth —the share of fuel and energy consumption conditionally attributed to the maintenance of wastewater disposal facilities; VW D —the volume of wastewater discharged to its own treatment facilities, m3 . The share of fuel and energy consumption of all types conditionally attributed to the maintenance of wastewater disposal facilities is calculated by the formula: γ BW D oth = PW D /(PH S + PW S + PW D )
(9)
The specific energy efficiency of production activities in terms of such services provided to consumers as the transportation and treatment of wastewater for the reference year, m3 /MJ, is determined by the formula: E EW D =
VW D 3.6 · (WW D + γ BW D oth · Woth i ) + 29.31 · 103 · Bothi · E i
(10)
i
The advantage of the proposed methodology is the ability to analyze the results of activities for the whole department during certain time periods without taking into account local calculations for each activity aimed at improving energy efficiency and reducing energy intensity.
3 Results The data were collected and calculations were made on the case study of Gorky Directorate for Heat and Water Supply (hereinafter referred to as Directorate) to verify the proposed approach in operation. The Directorate manages a complex of stationary heat power, water supply and water discharge facilities at Gorky Railway operating domain and owns 104 boiler stations using various types of boiler and furnace fuel (coal and ligneous coal, residual fuel oil, natural gas, in addition, with part of the electric power used to generate thermal energy), over 220 km of single-pipe heating networks, 100 km of sewerage systems. The list the directorate consumers includes more than 500 facilities of the company’s structural divisions and a number of facilities of external organizations and housing and utility complex. The main tool for reducing fuel and energy consumption was the implementation of the “Resource Saving and Energy Efficiency Improvement Program of JSC “Russian Railways”, whose main targets are: a set of measures to improve the efficiency of heating systems and heating networks (cleansing and adjusting of heat supply systems, replacing shut-off and control valves); modernization of boiler equipment; optimization of heat generating equipment operation; supply and installation of new
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solid fuel systems; optimization of operation modes of lighting systems; modernization and replacement of engineering equipment; optimization of the operation modes of official vehicles; replacement of pumping units with long service life for modern ones; modernization of boiler stations with steam boilers; replacement of heating boilers with excess service life; carrying out hydro-mechanical cleansing of water supply and water discharge networks installation of frequency controlled drives and soft start devices on electric installations of heat supply, water supply and water discharge facilities; replacement of steel pipelines used in heat, water supply and water discharge networks for the pipelines made of modern polymer materials. The experience of implementing these measures suggests that they are quite effective [9–15]. In accordance with (1)–(10), further calculations were made for each of the Directorate’s production activities. The results obtained for 2015–2019 as for the calculation of energy intensity and energy efficiency for each of the Directorate’s production activities are shown in Figs. 1 and 2.
Energy efficiency
MJ/Gcal 5,750
5,739
180.2 5709
5,700 5,650
5,550
177.0 5601
5608
5,600
179.0
178.5
178.3
175.0
175.2
174.2
183.0 Gcal×10-6 181.0 MJ
5549
5,500
173.0
Energyefficiency
5,800
171.0 2015
2016
2017
2018
2019
Energy efficiency
Fig. 1 Changes in energy intensity and energy efficiency of the Directorate’s production activities in terms of such services provided to the consumers as for the output and transportation of thermal energy 60.0 m3 50.0 GJ
51.7 43.3
Water output and transportation
40.0 37.5
30.0 20.0 10.0
28.8
29.8
Wastewater transportation and cleansing
10.5
10.7
11.2
11.4
12.9
2015
2016
2017
2018
2019
0.0
Fig. 2 Changes in energy efficiency of the Directorate’s production activities in terms of such services provided to consumers as the output and transportation of water and the transportation and treatment of wastewater
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4 Discussion The analysis of the results shows that the engineering policy of increasing energy efficiency and reducing energy intensity in the Directorate during the analyzed period resulted in the following. Energy intensity of production activities in terms of such services provided to the consumers as: the output and transportation of thermal energy has decreased by 190 MJ/Gcal or by 3.3%; water output and transportation has decreased by 15.3 MJ/m3 or by 44.3%; transportation and wastewater treatment has decreased by 18.3 MJ/m3 or by 19.11%. Specific energy efficiency of production activities in terms of such services provided to the consumers as: the output and transportation of thermal energy has increased by 6 Gcal *10–6/MJ or by 3.4%; water output and transportation increased by 22.9 m3 /GJ or 79.5%; water discharge, transportation and wastewater treatment has increased by 2 m3 /GJ or by 22.9%.
5 Conclusion As a conclusion, the following points can be noted: 1. A performance check of the “Methodology for determining the energy intensity and specific energy efficiency of the Central Directorate production activities for Heat and Water Supply” was carried out on the example of one of the regional divisions. 2. The initial data were collected and calculations were made for such production activities as heat supply, water supply and water discharge. Calculations were made for the period of 2015–2019 to determine the energy intensity of production activities and specific energy efficiency. Thus, the energy intensity and specific energy efficiency in terms of heat supply for the controlled period have changed by 3.3 and 3.4% respectively, and the similar indicators for water supply and water discharge have bigger values. The latter can be explained by a change in engineering policy when fuel and energy consumption for these needs is considered, i.e. the so-called low base effect; in future these indicators should reasonably grow (decrease) of 1–2% per year. 3. The obtained results confirm the applicability of this approach both for assessing energy intensity and specific energy efficiency of multifunctional production units (heat supply, water supply and water discharge).
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References 1. Jin Y et al (2021) An energy management maturity model for China: linking ISO 50001:2018 and domestic practices. J Clean Prod 290:125168. https://doi.org/10.1016/j.jclepro.2020. 125168 2. Jovanovi´c B, Filipovi´c J (2016) ISO 50001 standard-based energy management maturity model–proposal and validation in industry. J Clean Prod 112(4):2744–2755. ISSN 0959-6526. https://doi.org/10.1016/j.jclepro.2015.10.023 3. Dall’O’ G, Ferrari S, Bruni E, Bramonti L (2020) Effective implementation of ISO 50001: a case study on energy management for heating load reduction for a social building stock in Northern Italy. Energy Build 219:110029. ISSN 0378-7788. https://doi.org/10.1016/j.enbuild. 2020.110029 4. Fichera A, Volpe R, Cutore E (2020) Energy performance measurement, monitoring and control for buildings of public organizations: standardized practices compliant with the ISO 50001 and ISO 50006. Dev Built Environ 4:100024. ISSN 2666–1659. https://doi.org/10.1016/j.dibe. 2020.100024 5. Gopalakrishnan B, Ramamoorthy K, Crowe E, Chaudhari S, Latif H (2014) A structured approach for facilitating the implementation of ISO 50001 standard in the manufacturing sector. Sustain Energy Technol Assess 7:154–165. ISSN 2213-1388. https://doi.org/10.1016/j.seta. 2014.04.006 6. Wu L, Huo H (2014) Energy efficiency achievements in China’s industrial and transport sectors: how do they rate? Energy Policy 73:38–46. ISSN 0301-4215. https://doi.org/10.1016/j.enpol. 2014.05.039 7. Yang X et al (2022) Energy-saving potential prediction models for large-scale building: a stateof-the-art review. Renew Sustain Energy Rev 156:111992. ISSN 1364-0321. https://doi.org/ 10.1016/j.rser.2021.111992 8. Komyakov AA, Legchilina EY, Tkachenko Z, Chulembayev A (2021) Approaches to assessing the impact of transformation of professional competencies of the staff on the energy efficiency of railway transport enterprises. Herald Ural State Univ Railw Transp 2(50):57–66. https://doi. org/10.20291/2079-0392-2021-2-57-66 9. Redko I, Ujma A, Redko A, Pavlovskiy S, Redko O, Burda Y (2021) Energy efficiency of buildings in the cities of Ukraine under the conditions of sustainable development of centralized heat supply systems. Energy Build 247:110947. ISSN 0378-7788. https://doi.org/10.1016/j.enb uild.2021.110947 10. Kazarinov LS, Kolesnikova OV, Tsypkaikina AD (2018) A method for steam boilers load optimization. IFAC-PapersOnLine 51(32):765–769. ISSN 2405-8963. https://doi.org/10.1016/ j.ifacol.2018.11.453 11. Lin H, Clavreul J, Jeandaux C, Crawley J, Butnar I (2021) Environmental life cycle assessment of heating systems in the UK: comparative assessment of hybrid heat pumps vs. condensing gas boilers. Energy Build 240:110865. ISSN 0378-7788. https://doi.org/10.1016/j.enbuild.2021. 110865 12. Camaraza-Medina Y, Retirado-Mediaceja Y, Hernandez-Guerrero A, Luis Luviano-Ortiz J (2021) Energy efficiency indicators of the steam boiler in a power plant of Cuba. Therm Sci Eng Progress 23:100880. ISSN 2451-9049. https://doi.org/10.1016/j.tsep.2021.100880 13. Il-Hak S, Jong-Ho L, Jae-Weon J (2021) Energy efficiency and economic analysis of variable frequency drive and variable pitch system: a case study of axial fan in hospital. J Build Eng 43:103213. ISSN 2352-7102. https://doi.org/10.1016/j.jobe.2021.103213 14. Duan M, Ramani KS, Okwudire ChE (2020) Energy optimal control of an over-actuated hybrid feed drive under variable-frequency disturbances—with application to machining. Control Eng Pract 100:104442. ISSN 0967-0661. https://doi.org/10.1016/j.conengprac.2020.104442 15. Alabtah FG, Mahdi E, Eliyan FF (2021) The use of fiber reinforced polymeric composites in pipelines: a review. Compos Struct 276:114595. ISSN 0263-8223. https://doi.org/10.1016/j. compstruct.2021.114595
Production of Au Nanoparticles by Laser Ablation in Liquids Dmitry Melnikov , Olga Lutikova , Polina Gubareva, Maria Melnikova , and Kirill Fomichenko
Abstract In this paper, the technological aspects of gold nanoparticles producing by laser ablation in liquids were studied. The ambiguous effect of the laser pulse energy, the duration of radiation, and the size of the cuvette with liquid on the process was estimated. It was shown that reaching optimal process performance with the required dispersion is a compromise, to achieve it is necessary to accurately control these parameters. An increase in energy density increases productivity, but reduces the stability of the solution and leads to particle sticking. Long-term irradiation of the target in a constant volume of liquid makes it possible to increase the concentration of the solution, which is useful for subsequent drying of the solution to a nanoparticles but reduces the efficiency of the process and negatively affects the dispersion. Nanoparticles that are already generated after previous pulses, firstly, absorb laser radiation, and secondly, they heat up and can coagulate. This effect was demonstrated by the results of measuring the growth rate of the extinction coefficient at various cell volumes. Keywords Nanoparticles · Laser ablation · Gold nanoparticles · Light extinction
1 Introduction Currently, the use of nanomaterials has shown significant efficiency in the solution of various scientific, medical and industrial problems. Nanoparticles are one of the most widely used nanomaterials due to the relative simplicity of synthesis and predictability of properties. The range of their applications covers photonics [1, 2], superconductors [3], sensitizers [4], photocatalyst [5], additive materials [6], raw optical materials [7, 8], as well as medical research [9–11]. Despite the simplicity D. Melnikov (B) · O. Lutikova · P. Gubareva · M. Melnikova Bauman Moscow State Technical University, 2nd Baumanskaya Street, 5, 105005 Moscow, Russia e-mail: [email protected] K. Fomichenko Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_36
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Fig. 1 Scheme of the experiment setup for the synthesis of nanoparticles by laser ablation in a liquid: 1 – Q-switched Nd:YVO4 laser 532 nm, 2 – F-theta lens, 3 – cuvette with a liquid, 4 – synthesized nanoparticles, 5 – gold target
of the form and, often, the composition, nanoparticles strongly differ in their properties from macromaterials [12], which, on the one hand, makes their application promising, and on the other hand, requires a large number of studies concerning both their operational properties and conditions of their synthesis. There are various methods for the synthesis of nanoparticles, among which physical and chemical ones can be distinguished [13]. Among them, laser ablation in a liquid is distinguished separately, in which concentrated energy flows are used. It allows the synthesis of nanomaterials of various compositions, including noble metals, in various solutions The process of laser ablation in a liquid, a schematic diagram of which is shown in Fig. 1, is quite flexible, ecological, and easy to automate. Its application made it feasible to control the characteristics of particles directly in the generation process. [14] One of the problems of the method is the repeatability and stability of the solution over time [15, 16]. The process of nanoparticle synthesis itself takes a certain amount of time. During this time, under typical irradiation conditions [9, 12], the target is in a cuvette with a liquid, where laser radiation activates the ablation mode. One of the problems encountered in the manufacture of nanoparticles is the re-irradiation of existing nanoparticles. This problem is associated with the limited capabilities of existing flow-type laser installations [17]. Such repeated ablation leads to a size and properties changings of the nanoparticles. The degree of re-irradiation depends on the distribution of particles in the cuvette, which is not uniform without forced mixing. For these reasons, the repeatability of the method is not very high. To increase it, additional research should be conducted.
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Despite the apparent simplicity of the method for laser synthesis of nanoparticles, a number of difficulties can be encountered in the development of a specific technology. It is necessary to associate the process parameters with the required particle sizes, the stability of the method, as well as productivity. Today there are many scientific papers that differ in their fundamental approach to the synthesis of nanoparticles [18–21], but they pay little attention to technological issues. In this paper, aspects of process productivity control are examined, as well as the determination of important factors that increase the stability of the obtained nanoparticles.
2 Materials and Methods The experimental design is shown in Fig. 1. The target was placed in a quartz cuvette with distilled water. The second-harmonic radiation of a Q-switched Nd:YVO4 laser was focused on the target and scanned along its surface. Based on the typical dynamics of the development of a cavitation bubble during laser ablation in a liquid [7], the distance between the pulses in the lateral direction was 100 μm. A sample of pure gold (>99.9%) was used as a target. For the laser system used, the wavelength was 532 nm, the pulse duration was 5 ns, the pulse repetition rate was 2 kHz, and the pulse energy varied from 220 to 365 μJ. The parameters of the obtained colloidal solutions were measured using optical spectrometry. Since the peak of plasmon resonance for gold nanoparticles is at ~530 nm, the samples were transmitted through a spectrometer in the range from 350 to 700 nm. This approach allows reliably evaluate the optical properties of a colloidal solution and determine the size of the resulting nanoparticles [22]. In addition, the parameters of the obtained nanoparticles were measured using a method based on the Mie theory of compensation for spherical particles [23]. In this work, we used the Bluewave Microtrack equipment, which allows us to measure particle size in the range from 0.01 to 2800 microns.
3 Results 3.1 Number of Pulses The main factor that determines the productivity of the nanoparticles synthesis process by laser ablation in a liquid is the number of pulses per unit time for a certain volume of liquid. Number of laser pulses per sample determines the degree of irradiation of already synthesized nanoparticles, which means that it directly affects the results of work. In addition, the transmission of the laser radiation by the solution decreases with increasing gold concentration in the solution. This is especially
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Fig. 2 The growth dynamics of the extinction coefficient of a colloidal solution for a wavelength of 532 nm depending on the number of pulses during laser ablation in liquid
important when accepting the fact that the peak of plasmon resonance (therefore, extinction) of gold nanoparticles practically coincides with the wavelength of laser radiation. Figure 2 presents the experimental results of the study of the influence of the number of pulses on the extinction of the solution. The pulse energy in the pulse was 250 μJ, the number of pulses varied from 250 to 5000 thousands. With a relatively small number of pulses the extinction coefficient grows linearly. But even with extinction 0.6, the linear relationship is violated. The synthesized√particles shield the incoming laser radiation. The nature of the curve becomes α N (number of pulses). With a significant number of pulses, more than 3500 thousands, the extinction coefficient does not noticeably increase, because the shielding effect is getting too strong.
3.2 Energy To determine the effect of energy in the pulse on the characteristics of the resulting colloidal solutions, experiments were carried out in which the number of pulses was 800 thousands, and the energy varied from 220 to 365 μJ. The pulse energy affects not only the laser ablation of the target, but also the heat balance in the nanoparticle synthesis zone. Figure 3 presents results of this study. It can be seen that although the energy varied linearly, the extinction peak can be divided into two groups: for lower and higher pulse energies. The optical density of a gold colloidal solution depends on the laser pulse energy. The greater the energy per pulse, the greater the optical density of the solution. However, with increasing energy, the peak does not become more pronounced. It is
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Fig. 3 Gold colloid extinction versus pulse energy: 1 – 220 μJ, 2 – 265 μJ, 3 – 310 μJ, 4 – 340 μJ, 5 – 365 Mj
also important to note that with an increase in energy, the extinction index increases not only in the region of the peak of plasmon resonance, but also in the whole spectrum. Most likely this is due to an increase in the amount of a larger fraction of nanoparticles (over 100 nm). In [23], it was noted that during laser ablation, two fractions prevail in the liquid: about 20 nm and above 100 nm. In this case, the coarse fraction no longer exhibits plasmonic properties, or weakly. This explains the increase in the extinction coefficient on average over the spectrum, observed in Fig. 3 Next, the effect of laser synthesis parameters on the stability of the resulting colloidal solutions over time was (aging) investigated. All colloidal solutions have certain stability limits. Under the influence of various factors (temperature, light, electricity, changes in concentration, mechanical stress, the presence of negligible amounts of impurities), which are sometimes difficult to establish, a number of irreversible processes occur in colloidal systems leading to a change in the distribution of particle sizes, as well as their sedimentation [8].
3.3 Rate of Extinction Growth The degree of irradiation of nanoparticles during synthesis (in the presence of a target) shows a great influence on the reproducibility of the results. However, it is difficult to control this parameter, since it depends on the nature of the distribution of the cloud of nanoparticles in solution. In addition to the number of shots, the degree of irradiation is affected by the different volume of water between the target and the
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solution boundary, as well as the shape of the cuvette. In this paper, it was proposed to use the rate of extinction coefficient growth as a comprehensive assessment of the effectiveness of the laser synthesis of nanoparticles by ablation in liquid. The rate of extinction growth was measured for liquid volumes of 3, 5 and 9 ml in the same 10 × 10 mm cuvette. An area of 5 × 5 mm was scanned, with a pulse energy of 290 μJ. The results of the study are shown in Fig. 4. It can be seen that for a few shots, extinction increases rapidly, because the finished nanoparticles weakly shield laser radiation. With an increase in the shots number, the rate of extinction growth for all modes decreases. At the same time, a different volume of water falls on the same number of shots, i.e. a decrease in the rate of extinction growth is expected due to a lower concentration. Nevertheless, it can be seen that the volume has an ambiguous effect, the process is more efficient for 5 ml than for 3 ml, and then decreases due to a decrease in concentration. When developing a technology for the synthesis of nanoparticles, a compromise will have to be made: too small a liquid volume leads to a rapid oversaturation of the solution and a decrease in efficiency; with a large volume of liquid, the process is more stable, but with a lower concentration. Thus, an increase in the volume of liquid in the cuvette will reduce the re-irradiation of finished particles in the presence of a target, which has a beneficial effect on their overall dispersion, but complicates the process of drying the colloidal solution to obtain a nanoparticles.
Fig. 4 Rate of extinction growth during Au nanoparticles synthesis by laser ablation in liquids
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3.4 Nanoparticle Sizes According to the results of the study, it was found that an increase in pulse energy leads to an increase in the concentration of nanoparticles in a colloidal solution, but the fraction of nanoparticles in the size range less than 100 nm may not increase. A significant amount of energy in the region of nanoparticle growth can lead to their excessive coalescence and the formation of larger fractions. This was previously noted by an increase in the extinction of solutions on average over the spectrum while the plasmon resonance peak increased weaker. In addition, size distributions of the obtained colloidal particles were measured using a BlueWave MicroTrack diffraction analyzer. Figure 5 presents the obtained particle size distributions for two energies: 220 and 365 μJ. It can be noted that for an energy of 220 μJ (Fig. 5,a), two fractions can be clearly distinguished: about 40 nm and about 1000 nm. For an energy of 365 μJ (Fig. 5,b), the distribution of the finer fraction was shifted closer to 100 nm, although it has a narrower distribution. The coarse fraction at higher energy quantitatively decreased, but this may be due to sedimentation. Thus, an increase in the pulse energy leads to a significant change in the distribution of particles over fractions, and at the same time increases the mass yield of laser ablation in a liquid [24]. To efficiently obtain nanoparticles of the most promising fraction of less than 100 nm, it is advantageous to reduce the specific energy of irradiation. Performance can be maintained by increasing the pulse repetition rate. In addition, as noted above, the stability of the solution in time is also higher for low energies.
Fig. 5 The particle size distribution of the colloid obtained by diffraction analysis: a the pulse energy of the laser ablation in liquid process–220 μJ; b 365 μJ
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4 Conclusion In this work, the issues related to the influence of the parameters of the generation of Au nanoparticles by laser ablation in a liquid on productivity were considered. One of the important factors affecting the quality and performance of a colloidal solution and, accordingly, nanoparticles is the laser pulse energy. An increase in energy leads to a larger mass yield of the ablation process, but it can reduce the fraction of nanoparticles with sizes smaller than 100 nm. An important factor is the aging of the colloidal solution, i.e. its stability over time. It is important to choose the optimal energy per pulse so that the nanoparticles in the colloidal solution remain stable and do not coagulate into large conglomerates. An increase in specific energy leads to a decrease in the fraction of particles less than 100 nm in the total mass of the colloidal solution. The key findings of this research are: • with an increase in the specific radiation energy during laser ablation in a liquid, the optical density of the resulting colloidal solution increases, which indicates a greater mass yield of ablation and an increase in the number of particles in the solution; • at the same time, an increase in the average particle size of the resulting nanoparticles is observed; • at high specific energies, a fraction of particles with a size of less than 100 nm may be absent or negligible in relation to other fractions; • to increase the stability of the colloidal solution over time, the specific radiation energy should also be reduced. • it is necessary to carefully select the size of the cuvette and the volume of liquid during the synthesis of nanoparticles, in order to achieve optimal performance on a certain laser tool. Based on the obtained data, we are planned to investigate the effect of these parameters on productivity and to develop a final technology for the synthesis of nanoparticles in a liquid for a production scale.
References 1. Boginskaya I et al (2019) SERS-active substrates nanoengineering based on e-beam evaporated self-assembled silver films. J Appl Sci 9:3988 2. Matrosova AS, Kuzmenko NK, Nikonorov NV, Dukelskii KV, Evstropiev SK (2021) Formation of Gd2O3:Nd3+ nanocrystals in silica microcapillary preforms and hollow-core anti-resonant optical fibers. Opt Fiber Technol 65:102547 3. Pavan Kumar Naik S, Muralidhar M, Koblischka MR, Koblischka-Veneva A, Oka T, Murakami M (2019) Novel method of tuning the size of Y2BaCuO5 particles and their influence on the physical properties of bulk YBa2Cu3O7-δ superconductor. Appl Phy Express 12(6):063002 4. Yao Z, Zhang M, Wu H, Yang L, Li R, Wang P (2015) Donor/acceptor indenoperylene dye for highly efficient organic dye-sensitized solar cells). J Am Chem Soc 137(11):3799–3802
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5. Sarmah K, Pratihar S (2017) Synthesis, characterization, and photocatalytic application of iron oxalate capped Fe, Fe-Cu, Fe-Co, and Fe-Mn oxide nanomaterial. ACS Sustaine Chem Eng 5(1):310–324 6. Aleshin NP et al (2018) Modification of weld metal with tungsten carbide and titanium nitride nanoparticles in twin submerged arc welding. High Energy Chem 52(5):440–445 7. Nethi SK, Das S, Patra CR, Mukherjee S (2019) Recent advances in inorganic nanomaterials for wound-healing applications. Biomater Sci 7(7):2652–2674 8. Ulitko VE, Katyba GM, Zhelnov VA, Zaytsev KI, Skorobogatiy M (2021) Opal-based terahertz optical elements fabricated by self-assembly of porous SiO2 nanoparticles. Opt Express 29(9):13764–13777 9. Amendola V, Meneghetti M (2013) What controls the composition and the structure of nanomaterials generated by laser ablation in liquid solution? Phys Chem Chem Phys 15:3027–3046 10. Sun T, Zhang YS, Pang B, Yang M, Xia Y (2014) Engineered nanoparticles for drug delivery in cancer therapy 53(46): 12320–12364 11. Ahn J, Ko J, Lee S, Yu J, Kim Y, Jeon NL (2018) Microfluidics in nanoparticle drug delivery; From synthesis to pre-clinical screening. Adv Drug Deliv Rev 128:29–53 12. Golubenko YV, Savkin AN, Sidorovnina TY, Timoshenko VA (2016) Laser ablation of metals in liquids: a method for producing Au and Cu colloid systems. Bull Russ Acad Sci Phys 80:989–990 13. Scaramuzza S, Zerbetto M, Amendola V (2016) Synthesis of gold nanoparticles in liquid environment by laser ablation with geometrically confined configurations: Insights to improve size control and productivity. J Phys Chem C 120(17):9453–9463 14. Gökce B, Amendola V, Barcikowski S (2017) Opportunities and challenges for laser synthesis of colloids. Chem Phys Chem 18(9):983–985 15. Nikov RG, Nikolov AS, Nedyalkov NN, Dimitrov IG, Atanasov PA, Alexandrov MT (2012) Stability of contamination-free gold and silver nanoparticles produced by nanosecond laser ablation of solid targets in water. Appl Surface Sci 258:9318–9322 16. Kim KK, Kwon HJ, Shin SK, Song JK, Park SM (2013) Stability of uncapped gold nanoparticles produced by laser ablation in deionized water: the effect of post-irradiation. Chem Phys Lett 588:167–173 17. Streubel R, Barcikowski S, Gökce B (2016) Continuous multigram nanoparticle synthesis by high-power, high-repetition-rate ultrafast laser ablation in liquids. Opt Lett 41:1486–1489 18. Zhang J, Chaker M, Ma D (2017) Pulsed laser ablation based synthesis of colloidal metal nanoparticles for catalytic applications. J Colloid Interface Sci 489:138–149 19. Snegirev NI, Lyubutin IS, Yagupov SV, Khmelenin DN, Strugatsky MB (2021) Size effects in iron borate FeBO3 nanoparticles. Russ J Inorg Chem 66(8):1217–1222 20. Simakin AV, Baimler IV, Smirnova VV, Kozlov VA, Gudkov SV (2021) Evolution of the size distribution of gold nanoparticles under laser irradiation. Phys Wave Phen 29(2):102–107 21. Zhigalina OM, Khmelenin DN, Atanova AV, Sviridov AP, Tsvetkov MY (2021) From nanoparticles generation to nanostructures diversity at thermoplasmonics laser-induced backside wet etching of sapphire. Appl Surface Sci 536:147837 22. Yu J, Nan J, Zeng H (2017) Size control of nanoparticles by multiple-pulse laser ablation. Appl Surface Sci 402:330–335 23. Starinskiy SV, Shukhov YuG, Bulgakov AV (2017) Effect of nanoparticle sizes on the extinction spectrum of colloidal solutions produced by laser ablation of gold in water. Quant Electron 47:343–346 24. Shiganov I, Melnikov D, Misyurov A, Melnikova M, Shtereveria D, Myat Z (2020) Investigation the effect of laser ablation parameters in a liquid in order to reduce the pulse energy during laser shock peening. Opt Quant Electron 52(4):203
Improving the Efficiency of the Locomotive Complex Through Modern Methods of Managing Traction Resources Alexander Vilgelm , Alexander Komyakov , and Alexey Kashtanov
Abstract Improving the efficiency of the main activities of JSC “Russian Railways” is currently a relevant and significant issue. According to the provisions of the company main strategic documents, the key performance indicators for the locomotives are to be improved by 2025 and continue so until 2035. The paper deals with the analysis of problems and proposals for improving the management of electric locomotives that carry most of goods on the railways of the Russian Federation. The paper analyzes the possibilities to improve the main operational indicators of locomotive complex by increasing the efficiency of the organization of electric locomotives operation. One of the key performance indicators of the locomotive complex is the average daily performance of electric locomotives. To improve this indicator, it is necessary to increase the amount of work per unit of electric traction rolling stock. The given paper proposes two ways to achieve this. Firstly, it is the qualitative improvement of advantageous locomotives, increasing their traction properties; secondly, the improvement of the technology used to manage traction systems. The paper shows that in order to achieve the company targets, JSC “Russian Railways” has to necessarily implement the second solution, namely, introduce and improve the polygon technologies for managing traction resources and switch to extended railroad hauls of electric locomotives. The paper presents the main requirements and conditions for implementing these technical solutions. Keywords Locomotive complex · Average daily performance of locomotives · Locomotive hauls · Polygon technologies · Electric locomotives · Traction resources management · Operational fleet of electric locomotives
1 Introduction About a third of all operating expenses of JSC “Russian Railways” are accounted for by the locomotive complex. About 190 thousand workers are employed in the A. Vilgelm (B) · A. Komyakov · A. Kashtanov Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_37
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locomotive industry. Approximately one-fifth of the total cost of railway transportation amounts to the cost of maintenance of traction rolling stock. The inventory fleet of locomotives of JSC “Russian Railways” is more than 20 thousand units, the operational fleet is more than 14 thousand units. All these indicate the essential importance of the locomotive complex in the overall work carried out on the Russian railway network. The efficiency of the locomotive complex also plays an important role in the overall efficiency of the company. Moreover, with the low efficiency of locomotives and low organization of their management, the other achieved efficiency may simply be invalid in terms of the costs of maintaining infrastructure and traction rolling stock. 1. In general, the efficiency of the locomotive complex includes the following components: 2. the readiness of the locomotive fleet and foot-plate staff to carry out full transportation on the entire network; 3. the reliability of the locomotive fleet in operation and the safety of its operation; 4. manning of foot-plate staff; 5. performance of locomotives and foot-plate staff; 6. process efficiency and cost-effectiveness of the complex. The first three components must be strictly followed, and they are regularly fulfilled on the road network. At the same time, performance, process efficiency and cost–effectiveness are relative concepts that depend on the accepted criteria for their evaluation. Thus, the performance and technological efficiency of the railway locomotive complex can be characterized by a large number of qualitative indicators, the main of which include: • • • • • • •
the average operating, service, running speed of trains; the average mass of trains transported; average daily locomotive mileage; total locomotive network; specific energy intensity (or energy efficiency) of train traction; average daily locomotive performance; costs of operation and maintenance of locomotives [1].
Quite a number of works related to the optimization of electric rolling stock control modes [2], improvement of the efficiency of the traction power supply system and the organization of traction resources management [3–5] discuss improving the energy efficiency of train traction. In the works [6–8], this issue is viewed in the context of the impact of locomotive usage on the environment with the cost of locomotive life cycle taken into account. In the articles [7–13], regenerative braking is considered a key indicator of locomotive efficiency. Despite the large number of scholarly papers in the field, the issue of qualitative and quantitative assessment of the impact of the organization of electric locomotive operation on the integral performance indicators of the locomotive complex, in
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particular, on the average daily performance of locomotives of the operational fleet, have not been thoroughly studied. For instance, according to the Long-term Development Programme of JSC “Russian Railways”, the average daily performance of locomotives of the operational fleet by 2025 is to increase by 11.6% compared to the figures of 2019. The measures are being taken, and the ways to improve this indicator are obvious. They are the increase in the load of available locomotives [14] and modernization of the fleet by purchasing new more powerful and innovative locomotives including those running on gas and other alternative energy sources [15, 16]. The possibility for increasing the load of existing electric locomotives is not infinite, and therefore the modernization and reinforcement of the locomotive fleet is an important task that contributes to achieving the planned indicators. The number of new electric locomotives purchased today is a positive trend (Fig. 1, where N is the number of electric locomotives purchased per year). In total, during the implementation of the Long-term Development Program, it is planned to purchase about 6,000 locomotives, so it is expected that by 2025, the cases of train delays due to the technical condition of the locomotives will be reduced by 25–33%, which, in turn, will increase both the performance of the locomotives and the efficiency of the locomotive complex. The technical requirements for new locomotives are also becoming more exacting. One of the main requirements for the newly designed electric locomotives is an increased axle load of up to 27–30 tons, the ability to drive trains weighing up to 10,000 tons, carrying out the functions of an intelligent control system and traffic safety, the ability to switch to maintenance according to the technical condition, for instance, through the development of diagnostic onboard systems [17], and many others. However, a qualitative improvement of the fleet of operational electric locomotives by itself without a competent organization of their work (with minimizing train delays and locomotive downtime [18] is not able to significantly increase the efficiency of the 250 209
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locomotive complex. For these purposes, it is necessary that each electric locomotive operates in modes close to its nominal capabilities [19]. However, the procedure of railway operations and local operational conditions will always determine the tasks and problems that need to be solved in order to achieve the optimal values of locomotive operational efficiency indicators. The abovementioned factors have a significant potential for improving the efficiency of the locomotive complex. The purpose of this study is to substantiate the use of such means of organizing the operation of electric locomotives as polygon technologies for managing traction resources with the switch of electric locomotives to extended hauls, as well as to assess the potential for improvements due to this key performance indicators of the locomotive complex.
2 Materials and Methods Thus, it can be argued that it is important not only to design powerful reliable highspeed locomotives but also to organize their operation in such a way that they would show the maximum efficiency. The efficiency of using a locomotive is characterized by its performance, i.e., the net work performed by it to move goods per unit of time. The performance of a locomotive is determined by the product of the mass of goods transported by it per day by the distance over which these goods are moved. The average daily performance of locomotives can be regarded as the main integral indicator of the efficiency of the locomotive complex. This indicator depends on the volume of work performed related to the number of locomotives involved in this work. Thus, the main way to increase the average daily performance of locomotives is to increase the rate of freight traffic rather than the number of locomotives in the fleet. The average daily performance can be determined in relation to the operational fleet of electric locomotives. As it was noted above, the factors hindering the improvement of the performance of locomotives are, firstly, the peculiarities of railway procedures, and, secondly, the local operational conditions. The first one refers to such features as, for example: • mandatory load for auxiliary types of traffic; • mandatory traffic with empty trains; • the need for systematic maintenance with the uncoupling of electric locomotives from trains; • the need to replace electric locomotives at the station splicings due to the change in the type of current rate. • the second one means such conditions as, for example: • the track layout that necessarily requires the mandatory use of multiple traction or pusher locomotives on separate station-to-station blocks and as a result, the need for additional stops in the cargo delivery;
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• climate conditions that create additional resistance to traffic and affect the possibility of applying optimal operational modes of locomotives including regenerative braking [20]. Taking into account these features is the most important condition both when improving the locomotives themselves and when planning the organization of their operation management. For instance, the heaviest coal train traffic routes “KuzbasNorth-West” and “Kuzbas-Center” have three station splicings, the Kuzbas–South destination has two of them. And at the Eastern operating domain, many sections, both electric and heat-drawn, require the use of pusher locomotives even when applying the currently set weight standards, not to mention the target weight standards. The grading of track and climate conditions for these destinations can also differ significantly during the train traffic from the place of the departure to the destination station [21]. At the same time, it is necessary to understand that each train stop is a loss of time, a decrease in delivery speed and an increase in the time of locomotive full round trip. Accordingly, this is an increase in the required number of locomotives of the operational fleets and, as a result, with the same volumes of work performed, the average daily performance of locomotives is reduced while the cost of their maintenance increases. Therefore, stops caused by the need to change the locomotive or install a pusher locomotive are in any case the factors that reduce the performance of locomotives despite the fact that these problems are actually caused by the imperfection of technical systems. The imperfection here means the absence of two-system electric freight locomotives, the lack of developed on-board diagnostic systems that can ensure the locomotive maintenance according to their technical condition, the lack of power and traction properties of electric locomotives to operate without auxiliary locomotives. As you can see, one of the factors that cause forced stops to change the locomotive is the need to perform its maintenance. The electric locomotives operated today have to go through the second line maintenance (MNT-2) at certain time intervals specified by the operating manual and other regulatory documents. For different series of electric locomotives, this value varies from 48 to 180 h and determines the maximum possible mileage between the necessary uncoupling of the electric locomotive to perform maintenance, km: Lmax = α·V · (T − t),
(1)
where α is the coefficient that characterizes the placement of maintenance points; V —average service speed, km/h; T —regulated time between MNT-2, h; t—the total time spent by the electric locomotive at the points of round trip, h. Estimated calculations show that for the values of the average local speed of about 40 km/h and the lowest values of the regulated time between MNT-2 (48 h), depending on the total time spent by electric locomotives at the turnover points (from 6 to 12 h) the mileage of the L max , which determines the length of the possible route without uncoupling the electric locomotive, varies from1400 to 1800 km (Fig. 2).
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Fig. 2 The dependence of the acceptable mileage of electric locomotives between MNT-2 (km) for different regulated times between MNT-2 at different values of the time spent by electric locomotives at the turnover points
The given figure shows that in case of using electric locomotives with an extended time between MNT-2 (72–180 h), the value of the possible mileage and, consequently, the length of the acceptable railroad haul of the electric locomotive increases by a multiple. For example, with a regulated time between MNT-2 for 180 h, the mileage without uncoupling the electric locomotive can reach 6,700 km, which can be beneficially used when operating electric locomotives on long stations of the Eastern Operating Domain. In order to improve and optimize the traffic procedures, eliminate the “bottlenecks” of the train handling capacity and carrying capacity, as well as expand or eliminate the limiting factors of improving the efficiency of the locomotive complex, JSC “Russian Railways” is designing, implementing Traction Devices Control Centers (still considered promising) with polygon technologies for the operation of locomotives. The main task of these Centers is to organize the optimal and day-to-day control of the use of traction resources on the extended sections of the locomotive circulation (up to four railways). Within the framework of this work, the calculations were made to assess the possibilities of improving the main performance indicators of electric locomotives when using this technology. For this purpose, the calculations were made to determine the key performance indicators for the two options of electric locomotive use: a) on two adjacent short sections by two separate electric locomotive fleets of two different depots (Fig. 3a); b) on a combined long section with a common fleet of electric locomotives from two different depots (Fig. 3b). The first diagram (Fig. 3a) shows a standard scheme for the maintenance of sections by electric locomotives, when the two adjacent main depots B and D serve two adjacent sections A–B–C and C–D–E separately. At the same time, at the stations A, C and E, the electric locomotives are uncoupled, correlated to the oncoming trains and sent in the opposite direction. At the stations C and E, there are MNT-2 electric locomotives of depot B and D, respectively.
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- main depot;
- electric locomotive maintenance point; - electric locomotive turnover point; - locomotive crew work scheme - electric locomotive scheme;
Fig. 3 Schemes for organizing the operation of electric locomotives on two short sections of circulation a and one long combined section b
The second diagram (Fig. 3b) shows a promising scheme for servicing sections with electric locomotives when all electric locomotives are located in the corporate fleet of two depots and operate on the entire district A–B–C–D–E. At the same time, electric locomotives are uncoupled for their turnover only at the stations A and E, and at the station C, in this case, the trains are stopped only for changing locomotive crews, which increases the average speed of electric locomotive turnover and the cargo delivery by reducing the downtime of trains at the station C. For these loading schemes for section A–B–C, the traction calculations were made, the train schedules were drawn up, the electric locomotives were linked to trains at the corresponding turnover points, and electric locomotive turnover sheets were compiled. For the C–D–E section, the similar values of the operation parameters were adopted. The data obtained from the electric locomotive turnover sheet of the section A–B–C and a number of assumptions about the work on the adjacent section were used to calculate key performance indicators of locomotive depots. Next, we will present the calculations for determining these indicators for the option “a” of the organization of electric locomotive operation (Fig. 3a) and the option “b” of the organization of electric locomotive operation (Fig. 3b). The total operational time of electric locomotives on two short sections of circulation is calculated by the formula, h: n 1
Tia =
n 1
Ti ABC +
2 · (L 3 + L 4 ) · n n + t1 , 1 V C DE
where n is the number of pairs of trains on the section A-B-C-D-E; n 1
Ti ABC ,
(2)
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the total operating time of electric locomotives on the section A-B-C determined by the received sheet of electric locomotive turnovers; VCDE —service speed on the section C-D-E assumed to be equal to that obtained from the train schedule for the section A-B-C; n 1
t1 ,
the total time spent by all electric locomotives at the turnover points, h. The total operating time of electric locomotives on the combined circulation section is calculated by the formula, h: n 1
Tib =
n 1
Ti ABC +
2 · (L 3 + L 4 ) · n n + t2 , 1 V C DE
(3)
where n 1
t2 ,
is the total downtime of electric locomotives due to the change of locomotive crews, h. The quantitative composition of the operational fleet of electric locomotives for two depots for the operation on two short sections of circulation is determined by the formula: n a T a N = 1 i . (4) 24 The quantitative composition of the operational fleet of electric locomotives for two depots for the operation on the combined section of the circulation is determined by the formula: n Nb =
Tib . 24 1
(5)
The average daily mileage of electric locomotives of the operational fleet on two short sections of circulation is calculated by the formula, loc. - km: Sa =
2 · (L 1 + L 2 + L 3 + L 4 ) · n , (1 − β0 ) · N a
(6)
where β0 is the coefficient of auxiliary mileage of electric locomotives. The average daily mileage of electric locomotives of the operational fleet on the combined circulation section is calculated by the formula, loc. - km: Sb =
2 · (L 1 + L 2 + L 3 + L 4 ) · n , (1 − β0 ) · N b
(7)
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The time of net traffic of electric locomotives of the operational fleet on two short sections of circulation is calculated by the formula, h: n
ABC 2·(L 3 +L 4 )·n + V C DE 1 t3 Na
=
t3a
−
n
1 t2
,
(8)
where n
t ABC , 1 3
is the total time of net traffic of electric locomotives on the section A-B-C determined by the received sheet of electric locomotive turnovers. The time of net traffic of electric locomotives of the operational fleet on the combined circulation section is calculated by the formula, h: n
ABC 2·(L 3 +L 4 )·n + V C DE 1 t3 Nb
=
t3b
−
n
1 t2
.
(9)
The net work time of electric locomotives of the operational fleet on two short sections of circulation is calculated by the formula, h: n t4a
ABC + 1 t3
=
n
1 t2 + Na
2·(L 3 +L 4 )·n V C DE
.
(10)
The net operating time of electric locomotives of the operational fleet on the combined circulation section is calculated by the formula, h: n t4b
=
ABC +2· 1 t3
n
1 t2 + Nb
2·(L 3 +L 4 )·n V C DE
.
(11)
The average daily productivity of electric locomotives of the operational fleet on two short sections of circulation is calculated by the formula, gross tonne-kilometre: Wa = Q · S a · (1 − β0 ).
(12)
where Q is the average mass of trains on the section A-B-C-D-E; The average daily performance of electric locomotives of the operational fleet on two short sections of circulation is calculated by the formula, gross tonne-kilometre: Wb = Q · S b · (1 − β0 ).
(13)
A total of preparatory work, including traction calculations, the train schedules, and all the rest including the receipt of calculation notes and the necessary parameters for further calculations was performed for various values of the service speed on the section ranging from 40 to 48 km/h. Then, the above calculations were used to
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determine the values of the key performance indicators for the operation of electric locomotives for two options of organizing their operation and for different values of the service speed on the section. Next, we will consider the results obtained.
3 Results The calculations of determining the main performance indicators for the two short railroad hauls of electric locomotives are given in Table 1. The calculated results of determining the main performance indicators for the combined extended haul of electric locomotives are given in Table 2. The data presented in Tables 1 and 2 allow to analyze the percentage of improvement in the considered indicators when switching to the operation of electric locomotives on the combined extended railroad haul. So Fig. 4 shows the graphs of the percentage increase in the net work time of electric locomotives, the reduction of the operational fleet of electric locomotives required to maintain the given train schedule, and the increase in the average daily performance of electric locomotives of the operational fleet. Table 1 Calculation results for two short work hauls V–average service speed, km/h;
Total operating time of electric locomotives, loc. hour
Operational fleet of cargo locs, units
Daily average distance mileage, km
Time of net traffic, h
Net work time, h
Daily average performance, gross tonne-kilometre
40.0
1215
51
733.7
12.3
16.1
3,877,531
40.5
1205
50
774.0
12.4
16.2
4,090,326
41.0
1190
50
783.6
12.5
16.2
41,408,241
41.5
1176
491
793.3
12.6
16.2
4,192,180
42.0
1161
48
803.2
12.6
16.2
4,244,428
42.5
1147
48
813.2
12.7
16.3
4,297,600
43.0
1133
47
823.5
12.8
16.3
4,351,731
43.5
1119
47
833.9
12.8
16.3
4,406,856
44.0
1105
46
844.5
12.9
16.4
4,463,012
44.5
1091
45
855.4
13.0
16.4
4,520,239
45.0
1077
45
866.4
13.1
16.4
4,578,576
45.5
1063
44
877.7
13.2
16.5
4,638,065
46.0
1049
44
889.1
13.2
16.5
4,698,748
46.5
1035
43
900.9
13.3
16.5
4,760,673
47.0
1022
43
912.8
13.4
16.6
4,823,885
47.5
1008
42
925.0
13.5
16.6
4,888,434
48.0
995
41
937.5
13.6
16.7
4,954,372
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Table 2 Calculation results for the combined extended railway haul Total operating time of electric locomotives, loc. hour
Operational fleet of cargo locs, units
40.0
1110
46
40.5
1101
46
41.0
1087
41.5 42.0
Daily average distance mileage, km
Time of net traffic, h
Net work time, h
Daily average production, gross tonne-kilometre
803.2
13.5
19.7
4,244,324
847.1
13.6
19.7
4,476,631
45
857.8
13.7
19.7
4,533,016
1074
45
868.6
13.8
19.7
4,590,356
1060
44
879.7
13.8
19.7
4,648,687
42.5
1047
44
890.9
13.9
19.8
4,708,045
43.0
1034
43
902.3
14.0
19.8
4,768,470
43.5
1021
43
914.0
14.1
19.8
4,830,002
44.0
1008
42
925.8
14.2
19.8
4,892,682
44.5
995
41
937.9
14.3
19.8
4,956,555
45.0
982
41
950.3
14.3
19.8
5,021,664
45.5
969
40
962.8
14.4
19.9
5,088,057
46.0
956
40
975.6
14.5
19.9
5,155,782
46.5
943
39
988.7
14.6
19.9
5,224,891
47.0
931
39
1002.1
14.7
19.9
5,295,436
47.5
918
38
1015.7
14.9
19.9
5,367,473
48.0
906
38
1029.6
15.0
20.0
5,441,060
Improvement, %
V–average service speed, km/h;
Service speed, km/h Reduction of the operated fleet of electric locomotives Increase in the average daily productivity of electric locomotives Increasing the useful life of electric locomotives
Fig. 4 The graph of the expected improvement of the main performance indicators of electric locomotives in the considered range of service speed
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The presented relations show that in the entire range of the considered service speeds on the section, the switch to the extended railroad haul of electric locomotives improves the analyzed indicators: the net work time of electric locomotives is increased by 22.2–19.8%, the required operational fleet of electric locomotives is decreased by 8.6–8.9%, the average daily performance of electric locomotives is increased by 9.5–9.8%.
4 Discussion As the presented results show, the implementation of the polygon technology for managing traction resources with the switch to extended railway hauls of electric locomotives can ensure the growth of key performance indicators of the locomotive complex. The growth values of these indicators are comparable to the figures that are the benchmarks in the Long-term Development Program of JSC “Russian Railways” according to which the average daily locomotive performance by 2025 is to increase by 11.6% compared to that of 2019. The calculations made on the basis of the proposed loading diagrams for organizing the operation of electric freight locomotives by conventional gage sections showed the results close to these reference points. The major asset of the work is the verification of achieving the planned performance indicators of the locomotive complex provided that the procedure of train management is improved together with enhancing traction properties, power and equipment of the locomotives. It is necessary to understand that all the main performance indicators of the locomotive complex are determined by the volume and speed of goods transportation. Both of them depend, among other things, on the rate of usage of traction resources and the quality organisation of train management. The proposed loading diagram and methodology for evaluating the key performance indicators of the locomotive complex allows us to understand the essence and significance of changes in the organization of locomotive operation by speeding their turnovers reducing the time spent without trains (due, for example, MNT-2 operations) and increasing the time of network with trains. The proposed methodology also allows us to quantify the percentage improvement of indicators and, if applied to real railway sections, it can be of practical use for the technical and economic assessment of measures to improve the management of the locomotive complex. Further research in this field should deal with determining the technical requirements for electric locomotives and their operating conditions to ensure their safe and failure-free operation when the trains are serviced according to the schemes with extended railroad hauls.
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5 Conclusions Summing up the results of the given work, we will note once again that the improvement of electric locomotives is certainly an important factor to achieve the target parameters of the Long-term Development Program of JSC “Russian Railways”. However, without parallel optimization of the traction resource management system, it is becoming more difficult to achieve the planned indicators. The given paper shows that the technological characteristics of the railway transport operation cause stray train delays due to the change of locomotives, which establishes provision for improving the efficiency of the locomotive complex. It is possible to achieve the provision by increasing the acceptable runs of electric locomotives between the uncoupling to perform MNT-2, as well as by improving the traction resource management system. The proposed loading diagram and methodology for assessing the improvement of performance indicators of electric locomotives due to their switch to extended railroad hauls allows us to quantify the expected percentage improvement in key performance indicators of the locomotive complex. The calculations done in the work on the basis of the proposed methodology showed results that make it possible to assert that the use of polygon technologies for managing traction resources with the switch of electric locomotives to extended railroad hauls can increase the value of the average daily performance of electric locomotives by about 10%. Further implementation of polygon technologies for managing traction resources with regard to the provisions of this study will ensure that as many electric locomotives as possible operate in modes close to their nominal capabilities.
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Additive Technologies Features for Manufacturing Metal Products from Powder Materials by Direct Laser Deposition Oleg Supchinsky , Maria Melnikova , Andrei Kholopov , Dmitriy Melnikov , and Alexandr Bogdanov Abstract Large-scale additive manufacturing as direct laser melting makes it possible to produce significantly stronger structures than those produced using standard 3D printing. Copper alloys are promising in terms of their properties. The high thermal conductivity of copper has led to its application in various kinds of heat exchangers, furnace designs for arc melting of such active metals as titanium, zirconium, refractory metals. Water-cooled molds, pallets, and crystallizers are made of copper, which provide intensive heat removal from the melt. Despite their wide application, there is a small amount of data and research for direct metal melting technology when talking about copper alloys. This work is devoted to the study of the features of the formation of single tracks depending on the processing parameters, as well as the study of their geometric parameters to determine the possibility of manufacturing products from such materials. It was found that among the tracks obtained by direct laser melting there are stable regimes in which geometric parameters are preserved, the patterns of the manufacturing process are revealed. The influence of processing parameters on the geometric dimensions of the tracks is discussed. Based on the selected regimes, a three-dimensional object of primitive shape was created. It demonstrates the possibility of creating such products. Defects (pores and cracks) have been identified and the possibilities of their elimination have been determined. Keywords Laser · Additive technologies · Coaxial laser melting · Copper alloys
O. Supchinsky (B) Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] M. Melnikova · A. Kholopov · D. Melnikov · A. Bogdanov Bauman Moscow State Technical University, 2nd Baumanskaya Street, 5, 105005 Moscow, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_38
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1 Introduction Additive technologies are actual tendency for manufacturing parts with a complex configuration. Currently, they are among the most common both in the field of development and in the field of industry [1–3]. The advantages of these technologies include the possibility of regulating the parameters and processing regimes, which ensures the wide use of a large range of materials. Due to the peculiarities of laser exposure in manufacturing process, the properties of the resulting products in some cases may be even better than for products manufactured in the traditional way [4, 5]. One of these technologies is direct (coaxial) laser melting (CLM or DLM). Its core consists in manufacturing objects by sequentially applying powder layers and melting them from the lower layer to the upper one by simultaneously feeding powder and laser beam through a nozzle with laser radiation focusing into a given spot diameter into the processing zone. The DLM process, in comparison with selective laser melting (SLM), is characterized by high productivity, as well as the possibility of manufacturing parts from several materials simultaneously. DLM technology is used to create larger products made of powder materials. Various sources of radiation can be found as emitters. The most common lasers are, for example, gas lasers, visible-range lasers, solid-state or fiber lasers [6]. Most often, solid-state and fiber lasers are found in DLM systems [6], the wavelength of which is about 1 micron. One of the promising materials is copper and copper alloys. Due to its thermophysical properties, they are used in the aircraft industry, the space industry, the automotive industry, etc. The ability to create complex structures and multi-element products makes it possible to exclude some production operations by replacing them with new items manufactured with additive technologies. The high thermal conductivity and extremely low absorption at room temperature of infrared laser radiation require high laser power to achieve the melting process. In addition, low absorption also causes high sensitivity to changes in surface conditions, such as oxidation or roughness. Various studies have been conducted to stabilize work with copper, including in the field of welding [7]. To enhance the weldability of copper is to use frequency-doubled green YAG lasers, with significantly higher absorption at room temperature [7]. Green pulsed lasers showed an improvement in reproducibility for spot welding of copper [8]. As the most effective solution in this area, an option of using a laser in the blue or green wavelength range was proposed [9, 10]. Unfortunately, this solution is not always optimal, since the laser power for such wavelengths will be significantly lower and this may not be enough to ensure the transfer of the material. At the time, when analyzing the current state of the issue, it is shown [11] the possibility to use power densities of 2 · 108 W/cm2 for manufacturing products of copper materials. At the moment, there is not enough research in this area, only a few studies have been conducted to identify the features of manufacturing by the DLM for copper alloys and to establish dependences on the parameters and processing conditions that are necessary for effective processing. Such a property of copper alloys as high
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thermal conductivity complicates the creation and processing of objects, which leads to the necessity of selecting and varying processing regimes and strategies. It is also necessary to take into account the high thermal conductivity of the material, which produces high temperature gradients and cooling rates, determining the short lifetime of the melt pool [12]. The specifics of the melting and shaping of each layers determine the final characteristics and characteristics of the product. The purpose of this work is to identify the dependencies of the geometry of examples on the technological parameters of manufacturing.
2 Materials and Methods To develop one-dimensional objects, the “KLP-400” machine, designed at the Bauman Moscow State Technical University, was used. It is a machine for direct laser deposition with the ability to mix up to 4 different powders at the same time. Five-coordinate movement allows to work with any type of products, despite the complexity and configuration. Its characteristics are presented in Table 1. The powder CuCr1 (C18200) was selected as powder material, the particle size of which is 63–125 microns. It is proposed to use pure copper as a substrate. The application of such a substrate will allow to evaluate the features of material transfer and further shaping of layers in the manufacturing process. For the study, 18 samples were produced with varying power from 2500 to 3000 W (P), processing speeds from 400 to 800 mm/min (V), powder consumption from 2 to 14 g/min (G) and spot diameter FWHM from 1.0 to 1.2 mm (d). According to the results of the processed tracks the size and stability of height and width, and their dimensions were evaluated. Measurements of the geometric parameters of single tracks, measurements of the cross-sectional area of the melted part of the material and the size of the thermal impact zone were carried out. As a result of the experiment, the main geometric parameters of the track were studied, which determine the specifics and features of 3d processing parts afterwards. The study of the characteristic, measurement of geometric parameters was carried out by the method of sample preparation. The preparation of the grinds was carried out by the standard method of polishing and etching on Struers installations. The study was carried out on Olympus GX53 and SZ61 optical microscopes. Table 1 Characteristics of the KLP-400 laser machine Parameter
Units
Value
Power, max
W
3000
Wavelength
μm
1.07
Spot diameter (FWHM), min
μm
1200
Weight of the processed part, max
kg
500
Installation dimensions
m
2.0 × 2.0 × 3.0
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3 Results and Discussion When powders are remelted by direct laser melting, complex interactions and processes occur in the processing zone. Under the action of laser radiation, the substrate material is heated, and the powder enters the front part of the melt pool. Gradually, the material solidifies in its back, while the melt pool quickly moves along the surface, following the laser beam. When mixing the substrate material and the deposited material, the probability that the melting point of the melt pool will differ from the melt pool of pure powder and the substrate is high. In this case, the melting temperature changes during mixing: it can move both down and up, so it is important to take into account such features of materials. The most visual samples of the obtained one-dimensional tracks are shown in Fig. 1. They correspond to the following processing parameters, indicated by letters from A to D: A: P = 3000 W, d = 1.2 mm, G = 4 g/min, B: P = 3000 W, d = 1.2 mm, G = 12 g/min, C: P = 2500 W, d = 1.0 mm, G = 4 g/min, D: P = 2500 W, d = 1.0 mm, G = 12 g/min. Such parameters are due to high reflectivity and conductivity of copper. The cross-section profile of a track is defined using width w, depth d and contact angles θ [13]. At the first stage, the formation of the track was analyzed at various parameters of regimes based on the analysis of images of their formation. It was found that in almost all the studied modes, the axial line of the zone of thermal influence formed by the laser beam on the surface of the substrate does not correspond to the axial line of the track. The cross-section of the tracks is asymmetrical with respect to the axis directed along the line of motion of the laser radiation. The most likely explanation is the extremely uneven supply of powder along the axial section. The higher the processing speed, the more visible effect of misalignment of the track and the beam. The heat-affected zone (HAZ) when exposed to a laser in the DLM process is the volume of the previous metal layer, which, when exposed to a laser and surfacing, is not brought to melting, but its microstructure and properties change. The HAZ can be used to study the characteristic features of the process, i.e. melting the powder. This can be achieved through panoramic analysis of the surface topography and cross-section. It should be noted that most modes are characterized by deviation of the centerline of the HAZ on the substrate from the centerline of the track. Figure 1 shows the features of the formation of tracks most clearly: in cross-section, they are not symmetrical with respect to the axis directed along the manufacturing line. Three different types of tracks were identified, including continuous, discontinuous, and balled tracks. Stable tracks are regarded as the most preferable, in which the centerline is preserved, and the edges remain continuous. In the studied power range, the continuity of the formation of a single track was due to the amount of powder consumption. With a radiation power of 3000 W and a beam diameter of 1.2 mm, a stable roller is formed in almost all processing modes. Another important parameter when working with DLM is the powder utilization factor (PUF) μ, %, which also shows the efficiency of the work performed, which is calculated by the formula:
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Fig. 1 Optical images of longitudinal and cross-sectioned samples obtained using different parameters: a – P = 3000 W, d = 1.2 mm, G = 4 g/min, b – P = 3000 W, d = 1.2 mm, G = 12 g/min, c – P = 2500 W, d = 1.0 mm, G = 4 g/min, d – P = 2500 W, d = 1.0 mm, G = 12 g/min
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μ=
m · 100 G
(1)
where m is the mass of the deposited powder per unit time m, g/min, was determined by the formula: m=
ρ·S V
(2)
where ρ = 8,9 · 10–12 g/μm3 —the density of the alloy CuCr1. S, μm2 —the cross-sectional area of the track above the substrate line, measured from the sample. PUF for the tracks shown in Fig. 1 is: A–20.72, B–48.69, C–16.54, D–34.81. Obviously, for tracks with good adhesion to the substrate, large values of material use correspond, that is, the process is more efficient, and the tracks are more promising for further manufacturing. Such values determine the best productivity. The geometric parameters of the obtained single tracks have a linear dependence on the powder consumption. Figures 2 and 3 show the main dependences of the height, width and depth of the cross-section of the samples on the technological parameters of the laser. From the analysis of the graph in Fig. 2, it can be seen that the track height increases with increasing powder consumption and radiation power density, and the height increase with increasing powder supply is close to linear. The lower the processing speed, the more clearly this trend can be traced. Obviously, at high processing speeds, the linear powder consumption will be lower, and the track height will be less. The track width (Fig. 3) depends little on the powder consumption. In fact, the width is largely determined by the beam diameter. It can be seen that with its value of 1.2 mm, the graph is higher. Probably, the relative position of the constrictions of the gas-powder flow and the laser beam has a significant effect, which should be taken into account for a deeper understanding of the process. As the degree of defocusing increases, the radiation power density decreases and, as a result, the
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amount of powder used decreases. The height of the tracks will decrease, and the width will first increase and then decrease. The graphical dependences show that the height and depth depend on the powder consumption: with increasing consumption, the linear dimensions of the track elements increase. Figure 3 shows that the width of the tracks varies according to a slightly more complex law, which includes many factors. The geometry of the track is determined by the influence of a set of parameters of power, speed, cooling, etc. In general, it is worth noting that reducing the beam diameter to 1.0 mm adversely affects the formation of deposited tracks. This is most likely due to the relative position of the laser beam and the gas-powder flow. The formation of the microstructure is significantly influenced by the thermal effect on the solidifying metal. Laser surfacing is characterized by extremely high cooling rates, the increase in the size of the HAZ with an increase in powder consumption can be explained if we assume that the copper substrate reflects a significant part of the radiation, and part of the reflected radiation falls back into the powder movement zone, which also correspond to mixing powder and substrate, changing the melting point. Thus, the role of heat absorption by the powder increases. With an increase in its temperature, which is easier to achieve for the powder, since heat removal from it is practically impossible, the absorption coefficient increases. Thus, for CuCr1, the absorption of radiation by the powder dominates and has a higher effect on the formation of the roller than the absorption by the substrate. The possibility of several layers manufacturing of powder was studied next, in order to understand the process of layer formation. Based on the results obtained, volumetric elements were created for regimes B and D. The result is shown in Fig. 5. It can be noted that bonding with a copper substrate is a rather complex process that depends on a large number of factors. Figure 4a show the formation of cracks, while in Fig. 5b the adhesion to the substrate is much better, however, the formation of pores is observed. The porosity and discontinuity of the resulting samples are quite common phenomena that adversely affect the properties of the final object. When choosing processing modes, one should be guided by such parameters that will help to avoid such an undesirable effect.
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Fig. 4 Adhesion zone of 3D part a B-parameter, b D-parameter
In general, there is a positive trend in the creation of volumetric products. Analysis of the macrostructure of the samples showed flatness and areas not associated with melting. The reason for this is the thermal conductivity of the underlying layers, which increases significantly as the part is formed. Surface oxidation also occurs, which leads to a significant increase in the wettability angle. As a result, local crystallization centers are formed, which attract more and more material with each new layer. The solution to the first problem is to change and vary the parameters during the transition from layer to layer [14].
4 Conclusion When manufacturing a powder CuCr1 on a copper substrate, the formation of a sufficient total remelted zone between the track and the substrate depends on the choice of technological parameters, which is associated with a significant removal into the substrate of both the heat coming to it from laser radiation and from the incident powders. With increasing powder consumption, the size of individual tracks and the size of the HAZ, and the size of the total cast zone decreases, thus the largest samples have adhesion defects with the substrate. Reducing the beam diameter to 1.0 mm leads to a suboptimal combination of beam shapes and gas-powder flow, reducing the efficiency of powder use and the stability of the formation of single tracks. So, it is more preferable to choose 1.2 mm beam diameter. With laser coaxial melting of chromium bronze, the formation of defects in the form of pores and non-melts is possible; the formation of the former is associated with excessive linear energy, the latter with insufficient.
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References 1. Joshi SC, Sheikh A (2015) 3D printing in aerospace and its long-term sustainability. Virtual Phys Prototyp 10(4):175–185. https://doi.org/10.1080/17452759.2015.1111519 2. Amin Yavari S et al (2013) Fatigue behavior of porous biomaterials manufactured using selective laser melting. Mater Sci Eng 33(8):4849–4858. ISSN 0928-4931. https://doi.org/10.1016/ j.msec.2013.08.006 3. Gong G et al (2021) Research status of laser additive manufacturing for metal: a review. J Mater Res Technol 15:855–884. ISSN 2238-7854. https://doi.org/10.1016/j.jmrt.2021.08.050 4. Wang JC et al (2022) Comparison of microstructure and mechanical behavior of Ti-35Nb manufactured by laser powder bed fusion from elemental powder mixture and prealloyed powder. J Mater Sci Technol 105:1–16. ISSN 1005-0302. https://doi.org/10.1016/j.jmst.2021. 07.021 5. Pinkerton A, Mahmood K (2013) Direct laser deposition with different types of 316L steel particle: a comparative study of final part properties. Proc Inst Mech Eng Part B J Eng Manuf 227:520–531. https://doi.org/10.1177/0954405413475961 6. Lee H et al (2017) Lasers in additive manufacturing: a review. Int J Precis Eng Manuf Green Technol 4:307–322. https://doi.org/10.1007/s40684-017-0037-7 7. Heider A, Stritt P, Hess A, Weber R, Graf T: Process stabilization at welding copper by laser power modulation. Phys Procedia 12:81. https://doi.org/10.1016/j.phpro.2011.03.011 8. Hess A, Schuster R, Heider A, Weber R, Graf T (2011) Continuous wave laser welding of copper with combined beams at wavelength of 1030 nm and of 515 nm. Phys Procedia 12:88. https://doi.org/10.1016/j.phpro.2011.03.012 9. Engler S, Ramsayer R, Poprawe R (2011) Process studies on laser welding of copper with brilliant green and infrared lasers. Phys Procedia 12:339–346. https://doi.org/10.1016/j.phpro. 2011.03.142 10. Balck A, Baumann M, Malchus J, Chacko RV et al (2018) 700W blue fiber-coupled diode-laser emitting at 450 nm. Proc SPIE 10514:1051403. https://doi.org/10.1117/12.2286631 11. Onuike B, Heer B, Bandyopadhyay A (2018) Additive manufacturing of Inconel 718—Copper alloy bimetallic structure using laser engineered net shaping (LENS™). Addit Manuf 21:133– 140. https://doi.org/10.1016/j.addma.2018.02.007 12. Imran MK, Masood SH, Brandt M, Bhattacharya S, Mazumder J (2011) Direct metal deposition (DMD) of H13 tool steel on copper alloy substrate: evaluation of mechanical properties. Mater Sci Eng A 528(9):3342–3349386. https://doi.org/10.1016/j.msea.2010.12.099 13. Zhiqi F et al (2018) Selective laser melting of alumina: a single track study. Ceram Int 44:9484– 9493. https://doi.org/10.1016/j.ceramint.2018.02.166 14. Melnikova MA, Shishov AU, Kholopov AA, Misyurov AI, Perestoronin AV, Smirnov AR (2021) Application features of laser coaxial melting of powder materials to produce objects from copper alloys. In: AIP Conference Proceedings, vol 2318, p 150018. https://doi.org/10. 1063/5.0035860
Image Processing for Visual Inspection of Hollow Reinforced Concrete Supports’ Inside Surfaces Andrey Kuznetsov , Anton Ponomarev , Georgy Volchanin , Kirill Fomichenko , and Andrey Gritcutenko
Abstract Corrosion condition diagnostics of reinforced concrete supports of contact network requires implementation of automated control means and application of digital technologies of data processing. The methodology and technical means of visual control, providing improvement of image quality, due to elimination of oscillations of flexible optical probe position at its vertical movement, providing increase of diagnostics process automation level with defect coordinates registration and documentary evidence in the form of replenished database containing images of diagnostics object - inside surface of hollow reinforced concrete supports from ground surface to their base - are offered. This article presents the results of a panoramic image for a cylindrical surface obtained using a controlled video endoscope. This method allows visual inspection and examination of the surface in hard-to-reach places. The aim is to search for defects and corrosion damage in the images obtained, as well as to develop the system for processing and storing data on the support corrosion defects condition. Keywords Reinforced concrete supports · Inside surface · Corrosion · Visual inspection · Information system · Panoramic view
1 Introduction Currently, reinforced concrete structures are widely used in the electrified transport sector. However, due to some reasons, the service life of the catenary supports is decreasing and they are losing their load-bearing capacity. This leads to the catenary network destruction, which entails major economic losses. The main cause of catenary supports breakdown is electrochemical corrosion of steel reinforcement in reinforced concrete structure, which is caused by stray currents.
A. Kuznetsov (B) · A. Ponomarev · G. Volchanin · K. Fomichenko · A. Gritcutenko Omsk State Transport University, 35, Marx Avenue, Omsk 644046, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_39
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The existing methods of diagnosing reinforced concrete towers help to solve the problem of identifying the pre-emergency state, but have a number of drawbacks [1–5]: – the digging method of supports is labor-intensive due to the excavation of the support and the influence of the human factor; – inductive method also requires digging up the support; influence of external electromagnetic field on the device indication; impossibility of diagnosing through the reinforcement mesh; influence of changing thickness of protective layer and pressing force of sensor; corrosion presence is determined by indirect indicators; acoustic and electrochemical methods determine the presence of corrosion by indirect indicators; vibration method allows only diagnose aboveground part, thus not determining its presence and corrosion degree.
2 Methods A promising device for diagnosing corrosion condition is based on quantification of reinforcement corrosion products on hard-to-reach surfaces of reinforced concrete products based on laser-induced breakdown spectrometry (LIBS). A fiber optic cable is moved along the inner surface of the support and the required number of measurements of quantitative composition of corrosion products is made [6, 7]. The disadvantage of the device is that it is difficult to accurately aim the laser at the alleged defect and it is impossible to read off the alleged defect coordinates. The proposed device for diagnosing corrosion condition of the inside surface of reinforced concrete supports is a mechatronic complex with flexible video endoscope probe movement control, presented in Fig. 1. The mechatronic complex contains a control system of the optical probe movement of the video endoscope inside the reinforced concrete supports of the contact network with registration of the alleged defects coordinates and obtaining images of such defects with indication of their sizes and coordinates of their location. The video endoscope includes a flexible optical probe with a short-focus lens and an illumination system. The flexible optical probe has the ability to move by using a stepping motor and rotating the distal part in four directions, the image through the lens enters the opto-electronic converter, the signal is then transmitted via cable to the conversion unit and is displayed on the monitor. The result is a panoramic scan of the reinforced concrete catenary support inside surface, and a controlling personal computer and an algorithm for processing the resulting defect images are used to obtain data on the supports’ condition.
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Fig. 1 Device for corrosion condition diagnostics of the inside surface of reinforced concrete catenary supports: video endoscope 1 with flexible optical probe 2, guide wire 3 with load 4, fixing rings 5, guide tube 6 with limiting ring 7, controlling personal computer 8, stepping motor 9, microprocessor control unit 10, drive roller 11, pressure roller 12, spool of guide wire 13, reinforced concrete contact network support 14 installed in the ground, with steel reinforcement rods 15 and possible corrosion defect 16
3 Main Part In order to verify the mechatronic performance and to obtain a panoramic image, a model of a hollow reinforced concrete support, in the form of a cylinder 160 cm high, 40 cm in diameter, shown in Fig. 2, was fabricated. The inner surface of the cylinder is marked into 10 × 10 cm squares. The symbols of the squares are made in a cylindrical coordinate system. The first digit represents the linear downward displacement (cm), relative to the technological hole. The second digit represents rotation angle, relative to a vertical line through the technological hole. A square with a side of 10 cm corresponds to a rotation of 30 angular degrees. A JProbe-VE type video endoscope with a 6 mm diameter and 3 m length flexible probe, with distal control capability, was used as a visual inspection tool. The graphical diagram of the program algorithm is shown in Fig. 3.
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Fig. 2 Layout of the reinforced concrete support inner surface with markings in cylindrical coordinate system start Sort criterion = date of next measuring Getting supports list (Sort by selected criterion) Showing Supports list by selected criterion yes
Change sort criterion? no
Add new support?
yes
Enter basic parameters of support (type, year of installation, location etc.)
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Selection of measuring; editing of measuring results Define the dynamics of basic parameters changes Calculating planing date of next measuring Editing of planing date of next measuring end
Fig. 3 GSA of the main program module
Define date of measuring; enter measuring results (basic parameters, loading photos of support surface)
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The following sorting criteria are available: by name, by location, by type, by year installed. However, the main default sorting criterion for the displayed supports is the scheduled date of the next support check. In this way, supports to be checked in the near future are displayed first. When adding (creating) a support, its name (designation in accordance with the company’s system for designating supports), year of installation, support type, information on its location are displayed. All these parameters can be corrected later, if necessary [8–14]. When a tower is selected, a list of the measurements taken in that tower is shown. For every measurement the following data is stored. – date of measurement; – planned date for the next check (can be set manually or automatically on the basis of an algorithm that takes account of the support’s current state); – measurement description (describes in plain text what measurements were taken, which features were identified in the support diagnosis); – pictures of the support inner surface, taken in the diagnostic process; – parameters of the defects determined by means of photographs and video analysis of the diagnosis process. It is proposed that all support data and measurements be stored in a local database. The information about the supports is located in the Supports table. The information about the measurements is stored in the Measuring table. However, the number of photos taken for each measurement as well as the number of identified defects may vary. Therefore, it was decided to put photos and information about defects into two separate tables: Images and Defects. As a result, the structure of the database with links between the tables is shown in Fig. 4. When a defect is found, it is suggested to be classified. For this reason, the Defects table contains fields indicating the category of the defect, a numerical assessment of its magnitude, and references to the image in which it was detected and to the relevant measurement. Images Supports
Measurings
Id Name Location Type InstallDate
Id SuppordId Description MeasuringDate State WarningDate
Fig. 4 Database structure
Id MeasuringId Image Defects Id MeasuringId ImageId Size Category
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Fig. 5 Exterior view of the main program window
4 Results As a result of processing the defect information, the support condition (according to the set categorization system) is determined and a suggested date for the next support inspection is suggested. A sample view of the program’s main window is shown in Fig. 5. The images shown in Fig. 5 are a complete development of the inner surface of the reinforced concrete support. To represent a surface 160 cm long and 40 cm in diameter, 180 separate 10 × 10 cm images had to be saved. The program allows you to view all registered images and analyze defect areas in more detail.
5 Conclusion As a result of this research, a prototype of a mechatronic complex for visual inspection of corrosion defects in hollow reinforced concrete supports has been developed. An information system for processing and storing a panoramic image of the support inside surface has been developed. The panoramic image is obtained taking into account the resolution and viewing angle of a video endoscope camera. The described system makes it possible to detect defects with dimensions of at least 1 mm as well as to determine their coordinates.
References 1. Li V, Demina L, Vlasenko S, Zheltenkov A, Mottaeva A (2021) Improving diagnostics of damage to railway catenary supports. In: E3S Web of Conference, vol 284, p 06004. https:// doi.org/10.1051/e3sconf/202128406004
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2. Romanenko Y, Trubitsin MA (2018) Combined way of diagnostics of reinforced concrete conical structures. Mater Sci Forum 931:346–351. https://doi.org/10.4028/www.scientific.net/ MSF.931.346 3. Lundgren K (2002) Modelling the effect of corrosion on bond in reinforced concrete. Mag Concr Res 54(3):165–173. https://doi.org/10.1680/macr.2002.54.3.165 4. Daniyal MD, Akhtar S (2019) Corrosion assessment and control techniques for reinforced concrete structures: a review. J Build Pathol Rehabil 5:1. https://doi.org/10.1007/s41024-0190067-3 5. Chen Z et al (2015) Stray current induced corrosion control in reinforced concrete by addition of carbon fiber and silica fume. MRS Proc 1768. https://doi.org/10.1557/opl.2015.320 6. Tang K (2017) Stray current induced corrosion of steel fibre reinforced concrete. Cem Concr Res 100:445–456. https://doi.org/10.1016/j.cemconres.2017.08.004 7. Nguyen T-H, Le A-T, Nguyen D-D (2020) Bending strength diagnosis for corroded reinforced concrete beams with attendance of deterministic, random and fuzzy parameters. J Struct Int Maint 5(3):183–189. https://doi.org/10.1080/24705314.2020.1765268 8. Carter S, Clough R, Fisher A, Gibsonc B, Russell B (2021) Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials. J Anal At Spectrom 36:2241–2305. https://doi.org/10.1039/D1JA90049H 9. Elsener B (2005) Corrosion rate of steel in concrete–measurements beyond the Tafel law. Corros Sci 47:3019–3033. https://doi.org/10.1016/j.corsci.2005.06.021 10. Ya D (2012) Ultra-wide to mid-wide angle 3X zoom and focus adjustable lens design for industrial video endoscope. Proc SPIE 8557(85570P):9. https://doi.org/10.1117/12.999432 11. Chernin L, Val DV (2011) Prediction of corrosion-induced cover cracking in reinforced concrete structures. Constr Build Mater 25(4):1854–1869 12. Kuznetsov AA, Bryukhova AS, Demin YV (2019) System of optical probe positioning for diagnosing internal surface of hollow reinforced concrete structures. J Instrum Eng 62(3):272– 277. https://doi.org/10.17586/0021-3454-2019-62-3-272-277 13. Wilsch G, Weritz F, Schaurich D, Wiggenhauser H (2005) Determination of chloride content in concrete structures with laser-induced breakdown spectroscopy. Constr Build Mater 19(10):724–730. https://doi.org/10.1016/j.conbuildmat.2005.06.001 14. Martelli S et al (2018) Deep endoscope: intelligent duct inspection for the avionic industry. IEEE Trans Ind Inf 14(4):1701–1711. https://doi.org/10.1109/TII.2018.2807797
The Use of Heat Pump Systems for Heat Supply to Consumers Aleksandra Finichenko , Maria Glukhova , and Sergey Glukhov
Abstract Various heat engineering systems are investigated to utilise low potential waste energy to supply heat and cold to integrated steelworks. The use of heat pump systems for the purpose of supplying heat to consumers is an urgent energy and resource saving issue. The article considers the issue of application and use of airsource heat pump units for heat supply of consumers with heat energy. The scheme of heat pump installation connection in a heating system of a building is offered. With the help of heat pump installation with heat pump Vitocal 242-S installed in a laboratory classroom of Omsk State University of Railway Transport, in the heating period of the current year, the readings of the main parameters of its operation were recorded. According to the research results of these parameters, the following was calculated: heat load on the heating system of the room; temperature of the heat carrier in the supply pipeline; amount of consumed electricity; energy conversion factor. The optimum values for the given heat pump installation at the given modes of work are received. Effective advantages of application of working substance freons are reflected. The question of the heat pump installation application as a source of heat supply in a complex with application of modern devices of heating system, for example, such as fan coil, chiller, underfloor heating, is considered. Keywords Energy saving · Heating system · Heat pump system · Heat energy · Ecology · Conversion factor · Energy · Heat source
1 Introduction The main objective of alternative energy sources is to reduce the burden on the environment. Lack of reliable information on alternative and renewable energy sources and possibilities of energy-saving technologies hinders development of alternative energy and energy-saving market in the Russian Federation. One of the priority tasks is to remove this information blockade, to provide quality and reliable information A. Finichenko (B) · M. Glukhova · S. Glukhov Omsk State Transport University (OSTU), 35, Marx Street, Omsk 644046, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_40
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on the alternative technologies, development in the Russian Federation and in the world. For successful competition of alternative energy with traditional sources, it is necessary to increase literacy of specialists - graduates of higher education institutions, advanced training courses, awareness of citizens, to evaluate the effectiveness in a particular region, taking into account: climatic features; economic peculiarities; fuel and energy balance. Alternative energy sources are the most environmentally friendly in comparison with the traditional ones. Today one of ecological and economic alternative sources of thermal energy is the heat pump unit (HPU). Use of these devices makes it possible to reduce emissions of CO2 , and consequently, and to reduce a greenhouse effect of a planet. Average efficiency of HPU makes about 67%, and also zero emission of harmful substances into atmosphere [1]. The operating process of HPU consists in the following. The source of lowpotential heat (ground, ground water, air) transfers heat to a working body of the heat pump (non-freezing liquid with low boiling point), at that cooling down by some degrees. When circulating in the circuit, the liquid again receives heat from the low-potential heat source and heats up a few degrees, and the heat pump working body heating cycle is repeated. The working medium of the heat pump evaporates when it receives heat, as it has a low boiling point. The resulting gas is compressed by the heat pump compressor and its temperature increases significantly. The heated gas then gives off heat to the consumer (water heating, air heating, heating systems), its temperature drops and it condenses. Since the gas pressure is still high, it has a higher condensation temperature. The condensate pressure is then reduced by throttling. At the outlet, the liquid has a lower temperature than the heat source, so the cycle is repeated [2]. In addition to the possibilities for central heating and cooling, one of the main advantages of heat pumps is that a large amount of heat can be dissipated using a small amount of electrical energy. For example, expending 1 kW of electric power to drive heat pumps we can get 3–4 and sometimes 5 or 6 kW of heat output on the consumer side (Fig. 1). It should be emphasised that electricity in heat pump systems is used to compress and circulate the working fluid.
Fig. 1 Heat pump energy conversion factor
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Indeed, in the actual compression process, part of the electrical energy is used to heat the working body, but most of the heat that is released to the consumer, which is around 65–80% is transferred from the lower potential source (ground).
2 Materials and Methods There are several varieties of heat pumps: ground source and air source (Fig. 2). One heat pump type is a ground source heat pump. In a ground source (geothermal) heat pump, the ground is used as a heat source or radiator. During the winter period the heat is extracted from the ground (the evaporator is in the ground) and in the winter period the heat is pumped into the ground (the condenser is in the ground). So, the working principle is similar to other heat pumps. As a result, geothermal heat pumps can be installed and retrofitted in all large municipal and residential buildings. There is an enormous amount of heat present in the ambient air. This widespread low-potential energy can be produced by air-source heat pumps. The heat from the source (air) is literally taken from the air by the pumps. In winter, heat is taken from the outside air; and in summer, heat is removed from the indoor air. Heat pumps with the air source are usually used both in new buildings and in modernization of existing buildings. Compared to other heat pump types, installation costs are relatively low. However, air-source heat pumps can cause some noise and problems that are more difficult to eliminate [3, 4]. The ground as a heat source is quite stable compared to air. Thus, in winter, geothermal heat pumps can be more efficient than air-source heat pumps due to the relatively high ground temperature. Thus, in colder climates, ground-source heat pumps usually have a higher efficiency than air-source heat pumps. With a certain depth of pipe work, the heat source can remain above the freezing point each year, the depth of pipe work depends on the design method and the climatic conditions. Most air-source heat pumps are so-called split-system heat pumps, which means that one part of the system is physically located inside and another part outside the
Fig. 2 Types of heat pumps: a ground; b air
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Fig. 3 Energy conversion ratio plot on the required temperature of the coolant in the heating system
building. Both sides are connected by refrigerant pipes. Typically, the compressor is located on the outside of the heat pump system. A graph of the energy conversion coefficient versus heating medium temperature in the heating system is shown in Fig. 3. It should be noted that as the required temperature in the heating system decreases, power transfer coefficient (PTC) increases and can reach significant values, hence the efficiency of the installation will increase. It can also be noted that the transformation coefficient depends on the temperature of the low-potential heat source. For example, using the ground loop in a heat pump system, as a low potential heat source, is most efficient, as the ground soil has a constant temperature above 0 °C, unlike air. In terms of rationality, the most efficient way of realising the energy of a heat pump system is the floor heating, as it requires the lowest temperature (around 35– 45 °C), whereas a fan coil or radiator requires 50–55 °C. When directing the energy to the underfloor heating, the conversion factor or heat factor of the heat pump is higher than with a fan coil [5, 6]. However, it is worth noting that the heat pump unit is a supplementary unit, i.e., it works in conjunction with the main heat source. For its more efficient operation, the external circuit of the HPU should be correctly selected according to the living environment and the lowest comfort temperature should be set. A significant advantage of a heat pump system is its environmental friendliness and very high cost-effectiveness, as energy is used only for the pump drive and the heat is extracted from naturally regenerative sources [7, 8]. In order to assess the environmental performance of a plant more accurately, certain evaluation criteria, such as the location of the emission source when using conventional feedstocks and the fuels used, have to be taken into account. It is also necessary to take into account the height of chimneys and the occupancy of the closest territories as well as the obsolescence and physical deterioration of industrial boilers. The introduction of heat pumps is sporadic in Russia. Experience in the use of such units is small, although the conditions for their introduction are quite large, given the latitude of geographical zones of Russia. Nevertheless, every year heat pumps occupy a more significant position in heat supply systems, successfully competing with conventional energy sources. Today, the heat pump is a finished product, represented
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quite widely in the market. It includes not only the basic technological units, but also the controller that operates heat pump and heating system. Considering the lack of own production of heat pump equipment that meets modern technical, operational and economic indicators, and the presence of only fragmented private use of heat pumps, there is a problem of lack of its own positive experience in this area. The experience of design organisations concerning heating on the basis of heat pumps, selection of the heat-carrying equipment according to geographical, climatic and economic features of specific territories is necessary. The lack of scientific research supported by practical experience in the use of heat pumps does not allow the large-scale implementation of heat pumps in the domestic fuel and energy complex. Also, the following factors have a negative impact on the attractiveness of heat pumps in the region: technology is not adapted to the climatic conditions of Siberia; lack of serial supplies of heat pump equipment; lack of experience and competition in design and survey, construction and installation and commissioning of heat sources based on heat pumps; undeveloped service system; inability to combine a heat pump with a traditional heating system [9].
3 Results In order to determine the energy conversion factor of an air-source heat pump, in the period 1–30 October, 2021, in the laboratory classroom of the training building of the Omsk State Transport University, readings of the main parameters of the heat pump unit with a Vitocal 242-S heat pump were recorded (Fig. 4). As a result, the following indicators were obtained and calculated: heat load on the heating system of the room in which the heat pump is installed; temperature of the heating medium in the supply pipeline (τ1 ); the value of consumed electricity, fixed
Fig. 4 Heat pump laboratory unit with heat pump Vitocal 242-S
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Table 1 Summary table of the heat pump system study results Consumption rate
10th day
20th day
30th day
Average for the period
Day
Night
Day
Night
Day
Night
Day
Night
Electrical power, kWh
3.45
3.48
3.43
3.79
3.2
3.17
3.36
3.48
Tp. a. , °C
8
5
2
0
3
−2
4.330
1.0
τ1 , °C
40
38
36
35
39
38
38.33
37.00
Amount of heat Q, kW
8
8
8
8
8
8
8
8
PTC conversion ratio
2.32
2.30
2.33
2.11
2.54
2.52
2.38
2.31
Fig. 5 Schematic diagram of the operation of a heat pump installation in the heating system of a building 1—fan coil; 2—three-way mixing valve; 3—ball valve; 4—circulation pump; 5—buffer tank; 6—thermal relief valve; 7—expansion tank; 8—external module; 9—pumping station; 10— fan; 11—boiler
by two tariff electric meter, PTC. The results are shown in the Table. The table shows that the heat pump operates with an optimum conversion factor, which is between 2.3 and 2.5 (Table 1). A schematic diagram of a heat pump system (shown in Fig. 3) in a building heating system is shown in Fig. 5. A fan 10 is used to supply the external module 9 with ambient air temperature. The heat pump 8 transfers, transforms and converts the heat energy of the working medium. The water is heated to the desired temperature and fed into the buffer tank 5. The upper part of the buffer vessel drains the hot water to the building heating system. The water flows through the circulation loop back to the lower end of the buffer tank and from there enters the heat pump where it is heated further. The mixing valve 2 regulates the temperature of the heating medium entering the fan coil 1 for space heating. The most acceptable, and with high performance, working medium in HPU is Freon R22, which has proven itself in low-capacity heat pump installations at optimum condensing temperatures. The possibility of considering its operation is limited by the condensation temperature of 65 °C and due to the relatively low critical temperature tcr = 96.13 ◦ C.
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The most effective advantages of using freons are their harmlessness, chemical inertness, low flammability and low explosiveness [10].
4 Discussion Also, an important issue in considering the use of HPU as a heat source is the use of modern heating system appliances, such as fan coil units, chiller, underfloor heating, etc. Recommended types of heating systems and supply and return water temperature values: For a system with conventional radiators the temperature range is 60–50 °C; for underfloor heating systems, temperature range is 35–30 °C, and for ventilation and convection systems, the temperature range is 45–35 °C. For the proposed systems, the PTC values are between 2.5 and 4.0. As it is visible from the table the corresponding temperature mode of supplied and removed water in building heating system has low values that corresponds to calculated indicators of heat transfer in a HPU condenser, and also energy conversion factor PTC is in allowable values at which this source of low-potential energy can be considered. Heat pumps possess certain advantages in comparison with traditional ways of heat generation for heating of buildings of various purposes in cold regions of our country. Introduction of heat pumps for heat supply of our region would greatly help to reduce the harmful impact of traditional heat generators on the atmosphere of the city. The advantages of heat pumps are described in works [11, 12]. Economy. Heat pumps, if a source of low-grade energy is properly selected, are more efficient than any boilers. Ubiquity of use. Energy sources for heat pumps are everywhere. Air, water, ground, sewage and many other types of heat sources exist for unlimited use. Eco-friendliness. The plant requires no fuel combustion and therefore produces no harmful emissions into environment. The refrigerant circulating in the system is harmless for people and environment. Versatility. Heat pumps can operate both in heating mode in winter and in airconditioning mode in summer. Safety. Heat pump is fire and explosion-proof, because there is no coolant that heats up to temperatures that can cause ignition. The disadvantages of heat pump systems are the high hardware and installation costs for external circuits and the low temperature of the heated water going to the consumer. Considering the rate of low-rise construction in the RF constituent entities, one can conclude that the use of HPU in the heat supply system of residential buildings will increase. That first of all will tell on reduction of harmful emissions into environment, and also on economy of use of traditional kinds of fuels, such as gas, coal and black oil [13, 14].
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One of the main advantages of using heat pumps EHPA (European Heat Pump Association) is in the reduction of traditional (fossil) fuels, which, in turn, leads to lower emissions of CO2 into the atmosphere. The association predicts that by 2050, 75% of heating in the EU will be using heat pumps [15]. Heat pumps work reliably and safely, providing efficient heating or cooling for buildings. In addition, these technologies can bring noticeable energy and cost savings, adding to the comfort of living.
References 1. Amerkhanov RA (2006) Heat Pumps, p 160. Energoatomizdat, Moscow 2. Burov VD (2007) Thermal Power Stations: textbook. MPEI Publishing House, Moscow 3. Kadtcyn II, Starikov AP, Vedruchenko VR, Agilbayeva MJ (2020) IOP Conference Series: Materials Science and Engineering, vol 8, p 012158. https://doi.org/10.1088/1757-899X/918/ 1/012158 4. Filippov SV (2011) Efficiency of using heat pumps for heat supply of low-rise buildings. Teploenergetika 11:12–19 5. Filippov SP et al (2011) Efficiency of using heat pumps for heat supply of lowstoried housing areas. Therm Eng 58(11):894–902. https://doi.org/10.1134/S004060151111005X 6. Stupitskii EL (2005) An atmospheric discharge initiated by a high-power electron beam. High Temp 43(6):801–809. https://doi.org/10.1007/s10740-005-0127-z 7. Kadtcyn II, Starikov II (2020) Study of the temperature region of coils the city of Omsk for use in heat transfer transformers at railway transport facilities. In: IOP Conference Series: IOP Conference Series: Materials Scienes and Engineering (MSE). IOP Publishing (United Kingdom) AC-2020 8. Makovetskiy MY et al (2018) Actual problems of the development of the Omsk region in the context of modern socio-economic processes in the Russian Federation. Omsk Sci Vet 16(4):94–98 9. Didikov AE (2016) Analysis of economic and environmental aspects of the use of heat pumps for disposal of low-grade heat treatment facilities. J Environ Econ Manag 1:92–98. https://doi. org/10.17586/2310-1172-2016-9-1-92-98 10. Zhang Z, Du F (2013) Hindawi publishing corporation. Optimization and thermoeconomics research of a large reclaimed water source heat pump system. Sci World J 893020. https://doi. org/10.1155/2013/893020 11. Khallyev IA, Tanachev NO (2019) Combined heat supply system heat pump–solar collector. In the book: Energy-2019. Paper presented at the 14 th International Scientific and Technical Conference of Students, Graduate Students and Young Scientists. Conference Materials in 6:95 12. Fedosov SV, Fedoseev VN, Loginova SA, Zaitseva IA (2021) Approximate calculation of a theoretical cycle of a vapor-compression freon loop in an air heat pump. Smart Comprosite Constr 2(4):24–34. https://doi.org/10.52957/27821919_2021_4_24 13. Karnaukh VV (2021) An application of CO2 as a refrigerant for medium temperature heat pumps. J Siberian Fed Univ Eng Technol 14(6):703–713. https://doi.org/10.17516/1999-494X0344 14. Finogenov SL, Kolomentsev AI (2019) Solar thermal propulsion systems with various hightemperature power sources. Siberian J Sci Technol 20(2):251–265. https://doi.org/10.31772/ 2587-6066-2019-20-2-251-265 15. Klyueva NA (2019) Geothermal heat pump–clean energy source. In the collection: the potential of digital transformation of entrepreneurship. Paper presented at the International Scientific and Practical Conference, pp 43–45
Designing a 3D Application Based on Digital Models of Railway Infrastructure Kirill Bogunov
and Stanislav Istomin
Abstract The paper considers the creation of a digital model for railway infrastructure buildings, track, contact network, flora, terrain, etc., as well as the creation of traction and non-traction rolling stock for the simulator with virtual modes of operation. The process of creating 3D models, stations, runs, railway electrification, setting up safety and centralization devices is described. There is no full attachment to the driver’s seat, it is possible, for example, to understand how a traction substation works, how to load/unload cargo in the wagons correctly. In the simulator, it is possible to simulate the movement of trains according to real traffic schedules and change something in this schedule directly in the simulator, which will save millions of dollars in experiments in real life. It is also important that the project offers the possibility of using the multiplayer, i.e., the possibility of organizing remote training for many students and employees within the simulated area. Keywords Railway simulator · Electric railways · Railway infrastructure · Traction substation · Railway stations
1 Introduction At the moment, many simulators are being built both in the Russian Federation and around the world to train employees and students to operate traction rolling stock [1–17]. In Russia, there are currently several companies involved in the development of simulators: Torvest, Zarnitsa and PKB TsT. The simulators offered by these companies are of course effectively used in training, but they simulate the operation of locomotives without regard to the railway infrastructure. In this connection, the issue of developing an application “3D model of traction rolling stock control” using “Imitation Modeling” technology to control cars and locomotives, allowing to determine the optimal mode of operation of rolling stock, taking into account its location, owner, status, plans of use and technical condition, and also to reserve car K. Bogunov (B) · S. Istomin Omsk State Transport University, Marksa Pr. 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_41
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places in order to increase the coefficient of usefulness of rolling stock, and also to train employees and students at managing traction rolling stock.
2 Methods Developing models is a rather time-consuming process that requires a fair amount of developer time and effort. To create models, a basic material is required, an idea of what the object looks like, for example. Firstly, the size must necessarily be in metres, as the engine only works with this unit of measurement, secondly, if we make the model in millimetres, for example, then the model in the modelling program will appear properly, but when export occurs, it will turn out to be very insufficient. Another important material is texture material, the texturing process is considered an important step in creating a model, to get texture material all we need to do is to take a camera and go take a picture of our future model. However, things may not always go smoothly and we have to process the texture material to get quality material. Finally, the most important thing is the personal code. When the key is purchased and registered a personal code is issued to which the objects will be attached. The creation process takes place in 3Ds Max 2021. Without a basic knowledge of 3D Max it is impossible to get a good object, so it is better to study the program first.
3 Results 3.1 Creating a 3D Railway Space in the Trainz Railway Simulator The main challenge during the development process was the accuracy of the station track. An exact replica of the station had to be created. Google satellite maps as well as photographic material of the station were used for the task (Fig. 1). Fig. 1 View of the station from Google Maps satellite maps
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Fig. 2 Example of arranging objects using rulers
Fig. 3 Bridge over the river example of landscape work
The railway personnel working at the station were consulted during the design process. A diagram of the station, showing the traffic lights and switches with their names, was used to arrange the traffic lights. In order to keep the scale realistic, rulers built into the engine were used in the creation process. First the distance was measured on the satellite map and then in the engine. Hence every tree, every house is located where it’s supposed to be located (Fig. 2). The number of rulers on the map is enormous, as it can be seen in the figure above; of course they affect the performance of the map in developer mode, and they can be removed or placed on a separate layer to hide them from the map. The principle of development with rulers has been applied across the whole map. i.e., all the parks, tracks and stations are drawn at realistic scale. A terrain editing section has been used to create realistic terrain. A default elevation of 5 m was used, i.e., a flat surface of 5 m. The section was used to create rivers, lakes, marshes, such as a river or lake (Fig. 3). A set of landscape textures has been selected to give the map its atmosphere. The plan was to make a spring–summer and summer-autumn style map, meaning that when the seasons change the balance of colours is maintained and in harmony with the vegetation on the map.
3.2 Contact Network The railway uses direct current to operate the electric locomotives. Therefore, the overhead line network was designed and installed on the map in accordance with the operating rules. The spans of the overhead contact line network in straight lines are 60 m apart in curves from 40 to 25 m to measure this distance a special spline ruler was used, which every 60, 40 or 25 m, respectively, made a square, in which
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Fig. 4 The outer attachment type is on the left and the inner attachment type is on the right
Fig. 5 Mounting in a curve by external-external type
Fig. 6 Substation at the station
the support with the cantilever should be located. The mounting process proceeds as follows. The first step is to stretch the ruler depending on the chosen one, say 60 m. The second step is to install the brackets, which should be in a zig-zag shape, so that the locomotive power collector rail wears down evenly and does not fray in one place. For this reason, consoles have been designed with an inner conductor fixing and an outer conductor fixing (Figs. 4 and 5). The curves are set to external-external or internal-internal, depending on the type of curve. Substations have also been created to supply the contact line network (Figs. 6 and 7). The physical properties of direct current are that its voltage strength is sufficient for short distances, so it was decided to install substations to maintain a stable voltage. Also the substations on the map are the contact line powering the catenary network. They are also designed according to the operating rules. The operation of the substation is as follows: the substation receives voltage from, for example, the city power grid of 110 kV, then the current is rectified, passes through a kind of filter and the output is 3 kV to supply DC electric locomotives. The location of the traction substations is also practicable. The substation has been installed according to all the rules described above. As can be seen in the drawings, the 110 kV supports come to the substation, then the wires go into the substation and after rectification into the overhead line.
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Fig. 7 Substation stopping point
Fig. 8 Mounted rail gap
Fig. 9 Location of the overhead contact line end
There are also current dividers installed (Fig. 8). The dead section (air gap) is an insulating connection between adjacent sections of the overhead line. It is designed in such a way that when the current collector of the EPS passes, the adjacent sections are electrically connected. Regarding the overhead contact line, it is also worth noting that all warnings related to it are recreated in the simulator. For example: signage of the end of the overhead contact line (Fig. 9).
3.3 Railway Tracks Without question, what is a railway simulator without the railway itself? The railway is also laid using rulers. A set of different tracks has been assembled, for example with concrete and wooden sleepers. The track profile has also been customized, and additional parameters in the track section have been used for this. In the parameters it is possible to set separate heights for spline points. For example, we stretch the track from A to B, obtain two spline points and use the parameters to set a separate height for point A, for example, 5 m, and for point B 8 m is obtained elevation. The engine will raise the terrain by itself when you click on the resulting segment, using
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Fig. 10 Concrete sleeper tracks
Fig. 11 Tracks with wooden sleepers
the mound creation parameter. The track profile can be seen below in the additional software section, where the profile was measured with the software (Figs. 10 and 11).
3.4 Implemented Track Development Skipping away from the environment settings’ description, it is worth returning to one of the important points, namely the track development. All parks have been created in the station model and can be viewed below (Figs. 12 and 13). Fig. 12 General view of the station
Fig. 13 View of the even-numbered station park
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Fig. 14 The process of unloading coal from open railcars
3.5 Industry Work Industry has been implemented in the project. For example, bringing and unloading coal at the TPP. To implement unloading, discharge points are used. A reset point is a section of track with the script for unloading or loading the cargo selected during the script creation process (Fig. 14). As can be seen there is no coal on the dumping point, and there is also a coal icon with a red arrow in the window, which notifies that the industry is acting as a consumer. As can be seen the amount of coal has increased, not so much because there are several dumping points and each point is unloaded almost evenly. Generally, the railcars can be loaded with anything, naturally with what the railcar can be loaded with. The implemented plants at the station are as follows: – – – – – – – – –
unloading coal at the thermal power station; unloading of lumber at PMS-175; unloading of railroad bed at PMS-175; loading of boxes with various goods at LKM Market; loading of grain at Kondratowki; unloading of boxes with various goods at LKM Market; unloading of grain to the FLVZ; unloading of wood chips at the furniture factory; unloading of coal at PMS-175.
As described above, the Su DSP control unnit has been configured for dispatching. The console control unit itself will be demonstrated here. The control unit is responsible for the complete route check, route collection options, arrow check and traffic light check.
3.6 Control Unit Su DSP (zxPath) It is possible to calculate the stations in the properties panel, if everything is OK the unit will show all stations the number of their traffic lights, arrows and route variants.
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For correct operation it is recommended to delete the variant routes, the delete button is in the rightmost corner opposite each station. The initialisation for Petropavlovsk station has found 431 points, 267 traffic lights and 455 routes. Of course, the desk will not work without a properly configured automatic interlocking. On DC-electrified railways, the ALSN frequency is 50 GHz. Also in the project the signalling system operates at 50 GHz. The traffic lights are arranged in accordance with the technological instructions of Petropavlovsk station, the station scheme was used for location and naming of the traffic lights. The triggers installed on the map were SAUT and CLUB, a detailed description of these triggers can be found above. The voice warnings to be installed were selected according to the obstacles. Special attention was paid to lighting in the project. A new set of TSW lighting with halos of light at a distance has been applied. The lighting was arranged using photographic material from the station facilities.
3.7 Artificial Intelligence The project also has an artificial intelligence called bots set up. The bot performs the task assigned to it. Tasks are assigned in the rules section, specifically in the Driver Setup rule. The process of creating tasks for the bot can overlap with programming. For example, to track an arriving train. As an example, you can sort out a small set of tasks for the bot in the introductory session of the project. In the Driver Setup rule the driver controlled by the bot should be found as well as the rules to be assigned to it (Fig. 15). Before setting tasks to the bot, the sequence of tasks needs to be planned. In the example it is necessary for the bot to start the locomotive, drive to the odd traffic light at NM17, unhitch from the train and drive to the depot after the signal is given, and turn off the locomotive when it arrives. Task description from left to right: – – – – –
task to raise the current collector; task to assign freight priority; task of switching on the spotlight; task to check for the opening of the route into the odd-numbered park; task to proceed to exit traffic light HM17;
Fig. 15 Rules for a bot
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task to uncouple two wagons from the train, i.e. two-section locomotive; task to move in shunting order to the depot; task to switch off the searchlight; the task of lowering the current collector.
The zxPath system is used to prepare routes and the zxPath AddPath rule in this rule requires the developer to prepare the routes themselves in advance, which will be assembled automatically. These tasks will start immediately after startup, in case it is necessary for the bot to start the task later, special tasks are created with a waiting time of 30 s to 1 h.
4 Conclusions A model of four stations, marshalling and receiving yards, locomotive and railcar depot stations, it is possible to improve traction rolling stock management skills, improve dispatcher skills, learn the basics for operation of different railway divisions and the situations associated with them. Understand the operation of the railway: making up trains, dispatching and receiving freight. A track signalling system is set up in the work in accordance with the Railway Signalling Instruction (RSI). A dispatching system is implemented in the work. The principle of its operation is that a person can use it to collect routes from point A to point B or open/close traffic lights by their names. There is also a scripting system in operation, the principle of which is that the user has to perform tasks that will appear on the screen. All locomotives have locomotive signalling, ALSN, CLUB and TSCBM systems set up. An industrial and freight transport system has been implemented on the map. A marshalling hump with braking positions which slow down the wagons has also been implemented. The work also created a DSP desk for training of dispatcher skills and presented a properly designed and installed overhead contact network, demonstrated the work of the substation. The prototype 3D application has been implemented in the educational process at the B. Ashimov Petropavlovsk Railway College to train specialists in the field of electric transport of railways.
References 1. Liu C, Song Y et al (2019) Parallel implementation of the auxiliary power system model of the electric locomotive for hardware-in-the-loop simulation. IET Power Electr 12(13):3521–3526. https://doi.org/10.1049/iet-pel.2019.0220 2. Huang J et al (2021) Slipping detection of electric locomotive based on empirical wavelet transform, fuzzy entropy algorithm and support vector machine. IEEE Trans Veh Technol 70(8):7558–7570. https://doi.org/10.1109/TVT.2021.3094872
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3. Rodriguez RF, Trovão JP, Solano J (2022) Fuzzy logic-model predictive control energy management strategy for a dual-mode locomotive. Energy Conv Manag 253:115111. https://doi.org/ 10.1016/j.enconman.2021.115111 4. Lysenko DA et al (2021) Implementation of the control algorithm of the traction electric equipment. J Phys Conf Ser 2061(1):012135. https://doi.org/10.1088/1742-6596/2061/1/ 012135 5. Kutovoj Y, Kyrylenko Y, Obruch I, Kunchenko T (2021) Application of intelligent control systems in electric drives of rail vehicles. In: IEEE 2nd KhPI week on advanced technology, KhPI week 2021–conference proceedings, pp 709–713. https://doi.org/10.1109/KhPIWeek5 3812.2021.9570026 6. Montrone T, Pellegrini P, Nobili P (2018) Real-time energy consumption minimization in railway networks. Transp Res Part D Transp Environ 65:524–539. https://doi.org/10.1016/j. trd.2018.09.018 7. Montrone T, Pellegrini P, Nobili P (2017) Energy consumption minimization problem in a railway network. Transp Res Procedia 22:85–94. https://doi.org/10.1016/j.trpro.2017.03.013 8. Bécsi T, Aradi S (2017) Energy saving possibilities at the hungarian state railways. Transp Res Procedia 27:617–623. https://doi.org/10.1016/j.trpro.2017.12.054 9. Sanchis IV, Zuriaga PS (2016) An energy-efficient metro speed profiles for energy savings: application to the valencia metro. Transp Res Procedia 18:226–233. https://doi.org/10.1016/j. trpro.2016.12.031 10. Ding Y, Bai Y, Liu F, et al (2009) Simulation algorithm for energy-efficient train control under moving block system. In: WRI world congress on computer science and information engineering, CSIE 2009, vol 5, pp 498–502. https://doi.org/10.1109/CSIE.2009.323 11. Carvajal-Carreño W, Cucala AP, Fernández-Cardador A (2014) Optimal design of energyefficient ATO CBTC driving for metro lines based on NSGA-II with fuzzy parameters. Eng Appl Artif Intell 36:164–177. https://doi.org/10.1016/j.engappai.2014.07.019 12. Albrecht AR, Howlett PG, Pudney PJ, Vu X (2013) Energy-efficient train control: From local convexity to global optimization and uniqueness. Automatica 49(10):3072–3078. https://doi. org/10.1016/j.automatica.2013.07.008 13. Scheepmaker GM, Goverde RMP, Kroon LG (2017) Review of energy-efficient train control and timetabling. Eur J Oper Res 257(2):355–376. https://doi.org/10.1016/j.ejor.2016.09.044 14. Treige P (2000) On-board energy measurement at electric motor vehicles of deutsche bahn. Energiemessung auf elektrischenTriebfahrzeugenbei der DeutschenBahn. Eb - ElektrischeBahnen 98(8):300–305 15. Behmann U (2015) Energy-saving driving in an area of conflict between informatics and reality. EnergiesparendesFahrenimSpannungsfeldzwischenInformatik und Realität. Eb ElektrischeBahnen 113(11):578–583 16. Graßmann S, Behmann U (2014) Bahnenergievermessung und -rückspeisungbei den DBVerkehrsunternehmen. ElektrischeBahnen 4:168–171 17. Van Der Spiegel B (2009) Railway energy measuring, managing and billing. In: 6th international conference on the European energy market, EEM 2009. https://doi.org/10.1109/EEM.2009.520 7111
Designing a 3D Application Based on Digital Models of Rolling Stock Kirill Bogunov
and Stanislav Istomin
Abstract The article considers creation of traction algorithm in E2 engine, presents graphs of traction characteristics, gives algorithm flowcharts. The project also includes not only the driver’s cab of traction rolling stock, but also cabins of MU and passenger cars of various classes. In the simulator, it is possible to simulate the movement of trains according to real traffic schedules and change something in this schedule directly in the simulator, which will save millions of dollars in experiments in real life. It is also important that the project offers the possibility of using the multiplayer, i.e., the possibility of organizing remote training for many students and employees within the simulated area. The goal of the described project is to develop an application “3D management model for traction rolling stock” using “Imitation Modeling” technology for the management of wagons and locomotives, allowing one to determine the optimal operation mode of rolling stock, taking into account its location, ownership, status, usage plans and technical condition, as well as to reserve car places in order to increase the efficiency of the rolling stock, and to train employees and students on traction management. Keywords Electric locomotives · Digital locomotive · Locomotive characteristics · Simulators
1 Introduction The use of various types of simulators in a wide range of human activities is extremely widespread. Although the word ‘simulator’ in its modern meaning emerged in the twentieth century, the notion of a device used for human training and shaping certain skills probably existed at the dawn of civilisation. Historically, the objects of modelling on simulators were first of all processes where training on real objects could lead to severe consequences or processes which are difficult or impossible to K. Bogunov (B) · S. Istomin Omsk State Transport University, Marksa Pr. 35, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_42
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reproduce during training. In today’s environment, this is especially true in areas such as railways, the military, aviation, nuclear power, etc. With the development of simulation technology on the one hand and the increasing complexity of the technical solutions being studied on the other, simulation methods have penetrated into many other fields of human activity. The need to train large numbers of specialists with similar skills to work with similar equipment has also stimulated the development of simulation technology. In some fields, e.g. air transport, simulators are an indispensable part of the training process, as well as of the employee certification process. Another aspect of the use of simulators should be mentioned: simulation of critical, extreme conditions on them. NADS (National Advanced Driving Simulator), the most advanced automobile simulator worth more than 50 million dollars, is one of such simulators. A typical task for such a simulator: everyone knows that driving under the influence of alcohol is dangerous. However, there is almost no concrete information about the behaviour of drunk drivers, and carrying out relevant experiments on a real car in urban conditions will undoubtedly have the most unfortunate consequences. The use of a simulator for such studies is the only alternative. The increasing complexity of railway technology has made the use of various types of simulators feasible. Simulators have been used on US railways for more than 20 years to train, monitor and certify drivers. On European railways, simulators were introduced in France in the 1980s, following a number of serious accidents. However, they are not used in Europe for employee assessment, due to the European railway unions’ disapproval of the methodology. At the moment, many simulators are being built both in the Russian Federation and around the world to train employees and students to operate traction rolling stock. In Russia, there are currently several companies involved in the development of simulators: Torvest, Zarnitsa and PKB TsT. The simulators offered by these companies are of course effectively used in training, but they simulate the operation of locomotives without regard to the railway infrastructure. In this connection, the issue of developing an application “3D model of traction rolling stock control” using “Imitation Modeling” technology to control cars and locomotives, allowing to determine the optimal mode of operation of rolling stock, taking into account its location, owner, status, plans of use and technical condition, and also to reserve car places in order to increase the coefficient of usefulness of rolling stock, and also to train employees and students at managing traction rolling stock [1–17].
2 Methods Developing models is a rather time-consuming process that requires a fair amount of developer time and effort. To create models, a basic material is required, an idea of what the object looks like, for example. Firstly, the size must necessarily be in metres, as the engine only works with this unit of measurement, secondly, if we
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make the model in millimetres, for example, then the model in the modelling program will appear properly, but when export occurs, it will turn out to be very insufficient. Another important material is texture material, the texturing process is considered an important step in creating a model, to get texture material all we need to do is to take a camera and go take a picture of our future model. However, things may not always go smoothly and we have to process the texture material to get quality material. Finally, the most important thing is the personal code. When the key is purchased and registered a personal code is issued to which the objects will be attached. The creation process takes place in 3Ds Max 2021. Without a basic knowledge of 3D Max it is impossible to get a good object, so it is better to study the program first. Let’s consider the example of EP2K electric locomotive for creating an add-on.
3 Results To create a model of a DC locomotive brand EP2K its drawings were used. The drawings are required for our model to have the correct scale and to be correctly perceived by the engine. The locomotive drawings are made in metres and the E2 engine understands metres. After preparing the drawings in 3D Max, the chasing process starts. As far as we know, embossing is a technological process of making a pattern, an inscription, an image, which consists in embossing a certain relief on a plate. It is a type of arts and crafts. Also, in 3D Max, a cube is created and embossed from drawings. Embossing in 3D Max can be done using tools. For example: Cut to make cuts in polygons, Extrude to stretch or deepen objects and Chamfer to create a chamfer. (Figs. 1, 2, 3 and 4). The traction characteristics of the rolling stock are required for traction control in the E2 engine and can be found in the rolling stock manual. Once the traction characteristics have been determined, they need to be implemented in the engine. In
Fig. 1 Modeled and painted electric locomotive EP2K in 3Ds Max
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Fig. 2 Modeled and painted high-voltage roof equipment of the EP2K electric locomotive
Fig. 3 Modeled and painted body and mechanical equipment of the electric locomotive EP2K
Fig. 4 Modeled and painted EP2K electric locomotive driver’s console
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engine E2 possibility of file enginespec creation is realized in it and it will store all traction and brake characteristics, there are two ways of filling of a file, to make them manually breaking traction characteristics on positions, and by means of the special program, however the essential lack of the program is limitation of positions, all in the program them 8 and at electric locomotive EP2k their 51 not including running positions which turns out in total 15 (on 5 on each TEM connection). However it is necessary to tell that running positions will be not traction positions because of the engine feature, therefore running we will have only 5 positions and in total it turns out 56 positions which should be processed under the throttle-power tag. It is also worth noting that the EP2k electric locomotive has the possibility of using rheostat braking with only 14 positions to implement rheostat braking, it is also necessary to enter in the enginespec file settings of rheostat braking under dynamicbrake tag. The Throttle-power container has nn elements defining a sequence of paired sets of numerical data grouped into sub-containers (data arrays), which depend on the type of propulsion force at each thrust setting. Each sub-container or array refers to a particular throttle of a particular engine’s performance curves, points on the graph for inclusion in dynamic simulation models. The first value(s) corresponds to zero power or neutral and no thrust or speed values (both are zero factors). Most of the Throttle-power container has a sequence of numeric subcontainers, matched by numbers, which represent the count of integers defined in the throttlenotches tag value of the “Motor” container. The last Throttle-power subcontainer index specified in the list must match the number of the integer defined by the value set by the throttle-notches tag in the “Motor” container. Typically this value is either 8 or 32. {set: 0, 1, 2,…, 6, 7, 8} for diesels and trains; {set: 0, 1,…, 30, 31, 32} for electric locomotives or mainline diesel locomotives. A block with dynamic brakes will have a double array of 8 or 32 values corresponding to dynamic braking enabled (deceleration or braking mode) or not enabled (acceleration). There are rows with numerical names within each sub-container. Each line indicates the value of speed (m/s) and tractive force (kilonewtons (kN)). Together, these points define the tractive force graph for a particular throttle mark. Next, the driver’s controller needs to be programmed for traction control, the controller has 18 positions, 3 traction (H, FP, C) neutral position 0 and 14 rheostat braking positions (PT1-PT14). After programming the driver controller, the position switch is then programmed in a separate flow function. Position switching has been programmed for two modes of manual and auto dialling. Manual mode involves dialling the position by moving the train driver controller from FP position to N position when raising the position, and from FP position to S position when resetting the position. Autosetting involves increasing positions according to the current set in the crossing current and the maximum speed set, the crossing current and maximum speed being set by the driver. Transition current is set from 0 to 700 A, usually from 350 to 550 A, which provides a smooth acceleration of the train, and the speed can be adjusted to 160 km/h.
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Automatic up-setting is achieved by setting the driver’s controller to N position, the locomotive increases its position according to the set current and simultaneously compares the current speed with the set speed limit. If the current speed has reached the speed limit, the locomotive stops gaining positions. If the locomotive reaches the travel position (travel positions: 21, 38, 51), the autoset stops for 5 s, the buzzer sounds to indicate reaching the travel position and, if the driver does not carry out lowering (bypass) during the delay, the locomotive re-arranges the motors and continues dialing. To reset positions in autoset, the driver’s controller must be placed in position S and the locomotive will reduce to position 1; when it reaches a running position, the reset will be delayed for 5 s in the same way as in the case of dialling. It is worth noting that both manual and auto mode reset to 1 position in order to disassemble the traction diagram, the controller’s crank is placed in position 0. To use rheostat braking it is necessary to switch on the tumbler “electric braking”, the tumbler is on the panel near to gauges, after switching on the tumbler the driver controller is put in position PT—the circuit is assembled on braking. By placing the controller further in the direction of the braking zone braking force increases, in total there are 14 such positions, braking is carried out with force to 175 kN on 14 positions that it is possible to check up by looking the brake characteristic, in drawing it is visible that the maximum rated force will be 175 kN graphs all fall on this value. It should also be noted that rheostat braking cannot be used in combination with pneumatic braking as it produces negative longitudinal reactions in the train and burns out of the braking resistors as the load increases, so the circuit is disassembled in the presence of pressure in the brake cylinders, when the condition that braking was nevertheless applied together with pneumatic braking is disassembled, braking is done pneumatically and the microprocessor control system displays a notice.
4 Conclusions A track signalling system is set up in the work in accordance with the Railway Signalling Instruction (RSI). The SAUT voice warning system and the DISK axle-box checking system have also been implemented. The work includes implementation of level crossings, both regulated and unregulated, a large set of different railway equipment with the possibility of control, DC locomotives such as: VL-10(U, K), VL-11, 2ES6 “Sinara”, 2ES10 “Granit”, EP2K, CHS2(T, K), CHS7, DC electric trains ED4(M), ED2(T), ET2(M, EM), ER2(T, R), and also implemented 2TE10(M, U), 2TE116, CHME3(T), TEM1, TEM2. There is also a scripting system in operation, the principle of which is that the user has to perform tasks that will appear on the screen. All locomotives have locomotive signalling, ALSN, CLUB and TSCBM systems set up.
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References 1. Liu C, Song Y et al (2019) Parallel implementation of the auxiliary power system model of the electric locomotive for hardware-in-the-loop simulation. IET Power Electron 12(13):3521– 3526. https://doi.org/10.1049/iet-pel.2019.0220 2. Huang J, Jiang B, Xu C, Wang N (2021) Slipping detection of electric locomotive based on empirical wavelet transform, fuzzy entropy algorithm and support vector machine. IEEE Trans Veh Technol 70(8):7558–7570. https://doi.org/10.1109/TVT.2021.3094872 3. Rodriguez RF, Trovão JP, Solano J (2022) Fuzzy logic-model predictive control energy management strategy for a dual-mode locomotive. Energy Conv Manag 253:115111. https://doi.org/ 10.1016/j.enconman.2021.115111 4. Lysenko DA, Konyukhov VY, Astashkov NP (2021) Implementation of the control algorithm of the traction electric equipment. J Phys Conf Ser 2061(1):012135. https://doi.org/10.1088/ 1742-6596/2061/1/012135 5. Kutovoj Y, Kyrylenko Y, Obruch I, Kunchenko T (2021) Application of intelligent control systems in electric drives of rail vehicles. In: IEEE 2nd KhPI week on advanced technology, KhPI week 2021-conference proceedings, pp 709–713. https://doi.org/10.1109/KhPIWeek5 3812.2021.9570026 6. Montrone T, Pellegrini P, Nobili P (2018) Real-time energy consumption minimization in railway networks. Transp Res Part D Transp Environ 65:524–539. https://doi.org/10.1016/j. trd.2018.09.018 7. Montrone T, Pellegrini P, Nobili P (2017) Energy consumption minimization problem in a railway network. Transp Res Proc 22:85–94. https://doi.org/10.1016/j.trpro.2017.03.013 8. Bécsi T, Aradi S (2017) Energy saving possibilities at the Hungarian state railways. Transp Res Procedia 27:617–623. https://doi.org/10.1016/j.trpro.2017.12.054 9. Sanchis IV, Zuriaga PS (2016) An energy-efficient metro speed profiles for energy savings: application to the valencia metro. Transp Res Proc 18:226–233. https://doi.org/10.1016/j.trpro. 2016.12.031 10. Ding Y, Bai Y, et al (2009) Simulation algorithm for energy-efficient train control under moving block system. In: WRI world congress on computer science and information engineering, CSIE 2009, vol 5, pp 498–502. https://doi.org/10.1109/CSIE.2009.323 11. Carvajal-Carreño W, Cucala AP, Fernández-Cardador A (2014) Optimal design of energyefficient ATO CBTC driving for metro lines based on NSGA-II with fuzzy parameters. Eng Appl Artif Intell 36:164–177. https://doi.org/10.1016/j.engappai.2014.07.019 12. Albrecht AR, Howlett PG, Pudney PJ, Vu X (2013) Energy-efficient train control: from local convexity to global optimization and uniqueness. Automatica 49(10):3072–3078. https://doi. org/10.1016/j.automatica.2013.07.008 13. Scheepmaker GM, Goverde RMP, Kroon LG (2017) Review of energy-efficient train control and timetabling. Eur J Oper Res 257(2):355–376. https://doi.org/10.1016/j.ejor.2016.09.044 14. Treige P (2000) On-board energy measurement at electric motor vehicles of deutsche bahn. Energiemessung auf elektrischenTriebfahrzeugenbei der DeutschenBahn. Eb - ElektrischeBahnen 98(8), 300–305 15. Behmann U (2015) Energy-saving driving in an area of conflict between informatics and reality. EnergiesparendesFahrenimSpannungsfeldzwischenInformatik und Realität. Eb ElektrischeBahnen 113(11):578–583 16. Graßmann S, Behmann U (2014) Bahnenergievermessung und -rückspeisungbei den DBVerkehrsunternehmen. ElektrischeBahnen 4:168–171 17. Van Der Spiegel B (2009) Railway energy measuring, managing and billing. In: 6th international conference on the European energy market, EEM 2009. https://doi.org/10.1109/EEM.2009.520 7111
Energy Efficiency Level Analysis of Train Traction in a Structural Unit Alexey Davydov
Abstract This article describes an approach to analysing the energy efficiency of train traction in a linear structural subdivision (operational locomotive depot) based on a statistical study of automated systems’ data sets on the transportation work and consumption of fuel and energy resources to draw the conclusions about the current situation. It is important to filter out unreliable data that has entered the databases due to the malfunction of accounting equipment, on-board systems or as a result of operator error at the information entry stage. Data filtering is carried out after decomposition of the array of information by rolling stock series, type of traffic and operation. If necessary, it can be detailed to each specific locomotive or locomotive crew. On the basis of the conclusions obtained, a programme to improve energy efficiency in the most expensive part of the railway enterprise budget—train traction—is formed or, if necessary, adjusted. It should be noted, however, that this analysis is performed mainly to identify rolling stock with increased energy consumption due to its technical condition or locomotive crews with inefficient train driving techniques. Keywords Energy efficiency · Train traction · Rolling stock · Specific energy consumption · Fuel and energy resources · Algorithm
1 Introduction Rail transport is one of the largest consumers of fuel and energy resources in the Russian Federation. Traction accounts for about 70% of all energy resources consumed in the industry. According to the forecasts presented in the Energy Strategy of the Russian Railways Holding until 2030, growth in transportation operations will lead to an increase in energy consumption and the consumption of electric power for traction trains will reach 58.3 billion kWh, and of diesel fuel, 3.66 million tonnes. In the context of the incessant rise in energy prices and instability on the global energy market, the search for ways to reduce energy consumption is taking centre stage in the A. Davydov (B) Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_43
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energy management system of railway enterprises. These include the introduction of rolling stock with more energy-efficient engines and the use of cheaper energy from the atom and natural gas. Both Russian [1–6] and foreign scientists [7–16] conduct research in the field of increasing the traction energy efficiency of trains. The accumulation of large amounts of information about the transportation process in the system of centralized processing of the driver’s route, automated system of operational transportation management, etc. make it possible to build trajectories of traction energy efficiency in a particular structural subdivision.
2 Materials and Methods The technical measures described above lead to a qualitatively new level of railway energy, but are extremely costly. The second way to improve energy efficiency, which is less costly, is a qualitative analysis of the relationship between electricity and diesel fuel consumption and the various qualitative and quantitative indicators that characterise the transportation process and the rolling stock on which it is carried. Based on this analysis, ways to improve the energy efficiency of traction can be identified. It is advisable to carry out this analysis at the same levels for which the specific fuel and energy consumption rate is established. This is done in order to target the problematic element. The main levels of traction energy efficiency analysis in a structural subdivision (operational locomotive depot) are shown in Fig. 1. Mathematical statistics and data mining methods are used to conduct the research. The technology of their application proposed by the author is described in this article.
Fig. 1 Basic levels of energy efficiency analysis of train traction in the structural unit
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3 Results In order to conduct an energy efficiency analysis, a volume of locomotive crew trip data for the last 3–5 years should be prepared. To test the technology, trip data for 2018–2020 were collected for the operating locomotive depot located in the Siberian region. The source of data is the information system of the corporate information repository “Locomotive Fleet” (LPS KIH), report form THO-125 “Report on fuel or electricity consumption for train traction”. Figure 2 shows histograms of average temperature, average maximum and minimum and fluctuations of atmospheric air temperature in Western Siberia for 1981–2020. When analysing the data in Fig. 2, data for December–January and June-July are allocated to different arrays to exclude the influence of outdoor temperatures. Travel information for the remaining months of the year is not included in the data set due to significant temperature fluctuations between February–May and August–November. As an example, we will highlight the travel data for June–July 2020. In order to compile the data to be examined from the travel data, trips for which the Specific Energy Consumption (SEC) in the jth type of movement of the kth locomotive series along the mth track, within the pth axle load quantum of a freight car (train weight), do not satisfy the ratio: jkmp
bi
≤ b jkmp ± 3σ jkmp ,
jkmp
(1)
is the value of specific consumption in each ith trip in the jth type of where bi traffic of the kth locomotive series along the mth section within pth quantum of freight car axle load (train weight), kW·h/10 thousand tonne-km gross; bjkmp is the average value of the specific consumption in each ith trip in the j-th movement mode, kth locomotive series along the mth section, within the pth quantum
Fig. 2 Atmospheric air temperature characteristics in West Siberian region for 1981–2020
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A. Davydov
of freight car axle load (train weight), calculated as the ratio of total fuel and energy resources (FER) consumption to total work in a sample of trips, kW·h/10 thousand t-km gross; σ jkmp is the root mean square deviation in the general population of jth type of travel, kth locomotive series, along the mth section, within the pth quantum of freight car axle load (train weight), kW·h/10 thousand tonne-km gross. The possibility of applying the three-sigma rule for the general population of the specific consumption of electricity (diesel fuel) has been proved by the author using extensive statistical material collected for all railways of the Russian Federation for 2008–2012. After excluding the trips with unreliable energy consumption data from the general population and the trips in the itinerary sheets for which the rationing sign “fact according to the norm” is set up, a table in the form of Table 1 is generated. Based on Table 1, an analytical Table 2 was constructed, containing information on the contribution of each analysis category to the total value of specific fuel and energy consumption for the structural subdivision as a whole. For this purpose, the values of the shares of work for each category of analysis were calculated in column 4:
δi =
A jkm · 100%, Asu
(2)
where A jkmp is the transport work in the jth type of traffic performed by the kth locomotive series, along the mth section, 10 thous. t-km gross; Asu is transport work for the entire structural unit, 10 thousand t-km gross. The following formula is used to calculate the specific consumption components for each category of analysis: rb = δi · b jkm .
(3)
where b jkm is the specific consumption of fuel and energy resources in the jth type of traffic performed by the kth locomotive series on the mth section, kW·h/10 thousand tonnes-km gross. Thus, the sum of the components is the specific consumption for the structural unit as a whole: rb = bsu . (4) jkm
The study in the next step depends on the analysis objectives. Usually, the objective is to reduce the specific flow rate. Considering that it is almost impossible to influence the structure of the work, energy efficiency improvements should be sought in the rolling stock that carries out the highest volume of work.
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Table 1 Input data for energy efficiency analysis of electric traction trains Train station
Type of movement
Section 1
Freight
Rolling stock series
Number of trains per period
2ES6
1236
88,288
7,213,130
81.7
211
10,799
987,029
91.4
VL10K
Specific fuel and energy consumption, kW·h/10 thousand tonnes-km gross
89
5923
461,402
77.9
Other
43
1883
170,788
90.7
Passenger
EP2K
511
4324
555,202
128.4
Suburban
CS4
64
258
50,749
196.7
2ES6 VL10K
9
191
52,983
277.4
379
4043
1,331,764
329.4
EP2K
18
103
40,016
388.5
Shuttle
VL10K
24
40
30,604
765.1
Freight
2ES6
962
72,530
6,186,809
85.3
2ES4K
117
7779
651,102
83.7
Other
38
1797
174,489
97.1
Passenger
EP2K
211
2082
300,433
144.3
Commercial
2ES6
11
64
18,195
284.3 314.7
VL10K Section 3
Fuel and energy consumption, kWh
2ES4K
Commercial
Section 2
Work, 10 ths t-km gross
Freight
264
1409
443,412
1028
58,786
5,596,427
95.2
324
16,398
1,582,407
96.5
2ES4K
73
2962
275,762
93.1
Other
27
982
90,835
92.5
2ES6 VL10K
Commercial
2ES6 VL10K
Total for the structural unit
14
217
63,863
294.3
137
1558
609,490
391.2
5790
282,416
26,886,891
95.2
The data in Table 1 shows that 94.9% of the work is for the freight traffic, including 82.2% performed on electric locomotives of 2ES6 and VL10K series. It is this type of traffic on these rolling stock series that should receive the most attention. Further research is conducted to identify traction rolling stock and locomotive crews that have a significant deviation from the statistical average. We will choose the VL10K series as the one under investigation. From the set of trips of electric locomotives of VL10K series in freight traffic it is necessary to exclude those in which: • linear run is less than the length of the train section, • non-scheduled stops and stops before interdiction signal are present; • the weight of the train varied while travelling the section.
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Table 2 Analytical table of the study of fuel and energy consumption in the structural unit Train station
Type of movement
Section 1
Freight
Section 2
Section 3
Rolling stock series
2ES6
Share of work performed by a series of rolling stock on a section in the form of traffic δi , %
Specific fuel and energy consumption component, 10 kt-km gross
Contribution of the specific fuel and energy consumption component of the rolling stock series on the section as traffic to the value of the specific fuel and energy consumption of the structural unit, %
31.26
25.54
VL10K
3.82
3.49
26.83 3.67
2ES4K
2.10
1.63
1.72
other
0.67
0.60
0.64
Passenger
EP2K
1.53
1.97
2.06
Suburban
CS4
0.09
0.18
0.19
Commercial
2ES6
0.07
0.19
0.20
VL10K
1.43
4.72
4.95 0.15
EP2K
0.04
0.14
Shuttle
VL10K
0.01
0.11
0.11
Freight
2ES6
25.68
21.91
23.01
2ES4K
2.75
2.31
2.42
other
0.64
0.62
0.65
Passenger
EP2K
0.74
1.06
1.12
Commercial
2ES6
0.02
0.06
0.07
VL10K
0.50
1.57
1.65 20.81
Freight
Commercial
Total for the structural unit
20.82
19.82
VL10K
2ES6
5.81
5.60
5.89
2ES4K
1.05
0.98
1.03
other
0.35
0.32
0.34
2ES6
0.08
0.23
0.24
VL10K
0.55
2.16
2.27
95.20
100.00
100.0
A total of 164 trips on section 1 and 281 trips on section 3 were selected for further investigation. The next step is to group the trips according to the average axle load of the freight wagon. The distribution of trips in the considered set of trips is shown in Fig. 3. A study is then required for each axle load range. In this case, trips for which the condition is fulfilled are subject to a detailed analysis: σb bk ≥ b + tα,n−1 · √ , n
(5)
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80 70 60 50 40 30 20 10 0 5-7
7-9
9-11
11-13 13-15 15-17 17-19 19-21 21-23 23-25 1
3
Fig. 3 Distribution of VL10K electric locomotive trips in freight traffic by axle load of the freight car
where bk is specific consumption in the kth trip on a section with a train from a certain load range on the freight car axle, kWh/10 thousand tonnes gross tonnes: b is specific consumption calculated over all selected trips (ratio of the total fuel and energy consumption over all selected trips of a locomotive series on a specific section as it runs with trains of a fixed range of freight car axle load (train weight) to the operation on these trips): b=
Bz , Az
(6)
tα,n−1 is the critical value of the t-statistic (Student distribution) with a significance level of ∝ , number of degrees of freedom n-1; σb is the root mean square deviation calculated for trips on the kth section with a train from a given range of freight car axle loads, kWh/10 thousand tonnes gross; n is the number of trips in the sample. Itinerary sheets satisfying this condition are considered in terms of the number of locomotive and locomotive crews performing the trips. If a systematically higher specific energy consumption is determined for the trips with similar conditions on the same traction vehicles or the same locomotive crews, the sample size is increased to several months. If a systematically higher specific fuel consumption is also observed in the increased time range, it is recommended to perform unscheduled maintenance of the identified locomotives or to conduct monitoring trips with the locomotive crews with higher specific fuel consumption in their trips. Here is an example of a further analysis on the data series VL10K, freight traffic, on the train section 3 with trains with an average axle load of a freight car from
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Table 3 Analysis of specific fuel and energy consumption for electric locomotives of VL10K series in freight traffic on Section 3 with trains with a freight car axle load of 15 to 17 tonnes No
Electric locomotive number
1
1989
8
2045
190,390
93.1
2
1698
14
2042
218,698
107.1
3
2340
3
2042
196,440
96.2
4
1718
8
2053
199,962
97.4
5
2357
9
2049
195,270
95.3
6
1549
17
2048
195,584
95.5
7
1815
5
2038
201,354
98.8
8
2440
Total
Number of trips
Work, 10 th t-km gross
Fuel and energy consumption, kWh
Specific fuel and energy consumption, kW·h/ 10 thousand tonnes-km gross
7
2043
184,709
90.4
71
16,398
1,582,407
96.5
Maximum value of the specific energy (formula (5))
100.5
15 to 17 tons. During the period under consideration, 71 trips were made on 8 electric locomotives and the number of locomotive crews was 14. The results of the calculation using the method described above are shown in Table 3. Thus, the condition (5) corresponds to the electric locomotive No. 1698, which shows consistently higher specific fuel and energy consumption under similar operating conditions. This electric locomotive is recommended for unscheduled maintenance in order to identify the causes of increased fuel and energy consumption. The analysis for locomotive crews is carried out in a similar way.
4 Conclusions The procedure described above for performing energy efficiency analysis can be presented as a general algorithm, shown in Fig. 4. Elements of the developed algorithm were tested during the activities to develop programmes to improve the energy efficiency of traction power supply systems and electric rolling stock, carried out by specialists of the Omsk State Transport University on all railways of the Russian Federation. The complexity of creating a general algorithm for energy efficiency analysis lies in the need to take into account the specifics of the transportation process in each individual structural subdivision.
Energy Efficiency Level Analysis of Train Traction …
Data
collection
445
Highlighting the relevant categories that make up energy efficiency
TCO-125 (KIH LP) Analysis of the seasonality of the change in energy efficiency
Setting aside periods with a minimum of δb
Raw data filtering
Grouping trips by the main rationing criterion
Traction unit analysis
Allocation of TPEs for maintenance
Determining the necessary levels of detail in the data
Analysis by locomotive crews
Selection of teams for monitoring visits
Conducting maintenance and training for locomotive crews
Fig. 4 General algorithm for analysing traction energy efficiency of trains in a structural unit
The developed algorithm makes it possible to determine the reserves for increasing energy efficiency within the system in question without its global modification. In the field of energy management, it makes sense to apply Deming’s principles of continuous improvement cycle, that’s why the algorithm in Fig. 4 is cyclic.
References 1. Komyakov AA, et al (2018) Application of an intelligent system for the monitoring of energy efficiency indicators at service locomotive depots. In: Paper presented at the international multiconference on industrial engineering and modern technologies, FarEastCon 2018. Institute of Electrical and Electronics Engineers Inc., Vladivostok, 03–04 October 2018, p 8602926. https:// doi.org/10.1109/FarEastCon.2018.8602926 2. Cheremisin V, Vilgelm A (2020) Intellectual monitoring and planning system of energy efficiency indices of the traction power supply system. IOP Conf Ser Mater Sci Eng 8:012092. https://doi.org/10.1088/1757-899X/918/1/012092 3. Cheremisin VT et al (2018) Development of device for monitoring of energy efficiency of production processes at enterprises. In: Paper presented at the international conference on industrial engineering, applications and manufacturing, Moscow, 15–18 May 2018, p 8728612. https://doi.org/10.1109/ICIEAM.2018.8728612
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4. Cheremisin V et al (2018) Technology for reducing the consumption and losses of electrical energy in the power supply systems of railway consumers. MATEC Web Conf 239:01033. https://doi.org/10.1051/matecconf/201823901033 5. Cheremisin VT et al (2016) Evaluation of the actual effectiveness of energy-saving devices based on artificial intelligence. In: Paper presented at the 2nd international conference on industrial engineering, applications and manufacturing, 19–20 May 2016. Institute of Electrical and Electronics Engineers Inc., Chelyabinsk, p 7911416. https://doi.org/10.1109/ICIEAM.2016. 7911416 6. Komyakov AA, et al (2015) Application of artificial neural networks for electric load forecasting on railway transport. In: Paper presented at the 15th international conference on environment and electrical engineering. Paper presented at the EEEIC 2015: conference proceedings, 10– 13 Jun 2015. IEEE Computer Society, Rome, pp 43–46. DOI https://doi.org/10.1109/EEEIC. 2015.7165296 7. Torben H (2020) Efficiency analyses for the railway sector: an overview of key issues. Res Transp Econ 82:100877. https://doi.org/10.1016/j.retrec.2020.100877 8. Frantasov D, Kudryashova Y (2021) Information and measurement system for electric power losses accounting in railway transport. Transp Res Procedia 54:552–558. https://doi.org/10. 1016/j.trpro.2021.02.107 9. Zhang H et al (2014) Research on traction energy cost intensity and passenger transport efficiency of a metro train. Procedia Soc Behav Sci 138:722–728. https://doi.org/10.1016/j.sbspro. 2014.07.247 10. Ren J, Zhang Q, Feng L (2020) Analysis of factors affecting traction energy consumption of electric multiple unit trains based on data mining. J Clean Prod 262:121374. https://doi.org/ 10.1016/j.jclepro.2020.121374 11. Wang X, Tang T, Su S et al (2021) An integrated energy-efficient train operation approach based on the space-time-speed network methodology. Transp Res Part E Logist Transp Rev 150:102323. https://doi.org/10.1016/j.tre.2021.102323 12. Kapetanovi´c M et al (2021) Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains. Appl Energy 294:117018. https:// doi.org/10.1016/j.apenergy.2021.117018 13. Wang P, Goverde R (2019) Multi-train trajectory optimization for energy-efficient timetabling. Eur J Oper Res 272(2):621–635. https://doi.org/10.1016/j.ejor.2018.06.034 14. Tang Z et al (2021) Predicting the electricity consumption of urban rail transit based on binary nonlinear fitting regression and support vector regression. Sustain Cities Soc 66:102690. https:// doi.org/10.1016/j.scs.2020.102690 15. Bigharaz MH et al (2014) Simultaneous optimization of energy consumption and train performances in electric railway systems. IFAC Proc Vol 47(3):6270–6275. https://doi.org/10.3182/ 20140824-6-ZA-1003.02368 16. Zhang C-Y et al (2016) Data-driven train operation models based on data mining and driving experience for the diesel-electric locomotive. Adv Eng Inform 30(3):553–563. https://doi.org/ 10.1016/j.aei.2016.07.004
Combined Heat Pump and Solar Collector Application Aleksandra Finichenko
and Anastasia Polozkova
Abstract To date, heat pumps are not very popular in the market for alternative energy generation. This is due to the lack of reliable information about the efficiency of a heat pump system. The performance of used installations, the combined scheme of use and the district climatic features were considered in the article. Decent indicators of joint work of a heat pump with a solar collector have led to the conclusions that application of these installations for the purpose of heat supply of consumers is an actual question of energy and resource saving. In the article, the combined method of a solar collector application together with the air heat pump is considered. On the basis of the actual statistical climatic data of Omsk, thermal calculation of a solar collector and the air heat pump in system of a building heat supply is made. The methodology of heat energy production calculation with use of the combined system is resulted. The offered scheme provides high energy efficiency and stable operation of the system during summer and transitional months of the year. Thermophysical properties of working substance of a solar collector and the air heat pump at change of temperature of an environment are considered. Technical calculation of heat pump conversion factor for one of the educational buildings of Omsk State Transport University was made. Keywords Heat pump · Solar collector · Alternative sources · Thermal energy · Heat pump conversion coefficients · Combined system · Ecology
1 Introduction The climatic characteristics of the Siberian region are characterised by high energy costs as well as high thermodynamic losses. The costs, which are calculated for the operation of heating networks and boiler houses, are increasing every year. The above-mentioned objects quite often cause accidents, and this, in its turn, requires both economic and technical solutions [1, 2]. A. Finichenko (B) · A. Polozkova Omsk State Transport University, 35, Marksa Pr, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_44
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The purpose of this work is to carry out performance evaluation in the conditions of a particular region, taking into account its: climatic features; economic features; fuel and energy balance. Researches have shown, that for successful introduction of the presented technology it is necessary to plan the consumption of the generated energy, for example, the specialized schemes of heating of dwelling objects. Nowadays, the development and implementation of alternative energy technologies is actual. But not all of them can boast of high efficiency: windmills (average 80–100 MW), hydroelectric power plants (up to 25 MW on average), various geothermal sources are relatively environmentally friendly (elements and compounds can be used in chemical industry) from 3000 MW in the USA and up to about 500 MW in Japan.) One economical and environmentally friendly alternative energy source is the heat pump unit (HPU). Its use reduces the emission of carbon dioxide and, consequently, the greenhouse effect of the planet. This installation is characterised by zero emission of harmful substances into atmosphere and average efficiency factor (AEF) of HPU makes 67% [3]. Combined systems on the basis of alternative sources of thermal energy which consist of several sources of thermal energy are relevant for today. Integration of work of heat pumps and solar collectors is an effective and economically reasonable solution.
2 Object and Methods of Research A schematic diagram of a combined solar collector and air-source heat pump system in a building heating system is shown in Fig. 1. Combined system of solar collector and air heat pump is presented in the building no. 2 of Omsk State Transport University. Name and technical characteristics of the equipment in this scheme: K-1—storage tank, K-2—external heat pump module, K3—vacuum manifold, K-4—pumping station, K-5—buffer tank, K-6—circulating pump, K-7—fan coil, 1.1, 1. 2—membrane expansion tank, 2—straight loop pipe, 3—safety valve, 4—ball valve, 5—manual pump, 6—ball valve, 7—non-return valve, 8—thermal relief valve, 9—automatic air vent, 10—indicator manometer, 11—indicator thermometer, 12—three-way mixing valve with an electric drive. In the vacuum solar collector K3, the working substance is heated by solar radiation, which by means of the pump station K4 flows into the storage tank K1, where in turn gives potential thermal energy to the cold water. In parallel, the external module (evaporator) of the air-source heat pump transfers ambient energy to the condenser, which is located in the K1 system. The heated water is pumped from the K1 storage tank to the K5 storage tank, where it is discharged to the K7 heating system and the HWS consumer by the circulating pump. A thermal relief valve 8 [4] is used to regulate the water temperature in the storage tank.
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Fig. 1 Schematic diagram of a combined solar collector and air-source heat pump system in a building heating system
3 Results Application of the considered scheme of solar system allows to solve the following design problems: to provide maximum efficiency on use of solar energy, as solar system is the first stage of heating of cold (network) water; independent from existing control system of heating system and HWS automatic regulation circuit, as solar system is the first stage of heating; possibility to use solar system in winter (heating) period as a preheating of cold water, that will lead to additional heating of cold water. Solar vacuum tube collector SVK-20A has been considered for heat supply of the building and hot water supply system of the second building of Omsk State Transport University. Proceeding from nameplate data of absorbing area, specified for all vacuum tube collector SVK-20A (consisting of 20 tubes) it is possible to determine absorbing area of one glass tube: 1.66/20 = 0.083 m2 . The number of tubes required depends on the amount of solar energy per 1 m2 . Then 1 m2 /0.083 m2 = 12.05. In other words, 1 m2 = 12 vacuum manifold tubes. To determine the number of solar collector tubes for generating the required amount of heat output, it is necessary to know the heat output per tube. The heat output per tube (cold period) is the product of the absorption area of one tube per square metre of insolation for the region (cold period) and the collector efficiency. The optimum angle of the solar panels in relation to the ground surface is given in Table 1 and Fig. 2 shows a graph of the change in solar insolation in the city of Omsk. This figure is needed to calculate the maximum collector efficiency for any time of year [5, 6].
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Table 1 Solar insolation and slope values for the city of Omsk by month as a latitude function Period
Solar insolation, kWh/m2
Optimum tilt angle, °
January
31
72
February
61
64
March
130
52
April
181
36
May
233
21
June
243
11
July
243
18
August
193
28
September
135
44
October
74
59
November
35
70
December
23
75
Annual average
131.8
45.7
300
kWh/m2
250 200 150 100 50 0 1
3
5
7
9
11
month
Fig. 2 Diagram of solar insolation in the city of Omsk
Solar insolation is a value that determines the amount of surface irradiation by a beam of sunlight (even reflected or scattered by clouds). When considering the application of a combined solar collector and air-source heat pump scheme in the heating and HWS system, the climatic characteristics of the region, the economic justification as well as the fuel and energy balance of the area must be taken into account. The choice of the bivalence point depends on the annual and seasonal averages of the ambient air temperature—this is the tipping point when the heat supply system switches to a redundant heat source, as an alternative energy
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Fig. 3 Load schedule for the heating system
source system always needs to consider an additional “traditional” source (in our case, an electric boiler) when the outdoor temperature becomes too low [7]. The heat pump takes low-potential heat from the ambient air and the heat pump efficiency (HPE) depends directly on the outdoor temperature value, while the solar collector also changes its temperature value depending on the time of day and the outdoor temperature. The operation of an air-source heat pump and solar collector in a bivalent arrangement is more economically justifiable: In this case the heat output target value is not increased to cover the infrequent loads on the coldest days and therefore the cost of the combined system is reduced, consequently an efficient return on investment through energy savings is observed. The capital costs can be either one-off or spread over several periods [8, 9] (Fig. 3). In solar collectors the working medium is usually propylene glycol or ethylene glycol and in the heat pump circuit freon is used. Consideration of the working fluid thermophysical properties of the solar collector and the air-source heat pump under changing ambient temperatures is not a minor issue in the study of the combined heating and domestic hot water system [10]. At low ambient temperatures and at night, when there is no solar radiation to the solar collectors and hence no heat transfer to the storage tanks, the hot water temperature in the system decreases and the heat input to the HWS is reduced. It is necessary to investigate how the temperature and viscosity of the working medium change with decreasing ambient temperature. The freezing point of propylene glycol (ethylene glycol) depends on the concentration of the aqueous solution. Table 2 shows the values of freezing temperature of aqueous solutions of selected working substances depending on their concentration [10, 11]. As the temperature of ethylene glycol (propylene glycol) changes, their physical properties change significantly.
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Table 2 Freezing point of aqueous solutions of ethylene glycol and propylene glycol Mass glycol concentration, %
Ethylene glycol, ° C
Propylene glycol, ° C
10
−3
−3
15
−5
−5
20
−8
−7
25
−11
−10
30
−14
−13
40
−22
−21
50
−34
−33
60
−48
−51
Fig. 4 Head loss vs. propylene glycol (ethylene glycol) temperature graphs
The increase in density and viscosity of the ethylene glycol with decreasing temperature significantly changes the head loss, which in turn leads to a disturbance of the heat exchange circulation in the solar thermal system. Figure 4 shows plots of the head loss as a function of the propylene glycol (ethylene glycol) temperature, i.e., the working medium. Considering the significant influence of the heat transfer medium temperature on its viscosity, special attention needs to be paid to the hydraulic calculations and in particular to the diameters of the pipes connecting the collectors.
4 Conclusions Beneficial solutions for the efficient use of the system in question are floor, wall or ceiling heating systems, as these devices use a low temperature coolant of between 40 and 50 °C [12]. In turn, radiator heating systems in the Siberian region, taking into account the climatic characteristics, work effectively at operating body temperatures of 80–90 °C. The use of a heat pump in such a system can lead to a 2.5 times
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reduction in the efficiency of the radiators [13–15]. In order to ensure profitable economic and technical use of the combined system, a number of measures are implemented to increase efficiency. Firstly, the heating system should be completed with a backup heater (electric, gas, solid fuel) boiler etc. Secondly, organising a thermo-modernisation is one of the available and efficient ways to save energy.
References 1. Flaksman AS, Mozgovoy AI, Lopatkin DS et al (2021) Prospects for the development of alternative energy sources in the world energy. IOP Conf Ser Earth Environ Sci 723:052040. https://doi.org/10.1088/1755-1315/723/5/052040 2. Ovchinnikova S, Kukinova G, Borovkov A, Markina N (2021) Environmental substantiation for the use of alternative energy sources. E3S Web Conf 22. https://doi.org/10.1051/e3sconf/ 202124401007 3. Bashmakov I (2009) Economic Issues, Russian resource of energy efficiency: scale, costs and benefits. Quest Econ 2:71–89. https://doi.org/10.32609/0042-8736-2009-2-71-89 4. Selikhov YA, Kotsarenko VA, Kapustenko PO, Klemeš JJ (2018) The performance of plastic solar collector as part of two contours solar unit. Chem Eng Trans 70:2053–2058. https://doi. org/10.3303/CET1870343 5. Lertsatitthanakorn C, Jamradloedluk J, Rungsiyopas M et al (2013) Performance analysis of a thermoelectric solar collector integrated with a heat pump. J Electron Mater 42(7):2320–2325. https://doi.org/10.1007/s11664-012-2414-x 6. Khamokov MM, Chapaev AB (2020) Determination of efficiency of solar collectors used in regions with low solar radiation. Bull North Caucasian Federal Univ 6(81):33–39. https://doi. org/10.37493/2307-907X.2020.6.4 7. Kadtcyn II, Starikov AP, Vedruchenko VR, Agilbayeva MJ (2020) In: IOP conference series: materials science and engineering. VIII international scientific conference transport of Siberia 2020, vol 8, p 012158. https://doi.org/10.1088/1757-899X/918/1/012158 8. Sun J, Ma S, Huo C et al (2021) A large temperature difference thermal substation (ltdts) with electric heat pump and thermal storage tank. IOP Conf Ser Earth Environ Sci 2:012016. https:// doi.org/10.1088/1755-1315/661/1/012016 9. James A, Srinivas M, Jayaraj S, Mohanraj M (2020) Thermal analysis of heat pump systems using photovoltaic-thermal collectors: a review. J Therm Anal Calorim. https://doi.org/10.1007/ s10973-020-09431-2 10. Imanov HA, Huseynov GM (2021) Study of the conditions for the acquisition of tl3ass4 in ethylene glycol. Kimya Problemleri 19(3):135–142. https://doi.org/10.32737/2221-8688-2021-3135-142 11. Orlov PA, Il‘ina TN, Orlov KP (2021) Promising methods of ice control of air heat pump evaporators. J Phys Conf Ser, p 012017. https://doi.org/10.1088/1742-6596/1926/1/012017 12. Kuziyev OAU (2021) Analysis of energy parameters of steam-compressor heat pumps. Curr Sci Res Modern World 3–1(71):6–8 13. Tauasarov SU, Balabekov ZA, Anartaeva GU (2019) Exergy analysis of the operation of a heat pump compressor with a solar collector. In: Industrial technologies and engineering (ICITE). proceedings of VI international conference, Shymkent, pp 55–58 14. Bahan T, Boun V, Bezuhlyj R (2020) Application of heat pumps in the design of heating and conditioning systems. Curr Sci Res Modern World 4–1(60):13–16 15. Fedosov SV, Fedoseev VN, Loginova SA, Zaitseva IA (2021) Approximate calculation of a theoretical cycle of a vapor-compression freon loop in an air heat pump. Smart Compos Constr 2(4):24–34. https://doi.org/10.52957/27821919_2021_4_24
Selecting the Optimum Design Solution for Rolling Stock Repair Plants Under Multiple Preference Criteria Viktor Smirnov
Abstract The paper considers the problems of choosing the optimal variant of technological design solutions for enterprises of rolling stock repair under many preference criteria. The paper formulates the problems of multi-criteria optimisation when designing technological solutions. The classification of technological systems parameters of enterprises for rolling stock repair is given. The methodology of target indexes choice with the use of hierarchy analysis method is suggested. A calculation procedure of the integral target function to solve the problem of multi-criteria optimization of design solutions, including the principles of normalization of the design solution indicators having different scales of assessment, and the principles of calculating the weight coefficients on the basis of the degree of impact of the indicators on the rolling stock repair costs for some base, worked out and known design variant are proposed. The results of the proposed solutions approbation are given using the example of choosing the best technological design of a wagon repair depot. Keywords Repair of rolling stock · Technological design · Multi-criteria optimization
1 Introduction The theory of operations research represents multi-criteria optimization problem as a process of simultaneous optimization of two or more conflicting target functions in a given area of definition [1–3]. In the existing practice of designing industrial and transport enterprises, the most widespread is the method of reducing the multicriteria optimization problem to the problem of choice by the dominant criterion. At the same time all other criteria are taken as constraints [4, 5]. This approach significantly reduces the effectiveness of the decisions made, since almost every design problem has conflicting objectives. It is necessary to develop other solution principles. V. Smirnov (B) Omsk State Transport University, 35, Marksa Pr., Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_45
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In a general case, a multi-criteria optimization problem is of the form [1]: − → → − f1 → x , f2 − x , . . . , fk − x ,→ x ∈ S, min − →
(1)
x
→ x = where f i : F n → F is k in the target functions (k ≥ 2). Solution vectors − T (x1 , x2 , . . . , xn ) refer to the non-empty area of the definition S. The peculiarities of the design option evaluation system, which assumes the presence of a group of independent comparison indicators. It should be noted that solving the multicriteria optimization problem in the general case does not give the best values for each criterion, as improvement of one criterion may cause deterioration of another. Thus, when solving multi-criteria task, we get some compromise solution, and the criteria themselves may have different importance for a decision maker [1, 6, 7]. To date, the following multicriteria optimization problems can be formulated for the research object - enterprise for rolling stock repair. The first problem is related to the choice of optimality principle, which determines the properties of the optimal solution and allows distinguishing it from the set of admissible solutions. The problem of multi-criteria optimization involves several principles of optimality reflecting the interests of the rolling stock repair process participants (customers and performers), each of which can lead to a choice of different options as the optimal one. The second problem is associated with the choice of local criteria and their normalization. It is caused by the fact that local criteria, which are components of the design solution effectiveness vector, have different measurement scales, i.e., their normalization is required for comparison. The third problem is caused by the varying importance of the criteria in ensuring the achievement of the goals of the repair enterprise. This circumstance should be taken into account in view of the impossibility of obtaining the highest quality of design solutions simultaneously for all local criteria [8]. Among the multicriteria optimization methods used in solving the problems of selecting variants of technological systems projects, the following should be noted: methods of criteria convolution, methods of incomparability thresholds, compensation methods, etc. [2, 6, 7, 9]. The most commonly used methods for multicriteria evaluation of alternatives are presented below. Linear criterion convolution method is probably the most well-known and common method for solving applied multi-criteria optimization problems. It consists in assigning coefficients in one way or another to a linear convolution (linear combination) of initial criteria and its subsequent extremification on the set of admissible variants. According to this method the solution found by this method is considered the “best” one [1, 6, 10].
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An approximate algorithm for multi-criteria assessment of alternatives using the linear convolution method is as follows [6]: • • • • •
the criteria for evaluating project options are defined; the criteria are ranked according to their importance; unimportant criteria are discarded; the numbers corresponding to the relative importance of the criteria are assigned; to normalize the ratios (ki ) in importance from the condition: n i=1
ki = 1.
(2)
where ki —the weight of the i-criterion assigned by the decision-maker; • to pre-screen quality alternatives (a quality index is defined on the criterion scales); • to determine the U utility functions for each of the criteria Ui (x) ∈ (0, 1) • to determine the utility of each alternative:
U=
N i=1
ki Ui ,
(3)
Non-comparability threshold methods were first proposed by Professor B. Roy in France. The essence of the methods is the following: solve the optimization problem with one first criterion, assuming that there are no other criteria. Then the problem is solved with one second criterion and so on. After identification of extreme levels, which are achievable by each criterion separately, for each criterion, starting from the most important, a threshold shall be set, which shall not be breached. The condition of the threshold not being violated is regarded as a constraint, then constraints on the threshold of the second criterion are added, and so on [11]. The relationship between any pair of alternatives is defined by a sequence of binary relations [12, 13]. Stronger binary relations correspond to larger requirements for the superiority of one alternative over the other. Weaker binary relations define conditions under which, despite a contradictory evaluation, one alternative is defined as better than the other. Binary superiority relations are defined by the levels of agreement and disagreement indices, which makes it possible to identify a kernel of dominant and incomparable elements. Once the kernel (Pareto set) is selected, its elements are incomparable (temporarily). Then a set of the following binary relations (by the second, third, etc. criterion) is set. Elements (alternatives) of the last kernel are considered to be the solution. The Pareto set method allows representing the most complete information about a multi-criteria optimization problem without any assumptions about relative importance of the criteria. However, this method is rather cumbersome and difficult to apply for solving the problems of selecting the optimal variant of design solutions due to a large number of criteria (more than three).
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2 Object and Methods of Research The efficiency of a company’s technological system depends on many indicators, which can be divided into the following classes on the object-functional basis: technical level of production, energy and infrastructure provision, production capacity, technological logistics (Fig. 1). The assessment of the entire set of influencing factors for many technological solutions is not possible due to objective reasons, including: high labour intensity of calculations, lack of reliable data or the need to clarify them by conducting additional research. There are many different approaches to the choice of indicators for assessing the activities of organizations and enterprises, depending on the characteristics of the object and the objectives of the study [14–17]. Guided by the principles of the system approach the following requirements for the target indicators for selecting the preferred option of the technological project of the enterprise for repair of rolling stock can be formulated:
Fig. 1 Classification of parameters and indicators of rolling stock repair plants’ technological systems
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• the composition of indicators should satisfy the principle of completeness of the design object and the functions performed by it; • indicators should have a direct impact on repair costs; • be independent within the same object-functional group; • calculation of numerical values of indicators should be simple and based on the implementation of standard design procedures. The selection of the composition of the criteria shall be performed by the method of hierarchy analysis [18]. For the criterion hierarchy obtained on the basis of subjective judgment scales, a matrix of pairwise comparisons of dimension n × n is formed: ⎡
w1 w1 w1 w2
⎢ . W =⎢ ⎣ ..
wn wn w1 w2
⎤ w1 ··· w n . . .. ⎥ . . ⎥ ⎦ n ··· w wn
(4)
local priority vectors are calculated Q = (q1 , q2 , . . . , qn )
n wi j=1 w j
n
qi = n i=1
n
n wi j=1 w j
,
(5)
To check the matrix consistency, the eigenvalue of the matrix is calculated μmax = Q · G, where n w j n w j n w j , (6) , ,..., G= j=1 w1 j=1 w2 j=1 wn the consistency index Is =
μmax − n , n−1
(7)
and consistency index ratios Is /Is for the matrix in question W and a matrix of similar dimensionality filled in by random modelling. The value Is /Is should be of the order of 10–20% or less, otherwise it is necessary to further investigate the problem and check the judgements. The problem of multi-criteria optimization of design solutions can be formulated as follows. Let there be a set of different variants of the technological design of an enterprise Vi , i = 1, . . . , n, where V0 —base case, for which there is full information about the values of the entire set of parameters and indicators of the enterprise, including the repair costs. One of the existing repair depots, corresponding to modern corporate standards of technological preparation and organization of production, can be taken as a base
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variant. Each variant of the technological project of the enterprise determines a set m of target indicators(Vi1 , . . . , Vim ). Let us identify the variants Vi with normalised target vectors (vi1 , . . . , vim ). The standardisation is carried out in relation to the base case, i.e.,vi j = Vi j /Voj . The normalised targets are positive numbers. For the base case, all are equal to one. A change in each indicator leads to a change in repair cost. For the chosen system of indicators, an increase in any of them leads to an increase in the cost of repair. If this is not the case, it is always possible to go on to consider the inverse 1/vik of the relevant indicator. As a further step, sensitivity factors are calculated k j , j = 1, . . . , m of the cost of repair relative to the normalised targets when the indicator is increased by a certain fixed value. Let S0 be the cost for the base case and δ j is an increase in the cost of repair if the indicator is increased by, for example, 1%, assuming that the other indicators remain unchanged. Then k j = δ j /S0 . As a generalised optimality criterion, we use a linear criterion of the form: Di =
m j=1
k j · vi j → min
(8)
Figure 2 illustrates the geometric meaning of minimisation for the two indicators. The slope of the parallel lines is determined by the sensitivity factors k1 and k2 v2 = − kk12 v1 + c . On each of these lines the value of the function k1 v1 + k2 v2 is constant (equal to c) and proportional to the distance of the line from the origin. Figure 2 shows that the third option is optimal, because the corresponding line is closer to the origin than the other lines.
Fig. 2 Graphical interpretation of a linear optimality criterion for two indicators
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3 Results We will consider the results of using the proposed methodology of choosing the best option for many preference criteria on the example of the project of the production complex of car repair depot in the Western region of the Republic of Kazakhstan. The technical specifications for the project set the maximum production program of depot repair of 4500 freight cars per year and overhaul in the volume of 1500 cars with the possibility of further increase in production capacity. As part of the manufacturing complex, the task included: the roundhouse, overhaul shop, bogie and wheel shop, warehouse of materials and components, workshops for repair of separate units and parts, administrative and amenity rooms. Three variants of technological solutions, differing from each other in methods of organization of technological process, layout of production workshops and sections, general area of production building and possibilities of its expansion, schemes of main equipment location (Fig. 3) have been worked out under the project. The first option was created on the basis of a standard variant of the wagon repair depot project and is taken as a base. Its advantages: a compact scheme with minimal space requirements, the possibility of expanding the overhaul area. Disadvantages: there is practically no possibility to adapt in types of products and increase depot repair production capacity. The second option was created with the use of flow technology in the organization of the wagon-assembly workshop. It allows temporary use of workshop equipment for the needs of the roundhouse; it has a high flexibility in the area of overhaul and certain opportunities for expansion. Its disadvantages: there is no possibility of extension ‘in length’ (low-cost extension option); turnover and overhaul areas have a common paint shop, which creates additional contra-flow. The third option involves an in-line repair method with flexible manoeuvring, providing the most flexible solution when expansion is needed; good flow of materials, transport and storage areas. The overhaul works do not share resources with the repair shop. Disadvantages: Limited ability to expand the trolley repair area, requires the erection of a freestanding office building. A comprehensive appraisal of the project options was carried out on the basis of the set of targets presented in Table 1. The selection of target indicators was performed by the method of hierarchy analysis according to the algorithm discussed earlier. Calculation of weighting coefficients (coefficients of elasticity of the wagon repair cost relative to target indicators) was carried out according to the calculation of the cost of freight car repair for the following cost items: electrical and thermal energy; depreciation deductions for fixed assets renovation, wages and salaries.
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Fig. 3 Options for design solutions for the technological system of a wagon repair depot
The results of the target function calculation are shown in Fig. 4. The diagram shows that the third option has the lowest value of the target function (8), i.e., it is the best of the three presented.
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Table 1 Input data for calculating the target function Name of target indicator
Method for calculating the indicator
Value k j
Production capacity of the company
(Karpichev, et al. [4])
Production area Length of railway tracks
Option for design solutions 1
2
3
0.00196
1
1.3
1.7
(Grundig [6])
0.0004
1
1.61
1.73
By direct measurement according to the project
0.00031
1
0.74
0.62
Average annual (Zhilin and Ananyev [19]) electricity consumption for technological needs
0.00075
1
1.3
1.37
Transitional stock of repair stock, materials and components
(Nurmukhamedov and Gulyamov [20])
0.0012
1
0.95
0.91
Process flexibility factor
(Miskin [21])
0.00011
1
0.8
0.6
Fig. 4 Results of the target calculation for the three variants of the wagon repair depot project
4 Conclusions As a result of the research, a classification of parameters and indicators for the technological systems of enterprises of rolling stock repair is accomplished, and a method of multi-criteria optimization by the principle of relative preference of possible alternatives of design solutions in comparison with some basic version, which has known values of quantitative parameters and indicators is proposed. Linear criterion-vector is offered as integral criterion, whereas weight coefficients of the indicators of sensibility of the repair costs in relation to normalized target indicators are introduced at increase of the indicator on the given value (for example, on 1%).
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As a conclusion, it should be noted that the preselection of the optimal variant for technological design solutions according to the proposed methodology can significantly reduce the complexity of the design process by eliminating the detailed study of alternatives and concentrating resources on refinement and modification of the preselected project variant.
References 1. Triantaphyllou E (2000) Introduction to multi-criteria decision making. In: Multi-criteria decision making methods: a comparative study. Applied Optimization, vol 44. Springer, Boston. https://doi.org/10.1007/978-1-4757-3157-6_1 2. Nayli A, et al (2021) Multi-criteria decision making: a systematic review. Recent Adv Electr Electron Eng (Formerly Recent Patents Electr& Electr Eng) 14:779–801. https://doi.org/10. 2174/2352096514666211029112443 3. Raju NVS (2019) Operations research: theory and practice, 1st edn. CRC Press, Boca Raton. https://doi.org/10.1201/9780367366070 4. Karpichev V, Sergeev K, Bolotina A (2019) Modeling of technological processes of machinebuilding and repair manufacture. Commun Sci Lett Univ Zilina 21(4):59–62. https://doi.org/ 10.26552/com.C.2019.4.59-62 5. Mulder H (2006) Rapid Enterprise Design. https://doi.org/10.13140/RG.2.2.26057.95840 6. Grundig C-G (2021) Fabrikplanung. Planungssystematik - Methoden – Anwendungen, 7 edn. Aktualisierte Auflage, p 333. https://doi.org/10.3139/9783446454019.004 7. Livshits M, Sizikov A (2016) Multi-criteria optimization of refinery. EPJ Web Conf 110:01035. https://doi.org/10.1051/epjconf/201611001035 8. Fridrikhson O, Mishkurov P, Bodnar O, Kornilov S, Say V (2021) Methodology for justification of the location of railcar repair complex enterprises. Transp Res Procedia 54:419–428. https:// doi.org/10.1016/j.trpro.2021.02.091 9. Stefanoiu D, Borne P, Popescu D, Filip FG, Kamel A (2014) Multi-criteria optimization. In: Optimization in engineering sciences: approximate and metaheuristic methods, pp 253–308. https://doi.org/10.1002/9781118648766.ch4 10. Nogin VD (2014) Linear convolution of criteria in multi-criteria optimization. Artif Intell Decis Mak 4:73–82 11. Akram M, Zahid K, Alcantud JC (2022) A new outranking method for multicriteria decision making with complex Pythagorean fuzzy information. Neural Comput Appl 34:8069–8102. https://doi.org/10.1007/s00521-021-06847-1 12. Miettinen K, Ruiz F, Wierzbicki AP (2008) Introduction to multiobjective optimization: interactive approaches. In: Multiobjective Optimization, pp 27–57 13. Benson H (2008) Multi-objective optimization: pareto optimal solutions, properties. In: Floudas C, Pardalos P (eds) Encyclopedia of optimization. Springer, Boston. https://doi.org/10.1007/ 978-0-387-74759-0_426 14. Sergushina ES, Kabanov OV, Kolesnik VS, Yakovlev AK, Kozhukalova OY et al (2021) Mathematic models for analysis of financial and economic activity of organizations under various condition. Ind Eng Manag Syst 20(2):297–303. https://doi.org/10.7232/iems.2021.20.2.297 15. Ilyin S (2021) The production potential of organizations. In: Transport business of Russia, pp 66–67. https://doi.org/10.52375/20728689_2021_4_66 16. Kavetskiy V, Ratushnyak O (2021) Modern management systems for planning and organization of production. Efektyvna Ekonomika 12. https://doi.org/10.32702/2307-2105-2021.12.94 17. Tertyshnik MI (2021) Production potential of the enterprise and economic assessment production efficiency. In: Azimuth of scientific research: economics and administration, vol 10. https:// doi.org/10.26140/anie-2021-1001-0079
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18. Saaty TL (2008) Relative measurement and its generalization in decision making: why pairwise comparisons are central in mathematics for the measurement of intangible factors - the analytic hierarchy/network process. RACSAM Rev Roy Spanish Acad Sci Ser A Math J 102(2):251–318 19. Zhilin I, Ananyev O (2021) On technological design of car service enterprises. Vestnik LSTU, pp 74–79. https://doi.org/10.53015/23049235_2021_3_74 20. Nurmukhamedov T, Gulyamov Z (2021) Warehouse operations of passenger service car depot with logistics elements. Globus Tech Sci 7:30–35. https://doi.org/10.52013/2713-3079-41-5-7 21. Miskin J (2021) Lessons for advanced therapy manufacturing flexibility and productivity. Cell Gene Therapy Insights 7:1581–1589. https://doi.org/10.18609/cgti.2021.212
Improving the Efficiency of Center-to Center Spacing Control Aleksey Obryvalin , Oleg Supchinsky , and Olga Sutkovay
Abstract The effectiveness of technical control of manufactured products is a key factor influencing the quality and productivity of machine building enterprises. The center-to-center hole spacing is one of the controlled dimensions in manufacturing machine parts. The quality of the assembly as a whole largely depends on measurement accuracy of the spacing. The article analyzes the existing methods and means for measuring the center-to-center spacing of the holes in machine parts and estimates the measurement errors when these methods are used in manufacturing products. The paper proposes a method and design for measuring the center-to-center spacing of holes in machine parts; substantiates the accuracy standards, determines the optimal dimensions of tapered measuring elements and gradation sizes of the controlled holes. Keywords Measuring instrument · Measurement error · Checking operation · Center-to-center hole spacing
1 Introduction At present, machine parts are subject to rather high requirements of accuracy and quality of manufacture, especially in aircraft and rocket and space industries, which are one of the most technically advanced branches of mechanical engineering. The production of high-quality aircraft and aerospace products is an important military economic objective. As a result, competition between the manufacturers of these products is continuously growing, which leads to the search for the most productive methods of their manufacture [1–8]. The quality and productivity of manufactured products of machine building enterprises largely depends on the effectiveness of technical control, which is closely connected with the process technology of machining parts. Therefore, increasing the efficiency of technical control of manufactured products is an important task [9–15]. A. Obryvalin · O. Supchinsky (B) · O. Sutkovay Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_46
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When intermediate and final control operations in the course of manufacturing a part are carried out, the shape, dimensions and quality of the surface are checked for compliance the specified parameters with the requirements of operational sketches or drawing. In accordance with GOST R ISO 5725-1-2002, the measurement accuracy should be understood as the degree of accuracy of the measurement result to the accepted reference value. An accepted reference value is a value that serves as an approved one for comparison and is derived as: 1) theoretical or set value based on scientific principles; 2) an assigned or certified value based on the experimental work of a national or international organization; 3) an agreed or certified value based on collaborative experimental work under the direction of a scientific or engineering group; 4) the mathematical expectation of the measured characteristic, that is, the average value of a given set of measurement results—only in case when 1), 2) and 3) are not available (ISO 3534-1). In national metrology, the error of measurement results is usually determined by comparing the measurement result with the true or real value of the measured physical quantity (which are actually reference values of the measured quantities expressed in legal units). The accuracy of measurements depends on the following factors related to the measuring process, such as: measurement object, measurement subject (operator), measurement method (method), measuring instrument, measurement conditions. The measurement object should be sufficiently studied and its model should be formed. The degree of detail of the model (the depth of study of the measurement object) should be adequate to the purpose of the measurement. The subject of measurement (controller) introduces subjectivity into the measurement process, which, if possible, should be lessened. The operator’s subjectivity depends on his qualification, psychophysiological state, comfort (sanitary and hygienic) labour conditions and other factors which can have a significant impact on the accuracy of measurements. The methods and means of measurement used have a significant impact on the accuracy of measurements. Measurements of the same quantity done with the help of different methods often give completely different results. When choosing measuring instruments, one should keep in mind the purpose of the measuring process and the conditions of measurement conduct since any measuring instrument has limited accuracy. One of the controlled dimensions in the manufacture of machine parts is the center-to-center hole spacing. Ultimately, the quality of the assembly as a whole largely depends on the accuracy of measuring this parameter.
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2 Materials and Methods At present, within piece and small scale production, the following methods are used to measure the center-to-center hole spacing: • bow compass and ruler; • only a bow compass according to the design shown in Fig. 1; • with a bow compass together with replaceable calibrated bushes and rollers according to the design shown in Fig. 2. These methods are indirect and require calculation to determine the center-tocenter distance hole spacing (size A) according to the formulas (1) for the method shown in Fig. 1, and (2) or (3) for the method shown in Fig. 2.
Fig. 1 The design for measuring the center-to-center spacing with a bow compass
Fig. 2 The design for measuring the center-to-center spacing with a bow compass with replaceable calibrated bushes and rollers: 1—controlled part; 2—a bow compass; 3.5—calibrated rollers; 4— end piece; 6.7—calibrated rollers
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A=L+
D2 D1 + , 2 2
(1)
where D1 is the diameter of the first hole, mm; D2—diameter of the first hole, mm; L is the minimum spacing between the generatrices of the holes, mm. A = L2 −
d1 d2 − , 2 2
(2)
where d 1 is the diameter of the calibrated roller, mm; d 2 —diameter of the calibrated roller, mm; L 2 —the maximum distance between the generatrices of the rollers, mm. A = L1 +
d2 d1 + , 2 2
(3)
where L 1 is the minimum spacing between the generatrices of the rollers, mm. The above methods are used to measure the center-to-center hole spacing with the measurement accuracy ranging from 0.05 to 0.08 mm. The advantage of these methods is that no special measuring instruments are required. The disadvantages are the complexity of the measurement process; high labor intensity; the increase in the number of links in the dimensional chain; increase in the number of measuring elements, which makes the cost of the control operation higher; the need to calculate the controlled size A. In addition, with these control methods, the measuring process is rather subjective, which results in measurement errors. Measurement error is the deviation of the measured value of a quantity from its true (actual) value. Measurement error is a characteristic of measurement accuracy. As a rule, it is impossible to find out with absolute accuracy the true value of the measured value. Therefore, it is impossible to indicate the deviation of the measured value from the true one. This deviation is commonly referred to as the measurement error. Errors are classified as follows: • • • • • •
by the form of presentation; by their cause; by the way of the manifestation; by the method of measurement; depending on the instrument lag; depending on the input quantity.
A particular attention should be paid to the categories of errors due to their causes. By their causes the errors are subdivided into:
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• instrumental/instrumental errors—errors that are determined by the errors of the used measuring instruments and are caused by the imperfection of the principle of operation, inaccuracy of the graduation of the scale, and the lack of visual clarity of the device; • theoretical—errors arising from incorrect theoretical assumptions during measurements; • methodological errors—errors caused by the imperfection of the method as well as by the simplifications underlying the method; • subjective/operator/personal errors—errors due to the degree of attentiveness, concentration, preparedness and other qualities of the operator.
3 Results The most significant and probable error when measuring the center-to-center hole spacer with a bow compass is the error resulting from incorrect application of the measuring jaws of the tool to the contact points of the measured size. This rotates the tool axis relative to the measuring axis by a certain amount. To determine the error in measuring the center-to-center hole spacing with a bow compass, a design scheme (see Fig. 3) was developed. Its analysis and solution through the theorem of sines and cosines for two arbitrary triangles OB1 C1 and OB2 C2 made it possible to obtain a formula for determining the magnitude of the measurement error (the formula is valid for two holes of the same diameter, while R1 = R2 = R): me = 2 2R 2 + 2Rl f + l 2f − 2R 2 cos(180◦ − α − arcsina
(R + l f ) sinα) − L f R (4)
Fig. 3 Design diagram of the error in measuring the center-to-center hole spacing with a bow compass
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Table 1 The results of calculating the error magnitude in measuring the center-to-center spacing of two holes
Tool axis offset angle relative to the measuring axis, degree
Measurement error, mm
0
0
1
0.06
2
0.25
3
0.55
4
1.0
5
1.6
measurement error, mm
where R is the radius of the circle, mm; l f —the actual spacing between the measuring points forming the circle, mm; L f is the actual center-to-center hole spacing, mm. Let us consider an example of the cause and detection of the magnitude of the error in measuring the center-to-center spacing of the holes with a diameter of 20 mm. When the spacing was being measured, the angle α was changed in the range from 0 to 5°. The actual center-to-center spacing was 100 mm. The results of calculating the magnitude of the measurement error are given in Table 1. The results obtained allowed us to construct the error magnitude graph for measuring the center-to-center spacing of two holes with a diameter of 20 mm with the actual center-to center spacing of 100 mm depending on the change in the angle α in the range from 0 to 5° (Fig. 4). It can be seen from the curve that if the measuring axis and the tool axis mismatch when the center-to-center hole spacing is measured by more than one degree, it
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 0
1
2
3
4
5
α, degrees Fig. 4 The curve of the change in the measurement error magnitude for the center-to-center spacing of two holes with a diameter of 20 mm when the angle α changes in the range from 0 to 5° and the actual center-to-center spacing is 100 mm
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already results in a measurement error of more than 0.1 mm. If the mismatch of the axes is five degrees, then the magnitude of the errors is more than 1.6 mm.
4 Discussion To optimize the measurements of the center-to-center hole spacing in machine parts by increasing the measurement accuracy and efficiency by minimizing the influence of the subjective factor and eliminating the need for calculations to determine the value of the center-to-center spacing, a typical measurement method (see Fig. 5) has been developed. It implies a direct measurement of the center-to-center hole spacing distance with a tapered bow compass (bow compass jaws). Grapho-analytical modeling in the KOMPAS environment made it possible to determine the gradation sizes of the holes and the dimensions of the tapered measuring elements shown in Fig. 6.
Fig. 5 Hole spacing measurement design
Fig. 6 Dimensions of tapered measuring elements
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The most optimal are cones numbered 3–5 as they provide the largest measurement range in comparison with the numbers 1, 2. It is recommended to use the measuring cone No. 3 when measuring the centerto-center spacing of the holes with a diameter of 2–20 mm and the center-to-center spacing of at least 20 mm according to the drawing. It is recommended to use the measuring cone No. 4 when measuring the centerto-center spacing of the holes with a diameter of 2–40 mm and the center-to-center spacing of at least 40 mm according to the drawing. It is recommended to use the measuring cone No. 5 when measuring the centerto-center spacing of the holes with a diameter of 2–65 mm and the center-to-center spacing of at least 65 mm according to the drawing. The use of these technical solutions will diminish the number of measurement errors of the center-to-center hole spacing, and will reduce the time spent on conducting technical control by eliminating the procedure for calculating the value of the center-to-center spacing.
5 Conclusion The study results showed that the existing measurement methods have a high labor intensity and the probability of making errors that distort the reliability of measurement during control operations. The obtained research results are the basis for the development of structural elements of the measuring instrument and the justification of their accuracy standards for manufacturing.
References 1. Balyakin AV, Vdovin RA, Ispravnikova SS (2020) Application of additive technologies for manufacturing turbine stator parts in aircraft engines. In: Paper presented at the Jop conference series: metrological support of innovative technologies, 2020, Krasnoyarsk. https://doi.org/10. 1088/1742-6596/1515/4/042108 2. Bezyazychnyy V (2020) Quality assurance of products of mechanical engineering and aerospace engineering at technological pre-production. Sci Intens Technol Mech Eng 103(1):8– 14. https://doi.org/10.30987/2223-4608-2020-2020-1-8-14 3. Agapov S, Sidyakin Y (2018) Hole accuracy increase at hole reaming in hard-to-machine parts. Sci Intens Technol Mech Eng 6:18–23. https://doi.org/10.30987/article_5b0e4112149753.477 33370 4. Deryabin IP, Tokarev AS (2021) Reducing the labor intensity of hole machining by increasing the accuracy of countersinking operations with precast tools. Vestnik Nosov Magnitogorsk State Tech Univ 19(4):107–115. https://doi.org/10.18503/1995-2732-2021-19-4-107-115 5. Sopin PK (2019) The study of the impact of the single-point mill cutting unit geometry on its cutting properties. Mod Technol Syst Anal Model 64(4):8–12. https://doi.org/10.26731/18139108.2019.4(64).8-12
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6. Voyachek II, Simutin SV (2020) Examination of measurement accuracy of linear dimensions of parts on coordinate-measuring machine. Trends Dev Sci Educ 61(3):12–15. https://doi.org/ 10.18411/lj-05-2020-41 7. Lutyanov AV, Leonov AV, Snimshchikov KA (2021) Accuracy of the technological operation of whole boring in basic parts. Int Res J 107(1–5):79–82. https://doi.org/10.23670/IRJ.2021. 107.5.012 8. Trusova EV (2021) Features of the use of high-performance equipment and robotic modules for processing and surface inspection of holes. Trends Dev Sci Educ 78(2):73–76. https://doi. org/10.18411/trnio-10-2021-59 9. Holesovsky F, Novak M, Lattner M, Vyslouzil T (2013) Machining and its influence to surface quality of machine parts. Key Eng Mater 581:354–359. https://doi.org/10.4028/www.scient ific.net/KEM.581.354 10. Malkova E, Kulnevich V, Oleinik N (2020) Standardization for technical control of technological processes in agricultural engineering. Vestnik BSAU 2:89–94. https://doi.org/10.31563/ 1684-7628-2020-54-2-89-94 11. Nazaryev A, Bochkarev P, Reshetnikova E (2020) Integrated approach to process design of manufacturing of high-precision products. In: Paper presented at the international conference on modern trends in manufacturing technologies and equipment. Sevastopol. https://doi.org/ 10.1088/1757-899X/709/3/033085 12. Ryazantsev AY, Smolentsev EV, Gritsyuk VG, Shirokozhukhova AA (2019) Quality assurance of the part surface layer when drilling holes in the rocket engines filters. Voronezh State Tech Univ 15(5):111–116. https://doi.org/10.25987/VSTU.2019.15.5.015 13. Suslov A, Fedonin O, Petreshin D (2020) Basic fundamentals to ensure and increase quality of mechanical engineering and aerospace products. Bull Bryansk State Tech Univ 87(2):4–10. https://doi.org/10.30987/1999-8775-2020-2020-2-4-10 14. Temirbekov ZT, Kadyrov IS, Turusbekov BS, Volhonov MS (2020) Development of a universal automatic system whole process control multiple tool. Agrar Bull Upper Volga Region 30(1):114–119. https://doi.org/10.35523/2307-5872-2020-30-1-114-119 15. Vivancos J, Costa L, Ortíz JA (2004) Optimal machining parameters selection in high speed milling of hardened steels for injection moulds. J Mater Process Technol 155–156(1–3):1505– 1512. https://doi.org/10.1016/j.jmatprotec.2004.04.260
The Linearization Method to Calculate the Equilibrium Composition of Combustion Products of Diesel Engine Alexandr Anisimov
and Igor Chernyshkov
Abstract During the operation of locomotive power plants, a large number of various toxic substances are released into the environment with the products of fuel combustion, the concentration of which depends on numerous factors. The control and limitation of toxic pollution are regulated by the norms and methods established in railway transport, which are based on instrumental methods. In addition to instrumental methods, calculation methods for determining the composition of exhaust gases, for example, equilibrium, are becoming more widespread. To solve a complex nonlinear system of equations of equilibrium, material balance and Dalton, a linearization method is proposed by taking logarithms to calculate the equilibrium composition, taking into account the nature of heat release during fuel combustion in the cylinders of a diesel locomotive engine. The values of the partial pressures of the components of the combustion products of the fuel obtained as a result of solving the system of equations make it possible to determine the mass fractions at constantly changing values of the pressure and temperature of the working heat, taking into account the characteristics of heat release throughout the process of fuel combustion in the diesel cylinder. Some results of modeling the formation of fuel combustion products for diesel locomotive 2A-5D49 of diesel locomotives TEP70BS for the nominal operating mode are presented, which confirm the possibility of using the proposed method of equilibrium composition and ways of its implementation to assess the efficiency of an autonomous locomotive both in terms of fuel efficiency and environmental safety. Keywords Diesel engine · Combustion products · Equilibrium composition · Nonlinear equation system · Linearization
A. Anisimov (B) · I. Chernyshkov Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_47
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1 Introduction The composition of diesel engine exhaust gases of diesel locomotives is quite diverse. Some elements of them are common, since they constitute a larger part in the total mixture of gases, while others are represented in very small concentrations or not always represented. The concentration of chemical elements in engine exhaust gases depends on the engine type, combustion chamber design, engine duty cycle setting, its operating mode, technical condition of its components and parts, fuel quality and a number of other factors [1, 2]. In various industries, and especially in transport industry, measures to control and limit the amount of emissions of some elements into the environment are provided. Thus, in railway transport, norms and methods to determine the amount of harmful substances, emitted by diesel locomotives into the environment, are established. In accordance with them the volume proportion of nitrogen oxides, carbon monoxide and hydrocarbons, as well as the smokiness of exhaust gases of diesel locomotives is subject to control and rationing. Calculation of these indicators is carried out with the help of a gas analyzer and a smoke gauge. In addition to experimental methods, calculation methods to estimate the equilibrium composition of exhaust gases are being developed in the theory of internal combustion engines. The method is based on a system of equations consisting of the material balance equations and Dalton’s equation. Preliminarily, a mathematical simulation of the actual diesel engine cycle is performed. The initial conditions to solve the system of equations are the pressure P and temperature T of the gas mixture at the considered moment of time, the excess air ratio α and the elementary composition of the fuel used. The combination of mathematical models will reflect the influence of peculiarities of the real working cycle of the diesel engine on the composition and amount of fuel combustion products. The obtained parameters of the gases in the cylinder depending on the angle of rotation of the crankshaft allow solving a system of equations for each moment of the combustion process. The present complexity associated with a large volume of calculations and poor convergence of the solution of the system of equations, which becomes even more complicated for each crank angle, leads to the improvement of the calculation algorithm by the equilibrium composition method, which will simplify the calculations and save time. The traditional approach to solving the system of equilibrium equations is considered in detail in the scientific literature. Thus, in the case of calculating the 18 components in the combustion products of diesel fuel, one will have to solve a system of 14 equilibrium equations, three material balance equations, and the Dalton’s equation.
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2 Materials and Methods The main difficulty in solving such a system is its bulkiness and extremely poor convergence, so the choice of the solution method is of great importance. For this reason, attempts have been made to solve it in several different ways. The possibilities laid down in the library Numpy, Simpy and SciPy of the programming language Python 3 [3, 4] to solve systems of nonlinear equations, as well as the use of known from mathematics methods to solve systems of nonlinear equations, such as Seidel method, Newton method [5] showed the following: Solving the system of equations takes a large amount of machine time, which complicates the application of the equilibrium composition method when multiple simulations of the power plant modes of operation take place; The system of equations has poor convergence, so it is not always possible to obtain a solution, which is probably due to the cumbersomeness of the given equations and their significant dependence on the calculation conditions. A fundamentally different approach to solve the system of nonlinear equations to determine the composition of fuel combustion products is given in (Dubovkin N). In it, at the first step, the elementary composition of fuel and oxidizer is set, after which the composition of the combustible mixture is calculated. Then, the values of pressure P and temperature T of the mixture are set, for which the calculation is performed. The values of the equilibrium constants are determined by the temperature value, and the auxiliary coefficients are determined based on the elementary composition of the combustible mixture.
3 Results The calculation of the first approximation begins with taking the initial values of the partial pressures of the components: PO2 = PO = PH = PO H = PN = PN O = 0.
(1)
Given a value of the equilibrium constant K2a , calculated partial pressure PN2 , coefficients a, b, and c, the partial pressure of carbon dioxide PCO2 is determined by solving the quadratic equation: (K 2a − 1)PC2 O2 + (K 2a c + a + b)PC O2 − ab = 0.
(2)
The values of partial pressures PCO , PH2O and PH2 are determined taking into consideration the value PCO2 and coefficients a, b, and c. To check for errors in the results of the solution it is necessary to calculate the equilibrium constant by equation:
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K 2a =
PC O PH2 O , PC O2 PH2
(3)
and the total pressure by formula: P = PO2 + PO + PH + PO H + PN + PN O + PC O2 + PN2 + PC O + PH2 O + PH2 . (4) The results of the first approximation K2a and P by formulas (3) and (4) should not differ significantly from those previously accepted. Then, the second and third approximations are calculated. If the difference in the values of these approximations does not exceed the required accuracy, the calculation of the composition of fuel combustion products is considered to be complete. The software implementation of this calculation method for the case of fuel combustion in the cylinders of a diesel locomotive engine showed its inexpediency, since in most cases it was impossible to obtain a positive real root of Eq. (2). Apparently, this is due to the fact that the calculation is based on initial conditions that are not suitable for the case of combustion in a diesel engine. For example, the assumption of a zero value of the partial pressure of oxygen at the beginning of combustion. In order to determine the influence of various parameters of the combustion process in a diesel locomotive diesel engine on the composition of combustion products, a mathematical model was developed that takes into account the variable values of pressure and temperature of the working body during the operation of the diesel engine. The model is based on a system of material balance equations and takes into account eleven elements in the composition of the exhaust gases: α P PO + PO2 + PO H + PH2 O + PN O + PC O + PC O2 = α PC O + PC O2 β P PN + PN2 + PN O = PO + PO2 + PO H + PH2 O + PN O + PC O + PC O2 , ⎪ γ P PH + PH2 + PO H + PH2 O = PC O + PC O2 ⎪ ⎩ P = PO + PO2 + PH + PH2 + PO H + PH2 O + PN + PN2 + PN O + PC O + PC O2 (5) ⎧ ⎪ ⎪ ⎨
where αP , βP , γP are coefficients depending on the elemental composition of fuel; α is total excess air coefficient; P is total pressure of the gas mixture; Pi is the partial pressure of the i-th element of the combustion products. The solution of the system of Eq. (5) is reduced to the representation of nonlinear equations to linear ones. For this purpose, both parts of each equation are logarithmic and decomposed into a Taylor series, assuming the unknowns are the logarithms of the partial pressures of the mixture. The expansion terms of the second and higher orders are not taken into account. As a result, we obtain a system of four linear algebraic equations relating to the four logarithms of the unknown partial pressures:
The Linearization Method to Calculate the Equilibrium Composition …
⎧ A1 ln(PH 2O ) + B1 ln(PH 2 ) + C1 ln(PC O ) + D1 ln(PN 2 ) = ⎪ ⎪ ⎨ A2 ln(PH 2O ) + B2 ln(PH 2 ) + C2 ln(PC O ) + D2 ln(PN 2 ) = ⎪ A ln(PH 2O ) + B3 ln(PH 2 ) + C3 ln(PC O ) + D3 ln(PN 2 ) = ⎪ ⎩ 3 A4 ln(PH 2O ) + B4 ln(PH 2 ) + C4 ln(PC O ) + D4 ln(PN 2 ) =
481
E1, E2 , E3, E4.
(6)
The coefficients A1 …E 4 in the system (6) are calculated using initial approximations of the partial pressures and equilibrium constants of the mixture components. Solving the system of linear algebraic Eq. (6) with respect to the additions to the logarithms of the partial pressures ln(PH2O ), ln(PH2 ), ln(PCO ) i ln(PN2 ) we determine the pressures for the current iteration as: init Pi = eln( Pi )+ln(Pi ) ,
(7)
where Pi is the partial pressure value of the i-th component for the current iteration; Piinit is initial approximation of the partial pressure of the i-th component for the current iteration; ln(Pi ) is the magnitude of the addition obtained by solving the system of Eq. (6). The partial pressures of the remaining components are determined by the first four calculated pressures, taking into account the equilibrium constants. The results of solving the system of Eq. (6) are used as initial values for subsequent iterations until the required accuracy is obtained according to the condition: P − P ≤ ε, P
(8)
where ε is the required accuracy of calculations. The resulting partial pressures of the mixture components are used to determine mass fractions based on the ideal gas equation of state. In the mathematical model the calculation of the mass of the products of combustion of diesel fuel of a given composition is conducted at constantly changing values of pressure and temperature, taking into account the characteristics of heat release at the whole continuation of the combustion process in the cylinders of the diesel fuel: m i (ϕ) =
ϕZ
mi j Pj , T j d x j ,
(9)
j=ϕ0
where mi is the mass of the i-th element of the combustion products for the whole process of fuel combustion; mij is the mass of the i-th element of the combustion products at the moment of combustion, corresponding to the j-th angle of rotation of the crankshaft; Pj is pressure of gases in the diesel cylinder at the j-th moment of the combustion process; T j is temperature of gases in the diesel cylinder at the j-th moment of the combustion process; dx j is the share of burnt fuel in the diesel cylinder at the j-th moment of the combustion process.
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CO mass, kg
The result of the simulation is the calculation of the mass of each component of the combustion products at any moment of the process of fuel combustion in the cylinders of a locomotive diesel engine. As an example, the dependences of the mass of CO, NO on the angle of rotation of the crankshaft during the combustion of fuel in the cylinder of the diesel engine 2A-5D49 of the locomotive TEP70BS in the nominal operating mode are shown (Figs. 1 and 2). The dependences obtained illustrate the difference in the dynamics of the formation of some elements in the process of fuel combustion. With the help of the described model, it is possible to study the patterns of formation of combustion products during the operation of diesel engines of diesel locomotives depending on the settings of the operation process, and vice versa - to judge the quality of its course by the data of combustion products analysis.
3.5E-07 3.0E-07 2.5E-07 2.0E-07 1.5E-07 1.0E-07 5.0E-08 0.0E+00 -20 -10 0
10
20
30
40
50
60
70
80
90 100
10 20 30 40 50 60 70 80 Angle of rotation of the crankshaft, hail.
90 100
Angle of rotation of the crankshaft, hail.
CO mass, kg
Fig. 1 CO formation rate during fuel combustion
4.5E-05 4.0E-05 3.5E-05 3.0E-05 2.5E-05 2.0E-05 1.5E-05 1.0E-05 5.0E-06 0.0E+00 -20 -10 0
Fig. 2 The rate of NO formation during fuel combustion
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4 Conclusion Thus, the conducted research allows us to conclude the following: The proposed method of linearization by logarithm to calculate the equilibrium composition of combustion products of a diesel locomotive allows, with a relatively small volume of calculations, quickly obtaining a solution to the system of equations underlying the mathematical model, and using it within the framework of the developed methodology to assess the energy efficiency of locomotives. The combination of mathematical models of the diesel engine operation cycle and the equilibrium composition of combustion products allows taking into consideration the impact of the peculiarities of the combustion process on the concentration of the elements of the diesel engine power plant exhaust gases. The mathematical model allows determining the content of some elements in fuel combustion products at different values of effective power of a diesel locomotive and maximum combustion pressure. With its help it is possible to implement the identification of these values in reverse order, that is to determine the values of N e and Pz by the known equilibrium composition. This will make it possible to make up for deficiency of parameters monitored by the onboard systems of locomotive operation parameters to determine the efficiency of diesel locomotives, provided it is possible to obtain data on the composition of combustion products during the operation of the locomotives.
References 1. Karim GA (2015) Dual-fuel diesel engines. CRC Press, New York 2. Merker G, Schwarz C, Stiesch G, Otto F (2006) Verbrennungsmotoren. Simulation der Verbrennung und Schadstoffbildung. 3. Auflage. Teubner – Verlag. Stuttgart, Leipzig, Wiesbaden, p 412 3. VanderPlas J (2016) Python data science handbook. O’Reilly Media Inc, Sebastopol 4. Kuhlman, DA (2009). Python book: Beginning Python, advanced Python and Python exercises. Open source MIT 5. Chivilikhin SA (2008) Computational methods in programming technologies. Elements of Theory and Practice. SPbGUITMO, Saint-Petersburg
Energy Efficiency of the Innovative Fifth-Generation 2ES5S Electric Freight Locomotive and the Results of its Tests Alexandr Baklanov , Andrey Shatohin, Andrey Shilyakov , Kiril Domanov , and Nikolay Esin
Abstract The article discusses the main parameters and test results of a innovative freight electric locomotive with rotary-field traction motors on Artyshta II— Altayskaya section of West Siberian Railway. The paper presents the results of the analysis of the technical equipment of the mainline asynchronous traction motor electric locomotive of innovative series. The paper focuses on traction electrical devices as well as the technical characteristics of the traction rolling stock under consideration. The article presents a comparative analysis of the main parameters of asynchronous traction motor electric freight locomotives with moving trains of estimated weight in nominal traction mode on the limiting upward journey of the serviced section of the railway operating domain per hour. The paper presents the results of experimental tests conducted by the authors of the article. The methodology for processing the results obtained based on the results of experimental trips is given. Conclusions are drawn and discussion questions are proposed. Keywords Electric locomotive · Rotary-field traction motor · Train weight · Electric power consumption for traction · Traction rolling stock · Energy efficiency
1 Introduction The Russian industry is currently producing a small number of advanced fifthgeneration electric AC and DC rotary-field traction motors (RFTM). Recently, there have been produced 77 one-section 6-axle passenger EP20 dual-power locomotive and 5 two-section 8-axle 2ES5 AC electric freight locomotives at Novocherkassk electric locomotive plant, together with the French company Alstom, 13 twosection 8-axle 2ES7 AC electric freight locomotive at the plant “Ural locomotives” in cooperation with the German company Siemens, two two-section 8-axle dual power 2EV120 electric freight locomotive on Engels locomotive factory together with the Canadian company Bombardier Transportation. The listed electric locomotives are A. Baklanov · A. Shatohin (B) · A. Shilyakov · K. Domanov · N. Esin Omsk State Transport University, 35, Prospekt Marksa, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_48
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almost completely equipped with expensive imported equipment, therefore large investments are required for their mass production [1–3]. In order to master the mass production of domestic fifth generation electric locomotives, at Novocherkassk Electric Locomotive Plant together with cooperating enterprises by analogy with the above samples, one two-section 8-axle 2ES5S AC electric locomotive and one three-section 12-axle 3ES5S electric locomotive with RFTM were developed and produced in 2018–2019. Their main difference from electric locomotives produced jointly with foreign companies is that 85% of the components are made at Russian enterprises, this results in much lower cost of an electric locomotive [4–8]. The main components of 2ES5S and 3ES5S electric locomotives developed and manufactured by Russian enterprises are traction transformers, traction converters, RFTM, an auxiliary drive, compressor equipment, bogies and control system equipment. A number of modern technical solutions are used in the design of these electric locomotives. These are a first-class traction transmission with motor axial antifriction bearings, a traction drive with RFTM and individual voltage inverters that allows for axial energy optimal control, a microprocessor control and diagnostic system, skid protection, an automatic train operation in traction and regenerative braking modes, a control system for distributed traction and brakes of long-trains.
2 Materials and Methods Table 1 shows the main parameters of the innovative 2ES5C electric locomotive in comparison with those of previously produced AC electric locomotives with rotational traction motors (RTM) with traffic in nominal traction mode per hour for trains of calculated mass on an upward journey of 8% slope. Here the following notation: Ue is the nominal voltage at the current collector, Kv; nnumber —number of axles of the locomotive; ml is the mass of the locomotive, t; Vmax is the maximum (design) speed, km/h; Vh is the nominal speed, km/h; Fkm/h —nominal rail tractive effort, kN; Pemf — nominal electric power of traction motors, kW; mtr —the estimated weight of the train, t; ate —estimated specific energy consumption for traction motors, kW•h/104 tonne-kilometre. In the calculations, 4-axle freight cars on rolling bearings with a mass per axle of the car m car axle = 24.8 t, continuous welded railway track [9]. The parameters of 8-axle electric locomotives in Table 1 show that the 2ES5S electric locomotive compared to electric locomotives with rotational traction motor with regard to the nominal traction mode per hour has greater power and rail tractive effort due to the greater power of the rotary-field motor. At the same time, the traction force and power of the 2ES5S electric locomotive are close to the same parameters of 12-axle electric locomotives, therefore, the 2ES5S electric locomotive allows for driving trains of almost the same mass as that of 12-axle electric locomotives with rotational traction motor. For the nominal traction mode per hour for trains of design weight on the upward journey with a slope of 8%, the estimated specific power
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Table 1 The main parameters of AC electric freight locomotives with moving trains of design weight in the nominal traction mode per hour for upward journey with a slope of 8% Electric Parameters locomotive U , n e number ml , model kV t family
Vmax , Vh , Fkm/h , Pelectromotive force , ms , t aelectric motor , km/h km/h kN kW kWh 10 4 t*km
VL80R,S
25
8
192 110
51.6
442
7199
4657 299.6
VL85
25
12
276 110
49.1
726
11,252
7722 296.7
2ES5K
25
8
192 110
49.9
464
7308
4912 298.2
3ES5K
25
12
288 110
49.9
696
10,963
7368 298.2
2ES5S
25
8
200 120
45
690
9801
7454 292.2
consumption of the 2ES5C electric locomotive is 1.5…2.5%, which is less than that of electric locomotives with rotational traction motor [7, 8]. After a test run of 5000 km on the Test Loop of JSC Railway Research Institute, certification and acceptance tests, JSC Russian Railways ordered that the 2ES5S001 electric locomotive should have operational tests in December 2019 at Artyshta II—Altayskaya section of West Siberian Railway (Fig. 1). The given section has seen 8-axle VL80S freight locomotives with dynamic braking in operation for about 40 years. The section of Artyshta II—Altayskaya with a length of 198 km has a complex track profile with steep slopes and numerous curves. For down trains, the two hauls of Artysht II—Alambay and Zarinskaya—Batunnaya have exessive gradients with a slope of 8–10% and a length of about 10 km, which heavy trains of over 5000 tons pass with VL80S electric locomotives only assisted by pusher locomotives. The rest of Artyshta II—Altayskaya section has lengthy down grades with a slope of 6–8% having total length of about 80 km. On those down grades heavy brake is applied. To test the 2ES5S-001 electric locomotive, a special experimental train was made up of loaded 4-axle cars with a total weight of 7,100 tons, equipped with strainmeasuring automatic coupling that allow for determining longitudinal dynamic forces at the head end of the train and after the 20th and 40th cars. The efficiency of regenerative braking of the 2ES5C electric locomotive with moving train of 7,100 tons is shown through the calculated dependences in Fig. 2. It can be seen that the specific recovery of electric power ae increases in proportion to the slope of the down journey i, and with an increase in the speed of movement V slightly decreases. The following provisions were used to determine the energy indicators of experimental trips [10–12]. Electric power in each section of an electric locomotive is measured by meters, while for an electric locomotive as a whole, its consumption in traction mode Aep and recovery in regenerative braking mode Are per trip are determined by formulas in which values with index 1 refer to the first section, and with index 2 refer to the second section of the electric locomotive:
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Fig. 1 Tests of an electric locomotive 2ES5S-001 with a freight train weighing 7,100 tons
Fig. 2 The calculated specific recovery of electric power of a freight electric locomotive in regenerative braking with a moving train of 7,100 tons at a steady speed on slopes of various steepness
Aep = Aep1 + Aep2 ; Are = Are1 + Are2 .
(1)
The electricity consumption in each section and for the electric locomotive as a whole is determined by the difference between its consumption and recovery and is calculated by the formula
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A = Aep − Are .
(2)
Specific consumption, recovery and consumption of electric power are determined by the formulas, kWh / 10 4 tonne kilometre: aep =
A E T · 104 A E P · 104 A E · 104 ; ar e = ; ae = m tr L m tr L m tr L
(3)
where mtr is the mass of the train, t; L—length of the section, km. The electric power recovery ratio is a relative value and is expressed by kp =
AE P aE P = . AE T aE T
(4)
3 Results The main results of one of the experimental trips are given in Table 2, their analysis shows the following. First of all, it should be noted that in experimental trips on Artyshta II—Altayskaya section, due to its greater power, the 2ES5S electric locomotive tractive effort and shunt characteristics of the rotary field traction motor, allowed for a movement of a freight train of an increased mass of 7,100 tons without a pusher locomotive. Due to this, the time taken on the section is reduced, the average operating and service speeds increase; other operating standards improve. Table 2 The results of an experimental trip with 2ES5S-001 two-unit electric locomotive on Artyshta II—Altayskaya section Parameter
Section 1
Section 2
Electric locomotive
Electric power consumption, kWh
4981
5007
9988
Recovery of electricity, kWh
2628
2662
5290
Electric power consumption, kWh
2353
2345
4698
Specific electric power consumption, kWh/10 4 tonne kilometre
–
–
71.6
Specific recovery of electricity, kWh/10 4 tonne kilometre
–
–
37.9
Specific power consumption, kWh/10 4 tonne kilometre
–
–
33.7
The electric power recovery ratio
–
–
0.53
Average speed, km/h
–
–
59.1
Ambient air temperature, °C
–
–
−12…−14
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The Table 2 shows that in the experimental trip, the specific electric power consumption of the 2ES5C electric locomotive was 71.6 kWh/104 tonne kilometre, which corresponds to the specific electric power consumption of 68…79 kWh/104 tonne kilometre of VL80S electric locomotives with pusher electric locomotives on this section with the same trains taken into account. The specific recovery of electric power in regenerative braking of the 2ES5C electric locomotive was 37.9 kWh/104 tonne kilometre, while the large ratio of electric power recovery equal to 0.53 indicates suitable for the use of regenerative braking track profile of Artyshta II—Altayskaya section and the high efficiency of this braking for the 2ES5C electric locomotive.
4 Conclusions As a result, due to regenerative braking, the resulting specific consumption of electric power for traction, which is a comprehensive integral indicator of the efficiency of electric locomotives in operation, for the 2ES5C electric locomotive was 33.7 kWh/104 tonne kilometre. This indicator is about half the specific consumption of electric power 68…79 kWh/104 tonne kilometre for VL80S electric locomotives on this section with such trains. Consequently, the 2ES5S electric locomotive has a higher energy efficiency than the previously produced VL80S electric locomotives without regenerative braking. The comparison of the specific energy indicators of the 2ES5C electric locomotive in Table 2 with the similar indicators in Table 1 and in Fig. 2 shows that the actual results are less than the calculated values. This is due to the fact that the actual data are given for the entire section, which primarily has the average gradient angle of the track profile in traction and regenerative braking modes. Thus, in the future, the operation of 2ES5S electric locomotives on Mid-Siberian trip of West Siberian Railway will allow for a great economic effect through increasing the weight of freight trains, increasing the handling and carrying capacity of the operating domain, reducing electric power consumption for traction, reducing the fleet of electric locomotives in operation.
References 1. Domanov K (2018) Innovative doubly-fed freight electric locomotive 2EV120 ‘“Knyaz’ Vladimir.”’ MATEC Web Conf 239:01001. https://doi.org/10.1051/matecconf/201823901001 2. Domanov K, Cheremisin V, Borodin A (2018) Traction capabilities of a dual-voltage electric locomotive 2EV120 on the West Siberian Railway. MATEC Web Conf 239:01031. https://doi. org/10.1051/matecconf/201823901031 3. Istomin S, Perestenko A, Dang C (2018) Development of the system of visual control of electric power consumption by electric rolling stock. MATEC Web Conf 23927:01035. https://doi.org/ 10.1051/matecconf/201823901035
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4. Douglas H, Roberts C, Hillmansen S, Schmid F (2015) An assessment of available measures to reduce traction energy use in railway networks. Energy Convers Manag 106:1149–1165. https://doi.org/10.1016/j.enconman.2015.10.05 5. Burggraeve S, Vansteenwegen P (2017) Robust routing and timetabling in complex railway stations. Transp Res Part B Methodol 101:228–244. https://doi.org/10.1016/j.trb.2017.04.007 6. Büker T, Seybold B (2012) Stochastic modelling of delay propagation in large networks. J Rail Transp Plan Manag 2(1–2):34–50. https://doi.org/10.1016/j.jrtpm.2012.10.001 7. Ghaemi N, Zilko AA, Yan F et al (2018) Impact of railway disruption predictions and rescheduling on passenger delays. J Rail Transp Plan Manag 8(2):103–122. https://doi.org/ 10.1016/j.jrtpm.2018.02.002 8. Scheepmaker GM, Willeboordse HY, Hoogenraad JH et al (2019) Comparing train driving strategies on multiple key performance indicators. J Rail Transp Plan Manag 13:100163. https:// doi.org/10.1016/j.jrtpm.2019.100163 9. Wang P, Goverde RMP (2016) Multiple-phase train trajectory optimization with signalling and operational constraints. Transp Res C Emerg Technol 69:255–275. https://doi.org/10.1016/j. trc.2016.06.008 10. Rao AV, Benson D, Darby C et al (2011) User’s manual for GPOPS version 4.X: a MATLAB software for solving multiple-phase optimal control problems using hp-adaptive pseudo spectral methods (report). https://doi.org/10.1145/2558904 11. Domanov K, Nekhaev V, Cheremisin V (2021) Optimization of operating modes of a train by the haul distance. Transp Res Procedia 54:842–853. https://doi.org/10.1016/j.trpro.2021. 02.142 12. Sicre C, Cucala AP, Fernandez-Cardador A (2014) Real time regulation of effiient driving of high speed trains based on a genetic algorithm and a fuzzy model of manual driving. Eng Appl Artif Intell 29:79–92. https://doi.org/10.1016/j.engappai.2013.07.015
The Role of Diesel Locomotives Operating Modes in Simulating the Operation of Fuel and Control Equipment of Diesel Locomotives Pavel Blinov
and Alexander Blinov
Abstract The article analyzes the operating modes of locomotive power plants, which are determined by the speed of rotation of the crankshaft of the diesel engine, the position of the regulatory body—the rails of the high-pressure fuel pump and the thermal state of the power plant. An analysis of the regime maps of locomotive control at the service area was carried out. The distance traveled at each position of the driver’s controller is determined. The factors affecting the operation of fuel equipment are analyzed; mathematical modeling of the process of fuel supply to the cylinders and the operation of the crankshaft speed controller of the diesel locomotive was made. A joint mathematical model of the operation of fuel equipment and the speed controller of the crankshaft of a diesel engine has been developed for use in the formation of kits before they are installed on a diesel engine and for calculating the parameters of fuel equipment parts used in the run-in of fuel pumps on stands currently used in locomotive depots. The paper uses mathematical and simulation modeling, methods of system analysis, comparative method, general logical methods and research techniques (analysis, generalization, classification, analogy). Keywords Diesel locomotive · Diesel engine · Fuel equipment · Pump performance · Speed controller · Mathematical model · Fuel supply · Operating modes
1 Introduction Diesel engines of mainline and shunting locomotives have frequent changes in operating modes: idle—load—idle. When the train is in operation, there are constant changes in modes coming in small intervals. At the same time, the fuel feed increases from 0 to maximum with its further sudden discharge. For mainline diesel locomotives, the main share in the total fuel consumption is accounted for operating modes close to nominal, and the other significant share is for unsteady modes. P. Blinov (B) · A. Blinov Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_49
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For freight mainline diesel locomotives, the operating time of the diesel engine at nominal mode is about 12%, at idle mode it is about 50%, at unsteady modes it is about 30%. The average number of mode changes (switching positions of the driver controller) per hour of operation for diesel engines of diesel freight locomotives is 50–60, for passenger locomotives is 110–115, for shunting locomotives is up to 130 [1].
2 Materials and Methods In order to identify the preferred positions of the locomotive driver controller (DC) and their further consideration in the mathematical modeling of diesel engines, an analysis of the mode maps of locomotive control at Kulunda—Karasuk section was done. The distance traveled at each DC position is determined. Figure 1 shows the results. 70 km 50 40 30
S 20 10 0
23
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39.6
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45.1
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8.7 11
driver’s controller positions b
Fig. 1 The dependence of the distance traveled on the DC position: a on Karasuk—Kulunda section; b on Kulunda—Karasuk section
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One of the main operational criteria for the high quality operation of a diesel engine is the minimum specific fuel consumption with a low irregularity of the cyclic fuel feed through the diesel cylinders [2, 3]. The cyclic fuel feed gc and its irregularity gc are influenced by the characteristics of the fuel equipment elements (FE). The performance of a fuel injection pump (FIP) Qp is determined by the movement of its rack x r , the density of the pump element ρpe and the pressure valve ρpv , the opening pressure of the valve Ppv and its spring rate C pv : Q p = f (xr , ρpe , ρpv , Ppv , Cpv ).
(1)
The pressure in the over-plunger enclosure Pop , in the injection nozzle chamber at the needle Pn , the amount of fuel injected into the cylinder gc in relation to the calculated angle of rotation of the crankshaft can be determined through a system of equations [4, 5]: ⎧ ⎨ Pop = Pop1 + P(h pl ) − P(Q pas ) − P(Q coh ) − P(Q c ) , P = Pn1 + P(Q pas ) − P(Z ) − P(Q c ) ⎩ n gc = gc1 + gc
(2)
where Pop1 , Pn1 , gc1 is the pressure and amount of fuel injected into the cylinder at the previous calculation step;P(h pl ), P(Q pas ), P(Q coh ), P(Q lp ), P(Q c ), P(Z ) is the increase in pressure as a result of plunger movement, the flow of fuel through the passageway, into the fuel cut-off hole, fuel leakage through the pump element, fuel feed to the cylinder and from the movement of the nozzle needle, respectively, for the time of rotation of the crankshaft by an angle ϕ; gc —the amount of fuel injected during the calculation interval. The pump discharge pressure is Pop determined through the equation: f (h−h ) btμ f Pop = Pop1 + pαop Vop1 − αop Voppas ρ2 Pop − Pn Q t f coh 2 Pop − Pcoh − αoplpVop , − ctμ αop Vop ρ
(3)
where f p is the cross section area of the plunger, m2 ; h, h1 —stroke of the plunger at the current and previous calculation step, m; α op is the average compressibility coefficient of fuel under a pressure Pop , Pa−1 ; V op is the average volume of the overplunger enclosure, m3 ; t is the calculated interval, seconds; ρ—fuel density, kg/m3 ; μf coh —effective flow passage of the pressure opening, m2 ; Q1p —fuel leaks through the gaps in the pump element, m3 /s; b, c—coefficients considering the direction of fuel flow; Pcoh —fuel pressure in the suction (sectional) chamber, Pa. Fuel pressure in the incoming chamber of the nozzle: btμ f pas Pn = Pn1 + αn Vn
tμ f n 2 Pop − Pn − ρ αn Vn
2 Pop − Pc , ρ
(4)
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where α n is the average compressibility coefficient of fuel at pressure Pn , Pa−1 ; V f is the average volume of the nozzle enclosure, m3 ; μf n —effective flow section of the nozzle, m2 ; Pc —gas pressure in the diesel cylinder, Pa; After Pop and Pn determined, the amount of fuel injected into the cylinder is calculated according to the equation [5]: gc = gc1 + tρμ f n
2 |Pn K − Pc |, ρ
(5)
where K is the coefficient of pressure loss in the pipeline considering the flow frictions associated with the final length of the pipeline. The pressure loss coefficient K in the pipeline is equal to [3]: K = C2
μ f pip − f pip
,
(6)
where C2 is the constant for this type of fuel equipment; For diesel locomotives with a linear change in the speed of the plunger, the plunger stroke is determined through [3, 5]: h = hb +
Ci (ϕ − ϕb ) (Ci+1 − Ci )(ϕ − ϕb )2 , + 6n 12nϕi
(7)
where hb and ϕ b is the stroke of the plunger and the output angle of the cam shaft corresponding to the beginning of the calculated section for the plunger speed performance curve; C i —the speed of the plunger at the nodes of the curve h = f (C), m/s; ϕ—calculated output angle of of the cam shaft, deg; n—the speed of rotation of the cam shaft used for constructing the curve h = f (C), min−1 ; ϕ i —the output angle of the cam shaft corresponding to the considered section of the plunger speed curve, deg. The area of the flow passage of the spill port for the stroke of the plunger is (h-h0 )sinβ > r equal to: f coh = πr 2 − r 2 arccos (h−h 0 )rsin β−r − r ((h − h 0 ) sin β − r )
2 (h−h 0 ) sin β−r 1− , r
(8)
and during the plunger stroke (h-h0 )sinβ > r: f coh = r 2 arccos r −(h−hr 0 ) sin β − r (r − (h − h 0 )
sin β) 1 −
r −(h−h 0 ) sin β r
2
,
(9)
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where h0 is the stroke of the plunger corresponding to the beginning of the fuel cutoff, m; β—the angle of the plunger helix to the plunger axis, deg; r—the radius of the spill port, m. Thus, a mathematical model of the fuel feed of diesel locomotive engines can be equated as follows: ⎧ ⎪ ctμ f coh 2 f p (h − h 1 ) btμ f pas 2 ⎪ ⎪ Pop − Pcoh Pop = Pop1 + Pop − Pn − − ⎪ ⎪ ⎪ α V α V ρ α V ρ op op op op op op ⎪ ⎪ ⎪ ⎨ Q lp t − , αop Vop ⎪ ⎪ tμ fn 2 √ ⎪ btμ f pas 2 ⎪ ⎪ Pn = Pn1 + αn Vn Pop − Pn − αn Vn ρ |Pn − Pc | ⎪ ⎪ ρ ⎪ ⎪ ⎩ gc = gc1 + tρμ f n 2 √|Pn K − Pc | ρ
(10)
Diesel locomotive engines often use multi-speed floating controllers of the speed of indirect action crankshaft with an isodromic feedback, which is an elastic element that allows one of the controller components to change its length during regulation. The differential equation for an isodromic automatic control system has the form [6]: + A0 ϕ A5 ddtϕ5 + A4 ddtϕ4 + A3 ddtϕ3 + A2 ddtϕ2 + A1 dϕ dt 2 dαP d 4 α0 d 3 α0 d α0 0 = S1 dt + S0 αP − B4 dt 4 − B3 dt 3 − B2 dt 2 − B1 dα dt 5
4
3
2
(11)
where is n
An dtd n the proper automatic control system operator; m k Bm dtd m , Sk dtd k , operators of disturbing effects; α0 ,αp —external influences on the controlled unit and the sensitive element of the controller; ϕ is an adjustable coordinate. Equation (11) is non-homogeneous, it describes the forced transient processes of the isodromic control system resulting from external influences α0 and αp . The values of the input and output components of the Eq. (11) are determined through the system of equations:
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⎫ A5 = To Tp2 Tc Ti ; ⎪ ⎪ ⎪ ⎪ 2 2 ⎪ A4 = Tp + To Tk Tc Ti + (Tc + Ti βi )To Tp ; ⎪ ⎪ ⎪ ⎪ ⎪ A3 = Tp2 + To Tk (Tc + Ti βi ) + (To + Tk )Tc Ti ; ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ A2 = (To + Tk )(Tc + Ti βi ) + Tc Ti ; ⎪ ⎪ ⎪ ⎪ ⎪ A2 = (To + Tk )(Tc + Ti βi ) + Tc Ti ; ⎪ ⎪ χ ϕ ⎪ ⎪ A1 = (Tc + Ti βi ) + Ti ko kp ; ⎪ ⎬ χ ϕ A0 = ko kp ; ⎪ χ ⎪ S1 = Ti ko kpα ; ⎪ ⎪ ⎪ χ α ⎪ ⎪ S0 = ko kp ; ⎪ ⎪ ⎪ ⎪ B4 = Tp2 Tc Ti koα ; ⎪ ⎪ ⎪ ⎪ 2 α α ⎪ B3 = (Tc + Ti βi )Tp ko + Tk Tc Ti ko ; ⎪ ⎪ ⎪ α α ⎪ B2 = (Tc + Ti βi )Tk ko + Tc Ti ko ; ⎪ ⎪ ⎪ ⎪ ⎪ B1 = (Tc + Ti βi )koα ; ⎪ ⎭ B0 = 0,
(12)
χ
where ko , koα , kpϕ , kpα are the gain factors for the input coordinates; T 0 —the time constant of the controlled object; T p —time constant of the controller; T k —dash pot time constant (compensating element); T c —the time constant of the servicing motor; T i —the time constant of proportional plus integral element; β i —proportionality coefficient.
3 Results Electronic automatic control systems are used as an effective means of reducing operational fuel consumption and emissions of toxic substances in diesel engines [7]. Modifications of electronic controllers of the ERCHM30T type have been developed to be installed on 2TE116, TEM18, 2TE10, 2TE70, 2TE25K, TEP70BS and TEP70U locomotives. The electronic system of automatic speed control of the crankshaft of a diesel engine of the ERCHM30T type consists of a diesel engine with a fuel injection pump; a diesel chopper; a magnetic transducer and an electronic speed controller containing a control unit and an electrohydraulic actuator; a lever mechanism from the actuator to the fuel injection pump. Figure 2 shows the block diagram of the electronic system of automatic speed control of diesel engine. The gain of the electronic speed controller is equal to the product of the gains of the control unit k ku and the actuator k act . It depends on the gain of the link in calculating the current rotational speed k cr , the coefficient at the average voltage supplied to the electromagnet of the actuator k u , constant time filtration link T f , constant actuator time T and control coefficients k 1 , k 2 , k 3 [7]:
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Fig. 2 Block diagram of the electronic system of diesel locomotive automatic speed control: n d—diesel engine speed; U—oltage fed from the control unit to the actuator; y—movement of the output element (servicing motor stroke) of the actuator; x r—the stroke of the fuel injection pump rack; z i m is the number of teeth of the chopper passing through the magnetic transducer per second when the diesel shaft rotates; z i is the number of periods of sinusoidal signals coming from the magnetic transducer per second
kesc = kku kact
2 k3 − k2 ω2 + k1 ω2 . = kcr ku · 2 1 + Tf2 ω2 1 − Tf2 ω2 + (2δT ω)2
(13)
Displacement of fuel injection pump racks, mm: xr = kl.g Y,
(14)
where Y is the displacement of the piston of the servicing motor of electric speed controller actuator, mm; klg —lever gear gain factor. The gain of the leverage from the electric speed controller actuator to the diesel fuel injection pump racks: kl.g =
aw 2 + bw 2 xr N = . cw 2 + dw 2 YN
(15)
where xrN is the nominal stroke of the fuel pump racks, mm; YN —nominal stroke of the piston of the servicing motor of electric speed controller actuator, mm. To connect the fuel equipment and the diesel engine speed controllers, a speed controller actuator and a leverage affecting the control body, which is the fuel rack, are used. The amount of fuel fed to the cylinder per cycle depends on the position of
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the screw helix of the plunger head against the side slot of the sleeve. The change in the load on the diesel engine leads to the fact that with the help of speed controller actuator the control fuel rack of the fuel injection pump moves through the lever mechanism. Thus, the rack turns the plunger against the sleeve with the help of a splined control sleeve. This leads to a change in the fuel feed to the diesel cylinders.
4 Conclusion The analysis of the presented data showed that mathematical models of the fuel feed and the operation of the diesel crankshaft speed controller can be linked through the stroke of the xr fuel injection pump rack. For a hydromechanical controller, it is necessary to link the performance of the injection pump Qp , which is determined by the output of the rack xr , with the equations of the controller (11)–(12). At the same time, it is necessary to take into account all the components of the equation that affect the performance of the fuel injection pump (1). Similarly, for an electronic controller, it is necessary to link the performance of the injection pump Qp with the equations of the controller (13)–(15). The presented model of the joint work of the fuel equipment and the diesel speed controller can be used for putting together the sets of the fuel equipment and the speed controllers before they are installed on the diesel engine and for calculating the parameters of the fuel equipment parts used in the bench running of the fuel injection pump in loco service depots.
References 1. Xin Q (2013) The analytical design process and diesel engine system design J Diesel Eng Syst Des 3–112. https://doi.org/10.1533/9780857090836.1.3 2. Marko K, Alfredo N, van Oort N, Goverde RMP (2021) Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains. Appl Energy 294:117018. https://doi.org/10.1016/j.apenergy.2021.117018 3. Huang F, Kong W (2020) Experimental investigation of operating characteristics and thermal balance of a miniature free-piston linear engine. Journal Applied Thermal Engineering 178:115608. https://doi.org/10.1016/j.applthermaleng.2020.115608 4. Bimal K. Bose (2020) Power electronics and motor drives. In: Advances and trends, 2nd edn. The University of Tennessee, Knoxville, TN, United States. https://doi.org/10.1016/C2019-002032-8 5. Kagramanian A, Stankevich P, Aulin D, Basov A (2019) Efficiency improvement of locomotivetype diesel engine operation due to introduction of resource-saving technologies for cleaning diesel and diesel locomotive systems. J Procedia Comput Sci 149:264–273. https://doi.org/10. 1016/j.procs.2019.01.133
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6. Markov VA, Furman VV, Ivanov VA (2013) Investigation of the automatic speed control system of diesel locomotive engine. BMSTU J Mech Eng 8:54–63. https://doi.org/10.1016/j.apenergy. 2021.117018 7. Ranjan G, Tiwar R (2020) On-site high-speed balancing of flexible rotor-bearing system using virtual trial unbalances at slow run. Int J Mech Sci 183:105786. https://doi.org/10.1016/j.ijm ecsci.2020.105786
The Categorization of Methods and Means of Energy Optimized Control of Electric Railway Rolling Stock Stanislav Istomin , Egor Avdienko , Kirill Domanov , and Andrey Shatohin
Abstract The purpose of the paper is to analyze the existing methods, means and technical solutions for improving the efficiency of electric railway rolling stock operation. The study focuses on energy efficient management of rolling stock, which can be improved through the use of breakthrough information technologies (Big Data and Industrial Internet of things) and a trainable neural network (artificial intelligence) according to the concept of “Digital Railway” by 2030. The first part of the article considers in detail the existing systems of automatic operation of freight, passenger, suburban and double trains of increased mass and length, as well as an autonomous driver information system with an electronic driver route function (hereinafter referred to as ADIS EDR). The work considers the scholarly papers of foreign researchers. The analyzed works show that the most often used is a continuous method of driving a train with the help of PMP program having a built-in algorithm for finding exact solutions during movement or a discrete control method with an approximation method. The development of new or modernization of the existing automatic operation system through breakthrough information technologies with such parameters as the traffic schedule, the capability of infrastructure, the crews of centralized traffic centers and the statuses of the proximate traffic participants taken into account are proposed as directions for further research. Keywords Electric railway rolling stock · Automatic train operation · Energy efficiency · Energy optimized
1 Introduction Currently, JSC “Russian Railways” has a developed strategy for the digital transformation of the holding. The main goal is to increase the competitiveness and efficiency of the Russian Railways holding through the use of breakthrough information technologies, including: S. Istomin (B) · E. Avdienko · K. Domanov · A. Shatohin Omsk State Transport University, 35 Prospekt Marksa, 644046 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_50
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The technologies of “Industrial Internet of Things” and “Big Data” for automatic operation taking into account a given train schedule, the infrastructure capability, traffic control center crews, the technical condition of rolling stock and the status of the approximate traffic participants. These technologies are used for the constant collection of primary data on the state of the rolling stock and infrastructure with the subsequent complex object descriptions in order to manage their life cycle, monitoring the condition of rolling stock in motion, digital infrastructure diagnostics and real-time interaction with participants in production and suppliers; “Imitation Modeling” technology for controlling cars and locomotives, which allows determining the optimal operating mode of the rolling stock considering its location, owner, status, operation and technical condition plans as well as reserving car seats in order to increase the efficiency of the rolling stock. the priority development directions in transition to modern methods and means of managing rolling stock according to are: the implementation of process procedures of infrastructure maintenance and the provision of the “unmanned train movement” system based on the digital infrastructure model with a geocentric coordinate system; the unification of local and metro train traffic control systems in large metropolitan areas; the creation of a new generation of on-board security systems with the help of computer technologies having elements of artificial intelligence; the development of the regulatory framework and technologies for collecting and processing information.
2 Materials and Methods At present, the Russian rolling stock in most cases has an automatic operation system of the AVP Technology company. The system includes a unified system of automated train driving (USATD), a universal system of automated operation of passenger electric locomotives (USAOPEL), a universal system of automated operation of freight electric locomotives (USAOFEL), as well as an intelligent system of automated driving of trains of increased weight and length with locomotives provided within a length of a train. The next step was the modernization of these systems by integrating into the control cabin such software and hardware packages as the driver information system (DIS) and autonomous driver information system with the electronic driver route (ADIS-EDR). Below we will give a more detailed analysis of these systems indicating some drawbacks. The USATD system is designed to provide an automatic control of traction and brake modes of DC and AC electric trains. The system allows you to follow a traffic schedule with high accuracy and facilitate the work of drivers while ensuring optimal power energy consumption for traction. The system of automatic operation
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of suburban electric trains is based on microprocessor technologies. It is a software and hardware package that provides an automatic control of an electric train. The main effects of an automatic operation system usage: it allows you to reduce the power energy consumption from 2 to 10% (depending on the operating conditions); increases the level of traffic safety; provides information support for the driver at night and in the morning as well as in conditions of poor visibility (snow, rain, fog); reduces the negative impact of complex traffic situations on the psychophysiological state of the driver; reduces the time for training drivers and learning of energy optimized train driving modes by inexperienced drivers; significantly improves the quality of passenger service due to accurate compliance with the schedule and the guaranteed announcement of stops and other social information. The USAOPEL system. This system was developed specifically for passenger electric locomotives of certain series, for automatic control of electric locomotives CHS2, CHS2K, ChS2T, ChS4T, ChS6, ChS7, ChS8, ChS200, EP1M, EP2K, EP20, KZ4AT. The automatic control is carried out in the mode of optimal power energy consumption with the exact compliance with the run time (set by the traffic schedule or other regulatory document). The use of USAOPEL contributes to improving traffic safety and facilitates the work of the driver. Its main difference from other systems is that USAOPEL ensures not only the maintenance of the speed selected by the system or set by the driver but also constantly calculates the optimal speed to minimize the consumed power energy and the compliance with the train schedule with an accuracy of ±1 min. The universal system of automatic freight and freight and passenger train operation are designed for automatic control of electric locomotives of the type VL10, VL11, VL80S, VL85, 2ES5K (3ES5K), KZ8A, 2ES5, 2ES6, 2ES4K (3ES4K). It has been upgraded by adding the function of the driver information system, which was developed in order to expand the functionality of automatic operation system. The intelligent system of automated driving of trains of increased weight and length with locomotives provided within a length of a train is designed for automated and simultaneous control of freight electric locomotives when multiple trains up to 12 thousand tons and above are operated. The specific feature of this intelligent system is the ability to control the rear car unit (RCU) and the train brake control system or train brake distributed control system for the trains weighing up to 9000 thousand tons. The implementation of this system allowed increasing the train-handling capacity of the sections by 5%, the route speed up to 1000 km per a full day. To have a more detailed understanding of the efficiency of the universal system of automatic train operation, one should consider it simultaneously with the complementary package of the driver information system (DIS) and its more advanced version of ADIS-EDR. This system is designed to receive various data on track
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occupancy, infrastructure capability, driver data, etc. via wireless communication channels from the interaction with the locomotive via radio communication. The system provides for the locomotive crew the display of all incoming information in graphic, text and speech forms. All these factors make it possible to increase traffic safety along the route by automating the processes of receiving and transmitting data via wireless communication channels. In the end, we can identify the following main functions of existing automatic operation systems: the calculation of the energy optimized motion trajectory; logging of movement parameters (speed, time, etc.); receiving signals from angular movement sensors; receiving signals from the ALSN (Continuous Automatic Train Signaling); following the traffic schedule; recording power energy consumption; brake equipment management; informing the driver during the operation. The main method used by the automatic operation system to determine the energy optimized trajectory is the Pontryagin maximum principle [1]. Its main task is to determine the control modes for the non-stop movement of the train along the section between the starting and ending points for a given time ensuring the minimum energy consumption for traction with the track layout, the length of the train, the type and load of cars, traction and brake characteristics of the locomotive, speed limits taken into account. The beginning of the solution is the search for the initial permissible train control mode that most closely satisfies all the conditions and constraints of the problem. In this case, an algorithm based on the regulation of the travel time is used, and then the optimization algorithm itself is used to consistently improve the initial approximation in terms of energy consumption [2–8]. That is, at each step of the iterative process, a motion trajectory satisfying all the conditions and constraints of the problem is constructed. During the implementation of this motion trajectory, the energy consumption is less than during the implementation of the trajectory calculated at the previous step. Outside of Russia, the issue of energy efficient management is also subject to numerous studies. The scholars from the Netherlands and Australia [9] tried to modernize some of their systems: MMTC (Minimum Time Train Control) and EETC (Energy Efficient Train Scheduling). They offer various ways to improve energy efficient control based on dynamic programming with the help of several methods (direct and indirect). The scientists from Switzerland [10] have proposed a different way to improve the energy efficient management of rolling stock. It is a method for adding aerodynamic drag to the equation of medium motion. In addition, the software has been developed for analyzing and processing all data in real time depending on the wind strength along the track section. The Chinese scientists [11, 12] proposed a method for reusing power energy (after recovery). An electric train is to begin the recovery process when there is another
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rolling stock on the border of this zone that can consume this power energy. In this case, the algorithm is linked to the traffic schedule to coordinate the proximate trains. Another group of researchers from Beijing [13–15] has developed a new algorithm for improving energy efficient control of rolling stock based on a dynamic model of switching train modes. This algorithm has been integrated into the existing Model Prediction Control System (MPC). Its operation is based on the interaction of three cycles of mode switching. The first cycle is responsible for monitoring the optimal time of switching the train mode until the train stops at the next station. The second cycle controls the constant updating of the limiting factors so that their maximum value does not exceed a certain threshold. The limiting factors mean the zero speed limit when the train arrives at the station and the run distance limit in the final time interval. The third cycle is used to control the constant updating of the mode switching time until the gradient of the loss function decreases to the value of the preset threshold. As a result, with an increase in travel time, the share of using the stopping regime increases due to the optimal switching time of train modes, which leads to a decrease in power energy consumption by rolling stock. The categorization of the trends developed by foreign scientists on energy efficiency management is presented in Table 1, where C is continuous control, D is discrete control, E is an accurate method, and A is an approximation method. Table 1 shows that the scientists prefer to use a continuous method of driving a train with the help of the PMP program having a built-in algorithm for finding exact solutions during the movement. At the same time, some of them prefer to use a discrete control method and the approximation method for further calculations. Basically, the scientists are engaged in developing the methods of reducing power energy consumption for suburban and freight rolling stock.
3 Results Having investigated the existing system of automatic operation in detail, the trends developed by foreign scientists and the development program of JSC “Russian Railways”, we can conclude that it is necessary to develop new or modernize the existing system of automatic operation through breakthrough information technologies. It is planned to develop a new system which will technically increase the automation of rolling stock control (unmanned energy efficient control) and improve traffic safety (the use of computer vision). This technical solution will be implemented through the use of a trainable neural network with the technology of Deep learning (a set of machine learning methods), which will be created in Python programming language. Figure 1 shows the scheme of functioning of this system. In this scheme: 1 is a memory block (in which all the data necessary for the implementation of an energy optimal motion trajectory will be stored and received), 2 is a computer vision system (receives the data from radars, lidars, IR cameras, etc.), 3 is a computation node (a trainable neural network), 4 and 5 are traction
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Table 1 The comparative analysis of development trends for optimizing energy efficient rolling stock management abroad Publications
Control
Method
In real time
Various parameters
Type of transport
V
grade
High-speed railway lines
Suburban
Freight
x
x
x
–
x
x
Howlett and Pudney (1995)
C, D
E
Vu (2006)
C
E
–
x
x
–
–
–
Howlett et al. (2009)
C
E
x
x
x
–
–
x
T. Albrecht et all (2013a)
C
E
–
x
x
–
–
–
T. Albrecht et all (2013b)
C
E
x
x
x
–
x
–
T. Albrecht et all (2014)
C
E
–
x
x
–
x
x
T. Albrecht et all (2015b, c)
C
E
x
x
x
x
x
–
Lechelle and Mouneimme (2010)
C
A
x
x
x
x
–
–
Dominguez et al. (2011)
C
A
–
–
x
–
x
Chevrier et al. (2013)
C
E
–
–
x
x
–
x
Lu et al. (2013) C
A/E
–
–
x
x
–
x
Rodrigo et al. (2013)
C
E
–
–
x
x
x
–
Sheepmaker and Goverde (2015)
C
E
–
x
x
x
x
–
Su et al. (2013) C
A
–
x
x
x
–
x
Su et al. (2014) C
A
–
x
x
–
–
x
T. Albrecht et all (2013c)
C
E
x
x
x
x
–
x
Jakel and T. Albrecht et all (2013)
C
E
x
x
x
x
x
x
(continued)
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Table 1 (continued) Publications
Qu et all (2014)
Control
C
Method
E
In real time
Various parameters
Type of transport
V
grade
High-speed railway lines
Suburban
Freight
–
x
x
x
–
–
Fig. 1 The scheme of functioning of the given system
and brake control units. The entire data flow will be sent to the artificial neural networks (ANN), which will calculate the energy optimized motion trajectory and form control signals for managing traction and braking. The proposed system will differ in that that it will be able to take into account a larger number of input data that were not previously considered. It will keep records of the statuses of the proximate traffic participants, have a connection with traction substations, receive signals from aerodynamic sensors. The system will also allow you to identify objects on the tracks during movement due to computer vision, remotely control the brake equipment, remotely start the rolling stock and perform automatic testing of the brakes. It is worth noting that the task of creating a fully automated railway rolling stock does not become less complicated due to the movement of the train along a fixed route specified by the rails. Due to the high speed of movement and the increased degree of danger of railway transportation, this task is becoming more complicated. Computer vision is one of the most important elements of an automated control system, it allows you to classify and identify the features of objects, process signals, recognize images, etc. For railway transport, the main tasks of computer vision are: – – – –
the movement along the given route; the movement on the railway turnout; the detection and recognition of traffic lights; the detection of interference and obstacles at the start of the movement;
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the visual inspection of rolling stock equipment; the visual assessment of the railway infrastructure integrity; the creation of digital models of the external environment; the safe boarding and disembarkation of passengers; humping of cars; the access to the cars; coupling cars.
The solution of these problems is possible through a trainable neural network as a part of a computer vision package.
4 Discussion At present, there are a huge number of methods and means of image processing, so one and the same method will not work for these tasks. To prove how difficult, it will be to solve a particular problem, we can give an example of detecting and recognizing traffic lights. The problem is complicated by the fact that the processed background is not simple, and the signal we are interested in occupies a very small area of the image. Traditional image processing methods do not allow you to achieve the desired result, they are prone to errors, especially at high speeds and a contrasting background. Currently, convolution neural networks with strong learning capabilities are also used for recognition but in order to avoid the risk of retraining such methods often require a large number of training sets, which are also available in the public domain [16]. Most methods still use the a priori color of the signal to obtain the area of interest in various color spaces, and then make further judgments based on the unique shape characteristics and angular characteristics of the signal [17]. In conclusion, it can be noted that today there is a significant interest in neural networks that are successfully used in various fields ranging from business to medicine. The use of a trainable neural network for an electric rolling stock will open up new opportunities for implementing energy optimized safe unmanned control of a locomotive.
References 1. Hai NT (2010) Evaluation of effect Pontryagin’s Maximum Principle for optimal control train by criteria of energy save. In: International symposium on computer, communication, control and automation (3CA). https://doi.org/10.1109/3CA.2010.5533807 2. Bao K, Lu S, Xue F, Tan Z (2017) Optimization for train speed trajectory based on Pontryagin’s Maximum Principle. In: IEEE 20th international conference on intelligent transportation systems (ITSC). https://doi.org/10.1109/ITSC.2017.8317820 3. Yurenko KI, Kharchenko PA, Fandeev EI, Yurenko IK (2018) Train operation control on-based of logical-linguistic model. EAI Endorsed Trans Energy Web 6:e4. https://doi.org/10.4108/eai. 13-7-2018.156388
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4. Scheepmaker GM, Pudney PJ, Albrecht AR, Goverde RMP, Howlett PG (2020) Optimal running time supplement distribution in train schedules for energy-efficient train control. J Rail Transp Plan Manag 14:100180. https://doi.org/10.1016/j.jrtpm.2020.100180 5. Trivella A, Wang P, Corman F (2020) The impact of wind on energy-efficient train control. Institute for Transport Planning and Systems. ETH Zürich, Switzerland, Zurich, 8093. https:// doi.org/10.1016/j.ejtl.2020.10001 6. Yang X, Li X, Ning B, Tang TA (2016) Survey on energy-efficient train operation for urban rail transit. IEEE Trans Intell Transp Syst 17:2–13. https://doi.org/10.1109/TITS.2015.2447507 7. Su S, Wang X, Yin J (2019) An energy-efficient train operation approach by integrating the metro timetabling and eco-driving. Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China, Beijing, p 100044. https://doi.org/10.1109/TITS.2019.2939358 8. Yazhemsky D, Rashid M, Sirouspou S (2019) An on-line optimal controller for a commuter train. IEEE Trans Intell Transp Syst 20:1112–1125. https://doi.org/10.1109/TITS.2018.284 6480 9. Azuma SI, Egerstedt M, Wardi Y (2006) Output-based optimal timing control of switched systems. In: Proceedings of the international workshop on hybrid systems: computation and control. LNCS, USA, CA, Santa Barbara. https://doi.org/10.1007/11730637_8 10. Wang P, Goverde RMP (2019) Multi-train trajectory optimization for energy-efficient timetabling. Eur J Oper Res 272(2):621–635. https://doi.org/10.1016/j.ejor.2018.06.034 11. Bin Z, You S, Zhang L, Li D, Chen Y (2021) Energy-efficient speed profile optimization for high-speed railway considering neutral sections. IEEE Access 9:25090–25100. https://doi.org/ 10.1109/ACCESS.2021.3056387 12. Visilter YV, Zheltov SY (2011) Problems of computer vision in modern aviation systems. In: Computer vision in mobile object management systems, pp 11–44. https://doi.org/10.1007/s10 846-017-0483-z 13. Lyasheva S, Shleymovich M, Shakirzyanov R (2019) The image analysis using fast radial symmetry transform in control systems base on the computer vision. In: International multiconference on industrial engineering and modern technologies, FarEastCon. 2019. https://doi. org/10.1109/FarEastCon.2019.8934298 14. Gu Q, Tang T, Ma F (2016) Energy-efficient train tracking operation based on multiple optimization models. IEEE Trans Intell Transp Syst 17(3):882–892. https://doi.org/10.1109/TITS. 2015.2502609 15. Wang Pengling, Rob MP Goverde (2016) Train trajectory optimization of opposite trains on single-track railway lines. In: 2016 IEEE International conference on intelligent rail transportation (ICIRT). https://doi.org/10.1109/ICIRT.2016.7588546 16. Komyakov AA, Nikiforov MM, Erbes VV, Cheremisin VT, Ivanchenko VI (2016) Construction of electricity consumption mathematical models on railway transport used artificial neural network and fuzzy neural network. In: 2016 IEEE 16th international conference on environment and electrical engineering (EEEIC). https://doi.org/10.1109/EEEIC.2016.7555450 17. Thendral R, Ranjeeth A (2021) Computer Vision system for railway track crack detection using deep learning neural network. In: 3rd international conference on signal processing and communication (ICPSC). https://doi.org/10.1109/ICSPC51351.2021.9451771
Interval Estimation of Magnetotelluric Response Function and Quality Control During Registration of Data Andrey Lavrukhin , Alena Tukanova , Aleksandr Onufriev , and Andrey Malyutin
Abstract In this paper, we consider algorithms for calculating impedance in the magnetotelluric sounding method. Most of the existing algorithms are based on the least-squares method, supplementing it with various robust approaches. Usage of them mutually with a remote reference can reduce the effect of noise and interference in the signals on the final result. The problem is that the confidence intervals of the estimates of impedance have a blurry essence since it is impossible to completely guarantee that the signals are free of interference that introduces bias in the estimates. Confidence intervals are in some cases ignored by geophysicists during further data processing. We propose to move away from traditional probabilistic statistics and use interval analysis methods. In addition, we propose to evaluate the adequacy of the obtained intervals, using physical limitations, which must necessarily obey the impedance and apparent resistance. In the process of accumulating a sufficient amount of data, there is a tendency to increase the compliance of calculated estimates with physical limitations. This fact can be used to roughly control the information content of the recorded signals and the quality of the data. To demonstrate the propositions, we present a number of numerical tests using natural magnetotelluric data. Keywords Magnetotellurics · Estimation · Interval analysis · Quality control
1 Introduction The technology of the magnetotelluric (MT) sounding method [1] consists of the registration of components of the electromagnetic field, which requires from 15 min to several days (depending on the modification of the method and investigated depths). There is a huge number of approaches to optimization of the technology to improve the accuracy of the results and reduce data collection time [2]. A. Lavrukhin (B) · A. Tukanova · A. Onufriev · A. Malyutin Omsk State Transport University, 35, Marx Avenue, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_51
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MT data processing algorithms use various methods based on the theory of probability and mathematical statistics [3]. The most common methods are least squares and maximum likelihood [4], and a wide variety of procedures increasing the robustness of estimates [5, 6]. The need to use robust procedures is since not all interference in MT signals can be identified and excluded [7, 8]. The nature of noise and interference often leads to violation of the hypothesis of the adopted distribution law [9]. Robust methods are aimed at eliminating or reducing the influence of those data that introduce the bias in the resulting solution. The obtained values of the response function are supplemented with confidence intervals, but the essence of the obtained intervals is lost in some cases. If correlated interference is present in the signals, the estimates may have significant biases [10], so the confidence interval is not the range in which the true value of the impedance is located with a given confidence level. For this reason, we propose to get away from the concept of confidence intervals towards ordinary ones, motivated by the fact that, in practice, a geophysicist can edit data guided by some a priori information about the investigated geoelectric section. Probability-theoretic constructions are applicable in cases where statistically stable phenomena take place. Signals not cleared of interference cannot be considered as a reflection of the statistically stable phenomenon. Interval analysis [11] describes uncertainties in terms of intervals without any probability distribution function. The objective of the current study was to examine interval analysis methods for calculating the impedance tensor. Earlier we described the first experience in the article [12]. For sufficiently accurate data processing, it is necessary to have high-quality field data. There are methods for quality estimation of MT data, such as [13]. Modern equipment allows real-time data transmission for preliminary calculation of apparent resistivity and construction of a geo-section by a geophysicist, where new methods like [14] can be applied. But usually, the time of registration is selected based on general recommendations. We propose an approach to simple quality control during registration, which aims to indicate that there is insufficient information in the signals to obtain a sufficiently accurate solution. This article discusses the analysis of the quality index of MT data, which compares the interval solutions with the physical constraints that the impedance must agree on, and can be used mutually with interval approach.
2 Materials and Methods The data processing algorithm has a general scheme, shown in the Fig. 1. It transforms time-domain signals E x , E y , Hx , Hy , synchronously obtained by a registration station at a certain field point, into the frequency domain, selects events with high magnetotelluric informational content, compilates systems of equations, and finds their solutions to get apparent resistances with confidence intervals. Next, we consider the stage 5 of the algorithm. The system of linear algebraic equations is compiled for complex signal values determined for one fixed frequency, taken in different time neighborhoods. The model connects the measured and processed
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Fig. 1 Common algorithm for processing magnetotelluric data
values of electrical E x , E y and magnetic Hx , Hy field by unknown components of impedance Z x x , Z x y , Z yx , Z yy [3]: H · Z x x x y = Ex H · Z yx yy = E y ⎡ ⎤ Hx1 Hy1 H = ⎣ ... ... ⎦ Hx N Hy N
(1)
(2)
T T E x = E x1 . . . E x N ; E y = E y1 . . . E y N
(3)
T T Z x x x y = Z x x Z x y ; Z yx yy = Z yx Z yy
(4)
where H is N × 2 matrix, E x and E y are N × 1 vectors, Z x x x y and Z yx yy are 2 × 1 vectors. The interval analysis requires the use of intervals instead of point values. An interval, given by its left and right ends, is a set of numbers in which a certain value can be located. Next, we bring model (1) to an interval form: ⎤ Hy1 − h y1 , Hy1 + h y1 [Hx1 − h x1 , Hx1 + h x1 ] ⎦ H =⎣ ... ... [Hx N − h x N , Hx N + h x N ] Hy N − h y N , Hy N + h y N ⎤ ⎡ ⎡ ⎤ E y1 − e y1 , E y1 + e y1 [E x1 − ex1 , E x1 + ex1 ] ⎦ ⎦; E y = ⎣ Ex = ⎣ ... ... E y N − ey N , E y N + ey N [E x N − ex N , E x N + ex N ] Z x x + [−z x x , z x x ] Z yx + −z yx , z yx Zx x x y = ; Z yx yy = Z x y + −z x y , z x y Z yy + −z yy , z yy ⎡
(5)
(6)
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where the original values Hxi , Hyi , E xi , E yi , Z x x , Z x y , Z yx , Z yy are the centers of intervals and values h xi , h yi , exi , e yi , z x x , z x y , z yx , z yy are their radii. A separate difficulty is that the elements of the original model are complex numbers, so we need to get the model for complex intervals. For simplicity, we leave the magnetic component in the point form, and convert the electrical component to the interval form, writing down the equations for the real and imaginary parts: Hri · Z x x x yri = E xri Hri · Z yx yyri = E yri
⎤ ReHx1 −ImHx1 ReHy1 −ImHy1 ⎥ ⎢ ImH ReH ImH ReH ⎥ ⎢ x1 x1 y1 y1 ⎥ ⎢ Hri = ⎢ ... ⎥ ⎥ ⎢ ⎣ ReHx N −ImHx N ReHy N −ImHy N ⎦ ImHx N ReHx N ImHy N ReHy N ⎤ ⎡ [ReE x1 − ex1r , ReE x1 + ex1r ] ⎢ [ImE − e , ImE + e ] ⎥ ⎥ ⎢ x1 x1i x1 x1i ⎥ ⎢ E xri = ⎢ ... ⎥ ⎥ ⎢ ⎣ [ReE x N − ex Nr , ReE x N + ex Nr ] ⎦ [ImE x N − ex N i , ImE x N + ex N i ] ⎡ ⎤ ReE − e , ReE + e y1 y1r y1 y1r ⎢ ImE − e , ImE + e ⎥ ⎥ ⎢ y1 y1i y1 y1i ⎥ ⎢ E yri = ⎢ . . . ⎥ ⎥ ⎢ ⎣ ReE y N − e y Nr , ReE y N + e y Nr ⎦ ImE y N − e y N i , ImE y N + e y N i ⎤ ⎡ [ReZ x x − z x xr , ReZ x x + z x xr ] ⎢ [ImZ x x − z x xi , ImZ x x + z x xi ] ⎥ ⎥ Z x x x yri = ⎢ ⎣ ReZ x y − z x yr , ReZ x y + z x yr ⎦ ImZ x y − z x yi , ImZ x y + z x yi ⎤ ⎡ ReZ yx − z yxr , ReZ yx + z yxr ⎢ ImZ yx − z yxi , ImZ yx + z yxi ⎥ ⎥ Z yx yyri = ⎢ ⎣ ReZ yy − z yyr , ReZ yy + z yyr ⎦ ImZ yy − z yyi , ImZ yy + z yyi ⎡
(8)
(9)
(10)
(11)
(12)
(13)
The parameters e in vectors (10), (11) are radii and we propose to calculate e as the residuals (difference between the measured and predicted values of the electric field): e = E − Eˆ
(14)
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To calculate the predicted values we can use the actual values and the predictor matrix [3] (* is Hermitian conjugation) [4, 12]:
−1 · H∗ Hˆ = H · H ∗ · H
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Eˆ = Hˆ · E
(16)
To obtain interval impedance estimates we used the Hansen-Bliek-Rohn method [15]. When searching for solutions to an overdetermined interval system of linear algebraic equations, the commonly used concepts are weak compatibility of data (the result is so-called united solution set) and strong compatibility of data (the result is so-called tolerable solution set) [16, 17]. In our case, it is convenient to search for a tolerable solution set (all solutions satisfies all intervals of the matrix E). In order to determine existence of a solution set, the method of the recognizing functional is used. If a solution does not exist, an additional regularization aimed at widening the intervals can give this solution. Usually, the intervals expand symmetrically by the same amount. But obtained characteristics have logarithmic dependencies, so we propose to regularize the equations by changing the radius of the intervals by a certain number of times. Equations (8) take the form with regularization parameter α: Hri · Z x x x yri = α E xri Hri · Z yx yyri = α E yri
(17)
Impedance, as a characteristic reflecting the physical properties of a geoelectric section, is subject to physical limitations. These limitations are reflected in the apparent resistance. The functional dependence of the apparent resistance on the signal period, if it is plotted on a logarithmic scale, cannot have a slope exceeding 45°. This means that the derivative of this logarithmic function must be within the range [–1;1]. We propose to introduce the coefficient of physical matching of interval solutions at close frequencies. This coefficient will be equal to zero if the rate of change of the apparent resistance is within acceptable limits. With an increase in the difference between adjacent intervals, the value of this coefficient increases. Formula for calculating the coefficient of physical matching is: γi = clip(ρ i+1 − ρi − f ) + clip(ρ i − ρi+1 − f)+ + clip ρi+1 − ρi − f + clip ρi − ρi+1 − f ; clip(b) =
b, b > 0 0, b ≤ 0
(18)
(19)
The meaning of the physical limitations is shown in Fig. 2. We introduce an integral quality index, which is equal to the sum of the coefficients γ for all frequencies numbered from 1 to N:
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Fig. 2 Physical limitations for neighboring interval values of apparent resistivity
Q=
N i=1
γi
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A decrease in the quality index in the process of data recording may indicate that the result obtained is more consistent with physical limitations, which means that the probability that fragments of the resulting impedance have local bias decreases. To test the proposed approaches, we used magnetotelluric signals obtained in the Tevrizovsky district of the Omsk region, Russia, at the point-1 (57° 32 3.84 N; 72° 19 12.65 E) and at the point-2 (57° 32 31.20 N; 72° 12 29.45 E). We obtained solutions using three algorithms that differ only at the stage 5. All algorithms perform the same signal preparation and rejection by the coherence criterion. The first algorithm (LSM) uses the least squares method without additional procedures [3]. The second algorithm (Robust) uses a robust scheme with a repetitive median estimate (modified Siegel’s method), which is described in [18]. The third algorithm (Interval) uses the Hansen-Bliek-Rohn method implemented in the library intvalpy for Python (developed by S. P. Shary and A. S. Androsov). The third algorithm does not use robust schemes that could improve interval solutions.
3 Results and Discussion
The obtained dependences
of the absolute values of impedance abs Z yx and the impedance phases arg Z yx for point-1 are shown in the Fig. 3. The Robust algorithm, when compared with the simple version of LSM, significantly improves the estimates obtained. However, an additional increase in the accuracy could be provided only by the remote reference method. The first version of the Interval algorithm, which we considered in this article, gave a solution that can be estimated as intermediate between the simple LSM solution and the Robust solution. Similar results were obtained for point-2. The difference is that the Z x y component has a strong influence of noise, which could not be eliminated by the rejection procedure based on coherence analysis.
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Fig. 3 Absolute impedance and its phase at point-1 using LSM a, Robust b and Interval c methods
We used the same field data for experimental test of the integral quality index. The total signal recording time was 2 h. In the process of recording signals, intermediate values of impedances and apparent resistances, as well as values of the Q index, were calculated. Figure 4(a) shows the dependence of Q/N on the normalized time for point-1, using each of the three algorithms: LSM, Robust, Interval. Figure 4(b) shows the same dependencies for point-2. In the course of registration, the index Q normally decreases and has convergence. The time of the transient process of the function Q(t) can be considered as an estimate of the required time for collecting information about the geoelectric section. Figure 4(b) shows a more complicated situation. The behavior of the Q index calculated from the intervals ρyx (lines 2) has the same common character as in the previous case. The Q index, calculated from the ρxy intervals (lines 1), tends to decrease during the first half of the time, but sharply increases during the second half of the time. This indicates the presence of stable correlated noise in the signal, the action of which is localized in the second half of the data registration time. It should follow that the impedance obtained from only the first half of the signals should have better characteristics than the impedance obtained from the complete signals. To verify this statement, we performed calculations using all considered algorithms. The results are shown in Fig. 5. With the exception of the dead frequency range (1 … 10 Hz), in which the quality of the impedance estimates practically did not change, the variance and smoothness of the estimates have even improved.
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Fig. 4 Dependence of the integral quality index on time when calculating ρxy (1) and ρyx (2) for point-1 a and point-2 b using the LSM (left), Robust (center), Interval (right) algorithms
Fig. 5 Absolute impedance a and its phase b at point-2 using Interval method (left: full time data, right: half time data)
In the process of registration of magnetotelluric signals, the variance of obtained estimates of the components of the impedance tensor decreases, and an increasing amount of data provides a decrease in confidence intervals. Correlated interference gives a bias in the estimates, and the magnitude of the bias can exceed the width of the confidence interval. During recording signals, two trends take place: 1. The bias of estimates relative to the desired true values caused by uncorrelated interference and noise decreases. Confidence intervals are reduced. 2. The relative discrepancy between neighboring confidence intervals may increase. The reduction of confidence intervals may not contribute to an increase in information about the impedance and characteristics of the geological section.
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A general rule for assessing the sufficiency of data: if a decrease in the variance of impedance estimates does not lead to a decrease in the Q index, but, on the contrary, to its further increase, this indicates that the information contained at the corresponding frequencies of the magnetotelluric signal describes not a geological section, but correlated noises. In this case, the decision could be made to stop registration data. We have considered the first variant of the impedance calculation algorithm using interval analysis methods. Interval analysis offers a more flexible apparatus because, in the absence of statistical robustness, it should not guarantee localization of the true value within any confidence interval. Interval analysis has an apparatus for regularizing solutions. In cases where the impedance estimates are biased locally (due to the effect of correlated noise on MT signals), it is relatively easy to increase the uncertainties in the raw data, leading to the broadening of interval solutions.
4 Conclusions In this work, we have obtained the results that indicate the possibility of application of interval methods when calculating the impedance tensor. In addition, we have proposed the coefficient of physical matching and the integral quality index, which describe in what degree the resulting interval solutions are consistent with each other. The dynamics of the integral quality index may indicate the termination of obtaining additional information about the geoelectric section, and convergence of this index can be used to recommend the termination of data collection. The use of interval analysis for the processing of magnetotelluric data poses a number of new research problems: how to form intervals correctly, using for this an estimate of the relative noise level in electric and magnetic channels; how to perform adaptive regularization using the principle of physical limitations; how to use interval analysis to solve the inversion problem.
References 1. Berdichevsky MN, Dmitriev VI (2009) Models and methods of magnetotellurics. Springer, Berlin. https://doi.org/10.1007/978-3-540-77814-1 2. Zhdanov MS (2009) Geophysical electromagnetic theory and methods. Elsevier, Salt Lake City. https://doi.org/10.1016/S0076-6895(09)70001-0 3. Chave AD, Jones AG (2012) The magnetotelluric method: theory and practice. Cambridge University Press, New York. https://doi.org/10.1017/CBO9781139020138 4. Chen H, Guo R, Dong H, Wang Y, Li J (2020) Comparison of stable maximum likelihood estimator with traditional robust estimator in magnetotelluric impedance estimation. J Appl Geoph 177:104046. https://doi.org/10.1016/j.jappgeo.2020.104046 5. Smirnov MY, Egbert GD (2012) Robust principal component analysis of electromagnetic arrays with missing data. Geophys J Int 190:1423. https://doi.org/10.1111/j.1365-246X.2012.05569.x 6. Garcia X, Jones AG (2008) Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform. Geoph 73:223. https://doi.org/10.1190/1.2987375
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7. Li G, Liu X, Tang J, Deng J, Hu S, Zhou C, Chen C, Tang W (2020) Improved shift-invariant sparse coding for noise attenuation of magnetotelluric data. Earth Planets Space 72:45. https:// doi.org/10.1186/s40623-020-01173-7 8. Escalas M, Queralt P, Ledo J, Marcuello A (2013) Polarisation analysis of magnetotelluric time series using a wavelet-based scheme: a method for detection and characterisation of cultural noise sources. Phys Earth Planet Inter 218:31. https://doi.org/10.1016/j.pepi.2013.02.006 9. Chave AD (2017) Estimation of the magnetotelluric response function: the path from robust estimation to a stable maximum likelihood estimator. Surv Geophys 38:837. https://doi.org/ 10.1007/s10712-017-9422-6 10. Prieto GA, Parker RL, Thomson DJ, Vernon FL, Graham RL (2007) Reducing the bias of multitaper spectrum estimates. Geophys J Int 171:1269. https://doi.org/10.1111/j.1365-246X. 2007.03592.x 11. Moore RE, Kearfott RB, Cloud MJ (2009) Introduction to interval analysis, vol 213. https:// doi.org/10.1137/1.9780898717716 12. Lavrukhin AA, Tukanova AS (2021) Interval approach to magnetotelluric data processing, J Phys Conf Ser 2096:012127. https://doi.org/10.1088/1742-6596/2096/1/012127 13. Imamura N, Schultz A (2020) Quality estimation of magnetotelluric impedance tensors using neural networks. Lead Edge 39:702–710. https://doi.org/10.1190/tle39100702.1 14. Nocelo Sampedro P (2021) Processing of magnetotelluric data using machine learning techniques. Dipòsit Digital de la Universitat de Barcelona. http://diposit.ub.edu/dspace/handle/ 2445/180406 15. Horacek J, Hladik M (2013) Computing enclosures of overdetermined interval linear systems. Reliable Comput 19(2). https://interval.louisiana.edu/reliable-computing-journal/volume-19/ reliable-computing-19-pp-142-155.pdf 16. Shary SP (2020) Weak and strong compatibility in data fitting problems under interval uncertainty. Adv Data Sci Adapt Anal 12(1):2050002. https://doi.org/10.1142/S2424922X205 00023 17. Shary SP (2017) Strong compatibility in data fitting problem under interval data uncertainty. J Comput Technol 22(2):150. https://doi.org/10.14529/mmph170105 18. Lavrukhin AA, Lobov KV, Tukanova AS, Onufriev AS (2020) Search for the optimal method for obtaining estimations for an automated magnetotelluric signal processing system. J Phys Conf Ser 1791:012102. https://doi.org/10.1088/1742-6596/1791/1/012102
Control Method for Mainline Freight Electric Locomotives with the Possibility of Adjusting Movement Modes Stanislav Istomin , Artem Perestenko , and Sergey Shantarenko
Abstract The article formulates the relevance of the development of methods for increasing the efficiency of using mainline freight electric locomotives by reducing electricity losses by improving on-board driving systems and decision support through the use of intelligent systems for generating optimal operating modes. As a parameter under study, when solving the problem of predicting the recommended operating mode of an electric locomotive, the setting of the traction force was adopted, since it has a significant effect on the amount of electrical energy consumption, determines the nature of the locomotive movement and is not tied to the design features of a particular series of electric locomotives. To solve this problem, long short-term memory (LSTM) networks were chosen. This network architecture is insensitive to time gaps between events, which allows them to be used in tasks where long-term and delayed effects must be taken into account. This property is achieved by isolating two feedbacks: the hidden state and the cell state, and adding gates to control them. As a result, a tuned artificial recurrent neural network was obtained, which allows calculating the traction force settings for the next 10 s based on the data on the locomotive operation over the last 30 s. Keywords Energy efficiency · Electric locomotives · Adaptive control of electricity · Electricity metering systems · Electricity rationing systems
1 Introduction JSC Russian Railways is one of the largest consumers of electrical energy in Russia, annually consuming about 5% of all electricity produced in the country. In turn, the share of electricity consumed for traction of trains is about 90% of the total electricity consumed by the company. Thus, the degree of efficiency in the use of electric energy for train traction has a key effect on the amount of the company’s S. Istomin (B) · A. Perestenko · S. Shantarenko Omsk State Transport University, 35, Marksa pr, Omsk 644046, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_52
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expenses for the purchase of fuel and energy resources and, if the trend remains unchanged, its importance will only grow over time. Long-term development program of the JSC Russian Railways until 2025, which is fully integrated with the Decrees of the President of the Russian Federation “On national goals and strategic objectives of the development of the Russian Federation for the period up to 2024”, “On the strategy of scientific and technological development of the Russian Federation” and “On the development of artificial intelligence in the Russian Federation” determines the need to increase the efficiency of the transportation process by improving the quality indicators of the use of rolling stock. It is planned to achieve this goal, including through the creation and implementation of dynamic traction control systems using artificial intelligence and the formation of end-to-end digital technologies for organizing the transportation process (“Digital Railroad”). The currently used methods for determining the energy-optimal sequences of control actions are based on preliminary calculations by analytical methods using simulation models [1–15]. These models operate only with information known before the start of the trip, almost without taking into account the rapidly changing traffic conditions, and are not flexible enough for their application in dynamic systems, including those operating in real time. Moreover, since these methods in most cases are applied to the analysis of the entire trip as a whole, giving feedback to the driver directly during the trip is in most cases impossible, which leads to untimely and insufficient accuracy of the corrective actions generated to control the locomotive. Thus, the development of methods for increasing the efficiency of using mainline freight electric locomotives by reducing electricity losses by improving onboard automatic driving systems and supporting decision-making through the use of intelligent systems for generating optimal operating modes is relevant.
2 Materials and Methods In general, the data from the on-board automatic driving systems RDPA are the matrix X , which describes the process of operating the locomotive as a sequential change in n states, each of which is determined by m parameters (features): ⎛
x11 · · · ⎜ .. . . X =⎝ . . xn1
···
⎞ x1m .. ⎟, . ⎠
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xnm
where x is the parameter value. This matrix can also be represented as a multidimensional time series, where each index t corresponds to a vector of parameters of dimension m: X = (X t : t ∈ T ) = (x1 , x2 , . . . , xn ),
(2)
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where x is vector of parameter values with dimension m; t is index of the set of dimensions; T is index set, T = {1, 2, . . . , n}. In this case, the task of processing data on the parameters of the movement of an electric locomotive can be reduced to the task of predicting the recommended operating mode of an electric locomotive y, described by m p parameters, for subsequent n p steps, based on known data from on-board systems x, described by m h parameters and containing n p measurements, i.e. samples from time series X. The setting of the traction force is taken as the parameters y y, since it has a significant effect on the amount of electrical energy consumption, determines the nature of the train movement and is not tied to the design features of a particular series of electric locomotives. Time series predicting problems can be solved by several methods. The most promising is the use of artificial recurrent neural networks (ARNN). Unlike feedforward networks, in which the input parameters are considered independent, ARNN can consider the input data as part of a sequence and are able to take into account not only the values themselves, but also their order. Classical RNNs acquire these properties due to the mechanism of short-term memory, implemented by adding feedback to the neurons of the hidden layer. The work of this type of networks is schematically shown in Fig. 1a. RNN networks can be represented as feedforward networks by means of the “sweep” operation schematically shown in Fig. 1b. In this case, the type and dimension of the RNN input does not have to coincide with the type and dimension of the output. Simple ARNN consider later data to be more significant, which is why the early data quickly cease to be taken into account by the model. This problem is called the problem of long-term dependencies and is a special case of the damped gradient problem. In cases where significant information can be sufficiently far removed from each other in a sequence or separated by unequal time intervals, this property can lead to the impossibility of obtaining a sufficiently high accuracy of predictions on this type of ARNN.
Fig. 1 Scheme of ARNN operation a “folded” view, b “expanded” view
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Fig. 2 Simplified diagram of the ANN learning process
Long short-term memory (LSTM) networks have been developed to solve this problem. This network architecture is insensitive to time gaps between events, which allows them to be used in tasks where long-term and delayed effects must be taken into account. This property is achieved by isolating two feedbacks: the hidden state and the cell state, and adding gates that control them. To train the model, from the time series describing the trip by the sliding window method, a set of training examples S is formed, each of which is a pair x, y. To form x and y, a slice of the time series X with a width w is made from it and a sequential sampling of measurements is made from it, after which the window is shifted by an amount d and the next training example is formed. This operation is repeated until the required number of examples is reached, or until the measurements are exhausted. A simplified diagram of this process is shown in Fig. 2. The scheme and algorithm for forming a set of training examples from a time series describing one trip is shown in Fig. 3.
3 Results Before searching for the optimal parameters of the ARNN, it is necessary to fix the sets of input and output features, the numbers of analyzed n h and projected n p time steps, the dimension of the hidden layer vector kh . At the moment, there are no analytical methods for determining the features necessary and sufficient for the assigned task. The problem of assessing the significance of the registered features is also nontrivial. Additional complicating factors are the stochasticity of the learning process and a strong dependence on the dataset used. The optimal set of features can be determined by a complete enumeration of all combinations of available features, which in the case of a large number of them becomes a very resource-intensive task. An alternative is the use of heuristic methods
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Fig. 3 Scheme of the formation of training examples a – a simplified scheme of passage by a sliding window, b – a scheme for sampling measurements from a time series
that allow one to determine a variety of features that provide satisfactory, but probably not the maximum possible accuracy of the model. Some of the most common approaches of this type are: • expert selection based on theoretical provisions; • using the least correlated subset of features; • sequential exclusion from the available set of features of those that lead to the smallest decrease in the accuracy of the model; • sequential inclusion in the initially empty set of those available features that lead to the greatest increase in the accuracy of the model. Due to the lack of standardized processes for registering, processing and storing data on the transportation process, the differences between the recorders of traffic parameters, the available and, therefore, the optimal set of features will generally be different. Despite the much greater prevalence of the onboard system for registering motion parameters MSUL-RPM, this system does not register a set of parameters essential for solving the problem, therefore, in this section and further, the RPDA G system will be considered. The traction force F realized on the trolley generalizes the traction and braking forces.
F = F[F > 0] − B[B > 0], where [ ] is the Iverson bracket. Let us form a set of training features: • exclude all non-quantitative features: the distance travelled from the beginning of the trip, the time elapsed since the beginning of the trip, and the length of the
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track profile element as having no theoretically substantiated connection with the predicted feature; exclude the mass of the train and the number of cars, since a significant spread in the values of these values is excluded due to the additional restrictions introduced earlier on the mass of the train and the axle load; exclude the pressure in the brake mainline and the pressure in the surge tank due to a close to zero correlation with the predicted sign (0.6% and 1.6%, respectively); exclude the armature current and the excitation current, since these values depend on the traction forse setting and are too dependent on the design features of a particular series of electric locomotives; replace the velocity limits with the maximum allowed velocity: vmaxt = min vtc , vtt , v d
where v c , v t is respectively constant and temporary velocity limits; v d is maximum design velocity. Since the slope of the track profile element and the maximum allowable velocity are known in advance, the model can be provided not with the current values of these features, but with values from the near future to ensure that future changes can be taken into account. The value of the time step shift for these values is taken equal to n h , that is, the model will have access to the value of these features in the following n h seconds from the moment of prediction. To prevent overfitting, the travel set used was randomly divided into three samples: • training (70%), used to correct the internal parameters of the ARNN; • test (20%), used to assess the quality of the ARNN prediction; • control (10%), used for the final assessment of the model and check the adequacy of predictions. Trips from this sample are not used in the training process.
The accuracy of determining F was approximately estimated at various values of n h and n p by training for three epochs on the first 1000 packets containing 64 examples from the training sample. Values of standard deviations of normalized predictions from true values for the entire test sample are presented in Fig. 4. Since at values of n p over 10, the accuracy is significantly reduced, we take n p = 10. For this value, large values of n h do not lead to an increase in the accuracy of the model, but they reduce the number of training examples and increase the computational complexity, so we take n h = 30. As a result, a tuned ARNN was obtained, which allows calculating the traction force settings for the next 10 s according to the data on the locomotive operation for the last 30 s. The locomotive control algorithm using the recommended values of the settings for traction and braking forces is shown in Fig. 5.
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Fig. 4 Loss on control samples at different values of n h and n p
Fig. 5 Algorithm for adjusting driving modes taking into account the current conditions
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4 Conclusions As a result of the research, a mathematical model was formed that, based on the data on the last 30 s of the locomotive’s operation, gives the recommended values of the traction and braking force settings for the next 10 s, taking into account the track profile and velocity limits. It is proposed to transfer these values to the microprocessor control system of the electric locomotive, which, in turn, can form and issue operating recommendations to the control panel, and independently correct the specified control actions. It should be noted that an increase in the accuracy of the method is possible with an increase in the amount of available data, since the algorithm is able to learn on a wider range of train situations and improve the quality of generalization of the practices of operating electric locomotives used in the best trips. The obtained algorithm for processing data on the parameters of the movement of an electric locomotive makes it possible to calculate the values of the settings of the traction force, ensuring an increase in the efficiency of its use, according to the data of on-board systems using artificial intelligence methods. The developed method for controlling mainline freight electric locomotives allows, on the basis of the recommended values of the traction force settings, to correct the locomotive movement modes, taking into account the existing train conditions to increase the operational indicators and the efficiency of the locomotive use. Acknowledgements «The reported study was funded by RFBR, project number 19-38-90140\19».
References 1. Albrecht AR, Howlett PG, Pudney PJ, Vu X (2013) Energy-efficient train control: From local convexity to global optimization and uniqueness. Automatica 49(10):3072–3078. https://doi. org/10.1016/j.automatica.2013.07.008 2. Behmann U (2015) Energy-saving driving in an area of conflict between informatics and reality 113:578-583 3. Bart Van der Spiegel (2009) Railway energy measuring. managing and billing. In: 2009 6th international conference on the european energy market, pp 1–8. https://doi.org/10.1109/EEM. 2009.5207111 4. Bécsi T, Aradi S (2017) Energy saving possibilities at the hungarian state railways. Transp Res Procedia 27:617–623. https://doi.org/10.1016/j.trpro.2017.12.054 5. Carvajal-Carreño W, Cucala AP, Fernández-Cardador A (2014) Optimal design of energyefficient ATO CBTC driving for metro lines based on NSGA-II with fuzzy parameters. Eng Appl Artif Intell 36:164–177. https://doi.org/10.1016/j.engappai.2014.07.019 6. Cheremisin V, Istomin S, Perestenko A (2020) Artificial intelligence methods to control the energy efficiency of electric rolling stock online. E3S Web Conf 175:05046. https://doi.org/10. 1051/e3sconf/20201750504 7. Cuéllar M, Delgado M, Pegalajar M (2007) An application of non-linear programming to .train recurrent neural networks in time series prediction problems. In: Enterprise information systems VII. Springer, Dordrecht, pp 95–102. https://doi.org/10.1007/978-1-4020-5347-4_11
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8. Ding Y, Bai Y, Liu F-M, Mao B-H (2009) Simulation algorithm for energy-efficient train control under moving block system. In: 2009 WRI world congress on computer science and information engineering, pp 498–502. https://doi.org/10.1109/CSIE.2009.323 9. Montrone T, Pellegrini P, Nobili P (2018) Real-time energy consumption minimization in railway networks. Transp Res Part D: Transp Environ 65:524–539. https://doi.org/10.1016/j. trd.2018.09.018 10. Montrone T, Pellegrini P, Nobili P (2017) Energy consumption minimization problem in a railway network. Transp Res Procedia 22:85–94. https://doi.org/10.1016/j.trpro.2017.03.013 11. Fatemeh N, Horst S, Udayan K et al (2017) Learning feature engineering for classification. In: Proceedings of the twenty-sixth international joint conference on artificial intelligence main track, pp 2529–2535. https://doi.org/10.24963/ijcai.2017/352 12. Sanchis IV, Zuriaga PS (2016) An energy-efficient metro speed profiles for energy savings: application to the valencia metro. Transp Res Procedia 18:226–233. https://doi.org/10.1016/j. trpro.2016.12.031 13. Scheepmaker GM, Goverde RMP, Kroon LG (2017) Review of energy-efficient train control and timetabling. Eur J Oper Res 257(2):355–376. https://doi.org/10.1016/j.ejor.2016.09.044 14. Yeh AB (2007) A modern introduction to probability and statistics. Technometrics 49(3):359. https://doi.org/10.1198/tech.2007.s502 15. Zhang S, Wu Y, Che T, Lin Z et al (2016) Architectural complexity measures of recurrent neural networks. In: Advances in Neural Information Processing Systems, pp 1830–1838. http://arxiv. org/abs/1602.08210
Modeling the Management of an Economic System Based on Random Processes Elena Schislyaeva , Natalia Vasileva , Vladimir Grigoriev-Golubev , Irina Evgrafova , and Vladimir Belopolsky
Abstract The article examines the algorithm for constructing a mathematical model of the functioning of the economic system, if its activity or one of the activities is associated with the flow of applications, which is random. In this case, it is possible to model the operation of such a system as a sequence of operations developing in the form of a Markov random process and apply the mathematical apparatus of the theory of random processes to study the effectiveness of its operation. It is shown how the constructed mathematical model makes it possible to predict costs and profits in the process of functioning of the system, on the basis of which the optimal decision can be made. An example is the task of estimating the costs of a TELECOM operator associated with training new employees in its branches in two training formats: full-time and distance learning. Keywords Random process · Mathematical model · Mathematical expectation · Costs · Cash flow · Digital platform · Distance learning
1 Introduction The modern theory of the study of the activity of economic systems and the adoption of management decisions based on this study is based on the methods and models of mathematics, the theory of probability, statistics and econometrics. The development and practical use of mathematical models of economic systems make it possible to predict and adjust the future system before it is paid for and physically implemented. In this regard, the purpose of modeling is the application of mathematical methods and the use of modern computing technology for the most effective solution of problems arising in the field of economics. All operations in the economic system that need to be analyzed when choosing the optimal solution take place in time and space and are random. It is necessary to E. Schislyaeva · N. Vasileva (B) · V. Grigoriev-Golubev · I. Evgrafova · V. Belopolsky State Marine Technical University, (SMTU), 190121, Lotsmanskaya Ulitsa, 3, St. Petersburg, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_53
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take into account or not take into account the randomness of the process depending on the purpose of the study and on how significant the influence of random factors on the functioning of the system is. If it is necessary to take into account the randomness of the process, then mathematical modeling is carried out on the basis of the theory of random processes, and numerical parameters that characterize the efficiency of the system are calculated on its basis. Any random process taking place in an economic system is a transition from one state of the system to another. The number of such states, as a rule, is finite. If the transition of the system from one state to another is carried out on the basis of a random flow of requests coming from clients, and if the flow of requests is Poisson, i.e. ordinary with independent increments, then the functioning of the system is a Markov random process. Since in reality any economic system is dynamic, it is advisable to describe its functioning as a Markov process with a finite number of states and with continuous time (continuous Markov chain). The use of Markov random processes in economics is described in detail in [1], where the finite-difference Kolmogorov equations are obtained and the Laplace transform is used to solve them. In [2, 3], a Markov model of the evolution of an economic system with discrete states and continuous time is constructed, where the Kolmogorov equations are solved for the stationary case, i.e. the final probabilities are calculated, on the basis of which the discounted income is calculated. In [4], a mathematical description of the dynamics of the ups and downs of economic activity is carried out on the basis of a mathematical model of the Markov random birth–death process. In this paper, we propose an algorithm for managing the costs of such an economic system as a TELECOM operator, associated with training new employees in its branches located in various cities of the Russian Federation, based on a Markov random process, where the exact solution of the Kolmogorov equations is found, as a result of which the cost function is calculated as a function of time t.
2 Materials and Methods Let S be some economic system with a finite number of possible states S1 , S2 , ..., Sn , which randomly at some point in time t ∈ T (T —observation time) goes from one state to another. We will assume that all transitions of the system from state Si to state S j at the moment of time t are independent and occur under the influence of the simplest Poisson flow of events with intensity λi j (t). In this case, the functioning of the system is a Markov random process in which the conditional probability pi j (k) that at the k -th time step, the system will be in state S j , provided that at the (k − 1)-th time step, it was in state Si , does not depend on the state of the system at earlier time steps [1]. If the moments of transition of the system from state Si to state S j are random, then the Markov random process is a random process with continuous time. In this case, the vector of state probabilities
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p(t) = ( p1 (t) p2 (t) ... pn (t))T determines the probabilities of states of system S in the moment of time t ∈ T . Let the transition probability densities λi j (t) and λ ji (t) be determined for each pair of possible states Si and S j . Then the probabilities of the states of the system pk (t) satisfy the system of Kolmogorov equations [1]: n dp(t) n = λik (t) · pi (t) − pk (t) · i = 1 i = 1 λki (t), k = 1, 2, ..., n (1) dt i = k i = k Which is redundant. Therefore, any equation of the system can be replaced by the obvious equality nk=1 pk (t) = 1, t ∈ T . If we introduce the matrix. ⎞ λ∗11 (t) λ21 (t) ... λn1 (t) ⎜ λ12 (t) λ∗ (t) ... λn2 (t) ⎟ 22 ⎟, (t) = ⎜ ⎝ ... ... ... ... ⎠ λ12 (t) λ2n (t) ... λ∗nn (t) ⎛
(2)
In which the diagonal elements are determined by the formula λ∗kk (t) = − n λki (t), k = 1, 2, ..., n, then system (1) can be written in matrix form. i =1 i = k dp(t) = (t) · p(t) dt
(3)
where p(t) = ( p1 (t) p2 (t) ... pn (t))T —vector of probabilities of the states of the system at the moment of time t. The system of ordinary differential Eqs. (1) or in matrix form (3) is solved by setting the initial conditions p(0) = p 0 =
0 0 T p1 p2 ... pn0 , determining the state of the system at a moment of time t = 0, i.e. solve the Cauchy problem in the form dp(t) dt
= (t) · p(t), p(0) = p 0 .
(4)
If the elements of matrix (t) are continuous for t > 0, then the Cauchy problem (4) has a unique solution and, therefore, the vector of probabilities of the states of the system is uniquely determined at any moment of time t > 0. A scalar Markov process with discrete states and continuous time is called homogeneous if the transition probability densities are constant, i.e. λi j (t) = λi j = const, i, j = 1, 2, ..., n, t ∈ T . When studying homogeneous Markov processes with discrete states, the important question is whether it becomes stationary over time, i.e. the system randomly passes from one state to another, but the probabilities with
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which it is in each possible state do not depend on time. In this case, the vector of state probabilities is constant p = ( p1 p2 ... pn )T and is called the vector of limiting probabilities. The vector of limiting probabilities p = ( p1 p2 ... pn )T is determined from the system
· p = 0, n . i=1 pi = 1,
(5)
⎛
⎞ λ∗11 λ21 ... λn1 ⎜ λ12 λ∗ ... λn2 ⎟ ∗ n 22 ⎟ where matrix = ⎜ ⎝ ... ... ... ... ⎠, λkk = − i = 1 λki , k = 1, 2, ..., n. i = k λ1n λ2n ... λ∗nn If the number of states of the system is finite and the system is ergodic, i.e. all states are reachable and all flows of events generating system transitions from state to state are simplest, then there are final probabilities of states (independent of either time or the initial state of the system). Note that if a system with a finite number of states, in which a homogeneous Markov process with continuous time occurs, is not ergodic, then there are still limit probabilities for it, but they depend on the initial probability distribution.
3 Results Let one of the directions of the functioning of some model economic system, which has five branches in the cities of the Russian Federation, be the training of new employees of the branches, which is caused by the process of their expansion, as well as a high turnover of personnel. Requests from branch offices for training courses are sporadic, and costs are associated with travel, hotel bills, and travel allowances for staff traveling to organize training. The company’s management was tasked with assessing the costs associated with this activity and making an effective decision: to continue training new employees of the branches in the same format or, by investing some funds, to conduct training in the on-line system. The described direction of the system functioning can be pictured in the form of a labeled graph (Fig. 1). The Markov process describing the operation of the system is assumed to be homogeneous, and the densities of transition probability λi j (t) = const are set on the basis of long-term statistical data and are mainly determined by the number of personnel and their predicted increase.
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Fig. 1 System state graph
0.1
0.2
S2
0.1
0.1 0.4 0.2 0.1
S1
0. 1
0.2
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S3
S4
S5
S6
Vector of limiting probabilities p = (0, 117647, 0.235294, 0, 117647, 0.235294, 0, 117647, 0.176471)T is defined as a solution to system (5) written in the form of a matrix equation A· p = B, where. ⎛ ⎞ ⎛ ⎞ −1.1 0.1 0.1 0.2 0.1 0.2 0 ⎜ 0.2 −0.1 0 ⎟ 0 0 0 ⎟ ⎜ 0 ⎟ ⎜ ⎜ ⎟ ⎜ 0.1 0 −0.1 0 0 0 ⎟ ⎜ ⎟ ⎜ ⎟ ⎜ 0 ⎟ ⎜ ⎟ (6) A = ⎜ 0.4 0 0 −0.2 0 0 ⎟, B = ⎜ ⎟, ⎜ 0 ⎟ ⎜ ⎟ ⎜ ⎟ ⎜ 0.1 0 ⎟ 0 0 −0.1 0 ⎜ ⎟ ⎝ 0 ⎠ ⎝ 0.3 0 0 0 0 −0.2 ⎠ 1 1 1 1 1 1 1 In the Mathematica (Wolfram) mathematical package through the function Linear Solve[ A, B]. It should be noted that this system has been redefined. The first 6 rows of matrix A contain the elements of matrix calculated by the state graph (Fig. 1) and the formula λ∗kk = − n λki , k = 1, 2, ..., n. The last line i =1 i = k consists of ones, i.e. the Linear Solve function 6 finds a solution to a homogeneous pi = 1. system · p = 0 that satisfies condition i=1 The resulting distribution of limiting probabilities makes it possible to estimate the costs required for training new employees. In Table 1, pk —the probability that the system is in state Sk , xk —the projected costs for the k—th trip in conventional units. If the values of λi j are related to one calendar month, then the calculated mathe matical expectation M[X ] = 6k=1 xk pk = 60 makes it possible to obtain the value of costs per year, i.e. the value of costs m(t) = 60 · 12 = 720 c. u. (thousand rubles) at t = 12.
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Table 1 A series of cost allocations by full-time study S1
S2
S3
S4
S5
S6
pk
0.117647
0.235294
0.117647
0.235294
0.117647
0.176471
xk
0
60
60
75
60
80
Table 2 A series of cost allocations by distance study S1
S2
S3
S4
S5
S6
pk
0.117647
0.235294
0.117647
0.235294
0.117647
0.176471
xk
0
15
15
15
15
15
If the training takes place in a remote format, and the corresponding on-line platform is already debugged, then the amount of costs is significantly less and is determined from Table 2: In this case, the cash flow of costs is determined through the mathematical expec6 tation M[X ] = k=1 x k pk = 13.2354 in one month, and in a year: m(t) = 13.235 · 12 = 158.824 ≈ 159 c.u. at t = 12. With this form of learning, the cost xk is the cost of maintaining the digital platform.
4 Discussion The calculated cash flow of costs for the year corresponds to the operation of the economic system in a stationary mode, which can be assumed only for a limited time interval [1, 5]. Moreover, calculating the cash flows of costs/profits, it is impossible to control the operation of the system, achieving its efficiency. To do this, you need to be able to calculate cash flows for any period of time, i.e. you need to know the probability distribution at any time t, and this, in turn, leads to the need to obtain an exact solution to the Kolmogorov system of Eqs. (4). As an example, let us find the costs of the considered model economic system as a function of time in order to estimate how long it takes to pay off the investment in the development of a digital platform for training new employees in a remote format. Since the Kolmogorov equations have infinitely many solutions, including zero solutions, we replace the first equation in Eqs. (4) with the 6 normalization condition 6 i=1 pi (t) = 1, from which we express p1 (t) = 1 − i=2 pi (t) and substitute it into the rest of the equations. We will obtain the following system. dpi (t) dt
= λ˜ i, j · pi (t) + f i , i, j = 2, ..., 6,
(7)
where f i —elements of vector F = (0, 2; 0, 1; 0, 4; 0, 1; 0, 3)T , λ˜ i, j —elements of matrix
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⎛
−0.3 ⎜ −0.1 ⎜ ˜ =⎜ ⎜ −0.4 ⎜ ⎝ −0.1 −0.3
−0.2 −0.2 −0.4 −0.1 −0.3
−0.2 −0.1 −0.6 −0.1 −0.3
539
−0.2 −0.1 −0.4 −0.2 −0.3
⎞ −0.2 −0.1 ⎟ ⎟ ⎟ −0.4 ⎟. ⎟ −0.1 ⎠ −0.5
(8)
The initial condition for system (7) will be zero. p(0) = p 0 = (0, 0, 0, 0, 0)T .
(9)
If p(t) = ( p2 (t), p3 (t), p4 (t), p5 (t), p6 (t))T —the exact solution of the Cauchy problem (7), (9) at the moment of time t, then the cash flow of costs m(t) can be calculated by the formula. m(t) =
6 i=2
xi · pi (t),
(10)
where xi —projected cash flow corresponding to i—the state of the system. The solution to system (7) with initial condition (9) can be obtained analytically, which will be very cumbersome due to the sufficiently high order of the system. Moreover, some eigenvalues of the system matrix can be multiples, which complicates the solution. Taking into account these difficulties, the system was solved in the Mathematica package through the Jordan form of the matrix of the system, as described in [6–8]. ˜ and the By defining the Jordan (quasi-diagonal) form A J of the system matrix Jordan basis—matrix S of transformation from the original basis to the canonical one, through the built-in function of the Jordan Decomposition [] layout, it is possible ˜ to calculate the matrix exponent of matrix : ˜
et = S · e A J t · S −1
(11)
And, using the Lagrange method, seek a solution to the inhomogeneous system (7) in the form (4): ˜
˜
p(t) = et · p(0) + ∫t0 e(t−τ ) · (τ )dτ or p(t) = pc(t) · C + p1(t),
(12)
where pc(t) = S · e A J t , C = (c2 , c3 , c4 , c5 , c6 )T —vector of arbitrary constants, pc(t) · C—general solution of a homogeneous system, p1(t) = pc(t) · ∫ pc−1 (t) · Fdt—particular solution of an inhomogeneous system. The matrix exponent (11) for matrix (8) is calculated in the package of Mathematica using the Jordan form.
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⎞ e−1,26569t 0 0 0 0 ⎜ 0 0 0 ⎟ 0 e−0,2t ⎟ ⎜ ⎟ ⎜ =⎜ 0 ⎟, 0 0 e−0,134315t 0 ⎟ ⎜ ⎝ 0 0 0 e−0,1t 0 ⎠ 0 0 0 0 e−0,1t ⎛
˜
et
and the solution p(t) of system (8), is determined by formula (12) using the Linear Solve function of Mathematica. ⎛ ⎞ 0, 235 − 0, 148e−0,265t − 0, 086e−0,134t ⎜ 0, 117 − 0, 074e−0,265t − 0, 043e−0,134t ⎟ ⎜ ⎟ ⎜ ⎟ p(t) = ⎜ 0, 235 − 0, 326e−0,265t − 0, 090e−0,134t ⎟. ⎜ ⎟ ⎝ 0, 117 − 0, 074e−0,265t − 0, 043e−0,134t ⎠ 0, 176 − 0, 244e−0,265t − 0, 068e−0,134t The vector of arbitrary constants C was defined as a solution to the system. pc(0) · C = p 0 − p1(0). The cash flow of costs m(t) was calculated using the formula m(t) =
6 i=2
xi pi (t) = 60 − 61, 819e−1,265t + 1, 819e−0,134t ,
(13)
And the predicted cost flows for each state were selected from Table 1: X = (60, 60, 75, 60, 80)T . The calculated cash flow of costs for the year, calculated by formula (13) as expected, turns out to be less than that calculated for the stationary regime (Table 1).
12 −1,265t + 1, 819e−0,134t dt = 682, 002. pol = ∫12 0 m(t)dt = ∫0 60 − 61, 819e Figure 2 shows a graph of the costs of an economic system, from which it can be seen that a random process quickly becomes stationary. The obtained costs of the economic system for educational activities in the form of a function m(t) make it possible to estimate these costs for any time interval in Fig. 2 Graph of costs of the economic system for educational activities
60 50 40 30 20 10 2
4
6
8
10 12 14
t
Modeling the Management of an Economic System … Fig. 3 Cost graphs for face-to-face and distance learning
541 800 600 400 200 2
4
6
8
10
12
14
t
the form of a cash flow ∫t0 m(ξ )dξ . Suppose that the company’s management makes a managerial decision: having invested money in the amount of annual expenses on educational activities, develop a digital platform with elements of virtual reality for the implementation of distance learning. To find out the time interval during which the investment will pay off, the corresponding cost function is calculated, determined by the formula: mm1(t) = 800 − ∫t0 m(ξ )dξ + a,
(14)
where ∫t0 m(ξ )dξ —amount of costs for a period of time [0, t], a = 13, 2—digital platform support costs. The cost function mm2(t) was calculated using the formula (14) as long as its value is greater than the costs determined by Table 2, the corresponding costs for distance learning, and was calculated according to Table 2, if the costs turned out to be less a = 13, 2, i.e. the random process has become stationary. The cost functions are shown graphically in Fig. 3: m[t]—costs for full-time training, mm2[t]—costs for distance learning. From Fig. 3 it is clear that the cost of creating a digital platform pays off in about t = 13. If t ≥ 13, the savings in monetary costs for educational activities of the system for the year is 561 conventional units.
5 Conclusion Modeling the functioning of an economic system in time in the form of a Markov random process creates a basis for predicting costs (profits) in its activities, for finding the optimal strategy for its development. The use of the Mathematica package in the calculations provides a powerful tool for assessing the parameters of the functioning of a dynamic system for any period of time and allows controlling its operation. As already mentioned, in reality, the stationary mode of operation of a dynamic system is possible only on limited time intervals. Therefore, it is especially important to use mathematical methods that make it possible to assess the parameters of the system at any time interval. The difference between this work and other works related to the construction of a probabilistic model is that using the Mathematica package, an exact solution of the Kolmogorov equations for a large-order system is obtained.
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The proposed algorithm for calculating the costs of activities of an economic system associated with random orders does not become more complicated if it is used for continuous Markov chains with a large number of states, as, for example, for large federal TELECOM operators included in the top four mobile operators of the Russian Federation and having about 50 branches across the country. Moreover, the proposed method for assessing the costs associated with the functioning of an economic system based on client requests or one of such areas of its activity can be used at the stage of management development, modeling a random process using Monte Carlo methods and implementing a so-called simulation model.
References 1. Sokolov GA, Chistyakova NA (2005) Probability theory. Controlled Markov chains in economics. Moscow, Fizmatlit, p 248 2. Grishina S (2015) The application of the theory of Markov processes to the study of dynamics of economic systems. Sci Res Dev Econ 3(3):14–18. https://doi.org/10.12737/11577 3. Schmidt AV, Churikin, VA (2015) Markov models of economic systems. J Vestnik SUSU Ser “Econ Manag” 9(3):100–105. https://doi.org/10.14529/em090314 4. Akaev AA (2007) Analysis of economic cycles using the mathematical model of the flow of random events. J Econ Math Methods 43(1):27–37. https://doi.org/10.1134/S10645624060 40247 5. Tsai ChW et al (2016) A multiple-state discrete-time Markov chain model for estimating suspended sediment concentrations in open channel flow. J Appl Math Model 40(23–24):10002– 10019 6. Volodicheva VV, Leora SN (2018) Study of graph isomorphism using jordan forms of adjacency matrices. J Appl Disc Math 40:87–99. https://doi.org/10.17223/20710410/40/7 7. Cardon DA, Tuckfield B (2011) The Jordan canonical form for a class of zero–one matrices. Linear Algebra Appl 435(11):2942–2954 8. Nina H, Soto RL, Cardoso DM (2013) The Jordan canonical form for a class of weighted directed graphs. Linear Algebra Appl 438(1):261–268
The Prospective Model of Organization of Freight Transportation on the North Caucasian Railway Range Viktor Zubkov , Nina Musienko , and Kirill Anoshkin
Abstract In connection with the development of international trade relations of Russia with the countries of Western Europe and East Asia, a further increase in the volume of export cargo transportation in the direction of the ports of the AzovBlack Sea basin (ABSB) is forecasted to 130 million tons. In the context of infrastructural restrictions on the North Caucasian Railway range, there is a risk of an increase in the number of freight trains temporarily suspended from traffic. This fact required an analysis of the carrying capacity of the route with heavy traffic Kotelnikovo—Tikhoretskaya—Kozyr’ki”yezd 9 km—Vyshesteblievskaya, through which the largest volume of export cargo is delivered to the ports of the basin and the development of measures aimed at improving the efficiency of operating the railway transport infrastructure. The main infrastructural restrictions on the carrying capacity on the considered direction will be removed by 2022, which will increase the carrying capacity to 154 train pairs per day. To pass the growing volume of traffic on the studied direction, an increase in the carrying capacity was considered due to an increase in weight norms when organizing the movement of heavy trains, which will create a reserve of the carrying capacity. This will make it possible to master the planned export cargo traffic to the ports of ABSB with a smaller number of trains, to use the locomotive fleet more efficiently, but this is possible with the implementation of reconstruction measures. Keywords Export transportation service · Prospective volumes · Infrastructural restrictions · The ways to increase the carrying capacity · Organization of heavy trains movement
V. Zubkov · N. Musienko (B) · K. Anoshkin Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Square, Rostov-on-Don 344038, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_54
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1 Introduction The real development of the market economy in Russia has fundamentally changed the geography of freight traffic on the southern range of the country’s railway network with its focus on the transportation of export cargo. In this regard, one of the main tasks assigned to the North Caucasian Railway (NCR) was to ensure the transshipment of export–import cargo from one mode of transport to another in the ports of the Azov-Black Sea basin (ABSB, Fig. 1). The problem of efficient organization of the transportation process on the road in the current conditions is multifaceted and requires the development of fundamentally new solutions. In this regard, we considered the issues of further solving infrastructure problems associated with the transportation of export cargo and the target task of improving the quality of service at the ports of ABSB. As it is known, today more than a third of Russia’s export freight traffic goes to the ports of ABSB. In connection with the development of international trade relations with the countries of Western Europe and East Asia, a further increase in the volume of export cargo transportation in this direction is forecasted, that causes significant problems due to the presence of infrastructure restrictions on the railway routes to the ports of ABSB. The data from the Institute for Economics and Transport Development (IEDT) predict an increase in volumes by the end of 2025 to the level of 130 million tons, and the ports are systematically preparing for this. The infrastructure of the ports of ABSB is constantly being modernized, modern, all-weather crane equipment is being introduced, its capacity is increasing and the carrying capacity of ships is increasing. The capacity of the Taman port for handling bulk cargo is increasing due to the introduction of modern bulk terminals [1–3].
mln. tons 30 25 20 15 10 5 0
Coal
26.5
26.8
23.5 22
26.9
Oil and oil products
24
Ferrous metals
21
21
11.3
11.5
11.5
12.5
Mineral construction cargo Mineral fertilizers
7.4
6.8
6.5
6.8
Grain cargo
2.7 2.5
2.6 2
2.7 2
2.7 2.3
Others
2018
2019
2020
2025
Years
Fig. 1 Forecasting the transportation volume of the main types of cargo by destination in the ports of the Azov-Black Sea basin
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2 Materials and Methods 2.1 Basic Organizational and Technical Measures to Increase the Carrying Capacity
0
109.2 83.4
97 36.4
79.9 6.4
49.1 31.8
41 32
43.5 39.9
51 34.9
32 33.1
50
45.2 45.2
68.5 86.2
100
93.3 99.4
150
101.1
N, trains
200
151.2
In these conditions, the analysis of the available carrying capacity, the development of measures aimed at increasing the efficiency of operation of the railway transport infrastructure, methods of organizing the transportation process, is a necessary tool for ensuring the sustainable functioning of the transport system to ensure the rhythmic supply of export cargo. Lack of reserves of the carrying capacity of railway lines leads to a temporary suspension behind the movement of freight trains, which in turn complicates management (Fig. 2). At present, at the approaches to the port and border stations on the North Caucasian Railway (NCR), on average, more than 100 “abandoned” trains are idle every day, waiting for the reception (the train set, which is set aside from traffic, stands without a locomotive on the siding of the station and it is secured by brake shoe holder), and at the transshipment stations themselves—about 1000 wagons awaiting for the transshipment of goods. The presence of the facts of suspension from the movement of trains is mainly caused by the failure to comply with technological standards for unloading by consignees due to the lack of containers because of unfavorable weather conditions, as well as because of the temporary placement of rolling stock on public tracks on the route to port stations. The share of trains set aside from the movement on the North Caucasus Railways, their distribution by stations of destination is shown in Fig. 3. As a result, railway transport suffers daily losses, according to the data of the North Caucasian Railways, in the amount of about 2.2 million rubles per day. The total losses due to suspension of trains include not only losses from deterioration in the operation of the wagon fleet, as a result of which the railways do not receive income
January
March
May
July 2018
September
November
2019
Fig. 2 The presence of trains suspended from the movement of the North Caucasus Railways on average per day for 12 months in 2018–2019
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Zarechnaya
Novorossiysk
Tuapse
Fig. 3 The share of trains suspended from the movement of the North Caucasus Railway and their distribution by stations
from transportation that could be performed by unproductively idle wagons, but also losses due to a decrease in the carrying capacity of sections, causing additional costs because of difficulties in train and shunting operations and the “lifting” of trains. An irregular and inconsistent supply of goods to transshipment points occurs due to the lack of a single transport conveyor, the disunity of types of ownership and the transport management system and other entities involved in the technological process of transporting goods. To ensure timely unloading at the port stations of the North Caucasian railway, it is necessary, along with timely supply, to ensure a high level of routing, as well as to comply with the network formation plan [4, 5]. In this regard, the ways of increasing the carrying capacity of the North Caucasus Railways sections are considered, they are subdivided into organizational, technical and reconstructive. The main organizational and technical measures include (Zubkov et al., 2019. Advanced technologies in railway transport: monograph, FSBEI VO RSTU) [6, 7]: • increasing the mass of trains based on the use of innovative carriages, modern train locomotives, installation of additional traction substations on electrified sections; • reduction of station and inter-train intervals at stations and track sides, limiting the carrying capacity of the section; • implementation of interval regulation of the movement of trains with moving block sections; • increasing the speed of freight trains; • changing the service schemes for intermediate stations by goods collecting trains. Methods for increasing carrying capacity and the sequence of measures implementation are formed for each direction, depending on local conditions, the specified size of traffic and the technical and economic efficiency of various options.
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2.2 The Analysis of the Carrying Capacity of the Heavy Direction Kotelnikovo—Tikhoretskaya—Kozyr’ki—Raz”yezd 9 km—Vyshestebliyevskaya To master the growing volume of traffic and achieve efficiency in operational work, an analysis of the carrying capacity was carried out on the example of the high traffic direction Kotelnikovo—Tikhoretskaya—Raz”yezd 9 km, through which the largest volume of export cargo is supplied to the ports of the basin. With the separation of passenger and freight flows in the near future, this direction will become predominantly freight. The final stage of the comprehensive reconstruction of the Kotelnikovo— Tikhoretskaya—Raz”yezd 9 km direction with a bypass of the Krasnodar junction is being implemented at the North Caucasian Railway range. Over the past 12 years since the start of the investment project, 554 km of second tracks have been put into operation. Until the completion of the entire complex of works, part of the infrastructure restrictions will be in effect. So, today the carrying capacity of the Sa’lsk—Tikhoretskaya section is limited by 44 train pairs, of which 26 are freight pairs. The limiting element is the singletrack section Yeya—Rovnoe—Poroshinskaya. On the Grechanaya—Raz”yezd 9 km section, the carrying capacity is 45 train pairs, of which 20 are freight pairs. The limiting element is the single-track section Sebedakhovo—Raz”yezd 9 km. In 2020, the commissioning of the second tracks with a total length of 49.4 km was completed. At present, 39 km of the second tracks on the track sides have already been put into operation: Starotitarovka—Vyshesteblievskaya (6.78 km), Yeya—Rovnoe (6.1 km), Rovnoe—Poroshinskaya (15.8 km), Protoka—Sebedakhovo (10, 33 km). In December, it is planned to complete the construction of the second track on the Sebedakhovo—Raz”yezd 9 km (10.4 km) section. During 2021, the final stage of the comprehensive reconstruction of the Kotelnikovo—Tikhoretskaya—Vyshesteblievskaya direction with a bypass of the Krasnodar junction is being implemented at the railway range. As a result of the implementation of the investment program, by the end of 2021 the carrying capacity will increase at the sites: • Salsk—Tikhoretskaya—up to 71 train pairs per day, of which 53 pairs of freight trains, • Kozyr’ki—Raz”yezd 9 km—Vyshestebliyevskaya up to 154 trains pairs, of which 123 pairs of freight trains. The limiting factor in passing the car traffic in 2021 will be single-track necks at the stations Yeya, Rovnoe, Poroshinskaya and the single-track section Tikhoretskaya— Kozyr’ki with the carrying capacity of 42 pairs of trains per day, of which 25 pairs of freight trains. In 2021, it is planned to commission second tracks on the Tikhoretskaya— Kozyr’ki section with a total length of 50.9 km, equip double-track necks at
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the stations Eya, Rovnoe, Poroshinskaya, and complete the reconstruction of Tikhoretskaya station. The implementation of the investment program in 2021 will increase the carrying capacity of the Kotelnikovo—Tikhoretskaya—Kozyr’ki—Raz”yezd 9 km—Vyshesteblievskaya direction to 154 train pairs per day, of which 123 are freight train pairs. Major infrastructure restrictions on carrying capacity will be lifted by 2022.
2.3 Calculation of Carrying Capacity in the Considered Direction With the unified weight norm of a train of 4500 tons adopted in this direction, for the development of the above cargo traffic, it is necessary to ensure the passage of freight trains in the amount calculated in accordance with the instructions for calculating the carrying capacity of railway lines. Nfr =
120 · 106 · 1, 1 V ·k = ≈ 121 train pair s, 365 · Q · ϕ 365 · 4, 5 · 103 · 2/3
(1)
where k—monthly coefficient of uneven traffic (k = 1,1); Q—gross train weight (Q = 4500 t); ϕ—the ratio of net and gross mass of train compositions (ϕ = 2/3). In addition to freight trains, passenger trains in the amount of 29 pairs of longdistance and local trains, three pairs of commuter trains and one pair of goods collecting trains will be passed along the investigated section. The average rate of removal of freight trains by passenger is calculated by the formula: t f r (1 − ) · 0.8 − 0.005 · n pass + 1.3, (2) ε pass = I where t f r —travel time of a freight train on a limiting range ( t f r = 18 min); —the ratio of the net travel time of a passenger (accelerated) train of this category, which has a higher speed than a freight train, and the travel time of a freight train on a calculated section ( = 0,77); n pass —a total number of passenger trains on the section (n pass = 31 trains); I—calculated inter-train interval on the section (I = 8 min). From here εeven/odd = pass
18 · (1 − 0, 77) · (0, 8 − 0, 005 · 31) + 1, 3 = 1, 63. 8
(3)
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The coefficient of the collection of the schedule lines by the combined train is determined by the number of serviced stations. The investigated section has 9 separate points, of which 5 stations are served by goods collecting train. When the goods collecting train stops at each station, the removal rate of the schedule line will be εas = 5. Then the required carrying capacity of the double-track section will be: Nr eq = N f r + N pass + Nas (εas − 1) · βr es , trains/day,
(4)
where Nas —a number of goods collecting trains, (Nas = 1); βr es —reserve of the section carrying capacity for a double-track section, (βr es = 1,1–1,15). Nr eq = [121 + 31 · 1, 63 + 1 · (5 − 1)] · 1, 1 = 193, 08 ≈ 193 train pair s. (5) According to the results obtained, the carrying capacity will not be enough to handle the growing volume of traffic, and this problem must be solved either by developing the infrastructure of the direction in question, or by reducing the number of trains based on increase in their weight norms.
2.4 Strengthening the Carrying Capacity of the Studied Direction One of the options for enhancing the carrying capacity of the studied direction is the organization of the movement of heavy trains. We believe that the primary direction in the development of the transportation process technology is the development of a larger volume of cargo transportation with a smaller number of trains, due to the wider use of heavy-weight trains with innovative cars on the railway network of the South-West range. The current methods optimize the choice of the weight norms of freight trains either according to an economic criterion or according to technical and economic calculations, but in modern conditions one should rely on the criterion of ensuring the maximum volume of traffic, since an increase in the production and economic efficiency of social production directly depends on the timely provision of transportation. Weak transport services lead to an increase in production costs and lose a large part of the economic effect due to dissatisfaction with market demand for transportation, deterioration in product quality and, as a result, an increase in production costs. All projects to improve the technology of the transportation process in transport and logistics systems should be aimed at ensuring the maximum volume of traffic with the subsequent minimization of costs for the measures being taken to achieve the required result. Driving heavy trains has a technical and economic justification
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only in the case of organizing constant circulation from stations with powerful car traffic volume loaded with bulk cargo. The observed dynamics of the growth of freight traffic to the ports of ABSB indicates an increase in the number of dispatched routes. Thus, taking into account the choice of certain sections and their current actual technical equipment, we consider it expedient to recalculate and further revise the weight norms on the sections of heavy trains on the southern range of the railway network. Heavy traffic today is an effective tool that helps to increase the carrying capacity of sections and directions, and create a reserve of carrying capacity. It contributes to the reduction of the number of trains passed at the established size of the car traffic volume due to the organization of the circulation of trains of increased mass relative to the values established by the traffic schedule and the sorting plan. Currently, for loading the largest producers of coal, ore, building materials are provided with innovative gondola cars with increased axle load. Since 35% of the total export freight traffic of fuel and energy cargo was shipped. The unified mass of such trains is 7200 2018, the number of railcars with an increased axle load of 25 tf has been growing and today it is more than 100,000 units, in which tons and the composition of 71 gondola cars with a standard length of 14 m is designed for full filling of receiving-departure tracks with a useful length of 1050 m. Organization of the movement of trains of this mass will reduce every 5th train weighing 6000 tons and every 8th train weighing 6300 tons. The operation of innovative rolling stock, due to improved technical and economic characteristics, allows to reduce the cost of an empty run per ton of cargo, to reduce the required fleet of gondola cars and to reduce the cost of their current maintenance. The elimination of technical inspection of rolling stock while traveling long distances increases the speed of their movement by 37 km per day and provides a cost reduction of 45 million rubles per year per train. In conditions of maximum load on the lines, it is necessary in the near future to improve the organization of the movement of trains of increased weight and length strictly according to constant schedule lines by organizing a non-stop process of running trains on the basis of shift-daily planning of the transportation process. The formation of heavy trains ensures a better use of the length of the receiving-departure tracks and the power of train locomotives. All this leads to the development of freight traffic by a smaller number of trains. When organizing the movement of heavy trains, it is necessary to determine the possible number of freight trains of standard weight that can be passed through the section and the number of formed heavy trains to ensure the missing reserve of carrying capacity. The possible number of freight trains passing through the section, subject to the 10% reserve of carrying capacity, is established by the formula: pos N f r = Nn · 0, 9 − N pass · εaκ pass + Nas (εas − 1) , pos
N f r = 154 · 0, 9 − (31 · 1, 63+) = 84, 07 ≈ 84trainpair s.
(6)
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To establish the required number of heavy trains, it is proposed to use the system of equations: ⎧ ⎪ ⎨ ⎪ ⎩
pos
n st + n h = N f r
ϕ · (Bst · n st + Bh · n h ) = Vd Vd /(ϕ · Bh )
4
Major project
1–4
Medium project
0.3–1
Small project
60% with inappropriate qualifications—0.4; >40% with inappropriate qualifications—0.6; >20% with inappropriate qualifications—0.8; full staffing with the appropriate qualifications—1.0
0.17
MSC 7
Branding, incl. HR brand strength
Brand awareness, brand penetration, goodwill, reputation, co-branding
No branding—0; there is a local brand—0.2; there are national brands—0.4; there are various brands—0.6; there are global brands—0.8–1.0
0.12
(continued)
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Table 1 (continued) Marketing Resource/competence Competitive sub-capabilities advantage (MSCs)
Assessment of MSC (in fractions of 1): possible values
MSC 8
No own sales 0.10 capacities—0; available, but not enough—0.25; available in sufficient quantity but do not meet modern requirements—0.5; e-commerce available—0.75; all modern distribution channels are available—1.0 MP gen. = MSP × 1.0 Cv.
Distribution network, availability of own channels, logistics system
General assessment
The speed and cost of delivery, convenience for customers
Coefficient values, Cv (in fractions of 1)
3 Results Approbation of the proposed methodology was carried out on a group of leading transport enterprises represented on the market of Russia [13]. The experts were the top managers of these enterprises, as well as independent consultants of the Chamber of Commerce and Industry, LLC MS Standard Analytical Bureau and members of the marketing departments of three universities in Belgorod and Saint Petersburg—a total of 37 people. They also set the coefficients of the value of marketing sub-capabilities in terms of competitive advantages in the sub-industry of business transportation. Note that the value coefficients differ: according to experts, the highest is the qualifications of personnel (marketers), the type of marketing behavior; this coefficient is also high for the breadth of the marketing contour (the composition of the business model). The sub-capabilities of the conceptuality of marketing in a transport company, digitalization of communications and distribution have approximately the same level of value [6, 11, 12, 14]. The results of assessing MC for a group of leading transport enterprises in Russia are presented in Table 2.
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Table 2 Results of assessing the level of marketing capability of the leading transport enterprises in Russia and market indicators (for 2020) Transport enterprises
Scaled and integral assessment of the marketing capabilities of enterprises
Transport company “Energy”
0.71
0.53
0.39
0.22
0.63
0.51
0.43
0.65
0.44
“Delovyye Linii” (business lines)
0.67
0.74
0.42
0.29
0.41
0.55
0.32
0.75
0.55
KIT (GTD) 0.61
0.31
0.46
0.14
0.38
0.42
0.50
0.45
0.37
Transport company “Baikal Service”
0.69
0.48
0.37
0.20
0.67
0.48
0.36
0.59
0.51
Trasko
0.56
0.37
0.25
0.23
0.54
0.50
0.35
0.33
0.40
DPD
0.55
0.41
0.37
0.19
0.44
0.47
0.33
0.46
0.39
Iteco 0.53 Corporation
0.60
0.39
0.26
0.56
0.61
0.22
0.68
0.48
CDEK
0.78
0.82
0.69
0.61
0.70
0.78
0.92
0.88
0.87
Logistic company “PEK”
0.55
0.58
0.53
0.29
0.65
0.61
0.58
0.63
0.56
MSC 1 MSC 2 MSC 3 MSC 4 MSC 5 MSC 6 MSC 7 MSC 8 MPgen. = MSC × Cv.
4 Discussion The results of MC assessment at the group of transport enterprises in Russia revealed the following. CDEK has the highest MC level (0.87), among the sub-capabilities of which the brand capability is in the lead. Logistic company “PEK” (0.56) and “Delovyye Linii” (0.55) have relatively high MC—in both cases, the level of distribution sub-capability is high. The MC in KIT (GTD) (0.37), DPD (0.39) and Trasko (0.4) are relatively low. The MC of Iteco Corporation (0.48) and transport company “Baikal Service” (0.51) are at the middle level. We can observe that most of the analyzed transport BOs have relatively advanced core concepts of marketing (MSC 1). Four out of nine companies have the functionality complex (MSC 2) gaps (below average—from 0.31 up to 0.48). Type of marketing behavior (MSC 3) is relatively low for most of the companies. Digital marketing technologies (MSC 4) and branding (MSC 7) scores vary dramatically among the companies. The breadth of the marketing contour (MSC 5) and personnel
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qualification (MSC 6) can be considered as sufficient for all. Six out of nine transport BOs have relatively strong logistics systems (MCS 8). The results obtained make it possible to identify the weak MSCs and to draw essential management conclusions on how to shorten capacity gaps. For any company, a deeper analysis can be carried out using this method and more accurate recommendations can be made. It is of scientific and practical interest to find the relationship between the level of MC and the target indicators of a transport BO achieved in the market. These data are presented in Table 3. As shown by the correlation-regression analysis (carried out at the MS Excel, see Fig. 2), the leveled assessment of MC is in a functional relationship with such market performance indicators of transport business organization as: (a) sales volume, in % of total market capacity; (b) share of regular customers. The calculation of the correlation coefficient showed that the relationship between marketing capability and such indicators as sales volume and share of regular customers exists and is moderate (the correlation coefficients are 0.45 and 0.55, respectively). Table 3 Comparison of MC levels and target market indicators of the leading transport enterprises in Russia Transport enterprises
Integral MC assessment by the level of sub-capabilities (in fractions of 1)
Sales volume (in % of total market capacitya )
Share of regular customers (%)
Transport company “Energy”
0.44
9.3
29.6
“Delovyye Linii” (business lines)
0.55
11.5
41.8
KIT (GTD)
0.37
5.4
19.7
Transport company “Baikal Service”
0.51
6.7
17.6
Trasko
0.40
7.3
25.9
DPD
0.39
5.1
30.2
Iteco Corporation
0.48
7.5
16.5
CDEK
0.87
16.6
40.3
Logistic company “PEK”
0.56
18.6
23.9
Others a
10.7
The market and its capacity in this case have a national profile
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Fig. 2 Correlation fields
5 Conclusion So, the topic of the MC of an economic entity is one of the most controversial in economic theory and practice. This is proved by the fact that there is no single position, a single methodology for assessing and shaping marketing capability among both foreign and domestic scientists. The marketing capability of an economic system operating in a competitive market as a phenomenon has two aspects: (a) a business management tool; (b) the basis of the economic capability of a BO. The study of the capability of any object or phenomenon is based on the analysis of available resources, which determine future opportunities, that is, capability, as well as the influence of various environmental factors on these resources. The specificity of MC is that its intangible nature must be fully taken into account. The structure of MC may be represented by groups of homogeneous elements, which all together characterize the state and capabilities of BOs to create, strengthen and develop their competitive advantages. The proposed method of multi-dimensional assessment of MC and its approbation on a group of transport enterprises showed that the MC level differs significantly for a particular transport BO and helped to reveal weak places with MC gaps. However, the general conditions for the formation of the full-capability marketing can be called the system-balanced development of individual sub-capabilities and its sustainable marketing management. The article also proves the existence of a significant correlation between the level of MC and market indicators—such as the sales volume and the share of regular customers of a BO.
References 1. Day GS (2011) Closing the marketing capabilities gap. J Mark 75(4):183–195 2. Herhausen D, Miocevic D, Morgan R, Kleijnen M (2020) The digital marketing capabilities gap. Ind Mark Manag 90:276–290. https://doi.org/10.1016/j.indmarman.2020.07.022
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The Formation of an Investment and a Transport Investment Innovation System Model of the Region Anna Zhdanova
Abstract Nowadays paradigm of the global economic system is dictated by the requirements of scientific and technological progress. It is possible to achieve high competitive positions and ensure a high level of development of states and territories only if its economy adapts to the requirements of a modern consumer. Hereupon, the question arises: how to achieve territorial development and maximize the effect of mobilizing available resources? The answer to this question can be the creation of a new resource management system, which presupposes close interaction of the structures that own them. Transport investments also affect the economic development of regions since an established transport network ensures interregional and interstate interaction. Thus, we come to the creation of an investment and innovation system of the region, within which the investment and innovation potential of the territories are combined to achieve common goals. The formation of an investment and a transport investment innovation system is based on the existing principles of a systematic approach, for the greatest clarity of how it should work, a graphical model is created using the digraph method. The feasibility of forming an integrated investment and innovation system of the region is described by a mathematical function that reflects the effectiveness of its functioning. The author proposes his own assessment system based on existing scientific approaches to determining the effectiveness of investment and innovation projects. Keywords Innovation · Investment · Regional innovation system · Transport investment · Transport investment strategy · Transportation investment for economic development
A. Zhdanova (B) Belgorod State Technological University named after V. G. Shukhov, 46, Kostyukov Street, 308012 Belgorod, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_70
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1 Introduction The key problem of the regions of the Russian Federation on the way to economic development, and to innovation particularly, is the differentiation of starting positions. Two problems are ensued from this thesis [1]: – the transition to innovative and high-tech production is becoming more complicated; – the existing innovations adopted from neighboring regions or other countries may not be effective enough. Besides technological innovations, the organizational and marketing innovations, which implementation is impossible without changing the institutional foundations of the regional economy, can also lead to an increase of competitiveness of the region and of its products. Thus, before increasing the effectiveness of the innovations themselves, it is necessary to achieve their popularization and to create stable bases, realizing innovative activities on an ongoing basis, reducing the risks of negative external influences. One of the direction of popularization of innovations and its formation in society can be called multi-agent interactions, that is the economic entities from different spheres and industries take part equally in such projects [2]. Both the interaction of various scientific and industrial structures and financial agents can be considered here. And if in the first case, the work has been going on for a long time and interdisciplinary research is reaching a new global level, then investors are often inclined to act independently. Today in the region the investment processes are not considered to be a separate system. Mostly, you can hear the term “investment infrastructure”, but this concept does not quite reflect the needs of the innovation market. That is why we propose for consideration a comprehensive investment and innovation system, in which the interaction of investment infrastructure elements will also be involved in a special subsystem of interrelated elements. The investment and innovation system of a region is a set of interrelated elements of innovation and investment infrastructures that interact directly with each other in the process of implementing a set of innovative projects and programs at the regional level. In contrast to the classical innovation system of the region, in the process of forming the investment and innovation system, special connections are formed between the subjects of the financial market, funds and corporations supporting innovative business, and independent investors. The formation of the investment and innovation system of the region is based on the following principles [3]: 1. The hierarchy principle. Within the framework of the system, investment objects are arranged in a hierarchy according to the goals and objectives of the economic development of the region, from which the order and size of investments in certain projects are determined. This principle makes it possible to achieve the objectives set by the innovation development strategy as soon as possible.
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2. The principle of goals consistency. This principle is based on the previous one and means that the forms of investment support should also correspond to the goals of innovative development of the region. For example, on the territories with low and high levels of innovation activity, the share ratio of the banking sector, venture funds and technology park structures will differ. 3. The principle of orderliness. The elements of the innovation system are clearly structured and occupy a certain position within the framework of investment and innovation processes. 4. The integration principle. Within the framework of the investment and innovation system, investment units interact with each other on mutually beneficial terms in order to achieve the goals of innovative and economic development of the region as soon as possible.
2 Materials and Methods Modeling the innovative development of a region is based on the establishment of close relationships between subsystems and their elements, therefore, the most appropriate is the use of the method of correlation-regression analysis for the most significant indicators. We have developed a system of indicators for the economic development of the region, which serves as the basis for assessing the feasibility of further formation of the investment and innovation system [4]. The statistical data from state statistics bodies and from open sources is an information base for compiling a map to assess the economic development of the Belgorod region [5] (Table 1). The map made up above serves as the basis for calculating the economic efficiency of the resulting model of the investment and innovation system. Based on the data presented, it can be concluded that in many indicators, in particular, innovation activity and current social-economic development, the Belgorod region is not much inferior to the leading regions. At the same time, we can observe a low level of investment in scientific and technical equipment and fixed fund, which means that the region under consideration needs to systematize investment activities and strengthen control over cash flows at all levels. Thus, the formation of the investment and innovation system of the Belgorod region is aimed at attracting a higher level of investment to innovation.
3 Results and Discussions The formation of an investment and innovation system is possible due to the algorithm we have developed (Fig. 1). This algorithm is universal, therefore, if it is necessary, you can reduce or, conversely, increase the number of stages in order to create a more perfect system that takes into account the advantages and problem
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Table 1 Economic development assessment map of the Belgorod region Indicator
Running value
Beat value by country
Pattern
Leading region
Share of teaching staff involved in basic research, %
46.129
66.678
0.692
Moscow
Number of patent applications filed, unit
157
5298
0.030
Moscow
Developed advanced production technologies, unit
38
342
0.111
Moscow
The share of graduates of engineering and technical specialties in the total amount of university graduates (for all forms of education), %
36.73
43.86
0.837
St. Petersburg
The number of 12 technopark structures, engineering centers and business incubators created on the territory, unit
80
0.150
Moscow
The share of high-tech and knowledge-intensive industries in the gross regional product,%
10.6
34.6
0.306
Kaluga region
Share of small enterprises implementing technological innovations, %
10.5
13.2
0.795
Altai region
The share of innovative 13.9 goods and services in the total amount of goods and services shipped in the region, %
23.8
0.584
The Republic of Mordovia
8
0.350
Nizhny Novgorod Region
I. Innovations
II. Investment The share of costs for innovative activities in the total volume of goods shipped, work performed, services, %
2.8
(continued)
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Table 1 (continued) Indicator
Beat value by country
Pattern
Leading region
Share of internal 0.250 expenditures on research and development in GRP, %
Running value
5.640
0.044
Nizhny Novgorod Region
Share of equipment acquisition costs in total research costs, %
4.697
24.526
0.192
Irkutsk region
Costs for innovative activities of small enterprises, mlns RUB
729.3
3579,2
0.204
Moscow
Interest rates on loans for small innovative entrepreneurship, %
7
7
1
Flat rate for state program
82.7
0.212
Amur region
Cash income per capita, 30,878 rubles per month, RUB
74,559
0.414
Nenets A D
Consumer price index
104.95
92.62
0.883
Irkutsk region
Subsistence minimum per capita, RUB
9720
24,164
0.402
Chukotka AD
Unemployment rate, % 4.9
2.4
0.490
Yamalo-Nenets AD
The share of the region’s population living in cities, %
96.1
0.702
Magadan Region
0.012
0.250
Volgograd region
The number of 142.2 employees of state bodies and local self-government bodies per 10,000 resident population, per
99.1
0.697
Moscow region
Share of graduates in specialties related to state and municipal administration, %
5. 77
0.783
Moscow
Share of investments in 17.5 fixed assets to GRP, % III. Social-economic relations
67.491
Number of institutions 0.003 of higher education per 1000 people, pcs IV. Political and legal sphere
4.52
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areas of the territories. However, it should be noted that the creation of a regulatory framework for the implementation of investment and innovation activities, as well as the development of advanced strategies and programs will be mandatory stages at an early stage of the formation of the system under consideration, since business entities, as well as investors, need to ensure the safety of their activities [6–9]. We also highlight the cluster as a necessary element due to the differentiation of the natural and geographical conditions of the regions. In our opinion, the concentration of innovative activity in those industries, not only economic, but also geographical ASSESSMENT OF ECONOMIC DEVELOPMENT OF THE REGION AT THE PRESENT STAGE DEVELOPMENT OF INDICATOR SYSTEM
CREATION OF AN EXPERT GROUP
MOBILIZATION OF INNOVATIVE POTENTIAL RESOURCES OF THE REGION INVESTMENT
MANUFACTURING
SCIENTIFIC AND TECHNICAL
CREATION OF AN INNOVATIVE DEVELOPMENT STRATEGY SETTING OF GOALS AND OBJECTIVES
FINDING OF PLANNED INDICATORS
APPOINTMENT OF PERSONS RESPONSIBLE FOR THE IMPLEMENTATION OF THE INNOVATIVE DEVELOPMENT STRATEGY CREATION OF A REGULATORY LEGAL FRAMEWORK FOR REGULATING INTERACTIONS OF INVESTMENT AND INNOVATIVE ACTIVITIES OUTSIDE THE TERRITORY OF REGIONS MERGER OF INVESTMENT INFRASTRUCTURE SUBJECTS, ENSURING THEIR INTERACTION ON MUTUALLY FAVORABLE CONDITIONS IN THE PROCESS OF IMPLEMENTATION OF THE INNOVATION STRATEGY CREATION OF SPECIAL CONDITIONS FOR INNOVATIVE BUSINESS AND INNOVATIVE INVESTORS ON THE TERRITORY OF THE REGION
ORGANISATION OF A REGIONAL INNOVATIVE CLUSTER BASED ON THE LEADING INDUSTRY, AUXILIARY PRODUCTIONS ARE LOCATED IN SMALL CITIES
ORGANISATION OF A UNIFIED INVESTMENT AND INNOVATION SYSTEM IN THE PROCESS OF FUNCTIONING OF AN INNOVATIVE CLUSTER AND CREATION OF RELATIONSHIPS BETWEEN INVESTMENT AND INNOVATION ACTIVITIES
Fig. 1 Algorithm for the formation of the investment and innovation system of the region
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advantages can be observed in, has a positive effect both on the dynamics of socialeconomic indicators and on increasing competitive positions. The investment and innovation system of the region relies on existing resources of innovation potential and the creation of the previously indicated conditions for the implementation of investment and innovation activities in the region. When creating a model of investment and innovative development of the region, we should take into account as follows [10]: – the difference between the resources of the innovative potential of each region, that is why the basic elements of the system are associated exclusively with the development of investment infrastructure; – innovative development in general is built on the basis of the integration of science, business and government. At the same time, these elements can create innovations both as a result of cooperation and individually, since there is a transfer of technologies; – at the first stages of the formation of the system, results should be obtained that ensure the further economic and innovative development of the region. The model of the investment and innovation system of the region takes the form of digraphs, that clearly represents the interaction of various structures at each stage of the innovation process (Fig. 2). Thus, the scheme of financing innovations is being modernized: it can be direct investments from the state, scientific or entrepreneurial sector; venture capital funds
Fig. 2 Model of the investment and innovation system of the region
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and debt fund; resources offered by business incubators and technology parks. At the same time, venture capital funds can invest not only directly in projects, but also support business incubators and technology parks in order to maintain the latter’s material and technical base at the required level, thereby ensuring the continuous implementation of innovative projects accepted for implementation. The banking sector and commercial credit organizations can contribute to the development of the investment and innovation system of the region through joint participation in the financing of innovative projects, as well as the provision of loans on a preferential basis, both directly for innovators (including scientific organizations) and for innovative organizational structures. When assessing the effectiveness of the regional investment and innovation system at the present stage, one should start from such methods as the “pattern” method— correlating actual values with the best in the country and the “multidimensional average” method—correlating actual values with the national averages. The choice of this or that method is justified by the current level of development and the goals set. The study used the “Patterns” method, since an assessment of the most developed regions will allow the most accurate identification of the weaknesses of the region and build an effective strategy. The function describing the efficiency of the investment and innovation system in general form will look like this: I I RS E = r ×
PI t
nI
×
PI nt
nIn
×
PSt
nS
×
PPlt , n Pl
(1)
where: IIRSE—efficiency of the investment and innovation system of the region (Investment-Innovative Regional System Efficiency); r—the obtained value of the correlation coefficient; PIt —pattern of the t-th indicator of the group of indicators «Innovation»; PInt —pattern of the t-th indicator of the group of indicators «Investments»; PSt —pattern of the t-th indicator of the group of indicators «Social-economic relations»; PPlt —pattern of the t-th indicator of the group of indicators «Political and legal sphere»; nI, nIn, nS, nPl —number of indicators in each respective group. The allowable values of the coefficient are determined based on the number of groups of analyzed indicators, since this affects the degree of reduction in the final result (Table 2). To determine the correlation coefficient, let us construct a graph of the linear dependence of the volume of innovative goods and services on the feasible costs of technological innovation (Fig. 3). We get the following coefficient value I I RS E: I I RS E = 0.948 ×
3.506 2.001 3.141 1.48 × × × = 0.054 8 6 6 2
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Table 2 Criteria for compliance of IIRSE with types of regions in terms of the level of innovative development Pattern values
Construction degree 1
2
3
4
1
1
1
1
1
0,9
0.9
0.81
0.729
0.6561
0,8
0.8
0.64
0.512
0.4096
0,7
0.7
0.49
0.343
0.2401
0,6
0.6
0.36
0.216
0.1296
0,5
0.5
0.25
0.125
0.0625
0,4
0.4
0.16
0.064
0.0256
0,3
0.3
0.09
0.027
0.0081
0,2
0.2
0.04
0.008
0.0016
0,1
0.1
0.01
0.001
0.0001
0
0
0
0
0
Allowable IIRSE correlation coefficient correction values Flagship
0.7–1
0.51–1
0.36–1
0.2–1
Innovator
0.4–0.69
0.16–0.5
0.065–0.35
0.025–0.2
Outsider
0–0.39
0–0.15
0–0.03
0–0.024
Fig. 3 Graph of the dependence of the volume of innovative goods and services production on the volume of expenditures on technological innovation for 2014–2019
Thus, the Belgorod region belongs to the group of innovative regions. If we consider the advantages and disadvantages according to the above calculations and the set of statistical data, we can see that the region has a fairly high level of socialeconomic development, and there is also an increase of innovation potential due to an increase in the production of innovative goods and services, but investments remain a problem area. The low level of investment in fixed assets and the purchase of equipment can negatively affect the intensity of the innovation process, therefore, stimulating the economic development of the Belgorod region needs to create an effective investment subsystem within the regional investment and innovation system.
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4 Conclusion At present the problem of improving the efficiency of using the investment and innovation potential of regional systems concerns most of the territorial units of the Russian Federation. The economy in Russia is still in a transition period meaning that a high level of differentiation of regional development leads to an industry imbalance, interrupts complementary production and import substitution. Offered by us mechanism for the formation of the investment and innovation system of the region is a tool for optimizing the activities of the relevant infrastructure entities. By determining the level of development in each of the specified areas, administrative bodies receive an information base for adjusting strategies and programs for the development of the territory. The usage of the «patterns» method allows us to assess the position of the region in the national innovation system and determine the degree of lag behind the leaders, which sets the vector for the developed growth and development strategies. Acknowledgements This work was realized under the support of the President Scholarship; in the framework of the Program of flagship university development on the base of the Belgorod State Technological University named after V. G. Shukhov.
References 1. Bulgakova MS (2020) Content of innovative process in a regional innovation system. Mosc Econ J 11:564–573. https://doi.org/10.24411/2413-046X-2020-10774 2. Suslov VI, Kostin VS, Ivanov EY, Ibragimov NM, Novikova TS, Tsyplakov AA (2020) Problems of development of multi-agent decision support system at the sub-federal level. World Econ Manag 20(3):5–26. https://doi.org/10.25205/2542-0429-2020-20-3-5-26 3. Ivanov PA (2021) Theoretical and methodological aspects of assessing the investment activity of regions. Ars Administrandi 13(4):495–515. https://doi.org/10.17072/2218-9173-2021-4495-515 4. Zhdanova AV (2021) Parameters for assessing the economic development of the region from the standpoint of the formation of an integrated investment and innovation system. Vestnik Belgorod Univ Coop Econ Law 87(2):146–152. https://doi.org/10.21295/2223-5639-2021-2146-154 5. Govorova NV (2021) Technological development of Russian Regions (on the example of Belgorod Region). Econ Inf Technol 48(1):25–33. https://doi.org/10.52575/2687-0932-202148-1-25-33 6. Bezugly EA, Tkachenko VV, Shaposhnikov VL (2020) Regional economic development: innovative approaches. Azimuth Sci Res Econ Adm 2(31):63–66. https://doi.org/10.26140/anie2020-0902-0010 7. Abdulsamedov TA (2021) Investment and innovation policy to ensure the competitiveness of the regional economy. Educ Law 8:120–123. https://doi.org/10.24412/2076-1503-2021-8120-123 8. Kirsanova EG (2020) Creation of clusters as a mechanism for the implementation of innovative policy in the European Union (case of innovation clusters in Germany). Bull ZabGU 26(1):93– 100. https://doi.org/10.21209/2227-9245-2020-26-1-93-100
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9. Merzlikina GS (2020) Innovative development of the region: new criteria—evaluation indicators. Bull Astrakhan State Tech Univ Ser Econ 3:7–18. https://doi.org/10.24143/2073-55372020-3-7-18 10. Doroshenko YA, Somina IV, Malykhina IO (2020) Methodology of the formation of a comprehensive support mechanism of innovation and investment development in the region. In: Lecture notes in networks and systems, vol 128, pp 916–923. https://doi.org/10.1007/978-3-030-468170_103
Study of the Level of Digitalization of the Banking Sector of Russia in the Context of the Pandemic and the Development of Transport Technologies Sofia Bukhonova
and Anna Yablonskaya
Abstract In modern conditions, the successful functioning of the banking sector largely depends on the level of use of modern innovations and technologies, including transport. Which helps increase the level of digitalization. The aim of the study is to assess the level of digitalization of the Russian banking sector, taking into account epidemiological conditions. This research is based on the use of a systematic approach, covering methods of induction, deduction, abstraction, analogy, comparison, analysis and synthesis. The paper defines the concept of “digital economy”, presents some modern banking technologies, considers, analyzes and groups the results of research conducted by the World Bank, Deloitte Company, the Institute of Statistical Research and Knowledge Economy of the National Research University “Higher School of Economics”, the analytical agency NAFR, the rating agency “Expert RA”. This allowed the authors to identify the key factors that influence the acceleration of the digital transformation of the banking sector. At the end of the research, the conclusion was made that Russia has a favorable environment for accelerating the digital transformation of the banking sector, as evidenced by such facts as, for example, an increase in the number of clients who use modern remote banking channels. In addition, the current epidemiological conditions are conducive to the intensification of the banking sector in the implementation and use of modern technologies. Keywords Banking sector of Russia · Digital economy · Digital transformation · Transport sector · Transport investment strategy · Transportation investment for economic development
S. Bukhonova (B) · A. Yablonskaya Belgorod State Technological University Named After V. G. Shukhov, 46 Kostyukova Street, Belgorod 308012, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_71
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1 Introduction Today, the dynamic development of society lies in the innovative progress of science, advanced technology, and changes in technical processes. In modern conditions, the development of the economy and social changes in society depend directly on the level of digitalization. This is noted in the Decree of the President of the Russian Federation “On the strategy for the development of information society in the Russian Federation for 2017–2030”. The goal of the strategy is to develop and use new information technologies in our country to ensure the socio-economic development of society at the proper level. In addition, since June 2019, the national program “Digital Economy of the Russian Federation” has been put into action. These programs are designed, firstly, for the development and successful use of modern technologies; secondly, for convenient processing and storage of data with a large volume; thirdly, to develop a simple and secure information society infrastructure. According to its specific structure, the program includes the following federal directions (projects): “Statutory regulation of the digital environment”; “Information Infrastructure”; “Personnel for the digital economy”; “Information Security”; “Digital Technologies”; “Digital Public Administration”. The project implementation period is indicated from October 2018 to 2024 inclusive. That is, in order to be successful, competitive, in addition to the development and implementation of innovative technologies, it is necessary to be “digital”. What is the digital economy? Let us try to figure it out. The digital economy is a certain, independent branch of activity based on the informatization of society through the use of modern information technologies for the production and sale of products and services. To date, there are several international ratings, which to a certain extent allow us to characterize the level of development of information support for society and business conditions in different countries. Thus, one of the most important indicators of how much the state is ready to implement information and communication technologies, the level of economic development in the context of digital transformation is the Networked Readiness Index. This indicator is analyzed annually by the Portulans Institute, the World Information Technology and Services Alliance, and its data is presented in reports [1]. In our opinion, the level of development of information technologies largely depends on the degree of economic development of the state. Therefore, the level of development of modern information technologies affects the structure of the economy, contributes to the improvement of modern production, and increases competitiveness. This affects the state of development of society. Accordingly, the network readiness index can be calculated by states for a logical assessment of the level of development of their country, including in the field of digitalization. The specialists of the designated organizations compute the network readiness index on the basis of 62 different indicators, characterizing countries by technological components, management skills, human factors of development, the degree of
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influence of the state at the international level. According to the results of computations of the index for 2020 the first ten countries are Sweden, Denmark, Singapore, Netherlands, Switzerland, Finland, Norway, USA, Germany and Great Britain. Russia is on the 48th place with an index value of 54.23. According to the Russian Association of Electronic Communications (RAEC), the digital economy of our country is based on the markets of marketing and advertising, e-commerce, infrastructure and communications, as well as digital content. Their share in the country’s GDP for 2019 was about 4.7 trillion rubles, and for 2020, taking into account the economy of the Runet as a whole, it was 6.4 trillion rubles.
2 Materials and Methods The methodological basis of the research is the system, process, structural, and functional approaches. General and special methods of scientific knowledge, methods of statistical, comparative analysis and expert selection were used to solve analytical problems. The information base of the research is the data of the Bank of Russia, analytical and statistical data of individual banks, the results of research by rating agencies, international consulting companies, development research centers, and statistical materials published in the mass media.
3 Results and Discussion In modern conditions, the structure of the introduction and development of digital technologies in the types of economic activity of our country is quite heterogeneous. It should be noted that a significant development of the digital transformation process is observed in the financial industry, namely in the banking sector of the country. In addition, digital technologies are implemented at a fairly good level in such industries as education, healthcare, and ICT segments. However, such industries as the processing industry, mining, and transport are still showing weak implementation of new information technologies for digitalization. The Institute for Statistical Research and Knowledge Economics of the National Research University Higher School of Economics (HSE) has developed an indicator that characterizes the level of adaptation of economic entities in the real sector of the economy of Russia, Europe, the Republic of Korea, Turkey and Japan to digitalization. This is the Business Digitalization Index (BDI—Business Digitalization Index), calculated by the following five indicators: the level of use of broadband Internet, cloud services, RFID technologies, ERP systems, and involvement in ecommerce. So, by the end of 2019, the top ten leaders in the value of this index include Finland, Denmark, Belgium, Sweden, North Korea, the Czech Republic, France, Great Britain, Germany, and Italy (Fig. 1) [2].
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52
50
49
47
47
40
39
39
36
36
34
32
Business digitalization index Fig. 1 Business digitalization index value by country in 2019
Russia is on the 12th place with a value of 32 points, and is ahead of such countries as Poland, Greece, Bulgaria and Romania. In August-September 2020, the multidisciplinary analytical agency NAFR conducted a study on the readiness of Russian small and medium-sized businesses to digital transformation. More than 1,000 entrepreneurs and managers of small and medium-sized businesses in our country took part in the research process. So, according to the survey in the first half of 2020 digitalization index of SMEs in Moscow and Russian regions is 50 points on a scale from 0 to 100. Experts say that our business is only half-ready for digitalization. Perhaps there are those organizations were not enough attention is paid to the implementation and development of digital technology. NAFR experts indicate that about 8% of Russian companies, 20% of medium-sized companies, about 7–8% among individual entrepreneurs and microcompanies have a high level of digitalization, and the share of small businesses with a high level of digitalization is 17%. One of the factors restraining the growth of the business digitalization index is the lack of company managers to stimulate and organize training for their employees in terms of digital development. For example, at the beginning of this year, the proportion of companies that did not provide their employees with training or advanced training in the form of seminars and master classes on the implementation and use of information technology increased from 57 to 73% [3]. As it was noted by the authors earlier, the banking sector is a leader in digital development. Let us particularize the characteristics of the level of digitalization in this area. In 2020, the Russian banking sector developed at a fairly high level and demonstrated high growth rates in key macro-prudential indicators. Some of them are presented in Table 1. The total number of credit institutions for the period from 2018 to 2020 tends to decrease. This change is due to the following circumstances. Firstly, the current
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Table 1 Some indicators that characterize the financial results of the Russian banking sector for 2018–2020 Indicators
01.01.2018
01.01.2019
01.01.2020
Absolute deviation (+; –)
1. Number of credit institutions, units
561
484
442
– 119
2. Share of profitable credit institutions, %
78.6
83
79.1
0.5
3. Share of unprofitable credit institutions, %
21.4
17
20.9
– 0.5
policy of the Central Bank of the Russian Federation is aimed at improving and strengthening the country’s banking sector. Secondly, the main direction of this policy is the development of reliable, sustainable banks that carry out real banking activities. Therefore, the Bank of Russia cleanses the banking system of financially unstable credit institutions. The value of banking sector assets increased, with an increase of 16.8% in nominal terms and 11.6% in real terms. This positive trend is primarily due to the proper support of the entire economy of the country from the state and the debt financing of the budget deficit. Consumer lending to the population tends to slow down. So, in the period from January to November 2020, the growth of the retail lending portfolio was 12.8%. And, for example, in 2019 and 2018, the growth of this indicator was 17.4% and 20.9%, respectively. However, the volume of corporate lending increased in 2020 [4]. According to the data of the Bank of Russia, the corporate lending portfolio increased by 9.2% in the first 11 months of 2020, and in 2019 the growth rate was 5%. The increase in lending to legal entities is associated with timely measures to support businesses in the pandemic conditions and with a decrease in average market interest rates due to a decrease in the key rate. The size of the banking sector liabilities increased. This increase was mainly due to the increase in funds of legal entities, while the increase in deposits of individuals was 2.1%. That is, during 2020, there is a replacement of public funds with corporate clients’ money, which is actually new for the formation of the resource base of the country’s banking system. The insignificant growth rate of the population’s deposits is due to the fact that during the pandemic, most citizens faced the search for a new job and (or) certain restrictions, and as a result, a reduction in income. And also, because of the interest rate policy of banks to attract funds from citizens, the population is actively looking for alternative ways of saving (bank insurance, securities market, real estate market and other ways). Thus, the state of the modern Russian banking sector indicates favorable conditions for intensive digitalization [5]. As it was noted by many experts from open sources in 2020, the level of digitalization in the banking sector increased significantly compared to 2019. In the pandemic conditions, banks increased significantly the range of digitalized products and services for their customers. The epidemic contributed to increased competition in the banking environment, banks rapidly introduced and mastered new digital platforms in their operations to attract customers, which led to an increase in their capital
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base. In addition, certain conditions in society changed significantly the behavior of customers who actively used remote service channels. The international company Deloitte Digital published a report on the digitalization of commercial banks in 2020. Thus, according to the results of the study, Russia entered the top 10 leading countries in terms of digital banking development. The top ten countries include Japan, Singapore, Norway, Spain, Belgium, Turkey, Poland, Saudi Arabia and Qatar. In total, the company’s consultants and analysts investigated more than 1,000 banking products and services in 318 banks from 39 countries. Among the main criteria for studying the parameters of banking products and services were: the level of customer support, the ability to order a card online, account management through the app, and so on. It is worth noting that such major banks of the country as Ak Bars, Alfa-Bank, Saint Petersburg Bank, Gazprombank, Otkrytie, Pochta Bank, Promsvyazbank, Raiffeisenbank, Rosbank, Rosselkhozbank, Sberbank, Sovcombank, Tinkoff, UniCredit Bank and VTB took part in the study [3]. The digitalization index of banks in Russia is 51%, and the average value of this indicator in the world is 45%. We believe that the main incentive for the Russian banking sector to achieve the proper level of digitalization is the global epidemiological situation. Deloitte Digital experts note that about 60% of banks in the world in the pandemic conditions were forced to reduce working hours in their offices and (or) completely close branches and offer their products and services to customers in an online format of interaction with customers. For example, in 34% of the banks studied in the world, it is possible to open an account online without hindrance. When the client uses the bank’s services remotely, its authentication is important, which can be offered by about 23% of banks at the international level. Deloitte Digital experts analyzed more than 1,000 modern banking products and services based on specific features and technical characteristics used by bank customers, and presented the following grouping. Four groups of banks are identified according to the degree of their digitalization: 1. 2. 3. 4.
Group. Latecomers. Adopters. This classification category includes 3 national banks. Smart Followers. There are 9 banks from Russia listed here. Champions. This group includes 3 Russian banks.
The company notes that the group of leaders includes banks with high-tech bases and infrastructure. They are ahead of their competitors in terms of the technical characteristics of digital banking [6–10]. Consequently, Russia has favorable conditions for a successful digital transformation of the banking sector. This is evidenced by the active introduction of modern banking technologies by credit institutions (Table 2). The Skolkovo Foundation, in cooperation with the innovative Russian company VR_Bank, has compiled the third rating on the digitalization of Russian banks in 2020. The leading positions in the rating are held by the following banks: Tinkoff, VTB, Sberbank, Raiffeisenbank, Alfa-Bank. It should be noted that positive changes
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Table 2 Some modern banking technologies used in Russian banks for the purpose of successful digitalization Types of modern bank technologies 1. Biometric identification of customers 2. Voice identification 3. Using Artificial Intelligence (AI), Big Data, and Machine Learning 4. Using POS-lending 5. Remote lending via a mobile app 6. Using a Blockchain solution for customer identification 7. RegTech—technologies 8. Design thinking 9. Digital Wallet 10. Contactless payment 11. Trade platforms 12. Robots in the departments
Table 3 Key factors influencing the acceleration of the process of digital transformation of the Russian banking sector Internal factors
External factors
1. Extensive use of remote service channels by 1. Participation of banks in state programs to bank customers support the Russian economy in key industries 2. Flexible adaptability of management systems to the transition to online operation in the pandemic conditions
2. Support of the Bank of Russia as a regulator of the banking system
3. Proper development of the IT infrastructure of banks
3. Created epidemiological conditions
in this research vector are observed in such banks as Sovcombank, Home Credit Bank, and the Ural Bank for Reconstruction and Development [1]. Thus, our analysis of research and publications in this subject area allows us to identify certain factors that affect significantly the increase in the level of digitalization of the banking sector, which we will divide into internal and external ones (Table 3). Consequently, the factors, we have identified, further contribute to the active digitalization of the Russian banking system.
4 Conclusion Thus, the conducted research allows us to conclude that Russia has formed a favorable environment for accelerating the digital transformation of the banking sector.
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This is evidenced by a significant increase in customers who use modern remote banking channels. In addition, banks are actively implementing and using banking technologies in their operational activities, and this is facilitated by the current conditions of the epidemiological situation. This contributes to improving the information processing process, cybersecurity, and adequate decision-making in the field of reducing certain risks. Acknowledgements This work was realized in the framework of the Program of flagship university development on the base of the Belgorod State Technological University named after V G Shukhov.
References 1. Abdrakhmanova GI, Vishnevsky KO, Gokhberg LM (2021) Digital economy: 2021. HSE, Moscow, p 124. https://issek.hse.ru/mirror/pubs/share/434007067.pdf 2. Barshchevskaya A (2021) “Skolkovo” and VR_Bank made the third rating of digitalization of banks. https://sk.ru/news/skolkovo-i-vr-bank-sostavili-tretiy-reyting-cifrovizacii-bankov/ 3. Bukhonova SM, Yablonskaya AE (2020) Study of the digital transformation of the Russian banking sector in the context of its investment attractiveness. Iss Innov Econ 10(2). https://doi. org/10.18334/vinec.10.2.100875 4. Glagolev SN, Bukhonova SM, Chikina ED (2018) Relevance of deterministic chaos theory to studies in functioning of dynamical systems. IOP Conf Ser Mater Sci Eng 327(2):022017. https://doi.org/10.1088/1757-899X/327/2/022017 5. Glagolev SN, Bukhonova SM, Chikina ED (2020) Implementing lean production management system (LPMS) in the practice of Russian organizations. IOP Conf Ser Mater Sci Eng 753:072019. https://doi.org/10.1088/1757-899X/753/7/072019 6. Glagolev SN, Bukhonova SM, Sidorin YM (2019) The realization of joint Russian-Serbia innovative projects in the regions. IOP Conf Ser Mater Sci Eng 753:072016. https://doi.org/ 10.1088/1757-899X/753/7/072016 7. Kirakisyants A (2021) Deloitte assessed the level of digitalization of banks’ development. https://frankrg.com/25912 8. Seliverstova N (2021) Results of the banking sector in 2020. https://riarating.ru/finance/202 01230/630193896.html 9. Shishin G (2021) How will the experience of 2020 affect the future of the Russian banking sector? https://www.ey.com/ru_ru/banking-capital-markets/ey-russian-bank-sectorsurvey-march-2020 10. Vederina E (2021) Russia is among the top 10 countries in terms of bank digitalization. https:// www.vedomosti.ru/economics/articles/2020/10/11/842808-rossiya-voshla
On the Problem of Investment and Innovation Activity Tatiana Kovaleva
and Elena Atabieva
Abstract An indispensable condition for the stable functioning of the economy, especially its development, is effective innovation in the transport sector. In terms of the level of innovation activity in general and the innovation activity of the industrial and transport sectors of the economy, Russia occupies one of the last places among European countries. Weak activity of the innovation process in Russia is caused by a complex of reasons. These reasons do not include the number of R&D employees. According to this indicator, Russia is in the lead. Domestic costs for research and development in Russia are growing every year and exceed those of most European countries. The structure of research funding sources in Russia is significantly different from the structure of other countries. It is necessary to establish the reasons why entrepreneurs in Russia do not show sufficient interest in financing research and development. The low interest in investment in the innovative activities of Russian enterprises (organizations) on the part of foreign investors can be caused by the same reasons: political, imperfect legal framework, high risks. Keywords Innovation · Investment · Public–private partnership · Foreign investment · Transport enterprises · Transport sector · Investment strategy in the field of transport · Investments in transport for economic development
1 Introduction Effective management of investment and innovation activities, including the transport sector, is one of the main conditions for the development of the economy both at the regional and macro levels [1–3]. The scale, structure and efficiency of the use of investments in fixed capital and transport largely determine the results of management at various levels of the economic system, development prospects and competitiveness of the national economy [4]. T. Kovaleva (B) · E. Atabieva Belgorod State Technological University Named After V. G. Shukhov, 46, Kostyukov Street, Belgorod 308012, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_72
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Table 1 Share of investments in fixed assets in GDP (as a percentage of total) Years
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Share of investments in fixed assets in GDP
20.7
21.0
21.4
20.8
20.0
21.3
21.4
20.0
20.6
21.8
Table 2 The level of innovative activity of organizations in the Russian Federation Years
2010
2013
2016
2019
Russian Federation
9.5
10.1
8.4
9.1
Today, one of the causes of economic problems in Russia is the long-term investment behavior of society. This problem is a consequence of the investment behavior of society in the past: since the late 50 s, a significant slowdown in the growth of investment activity, since the early 90 s, the transformation of net investment into negative values. At present, in the era of the digital economy, the investment process has noticeably intensified. The share of investments in fixed capital over the past decade has amounted to about 20% (Table 1). Innovation activity—all research (research and development), financial and commercial activity that, during the observation period, is directed or leads to the creation of new or improved products (goods, services), significantly different from the products previously produced by the organization, intended for introduction on the market, new or improved business processes that are significantly different from the organization’s previous corresponding business processes intended for use in practice [5, 6]. According to the Federal State Statistics Service, the level of innovative activity of organizations over the past decade has been about 9%. The innovative activity of organizations is characterized by the share of organizations engaged in innovative activities in the total number of functioning organizations and enterprises. The data is based on the results of a study of innovation by European scientists in 2014–2016. Aggregated data on industrial enterprises are presented for Russia (Table 2). In terms of the level of innovative activity in general and the innovative activity of the industrial sector of the economy, Russia occupies one of the last places among 33 European countries (according to Rosstat).
2 Materials and Methods In order to compare the activity of innovation and investment activity in Russia and other countries, the indicators published in the collection of the Russian State Statistics Service have been analyzed. For comparison, Table 3 provides information on the level of innovation activity in the largest European countries. Weak activity of the innovation process in Russia is caused by a complex of reasons. These reasons do not include the number of R&D personnel. According to this indicator, Russia is in the lead. The graph provides
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Table 3 The level of innovation activity of European countries Countries
The level of innovative activity of organizations, %
The level of innovative activity of industrial organizations, %
Russia
12.8
15.6
Germany
63.7
68.9
Spain
36.9
38.6
Italy
53.8
57.1
Great Britain
58.7
58.9
France
57.7
59.6
Sweden
54.2
55.8
Russia Germany Spain Italy UK France Sweden
Fig. 1 R&D staff, full-time equivalent (person-years)
information on the number of personnel engaged in research activities in 2018 (Fig. 1). Despite the downward trend in the number of personnel engaged in research and development, Russia is the leader in terms of this indicator, in full-time equivalent (person-years). Comparing the indicators of the number of employees engaged in scientific research with the level of innovative activity, it can be judged that research activities in Russia are not efficient enough (in comparison with the indicators of other countries represented in the sample) (Table 4). Internal costs for research and development in Russia are increasing every year and exceed those of most European countries. That is, the lack of funding from the state and business for scientific activities cannot be considered the main reason for weak innovation activity (Table 5). Internal costs for research and development activities in Russia cannot be characterized as excessively low. Comparing the value of domestic expenditures on research in Russia and a number of other European countries, it can be concluded that investments in Russia are comparable to similar indicators in countries such as Italy, Spain and the UK. In 2018, investment in research and development, as a percentage of
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Table 4 Internal costs of research and development, mln. US dollars Countries
2010
2012
2013
2014
2015
2016
2017
2018
Russia
33,080
37,911
38,607
40,330
38,776
39,008
42,375
41,505
Germany
87,028
100,490
102,905
109,562
114,128
122,459
134,429
141,433
Spain
20,082
19,269
19,282
19,356
19,820
20,631
22,319
23,552
Italy
25,400
27,419
28,459
29,448
30,002
33,073
34,657
36,006
UK
37,564
38,490
41,532
43,811
45,678
48,106
49,993
53,137
France
50,896
55,097
58,353
60,585
61,645
63,645
66,044
68,441
Sweden
12,552
13,970
14,496
14,191
15,493
16,248
17,837
18,117
Table 5 Internal expenditures on research and development, as a percentage of GDP Countries
2010
2012
2013
2014
2015
2016
2017
2018
Russia
1.13
1.03
1.03
1.07
1.1
1.1
1.11
0.98
Germany
2.73
2.88
2.84
2.88
2.93
2.94
3.07
3.13
Spain
1.36
1.30
1.28
1.24
1.22
1.19
1.21
1.24
Italy
1.22
1.26
1.30
1.34
1.34
1.37
1.37
1.39
UK
1.65
1.58
1.62
1.64
1.65
1.66
1.65
1.71
France
2.18
2.23
2.24
2.28
2.27
2.22
2.21
2.2
Sweden
3.17
3.24
3.27
3.11
3.23
3.25
3.37
3.31
GDP in Russia, was less than 1%, while in all countries selected for comparison, this indicator increased.
3 Results and Discussions Thus, the reasons for weak innovation activity can be attributed to a decrease in the share of domestic spending on innovation in GDP (Table 6). In 2018, state funds dominate as sources of financing for investment in research and development in Russia—67%. The structure of research funding sources in Russia differs significantly from the structure of other countries. In Germany, the main source of funding for research and development is private business—66.2%. In Spain, Italy, the United Kingdom and Sweden, the share of private business in R&D investment also prevails over other sources of funding. Thus, we can conclude that the state makes rather large investments in innovation, while it is not efficient enough. It is necessary to establish the reasons why entrepreneurs in Russia do not show sufficient interest in financing research and development. Also noteworthy is the fact that the share of foreign sources in Russian research and development is 2.3%. While the UK attracts 15.6% of foreign funds in its development, Italy—11.7%, Sweden—10.1%.
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Table 6 Structure of internal expenditures on research and development by funding sources in 2018, % Countries
Internal research and development costs
State funds
Business sector funds
Other national sources
Foreign sources
Russia
100
67.0
29.5
1.1
2.3
Germany
100
27.7
66.2
0.3
5.8
Spain
100
38.9
47.8
5.1
8.2
Italy
100
32.3
53.7
2.3
11.7 15.6
UK
100
26.3
51.8
6.4
France
100
32.4
56.1
3.7
7.8
Sweden
100
25.0
60.8
4.0
10.1
The reasons why entrepreneurs in Russia show little interest in innovation can be [7]: • the lack of formation of state policy in relation to private investment in innovation; • insufficient experience in creating and promoting innovative products on the market, as market relations in Russia were formed not so long ago in comparison with other countries; • a long payback period for innovation and investment projects, which causes mistrust among entrepreneurs in an unstable economy, economic sanctions and a pandemic (2020–2021); • a high level of monopolization in the Russian economy and, accordingly, a low level of competition; • weak information support for innovative projects and innovative activities in general; • imperfection of the copyright protection system in Russia; • difficulties with the commercialization of the results of innovative activities. In order to attract entrepreneurs’ funds into innovative activities, it is necessary to develop public–private partnerships. The mechanism of public–private partnership implies the participation of private business in innovative activities with guaranteed support from the state. The development of public–private partnerships in Russia is a very promising area, primarily because Russians show very high confidence in the state and cooperation with it. Also relevant are the problems of tax incentives for innovation, creating a favorable climate for innovation and investment. It is necessary to create additional financial instruments, mechanisms to support innovation and investment activities [1]. In his message to the Federal Assembly in April 2021, the President of Russia emphasized the importance of supporting entrepreneurs who channel funds for the development of entrepreneurship. The mechanism of special investment contracts has
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also been improved with the help of a new instrument—an agreement on the protection and encouragement of investment. It is proposed to reduce risks for investing private capital, to help create new markets and investment mechanisms within the framework of the Project Finance Factory. Low interest in investments in innovative activities of Russian enterprises (organizations) on the part of foreign investors can be caused by the same reasons: political, imperfect legal framework, high business risks. However, I would like to outline another reason why foreign companies are in no hurry to cooperate with Russian organizations. This reason is the incompatibility of many economic terms and concepts, a different approach to calculating many indicators of project payback and the cost of innovation. Any innovative projects related to the development of investments are accompanied by a pool of documentation of a different plan—legal, organizational, financial, technological content. The legal aspect related to the distribution of profits from the development of investments depending on the size of the investment raises big questions for potential investors [8]. In the practice of Western companies, before the start of the investment process, drawing up a business plan for the development of a certain amount of money. Such a plan should contain information on relevant expenses and incomes so that all alternatives can be considered. In addition, the market capacity is calculated, the possibilities of geographic segmentation. The most important part of the business plan is to determine the sources of financing for the innovation and investment project. This part of the business plan contains the estimated costs and payback periods, and, therefore, its effectiveness. As practice shows, investors are more actively investing in an enterprise with already existing significant investment potential, primarily with their own sources of financing. Accumulated depreciation and retained earnings can be considered as such at Russian enterprises. The mechanism for calculating depreciation involves the transfer of the value of the depreciable property to the cost price or expenses in parts over the entire useful life of the object. As a result of the sale of these products, the company’s accounts accumulate an amount that exceeds the actual costs of production by the amount of profit plus depreciation. In this way, a reserve is created for replacing equipment retired due to deterioration with a new one. This source of funding can also be directed to a new, innovative project. The self-financing reserve due to amortization, in contrast to profit, is not taxed and is available even to unprofitable organizations, since it is dispersed in other assets. Consequently, in the composition of the contractual value of the sold products, depreciation is received by the enterprise in the form of money, which can be used to acquire other highly liquid assets. In this context, depreciation can be reasonably included in the sources of funding for innovation. However, there is another way of looking at this phenomenon. In particular, International Financial Reporting Standard No. 36 "Impairment of Assets" recommends writing off the amortization accrued for the reporting period from net profit, i.e. do not consider it part of the cost of production. In this sense, the accrued depreciation is simply a loss to the organization (Official website of the State Statistics Service of the Russian Federation). And,
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although this standard is approved for use by Russian enterprises, in this matter it conflicts with other Russian regulatory documents. So, the Chart of accounts of accounting and the instructions for its use established the accrual of depreciation by including it in the composition of production costs, the formation of a depreciation reserve is not provided. This, of course, reduces the value of reporting information as a reliable source of information for potential investors. It should be noted that the financial statements continue to be, in fact, the only source of reliable information about the organization. However, there is no information on accumulated depreciation in the reporting forms that are required to be submitted. This information is contained in the Notes to the Balance Sheet and the Statement of Financial Performance, which are by no means all Russian enterprises compiled and presented to users. In addition to the differences described above in the definition of economic processes and their consequences in Russian accounting standards and those that guide potential investors, there are others. So, at some points, the recognition of revenue, established by PBU 9/99 "Income of the organization" does not coincide with the interpretation of revenue in IFRS 18 "Revenue". For example, in terms of recognition of shipped products as income in export trade (Official website of the State Statistics Service of the Russian Federation). Such discrepancies affect the indicator of retained earnings, which is the main own source of investment financing. As a result of the above, it is rather difficult to determine the degree of the organization’s provision with its own sources of funding from Russian public reporting. Russian legislators are still faced with the task of adapting statutory and legislative acts governing accounting, and, accordingly, the reporting of Russian enterprises with IFRS.
4 Conclusion It is necessary to note the increasing role of work on the formation of reporting information adapted to IFRS and other foreign standards in order to attract the attention of investors to Russian enterprises as promising objects for the implementation of investment programs (Fig. 2). Measures to attract additional sources of financing for innovation and investment from private business can be: measures aimed at developing public–private partnerships, improving the legal framework, tax incentives for innovation and investment. To attract additional foreign investment, it is also necessary to improve the legal framework, as well as bring Russian and international accounting and reporting standards into line.
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Types of funding sources
Business sector funds
Development of public-private partnerships
Improving the legal framework
Foreign sources
Tax incen ves
Improving the legal framework
Alignment of interna onal and Russian accoun ng standards
Fig. 2 Measures to attract additional sources of financing in innovation and investment activities
Acknowledgements This work was realized in the framework of the Program of flagship university development on the base of the Belgorod State Technological University named after V. G. Shukhov, using equipment of High Technology Center at BSTU named after V. G. Shukhov.
References 1. Glagolev SN, Slabinskaya IA, Veretennikova II, Kovaleva TN, Atabieva EL (2012) Directions for improving the forms and methods of state regulation and economic incentives for investment activities. BSTU Publishing House, Belgorod 2. Domozhirova OV, Rudychev AA, Petlyuk A, Razuvaev NN (2017) Production potential of an industrial enterprise. Belgorod Econ Bull 2(86):65–70 3. Veretennikova II, Kovalyova TN, Schechovzov VV (2013) Improvement of capital investments structure as direction to increase fixed assets efficiency. World Appl Sci J 25(2):222–226. https:// doi.org/10.5829/idosi.wasj.2013.25.02.7055 4. Veretennikova II, Kovalyova TN, Laboda EN (2013) State regulation of investment processes of simple and expanded reproduction of fixed capital. World Appl Sci J 24(12):1681–1685. https:// doi.org/10.5829/idosi.wasj.2013.24.12.7041 5. Doroshenko YA, Malykhina IO, Somina IV (2020) Regional innovative development in the context of current trends of neoindustrialisation. Econ Reg 16(4):1318–1334. https://doi.org/10. 17059/ekon.reg.2020-4-21 6. Doroshenko YA, Malykhina IO, Brezhnev AN (2017) A Model for initiating investment projects as a tool for enhancing the investment and innovative activity of the region. Bull BSTU 6:178– 181. https://doi.org/10.12737/article_5926a05a9394b9.08350587 7. Atabieva EL, Tumin TA, Rudychev AA et al (2012) Directions for improving the forms and methods of state regulation and economic incentives for investment activities. BSTU Publishing House, Belgorod 8. Bozhkov YN, Kovaleva TN, Nosov SM (2016) Specificity of investment processes in the Russian economy. Bull BSTU 8:246–250
Quality Management in Modern Business and Transport Business Activities Anatoly Stepanov
and Natalya Mityakina
Abstract The paper deals with the modern conditions of business activity and transport business activities, analyzes the concepts of “quality” and “competitiveness”, given in various literature sources, provides a formula for competitive quality (1) that best meets its essence. It is stated that the emerging trends to achieve an advantage in business by non-market methods are unacceptable, as they lead to the degradation of the principles of the market economy. It is emphasized that the quality management of the transport enterprise (organization) shall be carried out on technology project management providing the project manager in the rank not below deputy managing director for quality, the project team trained professionals in the field of quality, able to perform all this extensive work. The requirements for the conditions for training such specialists in accordance with the previously valid and currently implemented Federal State Educational Standard of Higher Education in the field of training 27.03.02 Quality Management are given. It is concluded that the status of such a specialist—“bachelor”—is insufficient for modern transport enterprises and organizations. It would be advisable to have a “specialist degree” in this area of training with the status of an “engineer-manager” for graduate, taking into account the importance of ensuring competitive quality at the current stage of development of market relations in Russia. Keywords Quality management · Business activities · Product · Service · Transport enterprise · Transport sector · Transport organization · Coefficient of competitiveness
1 Introduction Quality, as a characteristic of product properties, has always been and still is of great practical importance for people’s lives. Modern production is the production A. Stepanov · N. Mityakina (B) Belgorod State Technological University Named After V. G. Shukhov, 46, Kostukov Street, Belgorod 308012, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_73
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of high-quality products. The quality of products is a kind of symbol of today’s economy of the enterprise. As modern managers note, quality is not a slogan, it is a whole philosophy in which cost reduction, labor productivity growth, are replaced by product quality, which has come to the fore. Modern conditions of business activity are characterized by a sharp increase in competition, turning it into a realistic basis for the survival of an enterprise or organization, ensuring their stable position in the global world market. These circumstances lead to a natural increase in the role of quality management as the main tool that allows enterprises and organizations operating in both production and non-production areas to achieve sustainable success and ensure their competitiveness in existing sales markets. When an enterprise has a well-organized quality management system aimed at the interests of consumers, affecting all its divisions and acceptable to all staff, then the results of the enterprise activities allow creating competitive products, and therefore achieve success in the business it carries out.
2 Research Methodology The aim of the research carried out in this paper is to consider the reasons and factors that determine the success of business activities, which ultimately are reduced to quality management issues in the production of specific products or services. The technology of quality management of products or services provided at an enterprise or organization includes the implementation (solution) of a number of different issues of their activities, each of which in one way or another affects the final result—the creation of competitive products (services). The paper considers both these issues themselves and the degree of their significance, so that the company can determine what it needs to pay special attention to in its activities, as well as what means and methods, what human resources can be used to solve the problem of creating competitive products (services).
3 Results 3.1 Quality as the Basis of Business Competitiveness Today, it is the high quality of products or services that is the most significant component that determines their competitiveness. In modern management, there are different definitions of quality. Quality is compliance with a standard; application; cost; hidden needs; public and global environment, etc. The current international standards for quality systems ISO 9000 series define quality as follows: “Quality is the totality of the characteristics of an object
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related to its ability to meet established and anticipated needs”. In other words, quality is nothing more than the degree of customer satisfaction. Only with this interpretation the quality can be competitive. In modern market economy, they cannot expect an enterprise or organization to be selected as a supplier of products (services) only on the basis that they are present in a particular market. The consumer chooses the one who will offer him the most value for money according to the criterion of his satisfaction, that is, the quality is calculated using the formula (1): Q = Cs =
V C
(1)
where Cs—customer satisfaction; V —product value from the consumer’s point of view and values; C—costs that a consumer can afford when purchasing a product or service. Thus, the consumer in each case compares alternative offers, measured by the ratio V C which in fact is the coefficient of customer satisfaction. Enterprises and organizations competing in sales markets should work to increase this ratio as much as possible.
3.2 The Quality Measure is Dictated by the Consumer As any product or service cannot be sold for a long time below its cost price, each manufacturer (service provider) should take care that the cost indicator that determines their price in the sales markets is as low as possible. There are many different ways and factors to reduce the cost of products (services) [1–4]: reducing production costs by improving technology, improving labor arrangement, transferring production to regions with cheaper labor, etc., but all these possibilities are not unlimited. Sooner or later, the limit will come when further reduction of production costs will become almost impossible or problematic. Another thing is the numerator in the formula of the competitiveness coefficient V—“the value of products from the consumer’s point of view”, i.e. what corresponds to their needs and expectations. Only this part of the product (service) properties the consumer considered as a value.
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Product
Reliability
Service
Safety Durability Compliance with Ecological compatiAesthetic qualities Liking Affordability Politeness Mutual understandSensitivity Related services
Fig. 1 Criteria by which the value of products (services) is formed by the consumer
There are two main factors that characterize the perception of value from the consumer’s point of view: • the number of criteria that determine the value of products by the consumer; • the significance of these criteria and its change over time. The essence of the first factor can be illustrated in Fig. 1. And even this set of indicators may not contain the specific characteristics that the consumer needs and that are essential for them. As for the second factor—the significance of the criteria, it may include: • • • • •
compliance with the fashion requirements; supplier’s image; opinion of other consumers; past experience; the stability of the quality for a long time etc.
Advertising of products or services in the mass media, the Internet, the level and content of marketing activities at the enterprise (organization) is of great importance for the formation of this factor. All this makes it possible to say that quality is multidimensional, and the right choice of the necessary measure is the manufacturer’s art to stay in business for a long period.
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Successful work of the company in terms of establishing consumer values gives it the opportunity, even without reducing production costs, to increase the price of products (services) and get additional profit. There are many such examples in the world practice.
3.3 Compliance with the Standard as a Quality Measure The most important criterion for evaluating the competitiveness of products is compliance with the standard. If the product does not meet the requirements of a certain standard (ND), then there is no need to talk about its quality. Compliance with the standard is a kind of business card, an entrance ticket to sales markets. But whether products will remain in these markets and how long they will remain there depends on how the manufacturer will be able to offer “value for money”, i.e. create a competitive quality. Therefore, realizing that competitive quality is nothing more than customer satisfaction Q = Sc , the management of any enterprise or organization should focus their efforts on the forms and methods of achieving this satisfaction both today and in the near future. Here it is impossible to note the emerging trend, which is often used at the present time, primarily by the United States of America, when competitive advantage is provided by sanctions pressure on competitors or the introduction of trade duties on the products of competing firms supplied to the United States. This practice has nothing to do with competitiveness in global sales markets and leads to the degradation of the principles of the market economy.
3.4 Enterprise Management by Quality Criteria If only competitive products or services lead to success in business, then this means that work at any enterprise (organization, firm) should be built in such a way that only such products are offered to the consumer, i.e. the entire management system at the enterprise should be oriented and built to work according to the quality criterion. Taking into account that ensuring the quality and competitiveness of any product or service depends on many and various factors, in each case different for the corresponding product (service), it is logical to assume that all this work should be led and coordinated by someone, i.e. actually manage it. For small businesses this of course needs to engage the first head, and for the larger ones, including the dominant role of the first manager, this daily work should be referred to designated specialist not below the rank of deputy of first-person in the enterprise. In the previous version of the ISO 9000 series of international quality system standards (ISO 9001 2011 version), it was specified that such a manager should appoint deputy managing director for quality, as a specialist who helps the first
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manager to exercise his leadership in accordance with the principles of creating and operating quality management systems. In subsequent versions of this standard GOST R ISO 9001-2015 there is no such requirement, it is hardly appropriate; experience shows that the activities for quality management are more successful when the management of all processes of the quality management system at the enterprise, with the aim of creating a competitive quality will be ongoing responsible employee in the position of deputy director for the enterprise quality, as it was in the previous version of the standard.
3.5 Managing Quality Means Managing a Business In quality management, the arrangement of activities based on the international standards of quality systems ISO 9000 series is of great importance. The latest version of these standards—GOST R ISO 9001-2015 and GOST R ISO 9004-2019—is radically different from the previous version. This difference is not only that new concepts such as “organization environment” (organization context), “documented information”, “risk-based approach” are introduced, but also long-used concepts are formulated differently: “products and services”, “quality guidelines”, “quality management principles”, etc. The main difference between the new version of the ISO 9001:2015 standard is that it positions itself as a standard for the business management system. Among all the processes of the quality management system, the main role in this standard is assigned to business processes. The ISO 9001:2015 standard is therefore an integral part of the organization overall business plan. Therefore, the effective functioning of business processes should be directed to the efforts of the entire team of the organization with the leading role of the first manager. Business processes are, when implemented, the basic foundation of a successful business, as the goals of any enterprise or organization. In essence, the ISO 9000 series quality management system standards in their latest version are business management standards.
3.6 Project Approach to Quality Management Practice also shows that quality management in an enterprise (organization) should be considered and implemented as a project, using a well-known project management mechanism. This means that at any enterprise (organization, firm), a project team should be created, including representatives of all categories of employees whose activities are directly or indirectly related to quality assurance and competitiveness (Antonina, 2011), i.e., the quality management work should implement the principle laid down
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in the international quality system standards ISO 9000 series, which provides for the “involvement of employees” at all levels in quality assurance work in order to use their abilities to benefit the image of the enterprise [5]. Among these employees, a special role is assigned to specialists in the field of quality management [6, 7] who should be in each organization (enterprise) in sufficient quantity to solve quality management problems. These employees can work independently, or they can be grouped into groups or departments (for example, “Quality Management Department”). At the same time, the principle of involvement of the entire team in quality work should be unconditionally observed, so as not to shift the solution of quality problems only to these specialists [8, 9].
3.7 Training Specialists for Quality Management Such specialists in the status of “bachelor” are currently trained in many universities located in almost all regions of Russia, implementing the training direction 27.03.02 “Quality Management”, the state educational standard of higher education, which was approved by the Ministry of Education and Science of Russia on February 9, 2016. It should be noted that the specialty “Quality Management” was introduced in Russia in the late 90 s of the XX century as a response to new requirements related to the transition of the country’s economy to market relations. At first it was the educational program codes 340100, 220501—specific standards of 1 generation, according to which the professional qualification was defined as “engineer-manager”, and then there were areas of training 221400—standard of 2 generation and 27.03.02—standard of 3 and generation 3+ generation (Order of the Ministry of Education and Science of the Russian Federation No. 92, 2016) related to the bachelor degree and the qualification of specialists was called “bachelor”. Taking into account that such specialists are assigned a crucial role in quality assurance at the enterprise (in the organization), they must certainly have the appropriate qualifications and meet the requirements of a modern market economy. In our opinion, the status of “bachelor” for such specialists is clearly insufficient, they should have a higher status of “engineer-manager”, whose training, in accordance with the previously existing standards of the 1st generation, was more appropriate for the role that they should perform in a modern enterprise or organization. Therefore, for the direction of training “Quality Management”, the “specialist degree” is more appropriate and meets the requirements of the time, taking into account the importance of the problem of competitive quality for the modern Russian
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economy. Moreover, today this is the only specialty where the existing methods and tools of quality management developed by the entire world practice are fully studied, and therefore the management of the enterprise as a whole, carried out according to the quality criterion; no specialist of a narrow training profile has such knowledge today [7]. The peculiarity and uniqueness of this specialist in the field of quality is that the knowledge and skills they have gained in quality management are universal and can be applied in any field of activity, both production and non-production, i.e. where it is necessary to ensure high quality and competitiveness of products or services provided.
4 Discussion The review and analysis of the reasons and factors that determine the competitiveness of products (services) carried out in the main part of this paper allows ranking them by the degree of significance for the final result—success in business activities (business). These reasons and factors can be described as follows: 1— “value for money” or the degree (coefficient) of customer satisfaction; 2—quality measure as a consumer’s expectation; 3—standards as a necessary quality measure; 4—enterprise management by quality criteria; 5—project approach to quality management; 6—quality management as the business management; 7—personnel decide everything. If the final result of business success is represented as a circle, then the impact of each of the above factors can be more likely represented in Fig. 2. Special attention should be paid to factor 7—personnel, which occupies the largest segment of success—up to 30%.
Fig. 2 Significance of the factors of success in business
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2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
90 80 70 60 50 40 30 20 10 0
Fig. 3 Graduation of specialists in standardization and quality management at BSTU named after V. G. Shukhov in 2002–2019
Therefore, training specialists for quality management is of paramount importance. The status of such a specialist should be an engineer-manager, as it meets the requirements of the time from the point of view of employers and is in demand for admission to universities among applicants. To do this, it is enough to look at the dynamics of the graduation of specialists in quality management in the status of bachelor (today, since 2010) and engineer (previous years) (Fig. 3).
5 Conclusion The current practice of business activity shows convincingly that in market conditions, they cannot count on success in business without engaging in quality management on a highly professional basis, without purposefully managing all the activities of the enterprise according to the quality criterion. Acknowledgements This work was realized in the framework of the Program of flagship university development on the base of the Belgorod State Technological University named after V. G. Shukhov, using equipment of High Technology Center at BSTU named after V. G. Shukhov.
References 1. Kane MM, Ivanov BV, Koreshkov VN, Skhirtladze AG (2008) Systems, methods and tools of quality management. Piter, St. Petersburg 2. Okripilov VV (2013) Quality management. Science, Moscow 3. Fedyukin VK (2013) Quality management of production processes. KnoRus, Moscow
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4. Antonova II, Antonova VA et al (2020) Universal quality management. The founders of total quality management. Ruscience, Moscow 5. Vdovin SM, Salimova TA, Biryukova LI (2018) Quality management system of the organization. Infra-M, Moscow 6. Grodzensky S (2019) Quality management. Prosoekt, Moscow 7. Serenkov PS, Kuryan AG, Volontey VP (2018) Methods of quality management. Process approach. Infra-M, Moscow 8. Shemyakina TY, Selivokhin MY (2018) Production management: quality management. Alfa-M, Moscow 9. Danilova-Volkovskaya GM, Molchanov GI (2019) Quality management of performance of works amenities and services. KnoRus, Moscow
Transport and Industrial Construction as a Driver of Commercialized Innovations in Regional Production Systems Maria Starikova , Alexander Troshin , Stephanie Togba , and Larisa Denike Abstract The article summarizes the factors that determine the grow in volume of innovation products output in regional production systems. It was determined that the desire to diversify the sectoral structure of regional production systems should be based on an understanding of the leading role of construction as the sector of economy that support the perspective economic development. The hypothesis about the existence of a strong relationship between the volume of work in transport and industrial construction and the volume of output of innovative products in regional production systems has been put forward and confirmed. It is proved that in 2010–2018 in Russia there is a close relationship between the amount of commercialized innovations and the amount of work in the transport and industrial construction sphere. At the same time, the correlation between these parameters in different federal districts and subjects of the Russian Federation is not unambiguous. Therefore, Russian regions are classified according to the strength of the relationship between these parameters. It is concluded that, mainly, in the border regions, transport and industrial construction is not associated with the development of innovative industries and innovative infrastructure. Keywords Transport construction · Transport sector · Transport economic system · Industrial construction · Regional production system · Commercialized innovations
1 Introduction The Russian economy needs a transition from a resource-innovation strategy to an innovation-technological development paradigm, which is confirmed by scientists [1]. Despite the complexity of this transition, there are successful examples of such transformations in the world economy [2]. The noted obstacles to Russia’s M. Starikova (B) · A. Troshin · S. Togba · L. Denike Belgorod State Technological University Named After V. G. Shukhov, Kostyukov Street, 46, Belgorod 308012, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_74
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achievement of economic growth driven by innovations are the lack of state support for the development of industry-science cooperation [3], the lack of workers and managers with innovative style of thinking and innovative behavior [4], a low level of commercialization of innovations [5], low funding for science [6], etc. There are justifications for the growth of the stability of national economies to crises in the event of an increase in their innovative potential [7]. Innovation opportunities, along with human capital and successful business experience, are considered determinants of economic development [8]. A lot of research is aimed at finding ways and conditions to improve the efficiency of innovation [9, 10]. One of the important performance indicators is the ability of an innovative company to create jobs [11]. There are also studies showing the positive impact of partnership on the effectiveness of innovation [12]. At the same time, the economic return from partnership diversification has a limit and decreases as partners move away from the local market [13]. The relationship between the development of different sectors of the economy has been empirically proven. So, there are studies confirming the positive impact of a high level of diversification of the sectoral structure of the economy on technological growth and the intensity of innovation [14]. In some studies, an attempt was made to identify the priority sectors for ensuring successful economic development. In particular, the construction industry is considered by scientists as a production and technological mechanism that ensures the functioning and development of the national economy [15] The growth in demand for building materials indicates the strengthening of reproduction processes in the economy [16]. Naturally, one should take into account the pace of development of individual segments of the construction industry. The main ones are such segments as industrial, civil construction and construction of trade objects [17]. It should also be understood that investment demand only supported by the development of the educational and research environment can provoke the development of new business in the innovation sphere [18]. The volume of work in construction (especially in transport and industrial construction) is traditionally considered to be an indicator that gives advanced estimates of the future development of the economic environment. The growth in transport and industrial construction indicates an improvement in the economic situation and is a harbinger of stable development. In a modern economy, development is associated with innovation and their successful commercialization. Therefore, it is logical to assume that there is a stable direct relationship between the volume of activity in construction and the volume of innovative products produced. The purpose of the article is to study the relationship between the results of activities in transport and industrial construction and output of commercialized innovations in Russian regions production systems and the classification of regions from the point of view of the strategic orientation of innovative growth. At the same time, authors of this paper identify border regions as a special type of periphery, mainly forming differentiation in the regional economic development of Russia. The hypothesis of the study is the assumption that not in all Russian regions there is a stable relationship between the results of activity in transport and industrial
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construction and the results of innovative activity. Moreover, in some regions, a deeper differentiation of spatial development is manifested.
2 Materials and Methods The article proposes to analyze the correlation between the volume of transport and industrial construction and the volume of innovative products produced at the level of the region production systems of the Russian Federation. The initial data are the information published on the website of the Federal State Statistics Service of Russia (https://rosstat.gov.ru/). The regions of the Russian Federation will be classified according to the tightness of the established connection. Comparison of border and “internal” regions will make it possible to draw conclusions about the prospective sustainability of economic development.
3 Results The hypothesis put forward is confirmed empirically at the level of the Russian Federation. According to the values shown in Fig. 1, the regression equation (y = 0.827x – 1940.3) is obtained and there is a high determination (the coefficient of determination is 0.886) between the results of activities in transport and industrial construction (x) and innovations (y). The correlation coefficient (0.94) indicates a close relationship between the studied parameters. At the same time, the situation typical for the country as a whole does not always apply to the regions (Table 1). An extremely weak relationship between the parameters under study is observed in the Southern Federal District, where construction is mainly aimed at creating the infrastructure of the non-innovative service sector. The inverse nature of the Results of activity in transport and industrial construction, billion rubles 8386
7573
7213
4167
4516
2014
4364
2013
7010
6125 3580
2011
3843
6019 3508
2012
5714
5140 2107
4454 1244 2010
2873
Volume of innovative goods, works, services, billion rubles
2015
2016
2017
2018
Fig. 1 Results of activity in transport and industrial construction and results of innovation activity
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Table 1 Correlation between construction and innovation in federal districts of Russia Federal district
Correlation coefficient between the volume of work in transport and industrial construction and the volume of innovative products
Siberian Federal District
0.9552
Volga Federal District
0.8870
Ural federal district
0.8386
Central Federal District
0.7671
North Caucasian Federal District
0.7277
Northwestern Federal District
0.7239
Southern Federal District
0.2633
Far Eastern Federal District
–0.5031
relationship between the volume of transport and industrial construction and the innovations produced in the Far Eastern Federal District is due to a decrease in economic potential, an outflow of the population in the post-Soviet period. However, in the rest of the federal districts, there is a strong enough connection between the studied parameters, which allows confirming the hypothesis of the study. The contribution of the border and “internal” regions of Russia to the formation of the volume of transport and industrial construction and innovations is shown in Table 2. The contribution of border regions to the volume of transport and industrial construction is decreasing, while their role in the production of an innovative product grows, which from 2010 to 2018 increased from 28 to 37%. The classification of Russian regions according to the relationship between the volume of transport and industrial construction and the volume of innovations is presented in Table 3. A feature of border regional economic systems is the presence in their structure of a fairly large number of subject of the Russian Federation, which are characterized by an inverse relationship between the commercialized innovations and the intensification of construction activities. Transport and industrial construction in these territories is not associated with the development of innovative industries and innovative infrastructure. These subjects of the Russian Federation determine the presence of deeper differentiation in the levels of regional development of border regions in the near future.
4 Discussion Construction is viewed as an industry, the development of which determines the long-term economic development of the country and its regions. During the analyzed
65.39
7.5
49.01
12.44
The total share of “internal” regions in the volume of transport and industrial construction, including:
share of Moscow
The total share of “internal” regions in the volume of manufactured innovative 72.21 products, including:
share of Moscow
5.2
10.68
27.79
The total share of border regions in the volume of manufactured innovative products 49.44
34.61
50.56
50.99
The total share of border regions in the volume of transport and industrial construction
2011
2010
Indicator
17.2
69.54
10.67
51.19
30.46
48.81
2012
19.6
72.49
11.20
51.77
27.51
48.23
2013
15.4
70.53
11.99
53.57
29.47
46.43
2014
22.2
77.01
11.50
52.80
22.99
47.20
2015
20.9
72.26
12.15
54.19
27.74
45.81
2016
6.0
63.05
12.03
53.93
36.95
46.07
2017
6.3
63.22
10.79
51.79
36.78
48.21
2018
Table 2 Shares of border and “internal” regions of Russia in the formation of the results of activities in transport and industrial construction and innovative products, percentage
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Table 3 Classification of regions according to the correlation between transport and industrial construction and commercialized innovations Correlation
Border regions of the Russian Federation
“Internal” regions of the Russian Federation
High direct
Rostov Region Kaliningrad Region Kursk Region Voronezh Region Omsk Region Altai Region Republic of Altai Kamchatka Territory Novosibirsk Region Republic of Karelia Sevastopol Tyumen Region Belgorod Region Pskov Region
Krasnoyarsk Region Republic of Bashkortostan Republic of Tatarstan Nizhny Novgorod Region Lipetsk Region Sverdlovsk Region Moscow Region Tula Region Yaposlav Region Stavropol Region Republic of Adygeya Ryazan Oblast
Noticeable direct
Chelyabinsk Region Kurgan Region Orenburg Region St. Petersburg Bryansk Region Republic of Crimea Leningrad Region
Perm Region Tomsk Region Samara Region Komi Republic Ulyanovsk Region Tambov Region Kaluga Region Vladimir Region Republic of Mari El
Moderate direct
Arkhangelsk Region Murmansk Region Republic of Tuva Chukotka Autonomous Area Saratov Region Sakhalin Region Smolensk Region Magadan Region
Udmurtian Republic Chuvash Republic Republic of Mordovia Irkutsk Region The Republic of Sakha (Yakutia) Moscow Kirov Region
Weak direct
Astrakhan region Jewish Autonomous Region Republic of Kalmykia Republic of Ingushetia
Kemerovo Region Novgorod Region Kostroma Region Penza Region Tver Region
Weak indirect
Primorye Territory Republic of Buryatia Trans-Baikal Territory Chechen Republic Republic of North Ossetia—Alania Volgograd Region Republic of Dagestan
Republic of Khakassia Vologda Region
Moderate indirect
Krasnodar Territory
–
Noticeable indirect
Amur Region Khabarovsk Territory
Ivanovo Region (continued)
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Table 3 (continued) Correlation
Border regions of the Russian Federation
“Internal” regions of the Russian Federation
Strong indirect
Karachayevo-Circassian Republic Kabardino-Balkarian Republic
Orel Region
period in Russia, transport and industrial construction acted as a driver of innovationoriented economic development. The Volga, Ural and Siberian federal districts made the greatest contribution to the formation of this stable connection. The least weak correlation between volume of transport and industrial construction and volume commercialized innovative products is noted in the Far Eastern and Southern Federal Districts, that shows not high level of prospective economic development there. The border regions of the Russian Federation demonstrate a higher level of differentiation in various aspects of economic development than the “internal” regions. The same trend is observed in terms of the relationship between the volume of transport and industrial construction activities and the volume of commercialized innovations. In most of the border regions, there is a need to increase investment in construction, which we consider as a guarantee of future innovative growth of industry and reducing the severity of the “center-periphery” problem.
5 Conclusion The assessment of the level of correlation between the volume of transport and industrial construction and the volume of manufactured innovative products by regions of the Russian Federation, carried out in the article, confirmed the hypothesis of the existence of a significant gap in the quality of spatial innovative development between Russian regions, and also made it possible to group the regions according to their strategic orientation of innovative growth in the branches of industry. Acknowledgements This work was realized in the framework of the Program “Priority 2030” on the base of the Belgorod State Technological University named after V. G. Shukhov, using equipment of High Technology Center at BSTU named after V. G. Shukhov.
References 1. Ivanter VV, Komkov NI (2007) Innovation-technological development of the Russian economy: prospects and conditions. Stud Russ Econ Dev 18:239–249 2. Cao X, Xi Y, Zeng X (2008) Upgrading resource-based regional industrial clusters to innovative clusters: the case of Shanxi province in China. Asian Bus Manag 7:277–295
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3. Roud V, Vlasova V (2020) Strategies of industry-science cooperation in the Russian manufacturing sector. J Technol Transf 45:870–907 4. Medvedeva TA (2012) Developing an innovative style of thinking and innovative behavior. Syst Pract Action Res 25:261–272. https://doi.org/10.1007/s11213-011-9221-9 5. Schetinina ED, Doroshenko YuA, Ovtcharova NV (2015) The problems of innovations commercialization and approaches to their decision. Int Bus Manag 9(6):1074–1078. https:// doi.org/10.36478/ibm.2015.1074.1078 6. Ryapukhina VN, Doroshenko YuA (2018) The problem of financial support for science in the context of its effective integration into the innovative system in Russia. Bull BSTU 6:135–146. https://doi.org/10.12737/article_5b115a73de6619.74703623 7. Bristow G, Healy A (2018) Innovation and regional economic resilience: an exploratory analysis. Ann Reg Sci 60:265–284 8. Robson PJA, Akuetteh CK, Westhead P et al (2012) Innovative opportunity pursuit, human capital and business ownership experience in an emerging region: evidence from Ghana. Small Bus Econ 39:603–625 9. Niebuhr A, Peters JC, Schmidke A (2020) Spatial sorting of innovative firms and heterogeneous effects of agglomeration on innovation in Germany. J Technol Transf 45:1343–1375 10. Colombelli A (2016) The impact of local knowledge bases on the creation of innovative start-ups in Italy. Small Bus Econ 47:383–396 11. Rodríguez-Gulías MJ, Rodeiro-Pazos D, Fernández-López S et al (2021) The effect of regional resources on innovation: a firm-centered approach. J Technol Transf 46:760–791. https://doi. org/10.1007/s10961-020-09811-8 12. Doroshenko YuA, Starikova MS, Somina IV, Malykhina IO (2019) Increasing the efficiency of high-tech companies based on interactions with the entities of the innovative environment. Econ Reg 15(4):1279–1293. https://doi.org/10.17059/2019-4-24 13. D’Ambrosio A, Gabriele R, Schiavone F et al (2017) The role of openness in explaining innovation performance in a regional context. J Technol Transf 42:389–408 14. Woerter M (2009) Industry diversity and its impact on the innovation performance of firms. J Evol Econ 19:675 15. Kamenetskii MI (2013) Construction sector as a factor of prospective development of the national economy. Stud Russ Econ Dev 24:249–258. https://doi.org/10.1134/S10757007130 30052 16. Budanov IA (2011) Involvement of resources in Russia’s construction materials complex. Stud Russ Econ Dev 22:31–43. https://doi.org/10.1134/S1075700711010023 17. Horta IM, Camanho AS, Johnes J et al (2013) Performance trends in the construction industry worldwide: an overview of the turn of the century. J Prod Anal 39:89–99 18. Fritsch M, Aamoucke R (2013) Regional public research, higher education, and innovative start-ups: an empirical investigation. Small Bus Econ 41:865–885
Express Assessment of Business and Marketing Environment of an Industrial and Transport Enterprise on the Basis of Probabilistic-Attributive Approach Assessment Ekaterina Schetinina , Elena Krasnoperova , Elena Schetinina , and Yuri Bogkov Abstract The article is devoted to the development of tools for analysis and assessment of the business environment (BE)—including marketing one—of an enterprise of various industries including transport sector. The factors affecting BE have been clarified, in particular, digitalization, networkization, changes in thinking formats, the emergence of new institutions, transformation of legislation, increasing turbulence in global economy, consumption trends changing, and environmental restrictions. The existing approaches to BE assessment are generalized, the incompleteness of the existing methods and the necessity in express methods are revealed. The authors propose a method of express assessment of BE of an industrial enterprise on the basis of probabilistic-attributive approach by a combination of digital information and semantic characteristics. The methodology takes into account various sub-environments and key factors of BE and proposes its extended structural and logical model with appropriate indicators. The proposed methodology is intended for making management decisions by business corporations, developing business and marketing strategies as a flexible response to changes in the environment. The results of approbation of the methodology in the regional market of ventilation equipment are presented and an overview of its state at the beginning of 2021 is made. Keywords Management · Business environment · Assessment of business environment · Transport industry · Transport enterprise
E. Schetinina (B) · E. Krasnoperova · Y. Bogkov Belgorod State Technological University Named After V.G. Shukhov, 46, Kostyukov Street, Belgorod 308012, Russia E. Schetinina Saint Petersburg State Technological Institute (Technical University), 26, Moskovsky Prospect, St. Petersburg 190013, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_75
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1 Introduction Any enterprise is exposed to a certain living environment—physical, technological, social, economic, psychological, creating both resistance to business and «following waves». There is almost no neutral environment. Another thing is that the environment may differ in the level of dynamism, favour, predictability, formality and other characteristics. But in any case as a system it includes a number of known elements: legal aspect, procedural and economic, technological, social ones. Qualitative assessment of business environment (BE), including industrial and transport business—the basis for managerial decisions—to build a business model, the choice of design strategies [1], suppliers and partners, market segments, production volumes, etc. Therefore, the accuracy and objectivity of the assessment and forecast of BE are extremely important for the management of any organization, identifying the framework and conditions of business activity, setting the current and target parameters of the company. BE and its assessment are attracting more and more attention from the theoreticians, practitioners and experts, as profits from the product are generated in the outsider business environment to a much greater extent than in the insider one. However, the existing approaches to the analysis and assessment, fare and quite accurate study of BE do not meet contemporary requirements. They need modification with the account of digitalization, networkization, change of thinking formats [2], transformation of the legislation of many countries, the growing turbulence of world economy [2, 3], consumption tendencies, ecological issues and limitations [4, 5]. Absence of the integrated system of BE assessment, taking into account digitalization and new values of the society, vividly testify to the complex character of the problem under consideration [6, 7]. A number of classical works are devoted to the study of BE and methods of its assessment, starting with M. Porter and F. Kotler and J. Evans. Summing up the definitions, it can be concluded that BE is a complex of factors of immediate environment of the organization, which include factors of supply and demand, as well as technology, business conditions, risks, investment and financial structure. In our opinion, it is a set of sub-environments, closely related to each other. There exist different aspects of BE—for example, Alexandrin distinguishes the initial (amorphous) environment and the developed, which is able to cause an impulse [8], and this is what the authors consider its purpose. Indicative methods, modeling, scenario approaches, ratings of companies and regions, and expert opinions are traditionally used to assess a company’s BE. In business community, the concept of «business activity» is widespread, in particular, investment activity, innovation activity, indices of entrepreneurial confidence, the number of transactions on the stock exchange. The World Bank methodology (https:// www.doingbusiness.org/en/rankings) also addresses a number of BE indicators: it ranges countries by 10 criteria, including: access to banking resources, trading across borders, taxes, enforcing contracts, etc. The evolution of approaches to the analysis and assessment of BE is presented in Table 1.
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Table 1 Evolution of approaches to the analysis and assessment of the business environment Stages
Principles, approaches and distinctive features
1880–1935
Awareness of the needs and consumption potential, competitors
1946–1975–present
Cyclicity and its allowances (technological waves and economic stages, life cycle of enterprises and product)
1960–1980–present
Existence of micro- and macroenvironment, M. Porter’s five competitive forces and "competitive diamond", PEST analysis, GAP analysis, etc
1980–present
Competitive analysis, dynamic trends and models, the World Bank methodology
1985–present
Index methods, business activity (BA), including global (PMI index) and average values of BA by enterprises of industry, region, country
1990–present
Consistency, complexity, holistic approach, turbulence awareness, environmental analysis
2000–2021 and further The observer’s influence on the observed object (Hawthorne effect), BE management on the basis of digital platforms and «big data», taking into account the concept of social ethics of business, narrative approach
It seems methodologically important to specify what is changing in the content of the BE analysis today—whether there are new concepts that clarify its essence, new objects of analysis, new relationships, etc. These can be new threats (biological), new environments (digital), types of position of firms (socially-oriented), competitive capability and its drivers, methods of influencing the target audience, elimination of the human factor in decision-making. So, environmental requirements of the social and business environment are especially important for transport enterprises. In any case, the assessment of such a complex phenomenon should be integrative, multi-dimensional. The combination of quantitative and qualitative approaches is the most acceptable for carrying it out, so there is a problem of quantification of non-numerical parameters. Another open question is the inclusion in the assessment of BE of marketing parameters, usually obtained on the basis of PEST, SWOT and GAP analysis. Some authors tend to equate these concepts though BE is a broader concept due to the fact that it implies legal and technic-technological aspects of doing business, in view of which the assessment of the marketing environment, in our opinion, should complement and clarify the assessment of BE. There are a number of differences in the set of parameters of BE assessment depending on the level of the business object: industry, market, regional, national, global. At the industry level such indicators are used as the dynamics of the industry’s share in the gross product of a region or country, barriers to entry into the industry/market, rates and directions of price changes, tariffs, tax conditions, preferences, etc.
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2 Methods The methodology of analysis and assessment of BE, in addition to systematic and logical approaches, should take into account both the development of economic theory, marketing management of external and internal environment of the enterprise, and practical experience gained in this area at the beginning of the XXI century. Thus, a BE can be described with a greater or lesser accuracy by a number of parameters reflecting its key properties. This is a specific database or a fragment of it, structured information. From the standpoint of the attributive approach, information is an immanent property of the material world. And then the information is a measure of order, of structuredness of any system. Otherwise making the significance is a functional approach. So we believe the solution lies in a combination of these approaches: Attribute + Significance = Decision making basis Significance is given to information based on the narratives, values and motives of society and its individuals. It is closely linked to the expectations of market participants and society and creates a business environment, especially marketing one. The business environment is specific (tied to place, time and industry) and has a complex structure, including interconnected sub-environments, which can be described by a group of quantitative parameters and attributive properties of the environment. Thus, the multidimensionality of the assessment in the methodology proposed is that—on one hand, the information in the form of numbers reflecting the various parameters of the sub-environments, and on the other hand, meanings (semantics or «letter»): stability, convenience, profitability, riskiness, progressiveness—are used. Table 2 presents a structural and logical scheme of multidimensional assessment of BE on the example of the ventilation equipment market (VEM) in the region (Belgorod region, Russia) based on the attributive approach. Each parameter (level— L) is assessed on a 3-point scale according to the established positive or negative degree in relation to the above semantic properties of the sub-environment: stability, attractiveness, etc. The scale of the express method is intentionally simple: 1, 2 and 3 correspond to the low, medium and high level of the attribute, respectively. The indicator aggregated for a particular sub-environment is calculated using the formula (1):
Lec.tot =
4 1
Lec. f /
4
Lec.max
(1)
1
where Lec.tot—aggregated indicator for the economic sub-environment (in points), Lec.f —values of individual indicators for the economic sub-environment (1–3 points), Lec. max—the highest economic sub-environment score (3 points).
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Table 2 Structural and logical scheme of express assessment of the business environment Sub-environment
Indices and characteristics
1. The economic Stage of an environment reflects economic the level of stability of cycle the economy
L ec.1 = 1.2
Sales volume in the industry, % or index of the physical volume of the industry
Inflation, %
Profitability (average) for the industry in the regional context, %
L ec.2 = 1.4
L ec.3 = 1.2
L ec.4 = 1.6
Assessment L ec.tot
L ec.tot = 5.4/12 = 0.45
2. Investment environment—reflects the level of opportuneness
Key interest Business rate, credit cost confidence index (investment security)
Dynamics of investments in fixed assets
Clarity of the "game’s rules", protection of investors’ interests
L inv.1 = 2.2
L inv.3 = 1.0
L inv.4 = 1.3
Assessment L inv.tot
L inv.tot = 5.7/12 = 0.44
3. Organizational and infrastructure environment—reflects availability of business services
Acceptability of entry barriers by cost, preferences
Availability of business services (cost and technical)
Formalization and Transportation transparency of and logistics business relations system
L org.1 = 1.8
L org.2 = 2.5
L org.3 = 1.6
L org.4 = 2.6
Assessment L org.tot
L org.tot = 8.5/12 = 0.69
4. Marketing environment reflects market attractiveness
Purchasing power of the population (cash income / minimum living wage)
Market capacity with the account of the density of competition
Cost of marketing communications (customer acquisition cost)
Ability to achieve key success factors and customer expectations
L mar.1 = 1.0
L mar.2 = 1.6
L mar.3 = 1.4
L mar.4 = 1.9
L inv.2 = 1.1
Assessment L mar.tot
L mar.tot = 5.8/12 = 0.48
5. Digital environment—reflects the depth of digitalization of business processes
Share of users with broadband Internet access
Impact of digitalization on commercial success
Share of digital Business technologies in compliance business processes with digitalization requirements
L dig.1 = 2.4
L dig.2 = 2.7
L dig.3 = 1.0
Assessment L dig.tot
L dig.4 = 1.7
L dig.tot = 7.8/12 = 0.63
The aggregate indicator for other sub-environments is calculated in the same way. Table 2 shows a scheme of express assessment of the BE of an industrial enterprise.
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3 Results and Discussion As you can see, the analysis of BE involves several aspects. First of all, current models of the market economy take into account and also assess the stability and sustainability [9]—in this case—of the industrial market, where the company operates or intends to operate. Its basic characteristics are the stage of the economic cycle, gross product, inflation, profitability within the industry. The semantic attribute of community expectations is stability. For VEM the current (at the time of assessment) economic stability is estimated as 0.51, which is at the average level. However, taking into account the probability coefficient (1–4 for economics) the values can be adjusted (Table 3). The scale for assessing the probability, determined by the expert method, is shown in Table 4. The second aspect is business, primarily investment, activity of a company. It implies competitive activity as well and is assessed by the number of transactions, for example, in the market of securities, real estate, insurance services, including, by their types. It also takes into account the prices of finished products and the prices of cost components, their tendency, the amount of proceeds, profitability, the level of employment, new orders [10, 11]. The study of the factors which limit the activities of enterprises and organizations of basic sectors of the economy in 2020, conducted by the Center for Economic Research of the Institute of Statistical Research and Knowledge of the National Research Institute Higher School of Economics (NRU HSE), showed that the most negative factor was insignificant demand for products and services. Of the 25 thousand surveyed enterprises, this was noted by 63% of trading companies and by 50% of manufacturers [12]. As we see from the results obtained, the investment environment and its opportuneness, risks and conditions of obtaining credit resources on VEM in Belgorod region are assessed at the level (L inv.) of 0.41, which is lower compared to the average in terms of its opportuneness, taking into account only 0.4. This can be considered insignificant, so the sub-environment practically does not change. The organizational and infrastructural sub-environment characterizes the comfort for business in terms of the development of the business services market, the organization of business processes in terms of their smooth operation, the requirements for their formalization and unification, and other infrastructure elements, including logistics. For VEM this indicator (L org.) is estimated as 0.69, which is above average, but taking into account the probability of possible changes—as 0.54. This deterioration is associated with an increase in transaction costs, namely, opportunistic behavior, transportation costs, as well as high barriers to entry into this market. The marketing sub-environment reflects a number of factors influencing the market position of the company, its product orientation and behavior strategy, types of promotion, marketing intensity, etc. To assess the behavior of consumers, in addition to the known methods of studying and testing demand, we recommend using a questionnaire that includes the following questions: a) your professionalism in product selection; b) what benefit is most important to you when buying a product; c) your dominant values. The importance of questions in this formulation follows
Adequacy of digital environment
Marketing attractiveness
Organizational and infrastructural opportuneness
1.2 1.1 1.0
2.7
1.0
1.7
1.0
1.9 1.1
1.3
1.4
2.4
1.3
1.0
2.6
1.7
0.8
1.6 1.0
0.7
1.0
1.0
0.9
1.4
2.5
1.0
1.0
1.8
1.1
1.1
0.9
1.6 0.7
1.0
1.2
2.2
0.8
1.4
Investment attractiveness
1.2
1.2
Economic stability
1.70
1.10
3.24
2.62
1.90
1.82
2.21
1.00
2.60
1.28
1.55
1.80
1.26
1.0
1.21
1.54
1.44
1.20
1.12
1.49
Coefficient of probability Adjusted of change sub-environment parameters
Level of sub-environment assessment (L1–4)
Sub-environment attribute
8.68 (0.74)
6.93 (0.59)
6.43 (0.54)
5.01 (0.41)
5.25 (0.42)
Final sub-environment assessment (12-score system)
Table 3 Results of BE assessment for VEM of Belgorod region on the basis of probabilistic-attributive approach
+0.88 improvement
+0.11 slight improvement
– 0.15 slight deterioration
– 0.03 practically unchangeable
– 0.04 practically unchangeable
Sub-environment BE trend
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Table 4 Scale of probabilistic assessment of environment changes and adjustment factors Probability range and the type of changes
Coefficient values, in fractions of 1 0–25%
26–50%
51–75%
75% and above
Negative
1.0
0.9
0.80
0.7
Positive
1.0
1.1
1.2
1.3
from Levitt’s remark about that economics provides answers, but there is a shortage of correctly asked questions [13]. According to our methodology, the level of marketing attractiveness (L mar.) for VEM is assessed as 0.48. This parameter is most affected by the possible growth of demand and market capacity due to the increase in average annual temperatures. Thanks to this, as well as due to the predicted reduction in communication and advertising costs in the context of further digitalization, according to probabilistic assessment, the marketing sub-environment in this market will improve to 0.59. Considering the digitalization trends and the opinions of many authors [6, 14– 16], the digital sub-environment should be included into BE today. Since it is the newest and most problematic element in the assessment of BE, we will consider some approaches to the assessment of the digital sub-environment. In Germany, the reports of the Federal Ministry of Economics and Energy include 3 main indicators: the use of digital devices—by the state and within companies, digitalization and the effect of the impact of digital technologies on business. In China, the "digital economy" is indexed by 5 indicators: the number of users with access to broadband Internet, mobile Internet users, mobile Internet access traffic, the volume of e-commerce transactions and the use of cryptocurrencies. It is important for an enterprise to assess the extent to which its business and the opportunities of the digital environment in the market correspond, what costs will be required to achieve such compliance. As there is a significant differentiation between the regions of Russia, we have chosen the Chinese experience of digitalization assessment for our methodology. For VEM this parameter (L dig.) is 0.63, which is above average. The coefficients of probability of change increase its value up to 0.74. So, there is an improvement in terms of business and its opportunities for this sub-environment.
4 Conclusion Summarizing the results of the study, we can make the following conclusions. In the context of social and digital transformation of the economy, methods and approaches to assessing the business environment must change incorporating new requirements and formats of business processes, progressive communications, etc. Otherwise, the management of corporations will not be able to objectively choose the market and business model, to build an adequate strategy to achieve the targets. In accordance with this, the competencies of management must change too.
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The state of the business environment and its attributive properties are influenced by the expectations and narratives of market participants and society. In this regard, the assessment of the current state of the environment as a whole and the subenvironments should be adjusted to take into account possible and most probable changes. The study of narratives relates to the functionality of corporate PR services and HR departments. Thus, the study of the business environment is an interdisciplinary activity and requires a joint effort of top-management on digital technologies basis. The proposed method of express assessment of BE does not pretend to the absolute completeness of its determinants and parameters. It can be attributed to the analysis of the first stage. Next, it is necessary to proceed (second stage) to a more detailed study of the specific features of a particular market and its traditions, as well as hidden risks. In particular, it is recommended to consider its inherent forms of integration and its depth, social orientation, the prevalence of agreements on co-production, cobranding, the presence of strategic alliances and clusters, including innovative ones, ecological restrictions and “green finance” [9, 17, 18]. Depending on the direction of possible changes in sub-environments and their business configuration, the enterprise chooses one or another type of market and functional strategies: in case of deterioration—preventive, if unchanged—synchronous, in case of improvement—adaptive, as well as the most adequate to the current BE business model. In conclusion, we note that the proposed research results leave behind the scene the question of the impact of an enterprise itself onto the BE. It is certainly quite possible and is a reality, especially for big business. However, this is a topic for subsequent research.
References 1. Shirinkina EV (2018) Features of functioning of industrial enterprises in the digital economy. Russ J Indus Econ 11(2):143–150. https://doi.org/10.17073/2072-1633-2018-2-143-150 2. Kormanovskaya IR (2015) Sustainable development of regional socio-economic systems in conditions of turbulence. Prob Mod Econ 56(4):189–192 3. Shchetinina ED, Kucheryavenko SA, Klimova TB, Konnova AV (2016) The system of factors and causes of turbulence as a measure of chaos and uncertainty in economic development. Bull BSTU 7:203–208. http://dspace.bstu.ru/jspui/handle/123456789/2331 4. Ivanova NI (2017) Current trends in the development of the world economy: new challenges and problems. The changing landscape of the world economy: a collection of materials from the round table of the department of world economy, dedicated to the 75th anniversary of the Faculty of Economics. Lomonosov Moscow State University, Moscow, p 8–16 5. World Economic Outlook (2021) Managing divergent recoveries. https://www.imf.org/ 6. Apatova NV, Korolev OL (2020) Digital economy as a tool for implementing sustainable socioecological-economic development sustainable development of the digital economy. Industry and innovation systems: Proceedings of the scientific and practical conference with foreign participation. PolitechPress, St. Petersburg 7. Perelet RA (2018) Environmental issues in a digital economy. World New Econ 12(4):39–45
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8. Alexandrin YN (2012) Assessment of the quality of the business environment of small business in the region: institutional and methodological aspects. Econ Manag 235(4):42–50 9. Dalvi MG, Singh A, Rambabu P, Murthy NN (2019) Business sustainability—A study of most sustainable corporations. Environ Manag Sust Dev 8(2):130–150 10. Doroshenko Y, Starikova MS, Malykhina I, Somina I (2019) Increasing the efficiency of hightech companies based on interactions with the entities of the innovative environment. Econ Reg 15(4):1279–1293. https://doi.org/10.17059/2019-4-24 11. Kravchenko LN (2019) Issues of assessing the business activity of the organization. Belgorodskiy. Belgorod Econ Bull 93(1):167–72. http://dspace.bstu.ru/jspui/handle/123456789/ 2657 12. Lipkind TM, Lola IS, Ostapkovich GV (2021) Factors limiting the activities of enterprises and organizations in the basic sectors of the economy in 2020. NRU HSE, Moscow 13. Levitt S, Dubner S (2012) Freakonomics (freakonomics: a rogue economist explores the hidden side of everything). Mann, Ivanov and Ferber, Moscow 14. López García JJ, Lizcano D, Ramos et al (2019) Digital marketing actions that achieve a better attraction and loyalty of users: an analytical study. Future Int 11:130. https://doi.org/10.3390/ fi11060130 15. Somina IV, Darmina AS (2020) Digital innovations in the modern world. Belgorod Econ Bull 99(4):39–45 16. Abdrakhmanov GI, Vishnevsky KO, Gokhberg LM et al (2020) Digital economy 2020: a short statistical collection. NRU HSE, Moscow 17. Semenova N, Eremina O, Skvortsova M (2020) Green financing as a condition for sustainable economic growth. Hum Soc Sci Rev 85:1–11 18. Shchetinina EA (2021) Design thinking in business strategies of corporations. Sci J NRU ITMO Ser Econ Environ Manag 44(1):85–93 https://doi.org/10.17586/2310-1172-2021-14-1-85-93
COVID-19 and Its Impact on Construction and Transport Construction Economy: An Integrated Framework Kumar Shalender , Babita Singla , Sandhir Sharma , and Marina Oberemok
Abstract The research develops an integrated framework for minimizing the damaging impact of COVID-19 on the economy in construction in the context of Indian real estate sector. Beginning with the extant literature review, the study analyses the challenges that housing, commercial, and industrial segments of the real estate sector is facing in the country. The insights from the literature are then used to underpin a theoretical schema that posits resource capabilities and managerial competencies crucial for sustaining construction economy in the real estate sector. With theoretical underpinnings in place, authors come up with an integrated model that explicates the role of strategic frameworks as a mediating factor between an organization and its performance. The model also investigates the role of environmental turbulence as a moderating factor impacting the relationship between different variables of the model. The study develops propositions related to the outcomes of environment turbulence and its influence on the firm performance in both short-term and long-term scenarios. The future research plan and implications of the study has been discussed towards the end of the study. Keywords Covid-19 · Construction · Transportation economy · Transport industry · Transportation sector
1 Introduction As the devastating impacts of COVID-19 continue to unfold, we are witnessing economic de-cline across countries around the world. The Indian economy is among the worst affected in the world with its GDP declining by a colossal 23.9% in the first K. Shalender (B) · B. Singla · S. Sharma Chitkara Business School, Chitkara University, Chandigarh-Patiala National Highway (NH-64), Rajpura 140401, Punjab, India e-mail: [email protected] M. Oberemok Belgorod State Technological University Named After V G Shukhov, Kostyukov Street, 46, Belgorod 308012, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_76
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quarter of the financial year 2020–2021. This decline has impacted all major business sectors in the country and specifically, the real estate sector has come under an intense pressure. This is because the Indian government imposed a complete lockdown in the country in March 2020 that resulted into closure of the entire construction economy [10]. Estimates vary about the financial losses to the industry due to lock down with some reports indicating erosion of up to $1 trillion dollar value from the sector by the end of FY21. However, with subsequent lift in the lockdown restrictions, it seems now that the industry is coming back on its track although experts agree that it’ll take monumental efforts be-fore the sector is able to achieve the desirable growth rate. The Indian real estate sector can be primarily classified into three categories: residential sec-tor, commercial sector, and industrial sector. The residential sector is the most important one as it has proved instrumental in powering the growth story of the real estate sector in India for decades now. However, the segment now has come under pressure owing to COVID-19 impact, lack of liquidity, dampening demand, unfinished projects, and piling of inventory [9]. Further many regulatory reforms such as the Goods and Services Tax (GST), Indian Bankruptcy Code (IBC), and Real Estate Regulation Act (RERA) has ratcheted up the pressure on industry stakeholders, resulting in slowing down of the sector. Similar to the residential segment, commercial sector and industrial categories have also got their own share of problems with the lack of liquidity emerging as the biggest challenges for the developers. The lack in the growth in the real estate sector can also be attributed to the stringent money lending policies in the country. In India, both public and private sector banks have high share of nonperforming (NPA) assets and as a result, these financial institutions have become very strict in borrowing the money to the industry. Consequently, the firms in the real estate industry are now facing the lack of finances to complete their ongoing projects or launching new business ventures.
2 Materials and Methods The importance of resource capabilities and managerial competence for superior firm performance is well documented in the literature [1]. The relationship has become even more important in the wake of COVID-19 pandemic as industry is going through high turbulence and environment of uncertainty. The construction economy today requires commitment of resources from top leadership and apt managers who can put these resources to optimum use in these testing times. In the context of ongoing turbulence created by coronavirus, the study conceptualizes a holistic model for sustaining the construction economy [6]. The model assesses the impact of organizational strength (resource capability and managerial competence) on its performance. In addition, the conceptual model also delineates the impact that strategic frameworks and environment turbulence have on the relationship between the organizational strength and firm performance.
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3 Results and Discussions 3.1 India Real Estate Sector: Changing Dynamics 3.1.1
Residential Sector
Residential Sector has remained a main driver of growth for real estate sector in India although it has been adversely impacted by the ongoing pandemic now. The growth in residential sector declined in 2008 though by 2010, the sector started picking up the pace owing to strong financial recovery and encouraging government policies. In 2016, however, demonetization and liquidity crunch hit the construction economy again. In 2017, the government of India came up with a real estate regulation act (RERA) which played a crucial role in bringing sustainable growth back to the segment. Moving further in 2019, GST execution made things better by removing the hurdles and providing a level-playing field to developers.
3.1.2
Commercial Sector
Post the 2008 financial crisis, the commercial sector of the Indian real estate industry has been on a continuous path of growth. Activity in the office leasing segment had picked up tremendously and between the years 2016 to 2019, industry has witnessed increase in the leasing space from 41.6 to 59 million sq. ft. This is equivalent to a 12% compounded annual growth rate for the three years. The revolution in the commercial sector has been led by the global corporations which have found India as a preferred destination for setting up their offices and innovation centers. There were many reasons behind this impressive growth with low operating cost and abundance of talent being the prominent ones. The situation, however, changed quickly with the onset of the covid-19 pandemic. Similar to the residential sector, the job losses, crunch in the money supply, and stringent lockdown across the country wreaked havoc on the segment. The financial year 2021–2022 is going to be an extremely important year for the segment. The category has to make some innovative arrangements and the use of new technologies such as artificial intelligence and machine learning are expected to power the future of not only the commercial sector but also for the entire real estate industry.
3.1.3
Industrial Sector
The growth of the industrial sector in the upcoming years will primarily depend upon the government initiatives related to the warehousing and food processing industry. This is because of most of the upcoming projects are coming in these business sectors of the economy. It’s unlikely that in near future, manufacturing companies will come up with new installations as these organizations are already struggling with their
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Fig. 1 COVID-19 and its impact on real estate sector
existing spare capacities. The demand for the industrial sector is likely to get a push from the public sector domain as government has earmarked heavy investment for warehouses and food processing units. Some private sector companies are also focusing on the business initiatives in processing industry which will present a wide scope of growth for the industrial sector. There is no doubt that the pandemic outbreak has fundamentally changed the Indian real estate sector. All the categories in the industry have got impacted by the pandemic and Fig. 1 below capture some of these changes that the industry is witnessing today. The conceptualization emphasizes that real estate organizations need to focus on developing capabilities which will enable them to a) to identify the right resources, b) acquire these resources, c) develop and deploy these resources, and d) create competitive edge on these resources [3]. The second important aspect of this theoretical foundation is building the distinctive managerial capabilities that will help the organization to derive the maximum benefit out of the process of accumulation, building, and deployment of resources. In the absence of trained and skilled manpower, resources will not get converted into any kind of distinctive advantage for the real estate firms. Hence, it’s fundamentally important for the companies to keep on recruiting, selecting, grooming and training its managerial staff to achieve more operational efficiency while delivering effective results on the business and customer front [2, 4]. One of the direct benefits that an organization can derive from the constant interplay of resource capabilities and managerial competencies is the generation of different options that can be utilized to have maximum benefit from the constantly changing business environment [8]. In other words, organization can generate different strategic frameworks and this capability is particularly relevant in the backdrop of COVID-19 outbreak. As the industry need to adopt a holistic approach to tackle this rough period, this entails that companies have to work on strategies simultaneously to match the requirements of different customer segments [7]. In addition
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to building capabilities on the resource and managerial front, the environment turbulence is another important factor that an organization has to consider for its long-term sustenance and survival in the real estate industry [5]. It is also imperative for the top management to adopt strategies while keeping in mind the level of turbulence in the external environment [12]. In the context of today’s turbulent environment, the need to adopt different strategies is very much obvious. However, it is equally important that as and when situations come back to normal, the level of disruption in the adopted strategies need to be attenuated by the companies [11]. In other words, the environmental turbulence should act as an input to the overall strategic framework that an organization plans to adopt in the long term. The integrated model for the construction economy in India is underpinned by resource capabilities and managerial competencies of the companies (refer Fig. 2). We expect both the dimensions to considerably impact of the performance of the company—both in the long-term period and short-term horizon. The net effect of resource capabilities and managerial competencies on the firm performance is mediated by the generation of different strategic frameworks by the organization. If the company fails to utilize its resources and build on its managerial competencies in terms of adopting specific customer-centric frameworks, it won’t be able to get the desired result on the business front. More importantly, we posit that this relationship is moderated by the component of the external environment turbulence. In the case of high environmental uncertainty, organizations need to exercise different options available in terms of their strategic frameworks that it has built on the mixed capabilities of resources and managerial competencies. The environment of relatively low tumult, on the other hand, requires companies to adopt a rather stable position while diverting the investment in generating more industry-specific options that can be utilized at a later point in time. The model envisioned here is expected to provide superior results to organizations in both short term and long-term orientations. The issues related to short-term performance such as quarterly sales, level of inventory, and market share are expected to see a gradual revival with the implementation of the model in the organization. Long term
Fig. 2 Integrated model for the construction economy in India
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benefits, on the other hand, accrue in the form of adding value to shareholders while boosting the overall growth and sustainability of the segment. It is once again emphasized that the strategic framework evolving from the continuous interplay between resource capabilities and managerial competencies need to be applied according to the level of turbulence prevailing in the business environment. Any wrong decision taken on this front may backfire and can potentially cause a lot of damage and harm to the organization. For example, in the case of high turbulence, the organization needs to apply a range of different strategic frameworks to effectively counterbalance the threats arising from the environment. However, the same is not true for the time of relative stability where the company should not apply these different frameworks and rather strive to preserve the investment for difficult times.
4 Conclusion The integrated model discussed here is purely theoretical in nature and yet to be tested empirically on the real estate sector companies in India. The model is built on the time-tested aspects of resource capabilities and managerial competencies. Further, in order to make it more holistic, the component of environmental turbulence has been added as a moderating factor. The interplay of resource capabilities and managerial competencies will help the organization to develop a range of strategic frameworks that can be applied according to the changing external circumstances. In fact, the level of uncertainty in the business environment is going to be a key deciding factor in the generation of these different frameworks and their application under various circumstances. The next logical step for us is to empirically test this model on the real estate sector in India. The integrated model has implications for both scholars and practitioners. It will provide an opportunity for scholars to dig deep into the retail of resource capabilities and managerial competencies in the context of the real estate sector. Practitioners, on the other hand, will able to understand the mechanism, processes, and methodologies involved in generating firm-specific strategic frameworks in the real estate industry. Once this integrated model is tested empirically, we plan to further take this research to develop a strategic framework scale for the real estate sector in India. Acknowledgements The work is realized in the framework of the implementation of a comprehensive project to create high-tech production “Development of new methods and tools for management of property in the budget sector and their implementation in the software package of the informationanalytical system for centralized management of property” (agreement No. 074-11-2018-026 of 07/11/2018).
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References 1. Adner R, Kapoor R (2010) Value creation in innovation ecosystems: how the structure of technological interdependence affects firm performance in new technology generations. Strateg Manag J 31(3):306–333 2. Avilova IP, Krygina AM, Krygina NM, Koshlich YA, Oberemok MI (2020) Sustainable development of residential real estate based on the use of construction waste recycling. IOP Conf Ser Mater Sci Eng 890:022071. https://doi.org/10.1088/1757-899X/890/1/012187 3. Lesovik RV, Klyuyev SV, Klyuyev AV, Netrebenko AV, Durachenko AV (2014) High-strength fiber-reinforced concrete containing technogenic raw materials and composite binders with use of nanodispersed powder. Res J Appl Sci 9(12):1153–1157. https://doi.org/10.3923/rjasci. 2014.1153.1157 4. Fang C, Lee J, Schilling MA (2010) Balancing exploration and exploitation through structural design: the isolation of subgroups and organizational learning. Organ Sci 21(3):625–642 5. Gerhart B, Fang M (2015) Pay, intrinsic motivation, extrinsic motivation, performance, and creativity in the workplace: Revisiting long-held beliefs. Ann Rev Org Psychol Org Behav 2(1):489–521 6. Krygina AM, Avilova IP, Oberemok MI, Grebenik AG (2020) Modeling of organizational and functional components of investment and construction controlling in the reproduction of ecoresidential real estate. IOP Conf Ser Mater Sci Eng 945:012020. https://doi.org/10.1088/1757899X/945/1/012020 7. Rigby DK, Suther J, Noble A (2018) Agile at Scale. Harvard Bus Rev 96(3):88–96 8. Schein EH (2010) Organizational culture and leadership, 4th edn. John Wiley & Sons 9. Shori T (2020) How COVID-19 pandemic is an opportunity in disguise for India’s realty sector. https://www.businesstoday.in/opinion/columns/covid19-pandemic-an-opportunity-indisguise-for-indian-real-estate-realty-sector-coronavirus-lockdown/story/411317.html 10. Sinha S (2020) Success mantras for realty developers to thrive in times of Covid-19. Financial Expert. https://www.financialexpress.com/money/success-mantras-for-realty-developersto-thrive-in-times-of-covid-19/2099031 11. Visnjic I, Neely AD (2011) From processes to promise: how complex service providers use business model innovation to deliver sustainable growth. Cambridge Service Alliance, p 1–16 12. West J, Bogers M (2013) Leveraging external sources of innovation: a review of research on open innovation. J Prod Innov Manag 31(4):814–831
Human Capital as the Market Value of a Geomarketing and Transport System Vladimir Moiseev , Zhanna Avilova , Olga Gerasimenko , Ludmila Polovneva , and Tatyana Tselyutina
Abstract The paper defines the main types of capital as market value in the field of geomarketing—financial and intellectual. Geomarketing is presented by the authors as a detailed study of the territorial features of market formation, consolidating both marketing instruments and geography in transport systems. The stages of the development of geomarketing—the emergence, formation, and popularization—are summarized. The purpose of the research is to develop a system of balanced marketing and geographical indicators that ensure the formation of the human capital of the geomarketing system. Methods of scientific research are: abstraction, analysis and synthesis, induction and deduction, bibliographic, graphic, statistical estimates and economic analysis, preferences, analogies, information technologies. The geomarketing system includes intellectual (human, structural) and financial capital in the market value in transport economy. The human capital in the geomarketing and transport system includes qualified management, contracts with specialists in the field to which the business belongs. Human capital in a geomarketing system also includes know-how that is inseparable from a particular individual. It is determined that the human capital of geomarketing is not reflected in the company’s asset, as it does not directly belong to the company. The authors identified the key types of balanced indicators of the social and economic geomarketing and transport system—finance, customers, internal business processes, and personnel development. Keywords Geomarketing · Human capital · Social capital · Geomarketing research · Transport system · Transport economy · Transport sector · Transport company
V. Moiseev (B) · Z. Avilova Belgorod State Technological University named after V G Shukhov, 46 Kostyukova Street, 308012 Belgorod, Russia e-mail: [email protected] O. Gerasimenko · L. Polovneva · T. Tselyutina Belgorod State National Research University Russian, 85 Pobedy Street, 308015 Belgorod, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_77
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1 Introduction Geomarketing appeared first in foreign and national methodology as a visual and marketing study of the market features of the territory, including both marketing and geodigital instruments. From the point of view of terminological formation, geomarketing exists in the scientific field of a number of national synonyms: “geography of sales markets”, “market geography”. At the same time, the foreign methodological field designates geomarketing as a combination of geo-market-digital factors. We will outline the key stages of the development and formation of geomarketing as a scientific and methodological field of research transport systems: • emergence (30–50s of the XX century): the emergence and origin of geomarketing research (USA), the basic concepts were defined, and the fundamental issues to be solved in the field of geomarketing methodology. The concept of geomarketing research, the formation of a conceptual and methodological apparatus, the analysis of the placement of real and potential trading companies, the use of geomarketing instruments mainly in the field of trade is reflected in the scientific works of W.A. Applebaum and Ch. Harris (2014); • formation (60–70s of the XX century): as the external and internal conditions for planning the company’s activities become more complex, the mathematical and analytical apparatus of geomarketing is formed in the works of many foreign scientists. Geomarketing is widely used in the transport, banking, and manufacturing sectors. At this stage, additional areas of scientific research were identified, among which one can distinguish the analysis of potential trade zones for the sale of goods/products, the study of the configuration of trade locations, the presentation of scientific results in the form of cartographic and marketing maps. • popularization (since 70s of the XX century). Geographical tools are actively used for advertising, improving distribution networks (GIS technologies, geomarketing maps). In the mid-90s, the focus of scientific research shifted to the area of regional markets. Some geomarketing studies are conducted on the territory of the CIS. The priority of fragmentary geomarketing schools belongs to Russia and Ukraine. Initially, this was formed as economic and geographical research of a separate territory, and later the development of the scientific direction—territorial marketing, in the focus of scientific attention—increasing the investment attractiveness of the territory [1, 2]. Aspects of scientific attention include the creation of the most positive image and business reputation of a particular territory in geomarketing studies of this period. Until the XXI century, geomarketing, mainly, had a narrow scientific direction of research in fundamental marketing. The main emphasis of geomarketing is geosegmentation and geo-positioning of goods and services that can be produced and sold in a particular territory. F. Kotler (2010) in the mid-90s proposed a scientific direction in the form of the concept of “place marketing” as an instrumental challenge to
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external (public policy, reforms) and internal (development of effective, sustainable strategies) global processes transport economy. Currently, geomarketing, as a symbiosis of geo-market-digital factors, is a priority instrument of the marketing mix 4P concept, contributing to the selection of the optimal sales location and the formation of a competitive advantage. According to the scientific research of L. Edvinsson (2011), the market composition of the geomarketing system includes both intellectual and financial capital. Intellectual capital includes: • human; • structural: client and organizational. • From the point of view of market and customer value, the key focus is on customer capital. It is associated with marketing research of the potential target audience of the geomarketing and transport system. Organizational capital, in turn, consists of: • innovative: intellectual property (patents, know-how, license agreements), copyrighted business ideas, brands, trademarks; • process: geoinfrastructural conditions of the company’s development (business processes, information technologies).
2 Materials and Methods The scientific field of geomarketing includes the instrumental apparatus of spatial analysis, visual and digital construction of models in the structure of human capital formation. Geomarketing research examines comprehensively large-scale, regional, spatial socio-economic processes and phenomena in transport sector. It is this advantage that forms the marketing instrument of human capital. The exclusivity of geomarketing lies in the combination of functional features of geographical conditions and marketing research in order to solve the strategic problems of opening companies in the context of digitalization of human capital. In the paper, the authors used the following research methods: • abstraction, analysis and synthesis, induction and deduction—for evaluating, diagnosing and predicting results; • bibliographic—for the analysis of basic economic categories of strategic marketing planning; • statistical estimates and economic analysis—for calculating the level and dynamics of geomarketing research parameters; • preferences—for systematization and selection of the most optimal geographical infrastructure objects; • analogies—for selecting spatial data and building a regression model; • information technologies—for IT support of scientific research, registration of results.
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3 Results and Discussions Let us take a closer look at the structure of the company’s market value. Structural capital is the arrangement of the working space, comfortable working conditions. Human capital in the geomarketing system is the intangible conditions for opening a company (Fig. 1) [3]. Structural capital in the content concept is close to social capital. In particular, A.V. Latsman in scientific research confirms this by the classification of human capital in the geomarketing system. Let us denote the forms of the structural capital of the geomarketing system: economic, human and social capital. Social capital “finds its expression in the establishment and maintenance of special relationships with other economic agents. This relationship is linked to the expectation that other agents will fulfill their obligations without sanctions. Unlike human capital, social capital is not an attribute of an individual. Its basis is formed by social networks. On the basis of social networks, which often tend to be relatively closed, the institutional basis of social capital is formed—belonging to a certain social circle or membership in a group. Social capital obeys the logic of self-growth” [3]. A.V. Lantsman includes such indicators as the involvement of employees in the work process and space, the level of trust in the team, the process of intra-group interaction, social conditions and activities in social capital. With this combination of social indicators in the geomarketing system, a cultural symbiosis arises, including the assessment of professional behavior or the level of working relationships. The structured view of geomarketing capital can be presented in Fig. 2: • economic capital (including financial one); • intellectual capital; • social capital.
Market value
Financial capital
Human capital
Client capital
Innovation capital
Intellectual capital
Structural capital
Organizational capital
Process capital
Fig. 1 The market value of an economic entity according to L. Edvinsson
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Geomarketing system capital Economic
Human
Social
Structural
Client
Intellectual
Fig. 2 Structured representation of the capital of a geomarketing system
R. Kaplan and R. Norton suggest using a generalized system of indicators that include intangible assets, elements of intellectual and social capital of the geomarketing system. The author’s model has the following form: • • • •
financial justification; customer focus; internal business processes; staff development and training.
Social and intellectual capital includes customer focus, internal business processes, and personnel directly. Figure 3 presents the author’s scale of trust relationships as a stage of applied assessment of the company in market conditions [4]. Trusting relationships are the formation of strategic goal-setting, the company’s profit indicators, the value significance of the purchase and the development of a unique value proposition, and the effects. The human capital of the geomarketing system is a fundamental platform, as it contributes to the formation of effective market relations, the exchange of goods/services [5]. The key indicators of the human capital are the experience and technological qualifications of the staff, the health and social security systems.
Fig. 3 The basis of segmentation of trust market relations from the perspective of geomarketing
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IV quarter Tambovsk region
III quarter
Lipetsk region
II quarter I quarter 2020
Kursk region Voronezh region
IV quarter
Belgorod region
III quarter II quarter I quarter 2019 0
10,000
20,000
30,000
40,000
50,000
Fig. 4 Average per capita monetary income of the population in the subjects of the Central Chernozem Economic Region, thousand rubles (2019–2020)
Among the basic indicators of the development of the geomarketing system, the real income of the company can be distinguished. On Fig. 4 shows income data for the Central Black Earth Economic Region (TsCHER). Positive dynamics of increase in cash income in the fourth quarter of 2019–2020 is observed in the Belgorod and Tambov regions. In general, we can observe an increase in clients’ cash income by 2–2.9% per 2019–2020, indicating the sustainability of human capital in the geomarketing system in this economic region. Thus, the territorial differences of the subjects of the TsCHER are reflected in the indicators of the human capital of the geomarketing system. These differences are reflected in the formation of the market and business space, geomarketing conditions for business development. The key tasks of forming the human capital of the geomarketing and transport system are the introduction of innovative, intangible assets, improving the working conditions of personnel and production conditions. The synergetic effect of the implementation of this task is to ensure effective busyness and the development of human capital [6–9].
4 Conclusion The analysis of human capital as the market value of the geomarketing and transport system allowed us to draw the following conclusions:
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1. The current stage of geomarketing development is characterized by a combination of marketing, geographical and digital factors. The market value of the geomarketing system includes intellectual and financial capital. In turn, intellectual capital is divided into human and structural capital. 2. The structure of the geomarketing and transport system is established in the form of the selection of elements and certain relationships between these elements. First of all, we are talking about a geomarketing model consisting of a core, a contour, and internal and external effects. 3. The instruments of the geomarketing and transport system are spatial analysis and digital modeling as a process of forming human capital. 4. The system of geomarketing indicators is formed through a combination of intangible assets and a combination of intellectual and social capital. Acknowledgements The reported study was funded by RFBR, project number 19-29-07024/20.
References 1. Vinogradova NP (2018) Essential presentation of geomarketing from the perspective of an evolutionary approach to the economy of managerial decision-making. Probl Econ Legal Pract 3:27–32. https://doi.org/10.15405/epsbs(2357-1330).2020.10.5 2. Strachkova MV, Luk’yanenko VA (2017) Geomarketing in the context of informatization of sociogeographical research: the essence, stages of development, scope. Scientific notes of the Crimean Federal University V.I. Vernadsky 3(1):97–107 3. Lantsman AV (2007) Social capital as a factor in improving the efficiency of management activities. Ph.D Thesis, Moscow 4. Kaplan RS, Norton DP (2008) The balanced scorecard: translating strategy into action. OlimpBiznes Publ, Moscow 5. Donichev OA, Beskrovnykh AS, Markova IS (2014) Human capital as a factor in the development of the innovative economic space of the regions. Univ Bull 6:27–33 6. Unified Interdepartmental Information and Statistical System (EIISS) https://fedstat.ru/indica tor/57039 7. Tkhorikov BA, Lomovtseva OA, Gerasimenko OA, Sablina OM, Titova IN (2020) Geomarketing—a new concept or an applied business tool? Bulletin of Tomsk State University. Economy 49:199–213. https://doi.org/10.17223/19988648/49/14 8. Moiseev VV, Tselyutina TV, Avilova ZhN (2019) Assessment of the human capital of the region in the conditions of transformation of economic processes. Int J Interdisc Soc Sci Stud 2:61–70 9. Tselyutina TV, Vlasova TA, Timokhina OA, Maslova YV (2019) Convergence of institutes of functional representation of group interests under transformation of social processes, quality of life, and human capital. Humanit Soc Sci Rev 7(6):111–117. https://doi.org/10.18510/HSSR. 2019.7624
Diagnostics of the Depth of Digitalization of Industrial Enterprises of the Construction and Transport Construction Complex Ekaterina Schetinina , Anatoly Rudychev , and Svetlana Kochina
Abstract The relevance of the article is determined by the fact that digital technologies, penetrating into various spheres of human activity and other economic entities, lead to the formation of new models of business, industrial relations and the digital economy as a whole. The purpose of the article was the development of methodological support for the management of transport enterprises and construction industry enterprises in the digital economy. The authors define the digital economy as a product of the evolutionary development of bio-socio-technical systems, argue that the main subject undergoing significant changes with the advent of the digital economy is entrepreneurial activity, taking into account its social aspects. The article examines the factors of digitalization, it is noted that the insignificant level of digitalization of the domestic industry, the transport system and its infrastructure is associated, among other things, with their insufficient readiness for transformation. Consequently, there is a need to develop a methodology for assessing the level of digitalization of the enterprise for the transport and construction industry. To this end, a methodology for assessing the level of digitalization of an enterprise is proposed, a procedure for diagnosing the depth of digitalization of the industrial and transport sector is described. Keywords Digitalization of business · Diagnostics · Transport construction complex · Transport infrastructure facilities · Transport system · Industrial and transport sector · Transport enterprise
1 Introduction Modern economic processes and phenomena occur in the era of digitalization. The digital economy can be defined as a product of the evolutionary development of bio-socio-technical systems, including enterprises, and in practice—as a E. Schetinina · A. Rudychev · S. Kochina (B) Belgorod State Technological University named after V.G. Shukhov, 46, Kostyukov Street, 308012 Belgorod, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_78
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set of socio-economic, financial and production and logistics activities provided by communicative-information, electronic-intelligent technologies and providing for the creation of a completely new product and service, the identification of a modern method of production and management of the organization. Today, among expert economists, there is still no common view on the essence of the digital economy and what part of the economy can be classified as digital [1]. Previously created and already new relevant digital technologies continue to penetrate all spheres of life, fundamentally changing many business processes and business structures, options for interaction between customers and suppliers of goods and services, as well as between partners and government institutions. At the same time, there is a division of enterprises of one industry by speed of implementation of digital technologies and their application (some have a high level, others have less), as well as differences in these parameters in the regional context [2]. In this regard, it became necessary to diagnose the level of digitalization industrial enterprises to identify their competitive advantages (strengths) and "vulnerabilities" in comparison with other market participants. For this purpose, a business digitalization index was developed. This index is designed to assess the speed of adaptation of business entities to digital transformation—the transition to a new technical order. The business digitalization index is used not only in Russia, but also in the United States, a number of European and Asian countries [3]. When calculating this index, broadband access of business structures to the Internet, the use of ERP systems (Enterprise Resource Planning System), RFID technologies (the use of radio frequency identification), as well as various cloud services and web platforms are taken into account. Thus, the Business Digitalization Index (BDI) is an indicator showing the degree of readiness of enterprises for digital transformation. The BDI index can take the following values: minimum—0 percentage points, maximum—100 percentage points, calculated as the arithmetic average between the values of five private indices (Fig. 1). Let’s take a closer look at the essence of private indexes BDI: – information and digital security is the use of modern and advanced systems and tools for protecting digital information; – human capital—the desire of the company’s management to train the existing personnel in the necessary digital technologies, as well as to attract highly qualified personnel in the field of digital transformation; – channels for transmission and storage of information—the use of modern technologies and systems for the transmission and storage of digital information, such as cloud services, Internet platforms, databases, etc.; – the use of Internet tools—we are talking about the following tools: artificial intelligence, blockchain, cloud computing, monitoring systems, digital marketing, etc. Ultimately, all these tools are designed to promote, develop, and enhance the competitiveness of an enterprise in the direction of mastering modern trends in digital transformation;
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BDI (Business Digitalization Index)
Information and digital security Human capital
Channels for transmission and storage of information Application of Internet tools Integration of digital technologies
Fig. 1 Business digitalization index structure. Source: compiled on the basis of materials from the NAFI analytical center
– integration of digital technologies demonstrates the level of development and implementation of digital technologies (e-commerce, CRM systems, electronic document management, etc.). Today we can already state that there are economic sectors in Russia that are quite digitalized (for example, telecommunications), while others are only trying to embark on the “digital path” (such as construction). Figure 2 shows the dynamics of the business digitalization index for the main sectors of the economy. 34.1 32
Hotels and catering Mining
29.4 29
Transportation and storage
29.3 27 35.6 35
Information technology industry Telecommunications
2019 41
44.5
2018
25.3 25
Building
39.2 39
Wholesale and retail trade
35.8 35
Manufacturing industry 0
10
20
30
40
50
Fig. 2 Dynamics of the digitalization index in Russia by main types of economic activity for 2018 and 2019. Source: Statistical Digest “Indicators of the Digital Economy”
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Based on the data in Fig. 2, we can note that such industries as information technology, manufacturing, wholesale and retail trade, and telecommunications have succeeded in digital transformation. The laggards are: construction, mining, transportation and storage. In general, if we compare the dynamics for 2019 compared to 2018, then all sectors of economic activity increased the index of digitalization—this is especially evident in the telecommunications industry (by 3.5 percentage points). As the analysis shows, the lag of the industrial sector, including the construction industry for this index is explained by a number of reasons: – misunderstanding of the whole essence of the transition to digital transformation and the lack of awareness of industrial leaders in the feasibility of this transition; – significantly high costs for the development and application digital technologies and tools; – a number of production facilities do not use modern digital technologies in full; – the risk of reducing the cybersecurity of the enterprise, which is inevitable with the expansion of the areas of implementation of digital technologies [4]. Despite this, at the state level, the digitalization of the industrial sector is positioned as a significant direction in the development of the domestic economy. Authors such as A. V. Babkin, A. Yu. Pestova, O. O. Shendrikova, L. D. Karavnova, I. F. Elfimova, V. A. Plotnikov, E. V. Shirinkina, E. A. Istomina, R. Bukht, R. Heeks, J. Westerman, W. Dhar, P. Romer, K. Shtab [5–8] in their works consider issues related to the creation of algorithms and schemes for diagnosing the potential of an enterprise in terms of its digitalization, analysis of the level and depth of digitalization of the industrial sector. But nevertheless, this issue remains not fully understood.
2 Materials and Methods From our point of view, in order to ensure the growth of digitalization in lagging industries of the economy, as well as not to slow down in the leading areas of the index alone BDI is small because it does not analyse in detail the totality of the use of digital tools and technologies and does not take into account the specifics features of a particular sector of the economy. To do this, you need to develop an algorithm for diagnosing the depth of digitalization, which will reveal the strengths and weaknesses of this enterprise and its management, clarify what risks exist in the transition to the digital path, and how to build a strategy to enhance competitiveness through digitalization. Thus, the requirement of complexity and taking into account the specifics of the construction industry will be met. These features are: a) the social nature of the industry’s products; b) the presence of a significant design part due to the growing requirements for taking into account the individual needs of customers; c) development as a new business model; d) the complexity of marketing in the construction industry market due to the multiplicity of types of participants; e) environmentally relevant aspects of the activity [9].
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With this in mind, to diagnose the depth of digitalization of construction enterprises, we propose the following algorithm, consisting of such stages as: 1. Grouping of homogeneous indicators of the depth of digitalization of an industrial enterprise; 2. Collection of insider data about the object under study; 3. Collection of market averages (competitor analysis) and customer requirements; 4. Determination of the rank of selected indicators; 5. Diagnosis of the industrial facility under analysis and determination of the selected parameter values in the mid-market aspect; 6. Calculation of integral (aggregate) indicator of the depth of digitalization of the enterprise; 7. Analysis and interpretation the results obtained; 8. Proposal of measures to increase the depth of digitalization of an industrial enterprise. In connection with the above, the depth of digitalization of an enterprise in the construction industry can be assessed by a number of indicators, which are combined into the following groups according to their purpose: – indicators of digital infrastructure—to take into account the conditions of the business environment and ensure compatibility with social and technological narratives; – indicators of material and technical support—for making operational decisions and automating production processes, in particular, multidimensional modeling, digital analogs of the structure, etc.; – software indicators—to increase the speed of information exchange, its accuracy, avoid routine and maintain security; – organizational, managerial and marketing indicators—for making market-based management decisions, knowledge of market conditions, effective communications with customers, including feedback, online design and for promoting products and services of a construction company; – indicators of labor resources—to ensure the necessary qualifications and competencies; – financial indicators—to analyze the sufficiency and balance of investments in digitalization and assess the effectiveness. Let’s briefly describe the main blocks of the technique. The digital infrastructure of an industrial enterprise is a collection of various digital, intelligent and artificial technologies that provide communication, network and computing activities. On the basis of this infrastructure, the enterprise develops and puts into operation the necessary software for industrial equipment and personal computers [10]. The block of material and technical support includes equipment for the pre-design, design and direct production stages of construction, in which modern digital technologies have been introduced, which will further create a single ecosystem “Industrial Internet of Things”.
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The software serves the technical side of management and coordination, improvement of document flow, including information security and control over processes at the enterprise, as well as with external partners and institutions. For the effective functioning and management of an enterprise on the path of digital transformation, specialists with high digital literacy are needed. This explains the importance of the analysis of labor force indicators in calculating the depth of digitalization: analysis of professional qualities, competencies of managers, their learning ability and attitude to change forms of work on the basis of “numbers” [11]. For top and middle management, there is an important task of high-quality strategic and operational management of the digitalization process, including digital marketing as a subsystem of market research using a big date, the use of digital technologies in the development of new products, online communications, promotion in networks, work with an enterprise website, and corresponding interfaces [12]. It is known that consumer behavior in the digital environment is changing significantly, as well as their requirements are, which also applies to the construction industry (online design, development, etc.). This means that marketing support is needed for the implementation of a digital innovation policy and strategy in the enterprise—in order to comply with Industry 4.0 [13]. In the context of the organization’s strategic plan for the development and strengthening of digitalization processes, cost-revenue comparisons, that is, budget controls, are very significant in order to gain experience in further managing business structures and apply competent strategic solutions in the field of digital transformation.
3 Results and Discussions To calculate the integral indicator of the depth of digitalization of an enterprise, must be installed first the weights of the indicators using the method of expert assessments, which involves the involvement of professional experts in this industry. Next, we will consider the specific parameters for the enlarged group of indicators for diagnosing the depth of digitalization presented earlier and indicate their weight (Table 1). To assess the depth of digitalization of an industrial enterprise, we propose the calculation of an integral indicator for each enlarged group according to formula 1: Gj =
n
gi · αi
(1)
i=1
where G j —is the integral indicator of the j-th group of criteria, gi —is the relative value of the i-th indicator, αi —is the weight of the i-th indicator, n—is the number of indicators in the group. Based on the obtained private integral indicators, a general integral indicator (as an arithmetic mean) is calculated for the entire enterprise, which will reflect the depth
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Table 1 List of parameters for diagnostics of industrial enterprise digitalization depth Indicator group
Parameters (values from 0 to 10)
Rank
Digital infrastructure indicators
– availability of the organization’s staff with computers;
0.4
– access to broadband internet
0.6
Total:
1.0
– the number of state-of-the-art software-controlled equipment;
0.3
– the number of robotic machines and equipment;
0.3
– availability of production units and mechanisms operating with Internet of Things
0.4
Logistics indicators
Software metrics
Total:
1.0
– availability of an ERP system;
0.2
– availability of a secure single digital platform for the interaction of all departments of the enterprise;
0.3
– availability of secure cloud services;
0.3
– availability of RFID technology
0.2
Total:
1.0
organizational and management indicators – the number of automated business and marketing processes, including marketing;
labor force indicators
0.1
– availability of digital marketing, CRM systems;
0.3
– availability of a strategy for the implementation of digital innovations;
0.2
– the level of electronic sales and SMM;
0.2
– the level of digitalization of workflow
0.2
Total:
1.0
– the level of digital literacy of staff;
0.5
– the number of employees in the field of digital development of the organization;
0.2
– number of employees using current digital tools and programs
0.3
Total:
1.0 (continued)
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Table 1 (continued) Indicator group
Parameters (values from 0 to 10)
Rank
value indicators
– organization’s digital development costs;
0.1
– the net profit resulting from the use of digital tools;
0.3
– the costs of the organization aimed at training personnel in the field of digitalization processes;
0.2
– the annual volume of production produced by digital tools
0.4
Total:
1.0
of digitalization (formula 2). Hd =
Gj m
(2)
where Hd —the depth of digitalization of the enterprise, m—is the number of groups of indicators. Based on the above parameters, we will analyze the depth of digitalization of the construction industry in the Russian Federation in 2019 (Table 2). Thus, the calculation of the depth of digitalization of the construction industry confirms its lag in the transition to the path of digital transformation. Integration of digital technologies is the main aspect of digitalization of the construction industry [14]. The transition to digitalization involves the attraction of highly qualified personnel with high digital competencies, an increase in the efficiency of business processes, and an increase in the level of openness of activities in general. All these are barriers to the growth of the index and the depth of digitalization of the construction industry.
Table 2 Diagnostics of the depth of digitalization of enterprises in the construction industry in the Russian Federation by the end of 2019 Indicator group
Partial integral indicator Depth digitalization
Digital infrastructure indicators
4.2
Logistics indicators
2.5
Software metrics
3.9
Organizational and management indicators and 4.3 marketing Labor force indicators
4.7
Financial indicators
2.7
3.72
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To increase the level of digitalization depth, Russian industrial enterprises need: – introduce modern and relevant digital technologies into production activities at an accelerated pace; – for competent digital development, the top management of the organization needs to form an idea of which trends in the field of digitalization will have the greatest impact on the state of the industry as a whole and which of them will benefit in the coming years; – concentrate resources, to develop common standards in the field of digitalization; – closely interact with government agencies, educational and research organizations in the design of new digital technologies and their development; – revise the policy of investing in human capital and digital technologies; – building on digitalization processes, develop a strategic plan for human capital management, thereby ensuring the development of the necessary infrastructure and the active involvement of digital professionals.
4 Conclusion Today, diagnosing the depth of digitalization of an industrial enterprise is an important task, because the use of digital technologies in the production environment provides the enterprise with increased efficiency of operation, staff quality, status and strengthening of the company’s brand, since the expedient use of digital technologies involves the formation of high-quality interaction between the seller and the client, as well as management decisions in the future in the field of digital development. We tested the proposed algorithm for diagnosing the depth of digitalization of an industrial enterprise on the example of the construction industry. The final results obtained showed a lag in digital development and provision of this sector of the economy. Ways to improve the digital lag situation are also outlined. Acknowledgements This work was realized in the framework of the Program of flagship university development on the base of the Belgorod State Technological University named after V. G. Shukhov.
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Impact of the Import Substitution Program on the Competitiveness of Industrial and Transport Enterprises Sergey Mikalyt , Tatiana Dubrovina , and Stanislav Ignatov
Abstract Industrial policy is an important stage of development for modern Russia. This article is devoted to the study of industrial, including transport infrastructure of the Russian Federation. In the work, the authors use various methods of information analysis: economic, mathematical, sociological, etc. An important point is the competitiveness of industrial and transport systems, namely the impact of import substitution on their competitiveness. An ideal scheme for the implementation of the import substitution policy has been developed, the essence of which is the stepby-step development of import-substituting goods, starting with raw materials and equipment produced at domestic enterprises. The production of industrial goods in the context of the implementation of the import substitution policy leads to a reduction in cost and an improvement in the quality of manufactured products. The calculation of the average growth rate before and after the implementation of the policy of import substitution of Russian industry and transport infrastructure by types of industry is given. The dynamics of the development of industrial sectors of the Russian Federation is reflected. Keywords Competitiveness of industrial and transport enterprises · Industrial policy of the country · Implementation of the import substitution program in industries and transport infrastructure · Transport system · Industrial and transport complex · Competitiveness of transport infrastructure facilities
S. Mikalyt · T. Dubrovina (B) Belgorod State Technological University named after V.G.Shukhov, 46, Kostyukov Street, 308012 Belgorod, Russia e-mail: [email protected] S. Ignatov JSC «Plant of Non-Standard Equipment and Metal Products», 6, Rabochaya Street, 308013 Belgorod, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_79
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1 Introduction Nowadays, we often begin to hear that the implementation of the import substitution policy in our country has not justified itself. To what extent this statement is true, it is difficult to say right away, since this issue requires study and analysis. Of course, in order to understand this issue, it is necessary to clearly understand the essence and role of the import substitution policy in our country, its impact on the enterprise and its competitiveness. Any activity of the enterprise is aimed at achieving high economic results, namely, obtaining and increasing profits. Unfortunately, achieving this goal is a rather laborious process and entails a number of conditions. As a result of any activity of an enterprise, an important element is its competitive advantage in the market, by creating a high-quality product or service, as well as satisfying consumer preferences. For businesses pursuing their goal of increasing competitiveness and income, it is necessary to have a clear understanding of what constitutes competition and competitiveness. The very first scientist who proposed the term “competition” was A. Smith. In his writings, he viewed competition as fair rivalry between entities pursuing their main goal of maximizing profits. In economic theory, there are several approaches to the definition of competition. From our point of view, this definition is general in nature and does not describe all the features of the economic situation in the country. When studying many foreign and domestic works, on the definition of the concept of competitiveness and its essence, we came to the conclusion that of the four approaches to the definition of competitiveness (structural, behavioral, functional and complex) at present relevant and more reliable describes modern competition— an integrated approach. The issue of competition is studied by many authors, both foreign and Russian: K.R. McConnell, S.L. Bru, M. Bouilly, N.G. Menkiw and F. Knight, R.A. Fatkhudinov, N.I. Pertsovsky, I.A. Spiridonov, M. Porter, A. Yu. Yudanov. E.S. Borisova, J. Schumpeter, F. Hayek, A. Marshall, E. Cherberlinand many others [1, 2]. The modern economy regularly creates new conditions for activity, one of such conditions is the policy of import substitution. We consider import substitution as a factor of the company’s competitiveness, and as a condition that affects other factors of the company’s competitiveness. To identify the essence of import substitution, we will consider the existing factors of enterprise competitiveness, highlighted by other authors and reflect the impact of import substitution on them [3]. Implementation of the import substitution policy as an independent factor of competitiveness refers to the political type, which speaks of its controllability by the enterprise and the state. Depending on the level of the enterprise, EPI as a factor can be both external and internal. Based on the analysis of the classifications of competitiveness factors identified by many of the above scientists, it should be noted that the competitiveness of an enterprise is always influenced by many factors, and many of them are complex, therefore, the management of enterprises must regularly
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analyze changes in existing factors and assess the level of their influence, as a result appropriate management decisions and make forecasts for the future [4]. All these measures are necessary to maintain and improve the competitive position of the enterprise.
2 Materials and Methods 2.1 Materials The authors use the methods of economic, statistical analysis, the method of expert assessments, methods of sociological research.
2.2 Methods To solve the problem, a systemic-holistic approach, general scientific dialectical methods, including analysis and synthesis, the method of scientific abstraction, the principle of considering phenomena from the general to the particular and the particular, were used; also used resource and evolutionary approaches to the study of economic phenomena. As for the methodological apparatus, the methods of scientific hypotheses and consistent judgments, grouping and classification, the principle of identifying the main link, the method of comparison, ranking and trend building, as well as descriptions were used. In addition, special methods of economic analysis were applied: factorial, comparison, grouping, etc., the methods of economic, statistical analysis, the method of expert assessments, methods of sociological research.
3 Results and Discussions Let us note P. Heine, who defined competitiveness as the ability to stay ahead, striving for leadership, using various means and methods, as well as its own merits and advantages. He identifies the main types of competitiveness: the competitiveness of a country, industry, region, enterprise or organization, the competitiveness of products. In this study, we study the competitiveness of an enterprise. The competitiveness of an enterprise as an economic category has a dual aspect, that is, to achieve the goal of managing competitiveness, it is necessary to rely on the interests of not only consumers, but also producers. Accordingly, each of the two parties pursues exclusively their own interests. So, for manufacturers, the main benchmarks are the amount of costs, which allows them to have a lower cost of production. In turn,
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an important criterion for the consumer is the high quality of the product, its cost availability and usefulness. But competitiveness must link both sides. The competitiveness category of an enterprise is one of the key in a market economy. Having systematized the definitions of the competitiveness of enterprises found in the works of domestic and foreign scientists, we have formed our own definition of this term. So, the competitiveness of an enterprise, taking into account the influence of the policy of import substitution on it, from the point of view of the author, sounds like this: “An economic indicator that reflects the result of adaptation of an enterprise in the process of exposure to various external and internal factors: economic, political, demographic, scientific and technical, social, marketing, etc.” [5, 6]. All of the above interpretations of competitiveness reflect the current state of the Russian economy. As a result of a critical analysis of the above definitions, the author’s definition was formulated. Under the competitiveness of an enterprise (in terms of import substitution), we mean an economic indicator that reflects the result of adaptation of an enterprise in the process of exposure to various external and internal factors: economic, political, demographic, scientific and technical, social, marketing, etc. And also an important factor is digitalization. For industrial enterprises, software updates will be an important moment. Due to the political situation in the world, the Russian Federation has introduced an import substitution strategy since 2015, which allows many enterprises to reduce the cost of their products. Note that in the implementation of the import substitution policy, the competitiveness of the enterprise is influenced by multiple factors. We include political, economic, social, natural and this list is endless. But it is worth choosing the most important factors in this matter: this is support for certain industries, state support for enterprises belonging to these specific industries, etc. State support is as follows: concessional lending (the interest rate on loans has been reduced, the terms of lending have been increased, etc.); simplified document management system; reduction or temporary cancellation of taxation, etc. But we still wanted to understand how all these support measures and factors affect the competitiveness of enterprises. The essence of the import substitution strategy is to ensure that the consumer receives a high-quality product at an affordable price [7]. If we consider import substitution as a chain of productive actions, then, ideally, it would look like this (Table 1). Thus, it is easier for manufacturers to control the quality of their products, since, basically, imported raw materials are replaced by domestic ones, which meet Russian quality standards. Thus, we can conclude that one positive side of the implementation of the import substitution policy (RPI) is the increase in the competitiveness of the company’s products, due to the release of quality products. But at the moment the question remains in the price of imported products. In order to determine how the import substitution strategy is being implemented in Russia, we calculated the average growth rate of industrial sectors before and after the implementation of the import substitution policy. We took the period “before the implementation of the import substitution policy” the last 5 years before the introduction of this strategy by the Russian state from 2099 to 2014 and from 2015 to 2019, the period is selected. Indicating the result of the implementation of the import substitution policy after the application of the strategy [8–10] (Table 2).
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Table 1 The ideal scheme for the implementation of the import substitution policy Step
Description
Industry Affected
First step
Raw material base, produced in our country, assembled on domestic equipment
engineering industry, agricultural industry, chemical industry
Second step
Delivery of raw materials to a domestic enterprise
Engineering industry
Step three
Acceptance of raw materials at the enterprise, its processing and processing, quality control
Engineering industry, light industry
Fourth step
Manufacturing of imported products using domestic equipment
Engineering industry, light industry
Fifth step
Packaging of imported goods in domestic packaging, with a domestic brand, logo, etc.
The intersection of manufacturing industries
Sixth step
Checking the quality of imported (domestic products) manufactured in accordance with state standards
Engineering industry, light industry
Seventh step
Distribution of products to the end Small business support consumer through domestic chain stores
Table 2 Development of industrial sectors before and after the implementation of the import substitution policy based on the average growth rate (calculated by the author). Data source: State statistics website https://belg.gks.ru/construction No
Production type
Average growth rate before FIR
Average growth rate after FIR
1
Food production, incl. Manufacture of beverages and tobacco products
1.14
1.03
2
Manufacture of textiles
1.14
0.96
3
Manufacture of leather and leather products
1.09
1.08
4
Wood processing and manufacture of wood and cork products, excluding furniture, manufacture of articles of straw and plaiting materials
1.17
1.12
5
Manufacture of paper and paper products
1.13
1.83 (continued)
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Table 2 (continued) No
Production type
Average growth rate before FIR
Average growth rate after FIR
6
Production of coke and petroleum products
1.27
1.10
7
Manufacture of chemicals and chemical products
1.19
1.14
8
Manufacture of rubber and plastic products
1.17
1.11
9
Manufacture of other 1.16 non-metallic mineral products
1.09
10
Metallurgical production
1.18
1.07
11
Manufacture of electrical equipment
1.20
1.43
12
Manufacture of other vehicles 1.30 and equipment
0.93
13
Manufacture of other finished 1.50 goods
0.85
Having shown graphically the dynamics of the development of industries in terms of the average growth rate, we can draw a conclusion about the impact of the import substitution policy [11]. From Fig. 1, we see that a significant leap in development is observed in the “production of paper and paper products”, “the production of electrical equipment.” But the decline in production is observed in the industries production of other vehicles and the production of other finished products. The production of foodstuffs, textiles and coke and petroleum products is also declining [12, 13]. Having studied the features of the competitiveness of industrial enterprises in the context of the implementation of the import substitution policy and analyzing the development of industrial sectors and, we can say that the development of industries during the implementation of the import substitution policy reflected the impact on enterprises. Accordingly, in those industries where production at an average growth rate has decreased, it tells us that enterprises have reduced production or have completely ceased to exist. Accordingly, in those industries in which the average growth rate is higher compared to the previous year, the production of manufactured products increased. One of the factors in the development of industrial sectors is the implementation of the import substitution policy [14–16].
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2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
before FIR after FIR
Wood process ing and Food manufa product Manufa cture of Product Manufa ion, Manufa wood Manufa Manufa cture of Manufa Manufa ion of cture of incl. cture of and cture of cture of other cture of Manufa coke chemic Metallu cture of Manufa Manufa leather cork paper rubber nonother cture of rgical electric and als and cture of cture of and product and and metalli vehicle other product al petrole chemic beverag textiles leather s, plastic c paper s and finishe ion equipm um al es and product excludi product product mineral equipm d goods product product ent tobacco s product s ng s ent s s product s furnitur s e, manufa cture of articl… 0
1.14
1.09
1.17
1.13
1.27
1.19
1.17
1.16
1.18
1.2
1.3
1.5
1.03
0.96
1.08
1.12
1.83
1.1
1.14
1.11
1.09
1.07
1.43
0.93
0.85
Fig. 1 Dynamics of development of industrial sectors based on the average growth rate
4 Conclusion In conclusion, it should be said that the implementation of the import substitution policy directly affects the competitiveness of industrial enterprises, through factors and support measures. As our research has shown, EPI does not always have a positive impact and leads to the development and growth of industries and enterprises. From our point of view, it is necessary to revise a number of measures to support industrial enterprises in the context of the implementation of the import substitution policy. Acknowledgements This work was realized in the framework of the Program "Priority 2030" on the base of the Belgorod State Technological University named after V G Shukhov, using equipment of High Technology Center at BSTU named after V. G. Shukhov.
References 1. Alston JM, Beddow JM, Pardee PG (2014) Agricultural research, productivity and food prices. The Giannini Foundation. http://giannini.ucop.edu/media/are-update/files/articles/v12n2_5. pdf. Accessed 15 Sept 2014
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2. Animitsa EG, Animitsa PE, Glumova AA (2015) Import substitution in the industrial production of the region: conceptual, theoretical and applied aspects. Econ Region 3:163–164 3. Kupriyanov SV, Dadalova MV, Dubrovina TA (2015) Assessment of competitiveness of industrial enterprises from the point of view of import placement. Res Results Ser Econ Res 4(6):20–26. https://doi.org/10.18413/2409-1634-2015-1-4-20-26 4. Makarov AN (2011) Import substitution as an instrument of industrialization of the regional economy: an innovative aspect (on the example of the Nizhny Novgorod region). Russian Foreign Econ Bull 5:36–40. https://doi.org/10.15688/jvolsu3.2014.5.3 5. International Competition Intermediate stage (2015) Competitive advantages of countries. International Relations, Moscow 6. Shchetinina ED, Kondrashov IB (2016) Intangible assets as innovative and strategic resources of an enterprise: methods of analysis and evaluation. Bull V.G. Shukhov BSTU 1:214–218. https://doi.org/10.12737/22765 7. Strekozova LV, Belykh TV, Ya V, Genenko VG (2018) Features of the Belgorod real estate market development. Bull V.G. Shukhov BSTU 9:139–144. https://doi.org/10.12737/article_5 bab4a2735b214.25960467 8. Troshin AS, Kupriyanov SV, Sandu IS (2019) Investment and innovation component of the strategic development of the region (on the example of the Belgorod region). IOP Conf Ser Earth Environ Sci 272(3):032236 9. Zaitseva OP (2018) Improving state support for agriculture in the context of import subsidies. Dissertation. Sciences: 08.00.05, Omsk, p 162 10. Pleshkova AO, Mikalut SM, Starikova MS, Shchetinina ED, Rudychev AA (2021) Belgorod Improving the competitiveness of an industrial enterprise on the basis of improving communication interaction with interested parties 11. Kistarikova MS, Usatova LV, Giamfi ED (2021) Analysis of industrial development problems in the context of challenges of innovative economy. Ekonomicheskiy vector 3(26):62–72. https:// doi.org/10.36807/2411-7269-2021-3-26-62-72 12. Starikova MS, Ponomarev N (2020) Marketing potential of the region as a driver of its economic. In the collection: Materials of the scientific International conference “FarEastCon” (ISCFEC 2020). Series: Achievements in Economics, Business and Management Research. Vladivostok, 2020. https://doi.org/10.2991/aebmr.k.200312.279 13. Shchetinina ED, Starikova MS, Shchetinina EA, Solovyov DB (2019) Methodology of assessment and analysis of regional competitiveness based on the evolutionary theory of In the collection: Proceedings of the scientific international conference “Far Eastern Con” (ISCFEC 2018). Ser. “Achievements in economics, business and management research” 2019, pp 1301–1304. https://doi.org/10.2991/iscfec-18.2019.294 14. Shchetinina ED, Ponomareva TN, Dubino NI, Dubrovina TA (2017) The mechanism of managing the competitiveness of an industrial enterprise in the context of import substitution policy. In: International conference on the transformation of research paradigms in the social sciences (RPTSS 2017), pp 1163–1172. https://doi.org/10.15405/epsbs.2018.02.137 15. Isayev JM (2021) The importance of increasing the strategic technological competitiveness of industrial enterprises. Theor Appl Sci 5(97):22–28. https://doi.org/10.15863/TAS.2021.05. 97.3 16. Shep P, Tarasenko A, Tikhanov E, Krivorotov V, Gruchenkova A (2018) The system of indicators of the functioning of the industrial park, reflecting the influence of factors of resident enterprises, In the collection: MATEC at Web Conferences 01036. https://doi.org/10.1051/mat ecconf/201819301036
Thermal and Economic Performance of a Solar Hot Water System in Tashkent Petros Axaopoulos , Alisher Shaislamov , Nodirbek Abdullaev , and Abzalkhon Akxrorkhodjaev
Abstract The article presents the results of studying the possibility of using solar collectors in the small business sector, in particular, to meet the needs of hot water supply for a medium size hotel located in Tashkent. The research methodology and the hot water supply system with its technical characteristics were described in detail. The study used the f-method to determine part of the load on hot water covered by solar collectors. An economic analysis of the proposed system is carried out using Life Cycle Saving method (LCS). The special computer program is developed based on both methods to simulate thermal and economic performance of proposed system. Results show that in spite of high level of solar irradiance in Tashkent region, installing and exploiting solar water heater system seems to be uneconomical. Due to relatively low price of conventional fuel, natural gas and electricity, investing in solar water heating system at all range of solar collector area is not economically attractive. Keywords Solar collector · F-chart · Solar irradiation · Net present value · Investment
1 Introduction Solar water heating systems are the most economical and environmentally friendly systems as they can use the free energy of the sun [1]. Several studies have been done on the technical advancement and economic feasibility of solar water heating systems [1–5]. In the long run, solar water heating systems are economically feasible compared with conventional systems and they have mostly a payback period of 2– 8 years which may be influenced by a number of factors [1–6]. The solar thermal P. Axaopoulos (B) University of West Attica, Ag. Spyridonos, 12210 Aegaleo, Greece e-mail: [email protected] A. Shaislamov · N. Abdullaev · A. Akxrorkhodjaev Tashkent State Technical University, 2 Universitetskaya, 100095 Tashkent, Uzbekistan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_80
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systems for hot water production in residential and hotel sector are the most accessible and promising energy saving options. Hiller and Johnson did some research on the water and energy consumptions in the hotel sector, and found that the domestic hot water system is one of the major end users of the energy and water [7, 8]. A survey on the domestic hot water (DHW) usage in hotels revealed that the total hot water use was as high as 9.84 million liters for the business hotel and 2.91 million liters for the travel hotel over a 13-month monitoring program [8–11]. The sizing of a solar hot water system, however, is a complex problem because of the many different parameters that must be considered. These parameters are always associated with significant uncertainties [8, 9]. For example, the usage pattern of the DHW system is strongly associated with the occupant behaviors, climatic conditions, seasonality, building type and its constructure [10], socio-economic factors [11] and therefore the usage is stochastic and highly time-diverse [12]. Selecting the right input values for these parameters is usually tricky and confusing for designers and building molders, especially for those who do not have much experience in this area [13]. The most accurate way of sizing a system is dynamic simulation by means of a computer model. Simulations, however, are not convenient because they require hourly meteorological data and are so complex to use that they are suitable only for computers. These have necessitated the development of simpler sizing methods as the f-chart [14] and other methods [15]. The f-chart method is one of the most comprehensive and widely used simplified methods, for predicting the monthly and annual solar fraction of active solar heating systems. Results from such methods are very helpful for solar system design since they allow one to learn about the complex interaction of a large number of variables in a short time, whereas experiments are time consuming and costly. After all these, we considered an active solar thermal system for hot water production installed in a medium size hotel in Tashkent, in order to evaluate its thermal performance and its economic viability. The computer programme used has been developed at Renewable Energy Laboratory of Mechanical Engineering Department of University of West Attica in Athens, Greece, and is based on f-chart method [16]. The developed software is a very fast and easy to use tool for predicting the monthly and annual solar fraction of active solar heating systems and to study its economic viability using the life cycle savings method.
2 Methods For the thermal performance evaluation of the proposed solar system, the developed software is based on f-chart method, while for the economic analysis is based on the Life cycle savings (LCS) method. The conditions of the simulations were varied over appropriate ranges of parameters of practical system designs. Several assumptions were made, most of which tend to lead to conservative predictions of performance. One of the three standard
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system configurations for which the method has been developed is the domestic hot water heating using water heating collectors and an external collector-storage heat exchanger to transfer heat from the collector to storage. Fanney and Klein [17] have compared f-chart predictions against the actual measured performance of six different domestic hot water solar thermal systems over an entire year, and have reported agreement between actual performance and f-chart predictions of solar fractions to within 5%. The required input parameters by the developed program are entered by the user at the beginning of the program. The input parameters are divided in two main categories, one for the solar system and the load and the other for the system’s economics.
2.1 System Configuration The thermal solar system is designed to produce domestic hot water for a medium size hotel in Tashkent, Uzbekistan and based on the standard system configuration defined by f-chart method. It consists of liquid glazed flat-plate collectors, a single water storage tank and an external heat exchanger between solar collector and storage tank, a pump, tee-piece, flow diverter, controllers and insulated piping. Each solar collector has an aperture area of 1.306m2. The technical specifications of the solar thermal system and load are shown in Table 1 and the monthly weather data for Tashkent are shown in Table 2. Tashkent’s climate falls into category Csa zone, according to KÖppen climate classification categories [18]. The hotel has three floors with 30 double rooms and is considered to have an average annual occupancy of 50%, (30 persons/day), with a total daily water consumption of 2 m3 at a delivery temperature of 50 0 C. Daily hot water consumption also includes hot water requirements for the restaurant (0.5 m3 /day). It should be noted that the total heating load consists of the water heating load and the piping heat losses. In addition, the roof of the hotel is not shaded, is more than 200 m2 and is available for installation of solar collectors. The collector used for the means of this study is a commercially available product which has been experimentally tested by an approved center for solar collector testing, in order to determine its thermal performance parameters according to standard test procedure EN-12975–2. The collector is suitably insulated, with glass wool of 40 mm at the back and 20 mm at the sides, and enclosed in an aluminium box supporting the absorber plate. The transparent cover is a low iron tempered glass with a thickness of 4 mm. The working fluid used in the closed loop of the collectors is a water–glycol mixture of 40% by volume to prevent freezing. An auxiliary heating unit is present as part of the system. It simply is a heater placed between the storage tank and the consumption in order to supply the auxiliary energy required to heat the water, if necessary. The orientation of the solar collectors is facing towards the true south, while its tilt angle is taken equal to the latitude of the city of Tashkent.
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Table 1 The solar thermal system and load specifications Collector parameter set
Value
Test slope parameter:
6.471 W/m2 °C
Test intercept parameter:
0.674
Number of glazing:
1
Collector tilt:
40°
Collector - heat exchanger correction factor:
0.97
Storage capacity:
64 l/m2
Piping parameter set Pipe length:
20 m
Piping heat loss coefficient:
0.5 W/m°C
Hours of daily operation:
16 h
Piping ambient temperature:
19 °C
Hot water load parameter set Occupants:
30
Daily consumption:
50 l/day·pers
Hot water temperature:
50 °C
Table 2 Monthly weather data for Tashkent Month
Ambient temperature, [o C]
Solar irradiation on horizontal surface, [kWh/m2 ] 54.3
Mains water temperature, [o C]
Jan
0.5
11.5
Feb
2.3
75.8
11.2
Mar
8.6
110.8
12.4
Apr
15.1
164.8
15.1
May
20.5
217.0
18.4
Jun
25.3
236.0
21.5
Jul
27.7
237.7
23.5
Aug
25.4
213.2
23.9
Sep
19.8
164.5
22.6
Oct
13.3
110.5
19.9
Nov
7.7
62.5
16.6
Dec
3.4
46.8
13.5
Thermal and Economic Performance of a Solar Hot Water … Table 3 Economic parameters
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Economic parameter set
Value
Area dependent cost
200e/m2
Fixed cost
350 e
Maintenance cost (MC)
30 e
MC inflation rate
6%
Domestic electricity price
0.0351 e/kWh
Natural gas price
0.0051 e/kWh
Domestic electricity inflation rate
8%
Heating oil price inflation rate
7%
Heating gas price inflation rate
8%
Bank loan interest rate
12%
Loan lifetime
20 years
Economic analysis
20 years
Market discount rate
12%
Furnace efficiency
0.85
2.2 Economic Analysis For the economic viability of the studied solar system, a simple economic analysis based on the Life Cycle Savings (LCS) method has been performed with the help of the second developed program. This method is widely applied for determining energy systems economics [18, 19]. In this method, the net cash flow of all anticipated future costs and benefits between two alternative energy investments are discounted to their present values. As it is emphasized on costs, it is a suitable method for evaluating the economic feasibility of projects that realize their benefits primarily by reducing the consumption and cost of fuel. This method can also be used to find the economically optimum design of a given system. The estimation requires the synthesis of both the energy performance results and a number of economic parameters. Required energy performance data have been calculated using the developed software tool. The set of assumed economic parameters are shown in Table 3 and were obtained from the Electricity Authority of Tashkent and one of the banks operating in Tashkent. The two energy systems compared in this study is a solar thermal system plus auxiliary energy and a conventional heating system. The fuel and electricity costs are being considered for each case and compared to each other. The conventional heating system is assumed to be a natural gas-fired boiler and an electrical respectively.
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3 Results and Discussion
0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0
800 700 600 500 400 300 200 100 0
Solar fraction Productivity 0
10
20
30 40 Collector area, m2
50
60
Productivity, kWh/m2y
Annual solar fraction
The calculations of the thermal performance for the active solar system considered were based on the developed tool at the Renewable Energy Laboratory of Mechanical Engineering Department. Using this software and taken into account the specification for this system, the program was run with the meteorological data of city of Tashkent and the results are shown in diagrams. The annual solar fraction and the useful solar heat output per unit collector area for different collector areas, are shown in Fig. 1. As it can be seen, the annual productivity values are satisfactory for the collector areas investigated, due to the high solar irradiation received on the collector area, for the city of Tashkent. According to Life Cycle Saving method, if the NPV is positive, then, on the basis of the anticipated costs and savings, the investment is economically viable. Thus, the economic results in Fig. 2, clearly shown that at current natural gas prices, and for the collector areas investigated, the solar system appears to be uneconomical. It is worth mentioning here that the economics of the system mainly depend on the end use, the climate and the prices in the country of application. Thus, while the climate in Tashkent is favorable for solar thermal systems, the prices of conventional fuels are still quite low. However, it is interesting to examine the viability of a specific solar project at different natural gas prices and investment costs. For this reason, an active solar thermal system for domestic hot water has been considered. The system consists of 40 m2 collectors and covers 50% of annual total hot water demand of the examined hotel. In Figs. 2 and 3, the horizontal line at zero profitability index divides the chart into the upper region, where the system is economic and to the one below where it is uneconomic. By definition, a zero value for the profitability index gives the break-even point. The Fig. 3 shows the values of profitability index, which is defined as the NPV/Investment cost (P.I.), at different natural gas prices. Points beyond the intersection of two lines indicate net system benefits. In addition, this figure indicates that if a natural gas price of 0.0051 e/kWh is assumed, the solar system
70
Fig. 1 Variation of annual solar fraction and annual productivity at different solar collector area
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is not considered economically viable until the natural gas cost reaches the breakeven point of 0.021 e/kWh. Obviously, the solar project is more profitable if the cost of displaced conventional fuel is more expensive than the current price of the natural gas. Thus, assuming that the displaced energy is electricity with the current value of 0.0351e/kWh, then the solar project appears to be economically viable. The profitability index for different investment costs is shown in Fig. 4. The investment cost should be reduced enough for the curve to meet the straight line. Assuming an investment costs lower than 1100 e, the system is economically viable. An investment cost to the right of the intersection point of the curve with the horizontal line, indicates an uneconomical system and probably a state financial support is required so to consider it viable. The last two figures show clearly the effect of state intervention on the fuel prices and solar market. Collector area, m2
0 0
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NPV, €
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Fig. 2 Variation of net present value at different solar collector area
Profitability Index
0.2 0 -0.2
0
0.005
0.01
0.015
-0.4 -0.6 -0.8 -1
Fuel cost, €/kWh
Fig. 3 Variation of profitability index at different natural gas prices
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-0.4 -0.6 -0.8 -1
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Fig. 4 Variation of profitability index at different investment cost
4 Conclusions The developed two programs are able to make energy and economic evaluation of the proposed solar system for hot water production respectively. The installation of a similar system in the region of Tashkent appears to have quite satisfactory thermal performance, presenting a high annual productivity. However, considering the actual economic conditions in Tashkent, the proposed system seems to be an uneconomical investment and probably state financial support is required to render it viable, as already applied in a number of European countries. At present, incentives for investment in solar collector systems are provided on a national level, including direct contributions, low interest loans, income tax relief or reduced VAT. In the future, the collector systems have to be cost effective without monetary incentives. Also, in country it is implementing market stimulation programs, including measures such as government purchasing and financial support of manufacturers and buyers of solar systems, because is the only way for a sustainable development which can lead to a sustainable society. Acknowledgements The authors thank the management of the Sayyokh Hotel in Tashkent for their kindly providing technical documentation and information on the hotel, which were used in the calculations and writing the article. The authors are also grateful to the ERASMUS + Financing Program, which made it possible to conduct joint research and write an article.
References 1. Shukla R, Sumathy K, Erickson P et al (2013) Recent advances in the solar water heating systems: a review. Renew Sustain Energy Rev 19:173–190. https://doi.org/10.1016/j.rser.2012. 10.048 2. Raisul Islam M, Sumathy K, Ullah Khan S (2013) Solar water heating systems and their market trends. Renew Sustain Energy Rev 17:1–25. https://doi.org/10.1016/j.rser.2012.09.011
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3. Gautam A, Chamoli S, Kumar A et al (2017) A review on technical improvements, economic feasibility and world scenario of solar water heating system. Renew Sustain Energy Revs 68:541–562. https://doi.org/10.1016/j.rser.2016.09.104 4. Sabiha MA, Saidur R, Mekhilef S et al (2015) Progress and latest developments of evacuated tube solar collectors. Renew Sustain Energy Rev 51:1038–1054. https://doi.org/10.1016/j.rser. 2015.07.016 5. Essabbani T, Moufekkir F, Mezrhab A et al (2015) Numerical computation of thermal performance of a simulation of a solar domestic hot water system. Appl Solar Energy 51(1):22–33. https://doi.org/10.3103/S0003701X15010089 6. Passos L, Cardemil JM, Colle S (2014) Feasibility study of using domestic solar hot water systems as alternative to reduce the electricity peak demand in Brazil. Energy Procedia 57:2487–2495. https://doi.org/10.1016/j.egypro.2014.10.258 7. Hiller CC, Johnson R (2017) Hot-water use in hotels: Part 4-Comparison of travel and business hotel hot-water system monitoring results. ASHRAE Conf-Pap 123:143–159 8. Hiller C, Johnson R (2015) Establishing benchmark levels and patterns of commercial hotwater use-hotels. https://www.techstreet.com/standards/rp-1544-establishing-benchmark-lev els-and-patterns-of-commercial-hot-water-use-hotels?product_id=1900399 Accessed 27 Oct 2021 9. Lowenstein A, Hiller CC (1998) Disaggregating residential hot water use - Part II. ASHRAE Trans 104(1B):1958–1863 10. Axaopoulos PJ, Fylladitakis ED, Shaislamov AS et al (2019) Financially optimum insulation thickness of external building walls. AIP Conf Proc 2190:020034. https://doi.org/10.1063/1. 5138520 11. Fuentes E, Arce L, Salom J (2018) A review of domestic hot water consumption profiles for application in systems and buildings energy performance analysis. Renew Sustain Energy Rev 81:1530–1547. https://doi.org/10.1016/j.rser.2017.05.229 12. Hendron R, Burch J, (2007) Development of standardized domestic hot water event schedules for residential buildings. Paper presented at ASME 2007 Energy Sustainability Conference, Long Beach, California, 27–30 July 2007. https://doi.org/10.1115/ES2007-36104 13. Pang Z, O’Neill Z (2018) Uncertainty quantification and sensitivity analysis of the domestic hot water usage in hotels. Appl Energy 232:424–442. https://doi.org/10.1016/j.apenergy.2018. 09.221 14. Klein SA, Beckman WA, Duffie JA (1976) A design procedure for solar heating systems. Sol Energy 18(2):113–127. https://doi.org/10.1016/0038-092X(76)90044-X 15. Aste N, Beccali M, Tagliabue LC (2012) Nomograph for rapid technical and economic assessment of solar thermal systems for DHW production. Sol Energy 86(9):2472–2485. https://doi. org/10.1016/j.solener.2012.05.022 16. Axaopoulos P, Pitsilis G (2007) Energy software programs for educational use. Renew Energy 32(6):1045–1058. https://doi.org/10.1016/j.renene.2006.08.006 17. Fanney AH, Klein SA (1983) Performance of solar domestic hot water systems at the national bureau of standards—measurements and predictions. J Sol Energy Eng Trans ASME 105(3):311–321. https://doi.org/10.1115/1.3266384 18. Panagiotidou M, Aye L, Rismanchi B (2020) Solar driven water heating systems for mediumrise residential buildings in urban mediterranean areas. Renew Energy 147:556–569. https:// doi.org/10.1016/j.renene.2019.09.020 19. MorrisseyJ HRE (2011) Life cycle cost implications of energy efficiency measures in new residential buildings. Energy Build 43(4):915–924. https://doi.org/10.1016/j.enbuild.2010. 12.013
Influence of Heat and Humidity Conditions on the Operation of the Pin Connections Sergey Fedosov , Vitaly Kotlov , Anatoly Pozdeev , Anatoly Aktuganov , Yulia Kuznetsova , Oleg Aktuganov , and Tatyana Pugacheva
Abstract Currently in Russia, a lot of attention is paid to the development of housing construction using wood. The share of housing construction with the use of wooden structures is planned to increase from the current 2 to 10% by 2030. Joints of wooden elements of such structures are carried out with the help of glues, dowels, nails, glued rods and metal connections. The main way to connect wooden elements in the nodes of the frame of multi-storeyed wooden buildings are cylindrical dowels made of steel, aluminium alloys, fiberglass, oak, birch, and other types of hardwood. The paper considers the strength characteristics of nail joints of wooden structures under cyclic changes in the temperature-humidity regime of the operating environment. Arrhenius law, which describes the rate of chemical transformations, is used as the basis of mathematical modelling. The maximum permissible number of moistening and drying cycles of wooden structures elements with dowel joints has been determined for the given duration and temperature processes. Keywords Wooden frame · Nagel connections · Heat and moisture transfer · Analytical expression
1 Introduction The dowel connections used in the joints of wooden structures are very simple in their design scheme, but are distinguished by the complexity of theoretical methods of calculation, taking into account different types of loads and the characteristics of the operating environment. S. Fedosov (B) · V. Kotlov · A. Pozdeev · A. Aktuganov · Y. Kuznetsova · O. Aktuganov · T. Pugacheva Volga State University of Technology, Lenin Square, 3, 424000 Yoshkar-Ola, Russian Federation e-mail: [email protected] S. Fedosov Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, 129337 Moscow, Russian Federation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_81
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The work of dowels is very complex and in the connections of wooden structural elements, it is customary to talk about the allowable load that does not cause a “shear” of a dowel. As applied to wooden structures, this definition is very conditional, since it is impossible to cut the steel dowel by wooden elements [1]. The stress–strain state of dowel joints is well enough studied, but the operation of metal dowels in hardwood structures under the effect of temperature and humidity conditions has not been practically studied. Metal dowels during operation are greatly influenced by the humidity of wood, leading to metal corrosion, flowing under a film of moisture and affecting the adhesion of metal to wood, as well as the destruction of the cell structure of wood [2].
2 Methods In the process of operation, heat and moisture transfer processes occur in the nail joints, the regularities of the influence of which are currently poorly studied. In [3], mathematical models of heat transfer processes in the “cylindrical nailwood” system are considered. As a simplifying assumption, it is assumed that in the initial state the temperatures of the dowel and the wood are the same. The boundary value problem of heat transfer in the general case is reduced to nonlinear inhomogeneous differential equations of parabolic type in partial derivatives. The method of “microprocesses” [4–7], which belongs to semi-analytical methods, allows this boundary value problem to be reduced to a system of linear homogeneous differential equations with constant coefficients. Dimensionless variables for the heat conduction problem have the form: T (x, Fo) =
t(x, τ ) − t0 ; t H − t0
a·τ x Fo = 2 ; x = . L 2 L 2
(1)
The solution of the problem posed was made by the operational method based on the integral Laplace transform [8] in the MathCad application software [9]. Hence follows the expression for the dependence of the temperature on the current radius and the Fourier number: 1 −R0 + r R0 · er f c · . (2) T (r, Fo) = −r · T (r ) + 2 · T0 · r 2 Fo1/ 2 Next, the numerical values of the dimensionless temperature and the relative radius of the dowel are set T0 := 0.1 and R0 := 0.01. Determination of the temperature distribution function along the radius at the initial moment of time in the form T (r ) = T0 · (r − R0 ) allows us to plot the dependence of the dimensionless temperature distribution on the dimensionless radial distance from the center of the pin and the Fourier number.
Influence of Heat and Humidity Conditions on the Operation …
T (r, Fo) = −T0 · (r − R0 ) + 2 · T0 ·
1 r − R0 R0 . · er f c · r 2 Fo1/ 2
793
(3)
When displaying the graph, the ranges of variation of the dimensionless radial distance from the center of the pin and the Fourier number are determined r := 0.01...1, Fo := 0...1.
3 Results and Discussion Cellulose fibres create a framework that takes up loads, and lignin acts as a binder for the elements of the cellulose framework. The chemical resistance of cellulose is higher than that of lignin. The destruction of lignin occurs due to the violation of bonds between the molecules of the compounds that make up lignin and to take into account the effect of temperature it is convenient to use the Arrhenius law for the chemical process of destruction of lignin molecules. It can be assumed that the mechanical strength of wood is proportional to the number of lignin chemical bonds remaining in operation during their gradual destruction under the influence of heat and mass transfer factors. Therefore, we can write the ratio: R = R0
N , N0
(4)
where R0 i R ≤ R0 —initial and current values of mechanical strength of wood; N0 —initial number of chemical bonds. The rate of increase in the kinetic energy of activation of intermolecular bonds , J/s. , J/s. The rate of change in the potential energy of intermolecular bonds The rate of chemical transformations is K, 1/s. Absolute temperature T, K. Boltzmann constant k = 1.380649 · 1023 , J/K. is proportional to the total potenThe increase in the kinetic activation energy equal to the product of the potential energy of intermolecular bonds tial energy , J/s. and the rate of chemical transformations Substitution of values of energy indicators of the process, J/s.
T · dK · k = E · K
(5)
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Forms of the energy balance equation, J/s T · dK = E · K,
E dK = . K k·T
(6)
Integration of the energy balance equation, J/s K 1 K0
ln(K ) − ln(K 0 ) i f 0 > K ∨ K 0 > 0 = E 1 dK = → unde f ined other wise K k·T
E k·T
.
(7)
Resulting the equation has the form
E , K = K 0 · exp k·T
(8)
which coincides with the Arrhenius equation [7]. Therefore, to determine the number of residual chemical bonds of lignin, it is advisable to use the Arrhenius law, according to which the rate constant of chemical transformations is equal to K = K 0 · exp
E , k·T
(9)
where is the K rate constant of a chemical reaction, 1/s; K 0 —the number of chemical interactions per unit of time, 1/s; E—activation energy of a chemical reaction, J; T —absolute temperature, K; k = 1.380649 · 1023 , J/K—Boltzmann’s constant. With a known constant of the rate of chemical reaction, the value of the rate of change in the number of unbreakable chemical bonds of lignin, kg/(s·m3 ), is determined by the expression
E dN = −K · N = −N · K 0 · exp − , dt k·T
(10)
where is the N—number of chemical bonds, 1/m3 , remaining in operation at a time t in a single reaction order. This makes it possible to obtain an expression for determining the value of the chemical bonds remaining N1 ≤ N0 in the work at the time t1 of the end of the first cycle of moistening and drying.
E , N1 = N0 · exp −t1 · K 0 · exp − k · T1 where t1 —the duration of the first cycle of moistening and drying.
(11)
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For the second cycle of moistening and drying wood, by analogy with the previous one, you can write N2 N1
dN =− N
t2 t1
E dt, K 0 · exp − k · T2
(12)
where N2 ≤ N1 —the number of chemical bonds remaining in the work at a time t2 ≤ t1 end of the second cycle; t1 , t2 —initial and final moments of time of the second cycle, s, t1 = 0; T2 —absolute temperature within the time interval of the first cycle, K. This allows us to obtain an expression for determining the value of the chemical bonds remaining in the work N2 ≤ N1 , at the time t2 of the end of the second cycle of moistening and drying
E E · exp −t2 · K 0 · exp − , N2 = N0 · exp −t1 · K 0 · exp − k · T1 k · T2 (13) where t2 = t2 − t1 —the duration of the second cycle of moistening and drying. By repeating similar calculations based on the method of mathematical induction, it is possible to obtain a formula for determining the number of chemical bonds remaining in the work, with an arbitrary number nu of consecutive cycles of moistening and drying the wood of the nail compounds (14) where ti is the duration of the i-th cycle of moistening and drying; Ti is the absolute temperature within which the cycle proceeded, K. After substitution (13) into (4) the formula for determining the current value of the mechanical strength of wood takes the form (15)
If the following cycles of moistening and drying of wood have the same duration ti = t = const and proceed at the same temperature Ti = T = const, the latter dependence is noticeably simplified. In this case, the summation in this formula can be replaced by the product (16)
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The resulting expression allows you to determine the permissible number of moistening and drying cycles. As you know, the ratio of the value of the ultimate strength R0 to the value of the allowable stress is called Rad the safety factor K3 =
R0 . R∂on
(17)
The practical significance of this parameter lies in the fact that during the operation of the nail joint, the mechanical strength of wood decreases over time and under the influence of cyclic processes of moistening and drying until it reaches an acceptable value. At this moment, the destruction of the wood and the nail joint occurs. The number of moistening and drying cycles of wood, which preceded this event, should also be considered an acceptable value of this parameter, and its knowledge is of practical importance. Obviously, if we take R = Rad on the left side of Eq. (15), we should assume that the number of cycles present on the right side will be equal to the allowed value n u = n ad . Then the equation taking into account (16) can be written in the form
E 1 . = exp −K 0 · n ∂on · t · exp − K3 k·T
(18)
As a result of solving this equation with respect to the following expression can be obtained for determining the permissible number of moistening and drying cycles of the wood of the nail joint n ∂on =
E ln K 3 exp − . K 0 · t k·T
(19)
Next, the number of moistening and drying cycles is displayed using an automated solution of the Arrhenius equation. As a result, the calculated number of humidification cycles was established, which is in good agreement with the experimental results. Universal gas constant R := 8.314 J/(mol·K). Relative air humidity. ϕ := 0.01...0.93. Empirical dependence of the activation energy the process of drying wood from air humidity E γ 1 (ϕ) := 107.6 · exp(3.46 · ϕ) + 34000, J/mol [10]. Set air humidity ϕ := 0.80. Energy activation of the wood drying process at a set air humidity E γ 1 (ϕ) := 3.571 × 104 , J/mol. Heating temperature T (t) := 273.15 + t, K. Heating temperature range, t := 0..50, °C. Change range heating temperature T := 273.15...50 + 273.15, K. Period of thermal vibrations of atoms around the equilibrium position τ0 := 10−12 , s. Frequency factor K 0 (ϕ, T ) := τ10 K 0 (ϕ, T ) = 1 · 1012 , s.
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Function of the specific rate constant from humidity and temperature
E γ 1 (ϕ) . κγ 1 (ϕ, T ) := K 0 (ϕ, T ) · exp − R·T
(20)
Relative air humidity ϕ := 0.80. Energies activation of the wood drying process at a given air humidity, J/mol E γ 1 (ϕa ) := 107.6 · exp(3.46 · ϕ) + 34000.
(21)
Heating temperature ta := 40◦ C. Heating temperature Ta := 273.15 + ta , K. Specific rate constant at given values of constant humidity and temperature
E γ 1 (ϕa ) , κγ 1a (ϕa , Ta ) := K 0 (ϕa , Ta ) · exp − R · Ta
(22)
κγ 1a (ϕa , Ta ) = 1.103 × 106 .
(23)
The logarithmic form of the Arrhenius equation has the form ln k(T ) := E 1 (ϕa ) κγ 1a (ϕa , T ) that allows you to write ln k(T ) := − γR·T + ln(K 0 (ϕa , T )). This dependence is reflected in the graph. Determination of the slope of the plotted curve Bending strength of wood for moisture more than 30%, σ := 59.5 MPa. Allowable mechanical stress during static bending, σ∂on := 100 MPa. σ K s := Ratio of ultimate strength to allowable stress in the dowel joint K s := σ∂on 0.595. hours. Duration of processes of moistening and drying Duration of processes of moistening and drying of wood . Boltzmann constant k := 1.380649 · 1023 J/K. Specific rate constant and its logarithmat a given moisture and temperature κγ 1a (ϕa , Ta ) = 1.103 × 106 ln κγ 1a (ϕa , Ta ) = 13.914. Frequency factor K 0 (ϕa , Ta ) := 10−12 , s. The number of wetting and drying cycles using the ratio of the tensile strength to the value of l of the dropped mechanical stress in the dowel joint n ∂ona
E γ 1 (ϕa ) ln(K s ) = 15.908 r ound(n ∂ona ) = 16. · exp − := − K 0 (ϕa , Ta ) · t R · Ta (24)
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4 Conclusions 1. The stress–strain state of dowel joints has been studied sufficiently, but the effect of temperature and humidity conditions on the work of wood and metal and dowels from hard wood has not been studied enough. 2. In the nodal joints with a metal dowel, processes of heat and moisture transfer take place, the patterns of influence of which are currently poorly understood. 3. The density of the heat flux transferred by means of thermal conductivity, proportional to the temperature gradient, which is taken as the basis for the influence of the temperature and humidity regime of the operation of the nail joint. 4. The strength of the wood of the dowel joint under cyclic fluctuations in the temperature and humidity conditions of operation is determined taking into account the effect of temperature on the chemical process of destruction of wood lignin and the chemical process of destruction of molecular bonds using the Arrhenius equation.
References 1. Smith I, Asiz A, Design SM (2006) Method for connections in engineered wood structures. University of New Brunswick, Fredericton 2. Glass SV, Zelinka SL (2021) Chapter 4: moisture relations and physical properties of wood. In: Wood handbook—wood as an engineering material. General Technical Report FPL-GTR-282. Department of Agriculture, Forest Service, Forest Products Laboratory, Madison 3. Glass SV, Boardman CR, Zelinka SL (2017) Short hold times in dynamic vapor sorption measurements mischaracterize the equilibrium moisture content of wood. Wood Sci Technol 51:243–260. https://doi.org/10.1007/s00226-016-0883-4 4. Jakes JE, Plaza N, Stone DS, Hunt ChG, Glass SV, Zelinka SL (2013) Mechanism of transport through wood cell wall polymers. J For Prod Ind 2(6):10–13 5. Glass SV, Boardman CR, Thybring EE et al (2018) Quantifying and reducing errors in equilibrium moisture content measurements with dynamic vapor sorption (DVS) experiments. Wood Sci Technol 52:909–927. https://doi.org/10.1007/s00226-018-1007-0 6. Zelinka SL, Glass SV, Jakes JE et al (2016) A solution thermodynamics definition of the fiber saturation point and the derivation of a wood–water phase (state) diagram. Wood Sci Technol 50:443–462. https://doi.org/10.1007/s00226-015-0788-7 7. Pásztory Z, Horváth N, Börcsök Z, Sanaev VG, Gorbacheva GA (2019) Thermal conductivity change in spruce and poplar wood after heat treatment. For Bull 23(3):95–100. https://doi.org/ 10.18698/2542-1468-2019-3-95-100 8. Candelier K, Thévenon MF, Pétrissans A, Dumarçay S, Gerardin P, Pétrissans M (2016) Control of wood thermal treatment and its effects on decay resistance: a review. Ann For Sci 73(3):571– 583. https://doi.org/10.1007/s13595-016-0541-x 9. Ermochenkov MG, Evstigneev AG (2018) Change of wood properties in thermal modification. For Bull 22(1):94–99. https://doi.org/10.18698/2542-1468-2018-1-94-99 10. Engelund ET, Thygesen LG, Svensson S, Hill CAS (2013) A critical discussion of the physics of wood–water interactions. Wood Sci Technol 47(1):141–161. https://doi.org/10.1007/s00226012-0514-7
Pattern of Distribution of Carbon Nanotubes in the Matrix of Polymer Compositions for Wood Stabilization Mikhail Lisyatnikov , Mikhail Sergeev , Danila Chibrikin , and Mikhail Lukin
Abstract The paper presents the results of studying the patterns of distribution of carbon nanotubes in the matrix of polymer compositions for wood stabilization based on polyester resins—methyl methacrylate. As a result of testing samples of destructed wood with modification under short-term loads, it was found that the highest compressive and chipping strength along the fibers was achieved by samples modified with a polymer composition based on Anacrol 90W2 with the introduction of carboxylated nanotubes into the composition (25–30% increase in strength relative to the sample without modification). Using scanning electron microscopy on Quanto 200 3D equipment, the nature of the distribution of the filler inside the matrix was established. The filler introduced into the polymer in the form of carboxyl CNTs is distributed evenly, in contrast to pre-activation in an ultrasonic bath and conventional carbon nanotubes, which causes a greater increase in strength during the stabilization of destructed wood. Keywords Polymer composition · Filler · Carbon nanotubes · Nanotube preactivation · Microscopy · Wood stabilization
1 Introduction Wood, as a structural material, has unsurpassed properties, being a natural renewable resource [1]. Manufacturability of processing, availability, high physical and mechanical properties, environmental friendliness allow the efficient use of wood in various areas of the construction industry [2–15]. However, the issue of preservation and restoration of monuments of historical and cultural heritage stands apart, in which wood was widely used in the construction of walls, ceilings and coatings. According to statistics, in 80% of cases, the failure of an element of wooden structures occurs for reasons caused by biological and structural defects in wood. M. Lisyatnikov (B) · M. Sergeev · D. Chibrikin · M. Lukin Institute of Architecture Construction and Energy Engineering, Vladimir State University named after Alexander and Nikolay Stoletovs, 87 Gorky Street, Vladimir 600000, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_82
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These include: rotting of the supporting and contact zones of wooden structures with metal, stone and reinforced concrete structures; the formation of defects in the form of cracks and delamination of wooden elements due to variable temperature and humidity conditions of operation; the influence of defects located in the most loaded areas of the structure, etc. In order to maintain the operable state of structures, extend their life cycle, as well as ensure operational reliability, it becomes necessary to carry out work to strengthen and surface repair of elements. For traditional buildings of historical and cultural value, the use of external reinforcement systems invariably leads to a loss of architectural appearance and authenticity, which is unacceptable. Therefore, the main way to strengthen wooden structures in such buildings is the stabilization of wood with polymer compositions [16–36]. The introduction of any filler and carbon nanotubes (CNTs), in particular, into the structure of the composite affects the structure and properties of the polymer binder, as well as the final composite material as a whole. There are a significant number of works devoted to the functionalization of CNTs, as well as to the study of the physico-mechanical properties of polymer composites based on them. In most works, when studying the properties of composites, CNTs functionalized according to some specific technique are used. The degree of functionalization can be expressed as the ratio of carbon atoms associated with functional groups to the total number of carbon atoms in functionalized CNTs. Functionalization allows the separation of entangled CNTs, which facilitates the transition of tubes into aqueous or organic solutions. It plays an important role in the preparation of composites, since it provides a stronger interaction of the filler with the matrix and thus improves the mechanical properties of the material. As a result of oxidation, various functional groups are formed on the surface of carbon nanotubes: ether, carboxyl, hydroxyl, aldehyde, ketone, anhydride, lactone. The subject of a specific study was the study of the patterns of distribution of carbon nanotubes in the matrix of polymer compositions for stabilizing wood. To achieve this goal, the following tasks were set: 1. Choose the initial binder (resin) of the polymer composition that has the best properties for stabilizing degraded wood. 2. To study the patterns of distribution of the filler in the form of carbon nanotubes in the matrix of the polymer composition using the microscopy method. 3. Choose a specific type of carbon nanotube filler to be added to the polymer composition.
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2 Methods At the beginning of the study, the initial binders (resins) of the polymer composition were considered: – – – –
Anacrol 901; Anacrol 90W2; Melamine resin; Etalak.
To improve the physicomechanical properties of these polymers, carbon nanotubes were introduced, the mass fraction of which was determined experimentally (from 0 to 1.1%). The following carbon nanotubes were chosen for the study: MCNT DEALTOME; CNT “Taunit M” carboxylated. All of the listed substances are used in the stabilization (modification) of wood, and they are relatively non-toxic. An ultrasonic cavitator was used to preactivate MUNT with DEALTOM. A container with carbon nanotubes was sonicated at an intensity of 50% for 20 min (Fig. 1).
Fig. 1 General view of the ultrasonic cavitator during the preactivation of carbon nanotubes
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As a result of the introduction of CNTs into the original resins and the modification of destructed wood, a series of prototypes were created for testing under shortterm loads [37–40]. The studies carried out on a universal tensile testing machine equipped with an automatic graph plotter showed that the highest compressive and shear strength along the fibers was achieved by samples modified with a polymer composition based on Anacrol 90W2 with the introduction of carboxylated nanotubes into the composition (25–30% of the increase strength relative to the sample without modification). These experiments made it possible to choose the initial binder, but the question of the nature of the distribution of CNTs inside the polymer matrix remained open. To study the regularities of the distribution of the filler inside the resin, polymer samples were prepared in a special form (Fig. 2). Since the polymerization of Anacrol 90W2 occurs at a temperature not lower than 90 º C, the samples were placed in an oven (oven) at a temperature of 90 º C for fast curing (Fig. 3). After extraction from the metal mold, the resulting polymer composites were placed in a solution of ED-20 epoxy resin and cured with polyethylene polyamine PEPA at room temperature for 24 h (Fig. 4.). This operation is necessary to create a flat surface in order to obtain the highest quality image using electron microscopy. For the best result, the cured samples were further processed on a flatbed machine until a smooth surface without flaws was achieved (Fig. 5).
Fig. 2 Preparation of samples of the polymer composition with filler
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Fig. 3 General view of the oven for curing polymer compositions
Fig. 4 General view of polymers filled with carbon nanotubes
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Fig. 5 Processing of polymer composites on a train machine
Further, the authors carried out a study of polymer samples filled with carbon nanotubes by microscopy on specialized equipment Quanta 200 3D.
3 Results and Discussion As a result of a microscope study of the nature of the distribution of different types of carbon nanotubes in a polymer matrix based on Anacrol 90W2, the following images were obtained (Fig. 6). After analyzing the results of microscopy, it was found that the filler introduced into the polymer in the form of carboxyl CNTs is distributed as uniformly as possible throughout the entire matrix. Preactivation carbon nanotubes and ordinary carbon nanotubes form cavities during distribution, which adversely affects the uniformity of the matrix, and, as a result, the strength of the final composite. That is why the samples of modified destructed wood with the use of carboxylated CNTs showed the highest strength.. The attachment of carboxyl groups to the surface of carbon nanotubes reduces the interaction of van der Waals forces between them, which facilitates the process of separating nanotube bundles into individual tubes or into small bundles.
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Fig. 6 General view of the results of microscopy. Distribution of different types of CNTs in the modifier matrix: a carbon nanotubes; b carboxylated carbon nanotubes; c pre-activation carbon nanotubes
4 Conclusion In the course of the present research, the following results were achieved: 1. By testing the short-term load of samples of destructed wood, it was found that the highest compressive and shearing strength along the fibers was achieved by samples modified with a polymer composition based on Anacrol 90W2 with the introduction of carboxylated nanotubes into the composition (25–30% increase in strength relative to sample without modification). 2. Samples of a polymer composition with fillers from different types of carbon nanotubes (CNTs, carboxylated CNTs and pre-activation CNTs) have been created. 3. The distribution pattern of the filler inside the matrix was established by microscopy. The filler introduced into the polymer in the form of carboxyl CNTs is distributed evenly, in contrast to pre-activation and conventional carbon nanotubes, which causes a greater increase in strength during wood stabilization. Acknowledgements The work was carried out within the framework of the grant of the President of the Russian Federation for state support of young Russian scientists—candidates of science (MK2972.2021.4). The study was carried out using the equipment of the interregional multispecialty and interdisciplinary center for the collective usage of promising and competitive technologies in the areas of development and application in industry/mechanical engineering of domestic achievements in the field of nanotechnology (Agreement No. 075-15-2021-692 of August 5, 2021).
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Application of Information Systems in the Technology of Servicing Energy Consumers Valerii Zubkov
and Nina Sirina
Abstract The existing system of accounting, monitoring and control of energy supply to housing and communal services enterprises does not meet the current conditions of coordination and management. Currently, each separate enterprise of housing and communal services solves the tasks of accounting, monitoring, controlling the consumption and remains of fuel resources, as well as the tasks of providing their enterprises with timely delivery of energy resources independently. The reason for this is the lack of information resources that allow to automate the main functions of these enterprises and the lack of a single information space between the subjects of the transport and support process. The organization of the transport and supply process of consumers and suppliers of energy resources is considered in this paper. It is concluded that it is necessary to improve the production process and transport services in the local railway transport in the segment of freight transport. An information resource in the form of a management system “Control of delivery, availability and remains of coal in warehouses of housing and communal services” is proposed. When creating the system, adaptive management methods and the principles of modular structuring were used. The results of using this system show that a positive effect has been achieved in ensuring high-quality planning of production volumes and high-quality performance of transport services. Keywords Energy consumers · Local traffic · Information system · Cargo transportation · Information space · Transport and logistics system
V. Zubkov (B) Moscow Representative Office of the Joint-Stock Company “Federal Cargo Company”, “JSC” “FGK”, 34 Masha Poryvaeva Street, Moscow 107078, Russia e-mail: [email protected] N. Sirina Ural State University of Railway Transport (USURT), 66, Kolmogorova Street, Yekaterinburg 620034, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_83
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1 Introduction To eliminate problematic issues in the organization of services for energy consumers and solving the problem of quality service for consumers-housing and communal services (HCS), the authors decided to develop an information resource in the form of a management system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”. This information system is an intersectoral management system. The use of the system allows to combine the necessary information flows that are formed as a result of the transport-providing process, both on the part of the carrier and on the part of consumers of transport services-housing and communal services enterprises. The purpose of creating an information and logistics resource is to improve the technology of servicing energy consumers in local traffic by methods of adaptation and self-support of intersectoral interaction based on an automated management system, taking into account the requirements for quality planning, accounting, control, monitoring of results and transport services [1]. The implementation and further use of the system is considered as an information and management resource that provides an increase in the efficiency and rationality of management, both by consumers and suppliers of energy resources, and by consumers and suppliers of transport services in local traffic. When automating the transport and supply process of energy consumers (housing and communal services enterprises), it is planned and implemented: – creation of a single information space between the carrier and the consumer of transport services-housing and communal services enterprises; – creation of a unified database of information data of enterprises, for visualization of transport and supporting technological operations in accordance with the regulations of the information and logistics project; – centralization of monitoring, accounting, control, coordination and management functions [2]; – obtaining high-quality operational reference and analytical information on the availability and condition of necessary cargo correspondence at all stages of cargo transportation in local traffic; – control of maintaining the standard values of energy reserves and its effective use; – automation of coordinated planning of cargo shipments to HCS enterprises; – automated formation of statistical reports [3]; – automated formation of coordinating decisions in the form of information messages [3].
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2 Materials and Methods Achieving the goal is possible by ensuring the formation of the following main subsystems at the stages of implementing the information program: 1. “Planning” stage: – collection, accounting, monitoring and processing of forecast, planned and actual values of the volumes of energy consumed by housing and communal services enterprises; – collection, accounting, monitoring and processing of forecast, planned and actual values of the volumes of transport services consumed by housing and communal services enterprises [4, 5]. 2. Stage “Logistics”: – preliminary information; – coordination of the values of the volume of transport services and methods of cargo transportation; – dispatching of transport and logistics services and creation of automated workplaces [5, 6]; – monitoring of the state of loading and unloading resources. 3. Stage “Production accounting”: – accounting, collection, monitoring of the availability and remains of energy resources in the warehouses of housing and communal services enterprises; – control of the use of energy resources; – control of the results of the transport and support process in local traffic [6]; – creation of corporate statistical reports. 4. Stage “Normative-legal”: – conditions of interaction of subjects of the transport-providing process and management bodies in the form of a set of norms, rules, standards [7]. When creating the system, the authors used accounting and monitoring methods to form options for servicing consumers of transport services and methods of coordinated adaptation, coordinated management and control, to build a versatile and multi-functional technological management system with self-control and selfsupport [8]. The system “Control of delivery, availability and remains of coal in warehouses of housing and communal services” performs its functions in the unified information space of the country, interacting with the information flows of the carrier and consumers of transport services-housing and communal services enterprises. The
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Database of the automated transportation management system
Minter client
http
Calculation result
Internet WebServer
Application Servers
Web-help http
Fig. 1 The process of passing and interaction of information flows in the system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”
basis for interaction is a unified database of information systems. Data exchange occurs at the request of the user or operator in accordance with the approved regulations of the information and logistics project [9]. Figure 1 shows the process of passing and interaction of information flows in the system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”. The system is built on a client–server model. General scheme: Database (IBM DB2 for z/OS) - Oracle database-application server-client (WEB). The system provides integration of electronic data from the information systems of the railway transport system. The interaction of the necessary systems is organized at the request of the user or operator, using the rules of exchange of the information and logistics project in a distributed SOAP environment, which creates conditions for the integrity of the information environment and the preservation of the safe operation of the system as a whole [10]. The data storage and software are installed on the server and do not require the creation of additional software resources on user automated workplaces [10]. The system allows to implement such basic activities as: – accounting, collection, transformation, coordination and storage of electronic data on the values of energy resources volumes predicted and planned for consumption [11]; – accounting, collection, transformation, coordination and storage of electronic data on the values of the volumes of transport services predicted and planned for consumption [11]; – comparative analysis of the planned and actual results of transport and support operations and the process as a whole [11, 12]; – monitoring, processing, and editing incoming, outgoing, and converted information streams; – coordination of options, methods and periods of the upcoming cargo transportation in local traffic; – preliminary calculation of the shortest distance of cargo transportation and its validity period [12];
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– formation of electronic application forms and transport and accompanying documents for the implementation of the upcoming cargo transportation in local traffic; – formation of corporate statistical reports on the availability, remains and needs for energy resources for the upcoming period, as well as on the cargo transportation and technological operations carried out with it at all its stages [13]; – preliminary information about cargo transportation at the request of the user or operator; – correction, elimination of possible errors by the operator, when making requests by the user for the organization of cargo transportation; – prompt provision of information to the system operator about an information request for possible cargo transportation [13]; – formation of options for coordinating solutions for the further implementation of the transport and support process in local traffic, in case of failures in its implementation. Figure 2 shows the main transport and logistics infrastructure of the system and its communications.
Information about the payment made for products and transport services Information about the agreed order for the provision of rolling stock, shipment and location of the cargo
Employees of the Ministry of Territorial Development-input of remains at district warehouses and enterprises, daily coal consumption and application for cargo transportation HCS enterprises, energy warehouses, - input of fuel remains, setting consumption standards
The system signals a critical situation with a color scheme if there is fuel left in the warehouse for a period less than the critical period
Dispatching - monitoring the availability of fuel at facilities and taking measures to replenish it
Fig. 2 The main transport and logistics infrastructure of the system and its communications
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3 Results Enterprises of housing and communal services use solid fuel–coal as an energy carrier. The geography of the location of energy suppliers and consumers is extensive and its further expansion is envisaged in connection with the ongoing development of the coal industry [14]. The location of consumers and suppliers is characterized by their distance from each other. The main carrier of coal products is rail transport. HCSenterprises are equipped with the main loading and unloading resources, and railway transport has an extensive network of transport and information infrastructure. Many municipal HCS enterprises are geographically located in low-activity areas. Railway transport has many limiting sections in terms of throughput and processing capacity, especially during the period of repair work on the railway infrastructure, which in turn makes it difficult to plan high-quality and timely delivery of energy resources to their destination. Figure 3 shows the organizational and functional scheme of the automated system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”. Visualization of the functioning of an automated control system is represented by the following main information layers: 1 Interface for monitoring the presence and remains of coal in HCS enterprises. In this layer, the system operators enter data on current coal reserves and their daily consumption. Then the system determines the period for which the HCS enterprise is provided with the current fuel supply using the values of the standard daily fuel consumption and its current reserve. If the period is less than the set value, the system informs the operator about it, in the form of an information message. This layer is necessary, in particular, because in general, the destination station for fuel delivery on the railway does not coincide with the municipality where
Employees of the Ministry of Territorial Development-input of remains at district warehouses and enterprises, daily coal consumption and application for cargo transportation Entering electronic data on energy reserves and remains by service area
Entering electronic data on energy reserves and remains for service companies
Entering electronic data “cargo notification-12 months” and “cargo notification-12 days” Entering electronic data on the loading and unloading of railway rolling stock, the location of railway rolling stock
Entering electronic data on the availability and supply of empty rolling stock to coal mines
Information from the Automated Transportation Management System (ATMS) for analysis by the involved employees of the energy carrier and the Ministry of Territorial Development
Fig. 3 Organizational and functional scheme of the system
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this cargo will eventually be delivered. This means that from the information systems of the carrier, this system can not get and select quickly information about the required amount of cargo volumes and the number of car shipments that are planned for municipalities-consumers of energy resources and transport services. This information layer is an adaptive and self-supporting resource of the system [15]. In the information layer, including the following regulatory and technical information is entered: the address of the location, the head responsible for the organization of production, the type of fuel boiler, the type of fuel (brand), the average power of the fuel boiler, the number of boilers, the current wear of the equipment, the date of commissioning of the boiler equipment, as well as information on heated objects: the number of residential buildings, industrial facilities, socially significant objects, the availability of a backup power source, and the number of people who may suffer in the event of an emergency shutdown of heating equipment [15]. 2 Interface for monitoring the organization of loading and transportation of loaded rolling stock. The main information layer, which uses, among other things, converted electronic data from the automated system of operational transportation management: – field “destination station”—railway station, where the car (group of cars) with cargo is directed. The destination stations are included in the regulatory and reference information and are selected from a single database; – field “recipient”—the consignee (company) for which the application for sending the rolling stock with the cargo is made. Selected from the report tables of the automated system of operational transportation management; – field “shipper”—the organization that issued the shipment of the cargo to the address of the recipient. Selected from the report tables of the automated system of operational transportation management; – field “cargo notification-12 month”—calculation data, the calculation is made by the developed system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”; – field “cargo notification-12 daily”—calculation data, the calculation is made by the system “Control of delivery, availability and remains of coal in warehouses of housing and communal services”; – field “Loading of coal at the mines”—calculated data, calculated by the proposed system based on data from the automated system of operational transportation management. The number of loaded cars and tons is determined, including the cumulative total; – field “Coal loading from the beginning of the month”—calculated data, calculated by the developed system, all loading from the beginning of the month is summed up, in case of non-compliance with the established standard, the system calculates options for the implementation of plans for the shipment of energy resources to the consignees, the best option is provided to the system operator in the form of an information message;
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– field “Dislocation of loaded cars”—dislocation of loaded cars at the end of the last reporting day, calculated data, calculated by the system “Control of delivery, availability and remains of coal in warehouses of housing and communal services” on the basis of information data of the automated system of operational transportation management. The provision of information on the car number in accordance with the protocol of the information and logistics project is available only for the system operators. 3 Interface for monitoring the organization of transportation of empty rolling stock and the time of its delivery to the loading facilities. This information layer contains information data on cars that at the end of the reporting period are in the composition of freight trains going to the address of energy suppliers, but have not yet arrived at the destination station. The data is grouped by delivery time, number of cars, and the consignee. The data is determined by the automated system of operational transportation management developed on the basis of the data of the reference and analytical report.
4 Conclusion The developed and put into operation system “Control of delivery, availability and remains of coal in warehouses of housing and communal services” improves the organization of production at HCS enterprises, the technology of transport services for consumers and energy suppliers in local traffic and provides: – automation of the process of coordinated forecasting, planning of energy consumption and transport services; – automation of the processes of accounting, collection, transformation, coordination and storage of electronic data of the transport and support process of housing and communal services enterprises; – automation (without the participation of the system operator) of the formation and provision of an information notice about the critical value of the energy reserve at the HCS enterprise; – automation (without the participation of the system operator) of calculations of options and determination of the optimal option for the implementation of the planned values of the volumes of energy resources shipment, as well as methods of its delivery; – automation (without the participation of the system operator) of the shortest distance and possible delivery time of energy resources to its consumers. Thus, the use of this system has made it possible to increase the purity of the planning of energy shipments in local traffic, to reduce the share of rolling stock downtime under cargo operations in local traffic and to increase the share of timely
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delivered goods in local traffic, and in some directions to reduce the delivery time of energy carriers at the destination station. The system has several distinctive features, such as: the ability to transform and consolidate information flows of various multifunctional automated systems into one, the calculation of options and the choice of the optimal method of cargo transportation based on electronic data of functioning information systems in a single transport and production process, the adaptation and self-support of the system in a single information space, the modular principle of system structuring. These distinctive features create conditions for its future development and expansion of functionality.
References 1. Chen Y (2016) Industrial information integrationa literature–a review 2006–2015. J Industr inf Integr 2:30–64. https://doi.org/10.1016/j.jii.2016.04.004 2. Cooke P (2011) Transition regions: regional–national eco-innovation systems and strategies. Prog Plann 76(3):105–146. https://doi.org/10.1016/j.progress.2011.08.002 3. Kavanagh P (2016) A case for negotiated performance-based contracting rather than competitive tendering in government public transport (bus) service procurement. Res Transp Econ 59:313–322. https://doi.org/10.1016/j.retrec.2016.06.006 4. Pimentel C, Alvelos F (2018) Integrated urban freight logistics combining passenger and freight flows–mathematical model proposal. Transp Res Procedia 30:80–89. https://doi.org/10.1016/ j.trpro.2018.09.010 5. Helo PT, Xu QL, Kyllonen SJ, Jiao RJ (2010) Integrated vehicle configuration systemconnecting the domains of mass customization. Comput Ind 61(1):44–52. https://doi.org/10. 1016/j.compind.2009.07.006 6. Walter J, Abendroth B (2020) On the role of informational privacy in connected vehicles: a privacy-aware acceptance modelling approach for connected vehicular services. Telemat Inform 49:101361. https://doi.org/10.1016/j.tele.2020.101361 7. Saccani N, Perona M (2007) Shaping buyer–supplier relationships in manufacturing contexts: design and test of a contingency model. J Purchas Supply Manag 13:26–41. https://doi.org/10. 1016/j.pursup.2007.03.003 8. Matteis T, Liedtke G, Wisetjindawat W (2016) A framework for incorporating market interactions in an agent based model for freight transport. Transp Res Procedia 12:925–937. https:// doi.org/10.1016/j.trpro.2016.02.044 9. Popova O, Gorev A, Shavyraa Ch (2018) Principles of modern route systems planning for urban passenger transport. Transp Res Procedia 36:603–609. https://doi.org/10.1016/j.trpro. 2018.12.146 10. Blyde J, Molina D (2015) Logistic infrastructure and the international location of fragmented production. J Int Econ 95(2):319–332. https://doi.org/10.1016/j.jinteco.2014.11.010 11. Wang H, Yang H (2019) Methodological ridesourcing systems: a framework and review. Transp Res Part B 129:122–155. https://doi.org/10.1016/j.trb.2019.07.009 12. Treber S, Breig R, Kentner M, Hafner B, Lanza G (2019) Information exchange in global production networks: increasing transparency by simulation, statistical experiments and selection of digitalization activities. Procedia CIRP 84:225–230. https://doi.org/10.1016/j.procir. 2019.04.214 13. Leviakangas P (2016) Digitalisation of Finland’s transport sector. Technol Soc 47:1–15. https:// doi.org/10.1016/j.techsoc.2016.07.001
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14. Goffin K, Lemke F, Szwejczewski M (2006) An exploratory study of «close» supplier– manufacturer relationships. J Oper Manag 24(2):189–209. https://doi.org/10.1016/j.jom.2005. 05.003 15. Zhenhua C, Kingsley H (2015) Multilevel assessment of public transportation infrastructure: a spatial econometric computable general equilibrium approach. Ann Reg Sci 54(3):663–685. https://doi.org/10.1007/s00168-015-0671-3
Criteria for Measuring the Economic Efficiency of Projects Based on Reusable Information Models Vladislava Aliulova , Marina Petrochenko , Maria Vrublevskaya , and Anna Gorodishenina
Abstract Improving the quality of reusable information models for capital construction objects with diverse functions is an important issue related to preparing a standard Basis of Design documents. The quality of design documentation depends on the quality of these models, which in turn is a key factor affecting the quality of the construction object. The goal of the study consisted in determining the economic efficiency of standard projects based on the key models of reusable information. To measure the economic efficiency of project documentation, we have formulated a comprehensive indicator for assessing the quality of the developed documentation based on the suggested criteria and their weight coefficients. The criteria for assessing the economic efficiency of project documentation are suggested taking into account three groups of quality indicators. Our findings confirmed that it is important to modify and formalize the requirements for assessing the economic efficiency of project documentation. It is proved that introducing qualitative and quantitative criteria for the economic efficiency of design documentation will ensure that projects with the most advantageous indicators of design solutions are selected for the library of basic information models for reusable capital construction objects of various functional purposes. Keywords Design documentation for reuse · Cost-effective design documentation · Standard design · Standard project documentation registry · Quality of design solutions
1 Introduction As the Construction Industry Development Strategy until 2030 introduces the concept of standard design and a transition to Building Information Modeling (BIM) is planned, a database of reusable information models has to be established for capital V. Aliulova · M. Petrochenko · M. Vrublevskaya · A. Gorodishenina (B) Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St. Petersburg, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_84
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construction projects of various functional purposes. The quality of design documentation depends on the quality of these models, which in turn has a key impact on the quality of the construction object. A system for assessing the quality of design has to be introduced to preserve a high quality of design given a large number of projects and to increase the economic efficiency of this process. While the output quality of the investment and construction sector depends on the quality at each stage, it is the project activity that is the first stage in this chain, therefore the quality of project documentation is the key contributor to the quality of the final product that is the construction object [1–3]. By and large, information on cost-effective design documentation for reuse is for reference only. Projects taken from the Registry may be similar projects with a good return on investments or requiring substantial adaptation to the conditions of the region where a specific capital construction object is planned, as well as the tasks set out in the project statement [4, 6–10]. Practice shows that not all concerns raised by the experts are addressed in the design documentation submitted for re-examination, which clearly confirms the insufficient qualifications of the designers and the lack of proper control from the general design organization and the technical customer [7, 9]. A system for assessing the quality of design should be introduced not only for ensuring the quality parameters of the building but also the quality of design in terms of errors and defects that require adjusting the design specifications both at the examination stage and at the construction stage [2, 5, 11–13]. Put simply, economically effective projects are assumed to provide the most advantageous technical solutions in terms of energy efficiency, in terms of functional, technical, and economic indicators, allowing rational use of capital investments, and widespread use of progressive construction methods [11, 12].
2 Materials and Methods An analysis of Russian and foreign experience in developing standards and the current pricing system was carried out in 2019 for determining the cost of design and survey. The results confirmed the need to optimize the cost of capital construction objects similar in their functional purpose by creating a library of basic information models for reusable capital construction objects of various functional purposes. However, the main problem arising even before such documentation is filed is that there is no mechanism for recognizing documentation as cost-effective for reuse and assessing its quality [2, 6, 8]. It is necessary to develop a multi-criterial model for selecting the projects comprising the library of basic information models for reusable capital construction objects of various functional purposes and for recognizing project documentation as cost-effective for reuse by assessing its quality. It is proposed to assess the quality of development of cost-effective design documentation for reuse by the method of expert assessments [2, 3].
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There are various methods of expert assessment: the ranking method, the method of paired comparisons, the method of successive comparisons, the method of assigning points to each factor on a certain scale. If there is a large number of parameters to process, the scoring method is the most optimal. Each expert assesses the importance of a certain criterion and gives it a score by the approved scale. The same score can be assigned to multiple parameters. This method was chosen to assign weights to the criteria within each group of quality indicators.
3 Results and Discussion We have considered the design documentation for construction of a school as an example, identifying 3 groups of quality indicators to assess the economic efficiency of the project: economic indicators, performance indicators, social indicators. These groups are arranged by ranking and have different weights that determine the degree to which the quality indicators affect the overall quality of the documentation. Several criteria are evaluated by experts within each group. These criteria also have different weights determined by the method of expert assessments. The quality indicator of the developed project documentation is calculated using the formula 1: Q=
p
Ai · K i , i = 1, 2, . . . , p
(1)
i=1
where Ai is the expert assessment in points based on a set of quality indicators i (0 ≤ A ≤ 5); p is the number of groups including quality criteria; K i is the weighting factor that determines the degree of influence of the quality indicator on the overall quality of documentation; the value is determined by the ranking method. An expert assessment of each group of indicators is determined by the following formula: Ai =
m
ain · kin , n = 1, 2, . . . , m
(2)
n=1
where ain is the expert assessment in points in a group of indicators i by criterion n (0 ≤ A ≤ 5); m is the number of quality criteria in a group of indicators i; k in is the weighting factor, which determines the degree of influence of the quality criterion; n on the expert assessment of a group of indicators i, the value is determined by the method of assigning points. The coefficients K i determined by the ranking method take the following values: 1. Economic indicators: K 1 = 0.5; 2. Performance indicators: K 1 = 0.3; 3. Social indicators: K 1 = 0.2.
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A questionnaire was drawn up to determine the weighting factors k in of the criteria in each group of indicators. During the survey, each criterion was assessed depending on the impact that this criterion has on the quality of the project. An average score was determined for each criterion, which was subsequently converted into a weighting factor. These weighting factors are subsequently multiplied by expert assessments in another questionnaire determining whether the project documentation can be included in the Standard Project Documentation Registry. The following criteria are considered within each group of quality indicators: economic indicators (construction cost, design cost, operating cost, duration of construction, labor costs during construction, material consumption of construction), performance indicators (estimated service life of the building, area per student, energy efficiency of the building, building layout that allows to quickly and safely leave it, materials used in the project), social indicators (creation of new training places, creation of new jobs, creation of an “accessible environment” for all categories of citizens, improvement of the adjacent territory, ergonomics of the building). Notably, the criteria within the group of social indicators will differ for another type of capital construction object. To determine the weighting coefficient of each criterion, we compiled a table of expert assessments (Table 1). The weighting factor is determined by the following formula: cr s fr s = t
s=1 cr s
, r = 1, 2, . . . , v, s = 1, 2, . . . , tr
(3)
where f rs is the weight of the criterion s determined by the expert r; crt is the score given to the criterion s by the expert r; t is the number of criteria in the group of t quality indicators; cr s is the sum of scores for a row r. s=1
Table 1 Table of expert assessments Experts
1
Criterion evaluation
Sum
1
2
…
s
…
t
c11
c12
…
c1s
…
c1t
t
c1s
s=1
2
c21
c22
…
c2s
…
c2t
t
c2s
s=1
…
…
…
…
…
…
…
r
cr 1
cr 2
…
cr s
…
cr t
… t s=1
cr s
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The final weighting coefficients of the criteria within each group are determined by the formula v =1 f r s ks = t r v s=1
r =1
(4)
fr s
where ws is the weighting factor of the score s. The sum of the weighting factors must be equal to unity. t
ks = 1
s=1
Based on the results of the survey, tables were compiled (Table 2) for each group of quality indicators, indicating the weights of the criteria based on the results of assessments of all experts. The sums of the criteria within one group were determined and their weight coefficients were calculated in each table. The evaluated quality criteria with the weights obtained during the survey are given in Table 3. To assess the given project, experts will be given a questionnaire with the following questions Table. 4). Table 2 Weighting factors determined by the scoring method Expert
1
Criterion
Sum
1
2
…
s
…
t
f 11
f 12
…
f 1s
…
f 1t
t
f 1s
s=1
2
f 21
f 22
…
f 2s
…
t
f 2t
f 2s
s=1
…
…
…
…
…
…
…
r
fr 1
fr 2
…
fr s
…
fr t
… t
fr s
s=1
…
…
…
…
…
…
…
v
f v1
f v2
…
f vs
…
f vt
Sum of criteria Weight coefficient
v r =1
k1
fr 1
v r =1
k2
fr 2
… …
v r =1
ks
fr s
… …
v r =1
kt
… t s=1
fr t
f vs
t v s=1 r =1 t s=1
fr s
ks = 1
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Table 3 Criteria for the quality of project documentation Quality criterion
Expert assessment
Weight coefficient
Expert assessment of a group of indicators
Construction cost
a11
k 11 =0.19
A1 =
Design cost
a12
k 12 =0.15
Operating cost
a13
k 13 =0.15
Duration of construction
a14
k 14 =0.19
Labor costs during construction
a15
k 15 =0.16
Material consumption of construction
a16
k 16 =0.16
Estimated service life of building
a21
k 21 =0.21
Area per student
a22
k 22 =0.13
Energy efficiency of building
a23
k 23 =0.17
Building layout that allows to quickly and safely leave it
a24
k 24 =0.24
Materials used in the project
a25
k 25 =0.25
Creation of new training places (number of students)
a31
k 31 =0.26
Creation of new jobs (number of employees)
a32
k 32 =0.17
Creation of an “accessible a33 environment” for all categories of citizens
k 33 =0.19
Improvement of adjacent territory
a34
k 34 =0.20
Ergonomics of space (degree to which classrooms can be transformed, colors, illumination, noise level)
a35
k 35 =0.18
Economic indicators
m
a1n · k1n
n=1
Performance indicators A2 =
m
a2n · k2n
n=1
Social indicators A3 =
m n=1
a3n · k3n
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Table 4 Expert questionnaire for assessing the quality of project documentation and the possibility of including it in the standard project documentation registry Indicator
Score on a five-point scale Experts 12…N
Economic indicators How profitable is the project in terms of construction costs? How profitable is the project in terms of the cost of design? How profitable the project is in terms of operating costs? How profitable is the project in terms of construction time? How profitable the project is in terms of labor costs during construction? How profitable is the project in terms of material consumption of construction? Performance indicators Evaluate the project in terms of the estimated life of the building Evaluate the project in terms of area per student Evaluate the project in terms of the building’s energy efficiency Evaluate the extent to which the building’s layout allows to quickly and safely leave it Evaluate the materials used in the project (quality, reliability, service life, environmental friendliness, modernity) Social indicators How much will the implementation of the project contribute to creating new training places? How much will the implementation of the project contribute to creating new jobs? To what extent does this project allow to create an “accessible environment” for all categories of citizens Evaluate whether the project has improved the adjacent territory Evaluate the project in terms of ergonomics (degree to which classrooms can be transformed, color schemes, illumination, noise level)
The estimates obtained from this questionnaire are multiplied by the weights given in Table 3. Thus, the expert estimate is calculated within the group of indicators, and then the quality indicator Q of the project documentation is determined using Eq. (1). The maximum possible value of this indicator is 5, the minimum is 1. Thus, the following decision options can be proposed depending on the calculated value of Q. If Q < 2.5, then the quality of the design documentation is insufficient for reuse. If 2.5 ≤ Q < 4, then it is possible to revise the design documentation and then re-evaluate its quality. If Q ≥ 4, then the design documentation is recognized as cost-effective reusable design documentation.
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Let us assume that the experts considered a certain project of the school and analyzed the design documentation for its construction. As a result of the analysis, scores were given to each criterion and an expert assessment of a group of indicators was calculated. The data are presented in Table 5. Table 5 Example of possible expert assessment of the quality of project documentation Quality criterion
Expert assessment
Weighting factor
Expert assessment for group of indicators
Construction cost
a11 = 4
k 11 =0.19
A1 = 4.05
Design cost
aType="Italic">12 = 3
k 12 =0.15
Operating cost
a13 = 3
k 13 =0.15
Duration of construction
a14 = 5
k 14 =0.19
Labor costs during construction
a15 = 5
k 15 =0.16
Material consumption of construction
a16 = 4
k 16 =0.16
Estimated service life of the building
a21 = 4
k 21 =0.21
Area per student
a22 = 2
k 22 =0.13
Energy efficiency of building
a23 = 3
k 23 =0.17
Building layout that allows to quickly and safely leave it
a24 = 5
k 24 =0.24
Materials used in the project
a25 = 5
k 25 =0.25
Creation of new training places (number of students)
a31 = 5
k 31 =0.26
Creation of new jobs (number of employees)
a32 = 5
k 32 =0.17
Creation of an “accessible environment” for all categories of citizens
a33 = 3
k 33 =0.19
Improvement of the adjacent territory
a34 = 3
k 34 =0.20
Ergonomics of space (degree to which classrooms can be transformed, colors, illumination, noise level)
a35 = 2
k 35 =0.18
Economic indicators
Performance indicators A2 = 4.06
Social indicators A3 = 4.13
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Thus, the final quality indicator is: Q = 4.05 0.5 + 4.06 0.3 + 4.13 0.2 = 4.069 Since Q ≥ 4, this documentation can be recognized as cost-effective for reuse.
4 Conclusions The economic efficiency of project documentation is directly related to its quality. This suggests that by assessing the quality of the project, it is possible to determine the economic efficiency of the documentation and conclude whether this project should be added to the library of basic information models for reusable capital construction objects of various functional purposes. 1. Analyzing the existing procedures by which design documentation is estimated to be cost-effective for reuse, we have concluded that they remain highly subjective. To reduce the role of the human factor in this process, qualitative and quantitative indicators of economic efficiency should be introduced for comprehensive assessment of the documentation. 2. The quality indicator Q defined in the study allows to objectively assess the economic efficiency of project documentation. Depending on its value, the project is either rejected (Q < 2.5), sent for revision (2.5 ≤ Q < 4), or recognized as a reuse project (Q ≥ 4). 3. A fundamentally new approach to the concept of standardized design as an entity will to establish and implement the mechanisms for creating information models, using information modeling technologies, innovative methods, and products of computer-aided design, and quality control of released projects. Applying the above criteria for assessing the quality of design allows to formalize the requirements for their quality in terms of the degree of project maturity, elimination of defects and inconsistencies, improving the safety of the construction object, implementation of the project on schedule and within the calculated cost of construction.
References 1. Sinenko S, Poznakhirko T (2018) Summarising progressive approaches to choosing organisational and technological solutions for the construction of buildings. MATEC Web Conf 193:05011. https://doi.org/10.1051/matecconf/201819305011 2. Jankowski B, Prokocki J, Krzemi´nski M (2015) Functional assessment of BIM methodology based on implementation in design and construction company. Proc Eng 111:351–355. https:// doi.org/10.1016/j.proeng.2015.07.100
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3. Sinenko S, Poznakhirko T, Obodnikov V (2019) Automation of visualization process for organizational and technological design solutions. MATEC Web Conf 270:05008. https://doi.org/ 10.1051/matecconf/201927005008 4. Zueva D, Babushkin E, Chulkov V (2018) Development of organizational and technological solutions for the implementation of projects of production programs of construction companies. MATEC Web Conf 251:05035. https://doi.org/10.1051/matecconf/201825105035 5. Bocharov A, Mamaeva O, Serdyuk M (2016) Features and problems of model project documentation. Urban Constr Archit 6(4):5–12 https://doi.org/10.17673/Vestnik.2016.04.1 6. Korkin A, Pavlov V, Motus S, Rymshin A, Orekhov A, Povalkovich N et al (2018) Automated use of standard design documentation in rosneft oil company. Neftyanoe khozyaystvo - Oil Industry 8:100–101. https://doi.org/10.24887/0028-2448-2018-8-100-101 7. Bartosz J (2015) Functional assessment of BIM methodology based on implementation in design and construction company. Proc Eng 111:351–355. https://doi.org/10.1016/j.proeng. 2015.07.10 8. Prušková K (2018) Reducing failures rate within the project documentation using building information modelling, especially level of development. MATEC Web Conf 146:01009. https:// doi.org/10.1051/matecconf/201814601009 9. Maleeva T, Selyutina L, Frolova N (2019) Use of modern technology of information modeling in capital construction object life cycle management. IOP Conf Ser: Mater Sci Eng 687(4):044002. https://doi.org/10.1088/1757-899X/687/4/044002 10. Kozlovska M, Mackova D, Spisakova M (2016) Survey of construction management documentation usage in planning and construction of building project. Proc Eng 161:711–715. https:// doi.org/10.1016/j.proeng.2016.08.747 11. Oleinik P, Yurgaytis A (2018) Planning of design works and formation of the initial permissive documentation for projects of general education institutions. MATEC Web Conf 251:05023. https://doi.org/10.1051/matecconf/201825105023 12. Tuhacek M, Svoboda P (2019) Quality of project documentation. IOP Conf Ser Mater Sci Eng 471(5):052012. https://doi.org/10.1088/1757-899X/471/5/052012 13. Moreno C, Olbina S (2019) BIM use by architecture, engineering, and construction (AEC) industry in educational facility projects. Adv Civil Eng 2019:1–19. https://doi.org/10.1155/ 2019/1392684
Research and Selection of Rational Parameters of a Refrigerated Container Terminal Daurenbek Ilesaliev , Jamshid Kobulov , Rashida Tursunkhodjaeva , and Mukaddas Tashmatova
Abstract The purpose is to study the refrigerator container terminal as a technical structure, to determine the relationship and mutual influence of parameters. The characteristic of a refrigerated container terminal in continuous refrigeration supply chains is given. The refrigerator terminal is investigated on the basis of a system analysis. The variety of technical and technological solutions is analyzed on the basis of structural-parametric and functional research. A classification of the parameters of a refrigerated container terminal has been developed. Keywords Railway transport · Road transport · Refrigerated container terminal · Refrigerated container · Container terminal operation · Container placement · Container storage
1 Introduction There is a misconception that warehouses and cargo terminals play a passive role in supply chains. In this article, we will try to show the role and place of refrigerating warehouse complexes, as well as to determine the relationship and mutual influence of the main parameters of refrigerated container terminals in continuous refrigeration supply chains. Today, cold storage warehouses and cargo terminals are important points of the transport system, providing a clear rhythm and organization of transport work. The key role is to ensure the required temperature mode during the storage and processing of perishable goods in a continuous refrigeration supply chain. The role of transport and cold storage facilities in a continuous cold supply chain must be considered collectively, since the transportation process begins and ends in warehouses, and at the same time forms a single network (Fig. 1). An important element of the continuous refrigeration supply chain is loading and unloading machines serving refrigerated container terminals. In modern refrigerated D. Ilesaliev (B) · J. Kobulov · R. Tursunkhodjaeva · M. Tashmatova Tashkent State Transport University, 1, Temiryulchilar Street, Tashkent 100167, Republic of Uzbekistan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_85
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S S
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Т S
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Т
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- regional level terminals - local level cold storage facilities - trunk transportation - local transportation Fig. 1 Block diagram of a continuous cold storage network
container terminals, the problem of multiple variants of technical and technological solutions is characteristic, which makes it difficult to choose a rational value of parameters. This study presents two types of loading and unloading machines that belong to the main technological equipment for processing large-capacity containers at the main storage site (Fig. 2 and 3). Gantry container cranes are the most common type of equipment in the CIS. Narrow aisles when stacking containers ensure tight stacking, as well as a long service life makes the gantry container crane popular among loading and unloading machines (Fig. 2).
1 3 b0
H1
H
2
bг
lc2
lk2
bт bт
bконт
λ,мм
Lпр
bт 4000 мм lk1
B1 lc1
Lкр
Fig. 2 A refrigerated container terminal serviced by a gantry crane
B2
Research and Selection of Rational Parameters … G
F
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H
1 2 3 Hп
bконт
Lпр
λ,мм
D
C E
Lкр
Fig. 3 A refrigerated container terminal serviced by a gantry pneumatic-wheeled crane
In Fig. 2: 1—the eclectic gantry crane; 2—refrigerated container; 3—racking for service stacks of refrigerated containers; L cr —length crane, m; L sp —span length, m; the number of lc1 , l c2 —length console, m; l k1 , l k2 —operating the flight console, m; bt —size chassis truck crane, m; B1 —the distance between the end beams, m; B2 the width of the crane, m. Abroad prefer pneumatic-wheeled gantry cranes (Fig. 3). The advantage of pneumatic valves is the lack of runways, and the ability to stack up to 5 containers high. In Fig. 3: 1—a gantry eclectic pneumatic-wheeled crane; 2—a refrigerated container; 3—racks for servicing a stack of refrigerated containers; H l —lifting height, m; L sp —span length, m; L cr —crane length, m; C—the distance between the end beams, m; D—the distance between the wheels, m; E—crane width, m. Rational selection and justification of equipment options for loading and unloading machines is an important task when calculating the main parameters of the storage area of a refrigerated container terminal.
2 Literature Review Determining the optimal values of the main and calculated parameters of a refrigerated container terminal is of great importance. A systematic study of a refrigerated container terminal in continuous refrigeration supply chains has been devoted to many studies by both foreign and domestic scientists [1], and [2]. The authors of the article [3] discussed various technologies used in cargo terminals for processing refrigerated containers. The optimal arrangement of containers on the storage area of the terminal is also proposed. The source [4] shows the role of container terminals in continuous refrigeration supply chains. In the study [5], the issues of placing racks
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serving refrigerated containers depending on the energy distribution are considered. The publication [6] is devoted to the development of a simulation model of energy consumption aimed at saving energy by distributing power between racks serving refrigerated containers. The article [7] considers the types of loading and unloading machines serving refrigerated terminals, as well as the influence of their parameters on the placement of refrigerated containers on the site. Thus, a brief scientific analysis of the methods shows that they can be used to determine the main values of the parameters of refrigerated cargo terminals, as well as the influence of the parameters of loading and unloading machines on the functioning of cargo terminals. However, some calculation methods are incomplete and require clarification. In addition, the studies do not take into account random factors that characterize the operation of a refrigerated container terminal.
3 Method. Structural and Parametric Description of a Refrigerated Container Terminal The structural description considers the refrigerator terminal in the dynamics of its functioning, taking into account the interaction of all technological sections (automobile loading and unloading section, railway loading and unloading section, as well as the storage section). The structure of the refrigerator terminal shows the connections between the technological sections (Fig. 4). The task of each technological section is to perform its functions with minimal costs. The task of each section is subordinated in turn to a common goal—the transformation of container flows to the requirements of the next element of the continuous refrigeration supply chain.
Automobile loading and unloading area 3 1
2 4
Railway loading and unloading area Fig. 4 Structure of a refrigerated container terminal: 1,2—direct transshipment from one transport to another; 3,4—transshipment through the main storage area of refrigerated containers
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e21 a1
e13
e12 e31 e23
a2
e32
a3 Fig. 5 Functioning of a refrigerated container terminal
Rational determination of the main parameters of individual elements of a refrigerated container terminal, such as a section of the main container storage, bypassing the selection and calculation of controlled parameters, is not possible. Therefore, the results in this study concerned both the main parameters of the terminal and the parameters of individual sections of the terminal. The vertices of the state graph ai of the container terminal in Fig. 5, the following states of the sections were marked: a1 —railway loading and unloading section; a2 —automobile loading and unloading area; a1 —storage area for refrigerated containers; As a result of the study, the following processes of transitions from one state to another were selected: e12 —direct reloading of refrigerated containers from railway transport to road transport; e21 —direct reloading of refrigerated containers from road transport to railway transport; e13 —unloading of containers from railway transport and moving it to the storage area; e31 —moving containers from the storage area and loading on railway transport; e32 —unloading containers from road transport and moving it to the storage area; e23 —moving containers from the storage area and loading them onto road transport. The adjacency matrix describing the state graph of the terminal has the following form: ⎤ ⎡ ⎡ ⎤ 011 e11 e12 e13 A = ⎣ e21 e22 e23 ⎦ = ⎣ 1 0 1 ⎦, (1) e31 e32 e33 110
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P21 P12
S1
S2
P23 P31
P13
P32
S3 Fig. 6 Functioning of a refrigerated container terminal at a discrete time
For a mathematical description of the functioning of a refrigerated container terminal (see Fig. 6) the mathematical apparatus of Markov random processes can be applied. If the state transitions of a refrigerated container terminal to a state are possible at a pre-fixed time: t 1 , t 2 , … t n , and in the time intervals between these moments, terminal S retains its state, then such a random process is called a Markov process with discrete time. Figure 6 shows a graph of states of a refrigerated container terminal for a Markov chain of discrete time. The process that occurs at refrigerator terminals can behave as follows: S 1 → S 2 , → S 4 → S 1 . The probability of terminal states Pi (k) after the k-step of transitions is determined as follows: n P j (k − 1)P ji (i = 1, ....n), (2) Pi (k) = j=1
where Pj(k-1) —is the probability of the terminal being in the Si state at the previous discrete time (k-1). The probabilities of system transitions can be written as a matrix of probability transitions: ⎤ ⎡ P11 P12 P13 (3) Pi j = ⎣ P21 P22 P23 ⎦ P31 P32 P33 The discrete-time Markov chain equations for a refrigerated container terminal have the following form: ⎧ ⎨ P1 (k) = P1 (k − 1)P11 + P2 (k − 1)P21 + P3 (k − 1)P31 ; P (k) = P1 (k − 1)P12 + P2 (k − 1)P22 + P3 (k − 1)P32 ; ⎩ 2 P3 (k) = P1 (k − 1)P13 + P2 (k − 1)P23 + P3 (k − 1)P33 .
(4)
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λ21 λ12
S1
λ13
λ31
S2
λ23 λ32
S3 Fig. 7 Functioning of a refrigerated container terminal at a continuous time
Equations (4) describes the process of transition of intraterminal work, the transition from one state to another. However, at terminals, transitions from state to state occur at random times, this is due to the uneven arrival and departure of external transport, in such cases, the Markov random process scheme with continuous time is used. Instead of the transition probabilities Pij , the transition probability density λij is introduced. The probability density of the transition λij is the limit of the ratio of the probability of transition in time t from the state Si to the state Sj to the length of the interval t: λi j = lim
t→0
Pi j (t) , t
(5)
where Pij (t)—the probability that the terminal system, which was in the Si state at time t, will switch from it to the Sj state during time t. Figure 7 shows a graph of the states of a refrigerated container terminal. Knowing the marked-up graph of states, it is possible to determine the probabilities of the states of the system as a function of time P1 (t), P2 (t),… Pn (t). The probabilities are satisfied by a differential equation of a certain type, called the Kolmogorov equation: ⎧ d P1 (t) ⎪ ⎪ = −λ12 P1 (t) − λ13 P1 (t) + λ21 P2 (t) + λ31 P3 (t) = −P1 (t) · (λ12 + λ13 ) + λ21 P2 (t) + λ31 P3 (t); ⎪ ⎪ dt ⎪ ⎪ ⎨ d P2 (t) = −λ21 P2 (t) − λ23 P2 (t) + λ12 P1 (t) + λ32 P3 (t) = −P2 (t) · (λ21 + λ23 ) + λ12 P1 (t) + λ32 P3 (t); ⎪ dt ⎪ ⎪ ⎪ ⎪ ⎪ ⎩ d P3 (t) = −λ31 P3 (t) − λ32 P3 (t) + λ13 P1 (t) + λ23 P2 (t) = −P3 (t) · (λ31 + λ32 ) + λ13 P1 (t) + λ23 P2 (t). dt
(6)
When composing this system of differential equations, it can be written as follows: n n d Pi (t) =− λi j Pi (t) + λ ji Pi (t), j=0 j=0 dt
(7)
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The system of Eqs. (7) describes the dynamics of the probability of finding a refrigerated container terminal in one of the states. State models based on Markov chains for describing the operation of refrigerated container terminals allow us to assess the workload of three sections, both in the process of discrete and continuous time.
4 Determination of the Capacity of the Terminal Storage Area The capacity of the storage area depends primarily on the main initial parameters of the site, refrigerated containers, as well as on the type of loading and unloading machine serving the terminal (Fig. 8). The formalized model of the controlled parameter, which is the processing capacity of the terminal, looks like this: N = {x, y, z, η}, cont/year
(8)
where x—the number of refrigerated containers by the width of the terminal, cont.; y—the number of refrigerated containers by length, cont.; z—the number of refrigerated containers by height, cont.; η—the turnover of refrigerated containers per year, 1/year The capacity of the storage area is determined as follows: R = x · y · z, cont.
(9)
The number of refrigerated containers by the width of the terminal is determined by the following formula: - when servicing with a gantry electric crane: 1
2
3
4
...
y
1 2 3 ... x z
... 1
Впл
1 2 3 ... x
λ
μ
bст
σ
Lпл
Fig. 8 The storage area of the refrigerated container terminal
lконт
bконт
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L sp − 2 · (bt + b0 ) B yar d ·ε , cont. L cr + ω bcont + λ
(10)
- when servicing with a gantry pneumatic-wheeled crane: L sp − bauto − 2 · bt − b0 B yar d ·ε , cont. x =ε L cr + ω bcont + λ
(11)
where Byard —the width of the container yard, m; Lcr —length crane, m; Lsp— length of the span of the crane, m; bcont —width refrigerated container, m; bt —size chassis truck crane, m; b0 —technology security clearance between trolley of the crane and the protruding part of the extreme refrigerated container, m; bauto —the width of the passage, m; ω—distance between the cranes, m; λ—the minimum distance between the containers, m. The number of refrigerated containers by width length is calculated using the following formula: - when servicing with a gantry electric crane: L pl − n pas · l pas , cont. y=2·ε brack + 2 · (lKOHT + μ)
(12)
- when servicing with a gantry pneumatic-wheeled crane: y=2·ε
L pl − 2 · lend − n pas · l pas , cont. brack + 2 · (lcont + μ)
(13)
where Lpl —the length of the platform, m; brack —the width of the rack serving the refrigerated container, m; μ—the gap between the container and the structure of the rack, m; lcont —the length of the container, m; lend —the distance along the length to the exit from the storage area at the ends of the platform, m; lpas —the width of the cross passage, m; npas —the number of cross passages. n np
L pl , pr. 80
(14)
Number of refrigerated containers by height:
Hl − h z=ε h cont
− 1, cont.
(15)
where Hl —the working height of lifting the crane sprayer, m; h—the minimum distance from the roof of the upper container and the bottom of the container being moved, m; hcont —the height of the container, m; 1—the container being moved over the stack.
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5 Results Figure 9 shows the results of the applicability of the main storage area of the terminal when comparing two types of loading and unloading machines. It can be seen from the graphs in Fig. 6 that under the same conditions, the maximum capacity of the terminal is provided when using gantry pneumatic-wheeled cranes. Studies of the conditions for filling the storage area for different types of refrigerated containers were carried out, as a result of which the regularities of changes in the terminal efficiency coefficients were derived. Studies of these patterns have shown that the capacity of the storage area is primarily influenced by the values of the parameters of the length and width of the site, as well as the type of loading and unloading machines.
Capacity, cont
10000 8000 6000 4000 2000 0 350
450
550
650
750
850
950
Length of the yard, m when servicing by an electric gantry crane when servicing by pneumatic gantry crane
processing capacity, cont/year
Fig. 9 Dependence of the capacity of a refrigerated container terminal on the length of the platform
2500000 Lpl=350 м
2000000
Lpl=450 м 1500000
Lpl=550 м
1000000
Lpl=650 м
500000
Lpl=750 м Lpl=850 м
0 1
2
3
4
5 6 7 Shelf life,day
8
9
10
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Fig. 10 Processing capacity of the terminal, when serviced by a gantry electric crane
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6 Discussion Also, research was carried out on the conditions of filling the storage area for different types of refrigerated containers, as a result of which the regularities of changes in the efficiency of the terminal were derived. Studies of these patterns have shown that the capacity of the storage area is primarily influenced by the values of the parameters of the length and width of the site, as well as the type of loading and unloading machines. The relationship between the capacity and processing capacity of a refrigerated container terminal is visible from the formula: N pr oc = R · η = x · y · z · η, cont/year
(16)
The turnover of refrigerated containers depends on the storage period at the terminal: η=
365 , 1/day τ
(17)
The final mathematical formula is as follows: N pr oc = 365
x·y·z , cont/year τ
(18)
processing capacity, cont/year
The results of calculations of the processing capacity of a refrigerated container terminal when servicing various types of loading and unloading machines are shown in Figs. 7 and 8. From the graphs in Figs. 10 and 11, it can be seen that with a reduction in the shelf life of refrigerated containers at the terminal, the throughput decreases sharply in the range of storage periods of 2–3 days. 4000000 Lpl=350 м 3000000
Lpl=450 м Lpl=550 м
2000000
Lpl=650 м Lpl=750 м
1000000
Lpl=850 м 0 1
2
3
4
5 6 7 Shelf life,day
8
9
10
Lpl=950 м
Fig. 11 Processing capacity of the terminal, when serviced by a gantry pneumatic-wheeled crane
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7 Conclusion A modern refrigerated container terminal has a number of properties that allow us to consider it as a complex technical system with individual elements, relationships with elements and functioning to achieve a single goal—the transformation of container flows in a continuous refrigeration supply chain. The characteristic features of the structure of a refrigerated container terminal, consisting of separate sections, are: their clear orderliness, organization, integrity, thanks to which they form a single system. A formalized model of the controlled parameter of a refrigerated container terminal is proposed, and mathematical models of the relationship and interaction of various parameters of a refrigerated container terminal with each other are developed. It was found that reducing the shelf life and processing of refrigerated containers by 1 day provides an increase in the processing capacity of a refrigerated container terminal by about 20–25% in the ranges of 2–3 days.
References 1. Ilesaliev DI, Makhmatkulov SG, Abduvakhitov SR (2020) Peculiarities of container terminal functioning in delivery chains. IOP Conf Ser: Mater Sci Eng 918(1):012043. https://doi.org/10. 1088/1757-899X/918/1/012043 2. Ilesaliev DI, Abduvakhitov SR, Ismatullaev AF, Makhmatkulov SG (2019) Research of the main storage area of the container terminal. Int J Eng Adv Technol 9(1):4625–4630. https://doi.org/ 10.35940/ijeat.A2923.109119 3. Budiyanto MA, Shinoda T (2020) Energy efficiency on the reefer container storage yard; an analysis of thermal performance of installation roof shade. Ener Rep 6:686–692. https://doi.org/ 10.1016/j.egyr.2019.11.138 4. Castelein B, Geerlings H, van Duin R (2020) The reefer container market and academic research: a review study. J Clean Prod 256:120654. https://doi.org/10.1016/j.jclepro.2020.120654 5. Parise G, Parise L, Chavdarian B et al (2019) Systems design criteria for refrigerated containers parks. IEEE Trans Ind Appl 55:2320 2326. https://doi.org/10.1109/tia.2019.2891612 6. Van Duin JHR, Geerlings H, Verbraeck A, Nafde T (2018) Cooling down: A simulation approach to reduce energy peaks of reefers at terminals. J Clean Prod 193:72–86. https://doi.org/10.1016/ j.jclepro.2018.04.258 7. Wiese J, Suhl L, Kliewer N (2011) Planning container terminal layouts considering equipment types and storage block design. Handb Terminal Plann 49:219–245. https://doi.org/10.1007/ 978-1-4419-8408-1_12
The Phenomenon of “Bias of Assessment” as the Basis of a Behavioral Model and a Potential Source of Problems Oleg Tikhanychev
Abstract In statistics, a phenomenon called “bias of assessment” has been known for a long time. It is determined by the fact that with the spontaneous formation of the studied samples, for example, in social research, a kind of “bias” occurs, determined by the motivation of the respondents. This principle can also be manifested in the formation of public opinion on socially significant issues: during elections, referendums, etc. Moreover, knowledge of the principle of “bias” can be used to organize a deliberate “bias” of the results of socially significant surveys. Using general scientific methods of analysis and synthesis, the paper shows possible approaches to the formation of such “bias”, analyzes the possible consequences of the implementation of such technologies, and formulates proposals to counteract them. The conclusion is made that the purposeful use of technologies of “bias” assessment can lead to the emergence of conflicts of interests of different groups of society and government, but the situation so far could not be corrected due to the lack of appropriate countermeasures. The development of mechanisms for assessing the consequences of “bias” and countering it, in theory, can provide greater resilience to society and make it difficult to use external influences to destabilize the state in the event of deliberate use of the “bias”. Keywords Results processing · Statistical methods · Bias of assessment · Public opinion management · Social technology
1 Introduction In some areas of statistics, it is customary to use the concept of “bias of assessment”, which most often arises when processing data from surveys conducted with the participation of a person. The factor of “bias” is determined by the subjectivity of an individual’s assessments of any event; it is especially enhanced by the independent formation of the sample under study, when the involvement in the survey occurs O. Tikhanychev (B) Company Group «Technoserv», 13, Yunosti Street, 111395 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_86
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on a voluntary basis. In statistics, this factor is taken into account, its influence is compensated by correction factors, or it is simply neglected as insignificant, especially when forming estimates for events of the same type, for which the “bias” is approximately the same and does not affect the obtaining of comparative estimates. As the world practice of the use of destructive social technologies in the last few decades has shown, the phenomenon of “bias” is much more complicated and problematic in the field of social engineering. This danger is especially manifested for countries and societies based on democratic principles of governance [1–3]. Historically, the basis of any democracy is the free expression of the will of every capable member of society, based on voting in the process of choosing power and making the most significant decisions. For many centuries, this approach ensured the election of power through the reflection of the will of the majority, as, in fact, the word “democracy” is translated from the Greek. It is the possibility of a public statement of the population on the problems of public life and the influence of the stated position on the development of socio-political relations that reflect the essence of public opinion as a special social institution, which is a collection of many individual opinions on a specific issue affecting a group of people. To determine the results of the expression of will, fairly simple but reliable methods are used. In the Greek city-states, the number of people who voted was counted; at the Novgorod veche (town’s meeting), the winning opinion was determined by the loudness of its expression and sometimes by the results of a fist fight, etc. With the increase in the size of states and, accordingly, the coverage of the audience taken into account, statistical methods for processing the results began to be used, based, in general, on modifications of the same approaches. For the time being, these methods worked quite successfully and made it possible to obtain adequate estimates. But with the growth of the scale of society, they began to fail. There was even a theory about the impossibility of applying democratic principles in a society of more than five thousand people. Then came the era of the information revolution, characterized, from the point of view of social relations, by an increase in the communication and activity of the population. Social networks, informal public organizations do not just influence the government, they begin to compete with it, including acquiring some features of the state. An example is multinational information corporations such as Facebook or Twitter Inc. And suddenly it turned out that the state, which uses the old methods of taking into account public opinion to interact with its citizens, is not ready for the challenges of the present time. This conclusion is confirmed by the practice of recent decades, numerous “color” revolutions based on the right of squares and maidans. But why did it happen? The need to answer this question determines the relevance of the topic of the paper.
2 Materials and Methods A systematic approach was chosen as the methodological basis for the study. The use of a systematic approach, methods of decomposition and comparative analysis
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made it possible to consider in a complex the problems of the so-called “bias” of assessment in economics and social statistics. To assess the state of the subject area and form options to counter the “bias” of assessment, the paper used the methods of comparative analysis and generalization. The source base of the research was made up of scientific articles and reference books on the mathematical apparatus, which are in the public domain.
3 Results For the analysis, it is proposed to recall the main approaches to defining public opinion and the principles of taking it into account in the activities of the state and society. Within the framework of the currently used methods, it is believed that public opinion is a set of individual opinions, attitudes, and, possibly, beliefs of a certain group of people in relation to the population of a certain state or its territorial unit. In modern society, the usual channels (and forms) of expression of public opinion are: elections of government bodies, participation of different groups of the population in legislative and executive activities, activities of the press and other mass media, holding meetings, demonstrations, etc. Along with this, statements caused by political, research interest and taking the form of elections, referendums, mass discussions of any problems, meetings of specialists, selective polls of the population by given “focus groups”, etc. are also widespread. It has always been believed that a correctly selected and sufficiently representative sample of respondents, correctly formulated questions and adequate methods of processing them provide accurate estimates of the results of such events. However, the practice of the last few decades has shown that more and more statistical methods begin to fail. Why? The analysis shows that the problems are generated by the peculiarities of the communications of modern society, which exists in the conditions of total informatization. There are many reasons for these problems, both objective and subjective ones. Most of the reasons are generated not by the mathematical apparatus of statistical calculations, which has long been verified and tested, but by the methods of its use. One of such reasons, as the analysis of the practice of processing the data of conducting sociological surveys shows, is complex, lying on the border of the formation of the sample and the calculation of the final estimate. It is proposed to consider it in more detail. Differences in the work of existing methods in the information society can be explained by the example of assessing the activities of any arbitrarily chosen organization formed on the basis of an analysis of reviews about it on the Internet. Practice has shown that a user who is satisfied with the activities of an organization very rarely spends his time on leaving a positive review. According to statistics, the share of such users is from one third to half of the respondents. At the same time, a user dissatisfied with the service leaves his negative feedback in 80–90% of cases. The processing of such an estimate by classical statistical methods gives a significant negative bias. The assessment is “biased” and does not correspond to the real situation. A similar
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Fig. 1 Graphical interpretation of the bias of assessment
situation is developing in the field of obtaining social assessments using modern communication networks, opinion polls, etc. [4, 5]. In this regard, we can recall the concept of unbiased assessment used in mathematics. In mathematical statistics, this is a point estimate, the mathematical expectation of which is equal to the estimated parameter (Fig. 1). For example, let X1 ,…Xn , be a sample from a distribution depending on the parameter θ . Then the estimate θ ≡ θ (X 1 , . . . X n ) is called unbiased if:
E θ = θ, ∨ θ ,
where E[X]—mathematical expectation of X; ∨—universal quantifier. Otherwise, the estimate is called biased, and the random variable Eθ − θ called its bias [2, 4]. In mathematical statistics, bias occurs due to gross errors in the formation of a sample or an incorrect choice of the distribution law that describes it. In the social sphere, the mechanism is similar, although more susceptible to the influence of subjective factors. Especially considering that in the latter case, the estimated sample, most often, is not randomly selected, but is formed by itself, based on subjective factors. A vivid practical example of the implementation of the principle of “bias” of social assessments—modern elections. As in the case of the assessment of the activities of organizations, citizens who are satisfied with the authorities do not rush to the elections, they are already doing well, and there is no desire to change anything. But the dissatisfied, even if they are a minority, go to vote. Another influencing factor is the presence of a turnout threshold, which additionally helps to ensure a bias in the resulting assessments. And the usually used mechanism for distributing unrealized votes in proportion to the share result given for certain candidates, further exacerbates the situation, increasing the “bias”. And the lower the turnout threshold, the easier it is for the active part of the population to make a decision that does not
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take into account common interests, or implement the “bias” of assessment through the implementation of PR-technologies. At the same time, the “stepwise” electoral system adopted in some countries does not correct the situation—it only changes the nature of the bias from a general assessment to a particular one, by individual groups and territories. In terms of the influence of “bias” on the electoral process, the so-called “smart voting” methodology is of research interest. When it is implemented, the possibilities of achieving success in each region (district) are calculated, unpromising districts are cut off, and efforts are redistributed to the most promising ones in order to achieve local success in specific points. In terms of mathematics, this is not really a “bias” of assessment, but a decrease in variance, which increases the likelihood of obtaining the required value at a given point (Fig. 2). Although the principle here is the same as in the case of the “bias” of assessment—an artificial modification of the random distribution law to obtain the required result, the “bias” is simply not along the horizontal scale, but along the vertical. And the problem is not only and not so much in the used mathematical methods, but in the principles of forming the processed statistical sample. If during sociological research, the sample is formed randomly, then, for example, in elections, the aggregate of voters is formed under the influence of certain factors, sometimes even determined by external influences. Accordingly, the result of processing this sample is displaced relative to the real state of affairs. The bottom line is that the election results do not fully meet the expectations of society. Subsequently, this results in protests, distrust of the authorities and discrediting of the basic principles of democracy. f(x)
Bias
E[X]
x
Fig. 2 Graphic interpretation of the principle of “smart voting” from the point of view of artificial “bias” of assessments
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4 Discussion An analysis of the essence of the problem of forming an assessment sample allows understanding the content of the selection process itself, during which each of its participants balances between the expected utility of the result and the costs of achieving it. The cost of achieving a goal in this example is the need to spend time visiting a polling station. Usefulness—the expected results of the implementation of the expression of will. Each individual can be forced to vote either by a strong desire to change something, or by an equally strong fear of change. But people with conscious assessments in any society, as a rule, are a minority, and they are unevenly distributed across social groups and regions. In most cases, it is the imbalance of this mechanism that generates a “bias” in the results of the expression of will. One of the recent examples of bias of assessment may be the BREXIT vote on the exit of Great Britain from the European Union. With an approximate equality of supporters and opponents, mostly elderly people spoke in favor of leaving. Since their selective activity is usually higher, then the result turned out to be noticeably “biased” [6]. The young part of the population began to show activity only after receiving the election results, certain actions were taken, but this did not solve the problem. The given example is a variant of an accidental, unintentional “bias” of assessment. Much more interesting are cases of deliberate “bias” of assessments aimed at achieving a particular goal. A typical example of deliberate “bias” is the assessment of the correctness of the organization of planning in all areas of production. In any economic structure, certain elements of activity planning are used, the difference, as a rule, is only in the proportion of planned processes from their total number. And when planning, the question arises: how correctly the plans are drawn up? are they not overestimated or underestimated? To answer this question, a mechanism similar to the search mechanism for “bias” of assessments can be used. It is simple: assuming that the probability of plan fulfillment, as is most often the case, is distributed according to a normal law, one can estimate how correctly the planning is estimated. Namely: if the share of those who overfulfilled and did not fulfill the plan is distributed approximately equally, the plan is drawn up correctly. But, in practice, it happens that the implementation is declared as 100 percent. This is a typical forced “bias”, when the plan is deliberately underestimated to ensure the possibility of its implementation by almost all participants in the process, and the facts of overfulfillment are hidden for postponement to the next period. An equally obvious and, perhaps, more dangerous manifestation of a deliberate “bias” of assessment in the social sphere is the previously mentioned methodology of the so-called “smart voting”. The formation of discrete assessments and the influence on those of them that can be changed, theoretically, ensures the solution of particular problems of holding the maximum possible number of candidates for the necessary authorities. From the point of view of mathematics: the problem is solvable and quite
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trivial, from the point of view of social engineering—effective and dangerous, and, accordingly, requiring the development of methods for detecting and countering such “biases”.
5 Conclusions Based on the described mechanisms, in order to counteract the deliberate “bias” of assessments, especially used in the framework of destructive social technologies, a mathematical apparatus is needed to determine the magnitude and direction of the “bias” of assessment and to develop recommendations for countering the results of this phenomenon. Finding and compensating for “bias” can be carried out using different approaches:n 1. 2. 3. 4. 5. 6.
heuristic, based on the use of subjective data of experts: expert assessment of the structure and correctness of the sample under study; assessment of the final results based on formal logic; formation of comparative assessments using the theory of similarity; methods of mathematical statistics: assessment of the form and characteristics of the distribution law for the results of processing statistics, the differences between its parameters from the normal; 7. search for correlations for the parameters of distribution laws and mathematical expectations obtained in different regions (areas, under different conditions), search for their anomalous “bursts”. The expediency of using certain methods is determined by the purpose of the study, the accepted limitations and requirements for accuracy, the structure of the initial data, and the possibilities for carrying out calculations [7–9]. Mathematical models for analyzing the “bias” of assessment, built using the proposed mathematical apparatus, can have two obvious aspects of application: • in the field of economics—the assessment of the correctness of the set plans and their subsequent correction; • in the field of sociological research—assessment of voting results and refinement of assessments taking into account their bias, as well as assessment of the legitimacy and forecasting of the parameters of protest movements. Taking into account the active use of destructive social technologies in geopolitics in recent decades, the second option for using the proposed mathematical apparatus seems to be the most relevant. In general, the formulation of the problem of the applied use of search mechanisms for the “bias” of assessments and countering this phenomenon, formulated in the paper, can be important in various areas of management activity. The solution to
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this problem will provide a certain optimization of the control cycle by increasing the accuracy of assessing the situation and predicting the consequences of decisions made.
References 1. Dzhurich J, Stoyadinovich M (2015) Neoliberal theory and practice in modern society, sociological research 3:107–113. http://socis.isras.ru/en/article/5168?printmode 2. Walker J (2010) Protect & serve, american conservative 9(5):35–37. https://www.theamericanc onservative.com/articles/protect-serve/ 3. Tikhanychev O (2021) Development of the theory of hybrid confrontation. A historical retrospective, voennyi sbornik 9(1):4–14. https://doi.org/10.13187/vs.2021.1.4 4. Kochenderfer M, Wheeler T (2019) Algorithms for optimization. The MIT Press Cambridge, London 5. Leyffer S (2016) Optimization: applications, algorithms, and computation. Argonne, LLC, Chicago 6. Snesarev AE (2016) A british exit from the European union as a factor of geopolitical transformation of the united Europe. United Kingdom. http://csef.ru/en/articles/print/7180 7. Abramova M (2016) The dialectics of the international and the national and the russian education system. Philoso Educ 5(68):59–68. https://doi.org/10.15372/PHE20160506 8. Tikhanychev O (2021) On the question of clarifying the structure of “hybrid forces.” Nota bene 1:40–48. https://doi.org/10.7256/2454-0668.2021.1.33387 9. Bartosh A (2018) Transformation of modern conflicts. Secur Issues 1:1–18. https://doi.org/10. 25136/2409-7543.2018.1.22294
Effect of Phubbing on Students’ Performance Tatiana Baranova , Aleksandra Kobicheva , and Elena Tokareva
Abstract The active use of smartphones among young people has changed the patterns of online and offline interactions. Phubbing (that is, when you look at your phone instead of paying attention to others) is becoming an increasingly popular phenomenon nowadays. The aim of the current paper is to analyze the level of phubbing among students of university and the effect of phubbing on students’ academic outcomes. For our research we used the Generic Scale of Phubbing and the students’ semester grades in professional disciplines. We collected both quantitative and qualitative data for our analysis (online survey and interview were conducted). The results showed a quite high level of phubbing among students and confirmed the negative effect of phubbing on student’s performance. Thus, such a phenomenon as phubbing should be deeply studied and can be considered as a serious threat to higher education. Keywords Education outcomes · Phubbing · Social media · Internet addiction · Smartphone addiction
1 Introduction Smartphones have many benefits, providing easy access to communication and allowing people to connect with friends and family throughout the day, anywhere [1, 2]. However, several researchers [3, 4] have become increasingly concerned about the adverse effects of smartphones on users’ mental and physical health and the quality of their social interactions with others. Moreover, overuse of smartphones when accompanied by other people has been found to have negative social consequences for users. So much so that ignoring other people in favor of using their smartphone is so important that this behavior has led to a new concept known as phubbing. Bipeta et al. [3, p. 2] defines phubbing as “the act of dismissiveness towards someone in a social environment when they look at their phone instead of paying attention to that T. Baranova · A. Kobicheva (B) · E. Tokareva Peter the Great Saint-Petersburg Polytechnic University, St. Petersburg 195251, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_87
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person.“ This behavior has negative consequences for interpersonal communication to the detriment of relationship satisfaction and a sense of personal well-being [4, 5]. Based on the best knowledge, phubbing is explored in several studies, as it is a relatively recent phenomenon, little is known about the reasons for this behavior and “how it became an acceptable or normative feature of modern communication” [6]. Research by Savci and Aysan [7] found that the group most susceptible to smartphone or internet addiction are young people and adolescents. The proliferation of smartphones and the subsequent use of social media in education has attracted the attention of scientists to study their impact on students [8]. The aim of our research is to analyze the level of phubbing among students and the effect of phubbing on students’ academic outcomes.
1.1 Literature Review The intensive spread of information and communication technologies (ICT) over the past decade has changed the social and communication norms of all segments of the population, the negative consequences of which are discussed by scientists. Turel et al. [9] call this phenomenon the “dark side of digitization,” which they see blurs the boundaries of social, personal and professional use of smartphones and social media. Consequently, there is a growing interest in how these technologies affect student behavior, especially with regard to the phenomenon of phubbing [10, 11]. We interpret phubbing as a separate form of smartphone use, which manifests itself in the fact that people constantly check their smartphones during interaction. In other words, people engage in the deliberate act of using a smartphone during social or professional interactions, which constitutes phubbing. Their interlocutors, in turn, may perceive such phubbing as a violation of communication etiquette and a form of social isolation. In our study, we are considering a certain category of people, namely students. Recent research has already shown that this phenomenon can influence the performance of employees who use personal social media during working hours [12, 13]. However, the studies that have come down to us present different views on the nature of this phenomenon. On the one hand, some scholars argue that the use of social media and smartphones can improve productivity [12, 14]. On the other hand, others believe that such use leads to adverse outcomes such as decreased productivity [15, 16] and wasting at the end of the day [17]. To resolve the confusion caused by such disparate findings, scientists have pointed to the urgent need for more sophisticated research into how smartphone and social media use affects productivity [11]. This is especially important in the current environment, when the ongoing coronavirus (COVID-19) lockdowns have forced people to rely on online platforms to maintain a perceived connection with their professional and personal social groups. While the emergence of this area of research explains to some extent the controversial and limited nature of the existing findings, a deeper review points to specific
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limitations that restrict the mainstream literature. Firstly, the existing scholarship has only recently begun to study the phenomenon of phubbing [18, 19]. Moreover, most of the existing research on phubbing focuses on studying the phenomenon in the context of peer relationships such as romantic partners or social media friends [20]. Meanwhile, in the context of the educational environment, previous studies have examined phubbing only among people belonging to different professional groups, for example, between a leader and his employees [21]. Thus, this phenomenon has not been studied among students. In our opinion, the possibility that phubbing can have a negative effect on the educational process carries serious negative connotations for learning outcomes and the quality of the educational process. We argue that the limited understanding of the impact of phubbing on student achievement is a significant knowledge gap that urgently needs to be investigated due to the deep penetration of smartphones into the personal and professional aspects of students’ lives [22, 23]. Also, only limited research examines problem behaviors associated with smartphones and social media [24, 25]. We argue that this is a significant gap, because the nature of everyday life shows that it is the free access to easy-to-use smartphones that creates the possibility of problematic use of social media and, as a result, the dark side of manifestation. As the use of online platforms such as social media and technology devices such as smartphones is expected to grow for the foreseeable future, this knowledge is invaluable in developing proactive interventions that enable people from different walks of life, including adolescents and students, to use these digital tools in a safe and appropriate way.
2 Methods and Materials Our research involved 3rd year undergraduate students studied at Humanity Institute of Peter the Great St. Petersburg Polytechnic University. All students took part in research on a voluntary basis. Table 1 shows the demographic profile of the students. To implement a comprehensive analysis of the level of phubbing we used both quantitative and qualitative data. To collect quantitative data on the level of phubbing among students we conducted an online survey at the spring semester 2021. The survey was based on the Generic Scale of Phubbing [18]. The scale included 15 items, students had to evaluate each item on 5-point Likert scale (1 = not at all true for me, 5 = extremely true of me). To get qualitative data we conducted an online interview with teachers, who taught the students from the sample during spring semester. The interview included 3 questions: “Do students spend a lot of time using their phones?”, “Are they distracted on seminars because of their phones?”, “Does the frequent use of the phone by students interfere with productive work during the seminar?”. We used the students’ semester grades in professional disciplines as measures of academic performance. To analyze the data, we used IBM SPSS Statistics and Person correlation analysis.
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Table 1 Demographic profile of students (N = 108) Demographic variables
Number
Percentage
41
37.96
Gender
Male Female
67
62.04
Field of study
Linguistics
34
31.48
Law
51
47.22
Psychology
23
21.30
3 Results and Discussion 3.1 The Online Survey The results of the online survey are presented in Table 2. The survey revealed a quite high level of phubbing among students (on 6 items answers exceed the measure of 2.5). The highest result was in item “I get rid of stress by ignoring others and paying attention to my phone instead”, that means students tend to deal with stress by plunging into their phones, that negatively influence their social and psychological well-being. Table 2 Level of phubbing among students (N = 108) № Items
Mean SD
1
I feel anxious if my phone is not nearby
2.9
0.67
2
I cannot stand leaving my phone alone
1.97
0.59
3
I place my phone where I can see it
2.73
0.65
4
I worry that I will miss something important if I do not check my phone
2.13
0.71
5
I have conflicts with others because I am using my phone
2.3
0.64
6
People tell me that I interact with my phone too much
2.6
0.55
7
I get irritated if others ask me to get off my phone and talk to them
2.34
0.58
8
I use my phone even though I know it irritates others
2.81
0.77
9
I would rather pay attention to my phone than talk to others
2.11
0.59
10 I feel content when I am paying attention to my phone instead of others
1.69
0.66
11 I feel good when I stop focusing on others and pay attention to my phone instead
1.79
0.71
12 I get rid of stress by ignoring others and paying attention to my phone instead 3.11
0.83
13 I pay attention to my phone for longer than I intend to do so
2.93
0.70
14 I know that I must miss opportunities to talk to others because I am using my 2.11 phone
0.68
15 I find myself thinking “just a few more minutes” when I am using my phone
0.64
2.97
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Table 3 Pearson’s correlation results for the variables under study 1 Phubbling level
1
Academic performance
−0.66***
2 1
Note: * p < 0,05; ** p < 0,01; *** p < 0,001
3.2 The Interview We conducted an online interview with teachers, who taught the students from the sample during spring semester. In total, 9 teachers took part in the interview. Among them there were 2 men and 7 women. It is important to note that the age of 4 teachers were between 30–36 years old, while the rest of the teachers were over 40 years old (the oldest teacher was 63 years old). The interview included 3 questions: “Do students spend a lot of time using their phones?”, “Are they distracted on seminars because of their phones?”, “Does the frequent use of the phone by students interfere with productive work during the seminar?”. All teachers unanimously agreed that students spend too much time using mobile phones. Also, everyone expressed the opinion that mobile phones often distract students during training, which undoubtedly interferes with the learning process and negatively affects student productivity. In general, none of the teachers knew such a term as phubbing, but everyone spoke negatively about the use of mobile phones by students during the seminars. Students are regularly distracted, losing the meaning of the lecture. In addition, students correspond with each other during class, which does not allow them to focus and study productively. It is worth noting that teachers under 40 also noted the positive aspects of using mobile phones during training: this allows the use of gamification methods in the classroom, which increases the motivation of students. It also allows students to always have with them, for example, electronic dictionaries, calculators and even electronic manuals. However, the problem of controlling the use of mobile phones requires special attention: “It is never clear whether a student is using a dictionary or a textbook, or is texting with friends on a social network,” notes one of the teachers. Thus, as a result of the interview, teachers expressed a negative attitude towards the use of mobile telephones during the educational process, noting that the mobile phone distracts students and does not allow them to study effectively.
3.3 The Correlation Analysis Also, we conducted a Pearson correlation analysis to identify whether the level of phubbing impact the academic performance scores of the students. The results are shown in Table 3.
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According to the results, there is a negative and significant correlation between the level of phubbing among students and their academic performance scores. Thus, it can be confirmed the negative influence of such a phenomenon on academic achievements, that should attract attention to this problem.
4 Conclusion The study is devoted to the actual topic of the influence of phubbing on student performance. This problem has hardly been investigated. Past researches [14, 20, 24, 25] reviewed in the literature have raised the issue of phubbing and its impact on interpersonal and professional relationships. However, it is important to deeply examine the impact of phubbing on students and the educational process. 3rd year students of the Humanitarian Institute of St. Petersburg Polytechnic University completed a survey, which allowed us to measure the level of phubbing among them. As a result of the survey, it was concluded that there is a high level of phubbing, which is most often caused by attempts to avoid stress by plunging into your own smartphone. To assess the impact of phubbing on the educational process and the effectiveness of student learning, we interviewed teachers. Teachers raised concerns about the overuse of their smartphones by students, as students are too often distracted by the phone, which reduces their productivity and effectiveness of the educational process. Despite the positive aspects of using a mobile phone for educational purposes, the negative consequences are quite serious, which worries teachers. For a more accurate assessment of the effect of phubbing on student achievement, we conducted a Pearson correlation analysis. The correlation between the level of phubbing among students and their academic performance scores is negative and significant. This confirms the negative impact of phubbing on student performance. Our research has limitations. We considered only Humanities students. In addition, the reasons for the phubbing have not been explored in depth. Future research should explore the reasons for phubbing and how to reduce its negative impact on education.
References 1. Anshari M, Alas Y, Hardaker G, Jaidin JH, Smith M, Ahad AD (2016) Smartphone habit and behavior in Brunei: personalization, gender, and generation gap. Comput Human Behavior 64:719–727. https://doi.org/10.1016/j.chb.2016.07.063 2. Baranova T, Kobicheva A, Tokareva E (2020) Web-based environment in the integrated learning model for CLIL-learners: examination of students’ and teacher’s satisfaction. In: Antipova T, Rocha A (eds) Digital science 2019 DSIC 2019 advances in intelligent systems and computing, vol 1114. Springer, Cham. https://doi.org/10.1007/978-3-030-37737-3_24
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Improving Management Methods for the Formation and Use of Information Resources of Enterprises Svetlana Ovchinnikova , Aleksandr Borovkov , and Elena Schneider
Abstract The paper proposes options for improving the methods of managing the formation and use of information resources of industrial economic entities that are modernizing and taking measures for the technological development of their production systems, taking into account the peculiarities of their activities, and the development of methodological support for managing the implementation of development projects. In particular, a methodological approach to the management of information resources in the course of modernization and development of industrial enterprises is proposed as a means of ensuring their sustainable development. This method differs in that for effective activity in the management systems for sustainable development of enterprises, special subsystems for managing information, intellectual capital and knowledge are introduced, which are a set of interrelated and interdependent components that function in a coordinated manner in the formation of knowledge, their accumulation and use in the implementation of organizational, technological and other changes in production systems. A method for assessing the efficiency of the development of production systems of an industrial enterprise in the field of information and knowledge is also proposed. It is based on calculating the share of an enterprise in the total volume of development knowledge in a certain market. To assess the efficiency of the information resource management system, which is subject to changes in the process of modernization, an integral parameter was proposed, characterized in that it includes indicators of performance, speed and resource intensity, which makes it possible to comprehensively take into account and assess the efficiency of modernization of the production system. During the modernization of industrial production, the correspondence of information and knowledge management processes and elements of organizational culture was revealed, which determine the quality and efficiency of the creation and use of knowledge and the formation of new intellectual capital on their basis. S. Ovchinnikova (B) Kuban State Agrarian University, Kalinin 13, Krasnodar 350000, Russia e-mail: [email protected] A. Borovkov · E. Schneider State Humanitory and Technical Institute, Mira Boulevard 17, Nevinnomyssk 357108, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_88
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Keywords Resource intensity · Method improvement · Modernization · Industrial enterprise · Efficiency · Capital
1 Introduction To analyze the features of industrial development, it is advisable to study the essence of reindustrialization as an economic process and the resulting applied tasks for industrial enterprises. In modern conditions, the lag of the Russian national economy in the technological sphere poses a threat to the country’s sovereignty and the prospects for its existence in the future [1–3]. Overcoming it is possible only under the condition of intensive modernization of industrial enterprises, carried out on the basis of modern technical and economic solutions leading to the development and application of the latest NBIC technologies. In a competitive world economy, the relevance of modernization and technological development of Russian industry has increased significantly. The modernization of industry requires an organizational and economic mechanism for managing the resources of its development. At the end of the first—the beginning of the second decade of this century, the world economy entered a period of reindustrialization—a new phase of development, in which the intellectual capital resulting from the convergence of information and knowledge becomes the leading economic resource for development, and its presence is a key competitive advantage of enterprises, business groups and society as a whole. Modern Russia really entered into a competitive struggle in the world markets only a little more than twenty years ago. The problem of the development of production systems directly related to the formation and use of knowledge (the cognitive component of the economy) is especially acute.For the successful development of industrial production systems, an effective intellectual capital, knowledge and information management system is required [4–6]. The creation and use of information and knowledge are becoming an indispensable condition for the development of modern industry [7–9]. Modern industrial enterprises, among others, have the following problems associated with the management of information resources: • lack of understanding of the role and essence of information, as well as its features in the development processes of various enterprises; • weakness of the methodological apparatus for managing information resources at the organizational level; • lack of effective tools for valuation and value management of information in enterprises; • lack of research of organizational culture as a factor of information support for the development of an industrial enterprise; • insufficient development of tools for managing information resources of innovatively active production systems and economic consolidation of innovative enterprises [10–12].
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The analysis of the available research on this topic revealed that various authors have a number of common approaches to information management in the modernization of production in industry and the management of its development, contributing to the growth of competitiveness. The topics of managing the organization and the use of information resources of industrial enterprises are currently being studied regardless of the individuality of the organizational culture of enterprises, without delving into the unification of the assessment of information in the context of managing the development of production and modernization. Improving the ways of managing education and the use of corporate information resources of industrial enterprises is, in our opinion, a more strategic solution to the aforementioned problems. The information and empirical base of the research consists of the results of research and development, the description of which is contained in the works of Russian and foreign researchers and research teams. In addition, legislative and other normative acts, data of state and corporate statistics, review and analytical materials published in open sources, materials of scientific and other conferences, symposia and other scientific events held in Russia and abroad were used. A significant part of the materials used were the results of authors’ research and development.
2 Methods and Materials Confident action and development of the production system must be presented as a process that includes financial, technological, innovative, market and information sustainability. Each of them must be studied as a subsystem for managing the development of a production system. In the context of this study, the priority is the information stability of the development of the production system, provided by means of managing information flows within the production system and information flows entering the production system across its borders. Thus, a comprehensive indicator of sustainability of the production system development can be proposed: S=
si wi
(1)
i=1
where i—the number of considered subsystems of sustainability of the production system development; si —sustainability of the i-th subsystem; wi —significance of the sustainability of the i-th subsystem. For effective activity in management systems for sustainable development of production systems of enterprises and business groups, special subsystems for managing information, intellectual capital and knowledge are needed, which are a set of interrelated and interdependent components that function in a coordinated manner in the formation of knowledge, their accumulation and use in the implementation of organizational, technological and other changes in production systems. After analyzing this, it can be noted that the more used basis for the development
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of production systems is the provision of information as a structured and ordered direction of data, which must be used to work on improving production in accordance with the purpose of the economic entity of the production system. The initial principles for the formation of knowledge - the result of the process of cognitive activity, we present as information, which is the basis. The information that entered the production system in the form of data is transformed into corporate knowledge, which is necessary for the development of production systems in accordance with the designated goals. It is preliminarily checked for authenticity and adjusted to the conditions of certain production systems. The composition of the functions of information, intellectual capital and knowledge management subsystems is presented in Table 1, and the nature of their interaction is shown in Fig. 1. Table 1 Functions in the information resource management system (author’s development) Subsystem
Function number Function content
Information management 1
Knowledge management
Intellectual capital management
Collection and primary processing of incoming information
2
Analysis of incoming information
3
Formation (replenishment) of the database “Engineering and technology”
4
Formation (replenishment) of the database “Modernization projects”
5
Formation (replenishment) of the database “Development strategies”
6
Identifying the need for additional information
7
Information personification
8
Updating the thesaurus
9
Additional education and professional development of employees
10
Generation of new development knowledge
11
Research of the knowledge and innovation market, formation of proposals for the protection of intellectual property
12
Formation of proposals for the purchase of rights to IPOs from third-party manufacturers
13
Acquisition of rights to IPO
14
Securing the rights of the enterprise to the intellectual capital created by employees
15
Formation of proposals for the commercialization of knowledge
16
Sale of rights to IPO
17
Registration of applications and registration of patents
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Fig. 1 Subsystems for managing information resources of an enterprise during modernization (authors’ development)
Part of the information management system is aimed at coordinating the arrays and flows of information. It includes the following functions: collection and primary use of incoming information; its analysis; formation of the database “Modernization projects”; formation of the database “Development strategies”; formation of the database “Engineering and technology”. Part of the knowledge coordination system with the professional vocabulary of employees is aimed at transforming information into knowledge and work. It consists of the following functions: determining the need for additional information; personification of information; supplementing the collection of information; advanced training and additional education of employees; formation of new development knowledge; studying the market of innovations and knowledge, completing proposals for complex measures for the protection of intellectual property. Part of the intellectual capital management system is mainly aimed at the legal protection of intellectual property rights and the widespread use of commercial principles of corporate knowledge, which are directly related to technological development and modernization. It consists of the following functions: collection of requests for the acquisition of rights to IPOs from third-party manufacturers; purchase of rights to IPO; securing the rights of the enterprise to the intellectual capital produced
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by the employees; completion of proposals for the use of commercial principles of corporate knowledge; sale of rights to OIP; registration of applications and patents. The economic assessment of information resources can be performed based on the classification of knowledge generated and used in production systems. With the effective use of organizational information resources within the enterprise, the competitiveness of the enterprise increases, and the competitive position of the enterprise in the relevant markets improves. At the same time, it is necessary to assess the nature of the market environment in which an economic entity operates for its innovativeness and the intensity of competition in knowledge, since it is the new knowledge generated in the production systems of the enterprise that is the basis for the most effective innovative activity. At the same time, an enterprise that is actively engaged in the modernization and development of its production systems and other innovative activities uses information resources acquired outside its borders (including new knowledge). Such an assessment can be carried out on the basis of indicators of the total volume of innovations in the market under consideration and the share of each market participant in it; the share of the enterprise in the total volume of innovations in the market for a certain period. Depending on this, it is possible to determine the position of the enterprise in the competitive environment in the innovation and knowledge markets (sectoral or regional).
3 Results On the basis of the above, a method has been developed for assessing the efficiency of the development of production systems of an industrial enterprise in the field of information and knowledge, based on calculating the share of an enterprise or a business group in the total volume of development knowledge in a certain market. It differs in that it assesses the competitive advantages of the production system based on interspecific knowledge of development, which is unique and cannot be imitated in other production systems, and also assesses the degree of influence of the competitive advantage on the choice of development strategy that provides the most complete transformation of intellectual capital for increasing the competitiveness of the production system and its cost. The efficiency of the information resource management system can be assessed as a combination of three indicators: performance, resource intensity and promptness. Taking into account the above, an integral parameter of information management efficiency has been developed: E = P · α P + R I · α R I + Pr ·α Pr
(2)
Improving Management Methods for the Formation … Table 2 Competitive positions in knowledge in the modernization of production systems of industrial enterprises (test of author’s development)
Table 3 Risks of resistance of the organizational culture of the studied enterprises to measures of modernization of the production systems of industrial enterprises
863
Company name Indicators of Competitive position competitive positions Enterprise 1
0.22; 0.26; 0
Outsider
Enterprise 2
0.38; 0.36; 0.4
Inventor
Enterprise 3
0.55; 0.57; 0
Follower
Enterprise 4
0.54; 0.58; 0
Follower
Enterprise 5
0.4; 0.37; 0.5
Inventor
Company name Bond strength (Spearman Nature of the risk coefficient) Enterprise 1
Moderate (0.37)
Critical
Enterprise 2
High (0.71)
Minimum
Enterprise 3
Moderate (0.49)
Critical
Enterprise 4
Significant (0.55)
Permissible
Enterprise 5
High (0.74)
Minimum
where P—system performance; RI—system resource intensity; Pr—system promptness; αP, αRI, αPr—weight of indicators. Using the proposed parameter of the efficiency of information, knowledge and intellectual capital management of the production system, estimates were carried out in relation to a number of industrial enterprises carrying out modernization (Table 2).
4 Discussion The organizational culture of an enterprise that is modernizing its production systems performs a number of functions related to the management of internal organizational knowledge and other information resources (Fig. 2).The performed diagnostics of the organizational culture of a number of enterprises showed that for the effective creation, distribution and use of information resources as an asset by these enterprises, it is necessary to reform and reorient their organizational culture, since there is a risk of rejection of modernization projects that are not in harmony with the existing organizational culture in the enterprise.
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1
PERSONAL
ROLE
2
2
3
TASK
Profile of the existing type of organizational culture Profile of the preferred type of organizational culture Fig. 2 Results of the questionnaire survey and the model of organizational culture of OJSC “Spetsinstrument” POWER 3 2 PERSONAL
3
2
ROLE
2
3
TASK
Profile of the existing type of organizational culture Profile of the preferred type of organizational culture Fig. 3 Results of the questionnaire survey and model of organizational culture of Enterprise 1
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5 Conclusions At the same time, the strategy for managing information resources in the course of modernization will also be negatively perceived by the team, which is the bearer of the organizational culture. At the same time, the following tasks were considered: determining the need for knowledge; knowledge creation; acquisition of knowledge; an increase in the share of explicit knowledge. The quantitative characteristics of the tightness of the relationship between the elements of the organizational culture and the parameters of modernization projects in terms of the risk of their rejection were determined by experts. As a result of the survey, the profile of the organizational culture is found and shown in a graphical way, which helps the researchers to authoritatively consolidate the priorities of the respondents presented in several options for each of the four main types of culture. In a similar way, the results of a questionnaire survey of the management and engineering personnel of Enterprise 1 were obtained. The reliability and validity of the results obtained are caused by the use of data with certain reliability, sufficient convergence of the results obtained by the author with the results of studies of other researchers using alternative methods, sound testing, publication and implementation of scientific and practical results into economic practice, correct application of modern scientific methods and tools. The significance of the study is caused by the new scientific knowledge about the economic mechanisms of sustainable development of production systems of industrial enterprises, including in terms of information resources management in the process of their modernization. The value of the research results for economic practice lies in the fact that they are ready to be used in economic entities of the industry of modern Russia for the development and management of the implementation of modernization projects that contribute to increasing their efficiency, competitiveness, and sustainability of functioning and development.
References 1. Ovchinnikova S, Borovkov A (2021) Schneider, E., KalinichenkD, A. Optimal ways to improve the greening of the production sector. E3S Web Conf 244:01013. https://doi.org/10.1051/e3s conf/202124401013 2. Ovchinnikova S, Borovkov A, Kukinova G, Markina N (2021) Environmental substantiation for the use of alternative energy sources. E3S Web Conf 244:01007. https://doi.org/10.1051/ e3sconf/202124401007 3. Ovchinnikova S, Schneider E, Borovkov Lyamina A (2021) Energy potential of modern wind turbines in the Krasnodar Krai). IOP Conf Ser: Earth Environ Sci 937(4):042049. https://doi. org/10.1088/1755-1315/937/4/042049 4. Kozyrev B, Tsoraeva E, Al-Azawi Nagam A, Chibirova and Kozyrev A, (2021) Rational use of land resources: regional aspect. E3S Web Conf 244:03018. https://doi.org/10.1051/e3sconf/ 202124403018
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5. Tsoraeva E, Bekmurzov A, Kozyrev S, Khoziev A, Kozyrev A (2020) Environmental issues of agriculture as a consequence of the intensification of the development of agricultural industry. E3S Web Conf 215:02003. https://doi.org/10.1051/e3sconf/202021502003 6. Tsoraeva E, Mezhyan S, Kataeva M, Hugaeva L, Rogova T (2020) GIS technologies used in zoning agricultural land for optimizing regional land use. E3S Web Conf 224:03001. https:// doi.org/10.1051/e3sconf/202022403001 7. Minaev VA, Pizengolts VM, Faddeev AO, Bystryakov AY, Savenkova EV, Kruglikova EV (2019) Modern information and mathematical models in construction industry. E3S Web Conf 116:00051. https://doi.org/10.1051/e3sconf/201911600051 8. Turski Michał (2018) Eco-development aspect in modernization of industrial system. E3S Web Conf 44:00181. https://doi.org/10.1051/e3sconf/20184400181 9. Zhukov VD, Tsoraeva EN, Perov AU (2021) Problems of land use of water protection zones. IOP Conf Ser: Earth Environ Sci 650(1):012028. https://doi.org/10.1088/1755-1315/650/1/ 012028 10. Borovkov A, Ovchinnikova S, Lyamina A, Zheludkova T (2021) Improving the information resource management strategy in the process of modernizing an industrial enterprise. E3S Web Conf 258:06059. https://doi.org/10.1051/e3sconf/202125806059 11. Faskhutdinov A (2015) Modernization of the Russian Economy in Terms of Innovative Development. Procedia Soc Behav Sci 210(2):188–192. https://doi.org/10.1016/j.sbspro.2015. 11.358 12. Pittaluga GB, Reghezza A, Seghezza E (2020) Reconsidering the modernization hypothesis: The role of diversified production and interest-group competition. Eur J Polit Econ 65:101929. https://doi.org/10.1016/j.ejpoleco.2020.101929
Influence of Changes in the Pavement Concrete Moisture on Its Water Resistance During Traffic Exploitation Ashot Arthur Antonyan
Abstract As a capillary-porous material, concrete constantly interacts with atmospheric moisture. Low environmental moisture leads to moisture desorption from concrete, and vice versa, its increase contributes to the water layers absorption in the cement stone pores. This particularly effects on the properties of concrete pavement during traffic. The article discusses the effect of changing the concrete moisture on its water resistance and strength. The author shows that a change in the concrete moisture has a particularly strong effect on its hydrophysical properties, which must be considered when designing water resistant structures. Keywords Pavement concrete · Traffic · Water resistance · Moisture · Penetration rate · Strength · Porosity
1 Introduction Fluctuations in the environmental temperature and moisture conditions where concrete is used, lead to a change in its properties over time. Shrinkage during moisture desorption (at low ambient moisture) and swelling during adsorption also affect the concrete water resistance. However, for some reason, when designing the structure and testing the concrete itself, this fact is not considered. Moisture in concrete appears due to the bonds between water and solid components. There are 2 sources of moisture in concrete: 1. Intrinsic moisture, due to the excess amount of mixing water, which does not enter a chemical reaction with the cement during its hydration. 2. Adsorbed moisture from the environment surrounding concrete. Water in concrete is held by one of the following bonds: chemical, physicochemical, and physicomechanical [1–4]. A. A. Antonyan (B) The National University of Architecture and Construction of Armenia, Teryan Street 105, Index 0009, Yerevan, Armenia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_89
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The chemical bond is caused by the water chemical interaction with cement minerals with the subsequent entry into the formed crystalline hydrate composition. The energy of the bond chemical form is very high. Calcination or chemical interaction only can break it. The physicochemical or adsorption bond is predetermined by the water adsorption in the molecular force fields’ action zone of the solid phase. It can be disturbed because of water evaporation (desorption) for a long time [5–7]. The physicomechanical bond of water can be found in thin capillaries, pores and cavities. This connection is rather weak and easily broken due to evaporation. The concrete moisture is composed of water, which is retained by physicochemical and physical and mechanical bonds. A change in the amount of physicomechanically and physicochemically bound water entails a change in the concrete moisture. It can either decrease due to desorption or increase slightly by adsorbing moisture from the atmosphere [8–13]. The concrete formation as a material is associated with water modification in the concrete mixture. The moisture content of the concrete mixture before the beginning of cement setting depends on the water content and is in the range of 6–9.5% (for mixtures on dense aggregates). The lowest moisture content corresponds to hard concrete mixes with a low water content. The upper limits of moisture relate to low-grade non-additive concrete mixtures with a mobility of 5–10 cm. The concrete moisture mixtures on porous aggregates are in the range of 18–25%, depending on the water content. Experience shows that the moisture content of hardened old concrete (both light and heavy), which is more than 1 year old, in dry operating conditions is within 3%. Thus, some moisture in concrete is always present due to the water physicochemical bond. The article [4] notes that an increase in the concrete moisture entails an increase in its water resistance. This phenomenon was explained by the swelling of the cement stone and a decrease in the channels’ radius. However, no quantitative data on this issue have been provided, so we experimentally examined the change in some hydrophysical properties of concrete depending on the change in its moisture content. For the present research, the authors used the following materials: basalt crushed stone 5–20 mm from the Yekhegi deposit, washed river sand (Mcr = 2.6), Portland cement CEMII/A-P 42.5 N (Ararat plant). Concrete composition: CS = 1010 kg/m3 , S = 840 kg/m3 , C = 360 kg/m3 , W/C = 0,60, where CS is crushed stone, S is sand, C is cement, W is water. Four series of samples were formed from one batch of concrete mixture, each of series consisted of 3 cylinders 150 × 150 mm and 3 cubes 100 × 100 × 100 mm. 3 series of samples hardened for 28 days under normal conditions, and 1 series in water. The test of the samples was performed according to the scheme given in Table 1.
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Table 1 Scheme of testing samples after 28 days of hardening under appropriate conditions Test immediately after removal from chamber or water
Test 24 h after removal from camera or water*
Test after drying in a drying chamber at 105 °C to constant mass of samples
Test after 6 months of natural drying to constant sample weight **
Normal hardening
+
+
+
+
Hydraulic hardening
+
+
+
−
Notes: “ + ” means that the test was performed, “ − ” that it was not *GOST 12,730.5 requirements for determining the water resistance grade. **natural drying took place in a laboratory room in the presence of silica gel over the samples.
2 Methods The moisture content of the samples was determined by a calculation method, which is based on the statement that cement by 28 days of hardening binds 15% of water from its own mass, therefore, knowing the composition of concrete, its density in an absolutely dry state is calculated as CS + S + C + 0.15C. The difference between the actual and calculated dry density in percent indicates the concrete moisture content. So, in this case, the actual concrete composition (after determining the concrete mixture density) is as follows: CS = 1012 kg/m3 , S = 842 kg/m3 , C = 361 kg/m3 , W = 217 l/m3 , hence the estimated density of absolutely dry concrete will be CS + S + 1.15C = 1012 + 842 + 1.15 × 361 = 2269 kg/m3 . Samples were dried according to the following scheme. After removing from the water and the normal hardening chamber, the samples remained for 1 day in the laboratory room at 20 °C. Then they were placed in a laboratory dryer at 105 °C. To avoid destructive processes from rapid moisture evaporation, the temperature in the dryer rose in a stepwise mode: in the first 2 h from 20 to 30 °C, in the next 2 h from 30 to 70 °C. After 2 h, the temperature rose to 105 °C. Drying of the samples continued until the difference in weight loss for each sample was less than 0.1% within 1 day. The concrete moisture and their density before testing are shown in Table 2. Concrete samples were tested for water penetration rate using the Germann GWT4000 device [5] and water penetration depth according to EN12390-8 after 28 days of hardening under appropriate conditions. The method for determining the water penetration rate is not standardized, but it is widely used in European practice [13–15]. The principle of the device operation is as follows.
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Table 2 Concrete parameters before testing Sample hardening conditions
Normal hardening Hardening in water
Estimated density of absolutely dry concrete, kg/m3
Concrete parameters on the moment of removal from the hardening chamber or from water
Concrete parameters 24 h after removal from the hardening chamber or from water
Concrete parameters after drying at 105° C to constant sample weight
Concrete parameters after 6 months of natural drying to constant sample weight
Density, kg/m3
Moisture, %
Density, kg/m3
Moisture, %
Density, kg/m3
Moisture, %
Density, kg/m3
Moisture, %
2269
2381
4.95
2360
4.0
2269
0
2287
0.79
2406
6.04
2382
4.98
2270
0.04
-
-
Fig. 1 a general scheme of the Germann GWT-4000 device b testing of concrete for the water penetration rate. 1—concrete sample, 2—GWT-4000 device, 3—clamps.
The device is fastened with clamps to a structure (or a sample) filled with deaerated water, and a pressure of 0.5–1.5 bar is created by moving the piston mechanism. The diameter of the device lower part (water penetration zone) is 62 mm. Since the pressure in the system drops due to water filtration, the required pressure is maintained at equally measured intervals by moving the same piston mechanism. Knowing the diameter of the filtration flow, according to D’Arcy’s law, the filtrate movement rate through the concrete is calculated (Fig. 1) [5].
3 Results and Discussion The test results are shown in Fig. 2 and Table 3. Points: A—concrete parameters on the moment of removal from the normal hardening chamber (after 28 days of hardening). B—concrete parameters after 24 h of being in laboratory conditions (GOST requirement for determining the concrete water resistance).
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Fig. 2 Changes in the hydrophysical properties of concrete depending on its moisture content. 1—dependence for concrete hardening in water, 2—same under normal conditions
C—normal hardened concrete parameters after drying in a drying chamber to constant sample mass. D—water-hardened concrete parameters after drying in a drying chamber to constant sample weight. E—concrete parameters on the moment of removal from water (saturated state). Table 3 Test results of concrete hydrophysical and strength properties at different moisture content Sample hardening conditions
Normal hardening
Hardening in water
Concrete moisture, %
Water penetration rate, mm/s
Water penetration depth, mm
Water resistance concrete grade*
On the moment 4.95 of removal from the chamber
2.53 × 10–4
–
W16
–
24 h after removal from the hardening chamber
4.0
4.52 × 10–4
61
W10
29.3
After drying at 1050 C
0
1.52 × 10–3
112
W4
35.7
After natural drying
0.79
1.32 × 10–3
110
W4
35.2
On the moment 6.04 of removal from water
0
–
–
28.5
After drying at 1050 C
9.01 × 10–4
100
W6
35.9
0
Note: * according to the data of the article [13]
Concrete strength, MPa
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F—concrete parameters after 6 months of natural drying in laboratory conditions (in the presence of silica gel). From the results of Table 3, one can understand that the change in moisture content strongly affects both the hydrophysical and mechanical properties of concrete. So, after removal from the normal hardening chamber, and after 24 h in the laboratory room, the concrete moisture content decreases by almost 1% (from 4.95 to 4%) due to desorption. In this case, the water penetration rate increases from 2.53 × 10–4 to 4.52 × 10–4, that is, 1.79 times. Due to forced or natural drying, the penetration rate increases by 6 and 5.2 times, respectively. Similar results are obtained when testing concrete for water penetration depth. The water penetration depth for dried concrete is increased by 1.8 times. This proves the fact that at high concrete moisture content, the radius of the capillaries decreases [16–21] due to swelling. So, the water penetration rate of water-saturated concrete on the moment of removal from water tends to 0. After drying the water penetration rate for the same concrete (hardening in water) increases to 9.01 × 10–4 mm/s. The decrease in the concrete permeability at high moisture can be explained not only by the cement stone swelling, but also by the fact that at high moisture the capillaries are filled (partially or completely) with water, which is retained by capillary forces, preventing the water penetration from the outside. Moisture desorption leads to an increase in the concrete strength, in contrast to water resistance. So, for concrete of normal hardening after drying in a dryer and under natural conditions after 6 months, the strength increased from 29.3 to 35.7 and 35.2 MPa, respectively. For concrete dried in a dryer, this increase is explained by the effect of additional heat and moisture treatment, where the moisture agent is water in the pores. High temperature and the moisture presence intensify the hydration reaction, which leads to an increase in strength. With natural drying, moisture removal goes very slow. During this time, part of it interacts with cement, so that the hardening effect is the same for 2 cases. The considered hardening refers to concretes of an early age, from which mainly physicomechanical and partially physicochemical water is desorbed. However, in [11], where the issues of old concrete strength, the age of which is more than tens of years, are considered, the author emphasizes that after a slight increase in strength its decline follows due to physicochemical water desorption.
4 Conclusion From the above, the authors draw the following conclusion: – Moisture desorption from hardened concrete leads to an increase in its permeability. This increase, depending on the test method, can be 1.8–6 times. – During desorption, an increase in concrete strength up to 20% is observed. – The negative effect of desorption on hydrophysical properties should be considered in the structures design and manufacture.
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References 1. Park SS, Kwon SJ, Jung SH, Lee SW (2012) Modeling of water permeability in early aged concrete with cracks based on micro pore structure. Constr Build Mater 27(1):597–604 2. Vanesa OL, Jos´e FA, Amaia S, Jos´e SJ, ´Angel A, (2018) Durability studies on fiber reinforced EAF slag concrete for pavements. Constr Build Mater 163:471–481 3. Özalp F, Yılmaz HD, Kara M, Kaya O, Sahin A (2016) Effects of recycled aggregates from construction and demolition wastes on mechanical and permeability properties of paving stone, curb and concrete pipes. Constr Build Mater 110:17–23. https://doi.org/10.1016/j.conbuildmat. 2016.01.030 4. Smyl D, Ghasemzadeh F, Pour-Ghaz M (2016) Modeling water absorption in concrete and mortar with distributed damage. Constr Build Mater 125:438–449 5. Home page. http://germann.org/products-by-application/water-penetrability-2/gwt 6. Claisse PA, Elsayad HI, Shaaban IG (2008) Absorption and sorptivity of cover concrete. J Mater Civ Eng 9:105–110 7. Yi S-T, Hyun T-Y, Kim J-K (2011) Effects of hydraulic pressure and crack width on water permeability of penetration crack-induced concrete. Constr Build Mat 25(5):2576–2583 8. Rani BD, Rao BK (2019) Service life prediction of high-performance concrete with respect to chloride ion penetration by incorporated with fly ash and silica fume. International conference on advances in civil engineering (ICACE-2019) 9. Rinker ME (2013) Determination of acceptance permeability characteristics for performancerelated specifications for Portland cement concrete. Report submitted to Florida department of transportation, university of Florida 10. Wang H, Sun X, Wang J, Monteiro PJM (2016) Permeability of concrete with recycled concrete aggregate and pozzolanic materials under stress. Mat 9(4):252. https://doi.org/10.3390/ma9 040252 11. Sandhu AR et al (2019) Effect of river indus sand and recycled concrete aggregates as fine and coarse replacement on properties of concrete. Eng Technol Appl Sci Res 9(1):3832–3835. https://doi.org/10.48084/etasr.2558 12. Bilir T (2012) Effects of non-ground slag and bottom ash as fine aggregate on concrete permeability properties. Constr Build Mater 26(1):730–734. https://doi.org/10.1016/j.conbuildmat. 2011.06.080 13. Loosveldt H, Lafhaj Z, Skoczylas F (2002) Experimental study of gas and liquid permeability of a mortar. Cement Concr Res 32(9):1357–1363. https://doi.org/10.1016/S0008-8846(02)007 93-7 14. Stark J, Wicht B (2008) Concrete strength (Kiev: Oranta, p 295) 15. Zhang X, Wang L, Zhang J (2017) Mechanical behavior and chloride penetration on high strength concrete under freeze-thaw attack. Cold Reg Sci Technol 142:17–24 16. Bravo M, de Brito J, Pontes J, Evangelista L (2015) Mechanical performance of concrete made with aggregates from construction and demolition waste recycling plants. J Clean Prod 99:59–74. https://doi.org/10.1016/j.jclepro.2015.03.012 17. Adnan SH, Lee YL et al (2008) Water permeability of recycled aggregate concrete presented at the technology and innovation for sustainable development conference. Khon Kaen, Thailand 18. Kondraivendhan B, Bhattacharjee B (2013) Pore size distribution modification of OPC paste through inclusion of fly ash and sand. Mag Concr Res 65(11):673–684 19. Zhu X, Zi G, Lee W, Kim S, Kong J (2016) Probabilistic analysis of reinforcement corrosion due to the combined action of carbonation and chloride ingress in concrete. Constr Build Mater 124:667–680 20. Yoo J-H, Lee H-S, Ismail MA (2011) An analytical study on the water penetration and diffusion into concrete under water pressure. Constr Build Mat 25(1):99–108 21. Liu X, Chia KS, Zhang MH (2011) Water absorption, permeability, and resistance to chlorideion penetration of lightweight aggregate concrete. Constr Build Mat 25(1):335–343
The Freezing Zone Formation of the Probe Around the Vertical Ground Heat Pumps Nikolay Rudenko , Irina Fursova , Darya Belyaeva , Sofya Popoudina , and Elena Dokhoyan
Abstract The work is aimed at studying questions of mathematical modeling and computational experiment to predict the effect of a heat pump probe operating during a year in various operating modes on freezing and thawing of the soil around it. The presented solutions make it possible, by calculation, to estimate the size of the freezing zone in an unsteady thermal regime, which helps to make a decision in the design of the required distance between the building foundation and the heat pump probe. Keywords The freezing zone · Vertical ground heat pumps · The heat flux depends · Soil freezes · Building · Heat pumps
1 Introduction When the soil freezes, there is a threat of swelling. If the ground repeatedly freezes and thaws it reduces its bearing capacity. An essential factor when choosing foundation structures is the presence of freezing zones. Quite a lot of works are devoted to the study of the properties of frozen soil [1, 2]. The most urgent is the study of this issue in zones with permafrost, when freezing can be tens of meters. This issue has become relevant for the southern regions of the country in connection with the emergence of ground heat pumps [3–5]. Many heats pump (HP) manufacturers recommend using soil as the main source of heat. In the southern regions of the country, at a depth of over five meters, the temperature practically does not change throughout the year and is about +10 °C. Such a heat source at a negative outside temperature can be regarded as a priority. The intake of thermal energy from the surface layers of the earth is associated with N. Rudenko · D. Belyaeva (B) · S. Popoudina · E. Dokhoyan Don State Technical University, 1 Gagarina Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] I. Fursova Southern Federal University, 105/47 Bolshaya Sadovaya Street, 344006 Rostov-on-Don, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_90
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Fig. 1 Scheme of ground probes for heat pumps
additional costs for earthworks. The use of depth boreholes leads to minimization of these costs. They represent boreholes up to 100 m deep, Fig. 1. The U-shaped pipe is lowered into the borehole, a refrigerant circulates through it with temperatures down to −15 °C. A zone of frozen ground is formed around the probe, spreading to a great depth. And the processes of freezing and thawing occur during the year. If these probes are in close proximity to building structures (piles), then this can lead to a decrease in the bearing capacity of the foundations of adjacent buildings.
2 Formulation of the Problem The size of the freezing zone around the heat pump probes can have a direct impact on the reliability of adjacent foundations [6, 7]. Let us carry out an analysis to clarify the size of the freezing zones around the probes. This will allow at the design stage to select the location of the heat pump probes. And it will prevent a negative impact on the base of the foundation.
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A heat pump that will be used to supply heat to heating systems will produce the maximum heat flow at minimum outdoor temperatures. The minimum air temperatures in most regions of Russia are observed in the second half of January, that is, in the middle of the heating season. The demand for heat energy in the first half of the season increases, and in the second half it decreases. Freezing and thawing cycles have the greatest impact on reducing soil strength. Freezing occurs once in the first half of winter. At the end of the heating period, the demand for heat extraction decreases, which leads to an increase in temperatures around the probe. The heat pump runs in on/off mode. Such a mode will inevitably lead to a change in the temperature field around the probe. If the bulk of the soil is frozen, practically the entire heating period, then the part located on the border of the freezing zone will be subject to frequent thawing. Periodic thawing and freezing affects the bearing capacity of the soil. Clarification of the size of the zone with the most frequent thawing processes is an urgent issue. After switching off the heat pump, temperature equalization will be observed. The average temperature in the zone of influence of the probe will increase due to the penetration of heat from the surrounding warm soil. However, the size of the freezing zone can increase for a short time due to non-stationary processes during the propagation of a heat wave. Taking into account that the temperature field around the probe is symmetric, it is possible to consider a one-dimensional problem using radial coordinates. Let’s conditionally select a cylinder around the borehole axis. In cylindrical coordinates, with distance from the axis, the heat flux density decreases. Let’s select inside the cylinder a thin layer of radius r and thickness dr. Using Fourier’s law, the following equation can be written [8]: Q = −λ
dt dt F = −λ 2πrl dr dr
(1)
After separating the variables, we get dt = −
Q dr 2πrl r
(2)
We integrate the temperature value in the range from t1 to t2, and the radius value in the range from r1 to r2. t2 t1
t1 − t2 =
r2
dr r
(3)
Q r2 ln 2πrl r1
(4)
Q dt = 2πrl
r1
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N. Rudenko et al. t, oC 15 10 5 0
0
0,5
1
2
1,5
2,5
3
-5 -10 -15 r, m
Fig. 2 Distribution of temperatures t o C around the probe depending on the radius r m under stationary conditions at a heat flux density 1) 30 W/m, 2) 40 W/m, 3) 50 W/m
Q = 2πrl(t 1 − t2 )/ln
r2 r1
(5)
The resulting dependence is valid for stationary thermal conditions. However, the heat pump is characterized by nonconstant mode of operation. Let us consider a non-stationary thermal mode to clarify the size of the thawing zone, the frequency of thawing, and the processes of equalization (regeneration) of the temperature field. The non-stationary thermal mode is described by the following differential equation [9]: dT d dT dT d λ + λ = −q − cp dx dx dx dy dt
(6)
An analytical solution to this equation is not possible under the boundary conditions corresponding to the temperature field shown in the graph (Fig. 2). Therefore, to solve this problem, we use the numerical finite element method. It will allow using a computational experiment to obtain a result with high accuracy [10].
3 Numerical Solutions and Analysis of Results The heat flux Q to the probe is determined by the thermal conductivity of the soil λ. The temperature distribution function will be non-linear (1). To clarify the graph of the temperature distribution around the heat pump probe, let us consider a specific case. We take the inner diameter d1 according to the size of the borehole (d1 =
The Freezing Zone Formation of the Probe …
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0.1 m), the temperature on the borehole axis is −15 °C (t1 = −15 °C), and the thermal conductivity of the soil is λ = 1.64 W/m2 °C. In the recommendations for the use of heat pumps [11], it is proposed to use the value of the heat flux from one running meter of the probe q = 30–50 W as a calculated value. The value of the heat flux depends on the thermophysical characteristics of the soil: thermal conductivity, heat capacity, density (5). Changes in these characteristics during operation are usually insignificant. To a greater extent, the heat flux depends on the zone of influence. During the first year of continuous operation, the probe lowers the temperature around itself by only a distance of up to 3 m, and the efficiency of heat removal is maximum. After several years, this zone increases several times, and the heat flux decreases to 30 W. Depending on the size of the zone of influence, the size of the zone of frozen soil will change. To determine this zone, we will perform calculations according to formula 4. The results are shown in Fig. 2. As seen in Fig. 2 in addition to increasing the radius of the cooled soil around the probe, the freezing zone around it also grows: in the first year its diameter does not exceed 0.7 m, after two, three years of operation it increases to 1.2 m, and after 10 years it reaches a maximum of 3 m. For further calculations, we will use the ELCUT 6.3 software package, which performs calculations using the finite element method [12]. To check the accuracy of the calculations, we will calculate the stationary heat transfer problem for the boundary conditions set forth above. Let us determine the temperature distribution with move away from the heat pump probe in the ground under stationary thermal conditions. As a study area, consider soil with a diameter of 10 m. This diameter is obviously larger than the zone of influence in the first year of operation. The values of temperatures (595 knots) are determined on the sought-for area. On the graph (Fig. 3), the solid line shows the values calculated by formula 4, and the marker shows the calculated points calculated using the finite element method. It is visually clear that there are practically no discrepancies. The analysis of the graphs allows us to conclude that the finite difference method can be successfully used to assess the change in the temperature field when the temperature field is equalized during the period when the heat pump is turned off. The switch off period of the heat pump can vary from tens of minutes to several hours. We will perform a series of calculations to clarify the zone of the most frequent defrosting. In Fig. 4 shows temperature graphs for switch off periods from 1 to 5 h. In Fig. 4 shows the distribution of temperatures for different points in time after switching off the heat pump. Let us determine the changes in the size of the freezing zone after switching off the heat pump. Let us consider an area that is obviously larger than the zone of influence of the heat pump, with a radius of 10 m. As the initial conditions, we use the temperature distributions for the stationary thermal mode. At the boundary of the probe, we take the value of the heat flux equal to zero. As can be seen from this graph, the size of the freezing zone changes slightly with periodic switch off of the heat pump. During the period when the heat pump is
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N. Rudenko et al. t, oC 8 6 4 2 0 -2
0
0,2
0,4
0,6
0,8
1
1,2
1,4
-4 -6 -8 -10 -12
r,m
Fig. 3 Temperature distribution graph t, °C in the soil depending on the radius r, m
t, oC
5 4 3 2 1 0 -1
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
-2 -3 -4 -5
r,m
Fig. 4 Temperature change soil t, o C depending on the radius r, m after switching off the heat pump after 1) 1 h, 2) 3 h, 3) 5 h
switched off, the temperature field will level out within the freezing zone. However, the size of this zone remains almost unchanged. It is also of interest to change the temperature field in the warm season, after switching off the heat pump for a long time. To analyze the processes, we will also consider a non-stationary mode. The calculation results are show in Fig. 5. From the analysis of the presented graphs it can be seen that the regeneration zone of the temperature field will increase with time.
The Freezing Zone Formation of the Probe …
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t, oC 15 10 5 0
0
0,5
1
1,5
2
2,5
3
3,5
-5 -10 -15
r,m
Fig. 5 Temperature change soil t,o C depending on the radius r, m. 1) at the moment of switch off. 2) after 10 h, 3) after 100 h, 4) after 50 days
From the data obtained in the course of the numerical experiment on the heating time of the zone around the heat pump probe, it follows that it is necessary to take into account not only the fact of soil freezing, but also the operating mode of the heat pump.
4 Conclusions When designing the mutual arrangement of building foundations and heat pump probes, it is necessary to calculate the size of the soil freezing zone. The calculation is necessary for those regions of construction in which, according to climatic data, the soil does not freeze to a considerable depth. The calculation algorithm and software package has been developed to calculate the freezing zone around heat pump probes, which allows calculations for various operating modes. The use of the finite element method gives a high accuracy of calculations, which can be used to calculate non-stationary thermal mode in the soil. The calculations show that the periods of cyclic operation of the heat pump during the day do not have a significant effect on the reduction of heat extraction from the soil. In this case, only the freezing zone slightly decreases in the immediate vicinity of the probe. In turn, if the heat pump does not work constantly for heating in the off-season, the operating cycles will significantly affect the change in the size of the freezing and thawing zone, and, as a consequence, the change in the bearing capacity of the soil.
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References 1. Sidnyaev NI, Vasiliev VI, Ilyina YuS (2020) Methods for calculating the influence of nonstationary temperature fields in the cryolithozone on the foundation. Arctic Antarctic 2:106–125. https://doi.org/10.7256/2453-8922.2020.2.32405 2. Xu Q, Yan X, Grantzc DA et al (2020) Improving estimation of evapotranspiration during soil freeze-thaw cycles by incorporating a freezing stress index and a coupled heat and water transfer model into the FAO Penman-Monteith model. Agric For Meteorol 281:107847. https:// doi.org/10.1016/j.agrformet.2019.107847 3. Hu X, Zhu Ch, Wu H et al (2022) Large-scale preparation of flexible phase change composites with synergistically enhanced thermally conductive network for efficient low-grade thermal energy recovery and utilization. Compos A Appl Sci Manuf 154:106770. https://doi.org/10. 1016/j.compositesa.2021.106770 4. Lee CK, Lam HN (2008) Computer simulation of borehole ground heat exchangers for geothermal heat pump systems. Renew Ener 33(6):1286–1296. https://doi.org/10.1016/j.ren ene.2007.07.006 5. Efimov VM, Vasilchuk YuK, Rozhin II, Popenko FE, Stepanov AV (2017) Modeling of the temperature regime of soil bases with seasonal cooling devices in the conditions of the cryolithozone of the Republic Sakha (Yakutia). Arctic Antarctic 4:86–97. https://doi.org/10.7256/24538922.2017.4.25036 6. Ozgan E, Serin S, Erturk S, Vural I (2015) Effects of freezing and thawing on the consolidation settlement of soils. Soil Mech Found Eng 5:7. https://doi.org/10.1007/s11204-015-9336-6 7. Hou X, Chen J, Jin H et al (2020) Thermal characteristics of cast-in-place pile foundations in warm permafrost at Beiluhe on interior Qinghai-Tibet Plateau: Field observations and numerical simulations. Soils Found 60(1):90–102. https://doi.org/10.1016/j.sandf.2020.01.008 8. Ali Shah N, Wakif A et al (2021) Effects of fractional derivative and heat source/sink on MHD free convection flow of nanofluids in a vertical cylinder: A generalized Fourier’s law model. Case Stud Therm Eng 28:101518. https://doi.org/10.1016/j.csite.2021.101518 9. De Lorenzo G, Corigliano O, Fragiacomo P (2022) Analysing thermal regime and transient by using numerical modelling for solid oxide electrolyser aided by solar radiation. Intern J Therm Sci 177:107545. https://doi.org/10.1016/j.ijthermalsci.2022.107545 10. Yavuzturk C, Spitler JD, Rees SJ (1999) A transient two-dimensional finite volume model for the simulation of vertical U-tube ground heat exchangers. ASHRAE Trans 105(2):465–474. https://doi.org/10.1007/s11630-003-0012-1 11. Marinelli S et al (2020) Environmental performance analysis of a dual-source heat pump system. Ener Build 223:110180. https://doi.org/10.1016/j.enbuild.2020.110180 12. Steiner TR (2022) High temperature steady-state experiment for computational radiative heat transfer validation using COMSOL and ANSYS. Results Eng 13:100354. https://doi.org/10. 1016/j.rineng.2022.100354
The Limiting Rut Depth by Conditions Safety of Traffic Anatoly Aleksandrov
and Tatyana Semenova
Abstract Currently, when calculating road pavements, a criterion is used that limits the depth of the ruts formed on the asphalt concrete pavement. The actual depth of the rut is calculated according to well-known analytical solutions and mechanicalempirical formulas, assuming that the rut is formed due to wear of the pavement, as well as the accumulation of residual deformations in the structural layers of the pavement and the subgrade soil. The actual rut depth is compared with the limit value, which is assigned according to the recommendations of the road agencies. Analysis of the limit values of the rut depth recommended by different authors and used in the practice of various road agencies showed that these values differ by a factor of 1.5–2.5. The article presents a method for calculating the limit depth of the rut, which allows limiting its values depending on the required values of the coefficient of adhesion of the tire with the coating, the speed of movement along the road section, the depth of the water layer in the rut and the roughness parameters of the coating. The calculation of the limit depth of the rut is based on the criterion according to which the actual value of the coefficient of adhesion of the tire with the coating cannot exceed the limit value. To calculate the coefficient of adhesion of a tire with a coating, a mathematical model was obtained describing experimental data on the dependence of the coefficient of adhesion of a tire with a coating from the depth of the water layer, the parameters of the roughness of the coating, and the speed of movement. From this dependence, at the required (limit) value of the coefficient of adhesion, speed of movement, roughness parameters, a dependence is obtained that allows calculating the critical thickness of the water layer and the corresponding limit depth of the rut. The results of calculating the limiting rut depths for various conditions of the pavement are presented. Keywords Road · Rut depth · Limit rut depth · Pavement
A. Aleksandrov (B) · T. Semenova The Siberian State Automobile and Highway University, 5 Mira Avenue, 644080 Omsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_91
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1 Introduction In the rut formed on the surface of road surfaces, rainwater accumulates. This leads to a decrease in skid resistance [1–5], and in some cases causes the effect of hydroplaning [6]. As a result of the lifting force of water on the tire, it comes into contact with the water film, and the vehicle becomes uncontrollable. Specialists of the road industry slip resistance is characterized by the value of the coefficient of adhesion ϕ of a tire with coating, which is determined by the ratio of the rolling resistance of the tire Fx to the vertical load on the tire axle Fh . The coefficient of adhesion has its own limit values, which are compared with the actual values measured under certain conditions. In terms of the value of coefficient of adhesion, the requirements for traffic safety are stricter than for the speed of aquaplaning. Therefore, the depth of the rut should not exceed the limit values at which the depth of water accumulated in the rut causes an unacceptable decrease in the coefficient of adhesion. Thus, by limiting the depth of the rut, safe movement is possible if the condition is met: R D ≤ R Dlim
(1)
where RD and RDlim —actual and maximum depth of rut, mm. Currently, models are known that link the depth of the rut with deformations accumulated by asphalt concrete in the coating, granular materials in the base and soil in the roadbed [7–10]. An overview of methods for calculating the deformation accumulated by granular materials and soils of the roadbed is presented by us in the works [11–13]. Proposals for determining the limit depth of the rut are made in [2, 14–20], but the values of the limit depth of the ruts regulated in them differ significantly. The difference is 2 or more times. Therefore, the purpose of the publication is to develop a methodology for calculating the limit depth of the rut from the conditions for placing rainwater in it, the depth of which does not lead to a critical decrease in the coefficient of adhesion of the tire with the coating.
2 Materials and Methods The flow of water from the roadway is provided by longitudinal and transverse (crossfall) slopes. Therefore, when filling the rut with water, the depth of the rut RD is greater than the depth of the water WD. Due to the crossfall, excess water flows out of the rut and is transported further, for example, to the kerb. This statement can be shown in the form of a scheme [6]. From the scheme shown in Fig. 1, it follows that the depth of the rut is determined by the sum of the depth of the water in the rut and the value d. The value d is the part
The Limiting Rut Depth by Conditions Safety of Traffic
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Fig. 1 Measuring the wheel rut [6]
of the depth of the rut that is not filled with water. This value is determined by the product of the distance from the edge of the rut to the measuring point of the depth of the rut brut and the slope i. Of course, the limit depth of the rut should be determined by the sum of the critical water depth WDcr and the value d corresponding to the maximum depth of the rut. Assuming that there are two ruts within the traffic lane without lateral bulges, the value of brut can be found as a fourth of the width of the traffic lane btl , that is, brut = 0.25 × btl . Then the limit depth of the rut, measured in mm, can be calculated by the formula: R Dlim = W Dlim + 0, 25 · bt1 ·
103 ·i 104
= W Dlim + 0, 025 · bt1 · i
(2)
The trajectory of the water flow depends on the slope of the drain i, which can be determined through the crossfall ic and longitudinal ils slope: i 2 = i c2 + ils2 ; i =
i c2 + ils2
(3)
The condition guaranteeing traffic safety is to ensure the required adhesion qualities of the wet coating with the tire and finding the critical water depth of the WDcr from this condition. As such a condition, we take the inequality according to which the actual coefficient of adhesion ϕ should not exceed a certain limit value ϕlim : ϕ ≥ ϕlim
(4)
Taking into account the requirements for measuring the coefficient of adhesion, the limit value of this coefficient ϕlim is given for certain conditions. Such conditions include a speed of 60 km/h, an air temperature of 20 °C, a water film thickness of 1 mm, the type of tire coating (with a tread depth of at least 1.0 mm or without a tread.
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Of course, if one of the listed factors changes, for example, the speed of movement, the value of the coefficient of adhesion will change. Therefore, factors affecting the value of the coefficient of adhesion must be taken into account when regulating its limit value. According to A. P. Vasiliev, the transition from the adhesion coefficient ϕϑ1 measured at one speed ϑ1 to the adhesion coefficient ϕϑ2 at another speed ϑ2 can be carried out by the formula: ϕϑ2 = ϕϑ1 − βϕ (ϑ2 − ϑ1 )
(5)
where βϕ – parameter that takes into account the change in the coefficient of adhesion depending on the speed of the vehicle, the type of coating and its condition. The dependence (5) is applied by us to calculate the required value of the coefficient of adhesion at different speeds of movement ϕlimϑ on wet clean and wet dirty coatings. In this case, dependency (5) will take the form: ϕlim ϑ = ϕlim − βϕ (ϑ2 − 60)
(6)
where ϕlim – the required value of the coefficient of adhesion, measured at a speed of 60 km/h. The results of the calculation of the limiting adhesion coefficients are given in Table 2, in which ϕ lim is adopted according to different standards (0.45; 0.40 and 0.35). The limit values of the coefficient of adhesion of a tire with the coating, presented in Table 1, can be used in criterion (4). The application of criterion (4) requires the development of a mathematical model that takes into account the influence on the value of the coefficient of adhesion, both the speed of movement and other factors, which, first of all, must include the roughness of the coating and its condition, characterized by the depth of the layer of flowing water. The value of the coefficient of adhesion of the tire to the surface was measured at different speeds of movement of the mobile device ϑ, different parameters of the roughness of the surface R and different depths of the water layer on the surface WD. In this case, the depth of the water layer WD was always such that the condition 0 ≤ R-WD < R was ensured. The difference R-WD is called the active average height of the roughness protrusions Ract . This parameter characterizes the value of roughness protrusions not filled with water and capable of being pressed into the tire providing Table 1 Limit values of the coefficient of adhesion for different speeds of movement Condition of the coating Asphalt concrete with chip seal, wet and clean β ϕ = 0.0035
Movement speed, km/h 60
70
80
90
100
110
120
0.45
0.41
0.37
0.33
0.29
0.25
0.21
0.40
0.37
0.33
0.30
0.26
0.23
0.19
0.35
0.32
0.28
0.25
0.21
0.18
0.14
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Table 2 Limit depths of rut to ensure safe movement at different speeds at the ensure adhesion coefficients of the tire to the surface Movement speed, km/h
Required coefficient of adhesion
Limit rut depth RDlim (mm) at an average height protrusions of roughness R (mm) 0.5
1.0
2.0
3.0
4.0
5.0
60
0.35
22.1
22.6
23.6
24.6
25.6
26.6
80
0.28
3.7
4.2
5.2
6.2
7.2
8.2
100
0.21
2.2
2.7
3.7
4.7
5.7
6.7
120
0.14
1.6
2.1
3.1
4.1
5.1
6.1
60
0.40
14.4
14.9
15.9
16.9
17.9
18.9
80
0.33
2.4
2.9
3.9
4.9
5.9
6.9
100
0.26
1.1
1.6
2.6
3.6
4.6
5.6
120
0.19
0.1
0.6
1.6
2.6
3.6
4.6
60
0.45
7.7
8.2
9.2
10.2
11.2
12.2
80
0.37
1.5
2.0
3.0
4.0
5.0
6.0
100
0.29
0.5
1.0
2.0
3.0
4.0
5.0
120
0.21
-0.4
0.1
1.1
2.1
3.1
4.1
the effect of adhesion of a wet rough surface with the tire of a mobile simulator. As a result of measurements of the depth of the flow, it was found that its experimental values are in good agreement with the theoretical values calculated by the formula: ⎞0.588 a · L · n w ⎠ WD = ⎝ −1 30 · k · 4 i c2 + ils2 ⎛
(7)
where a—rain intensity, mm/min; L w —length of water flow section, mm; n— hydraulic roughness factor; ils , ic —respectively, the longitudinal, transverse slope of the carriageway and the slope of the drain, % or %o; k – factor taken equal when measuring slopes, in % - k = 10, and when measuring the slope, in %o - k = 31.6228. Length of water drainage section L w and the coefficient of hydraulic roughness p are determined by the formulas: Lw = b ·
1+
ils ic
2 ;n=
R 0.2 23.3
(8)
where b—shortest distance from the point of determining the depth to the axis of the carriageway, mm; R—average height of roughness protrusions, m.
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Taking into account formulas (8), dependence (7) takes the form: ⎛
a WD = ⎝ ·b· 30 · k −1 · 4 i c2 + ils2
1+
ils ic
2
⎞0.588 R 0.2 ⎠ · 23.3
(9)
The results of the experiment on measuring the coefficient of adhesion of the tire and the surface were statistically processed. As a result, an empirical formula is obtained:
ϑ ϑ 2 − 1.3591 · + 1.226 × φ = 0.399 · ϑlim ϑlim
R −WD ϑ ϑ 2 × exp · 1.2473 · − 0.4861 · − 0.598 (10) 2 · Rlim ϑlim ϑlim where ϑ and ϑlim —actual and limit (ϑlim = 90 km/h) travel speed on public roads, km/h; R—average height of the coating roughness protrusions, mm; Rlim —limit values of the average height of the protrusions for smooth surfaces, 0.5 mm; WD— flow depth, mm. Formula (7) is convenient in that it is easy to determine from it the difference between the average height of the roughness protrusions R and the limiting water depth WDlim , at which, depending on the speed of movement ϑ, the required values of the adhesion coefficient ϕlimϑ are provided. From the obtained equation, the limiting water depth WDlim is expressed, at which in condition (4) the limiting state ϕ = ϕlimϑ appears. This formula has the form: W Dlim = R −
2 · Rlim 1.2473 ·
⎡ ⎢ × ln⎣
0.399 ·
ϑ ϑlim
ϑ ϑlim
2
− 0.4861 ·
ϑ ϑlim
2
− 0.598 ⎤
φlim ϑ − 1.3591 ·
ϑ ϑlim
+ 1.226
⎥ ⎦
×
(11)
Formulas (5) and (9) make it possible to assess traffic safety by the criterion of water depth on the surface. Traffic safety is ensured if the condition: W D ≤ W Dlim
(12)
After calculating the critical depth of water, according to the formula (2), the limiting depth of the rut is calculated.
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3 Results The illustrations of the solution to the problem of the limiting rut depth will be presented in the form of graphs and tables, displaying the main obtained dependencies. In Fig. 2 shows the dependence of the coefficient of adhesion of the tire to the surface on the speed of movement and the active average height of the roughness protrusions. The calculation of the adhesion coefficients was carried out according to the formula (7). This graph shows the limiting values of the adhesion coefficient, which are biggest taken presented in Table 2. Figure 2 illustrate the check of traffic safety according to criterion (4). From the analysis of these data, it follows that at a speed of 60 km/h with an active average roughness of the pavement from 0.5–5.0 mm, the actual values of the adhesion coefficient ϕ exceed the limiting value ϕlim60 = 0.45. This means that under these conditions, driving at a speed of 60 km/h can be considered safe. At other speeds, traffic safety is secured by the roughness of the coating, namely, by its part not filled with water. So for safe movement at a speed of 80 km/h, the condition Ract ≥ 1 mm must be met. For speeds of 100 and 120 km/h, the conditions Ract ≥ 2 mm and Ract ≥ 2.8 mm must be met. According to the formula (9), the limiting depths of the ruts WDlim were calculated, which ensure safe movement at speeds of 60; 80; 100 and 120 km/h on the surface with the ensured values of the adhesion coefficients indicated in Table 2. The calculation results are given in Table 3. From the analysis of the Table 3 follows that safe movement on a wet smooth surface (R = 0.5 mm) is possible only at low speeds of no more than 60 km/h. Wherein depending on the required value of the adhesion coefficient ϕlim60 = 0.35,
Fig. 2 Dependence of the coefficient of adhesion of a tire with a surface on the speed of movement and the active average height of the roughness protrusions. 1–4—actual coefficient of adhesion ϕ at speed 60, 80, 100 and 120 km/h; 5–8—limiting coefficient of adhesion ϕlimϑ at speed 60, 80, 100 and 120 km/h
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Table 3 Rut severity classification by highway agencies [2] Highway agency
Rut depth limits severity level Low
Medium
High
inch
mm
inch
mm
inch
mm
Pavement Condition Index (PCI) [2, 15]
0.25–0.5
6.3–12.7
0.5–1
12.7–25.4
>1
>25.4
PASER Manual, Asphalt Roads [2, 16]
0–0.5
0–12.7
>1
>25.4
>2
>50.8
Washington State 0.25–0.5 DOT (WsDOT) [2, 17]
6.3–12.7
0.5–0.75
12.7–19.1
>0.75
>19.1
Ohio DOT (OhDOT) [2, 18]
0.125–0.375
3.2–9.5
0.375–0.75
9.5–19.1
>0.75
>19.1
Massachusetts Highway Dept. (CMMPO) [2]
0.25–0.5
6.3–12.7
0.5–1.5
12.7–38.1
>1.5
>38.1
Ministry of Transportation and Infrastructure, British Columbia (MTI BC) [2, 19]
–
3–10
–
10–20
–
>20
California DOT (Caltrans) [2]
Schedule corrections when rut depth > 1 in. (>25.4 mm)
ϕlim60 = 0.40 or ϕlim60 = 0.45, the rut depths should not exceed RDlim 22.1 mm, 14.4 mm and 7,7 mm, respectively. This movement only corresponds to city roads of a certain category. Therefore, the requirements for the roughness of the coatings of country roads in Russia should be recognized as reasonable. On such roads, the average height of the roughness protrusions should not be less than 1 mm. The biggest limiting rut depth corresponds to pavements characterized by an average height of roughness protrusions of 5 mm. On such surfaces, depending on the driving speed and the required coefficient of adhesion, the limit rut depth is 4.1–26.6 mm. When the average height protrusion of the pavement roughness varies within 1.0–5.0 mm, the limit rut depth is from 0 to 26.6 mm.
4 Discussion The developed calculation method makes it possible to limit the rut depth by the limiting value at which the required coefficient of adhesion is ensured at the required speed of movement and given roughness parameters. This allows to ensure the safety of driving on a road surface with a rut filled with rainwater.
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The results of calculating the limit depth of the rut, presented in Table 2 can be compared with the results obtained by other authors. These results are shown in Table 3. From the analysis of the data in Table 3, it follows that in order to ensure safe movement with a low level of severity, road agencies limit the smallest values of the limit depth from 0 mm (PASER Manual, Asphalt Roads) up to 6.3 mm (PCI, WsDOT, CMMPO). Analyzing our data presented in Table 3, it follows that the limit rut depths from 0.1 to 6.3 mm are permissible at high speeds of 100–120 km/h on rough surfaces (R = 1.0–5.0 mm). The biggest values of rut depths of 9.5–12.7 mm, regulated by Table 3 for low severity level according to our Table 3, are permissible at speeds of less than 70 km/h. Table 3 data in comparison with the data in Table 3 take into account more factors. Therefore, the limitations of the rut depth according to Table 2 can be used as a specification of the limit depth of the rut specified in Table 3 for low severity levels.
References 1. Fwa TF (2017) Skid resistance determination for pavement management and wet-weather road safety. Int J Transp Sci Technol 6(3):217–227. https://doi.org/10.1016/j.ijtst.2017.08.001 2. Fwa TF, Pasindu HR, Ong GP (2012) Critical rut depth for pavement maintenance based on vehicle skidding and hydroplaning consideration. J Transp Eng 138(4):423–429. https://doi. org/10.1061/(ASCE)TE.1943-5436.0000336 3. Start RM, Joeng K, Berg WD (1998) Potential safety cost effectiveness of treating rutted pavements. Transp Res Rec: J Transp Res Board 1629:208–213. https://doi.org/10.3141/162 9-23 4. His A, Velin H and Wiklund M (2002) The influence of road condition on traffic safety: data from 1992–1998. VTI meddelande 909. Swedish national road administration 5. Christensen P, Ragnoy A (2006) The condition of the road surface and safety. The importance of rut depth, roughness (IRI) and changes in cross-slope for road safety (TOI Report 840/2006, Transport Economics Institute), Oslo 6. Glennon JC (2015) Roadway hydroplaning – measuring pavement wheel rut depths to determine maximum water depths. Crash forensics motor-vehicle accident investigation and reconstruction services. http://www.crashforensics.com/papers.cfm?PaperID=55 7. Hussan S, Kamal MA, Hafeez I (2018) Modeling and correlating rut depth observed in different asphalt mixture performance tests. Mehran Univ Res J EngTechnol 37(3):553–570. https://doi. org/10.22581/muet1982.1803.10 8. Hu S, Zhou F, Scullion T (2011) Development, calibration, and validation of a new M-E rutting model for HMA overlay design and analysis. J Mater Civil Eng 23(2). https://doi.org/10.1061/ (ASCE)MT.1943-5533.0000130 9. Li Q, Xiao DX, Wang KCP et al (2011) Mechanistic-empirical pavement design guide (MEPDG): a bird’s-eye view. J Mod Transp 19(2):114–133. https://doi.org/10.1007/BF0332 5749 10. Guo X, Timm DH (2016) Automating mechanistic-empirical pavement design calibration studies. In: Aguiar-Moya JP, Vargas-Nordcbeck A, Leiva-Villacorta F, Loría-Salazar LG (eds) The roles of accelerated pavement testing in pavement sustainability. Springer, Cham, pp 309–319. https://doi.org/10.1007/978-3-319-42797-3_20 11. Aleksandrov AS, Dolgih GV, Kalinin AL (2017) Analysis and modeling of process of residual deformations accumulation in soils and granular materials. IOP Conf Ser: Mater Sci Eng 262:1–7. https://doi.org/10.1088/1757-899X/262/1/012004
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12. Aleksandrov AS, Semenova TV, Aleksandrova NP (2016) Analysis of permanent deformations in granular materials of road structures. Road Bridges 15:263–276. https://doi.org/10.7409/rab dim.016.017 13. Yanov DV, Zelepugin SA (2019) Road pavement design using the finite element method. J Phys: Conf Ser 1214:1–8. https://doi.org/10.1088/1742-6596/1214/1/012024 14. Gercog VN, Dolgikh GV, Kuzin NV (2015) Calculation criteria for road pavement evenness. Part 1: substantiating the flatness standards of asphalt pavement. Magazine of Civil Engineering 5(57):45–57. https://doi.org/10.5862/MCE.57.4 15. Aleksandrov AS, Dolgih GV, Kuzin NV (2020) Method of calculating the limiting depth of ruts on the pavement of automobile roads. IOP Conf Ser: Mater Sci Eng 753:052019. https:// doi.org/10.1088/1757-899X/753/5/052019 16. Shahin MY (1994) Pavement management for airports, roads and parking lots, chapman and hall, New York, NY, p 574. https://doi.org/10.1007/978-1-4757-2287-1 17. Walker D, Entine L, Kummer S (2002) Pavement surface evaluation and rating (PASER), asphalt roads. wisconsin transportation information center, Madison, WI. p 29 18. Washington state department of transportation (WsDOT) (1999) Pavement surface condition field rating manual for asphalt pavements. Olympia, Washington. p 72 19. Ohio state department of transportation (OhDOT) (2006) Pavement condition rating system, Columbus, OH 20. Ministry of transportation and infrastructure, British Columbia (MTI BC) (2009) Pavement surface condition rating manual 3rd edition. British Columbia
Investigation of the Conditions for the Occurrence of Rail-Ground Potentials on AC Railways Evgeniy Tryapkin , Ivan Ignatenko , Sergey Vlasenko , Alexander Onischenko , and Natalia Shurova
Abstract Currently, there is a classical idea of current distribution in the rail circuits of 25 kV AC traction networks. However, due to particular complexity of mathematical representation processes occurring in boundary conditions and a variety of interrelated factors, simplified models of traction current flow in rails are considered. In this case, the traction current is considered as induced by contact network—ground circuit. And the role of traction current flowing from train (galvanic traction current) is practically not considered, due to its rapid exit from rail into the ground. However, these methods of representing the path of reverse traction current, as well as the studies and measurements carried out, show a very significant influence of galvanic current in rails on process of forming high rail–ground potentials. The purpose of this study is to analyze causes of the increased rail–ground potential, as well as generalize and describe influencing factors. Understanding these processes will make it possible to develop the most effective technical and organizational measures leading to a decrease in these potentials, and, as a result, an increase in reliability of AC traction power supply system. This article compares the results of mathematical calculations, simulation modeling and direct measurement of interest processes. The problem of increased rail-ground potentials is relevant for the network of electrified railways, on the territory of which heavy and intense traffic is carried out. From the results of earlier measurements, it was revealed that values of rail-ground potentials can reach significant values exceeding 1000 V, and be dangerous both for technical means of accompanying infrastructure and lead to electrical injuries. For these reasons, much attention has been paid to conditions for appearance of high rail-ground potentials. Keywords Electromagnetic compatibility · Railway · Traction · Potential
E. Tryapkin (B) · I. Ignatenko · S. Vlasenko · A. Onischenko · N. Shurova Far Eastern State Transport University, 47 Seryshev Street, Khabarovsk 680021, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_92
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1 Introduction The problem of increased rail-ground potentials is relevant for the network of electrified railways, on the territory of which heavy and intense traffic is carried out [1]. From the results of earlier measurements, it was revealed that values of rail-ground potentials can reach significant values exceeding 1000 V, and be dangerous both for technical means of accompanying infrastructure and lead to electrical injuries [2, 3]. For these reasons, much attention has been paid to conditions for appearance of high rail-ground potentials.
2 Materials and Methods Previously, when directly measuring voltage difference on a section of the rail circuit from flowing current, a nonlinear increase in voltage difference in the rail U = U1−U2 was recorded with an increase in flowing current. The results of calculating the ratio of voltage amplitude to current amplitude are shown in Fig. 1. The figure shows that with an increase in current flowing through the traction network, the ratio of voltage in the traction network to current also increases. This study has identified two main factors for the appearance of high rail-ground potentials. This is increased value of the ratio itself, caused by harmonic composition of current, as well as its nonlinear dependence on current value [4]. It is known from theory of the electromagnetic field that as an electromagnetic wave penetrates into a conducting medium, its attenuation is observed, the speed of which depends on properties of conducting medium, in particular, the specific electrical conductivity and magnetic permeability, as well as frequency of wave oscillations. The penetration depth of wave (thickness of skin layer) δ is estimated by the formula (1): δ=
2 , ω · γ · μst
(1)
where ω—angular speed (ω = 2·π·f), rad/s; f—frequency of electromagnetic wave oscillations, Hz; γ—specific electrical conductivity of medium; μst—static magnetic permeability, Gn/m (μst = 4·π·10–7·μ); μ—relative magnetic permeability of medium; From analysis of formula (1) it follows that thickness of the skin layer decreases with increasing frequency. From this, it follows that the alternating current is distributed unevenly over section of conductor, but flows only through its limited area. The phenomenon of uneven distribution of field over cross-section of a conducting body caused by the attenuation of electromagnetic wave when it propagates into a conducting medium is called the surface effect (skin effect) [4].
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ΔU
A
A V2
V1 1000 m
Fig. 1 A diagram of measurements carried out and a graph of dependence U f(I)
A lot of domestic [5–8] and foreign works [9, 10] have been devoted to study impact of surface effect on the electrical resistance of rails, most of which are based on the results of research, as well as application of the Umov–Poynting theorem. Consider the process of distributing alternating current across conductor section. Figure 1 shows distribution of currents inside a conductor when alternating current flows through it. For a cylindrical conductor, the formula for calculating the electrical resistance at a length of 1 m, taking into account the expression (1), can be represented as (2): Z=
√ 0 2 · b0 · e j · (β0 −β1 −45 ) , δ · π · γ · r · b1
(2)
where r—radius of cylindrical conductor, m; b0 —the module of Bessel functions of first kind zero order; b1 —the module of Bessel functions of first kind first order;
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β0 —the argument of Bessel functions of first kind zero order; β1 —the argument of Bessel function of first kind first order. The active resistance of conductor is real part of the formula (6), and internally inductive resistance is imaginary part: √ 2 · b0 · cos β0 − β1 − 450 , δ · π · γ · r · b1 √ 2 · b0 x = Im Z = · sin β0 − β1 − 450 . δ · π · γ · r · b1
ra = Re Z =
(3)
(4)
Figure 3 shows fragments of experimental curves of dependence active and internal inductive resistance of rails to alternating current with a frequency of 50 Hz on field strength in the rail. Since in order to calculate the resistances, it is necessary to have data on ψ and μst , then from the dependencies ra = f (H) and x" = f (H) presented in Fig. 1 and the joint solution of Eqs. (4) with respect to μst and ψ, the dependence μst = f (H). The current range 0 ≤ I ≤ 420 A corresponds to current range of magnetic field strength from 0 to 680 A/m. Figure 4 shows dependence δ = f (H) for a fixed frequency of 50 Hz, constructed by expression (1) using dependence μst = f (H), presented in Fig. 2. Analyzing the presented dependence, it can be concluded that even at a constant frequency, with an increase in the current value, the thickness of the skin layer of the rail decreases, since the value of μst increases, that is, within the operating range of 5 δ, mm
r
0.2
4
x 0.15
3
δ 0.1
2
0.05
1
0
0 0 40 80 120 160 200 240 280 320 360 400 440 480 520 560 600 640 680
x'', Ohms/km
0.25
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Fig. 2 Dependences of the active (ra ), internal inductive (x") rail resistances and the thickness of the skin layer (δ) on the field strength in the rail
Н, A/m
897
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6
0.5
5
0.4
4
0.3
x
0.2
δ
δ, mm
Fig. 3 Dependence of internal inductive resistance (x"), internal inductance (L") of the rail P50 and thickness of the skin layer (δ) on the frequency of alternating current at H = 35 A/m (21.7 A)
x'', Ohms/km L'', Ohms/km
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3 2 1
0.1
L 0 50 100 150 200 250 300 350 400 450 500 550 600
0 f, Hz
currents in the rails, the electrical resistance of the rail increases with an increase in its magnetization (until the onset of magnetic saturation). To analyze the nature of change in internal inductive resistance of the rail from frequency, we calculate module of the complex resistance, for a given frequency range 0 ≤ f ≤ 600 Hz at H = 35 A/m. Since module of the complex resistance of the rails is related to active and reactive resistances by ratio z p= (ra )2 + (x )2 , 2 the internal inductive resistance of the rails is defined as x = z p − (ra )2 . The internal inductance is defined as quotient of division x by ω. The calculation results are shown in Fig. 3. The curves shown in Fig. 6 show the dynamics of an increase in internal inductive resistance of the rails together with a decrease in thickness of the skin layer with an increase in frequency. Unlike active resistance of the rail, internal inductive resistance increases much more slowly, and internal inductance of the rail decreases. Thus, it can be established that resistance of the rails to alternating current due to the skin effect significantly exceeds resistance of the rails to direct current. For a rail of the P50 brand at a frequency of 50 Hz, the module of total complex resistance at a field strength of 35 A/m is about 3.5 times greater than the resistance of this type of rail to direct current (0.0318 Ohms/km), and at a frequency of about 600 Hz exceeds this indicator by about 12 times.
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Fig. 4 Simulation of current flow in a rail of type R65 a, and graphs dependence of the active b and total c resistance of 1 km of rail, and total resistance d when taking into account the parallel flow of currents
3 Modeling To confirm this factor, a simulation of current flow through the rail [11] was performed in the ELCUT program. The simulation of flow of current different frequency and intensity through the rail R65 and R75 in problem of magnetic field of alternating currents was carried out. In this model, magnetic properties of the rails and their conductivity parameters were taken into account. The results of values of total resistance of the rail from values of total current and frequency are shown in Fig. 4. The obtained dependences do not confirm the previously obtained results of direct measurements nature of the rail resistance from full value of flowing current. Further, the influence of magnetic coupling of the rails on each other was simulated (Fig. 4), as well as magnetic influence of the contact suspension and the roadbed. Consider case of the train situation presented in Fig. 5. The train is located in the middle of section, and consumes the same current 1/2 I from adjacent substations [12]. The reverse traction current is also distributed evenly along the rails towards their substations. The reverse traction network is homogeneous and symmetrical.
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½I
½I
½I
½I
Ik
899
Ik
Fig. 5 Flow diagram of traction and contour currents
satellite Ɵme synchronizaƟon
A1
A2
h=6m
V2
V1
500 m
V3
1323 m
Fig. 6 Scheme of measurements and oscillograms of currents and voltages
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The current in rails and contact suspension leads to appearance of a current loop in the ground Ik. At the same time, due to different removal of contact network and rails, the influence contour of the rails will be stronger. Considering an infinitesimally small section of the rail circuit located directly under the train, it can be seen that two circuits are created in different ones, having opposite direction of current flow. However, in layers of the earth there is no circuit capable of transmitting current for these circuits over a small considered length. Thus, directly under the train, currents of these circuits can be considered infinitely small. When moving away from the train, value of currents begins to increase, gradually reaching a certain saturation value. An increase in current in this circuit leads to a certain decrease in the growth of rail-ground potentials in section of the rail circuit remote from the train. At the same time, magnetic influence of the contact network on the rail, as well as rail circuits, remains unchanged.
4 Experiment To confirm the hypotheses put forward, a number of measurements were carried out on railway sections characterized by an increased frequency of occurrence of high rail—ground potentials. Direct measurements of potentials were made at several connection points, as well as monitoring of currents in rail circuits. For the possibility of implementing direct measurements in rail circuits, a system and a set of devices were developed that allow monitoring of measured parameters at remote points. The system was developed by the authors of this article and is a set of autonomous synchronous recorders that measure and record parameters in a single coordinate axis. Unlike already known systems [13, 14] synchronization of time points is achieved by using an accurate time clock corrected by the satellite navigation system [15]. Voltage monitoring is performed with respect to remote earths located outside the galvanic influence of rail circuits. This system allows measurements to be made on geographically distributed objects in conditions of significant electromagnetic influence of the AC traction network. Let’s consider the results of the control of reverse traction currents in section “A”. The situational scheme is shown in Fig. 6. The graph below shows values of currents and voltages of the rail circuits of recorders. The entire site under consideration is same structure of roadbed. The control was carried out at three points. The measurement results showed that change in the rail—ground potential occurs according to a pronounced exponential law (Fig. 7). At the same time, the value of current in the rail is almost unchanged. This is due to the absence of leakage currents in the rail-ground circuit in the section under consideration. The figure shows the calculation of the nature of the change in the rail-ground potential at a distance from the train. In general, the data shown confirm the previously made conclusions about the nature of the influence of current circuits in the ballast prism and the ground on the appearance of potentials in the rail circuit.
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U, V 986
U1
U2 U3
0.5km
1.823km
l, km
Fig. 7 Characteristics of change in maximum rail–ground potential (Umax) from length of the rail track
5 Conclusions Based on the above material, it is possible to judge the impact on the rail-ground potential of various structural features of the tracks. So, along with the height and conductivity of the ballast, and the presence of artificial structures at the base of the track, the presence of steel reinforcement in the construction of reinforced concrete sleepers also affects. Thus, the contours of the magnetic field of rails pass through the steel reinforcement of sleepers, which simultaneously leads to an increase in the magnetic influence of rail chains, and a decrease in the influence of rail—ground. These factors are also capable of increasing the growth potential in rail circuits. A series of experiments conducted in other areas with a changing ballast height and the presence of structures in the path of the path confirm these conclusions. The results obtained open up new ways to reduce the rail-ground potentials. The solutions may consist not only in ways of removing traction current from rail circuits or influencing magnetic processes in rails. The solution may also be to take into account the inductive coupling between the contours in the ballast and the rail track. Consideration of this direction can be applied when designing the structures of the base of rail transport, and when introducing technical means to reduce the increased potential of rail—ground by creating current circuits. For example, the use of rings made of conductive materials on reinforced concrete sleepers creates a current in their circuit under the influence of a magnetic flux in the circuit, thereby creating its own magnetic flux in the opposite direction. We also consider the creation of artificial contours in the ballast between the upper layer and the ground to be a promising direction, which, along with facilitating the draining of traction current, will ensure the flow of contour currents in the ballast. Also, the applied conclusions can contribute to a condition for reducing the increase in potential in rail chains when used without ballast traction networks. Acknowledgements We Express our deep gratitude to all our colleagues, authors of the works, familiarization with which greatly helped us in conducting research and obtaining relevant results, although they may not agree with all our interpretations and conclusions.
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References 1. Ogunsola A, Sandrolini L, Mariscotti A (2015) Evaluation of stray current from a dc electrified railway with integrated electric-electromechanical modeling and traffic simulation. IEEE Trans Ind App 51(6):5431–5441. https://doi.org/10.1109/TIA.2015.2429642 2. Zalesova OV (2021) Determination of electromagnetic influence of 25 kV AC electric traction network on 10 kV high-voltage overhead line. J Phys: Conf Ser 2096:012078. https://doi.org/ 10.1088/1742-6596/2096/1/012078 3. Lucca G (2019) Influence of railway line characteristics in inductive interference on railway track circuits. IET Sci Meas Technol 13:9–16. https://doi.org/10.1049/iet-smt.2018.5021 4. Ignatenko I, Tryapkin E, Vlasenko S, Onischenko A, Kovalev V (2020) Impact of return traction current harmonics on the value of the potential of the rail ground for the ac power supply system. In: Popovic Z, Manakov A, Breskich V (eds) VIII International scientific siberian transport forum, vol 1115. Advances in Intelligent Systems and Computing. Springer, Cham, pp 117–127. https://doi.org/10.1007/978-3-030-37916-2_13 5. Isaicheva AG, Basharkin MV, Zolkin AL, Malikov VN, Rudnev SG (2021) Application of machine learning in determination of the permissible level of traction current asymmetry. AIP Conf Proc 2402:070006. https://doi.org/10.1063/5.0071644 6. Tarasov EM, Teplyakov VB, Gumennikov VB et al (2017) On ensuring invariance in problems of control of rail-line conduction. Russ Elect. Eng 88:105–108. https://doi.org/10.3103/S10 68371217030166 7. Andronchev IK, Tarasov EM, Bulatov AA et al (2020) A Technique for Diagnosis of the Resistance of Conductive Rail Track Joints. Russ Elect Eng 91:149–152. https://doi.org/10. 3103/S1068371220030025 8. Mariscotti A (2011) Induced voltage calculation in electric traction systems: simplified methods, screening factors and accuracy. IEEE Trans Intell Transp Syst 12(1):201–210. https:// doi.org/10.1109/TITS.2010.2076327 9. Mirzaei M, Ripka P (2018) Analysis of material effect on rail impedance. In: 53rd International universities power engineering conference (UPEC), 18319950 10. Mariscotti A (2021) Impact of rail impedance intrinsic variability on railway system operation, EMC and safety. Int J Elect Comput Eng (IJECE) 11(1):17–26. https://doi.org/10.11591/ijece. v11i1 11. Enshaeian A, Rizzo P (2021) Stability of continuous welded rails: A state-of-the-art review of structural modeling and nondestructive evaluation. In: Proceedings of the Institution of Mechanical Engineers. Part F: Journal of Rail and Rapid Transit. vol 235, issue 10, pp 1291– 1311. https://doi.org/10.1177/0954409720986661 12. Li VN, Demina LS, Vlasenko SA, Tryapkin EY (2020) Assessment of the impact of the electromagnetic field of the catenary system on crack formation in reinforced concrete supports. Conf Ser: Mater Sci Eng 918:012118. https://doi.org/10.1088/1757-899X/918/1/012118 13. Sopel M, Stasyuk O, Kuznetsov V, Goncharova L, Hubskyi P (2021) Regina computer system for intelligent monitoring, diagnostics, and management of railway power supply systems. Diagnostyka 22(4):77–88. https://doi.org/10.29354/diag/143744 14. Andrusca M, Adam M, Dragomir A, Lunca E (2021) Innovative integrated solution for monitoring and protection of power supply system from railway infrastructure. Sensors 21:7858. https://doi.org/10.3390/s21237858 15. Tryapkin EY, Keino MY, Protasov FA (2016) Synchronous phase measurements in the automated monitoring system of railway power supply facilities. Russ Elect Eng 87:110–112. https://doi.org/10.3103/S1068371216020176
Conditions for Compliance Lewis Relationship When Air Flow is Contact with Ice Elena Tarasova , Vladimir Chernenkov , and Anton Eskin
Abstract The purpose of the article is to check the observance of the theoretical value of the ratio of the heat transfer and moisture transfer coefficients in schemes with direct contact of air flow and ice. Such heat and mass transfer is observed in the seasonal accumulation of natural sources of cold for air-conditioning. Therefore, it is necessary to know heat and mass transfer criteria for the engineering design of cold storages. A theoretical analysis of the observance of the constancy of the heat transfer and mass transfer coefficients for different options of the flow of the cooling process of the air flow in schemes with direct contact of air flow and ice has been carried out. Depending on the option of the process and the method of analysis, possible conditions for observing the similarity of heat exchange and mass exchange processes have been identified, however, in most cases, the processes are not similar. The results of theoretical analysis have been compared with the results of modeling heat exchange and mass exchange processes in the experimental installation. The data obtained during the physical experiment shows that the ratio of heat transfer and moisture transport coefficients is not equal to the theoretical value obtained by Lewis for liquid evaporation. The similarity of heat and moisture transfer processes is not observed over the entire experimental range of changes in the partial pressure of water vapor. This shows the necessarity to improve the theory of heat and mass exchange of air flow with natural sources of cold used for accommodation air conditioning systems. Keywords Cold accumulation · Heat exchange (transfer) · Moisture exchange · Conditioning · Thermodynamic parameters
1 Introduction One of the technologies that allow energy saving in air conditioning systems is the seasonal accumulation of natural cold sources [1–15]. In this case, schemes with E. Tarasova (B) · V. Chernenkov · A. Eskin Far Eastern Federal University, 10 Ajax Bay, Russky Island, 690922 Vladivostok, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_93
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direct contact of cooled airflow with snow or ice are often used [10, 11, 15]. A layer of melt water forms on the ice surface when the warm air is blowing. Therefore, an important issue for this technology is exchange of heat and moisture at the air–water boundary in the cold storage. The current research aims to test a hypothesis of the observance of the similarity of processes of heat exchange and mass exchange in cold storages. In air conditioning, the processes of heat and moisture exchange of air with water are often encountered, primarily in the contact devices for humidifying and cooling air. The similarity criterion is the ratio that connects the coefficients of heat transfer and mass transfer when the air flow is in contact with water. This relationship was first obtained by Lewis (Lewis WK The Evaporation of a Liquid into a Gas. ASME Transaction, vol 44, 1922). The ratio value is constant for iso-enthalpy humidification: ∝ = cp, (1) σ ; σ —mass transfer coefficient related to where ∝—heat transfer coefficient mW 2 ·K kg the head of moisture content m 2 ·s ; c p —specific isobaric heat capacity of humid J . air kg·K
2 Materials and Methods In order to describe heat and mass transfer when the air flow comes into contact with ice, it is necessary to analyze the theory of similar processes. The air comes into contact with a thin film of water on the surface of natural sources of cold— snow and ice. Contact air and water often occurs in the central air-conditioning. In humidifiers—irrigation chambers, the air flow comes into contact with water droplets. To test the hypothesis of compliance with the similarity of heat and mass transfer processes in cold storage, two versions of theoretical concepts were considered and experimental modeling was carried out. Concept 1. The transfer of heat and mass in—irrigation chambers based on the theory of similarity—the Kirpichev-Gukhman theorem (Kokorin O.Ya. (1978) Air conditioning installations. Basics of calculation and design. “Mechanical engineering” (in Russian)). The similarity of changes in the temperature and partial pressure fields is considered. Also, as shown by experimental studies (Gvozdkov A.N. (2014) Changing lewis ratio in processes with reduced enthalpy applied to contacting units of heating, ventilation and air conditioning systems. Privolzhskiy nauchnyy zhurnal 4:151–157. (in Russian)), the value of the Lewis relationship also depends on the coefficient of irrigation of contact irrigation chambers.
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Fig. 1 Various combinations of the initial parameters of air and melt water for joint processes of heat and mass transfer in ice storages on diagram Ramzin—Mollier h—x of wet air
Various combinations of the initial air parameters and changes in the temperature and partial pressure fields typical for heat and moisture exchange processes in natural cold accumulators are considered in Fig. 1. It is assumed that the final air parameters are unchanged and correspond to saturated air at a temperature of 0 °C (point A), and the initial moisture content is consistently increased. The features of the joint heat and mass exchange processes will changing with changing initial air parameters. Two conditions of single-valuedness are considering. First is the correspondence of geometrical equality of boundaries of heat and mass flows. Second is the compliance with the similarity of changes in the temperature pressure and partial pressures on the contact surface in the ice storage. Concept 2. Berman L.D. gives the conditions under which the Lewis ratio is satisfied, depending on the volume (molar) gas content in the mixture of εr and the dimensionless difference in the partial pressures of the vapor πq (Berman L.D. On the validity of the analogy between heat and mass transfer and the Lewis ratio for air conditioning and cooling towers. Kholodil’naya tekhnika—1974. № 2. 34–37 p. (in Russian)). The boundaries of the region for which the approximate analogy between heat and mass transfer is valid are determined by the ratio: Nu D Nu ≈ ≈ 1, Nu I Nu D I
(2)
where Nu , Nu D —the thermal and diffusion Nusselt number, I—index in the absence of the influence of the transverse mass flow on the velocity distribution of the vapor– gas mixture and heat transfer and semipermeability of the interface to mass transfer P (the existence of an analogy); εg = Pg —volume (molar) gas content in the mixture;
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v πq = P —a dimensionless difference in partial pressures; Pg —partial pressure ρ of gas (water vapor); P—mixture pressure; P v - change in partial pressure during heat exchange.
In the case of evaporation, the ratio (2) is observed at: – –
εg πq εg πq
≥ 9, εg ≥ 0.96—allowable error 10%; ≥ 9, εg ≥ 0.92—allowable error 15%.
In the case of condensation: ε
– εg ≥ 0.85, | πgq | ≥ 2.3—allowable error 10%; ε – εg ≥ 0.85, | πgq | ≥ 3.0—allowable error 15%. The ratio (2) was analyzed for the case of heat and mass transfer in the cold storage. It is assumed that the final air parameters are unchanged and correspond to saturated air at a temperature 0 °C, the initial partial pressure of water vapor in the air flow (Pv1) is sequentially increased from 0 to 5.4, while the value of εg varies from 0 to 0.0534. Conditions that are suitable for heat and moisture exchange in the ice ε ε storage: πgq ≤ 3—for condensation and | πgq | ≤ 10—for evaporation. In this case, the equality: −1 εg Nu D Nu = εgb = 1 − 0, 6 × ( − 0, 4) Nu I Nu D I πq
(3)
where εgb —volume (molar) gas content in the mixture at the phase boundary. Experimental modeling. Figure 2 shows a diagram of the experimental setup [16]. In a glass container with dimensions 880 × 285 × 480 mm, there are two rectangular air diffusers and a container with ice. The ice has a phase transition temperature of—0 ºC. The container is thermally insulated with 50 mm thick expanded polystyrene panels. The air flow is supplied by an air handling unit, the air passes through a glass container. Heat and mass exchange with ice occurs, then air leaves the unit through the second air duct. Measurements of the air parameters at the inlet and outlet of the container are carried out with an IVTM-7 M thermohygrometer with an IPVT-0 converter connected to it and an AV9201 digital hot-wire anemometer. The air velocity inside the container ϑc varied in the range from 0.08 to 0.37 m/s, which corresponds to the numerical values of the Reynolds criterion Re from 2950 to 13,050. The average moisture content of the air flow dm varied from 1.8 to 3.5 g/kg. It is accepted that mass transfer is determined by molar transfer and the Merkel equation is valid. The mass transfer coefficient σ was calculated using the heat transfer equation: d Q = σ (Iair − Iw )d F
(4)
where Iair —enthalpy of air flow; Iw —enthalpy of saturated air at the phase interface; F—the area of the interface between the phases.
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Fig. 2 Experimental setup [16]
3 Results Analysis of the first concept. For process 1-A on Fig. 1, the ratio of the initial air parameters is such that this ensures adiabatic humidification of air. The boundaries for the heat and mass fluxes are the same, and the change in the temperature pressure is similar to the partial pressure along the contact surface (Fig. 3). Lewis relationship is observing as a consequence of the fulfillment of all similarity conditions.
Fig. 3 Change in temperature heads from t1 to t2 a and partial pressures P1 to P2 b over the contact surface of air and melt water with temperature tw and partial pressure of saturated air Pw in the processes of adiabatic air humidification
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Fig. 4 Change in temperature heads from t1 to t2 a and partial pressures P1 to P2 b over the contact surface of air and melt water with temperature tw and partial pressure of saturated air Pw in the processes of cooling and humidifying air with a decrease in its enthalpy
In process 2-A on Fig. 1, conditions are observed when the process of cooling and humidifying the air takes place with a simultaneous decrease in its enthalpy. The peculiarity of this regime is that evaporation processes cause the removal of heat from thawed water and contribute to an intensification of the perception of apparent heat from the air Consequently, the equality of the geometric boundaries of the heat and mass fluxes is violated, and the Lewis relationship of the mean over the transfer coefficient surface will be greater than the theoretical (Fig. 4). For process 3-A on Fig. 1, this ratio of the initial parameters is characteristic, which ensures the flow of the air cooling process without changing its partial pressure. The absence of a mass flow causes non-observance of both similarity conditions (Fig. 5). The mass transfer coefficient tends to zero, and the Lewis relationship to infinity. In practical conditions, the complete absence of a mass change is impossible, since the value of the moisture content of the fresh air varies with time. Process 4-A on Fig. 1 meets the conditions when the processes of cooling and dehumidification of air with a decrease in enthalpy are observed. A feature of this mode is that the condensation processes cause the flow of heat to the melt water and reduce the perception of sensible heat from the air. Consequently, the equality of the geometric boundaries of the heat and mass fluxes is violated and the geometric boundaries for the heat and mass fluxes are not the same, and the change in the temperature heads and partial pressures over the contact surface does not have a similar character (Fig. 6). In this mode, the Lewis relationship will be less than the theoretical value, but greater than zero. Analysis of the second concept. Throughout the given range of variation of Pv1, the volume content of the gas in the mixture is much less than unity, which indicates a non-observance of the analogy between heat and mass change. The results of the calculation from expression (3) are shown in Fig. 7. At a partial pressure Pv1 from 0.438 to 0.583 (condensation) and from 0.583 to 0.647 (evaporation), the value of the ratio of the volumetric (mole) gas content in the
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Fig. 5 Change in temperature heads from t1 to t2 a and partial pressures P1 to P2 b over the contact surface of air and melt water with temperature tw and partial pressure of saturated air Pw in air cooling processes at constant moisture content
Fig. 6 Change in temperature heads from t1 to t2 a and partial pressures P1 to P2 b over the contact surface of air and melt water with temperature tw and partial pressure of saturated air Pw in the processes of cooling and dehumidification
mixture εg to the dimensionless difference of the partial pressures of the vapor πq is more than 3 and 10, respectively, and does not satisfy the conditions for using the Eq. (3). Experimental modeling. As a result of experimental modeling, data on changes in the thermal and humidity characteristics of the air flow upon contact with the ice surface were obtained, which are shown in Table 1. The relationship ∝σ varied in the range from 0.96 to 1.16.
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Fig. 7 Dependence of the ratio of the: a—thermal and diffusion Nusselt numbers Nu Nu I
Nu Nu I
on the partial
on the ratio of the volume (molar) gas pressure Pv1; b—thermal and diffusion Nusselt numbers gas content in the mixture εg to the dimensionless difference in the partial vapor pressures πq during condensation (1) and evaporation (2) Table 1 Results of experimental modeling of heat and mass transfer process in ice storage ∝ kJ σ , kg·K
ϑc , m/s
dm , g/kg
cp,
2955
0.08
3.63
1.012
1.16
2948
0.08
1.86
1.008
0.98
6364
0.18
3.37
1.011
1.08
Re
kJ kg·K
7381
0.21
1.82
1.008
0.96
12,027
0.34
3.28
1.011
1.01
13,063
0.37
1.82
1.008
1.00
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4 Discussion Testing the hypothesis of compliance with the similarity of heat and mass transfer processes in ice storage facilities showed the lack of similarity in the experimental study and in most cases of theoretical analysis. The analysis of first concept showed that the value of relation (1) can vary within wide limits, depending on the initial heat and humidity parameters of the air flow. The theoretical value of the Lews relationship is observed only with adiabatic air humidification; in all other cases, there is no equality of heat and mass fluxes. The analysis of second concept revealed non-observance of the Lewis relationship during heat and mass transfer between air and ice in the entire range of variation of the partial pressure of water vapor in the air flow—from 0 to 5.4. Experimental modeling. Based on the experimental data, in the range of Reynoldtz numbers from 2950 to 13,050, the values of the ∝σ relationship were obtained, which are close to the theoretical values of the specific isobaric heat capacity of humid air. This means that in the degree of accuracy of measuring instruments, relationship (1) is observed. It was also revealed the need for experimental studies with an average moisture content of the air flow of more than 3.5 g/kg, since it is required to check the effect of the moisture content of the air flow on the heat and moisture exchange process.
5 Conclusions 1. Based on the results of theoretical research, it was concluded that the values of the ratio of the coefficients of heat transfer and moisture transfer upon contact of the air flow with ice can vary widely depending on the chosen theoretical model of heat and moisture transfer. 2. Experimental modeling has shown that in the range of Reynoldtz numbers from 2950 to 13050 and the average moisture content of the air flow dm from 1.8 to 3.5 g/kg, the processes of heat and mass transfer in ice storage facilities are similar.
References 1. Yan C, Shi W, Li X, Wang S (2016) seasonal cold storage system based on separate type heat pipe for sustainable building cooling. Renew Energy 85:880–889. https://doi.org/10.1016/j.ren ene.2015.07.023 2. Skogsberg K (2005) Seasonal snow storage for space and process cooling. Doctoral thesis, Luleå University of Technology, Sweden. http://ltu.diva-portal.org/smash/get/diva2:990071/ FULLTEXT01.pdf
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3. Kumar V, Hewage K, Haider H, Sadiq R (2017) Sustainability evaluation framework for building cooling systems: a comparative study of snow storage and conventional chiller systems. Clean Tech Environ Policy 19:137–155. https://doi.org/10.1007/s10098-016-1198-8 4. Yan C, Shi W, Li X, Zhao Y (2016) Optimal design and application of a compound cold storage system combining seasonal ice storage and chilled water storage. Appl Energy 171:1–11. https://doi.org/10.1016/j.apenergy.2016.03.005 5. Hamada Y, Nagata T, Kubota H, Ono T, Hashimoto Y (2012) Study on a snow storage system in a renovated space. Renew Energy 41:401–406. https://doi.org/10.1016/j.renene.2011.11.012 6. Nordell B, Skogsberg K (2007) The sundsvall snow storage-six years of operation. Therm Energy Storage Sustain Energy Consum 234:349–366. http://ltu.diva-portal.org/smash/get/ diva2:993105/FULLTEXT01.pdf 7. Kumar V, Hewage K, Haider H, Sadiq R (2016) Techno-economic performance evaluation of building cooling systems: a study of snow storage and conventional chiller systems. Cold Reg Sci Technol 130:8–20. https://doi.org/10.1016/j.coldregions.2016.07.004 8. Persson J, Westermark M (2013) Low-energy buildings and seasonal thermal energy storages from a behavioural economics perspective. Appl Energy 112:975–980. https://doi.org/10.1016/ j.apenergy.2013.03.047 9. Yang T, Zhang X, Zhou B, Zheng M (2013) Simulation and experimental validation of soil cool storage with seasonal natural energy. Energy Build 63:98–107. https://doi.org/10.1016/j. enbuild.2013.03.019 10. Hamada Y, Nakamura M, Kubota H (2007) Field measurements and analyses for a hybrid system for snow storage/melting and air conditioning by using renewable energy. Appl Energy 84(2):117–134. https://doi.org/10.1016/j.apenergy.2006.07.002 11. Nordell B (2015) 8 - Using ice and snow in thermal energy storage systems. Adv Thermal Energy Storage Systems. Methods Applications Woodhead Publish Ser Energy, pp 187–200. https://doi.org/10.1533/9781782420965.2.187 12. Hamada Y, Kubota H, Nakamura M, Kudo K, Hashimoto Y (2010) Experiments and evaluation of a mobile high-density snow storage system. Energy Build 42(2):78–182. https://doi.org/10. 1016/j.enbuild.2009.08.012 13. Yan C, Wang F, Pan Y, Shan K, Kosonen R (2020) A multi-timescale cold storage system within energy flexible buildings for power balance management of smart grids. Renew Energy 161:626–634. https://doi.org/10.1016/j.renene.2020.07.079 14. Hamada Y, Nagata T, Kubota H, Ono T, Hashimoto Y (2011) Development of an ice container system for temporary space cooling. Cold Reg Sci Tech 68(3):106–112. https://doi.org/10. 1016/j.coldregions.2011.06.001 15. Morofsky E (2007) History of thermal energy storage. In: Paksoy HÖ (ed) Thermal energy storage for sustainable energy consumption. Springer Netherlands, Dordrecht, pp 3–22. https:// doi.org/10.1007/978-1-4020-5290-3_1 16. Tarasova E, Shtym A, Kobzar A (2021) Heatmass Transfer in Seasonal Natural Cold Storage Facilities for Air Conditioning Systems. In: Mottaeva A (ed) Proceedings of the XIII International Scientific Conference on Architecture and Construction 2020: Commemorating the 90th anniversary of Novosibirsk State University of Architecture and Civil Engineering. Springer Nature Singapore, Singapore, pp 426–434. https://doi.org/10.1007/978-981-33-6208-6_41
Approximate Solution of the Heat Transfer Equation as a Function of the Transfer Potential Coefficient Natalia Parfentieva , Marina Panfilova , Vladimir Konovalov , and Soniya Efremova
Abstract The paper considers the possibility and advantages of solving a nonlinear heat transfer equation when applying the comparison theorem and the BubnovGalerkin method, in fact the two approximate methods of solution are applied. Solutions for various dependences of transfer coefficients on potentials are presented, and a comparison with the results of numerical experiment is made. It shows the efficiency of this method and the possibility to use it for engineering problems and to evaluate the physical meaning of the numerical solution. Since the comparison theorem usage allows determining the range of possible values of the sought quantity, it may be widely used when evaluating the correctness of both the numerical solution and the approximate solution obtained by different methods. The method presented in this paper is efficient for a wide range of problems that includes both determining potential distributions in a semi-infinite domain and finite-dimension domain and, in a more complicated case, determining temperature distributions during phase transformations (Stephan’s problem) and calculating moisture fields. Another interesting case is the example of calculating the moisture content of a material by approximate methods, given in the article. Keywords Potential · Dynamic field · Boundary conditions · Heat transfer equation · Approximate methods
1 Introduction Modern human society makes extensive use of the heat transfer properties of various materials for its existence. Starting from water heating [1], heat treatment of food and products [2], waste decontamination [3], warm room fabrication [4], industrial N. Parfentieva · M. Panfilova National Research Moscow State University of Civil Engineering, 26, Yaroslavskoe Shosse, Moscow, Russia V. Konovalov (B) · S. Efremova Penza State Technological University, 1A/11, Pr. Baydukova/Gagarina Street, Penza, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_94
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production [5, 6] and other modern computer and nanotechnology [7, 8]. The energy transfer and diffusion within bodies [9], at body junctions [10], in fluid media [11], at energy source [12] and phase transitions [13], etc. are differentiated. Both increasing heat transfer [14] and decreasing it [15] are considered. The calculation and modelling of heat transfer to determine the properties and state indicators of substances during material operation is of known complexity and interest. In the work [16] multidimensional thermal structures in unsteady stationary models of heat and mass transfer with nonlinear thermodiffusion coefficient are considered. The question of classical Lyapunov steady-state solutions is investigated. The existence of boundary and internal transition layers as stationary thermal structures is taken into account. The authors of the work [6] consider particle behaviour and heat transfer realized in a rotary kiln on the basis of coarse-grained discrete element method. To solve this problem the Hertz-Mindlin contact force, rolling friction and heat transfer conductivity between particles are determined. A simulation of this process is carried out. In the work [7] a computational method for fast optimal thermal calculation of anisotropic multilayer structures with discrete heat sources is proposed. The calculation is based on the use of expressions based on Fourier decomposition series, which are proposed to solve the stationary anisotropic Laplace dependence. For conditions related to geothermal energy at shallow depths, sustainable construction, renewable energy sources and energy efficiency, the authors [9] carried out the prediction of soil temperature profiles with thermal conductivity based on the Fourier series equation. The main problem was an analytical solution based on environmental factors. The developed simulator improves the calculation accuracy. The determination of unsteady temperature fields, distribution of pollutant concentrations and pressure during fluid filtration is of great importance. The thermal conductivity equation is used to solve many problems under various initial and boundary conditions, it allows determining various physical quantities and then unsteady thermal flows, particle fluxes and flow rates of filtered liquid depending on time, which is important for solving many engineering problems. The aim of the research is to compare the solution of the material heat transfer equation by analytical and approximate methods.
2 Methods and Materials Research methodology includes theoretical analysis of obtained expressions and comparative verification of calculation results by analytical and approximate methods. The derivation of heat transfer equation is based on conservation laws— thermal and material balance equation, transfer laws—Fourier, Fick, Darcy laws, mathematical form of which is the same: q = −k · grad, where is the unsteady potential (temperature, pressure, etc.), q is the heat (substance) flow per unit time through a cross-section with an area of one, and k is the transfer coefficient. The
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minus indicates that, for example, in the process of diffusion the mass transfer takes place in the direction of decreasing concentration. Of particular interest for practice are the solutions when transfer coefficients are functions of the potentials themselves. In this case, we come to necessity of solving a non-linear equation, which presents difficulties both for analytical solution, and for solution by numerical methods, at application of which results may be obtained with large errors. This paper shows how approximate methods may be successfully used, such as the Bubnov-Galerkin method, which provides simplifications for solving nonlinear equations and is shown to be sufficient to retain one term of the approximating series. The calculation was carried out using the Labview graphical programming system, which has developed data representation systems and allows both approximate formulae and equation solving calculations to be carried out.
3 The Results of the Studies General statement of the problem: It is required to determine values of potential (temperature, pressure, concentration) at given boundary and initial conditions— (x, t) under the dependence of the coefficient defining the transfer process κ(). To do this, a non-linear equation should be solved: ∂ ∂ ∂ κ() , = ∂t ∂x ∂x
(1)
where (x, t)—dimensionless function: p − p0 T − T0 n − n 0 (x, t) = , , pc − p0 Tc − T0 n c − n 0 where: p, T and n—pressure, temperature and concentration, respectively; p0 , T0 and n0 —pressure, temperature and concentration at t = 0, pc , T c and nc —values of unsteady potentials at the boundary x = 0. The initial and boundary conditions are of the form (we consider the problem in a semi-infinite domain): (x, 0) = (∞) = 0, (0, t) = 1.
(2)
We consider several cases of dependence of the transfer coefficients: 1. case: κ() =
κ0 1 − α
(3)
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We do the conversion and proceed to the new function P() =
κ()d =
1 d = κ0 ln(1 − α) 1 − α
(4)
The Eq. (1) is converted to the form κ0 ∂ 2 P ∂P , = P 2 e ∂x ∂t
(5)
solved under the conditions P|x=0 = ln(1 − α) = A ≤ 0, P|t=0 = P|x→∞ = 0. In order to determine the desired function, the Eq. (5) must be solved. If the equation describing the potential field is: a(u)
∂u ∂ 2u = 2 ∂x ∂t
(6)
then by solving two linear equations a1
∂ 2u1 ∂ 2u2 ∂u 1 ∂u 2 a2 2 = , = 2 ∂x ∂t ∂x ∂t
where a1 and a2 —the minimum and maximum values of the coefficient a(u), we obtain the time and coordinate dependencies. Then the solution of the Eq. (6) under appropriate boundary and initial conditions at any point of the medium and at any time is within u 2 ≥ u ≥ u 1 . The solutions to the equations will be written in the form: √ u 1 = ln(1 − α) 1 − er f 1 − αξ , u 2 = ln(1 − α)(1 − er f ξ), ξ = 2√xa0 t .
(7)
We pay attention to the last expression, where ξ—is a dimensionless quantity and the unsteady potentials are a function of this quantity. When constructing an approximate solution of the heat transfer equation, this variable is often taken as the basis of dependence. Thus, it can be stated, according to the comparison theorem, that the solution of the Eq. (2) will lie between the quantities calculated by formulae (4). If we plot the dependency graphs P (x, t), we obtain the area within which the values of the desired function lie. By doing an inverse transformation, we obtain possible values of the required potential (temperature, pressure or concentration)
Approximate Solution of the Heat Transfer Equation …
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Θ 1
0.8
2
0.6 0.4 0.2 0
1
2
ξ
Fig. 1 The dependencies from the parameter ξ at α values: (1)—0.8; (2)—0.98
lying in the range √ of 1 to 2 . An approximate solution can be obtained using the formula np = 1 2 . Figure 1 shows the graphs of the dependence on the dimensionless parameter ξ, calculated by the approximate formula (dashed line) and by numerical methods (solid line). It is evident from the figure that the solutions begin to coincide with increasing values ξ. 2. The dependence (Fig. 3) is of great interest for practice. We are interested in the linear part of this relationship described by the equation: κ() = k0 (1 − α),
(8)
in case 1 to temperature values of 300° and in case 2—to 600°. This characteristic of the dependence of the thermal transfer coefficient is characteristic of minerals and rocks. For this case: P() = κ0 (1 − α)2 . The equation for this function is as follows: √ ∂2 P ∂P . κ0 P 2 = ∂x ∂t
(9)
The boundary conditions: P|x=0 = (1 − α)2 , P|t=0 = P|x→∞ = 1. Just as in the first case, find solutions of the two linear equations at the maximum and minimum values of the coefficients, and then make the inverse transition to the desired function. The approximate solution is obtained as the arithmetic mean of the two solutions (Fig. 2).
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1 2
10 5 0
80
40
Τ,°C
Fig. 2 Temperature dependencies of the thermal transfer coefficient: 1—granite, 2—basalt
Θ 1.0 0.8
1 2
0.6 0.4 0.2 0
0.2
0.4
0.6
0.8
1.0
1.2
ξ
Fig. 3 The dependence on ξ in the case of linear dependence κ(): 1—approximate solution by comparison theorem; 2—approximate solution by the Bubnov-Galerkin method
In this case we also obtained solution of the Eq. (1) by Bubnov-Galerkin method when introducing penetration depth: 2 1 , = 1− √ 2 10Mξ where M=
1 3 − α. 3 5
Figure 3 shows the graphs of the dependence on the dimensionless parameter ξ, plotted using two approximate formulas found by using the comparison theorem and the Bubnov-Galerkin method for the value = 0.24. We see that the solutions practically coincide.
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3. A similar method can be used to solve the problem of the temperature field in a medium in the presence of convective heat transfer. The nonlinear equation in this case is of the form: ∂ ∂ ∂ ∂ = κ() −β (10) ∂t ∂x ∂x ∂x The dependence is taken as (8): κ() = κ0 (1 − α). Substituting as we did in example 2, we obtain the equation √ ∂2 P ∂P ∂P = κ0 P 2 − β ∂x ∂x ∂t Under boundary conditions: P|x=0 = (1 − α)2 , P|t=0 = P|x→∞ = 1. By solving the two linear equations, with a maximum and a minimum coefficient at the second derivative and by making a backward transition, we find the region of possible values of the desired potential. 4. A similar method of solution has been used in solving the problem in the bounded domain in the case where there is no flow at one end and the value of the potential is given at the other end. The initial and boundary conditions are as follows: (x, 0) = 0, (l, t) = 1, ∂ = 0. ∂ x x=0
(11)
The exact solutions to the equation have the form: ∞
(−1)n+1 P1 = (1 − α)2 + π4 1 − (1 − α)2 2n−1 n=1
κ0 π2 (2n−1)t (2n−1)π x cos ×ex p − 4l 2 2l ∞
(−1)n+1 2 4 P2 = (1 − α) + π 1 − (1 − α)2 2n−1 n=1
2 (2n−1)t cos (2n−1)πx ×ex p − κ0 (1−α)π 4l 2 2l
The approximate solution of the Eq. (10) according to the Bubnov-Galerkin method is: κ0 t 2
Pnp1 = (1 − α)2 − 45 e−2,5 l 2 1 − xl 2 1 − (1 − α)2 κ0 (1−α)t 2
Pnp2 = (1 − α)2 − 45 e−2,5 l 2 1 − xl 2 1 − (1 − α)2
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1 2 1 2
0.75
0.50
0.5
0
1.0
Fo
Fig. 4 The dependence of functions P1,2 at x = 0 on dimensionless parameter: 1—the exact solution of the linear equation; 2—the approximate solution by the Bubnov-Galerkin method
Figure 4 shows a comparison of the dependencies of the function P at x = 0 on a dimensionless parameter: Fo =
κ0 t (Fourier parameter). l2
As can be seen from Fig. 4, the dependence curves calculated by the exact and approximate formulas coincide quite well. The above examples of solutions to the non-linear heat transfer equation show the possibilities of applying this method to a wide class of problems.
4 Conclusion The studies of the possibility of using the mentioned approximate methods for solving problems with several types of dependence of the transfer coefficient on the potential expressed by different functions based on experimental curves have shown good agreement with the values found by numerical methods. The proposed comparison theorem solution method provides an approximate analytical solution in the cases when exact solutions are difficult or even impossible and only numerical methods should be used. The use of the comparison theorem is important in evaluating the correctness of numerical solutions. According to the obtained solutions, we can obtain expressions for the flows, which allow us to draw conclusions, to study the dependencies on various quantities, which is important in practice. This method combined with the Bubnov-Galerkin method provides simple formulas for the calculation of unsteady fields. Linearisation of equations by the proposed method can also be used in obtaining solutions by numerical methods.
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References 1. Tutov ND, Avrorov VA (2017) On a power-saving method of heating fluids in an industrial tank without mechanical stirring. Chem Pet Eng 52:740–742. https://doi.org/10.1007/s10556017-0262-5 2. Tutov ND, Avrorov VA (2017) Development of an energy-saving cylinder drying machine for dispersed moist materials. Chem Pet Eng 52:743–745. https://doi.org/10.1007/s10556-0170263-4 3. Kurochkin AA, Frolov DI, Zimnyakov VM (2021) Extrudate dehydration rate increase by modernization of the extruder vacuum chamber. IOP Conf Ser Earth Environ Sci 640:072018. https://doi.org/10.1088/1755-1315/640/7/072018 4. Suwansaard A, Kongpun T, Khemkhao M (2022) Properties of mortar composites from plastic waste. J Appl Sci Eng (Taiwan) 25(1):59–70. https://doi.org/10.6180/jase.202202_25(1).0007 5. Singh AP, Ghoshdastidar PS (2022) Computer simulation of heat transfer in alumina and cement rotary kilns. J Thermal Sci Eng Appl 14(3):4051376. https://doi.org/10.1115/1.4051376 6. Saruwatari M, Nakamura H (2022) Coarse-grained discrete element method of particle behavior and heat transfer in a rotary kiln. Chem Eng J 428:130969. https://doi.org/10.1016/j.cej.2021. 130969 7. Hosseini AS, Khanniche S, Greaney AP, Romano G (2022) Universal effective medium theory to predict the thermal conductivity in nanostructured materials. Int J Heat Mass Transf 183:122040. https://doi.org/10.1016/j.ijheatmasstransfer.2021.122040 8. Belkhiria M, Echouchene F, Jaba N (2022) Nano-heat transfer in GAAFET transistor using single-phase-lag model. In: Ben Amar M, Bouguecha A, Ghorbel E, El Mahi A, Chaari F, Haddar M (eds) Advances in Materials, Mechanics and Manufacturing II. A3M 2021. LNME, pp 114–122. Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-03084958-0_12 9. Molina-Rodea R, Wong-Loya JA (2021) A new model to predict subsoil-thermal profiles based on seasonal rain conditions and soil properties. Geothermics 97:102261. https://doi.org/10. 1016/j.geothermics.2021.102261 10. Tang L-S et al (2022) Double-layered and shape-stabilized phase change materials with enhanced thermal conduction and reversible thermochromism for solar thermoelectric power generation. Chem Eng J 430:132773. https://doi.org/10.1016/j.cej.2021.132773 11. Ghazi-Hesami S, Wise D, Taylor K, Ireland P, Robert E (2022) Heat transfer and pressure drop of an angled discrete turbulator at elevated reynolds numbers up to 900,000. J Thermal Sci Eng Appl 14(7):071003. https://doi.org/10.1115/1.4052352 12. Zhang G, Li Q, Liu X, Lin B, Li X (2022) Numerical investigations on an improved dualchannel porous combustor fueled with lean methane for enhancing thermal performance. Fuel 309:122228. https://doi.org/10.1016/j.fuel.2021.122228 13. Courtois E, Glouannec P, Magueresse A, Loulou T (2022) Estimating thermal properties of phase change material from heat flux measurements. Int J Therm Sci 172:107307. https://doi. org/10.1016/j.ijthermalsci.2021.107307 14. An L, Zhang N, Zeng X, Zhong B, Yu Y (2022) Quasi-isotropically thermoconductive, antiwear and insulating hierarchically assembled hexagonal boron nitride nanosheet/epoxy composites for efficient microelectronic cooling. J Colloid Interface Sci 608:1907–1918. https://doi.org/ 10.1016/j.jcis.2021.10.094 15. Kiran S, Gorar AAK, Qadee TWA, Zhang DLL, Hussain JWA, Sami SSK, Liu WB (2022) Effects of hollow glass microspheres on the polybenzoxazine thermosets: Mechanical, thermal, heat insulation, and morphological properties. J Appl Polym Sci 139(7):51643. https://doi.org/ 10.1002/app.51643 16. Davydova MA, Zakharova SA (2022) Multidimensional thermal structures in the singularly perturbed stationary models of heat and mass transfer with a nonlinear thermal diffusion coefficient. J Comput Appl Math 400:113731. https://doi.org/10.1016/j.cam.2021.113731
Method for BIM and GIS Databases Integration for CIM Creation Support Mohamad Roumyeh , Vladimir Badenko , and Yulia Volkova
Abstract The building and construction industry has witnessed many developments during the past years. The most important of which is the use of building information modeling (BIM). BIM technologies contributed to the development of this industry significantly, as it was used at the level of individual buildings and projects. Nowadays the continuous need for development forced the transition to use BIM on a wider level to include cities, through integration with other systems, mainly Geographical Information Systems (GIS). The integration between BIM and GIS will contribute to obtaining digital models for cities or as called City Information Modeling (CIM). CIM will contribute significantly to supporting the decision-making process in addition to developing urban planning processes for cities. Furthermore, these CIM models will form the base to contribute in creating digital twins in order to conduct smart city. In this research paper, we will elaborate an approach about how to take advantage of the overlap and integration between BIM and GIS in order to create a CIM model without using IFC and City GML formats for a small region in Nizhny Novgorod in Russian Federation. As a result of this research, we will get a CIM model without losing features of 3D BIM models. Keywords Digital models · Building information modeling · Geographical information systems · City information modeling · Database integration
1 Introduction Building information modeling can be considered as the main technology to create 3D models that contained all assets information however the location accuracy of these assets models is often not taken into account [1]. GIS maps constitute one of the important sources of inputs for the BIM, by providing a two-dimensional representation of buildings and assets based on footprint or vertical representation, which M. Roumyeh (B) · V. Badenko · Y. Volkova Peter the Great St. Petersburg Polytechnic University, 29, Polytechnicheskaya ul., 195251 St. Petersburg, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_95
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in turn contributes to facilitating the process of creating three-dimensional models for these assets [2]. On the other hand, BIM models represent one of the richest databases that include all the information related to the physical assets during the various stages of their life cycle, starting from planning to the operational stage, furthermore, GIS models effectively contribute to enhancing the urban planning processes, which makes the process of merging between BIM and GIS very insistent [3]. The integration between BIM and GIS or as called GeoBIM has been represented the title of many studies in the recent period [4]. It was found that the number of papers related to integrating BIM and GIS is significantly limited in comparison with other issues. It was concentrated in a lot of articles on using of City GML format in order to create models based on BIM models because of the wide range of use of City GML, on the other hand, this approach had some problems such as losing features of BIM models [5]. The researchers [4] discussed the BIM/GIS integration from only the point of view related to exchanging data from IFC to City GML format. In addition, others illustrated how to create a GeoBIM 3D model by integrating BIM and GIS data throughout using IFC and City GML formats [6]. The BIM-GIS integration has been used in different scopes such as managing and monitoring historical assets as well as facility management in order to improve their performance [7]. GeoBIM used also to manage and monitor infrastructure projects like roads by using LiDAR [8]. Using integration between BIM and GIS was also shown in a research published recently in which the authors used GeoBIM integration for heritage buildings, furthermore, ArcGIS pro and Infraworks were used in this research [9]. A group of researchers confirmed, through a study they carried out, the role of GeoBIM in creating smart cities, by replacing the two-dimensional models usually used in real estate organizations and departments with a three-dimensional models of assets, which will contribute effectively to enhancing the urban planning process for smart cities [10]. On the other hand, it was obvious that the integration between BIM and GIS faces some challenges. Some researchers have determined, based on a study they conducted, that the data used must be closely related to the specific goal of integration because the presence of additional unrelated data will impede the integration process [11]. Several studies concluded that Integration between BIM and GIS will contribute to establishing a smart city because of the ability of BIM to create detailed 3D models besides the ability of GIS to use these models in the spatial system [12, 13]. In one of the recent studies, a platform for managing a park was created using the integration between BIM, GIS and the Internet of Things (IoT) [14]. Others found that integration between BIM, GIS, and the IoT represents the main key to creating smart cities. This integration will contribute to having sufficient management for city infrastructure [15, 16]. It had been concluded that using the integration between GIS and VR technology will be so effective in several issues related to the sustainable development of the urban areas, improve the decision-making process, decrease personnel dependency and enhancing facility performance, etc. [17]. Another study discussed some problems related to using BIM models in the GIS environment. It was found that converting the IFC file to shapefile is much sufficient than converting it to City GML, moreover, using the IFC-City GML approach still has some problems because of mismatches in modeling and
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semantics methods [18]. It should also be noted that when the term BIM is used, it is often referred as the design stage of building life cycle [19, 20]. Terms as-built BIM and as-is BIM are also used for existing buildings, in this case laser scanning technologies are widely used [21, 22]. It was elaborated in other articles that City GML models have several levels of details (LODs) which means that the higher LOD of the model the detailed features we get, however it was also concluded that several features of BIM models will be lost due to the conversion process [21–24]. According to the mentioned articles, it was obvious that a lot of studies considered the approach of using City GML and IFC format besides a limited number of articles that used Infraworks and ArcGIS pro so that, the aim of this research paper is to develop a method for the integration between BIM and GIS in order to create a CIM to improve the decision-making process and urban planning without using City GML and IFC, which will form a base for creating a city digital twin (CDT) to reach the end of creating smart cities. This work had been created by using ArcGIS data, Autodesk Revit 2021, and Autodesk Navisworks 2021.
2 Materials and Methods It is clear in this paper that we are dealing with the effect of integration between BIM and GIS by applying this to a realistic case study, which makes our method a mixture of quantitative and qualitative methods at the same time. It was mentioned in the previous chapter that a lot of researchers tended to use City GML and IFC format in their work in order to create integration between BIM and GIS, however, this method contains several problems related to the loosing features of the BIM models, so that our proposed method will help to create CIM model through integration between BIM and GIS without losing features of the BIM models, furthermore, in this method there is no need to use City GML or IFC format so this will lead to avoid the conversion problems and make our work easier. In order to have a good understanding of the proposed method, it had been decided to elaborate it by dividing the method into specific steps. First step. In this phase, we need to collect all information and data related to the studied area like elevations, topographical information, buildings borders, facades, etc. by using GIS, Google maps, and Yandex maps. It is important to get recent photos of the studied area including all assets in order to avoid any problems related to the development process such as demolishing some buildings or rebuilding it, etc. The purpose of using different software is to get photos of all facades of the buildings because in some cases we will not find some facades because of the location of the building. Second step. It is mandatory to create a central Revit file by using all inputs we’ve collected, in addition to make separated Revit files for each property and connect their coordinates and locations with the central file to make sure that each building will be located at accurate location. All these models had been created via Autodesk
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Revit 2021. Our modeling process depends on using only the photos we have, Due to the luck of plans of these assets. Third step. At this step we need to use all data and inputs we’ve collected to model the basic model LOD 100 of our assets in Autodesk Revit 2021. The purpose of this step is just to model the basic shape of the building and put them in the accurate location, furthermore, creating this step will make the detailed modeling process much easier. Fourth phase. At this stage, after we have improved the LOD 100 models we need to create detailed models by using facade pictures available in Google and Yandex Maps. Fifth step: this stage represents the final step in our work where we need to create one file which contains all models we created in Autodesk Revit. To do this we input all models in one file by using Autodesk Navisworks Manage 2021. Navisworks will help us to connect the model of our part with other regions’ models to create CIM. We can summarize our research steps in the Fig. 1. Also, by using Navisworks we will have our model with a smaller volume, which will make our work much sufficient in case we have a bigger area with more buildings or even when we want to combine our model with other models in order to create a CIM model for avenue or maybe for the whole city.
Fig. 1 Summary of the research steps
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3 Results The proposed method had been tested and used on a real object which represents an area Located in Nizhniy Novgorod in Russian Federation, and in the following, the final obtained results for this area will be clarified, depending on all the inputs and data that we’ve obtained with the application of the stages mentioned in the previous chapter as well as a result for each phase as mentioned before. As a result of our work, we obtained five Revit files, which include a central file that includes all the previously mentioned studied buildings, in addition to a separate file for each property, taking into account that all files share the same coordinates with the central file, which in turn represent the coordinates of the studied area. In the following figures we can see the final results we had from our work. The first step we have made according to our method was collection of the required data about the studied area. Our area located in Russian Federation in Nizhny Novgorod. This area located in the central part of the city between two streets (Maskima Gor’kohgo street and Frunze street). In Fig. 2 we can see photos and facades of the case study area. The boundaries of our area had been shown in Fig. 3. The total area we have is 7220 m2 . In our location we have a combination of building with different ages. According to all photos we got from the mentioned
Fig. 2 Pictures of some buildings facades
Fig. 3 The boundaries of the studied area in (Topographic) GIS Map
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Fig. 4 3D view of the central file and buildings at LOD 100
application. It has been noticed that we have the same results for all buildings without notable changes. Defining such changes if any can be useful to get as real models for all assets. At Fig. 4, we can see the central file, as well as the LOD 100 3D models for all assets we have in the studied area. The borders of all assets as well as plot borders had been determined. This LOD 100 model represents the foundation model for the next step of modeling. In Fig. 5 we can see the 3D models for the buildings we mentioned before, and as it has been shown, we got as real 3D models for all buildings, and this will help us to have a real CIM model. Specific families had been created via Autodesk Revit in order to have these detailed models. The general plan in the central Revit file has been shown in Fig. 6, in which we defined the location of all buildings according to the data we have besides the main infrastructures such as roads, sidewalks, and green areas, furthermore all slopes and elevation of the surface had been taken into account according to the data we got from GIS. Fig. 7 displays the final 3D result of the studied area in the Autodesk Navisworks file. It is obvious that in this work, Autodesk Navisworks had been used as a navigation software which will help us to
Fig. 5 3D models of the buildings
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show our model besides the ability to combine it with other models in case we want to extend it. This CIM model will be so useful and effective to use in urban planning decision making because it gives a realistic view of the required area including features of the
Fig. 6 3D model of the general plan of the location
Fig. 7 Final 3D result of the studied area
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Table 1 Total volume of all files of the work Files’ type
Number of files
Revit files (RVT)
5
92,236
Navisworks files (NWC, NWF)
6
76,117
Navisworks (central file)
1
Total volume (KB)
volume (KB)
75,886 244,239
assets as well as the existing infrastructure such as walkways and roads. Also using such models will be useful for real estate public organizations which will help to define the borders of each estate or plot, etc. In Table 1, the total volume of all files for this work has been show. It is obvious that the volume of Revit files is bigger than the Navisworks file and this difference in volume can be much bigger in case we have a plot with a large number of buildings, However, it is notable that the volume of the central Navisworks file is 244.239 MB which is also less than Revit files, which reflects one of the benefits of using Navisworks in this situation.
4 Discussion To elaborate the discussion, it was decided to divide it into the following points. The possibility of using integrating BIM and GIS had been elaborated in this research without using IFC and City GML formats. This method helped to create CIM model with avoiding the conversion problems between BIM and GIS environment. The CIM model which had been created forming the base point to create a CIM model for a city in the same way. It was notable that no features of the 3D BIM models had been lost by using the proposed way and this reflects the novelty and the strength of the method used in this research. This model can be used for several purposes such as improving the urban planning besides other purposes in the real estate organization, furthermore, this CIM model can be improved to create a digital twin which will be so useful for monitoring assets during the operation phase. This point can be considered as an idea for future research. It is important to mention that creating a 3D BIM model by using the proposed method is not limited to using Autodesk Revit, but also it is possible by using other software such as Renga, etc. and this reflects the elasticity of the method.
5 Conclusions The efficiency of the proposed method is confirmed by the results presented in Sect. 3. It is obvious that we finally got a 3D information model of the area similar to its
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real counterpart, and this model will contribute to improving the decision-making process in addition to making the process of determining the boundaries of real estate and urban planning more easy and effective because in this case, we are dealing with three-dimensional models and not with 2D drawings or objects as it is currently supported. Also, this CIM model had been created without using City GML or IFC format which let to protect the BIM models features. It is certain that the creation of such models will contribute effectively to the creation of the city information model CIM, which in turn will lead to the creation of the smart city, moreover, creating such a CIM model for a city will be effective for use in real estate organizations or cities municipalities. We believe that these models can then be used to create digital twins of the physical assets, which will contribute to simulating any change that affects the assets in addition to the possibility of using them to analyze and manage the expected risks to avoid them or to mitigate their effects as much as possible. One of the weaknesses that we encountered during the implementation of this research is the lack of information about the internal details of the studied properties, due to the presence of the studied area in another region. The volume of files must be taken into consideration in case of creating CIM model for a city.
References 1. Arroyo Ohori K, Diakité A, Krijnen T, Ledoux H, Stoter J (2018) Processing BIM and GIS models in practice: experiences and recommendations from a GeoBIM project in The Netherlands. ISPRS Int J Geo-Inf 7(8):311. https://doi.org/10.3390/ijgi7080311 2. Diakite AA, Zlatanova S (2020) Automatic geo-referencing of BIM in GIS environments using building footprints. Comput Environ Urban Syst 80:101453. https://doi.org/10.1016/j.compen vurbsys.2019.101453 3. Badenko V et al (2019) Comparison of software for airborne laser scanning data processing in smart city applications. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XLII5/W2(5/W2):9–13. https://doi.org/10.5194/isprs-archives-XLII-5-W2-9-2019 4. Noardo F et al (2020) Opportunities and challenges for GeoBIM in Europe: developing a building permits use-case to raise awareness and examine technical interoperability challenges. J Spat Sci 65(2):209–233. https://doi.org/10.1080/14498596.2019.1627253 5. Zhou X, Zhao J, Wang J, Su D, Zhang H, Guo M (2019) OutDet: an algorithm for extracting the outer surfaces of building information models for integration with geographic information systems. Int J Geogr Inf Sci 33(7):1444–1470. https://doi.org/10.1080/13658816.2019.157 2894 6. Eriksson H et al (2020) Requirements, development, and evaluation of a national building standard - a Swedish case study. ISPRS Int J Geo-Inf 9(2):78. https://doi.org/10.3390/ijgi90 20078 7. Rechichi F (2020) CHIMERA: A BIM+GIS system for cultural heritage. ISPRS Int Arch Photogramm Rem Sens Spat Inf Sci XLIII-B4-2:493–500. https://doi.org/10.5194/isprs-arc hives-XLIII-B4-2020-493-2020 8. Barazzetti L, Previtali M, Scaioni M (2020) Roads detection and parametrization in integrated BIM-GIS using LiDAR. Infrastructures 5(7):55. https://doi.org/10.3390/infrastructures 5070055
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9. Zhu J, Wu P (2021) A common approach to geo-referencing building models in industry foundation classes for BIM/GIS integration. ISPRS Int J Geo-Inf 10(6):362. https://doi.org/10. 3390/ijgi10060362 10. Souza L, Bueno C (2022) City information modelling as a support decision tool for planning and management of cities: a systematic literature review and bibliometric analysis. Build Environ 207:108403. https://doi.org/10.1016/j.buildenv.2021.108403 11. Wang H, Pan Y, Luo X (2019) Integration of BIM and GIS in sustainable built environment: a review and bibliometric analysis. Automat Constr 103:41–52. https://doi.org/10.1016/j.aut con.2019.03.005 12. Beck F, Borrmann A, Kolbe TH (2020) The need for a differentiation between heterogeneous information integration approaches in the field of BIM-GIS integration: a literature review. ISPRS Ann Photogramm Remote Sens Spat Inf Sci VI-4/W1–20(4/W1):21–28. https://doi. org/10.5194/isprs-annals-VI-4-W1-2020-21-2020 13. Badenko V, Fedotov A, Vinogradov K (2018) Algorithms of laser scanner data processing for ground surface reconstruction. In: Lecture notes computer science, vol 10961, pp 397–411. https://doi.org/10.1007/978-3-319-95165-2_28 14. Moretti N, Ellul C, Cecconi FR, Papapesios N, Dejaco MC (2021) GeoBIM for built environment condition assessment supporting asset management decision making. Automat Constr 130:103859. https://doi.org/10.1016/j.autcon.2021.103859 15. Celeste G, Lazoi M, Mangia M, Mangialardi G (2022) Innovating the construction life cycle through BIM/GIS integration: a review. Sustainability 14(2):766. https://doi.org/10.3390/su1 4020766 16. Badenko V et al (2019) Scan-to-BIM methodology adapted for different application. ISPRS Int Arch Photogramm Rem Sens Spat Inf Sci XLII-5/W2(5/W2):1–7. https://doi.org/10.5194/ isprs-archives-XLII-5-W2-1-2019 17. Lv Z, Li X, Lv H, Xiu W (2019) BIM big data storage in WebVRGIS. IEEE T Ind Inform 16(4):2566–2573. https://doi.org/10.1109/TII.2019.2916689 18. Kang T (2018) Development of a conceptual mapping standard to link building and geospatial information. ISPRS Int J Geo-Inf 7(5):162. https://doi.org/10.3390/ijgi7050162 19. Darko A, Chan AP, Yang Y, Tetteh MO (2020) Building information modeling (BIM)-based modular integrated construction risk management–Critical survey and future needs. Comput Ind 123:103327. https://doi.org/10.1016/j.compind.2020.103327 20. Badenko VL, Bolshakov NS, Tishchenko EB, Fedotov AA, Celani AC, Yadykin VK (2021) Integration of digital twin and BIM technologies within factories of the future. Mag Civil Eng 101(1):10114. https://doi.org/10.34910/MCE.101.14 21. Bosché F, Ahmed M, Turkan Y, Haas CT, Haas R (2015) The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: the case of cylindrical MEP components. Autom Constr 49:201–213. https://doi.org/10.1016/j.aut con.2014.05.014 22. Hamledari H, Rezazadeh Azar E, McCabe B (2018) IFC-based development of as-built and asis BIMs using construction and facility inspection data: Site-to-BIM data transfer automation. J Comput Civil Eng 32(2):04017075. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000727 23. Bolshakov N, Badenko V, Yadykin V, Celani A (2020) As-built BIM in real estate management: the change of paradigm in digital transformation of economy. IOP Conf Ser Mater Sci Eng 940(1):012017. https://doi.org/10.1088/1757-899X/940/1/012017 24. Deng Y, Cheng JCP, Anumba C (2016) Automation in Construction Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison. Autom Constr 67:1–21. https://doi.org/10.1016/j.autcon.2016.03.006
Modeling Professional Risk Elena Smirnova
and Nadejda Subbotina
Abstract The article discusses the problem of determining safe work experience in conditions of increased intensity of hard work in Russia. It is especially relevant in construction industry. The need for an objective analysis of industrial accidents is an urgent task not only for the prevention of injuries, but also for improving environmental safety, interpreted as occupational risk management in order to protect the health of people of active working age. The research methodology was based on the analysis of the characteristics of the occupational diseases risk, depending on the level of existing harmful production factors, as well as the length of service. Occupational risk gradually increases nonlinearly over the course of the employee’s work experience, and in the experience sector the risk begins changing at an increasing rate. The new system for assessing working conditions introduced in 2014 cannot provide completely environmentally friendly and safe working conditions and acceptable risk (R). The environmental safety of production activities is a big question and is at high risk in the construction industry, in particular due to the huge number of concealment of occupational injuries, violations of the regenerative capacity of the human body, as well as the extension of the retirement age to 65 and 70 years. Therefore, it is required to introduce a mechanism (model), providing a real system for assessing working conditions. Keywords Construction · Environmental safety · Industrial accidents · Modeling professional risk · Occupational diseases risk
1 Introduction The share of manual labor is quite high in construction sector, and hard work is one of the factors of increased risk, therefore, the definition of safe work experience in conditions of increased difficulty of work is especially important in construction E. Smirnova (B) · N. Subbotina Saint Petersburg State University of Architecture and Civil Engineering, 4, Vtoraja Krasnoarmejskaja Street, St. Petersburg 190005, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_96
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and transport industry [1–5]. Once in a while, statistical data on industrial injuries and occupational diseases are the main indicators in assessing the measures taken to improve industrial safety. Especially, when it comes to hazardous and harmful production conditions. In the Russian Federation, such organizations are responsible for data on injuries as: Rostrud (Russian Service of Labor), Rosstat (Russian Statistical Service), SIF (Social Insurance Fund), and Rostekhnadzor (Russian Technical Supervision). Each of these organizations keeps own records of statistics according to certain principles. For example, Rostrud takes into account accidents and industrial injuries registered on the bases of requests and complaints from employees themselves. While Rosstat takes into account accidents, only in the case when they were provided by employers. Rospotrebnadzor, in turn, pays great attention to occupational diseases, and the SIF focuses on insured accidents. The presented data can be considered, both separately for each component, and all together to draw up an overall picture of the safety level of a particular production branch. As a result, the need for an objective analysis of industrial accidents is an urgent task not only for the prevention of injuries, but also for improving environmental safety, interpreted as occupational risk management in order to protect the health of people of active working age [6, 7]. There are two different options. The first is to compare data with last year’s results and draw a conclusion about the effectiveness of the measures taken in relation to previous years. The specified option is intended to track the trend and clearly see how the injury indicators change from year to year. But due to inaccurate statistical information on labor protection provided by Rostrud (analyzes data on injuries at work, but in the case of severe injuries with fatal outcomes, single incidents are not registered, only group incidents), Rosstat (collects and analyzes data on all types of accidents in production at large and medium-sized enterprises, at small only selectively in 12 types of economic activities, excluding financial activities, public administration, military security, social insurance, education and some others), the FSS (records only insured events) and a number of other state organizations, there is no confidence in the accuracy of accounting. Moreover, there is no way to understand how effective the current measures are. For example, if we compare the data on victims in the construction sector, they differ significantly: 8.5% (Rosstat) and 23.2% (Rostrud). In 2019, according to statistics from the Social Insurance Fund (FSS), there were 1527 fatalities. According to Rostrud data, work-related fatal injuries affected 1613 workers. Obviously, the above statistics complicates the effective use of the first option for analyzing occupational injuries. The second option of the analysis is more informative due to the comparison with the data obtained in other countries. It is quite effective, because many European countries that are members of the International Labor Organization have a low rate of reduction in overall industrial injuries (for example, in 2016, in Germany, the number of injured people was 877.1 thousand by 40.1 million workers against 39.8 thousand industrial injuries in Russia for 44.4 million) (URL: http://www.ilo.org). This circumstance once again emphasizes on all the implausibility of Russian statistics. In the Western countries, the risk of fatal accidents at work is reduced by modernizing production and reducing a number of workers employed in hazardous and harmful
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conditions. Indeed, in Germany, between 1990 and 2015, the proportion of fatal injuries fell from 0.08 to 0.05% (URL: http://www.ilo.org/ilostat/faces/home/statis ticaldata?_afrLoop=680869279925113&_adf.ctrlstate=w7otyfthy_4). It is worth noting once again the principle, on the basis of which the effectiveness of the measures taken is achieved: reducing the number of workers in hazardous industries, rather than protecting them with personal protective equipment. Since 2007, the severity of industrial accidents in Russia has only increased every year. In 2016, economic losses from compensation in connection with accidents and occupational diseases caused by the state of production and labor protection at enterprises amounted to 1.53 trillion rubles, or 1.8% of GDP (URL: http://eisot.rosmintrud.ru/ attachments/article/47/results_2016.doc). Whatever the personal protective equipment is, the measures aimed at preventing deaths and taken by European countries in labor protection are really effective. They should be introduced in Russia. Let us consider the methodology of the International Labor Organization (ILO) regarding the reliability of statistics on industrial accidents in countries with imperfect accounting. For the already indicated reasons, Russia can be classified as such a country. The essence of the technique lies in the fact that fatal injuries are recorded better than other injuries, therefore, fatalities should become the basis for subsequent calculations of the probable total number of injured persons [8]. The transition from the number of deaths to the total number of injured persons is realized through a ratio confirmed by many years of experience in Western European countries, the USA, Canada, and Japan. It averages from 500 to 1000 injuries per one fatal injury and shows the number of injuries on average corresponds to one fatal accident at work. In connection with the above, the purpose of the article is to show the inability special assessment of working conditions (SAWC) not only to prevent (compared with the previous system of certification of workplaces for working conditions), but at least to weaken through compensatory measures (reduced working hours, annual additional paid leave or monetary compensation for them, as well as increased wages) negative impact on the health of workers of harmful and dangerous factors of the production environment and the labor process [8]. In the course of the study, the following tasks were solved: (1) the concept of risk in occupational safety and health was analyzed and (2) the reasons for the increase of occupational risk (OR) in construction and transport industry and the risk of occupational disease (OI) were clarified.
2 Materials and Methods The research methodology is represented by the following algorithm. In the first stage of studying the topic, a method of contextual analysis of the problems associated with professional risk, generated by unfavorable factors of production was applied. The inconsistency of official statistics of professional diseases with respect to an expert assessment was established, according to which their potentially possible number
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significantly exceeds a claimed one. Further analysis of the problem showed that the introduction of the SAWC system, which replaced the former procedure for workplaces certification, could not stop the growth of industrial accidents in Russia. Consideration of the Methodology of the International Labor Organization (ILO) regarding the truthfulness of statistical data of industrial accidents in countries with imperfect accounting has led to the conclusion that fatal injuries registered better than the remaining injuries is the basis for any reliable calculations of the likely total number of injured persons. The transition from the number of those who died to the total number of victims in Russia is represented by the relation 1:22 (1: 1732 in Germany) and indicates a huge “gap” in the data array, by which official statistics operates. In the second stage of the study, the concept of professional risk was taken as an additional context. In this regard, the features of the OI risk and their dependence on the level of existing harmful production factors, as well as work experience were analyzed. The identified patterns of professional risk occurrence are presented in formulas and drawings.
3 Results and Discussion Modern labor protection management systems are based on a risk-based principle. In the sphere of security, the term risk has two wording: 1. In Labor Code of the Russian Federation dated of 30.12.2001 N 197-FZ, the risk is defined as a combination of the probability of an event and its consequences (an injury, OI, an accident, etc.) (URL: http://www.consultant.ru/doc ument/cons_doc_LAW_34683/). 2. In Federal Law “On compulsory social insurance against accidents at work and occupational diseases” dated of 24.07.1998 N 125-FZ, OR is defined as the likelihood of damage (loss) of health or the death of the insured, associated with the fulfillment of their responsibilities for the employment contract and in other cases established by the legislation (URL: http://www.consultant.ru/document/ cons_doc_LAW_19559). The risks of the occurrence of industrial diseases and accidents are differentiated. The derivation of an element responsible for assessing the consequences of the implementation of negative events in the concept of risk is due to the fact that that meaning of risk came to safety from the insurance system [9]. In insuring, possible events are differentiated for damage to calculate insurance costs that employers should pay when insuring employees against accidents and/or OI. In labor protection, legislative risk categories specified for each sector of the economy are used for insurance, which do not provide differentiation of the type of workplace. The definition of OR from the Labor Code can be used for planning labor protection activities, which makes it possible to take into account the impact of hazardous and harmful production factors to evaluate the OR indicators. It is obvious that the presence of a large number of definitions and indicators of OR complicates the choice of the main indicator, quite
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accurately reflecting the advantages of SAWC, the legally introduced in 2013. To determine the long-term effect of labor protection activities, it is necessary to have the possibility to receive forecast values used for strategic planning [10–13]. For all kinds of economic activity, factors of the production environment became the main harmful and hazardous industrial factors affecting workers. So, in 2020, 23.6% of employees (every fourth) were subjected to their effects in the construction and transport industry. The factors of the labor process (difficulty and intensity) were followed by the significance of the negative impact on workers. In 2020, the share of workers engaged in hard work in construction was 15%. The number of employed in construction in the same year in jobs related to the intensity of the labor process, was 8.1% [7]. Since 2014 to 2020, the introduction of the SAWC procedure has not led to a radical change in the proportion of workers engaged in work with harmful and hazardous working conditions, but significantly affected the structure of hazardous and harmful production factors affecting employees. In the first place there were the hard work, various types of noise, vibrations, aerosols predominantly fibrogenic action and etc. Separate indicators characterizing the harmful and dangerous factors of the production environment and the intensity of the labor process, in general were excluded from the SAWC (for example, “Heating microclimate” and “Cooling microclimate”). Thus, as a result of the SAWC procedure introduction, (1) the factors of the production environment associated with a periodic change in working conditions due to the change of the geographical location of construction objects; (2) difficulty and intensity of construction work; (3) impact of harmful and dangerous factors on the health of employees are essential for strategic planning in the sphere of construction security [14]. Table 1 presents the proportion of jobs that do not meet the established standards for individual production factors at construction enterprises in Russia (URL: http:// rospotrebnadzor.ru/upload/iblock/0b3/gosudarstvennyy-doklad-2020.pdf). It should be noted that the high percentage of workers in the transportation and construction industry with unsatisfactory working conditions is due to: increased dust and gas content of the working area; high percentage of manual labor (up to 50%); depreciation of technological equipment (up to 50–65%); increased sound levels in workplaces (excess to 10–20 dBA); reduced air temperature (5–10 °C below normative); low mechanization of labor-intensive technological processes (35–50%) (URL: https://rosmintrud.ru/docs/mintrud/alanalytics/137). Dynamic change in these factors is reflected in the OR indicators. Their value changes randomly due to hazardous factors, as it depends not only on changes in the state of working conditions, but also on the behavior of staff at the workplace, time of year, day, etc. The value of OR indicators is characterized by slow, gradual development. With the growth of labor experience, the functional health indicators change gradually and linearly: the risk indicator first changes slightly, then changes with increasing speed [15]. The risk features of the OI occurrence include its dependence on the level of existing harmful production factors, as well as the experience. Thus, the OR is directly related to the dynamics of changes in harmful and hazardous production factors during the employment experience of the employee. The risk of
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Table 1 Quota of workplaces that do not meet the standards of working conditions for individual production factor and labor process in the construction industry of the Russian Federation Factors
Part of workplaces that do not meet the conditions of labor in construction,% 2018
2019
2020
Large difficulty
20,1
21,5
18,9
Noise
13,9
14,1
17,2
Labor intensity
7,5
7,3
5,9
Chemical factor
7,4
7,6
6,1
7
6,8
8,5
5,9
4,9
3,4
Light medium
3,9
3,3
1,6
Aerosols of predominantly fibrogenic action
3,8
4,
3,3
Non-ionizing radiation
1,6
1,8
0,8
Ionizing radiation
0,5
0,4
0,3
Biological factor
0,4
0,3
0,5
Vibration Microclimate
OI during the employment experience of the employee gradually increases nonlinearly, which can be called the accumulation of OR. In the experience zone, the risk begins to change with increasing speed (Fig. 1). Three OI risk zones can be distinguished in the dynamics of employment (Fig. 2). In the safe area, due to the short work experience (5 years), there are no reasoned data on health deterioration yet, but a certain attention is required. In the border zone (5–8 years), health deterioration exceeds the permissible level and becomes dangerous, close monitoring is required. In a danger zone at a fairly large experience (after 8 years), the OI frequency becomes high and unacceptable and the risk exceeds the value of 0.5. Thus, OR intensively accumulates. Its intensity can be assessed in terms of annual growth:
Fig. 1 Risk dependence on work experience [14]
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Fig. 2 Risk dynamics during employee’s work experience
Ri = Ri−1 + ΔRi ,
(1)
where Ri is the OR, accumulated by a worker during the i years of labor activity under the conditions of the production medium; Ri is the increment of OR on the i-th year of labor experience. The initial value of OR (R0 ) is given by the method of expert assessments for each specific enterprise of the construction and transport industry. An annual increase in OR must be provided at such a level so that for a period of safe experience the accumulated OR did not exceed acceptable values. It is assumed that accumulation of the risk begins during the primary arrival at the workplace not from the zero value, but from some background initial value (R0 ) due, for example, a person’s life, a place of residence or place of previous work. Thus, the safe state of the production environment can be expressed through an acceptable risk by the following formula [5]: R0 +
Tsafety i=1
ΔRi ≤ Racceptable ,
(2)
where R0 is the initial OR; Tsafety is a safe work experience in the specified conditions of the production environment. The concept of risk acceptable with respect to the difficulty of work correlates with the principles of the task of extremely permissible levels, which at 8 h of work, except the weekend, (but not more than 40 h per week) during the entire working experience do not cause occurrences of diseases or deviations in the health status of workers. Such labor protection measures that have ensured the non-exceedance of the acceptable value of OR during the work experience before reaching the age for retirement will be recognized as effective to reduce labor difficulty. For example, for the oilfield worker, an acceptable risk is ensured (1 × 10–3 ) for professional groups,
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while maintaining the technology of work and working conditions, and if the work experience will last 3–4 years [7]. The normative period of OR accumulation is determined using the following considerations: 1. The accumulation period to an acceptable OR value corresponds to the value of the work experience, in which the employee has reached a retirement age. In other words, the work experience of the personnel is determined before the retirement age (retirement experience in 45 and 40 years old in men and women, respectively). 2. If the accumulation period of OR (to an acceptable value) does not ensure the beginning of retirement age of an employee without OI, it is necessary to determine the experience at which an acceptable OR (safe experience) is achieved. To establish a safe work experience, the employers are guided by the requirement of the Pension Insurance Act on the maximum experiences of work in particularly harmful working conditions and a reduction in retirement age. If workplaces in the construction site are considered, for which the maximum work experience and the state of labor conditions does not allow for acceptable OR during the entire employment experience, it is necessary to establish the value of the work experience at which there is no excess of the acceptable risk. There is the following principle of establishing a safe work experience in labor medicine: work experience exceeding half of the average period of development of an occupational disease in a given profession is considered a significant risk factor. The effectiveness of measures for labor protection when using OR accumulation logic is presented in Fig. 3. As can be seen from the figure, in the second variant (b) using the OR increment logic, a new variable appears: Runacceptable (the value of unacceptable risk). Accounting for unacceptable risk allows you to change the strategy of occupational safety measures and achieve such an annual increase in the professional risk Rsafety , in which the normative safe experience Tsafety corresponds to Tretiremen and employees
Fig. 3 Evaluation schemes of unacceptable risk for labor protection: a without using the logic of OR accumulation of, b using one
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reach retirement age. Reducing the annual OR increment by value equal to the ratio of the actual safe work experience to the value of a safe work experience corresponding to the regulatory working conditions is expressed in the following formula: ΔRsafety Tsafety , = Tretirement ΔR
(3)
It is important that the annual increment R provides a safe work experience Tsafety . Thanks to the effective events, the ratio of the value of acceptable risk R before the retirement work experience to the value of acceptable risk up the beginning of the retirement work experience shows how actually an effective strategy will ensure a reduction in the annual incremental risk. The less this increment is, the more effective is the strategy to improve the conditions and protection of labor. The problem arises of developing mechanisms for determining the increment of OR and predicting it during the work experience of workers by the factor of labor difficulty. However, without referring to the implementation of this task in a small article, it should be emphasized that the reduction of the contingent of workers in respect of whom it is required to carry out SAWC procedure both as a whole and for individual hazardous and harmful production factors, as well as a change in the methodology for evaluating working conditions in which there were, in particular, certain indicators characterizing hazardous factors of the working environment and the intensity of the labor process are excluded from the SAWC, although they contribute to the decrease in the annual increment R, but cannot ensure safe duration of work experience of workers and an acceptable risk R until their retirement. With the introduction of the SAWC procedure, the indicators used to assess the difficulty of the labor process have not changed either quantitatively or qualitatively. Their impact on the reduction of the proportion of workers engaged in hard work, as well as in work with harmful and hazardous working conditions, cannot be reliably established only by reducing the contingent of workers in respect of whom the working conditions are evaluated. Yes, and this reduction in the proportion of workers, one can say, did not affect the change in the structure of hazardous and harmful production factors affecting employees. As already mentioned, the number of accidents per 100,000 workers in Russia is less (than in the UK by 6 times, with respect to Italy by 10 times, Germany by 18 times, France by 24 times, Spain by 25 times), but the number of deaths on production per 100,000 employees in Russia is the highest compared to the countries of the European Union. Thus, the average indicator of the considered relationship between fatal injury and the total number of accidents is 1:22 (1: 1732 in Germany) [16]. A significant number of accidents at the enterprises of the Russian Federation is hidden from registration and accounting, despite the decline in officially recorded cases of industrial injuries, including fatal ones. Calculations conducted by the Research Institute of Labor Medicine of the Russian Academy of Medical Sciences show the estimated specifications of the number of patients with occupational diseases from the number of employees undergoing compulsory medical examinations due to harmful working conditions is about 7.7%. This is more than 60,000 people and clearly exceeds the officially recorded annual statistics, fluctuating within 9000–12,000 cases per year
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[8]. Since employers have no funds to modernize the production and it is easier for them to provide financial compensation for the difficulty of the labor process, it is impossible to ensure safe work experience of workers and acceptable risk R before their retirement not only in dangerous industries in Russia, but also in the construction and transport industry, in particular. It must also be remembered that in the area of work experience, the health risk of workers begins to change at an increasing rate, regardless of the type of production. In addition, the inconsistency of the labor intensity to the restorative ability of the body is the most common, frequent and important cause of chronic fatigue and associated health risks, which is generally not taken into account by employers during the implementation of construction projects.
4 Conclusion The professional risk model, created on the basis of the SAWC procedure showed that the risk directly related to the dynamics of changes in harmful and hazardous production factors during the worker’s work experience, in the homosphere zone increases sharply and makes the high risk of occupational diseases unavoidable. The non-exceedance of the acceptable value of OR during the work experience until reaching the retirement age becomes impossible. Environmental safety of production activities is under great question, in particular, in the construction sector.
References 1. Reese CD (2018) Occupational Health and Safety Management: A Practical Approach. CRC Press, Boca Raton, FL 2. Kelloway EK, Francis L, Gatien B, Montgomery J (2021) Management of Occupational Health and Safety. Nelson, Toronto 3. McKinnon RC (2020) The Design, Implementation, and Audit of Occupational Health and Safety Management Systems. CRC Press, Boca Raton, FL 4. Dentch MP (2018) The ISO 45001: Guidance on Building an Occupational Health and Safety Management System. WI: Quality Press, Milwaukee 5. Idrisova JI, Myasnikov VN, Uljanov AI, Belina NV (2018) Increasing the efficiency of labor protection in the enterprise. In: Kwahakhoe HC (ed) The 32nd International Conference on Information Networking (ICOIN 2018), pp 586–588. IEEE, New York. https://doi.org/10.1109/ ICOIN.2018.8343186 6. Sorokin, GA, Syurin SA (2019) Assessment of the impact of harmful working conditions and smoking on the health of industrial workers. Gigiena i Sanitaria (Hyg Sanit Russ J) 98(6):646– 651. https://doi.org/10.18821/0016-9900-2019-98-6-646-651 7. Vadulina, NV, Gallyamov MA, Devyatova SM (2020) Occupational morbidity in Russia: problems and solutions. Saf Tech Nat Syst 3(1):7–15. https://doi.org/10.23947/2541-9129-2020-37-15 8. Hämäläinen P, Saarela KL, Takala J (2009) Global trend according to estimated number of occupational accidents and fatal work-related diseases at region and country level. J Saf Res 40(2):125–139. https://doi.org/10.1016/j.jsr.2008.12.010
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9. Larionov A, Nezhnikova E, Smirnova E (2021) Risk assessment models to improve environmental safety in the field of the economy and organization of construction: a case study of Russia. Sustainability 13(24):13539. https://doi.org/10.3390/su132413539 10. Smirnova E (2020) The use of the Monte Carlo method for predicting environmental risk in construction zones. J Phys Conf Ser 1614:012083. https://doi.org/10.1088/1742-6596/1614/1/ 012083 11. Smirnova E (2020) Environmental risk analysis in construction under uncertainty. In: Sementsov S, Leontyev A, Huerta S, De Nava IMP (eds) Reconstruction and Restoration of Architectural Heritage, pp 222–227. CRC Press, London. https://doi.org/10.1201/978100 3129097-47 12. Smirnova E (2021) Monte Carlo simulation of environmental risks of technogenic impact. In: Rybnov E, Akimov P, Khalvashi M, Vardanyan E (eds) Contemporary Problems of Architecture and Construction, pp 355–360. CRC Press, London. https://doi.org/10.1201/9781003176428 13. Nezhnikova E, Larionov A, Smirnova E (2021) Ecological risk assessment to substantiate the efficiency of the economy and the organization of construction. Hum Ecol Risk Ass 27(8):2069– 2079. https://doi.org/10.1080/10807039.2021.1949262 14. Sorokin GA (2016) The age and work experience dynamics of indices of health of employees - criteria for comparison of occupational and nonoccupational risks. Gigiena i Sanitaria (Hyg Sanit Russ J) 95(4):355–360. https://doi.org/10.18821/0016-9900-2016-95-4-355-360 15. Swaen GMH, van Amelsvoort LGPM, Bültmann U, Kant IJ (2003) Fatigue as a risk factor for being injured in an occupational accident: results from the Maastricht Cohort Study. Occup Environ Med 60:i88–i92. https://doi.org/10.1136/oem.60.suppl_1.i88 16. Lukyanchikova TL, Yamschikova TN, Kletsova NV (2018) Komparativistskiy analiz proizvodstvennogo travmatizma: Rossiya i mir (Komparativistic analysis of production traumatism: Russia and the world). Ekonomika Truda (Ek Tr Russ) 5(3):647–662. https://doi.org/10.18334/ et.5.3.39334
Sino-Russian Experience in Smart Grid Development: Issues and Perspectives Maksim Bikalenko
and Valentina Burtseva
Abstract The current power grid construction in China has made great progress and is gradually becoming mature. This happens due to the continuous development of the domestic science, technology and the enhancement of national power. The power grid construction has played a great role in people’s electricity safety, and has greatly improved the quality of life. Power engineering technology has been successfully integrated with the construction of smart grids. Such changes will improve the environmental protection and intelligence of smart grids, so that the grid construction can meet the current level of people’s actual needs. Therefore, the key technologies of the smart grid construction have become an urgent topic that the power industry attaches great importance to. The relevant study provides the analysis of power engineering technology in China and makes applications to apply these findings to the construction of smart grids in Russia. Keywords Smart grid · Power engineering · Chinese science · Modern technologies · Power design · Radio frequency identification (rfid) · Direct current (dc) power · Alternating current (ac) power
1 Introduction Power distribution, power supply technology, motor speed control technology and other aspects supported by power electronics technology have been widely used. These are closely connected and vital to the development and efficient use of hightech industries such as water conservancy engineering, shipbuilding engineering, automobile engineering, and elevator engineering. The strong demand of the rapid development of the modern economy has promoted the high-speed improvement M. Bikalenko (B) MGIMO University, Prospect Vernadskogo, 76, 1194542 Moscow, Russia e-mail: [email protected] V. Burtseva Council of Russian Federation, Ulitsa Bol’shaya Dmitrovka, 26, 105066 Moscow, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_97
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of power electronic technology with a trend of linear increase every year, and has become one of the pillars of modern intelligent equipment control technology. Hydroelectric power generation system is also one of the applications of power electronic technology. The development of modern network power electronics technology has improved the operating mechanism and characteristics of the core equipment of the power system generator set. In various power industries and electrical automation control, the application of power electronic technology will become more and more extensive, in-depth and intelligent. The combination of electronic technology and various electrical industries will promote the rapid improvement and stable development of the global economy [1]. The design process of a smart grid usually includes the following points. First, its self-healing ability is very strong. This feature shows the security and stability of the grid. It is precisely because of the characteristics of the smart grid that the power equipment can function long-term. Secondly, it can make better use of electric energy resources and reduce waste with a strong interactive ability. This makes the operation of the power grid more scientific, reasonable, and improves the quality and efficiency of the electric energy itself. What is more important, smart grids are also highly compatible [2]. The smart grid can collect information related to the power system as scheduled, including electricity consumption, power and frequency. Moreover, it can also signal voltage according to specific conditions through intelligent applications in the information exchange network. When a fault occurs, it can also be protected through monitoring in time, and the most reasonable treatment can be made for the existing lines and other possible faults to ensure the continuous and stable power consumption. In addition, the timeliness of information collection for power design is also reflected in the accuracy of related variables such as voltage and current. These data provide a fundamental basis for future power system work [3]. With the rapid advancement of power electronic technology and the continuous demand for living environment and life experience, people’s concepts have begun to gradually change, and now they are gradually pursuing lighting quality and emphasizing the comfort of the lighting environment. At present, household lighting is based on long-life, efficient, safe and stable lighting electrical products to improve the conditions and quality of people’s work, study and life, thereby creating a safer, more efficient and comfortable environment.
2 Materials and Methods 2.1 Chinese Smart Grid Concept Materials and Power Energy Methods The global needs are gradually increasing where resources have become increasingly scarce. This contradiction urges Chinese government to begin to pay more attention
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to the utilization of resources. The application of power design technology in smart grids solves the problem of power resources. In China most wind power generation is located in the northwestern regions with better wind energy conditions. However, if the local smart grid technology is not good, it will cost a lot of resources to develop and improve it that make it impossible to increase the utilization rate of electric energy. In addition, although wind power is a clean energy source, it has certain shortcomings. For example, the sharpness is an uncontrollable factor, which will affect the quality of power to a certain extent. The prospects of Chinese future power technology still lie in energy saving and environmental protection, so the problem of low resource utilization must be improved in the design of smart grids. Wind and solar power generation has become a widely used power generation method in China. In the near future the power generation lines used in the grid will rely on photovoltaics, because photovoltaics have strong stability and can make power supply more reliable. For related domestic technologies, even if there is a certain gap with foreign countries, energy conversion technology has made certain progress in the application process. It is used in the construction of smart grids despite the fact that it has not yet reached a mature state. Technology can realize the regeneration and utilization of energy, which not only reduces energy consumption, but also allows energy to be fully utilized, which is fully in line with the concept of sustainable ecological development in China [4]. The Chinese power quality optimization technology was first proposed to measure the operating status of electrical energy. By analyzing the operating status of electrical energy, targeted improvements can be made to ensure the continuous enhancement of power quality. It is vital to ensure that the following work is optimal to make the smart grid fully reflect its role in the power quality optimization technology. First of all, the power quality rating evaluation mechanism must be improved, so that the technology can be more convenient while performing. In addition, the technology must be combined with other processes to ensure the quality of power to the greatest extent and reduce energy consumption. Chinese superconductivity technology is to integrate superconductor and electric power technology. The characteristic of superconductor itself is that the resistance is extremely small and can be regarded as zero. Therefore, in the application process of electric power system, the superconducting system and electric power system can be combined. To increase the capacity and transmission capacity of the motor itself, this technology is a brand-new technology in the power system. If this technology is used reasonably, it can ensure a higher degree of safety and reliability of the grid operation, and give future intelligence. At present, direct current (DC) power is usually used in the power transmission process of the smart grid, and alternating current (AC) power is used in the power generation system. DC transmission has a large amount of electricity and high stability, which makes its application in the smart grid very effective. At the transmission end of the transmission line, the transformer sends the alternating current to the rectifier, which can be transformed into high-voltage direct current through the transformation, and then flows into the input line. In some long-distance power transmission systems, China usually adopts high-voltage direct current transmission
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technology. The application of this technology can not only overcome the disadvantages of long-distance, but also make the transmission efficiency higher. Especially in some remote places, the application advantages of this technology are more obvious. One more technology is Smart Substation [5] based on the realization of the informatization and standardization of the entire substation. It automatically measures, collects, and monitors various information data, analyzes the operation of the power grid system in depth, implements intelligent adjustment methods, and can also perform online analysis and decision-making work, strengthen communication and interaction with other substations and grid dispatching systems. Smart substation is composed of smart equipment, secondary equipment, and automation equipment. Intelligent equipment includes basic primary equipment, intelligent components, merging units and intelligent terminals; the main functions of secondary equipment are remote input and output, communication and protection; automation systems can collect, measure, and control the data of the entire station equipment for engineering. The status of various equipment in the intelligent substation can be monitored online. The intelligent primary equipment uses sensing and detection methods to determine the operating status of the primary equipment, and conducts preliminary analysis of the equipment when encountering problems, effectively judging and displaying the fault location, fault development, identify the fault signs of the system, and perform equipment maintenance in advance based on the diagnosis results, and conduct online monitoring of the entire process for the devices in the substation. In the smart substation project [6], the security operation and maintenance personnel and management personnel can use the remote smart substation monitoring system to monitor key equipment and operating status at any time. This is specifically reflected in the following aspects. First, the operation and maintenance personnel can remotely monitor the power supply system of the substation, environmental operating parameters. Secondly, the substation can be connected with alarm control equipment and switching devices, and perform pre-set actions in the event of an alarm. Finally, operations can be performed through authorization process, accurately record each operation, and then can query and count the operation records and automatically restart remotely in case of an abnormal problem. In smart substation projects, technicians need to focus on bay level equipment and transform the operating state of substation bay equipment into one-button intelligent operation. This system and the original station control level branch operation are more convenient, and it is the switching operation of the substation. The safety and convenience of the system are guaranteed to reduce the occurrence of operational errors. For example, in the process of intelligent load shedding applications, operators need to provide fast load shedding functions, using one-button smart operation to complete load shedding, which can be completed within 200 ms after the system is disturbed, which can save more operation time.
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2.2 Chinese Management System of Smart Grid The card issuance management module in China includes four modules: home labeling, label configuration, label inspection, label change management. It mainly completes the posting of user RFID tags, the configuration of user tags and customers, read the tags for consistency checks, and correct or replacement of lost labels [7]. After the security check terminal duty officer enters the security check task into the system, the patrol inspector uses a handheld patrol instrument to download the patrol check task through a wireless network such as GPRS/WIFI. The inspectors then patrol each district and input the results into the system through the handheld instrument. If you need to take pictures, inspectors can take pictures with a handheld inspection instrument and upload them to the server via wireless network. In addition to plan management, it includes a series of 7 modules including scientific formulation of construction safety management plan, plan implementation tracking, security inspection plan adjustment, security inspection task adjustment and security inspection appointment. It mainly completes the formulation of annual and monthly security inspection plans for large customers, industrial and commercial households, and small and medium-sized customers, and assigns security inspection tasks to specific security inspection personnel. At the same time, the system also supports security inspection personnel and security inspection personnel in the case of postponement of security inspection tasks and changes in security personnel. Security check task or security check time adjustment [8]. Security inspection is a module that runs on handheld terminal devices. The module is mainly composed of 7 modules including security inspection task download, temporary task download, appointment reminder, task reminder, due and overdue reminder, security inspection record and security inspection result submission [4]. For the problems found in the audit process, the data audit module can generate temporary tasks and send them to the security inspectors in the form of temporary tasks through the communication server. At the same time, the security inspectors send back to the management center system in the form of a problem feedback form after completing the problem processing, reviewed and confirmed by the data reviewer. The early warning and alarm module is mainly used by the system to analyze the user security inspection result information according to the customer safety early warning rules and alarm rules, and perform security early warning and alarm processing for users who meet the conditions. The troubleshooting verification management is used to manage the maintenance personnel’s early warning information and alarm information for customers, as well as the abnormal problems and safety hazards detected during the on-site security inspection. After the problems are resolved, the obstacles are eliminated, confirmed and archived.
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The query and statistics function inside the system can usually perform system data query and statistics of related information, which can not only accurately and reliably summarize the data, but also perform intelligent statistical analysis of the data.
3 Results and Discussion China is going through the stage of the continuous development. It provides an incentive to the application and popularization of smart grid technology. Regarding the progress in Chinese economy, science and technology, smart grid technology has begun to be applied in various fields, and has achieved considerable results. Smart technology will naturally be used in the Chinese power industry. In today’s highspeed two-way communication network, the application of smart grid can make the entire power system safe and reliable, which can not only guarantee the demand for electricity, but also support the concept of ecological sustainable development. Technicians need to use the power quality database as the basis to establish a complete power quality solution based on the relevant content of data integration, data analysis, and expert decision-making. Technicians should introduce advanced technology to obtain more related information in the event of a failure, such as the amount of failure, recording data, alarm information, fixed value, protection version, and also need to establish a failure analysis model to determine the type of failure and take corresponding measures to optimize. In addition, the accident analysis auxiliary decision-making expert system simulates the expert’s decision-making process to obtain more results. In the development of smart substations, the information of all substations and regional power grids can be shared, and it will be possible to configure the site protection of the whole station and regional power grid information. Realtime synchronous measurement data can be used to realize system detection, analysis and other functions. To determine the amount of alternative energy used in the world, the authors conducted an analysis of various sources of literature. The results showed that the growth of alternative energy sources is increasing every year, the most rapidly developing in Brazil, China, Turkey, Poland (Fig. 1). Based on Fig. 1, we can see that compared to 1996, the market for alternative energy has grown significantly. The most rapid pace of development has been observed since 2008, which allows us to draw conclusions about the need for alternative energy sources, as well as the use of smart technologies to improve the process of electricity supply.
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1400 1200
MW
1000 800 600 400 200 0 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 year Fig. 1 The growth of alternative energy sources
4 Conclusions To conclude, smart substation engineering [5] is a key content in modern power systems in China, and technicians must pay attention to it. It is also necessary to strengthen the attention to the design of electrical automation technology, fully consider the economy and safety of substation engineering, and improve smart substation engineering. For quality, designers also need to formulate corresponding design plans based on standard specifications and requirements to provide quality for subsequent maintenance and operation of smart substation projects. In Russia, the smart grid idea currently acts as a concept of an intelligent activeadaptive grid, which can be described by saturation of the network with active elements that allow changing the topological parameters of the network; a large number of sensors that measure current operating parameters to assess the state of the network in various operating modes of the power system; data collection and processing system (software and hardware systems), as well as means of control of active network elements and electrical installations of consumers; the presence of the necessary executive bodies and mechanisms that allow in real time to change the topological parameters of the network, as well as interact with adjacent energy facilities and high speed of the control system and information exchange. On the basis of these findings, it is possible to give a fairly clear definition of an intelligent network as a set of software and hardware consumers connected to generating sources and electrical installations, as well as information, analytical and control systems that ensure reliable and high-quality transmission of electrical energy from the source to the receiver at the right time and at the required amount.
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At the level of conceptual Russian laws, it is possible to determine the prerequisites for the development of domestic intellectual energy. According to the current Energy Strategy, the following aspects are identified as priority areas of scientific and technological progress in the electric power industry, such as creation of highly integrated intelligent backbone and distribution electric grids of a new generation in the Unified Energy System of Russia; the use of lowtemperature superconducting induction storage of electrical energy for electrical networks and guaranteed power supply to responsible consumers; widespread development of distributed generation; development of power electronics and devices based on them, primarily various kinds of network controlled devices; creation of a highly integrated information and control complex for operational dispatch control in real time with expert calculation systems for making decisions; creation and widespread implementation of centralized emergency management systems covering all levels of the Unified Energy System of Russia; creation of automated systems for managing the demand for electricity and creation of hydrogen energy storage systems and coverage of irregularities in the load schedule.
References 1. Yongmei, Jing L, Peng W (2019) Research on power design based on smart grid. Chin Minor 4:247–248 2. Zhihui L (2015) Innovative research on power design management. Commun World 2:181–182 3. Huaiqun W, Mingzhu Z (2018) Application analysis of electrical automation in electrical engineering. J Beijing Polytech Inst 17(1):34–54 4. Jianfei C, Huayong W, Huijun Z (2018) Research on construction safety management system based on internet of things and RFID technology. China Constr 10:66–67 5. Jianglong L (2019) Design and application of electrical automation in smart substation engineering. Eng Constr Design 9:171–173 6. Ke D, Xia W (2019) Characteristic analysis of electrical design of 110kV smart substation. Integr Circ Appl 36(4):75–76 7. Xun L (2017) Gas safety management system based on RFID and internet of things technology. Constr Technol 16:17–18 8. Bingyan F (2013) Analysis of international market competition in power design industry based on Porter’s five forces model. Economist 6:48–49
Prediction of the Service Life of Hybrid Ceramic Bearings by Integrated Deep Learning and Particle Filter Methods Xingyu Chen , Miao Dong , Longping Yi , and Zhiyun Wang
Abstract Bearings are one of the most critical components in many industrial machines. Predicting remaining useful life (RUL) of bearings has been an important task for condition-based maintenance of industrial machines. One critical challenge for performing such tasks in the era of the Internet of Things and Industrial 4.0, is to automatically process massive amounts of data and accurately predict the RUL of bearings. This paper addresses the limitations of traditional data-driven prognostics, and presents a new method that integrates a deep belief network and a particle filter for RUL prediction of hybrid ceramic bearings. Real data collected from hybrid ceramic bearing run-to-failure tests were used to test and validate the integrated method. The performance of the integrated method was also compared with deep belief network and particle filter-based approaches. The validation and comparison results showed that RUL prediction performance using the integrated method was promising. Keywords Prognostics · Deep learning · Particle filter · Bearing · RUL prediction
1 Introduction Mechanical big data has the characteristics of large volume, diversity, and high velocity. The prediction of remaining useful life (RUL) has been used as an important parameter for condition-based maintenance decision making [1]. Traditional data-driven prognostic methods have their limitations for processing mechanical big data. Many prognostic methods are developed based on explicit model equations [2]. Therefore, they are largely dependent on human expertise and knowledge in model building and signal processing, and hence are difficult to implement for automatic processing of massive data. These prognostic methods include recurrent neural networks [3, 4], Kalman filters [5–7], dynamic Bayesian networks [8], kreliable decentralized prognosis [9], particle filter-based [10–13], and combined particle filter and neural networks [14]. In addition, some fuzzy systems-based X. Chen · M. Dong · L. Yi · Z. Wang (B) Chongqing University of Posts and Telecommunications, Chongqing 400065, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_98
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approaches for prediction have been developed [15]. However, in comparison with fuzzy systems, particle filters take a probabilistic approach, in that the posterior distribution is modeled by sampling from a set of distributions, whereas in fuzzy systems the model output is based on the input variables of fuzzy set membership and an implication of rules. Among all the approaches, particle filters [16] have emerged in recent years as a comparatively good RUL prediction method and are becoming more and more widespread, mainly due to their capability of dealing with dynamic systems characterized with nonlinear and non-Gaussian natures. For example, Yoon and He [17] showed the superior RUL prediction performance of a particle filterbased approach using the gear data provided by the NASA Glenn Spiral Bevel Gear Test Facility. In this paper, a new integrated method that combines a deep belief network with a particle filter for remaining useful life prediction of hybrid ceramic bearings using vibration signals was presented. Real vibration data collected from hybrid ceramic bearing run-to-failure tests were used to test and validate the integrated method. The performance of the integrated method was also compared with a deep belief network and particle filter-based approaches.
2 Validation 2.1 Hybrid Ceramic Bearing Run-to-Failure Test Setup The hybrid ceramic bearing run-to-failure tests were performed using a bearing test rig in the laboratory as shown in Fig. 1. The bearing test rig consisted of the following main components: (1) 3-HP AC motor with a maximum speed up to 3600 rpm and variable speed controller; (2) Hydraulic dynamic loading system with a maximum radial load up to 4400 lbs or 19.64 kN; (3) Integrated loading and bearing housing. The rig can be used for testing both ball and tapered roller bearings. An automatic data acquisition system was constructed using a National Instrument CI 4462 board (NI, Austin, TX, USA) and NI LabVIEW software (LabView 2012, NI, Austin, TX, USA). The automatic data acquisition system is characterized with the following key features: (1) Maximum sampling rate up to 102.4 kHz; (2) 4 Input simultaneous anti-aliasing filters; (3) Software-configurable AC/DC coupling and IEPE conditioning; (4) Vibration analysis functions such as envelope analysis, cepstrum analysis, and so on for computing necessary condition indicators. The tested hybrid ceramic ball bearing was a SMR6205C-ZZ/C3 #3 L55/MG2 type bearing by Boca Bearing Company (Boca Bearings, Boynton Beach, FL, USA). It consisted of stainless steel inner outer races, and ceramic balls. The bearing was mounted on the test rig. Two accelerometers were stunt mounted on the bearing
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Fig. 1 The bearing run-to-failure test rig
housing in the direction perpendicular to the shaft. During the tests, the rig was run at a speed of 1800 rpm (30 Hz) and was subjected to a radial load of 600 psi. Vibration data were collected with a sampling rate of 102.4 kHz for two seconds at each sampling point. There was a 5 min gap between any two sampling points. At the end of the test, the test bearing was disassembled, checked, and photographed. The bearing data contained a total of 849 data files with a length of approximately 71 h. Table 1 describes the run-to-failure test setting. Table 2 provides the specifications of the tested bearing. The root mean square (RMS) of the vibration signals was computed to represent the degradation of the bearing over time during the run to failure tests. The RMS at each time interval (denoted as RMSt) can be calculated as follows: R M St =
1 n f2 i=1 ti n
(1)
where fti represents the ith raw vibration data point at time interval t and n is the length of the signal at time interval t.
Table 1 The settings of the run-to-failure test Test bearing name
Type of bearing
Load (psi)
Input shaft speed (hz)
B2
Hybrid ceramic bearing
600
30
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Table 2 Specifications of the test bearing Parameter
Specification
Bearing material
Stainless steel 440c
Ball material
Ceramic SI3N4
Inner diameter (d)
25 mm
Outer diameter (D)
52 mm
Width
15 mm
Enclosure
Two shields
Enclosure material
Stainless steel
Enclosure type
Removable (S)
Retainer material
Stainless steel
ABEC / ISO rating
ABEC #3/ISOP6
Radial play
C3
Lube
Klubber L55 grease
RPM grease (1000 rpm)
19
RPM oil (1000)
22
Dynamic load (kgf)
1429
Basic load (kgf)
804
Working temperature
121
Weight (g)
110.32
For the bearing data, the RULt (remaining useful life at time t) was calculated simply by taking the time index of the maximum recorded RMS value as the point of failure denoted as RMSTend and subtracting it from each time step: RU L t = R M STend − t
(2)
The raw vibration signals were preprocessed using the fast Fourier transform (FFT), and the FFT values were used as the only signal feature input into the integrated DBN-particle filter model to predict the RUL of the bearing. The FFT, which is an efficient algorithm for computing the discrete Fourier transform (DFT) at a time interval t, can be calculated as follows: D F Ttn =
N −1 k=0
f tk e
−2πikn N
(3)
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Equation (2) transforms the vibration signals from a time domain to a frequency domain in which we extracted ten equal bands ranging from 0 to 20 kHz.
2.2 Hybrid Ceramic Bearing RUL Prediction Results A total of 849 time steps were extracted from the bearing data in which all the data up until time step 792 were used. In the test, a rather large dip in the RMS values occurred from time steps 720 through 735. Features collected from those points were simply removed from the data and treated as outliers. L = 1 and L = 10 were used to predict 5 min and 50 min into the future for the bearing data, respectively. The predicted RUL values for the last 100 steps was seen in the next test for L = 1 and L = 10, respectively. The error metrics and hyperparameters of the DBN with L = 1 and L = 10 are provided in Tables 3 and 4, respectively. Table 4 shows the hyperparameters of the DBN for the state transition model which were determined using a grid search. Input data was also scaled to be in [0, 1], d = 100 was set as the embedding dimension, B was set as 50, M = 10, K = 5, P = 1000 and 50 particles were used for both L = 1 and L = 10 predictions. The predicted results show for both L = 1 and L = 10 that it can accurately predict the true RUL, and as the bearing approaches the point of failure, the accuracy of the predictions tends to increase. The confidence bounds for the L = 10 predicts the RUL of the bearing slightly early when compared to the L = 1 predictions and exhibits a greater variance. Table 3 Root mean squared error (RMES) and mean absolute percentage (MAPE) results Combined DBN and particle filter-based approach RMSE
MAPE (%)
α—λ Accuracy
1
2.04
7.33
0.80
10
3.52
8.68
0.61
RMSE
MAPE (%)
α—λ Accuracy
1
2.53
7.47
0.71
10
3.65
8.73
0.53
L
Particle filter-based approach L
Table 4 Hyperparameters of the deep belief network (DBN) L
DBN learning rate
DBN epochs
Hidden layer structure
FNN learning rate
FNN epochs
1
0.002
74
[146. 53]
0.0017
176
10
0.0023
82
[120. 54]
0.0014
92
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The common error metrics used in Table 3 are the root mean squared error (RMSE), α − λ metric [18, 19], and the mean absolute percentage error (MAPE). The MAPE, RMSE, and α − λ metric are defined by the following equations: 1 n At − Ft ) ∗ 100% t=1 n At 1 n RMSE = (At − Ft )2 t=1 n
M AP E = (
(α − λ)tλ =
1 i f (1 − α)RU L tλ ≤ RU L tλ ≤ (1 + α)RU L tλ 0 other wise
(4)
(5)
(6)
In Eqs. (4) and (5), At denotes the actual value, Ft represents the predicted value, and n equals the number of points to be predicted. In Eq. (6), α represents a user specified bound level, RUL tλ represents the actual RUL at time tλ , and RUL tλ represents the predicted RUL at time tλ . λ is given as a percentage of RUL for a given equipment (i.e., tλ = 50% represents the time index where half the RUL is left). The reported α − λ in Table 3 represents the average α − λ metric across the all testing samples. In the α − λ metric, results closer to one indicate better performance. The loss functions used to train the state transition models for L = 1 and L = 10 were the MSE (RMSE 2) and the MAPE respectively. Satisfactory hyperparameters for building up Equations for both L = 1 and L = 10 were set as [105, 59] for the hidden layer structure using 122 epochs with a learning rate of 0.00085. The hyperparameters for the reconstructed mono-dimensional measurement data were set as [142, 87] for the hidden layer structure using a small learning rate of 0.0094 and 212 epochs. The hyperparameters for each built network was done by employing a grid search and evaluating candidate hyperparameters on the MSE using a tenfold cross validation on the training set. Cross validation is a widely used method to avoid overftting when selecting hyperparameters [20]. The chosen hyperparameters were obtained by those that minimized the MSE during cross validation. For all of these networks, the activation function was set as the rectified linear unit (ReLU) function. It solves the vanishing gradient problem that other non-linear activation functions can cause [21]. The ReLU activation function for the input x of a neuron is defined as: RelU (x) = max{0, x}
(7)
Since the particle filter is the most competitive RUL prediction method for bearings, for a comparison purpose, the RMSE and MAPE of the RUL predictions obtained by the particle filter-based approach are also provided in Table 3. In comparison with the results obtained using the particle filter-based approach, the RMSE and MAPE values of the integrated approach were slightly lower and the α − λ metric values were higher. Note that since in [22], it was reported that using the same bearing data, the particle filter gave a better RUL prediction accuracy than a DBN
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based approach did, we consider the integrated method presented here as better than the DBN-based approach used on the same dataset. The comparison results showed the promising performance of combining the deep learning based approach with particle filter for hybrid ceramic bearing RUL prediction. Given that the integrated approach did not require explicit model equations like the particle filter-based approach and is scalable for big data applications, the RUL prediction performance achieved by the integrated approach has shown great potential for bearing RUL prediction with big data.
3 Conclusions Predicting the remaining useful life of bearings has been an important task for condition-based maintenance of industrial machines, as bearings are one of the most critical components in these machines. To meet the challenge of automatically processing massive data and accurately predicting RUL of the bearings in the era of the Internet of Things and Industrial 4.0, this paper addressed the limitations of traditional data-driven prognostics by presenting a new method that integrates a deep belief network and a particle filter for RUL prediction of hybrid ceramic bearings. Real vibration data collected from hybrid ceramic bearing run-to-failure tests were used to test and validate the integrated method. The performance of the integrated method was also compared with DBN and particle filter-based approaches. In comparison with the RUL prediction results obtained using the particle filterbased method, the prediction accuracy measured by RMSE and MAPE of the integrated method is slightly lower. Also, based on the previous comparison between DBN and the particle filter methods for the same dataset reported in [22], the RUL prediction performance of the integrated method is considered better than the DBN method. The validation and comparison results showed the promising RUL prediction performance of the integrated method. Since the integrated approach was a purely data-driven approach, future work should focus on increasing user confidence in the method. This may be accomplished by combining the integrated approach with other techniques such as employing the use of fuzzy similarity. This would require a large database of run to fail trajectories that can be compared based on their similarity with the observed data. This large database should not only increase the accuracy of the integrated approach, but also further validate it. Additional work may also include the processing of the raw vibration signals at each sampling interval by a DBN into a single dimension signal feature that can be used for prognostics.
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Resource-Efficient Use of Hydrocarbon Raw Materials as a Factor in the Transition to a “Green” Economy Oleg Andreev
Abstract The relevance of the study is determined by the fact that the current environmental situation necessitates the transition of sectors of the national economy from technogenic to sustainable environmentally balanced development, which will allow the transition of the industry to the principles of “green economy”. Resource conservation and increasing the level of resource efficiency in the use of hydrocarbon raw materials are priority issues, the solution of which will help to implement a set of energy, environmental and economic tasks for the transition to “green” development. Increasing resource efficiency will have a positive impact on the environment, as reducing the consumption of raw materials will significantly reduce waste and emissions. In the context of the growing shortage of non-renewable resources, the aggravation of environmental problems, the introduction of resource-saving and resource-efficient innovative “green” technologies aimed at the production of new types of “green” products is a necessary condition for the successful development of the economy and the preservation of the environment. In this regard, it is necessary to achieve the effect of “decoupling”, which implies an increase in the resource efficiency of the use of raw materials while reducing environmental risks. The most important direction of Russia’s transition to “green development” is to increase the complexity of the use of raw materials, increase the depth of processing, processing and disposal of by-products, production waste through their recycling. The novelty of the study is the reduction of the burden on the environment, based on the comprehensive use of environmentally friendly low-waste technologies. Keywords “Green Economy” · Resource Efficiency · Sustainable Development · Hydrocarbon Resources · Innovative Transformations · Integrated Use · Environmental and Economic Efficiency · Decoupling
O. Andreev (B) Samara State Economic University, 141, Soviet Army Street, Samara 443090, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_99
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1 Introduction In the context of globalization and regionalization, economic, political and environmental processes are influenced by both positive and negative factors. One of the positive factors of globalization, contributing to the accelerated growth of the national economy, is the expansion of access to world markets for capital, goods, services and modern technologies. Along with positive factors, globalization carries potential threats to sustainable development of the national economy, namely: one-sided development of the raw materials sector of the economy; reducing state control over basic industries; degradation of non-resource domestic industries producing products with high added value; aggravation of socio-economic and environmental problems. The current growth rates of the extraction of fuel, energy and other mineral resources, along with their underestimated economic assessment, determine a high degree of degradation of natural ecosystems. In this regard, the implementation of an adequate environmental policy in the sectors of the fuel and energy complex, as well as the development of tools and mechanisms for its implementation, is of particular relevance. In the context of globalization and many countries entering the trajectory of sustainable development, a number of international mechanisms have been developed and tested, participation in which allows the industries of the fuel and energy complex, on the one hand, to increase economic efficiency, on the other hand to reduce the negative impact on the environment. The complex of environmental instruments and mechanisms used does not allow to solve the problems of environmental degradation in the areas effectively where the objects of the fuel and energy complex are located. Degradation of the environment becomes the reason for the deterioration of the quality parameters of the life of the population. The incidence of the population is increasing, the problems of reproduction are aggravated, and life expectancy is decreasing. In this regard, the development of economic mechanisms to reduce the negative impact of the enterprises of the complex on the environment and at the same time prevent the deterioration of financial performance is an urgent task of science and practice.
2 Review of Literature Currently, it is legitimate to talk about the introduction of a new factor of production – the assimilation capacity of the natural environment. Local and global changes in the environment directly affect the economy and health of the population. They indicate that humanity in its development has crossed the permissible limits of impact on the environment, determined by the laws of biotic self-regulation of ecosystems. In the context of globalization, the assimilation capacity of natural ecosystems is becoming the main limiting factor in the economic development of countries.
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The production of new goods is impossible without the consumption of natural resources and the impact on the environment, the destruction of which affects human physiology and the quality of the life [1]. Solving the problems of reducing anthropogenic impact on the environment in the context of economic globalization dedicated to the works of such scientists as S.N. Bobylev, A.A. Golub, A.A. Gusev, V.V. Glukhov, K.G. Hoffman, V.I. DanilovDanilyan, J.A. Dixon, D. Dudek, M.Ya. Lemeshev, T.V. Lisochkina, K.S. Losev, A. Markandiya, G.M. Mkrtchyan, N.P. Nesterov, A.P. Nesterov, E.V. Ryumina, E.B. Strukova, A.V. Yablokov, etc. Despite the relevance and significance of these developments for the theory and practice of economics, they do not consider the ways of a comprehensive solution to the transition to a “green economy”. At the same time, the accelerated rates of development of the national economy, accompanied by an increase in environmental threats, require the search for new approaches to increasing the economic efficiency of production.
3 Methods The “green” economy concept is the basis for the implementation of the sustainable development strategy. Sustainable development based on the principles of a green economy contributes to the preservation of environmental parameters of the environment, as well as the preservation of normal reproduction processes. The country’s development strategy is aimed at building a sustainable and effective model of the economy based on the transition to “green” development, at maintaining the pace of economic activity while minimizing the use of resources, including hydrocarbons, and reducing environmental risks. Greening of the economy is the basis for environmentally balanced development, since the principles of sustainable development can only be implemented if environmental requirements associated with reducing resource intensity and increasing energy and resource efficiency are met, which entails the need, in turn, to greening industries and technologies [2]. Greening of the production is a tool for ensuring environmental safety and achieving sustainable development, combining socio-environmental and economic processes based on the adoption of interconnected economic, technological and social decisions that contribute to the effective achievement of environmental goals and objectives. Greening of oil refineries within the framework of the concept of sustainable development presupposes an increase in their efficiency and a decrease in resource intensity, i.e. achieving a decoupling effect, in which production should be aimed at increasing resource efficiency and at the same time reducing waste and emissions, i.e. to minimize environmental risks.
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Production waste (solid, liquid, gaseous)
Raw materials Technological process Energy
Useful Energy emis-
Fig. 1 Unclosed (open) diagram of technological processes
There are three types of technological production processes: unclosed (open), closed and isolated. The overwhelming majority of existing technological processes operate in open circuits, the use of which assumes the presence of waste in solid, liquid and gaseous form, as well as energy emissions (Fig. 1). All operating oil refineries have open technological processes, which causes significant emissions at these enterprises into the atmosphere, hydraulic system, soil, which entails a negative impact on ecosystems. When using a closed circuit, solid, liquid and gaseous emissions are completely absent, but energy emissions can exist (Fig. 2). Such technological schemes are classified as low-waste. Theoretically, it is possible to create isolated processes in which there is no waste and emissions in any form (Fig. 3), that is, such technological processes that are commonly called wasteless. Technological processes must be considered from the standpoint of their environmental friendliness, i.e. the extent to which they affect the environment. If the processes, affecting to a certain extent on the parameters of the environment, Raw materials
Technological process
Energy
Useful products Energy emissions
Fig. 2 Closed diagram of technological processes
Raw materials
Energy
Technological process
Fig. 3 Isolated diagram of technological processes
Useful products
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generally do not disrupt the functioning of ecosystems, then they can be considered relatively environmentally friendly. Technological processes that have a negative impact on the environment and create increased man-made loads are considered non-ecological. At the same time, even closed technological processes can be non-environmentally friendly, provided there are thermal emissions, noise, etc. [3]. Achieving the decoupling effect is possible when the following conditions are met: – improvement of existing and implementation of innovative low-waste technologies with closed cycles, aimed at increasing the resource efficiency of the use of raw materials; – a significant decrease in the number of resource-intensive industries with a high in quantitative terms level of emissions and waste in the sectoral structure of industry; – all-round development of related industries with closed technological processes aimed at using secondary resources and wastes of the main industries; – construction and use of treatment facilities that meet modern realities, having a high degree of emission capture rate and production waste disposal. The most acute issue of efficient energy consumption is facing the oil refining industry, since it is a major consumer of energy resources. The problem of reducing the energy intensity of the oil refining sector is that it is perceived as producing, not consuming energy resources. At the same time, it is this industry that is characterized by a high level of energy intensity, which in the future may increase under the influence of market factors, one of which is the rise in energy prices. Increasing the energy intensity of oil refineries must be attributed to the country’s strategic objectives, since energy conservation is the main way to ensure energy security. Energy resources necessary for internal needs can be obtained not only by increasing the extraction of raw materials, building new energy facilities using traditional technologies, but also by introducing innovative technologies for generating electricity from alternative sources. The main role in increasing the efficiency of energy use is assigned to modern energy-saving technologies, because their use allows saving energy resources, increasing production efficiency and minimizing negative consequences for the environment. It should be noted the possibility of using inexhaustible and environmentally friendly solar energy in the oil refining industry, which can be quite efficiently used for conversion into thermal, chemical, electrical and mechanical energy [4]. One of the directions of using renewable energy sources is the introduction of solar radiation sources into industrial production for heating oil raw materials in various technological processes and for transporting high-viscosity oil through pipelines. As you know, in the technological processes of primary and secondary processing of oil and gas raw materials (in the processes of oil distillation, adsorption drying,
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drying by cooling in thermocatalytic and thermodestructive secondary processes, etc.), a large amount of thermal energy is required for heating and cooling. In practice, heating of raw materials is carried out in tube furnaces due to the combustion of such valuable hydrocarbon raw materials as fuel oil and hydrocarbon gas. Heating of crude oil in certain processes can reach 300–350 °C, and in secondary technological processes of processing – 500 °C and above. In this case, harmful substances are formed that pollute the atmosphere with toxic components in the form of smoke. In addition to nitrogen, carbon dioxide and excess oxygen, flue gases contain harmful oxides of nitrogen, sulfur, carbon (up to 10%), as well as products of incomplete combustion of fuel. For 1 ton of refined oil, 500–600 m3 of flue gas are emitted from the furnaces [5]. The following arguments can be made in favor of using renewable energy sources: – renewable energy is the fastest and cheapest way to solve the problems of power supply for oil refineries; – the construction of renewable energy facilities does not require large one-time capital investments and pays off in a short period of time; – the latest achievements of innovative developments are implemented in renewable energy technologies. It is known that associated petroleum gas is most often flared. Preference should be given to the energy option of using associated petroleum gas, which should be considered as a high-calorific and environmentally friendly fuel for electric generators. By introducing their own power plants, oil and gas enterprises can solve the problem of supplying electricity to their own production facilities, which will significantly reduce energy costs. In addition, the flaring of associated petroleum gas at power plants is a utilization process that helps to reduce the negative impact on the environment. The experience of Russian oil and gas companies can be cited as a positive example of the use of associated petroleum gas. “Surgutneftegas” PJSC operates about 20 gas turbine power plants with a capacity of 630 mW. In the company “LUKOIL—Western Siberia” PJSC associated gas is used as raw material for power generation at seven gas turbine and gas engine generator plants. The capacity of power plants at the Vat-Yeganskoye field is 72 mW, and at the Teplinsko-Ruskinskoye field—48 mW. The largest field gas turbine power plant with a capacity of 315 mW will be built at the Priobskoye field of “Rosneft” in the Khanty-Mansi autonomous region. The main and most effective way to utilize associated petroleum gases (APG) is the construction of gas engine generator plants (GEGP) or gas turbine power plants. Most of the fields also require the construction of modern gas treatment facilities. There are no power plants capable of operating without gas treatment without significant losses.
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For example, in order to resolve the issues of associated petroleum gas utilization, the specialists of the Oil and Gas Production Department of “RITEK” company, which is the scientific and technical testing ground of “LUKOIL” PJSC (Russia), were given the task of ensuring the standardized selection of the product for the purpose of its further supply to the GEGP. A schematic diagram of a block installation has been developed, which ensures the separation of a droplet liquid from the gas and its supply to the GEGP with a given pressure and flow rate. In this case, the excess gas is discharged into the oil gathering network [6]. One of the most important tasks of the oil and gas complex is the utilization of associated petroleum gas. According to the existing legislation, companies are obliged to increase the utilization of associated petroleum gas to 95%. However, the existing disposal methods have some disadvantages, one of which is that they are economically disadvantageous. This is the reason for the unresolved problem of utilization of associated gas, as a result of which it is simply burnt in flares, which causes irreparable harm to the environment. In order to solve the urgent problem of utilization of associated petroleum gas, the Swiss company ENCE GmbH has created special installations in which electric and thermal energy is produced from fuel that was simply burned before. Such innovative installations operating on associated gas are quite efficient in terms of energy saving. The advantage of this kind of installations is reliability and the ability to operate on associated gas of any physical and chemical composition. It should also be noted their environmental safety, since they do not have harmful emissions into the atmosphere, they do not have noise pollution and vibration. In the Russian Federation, an associated gas utilization unit has also been developed, which makes it possible to be processed, utilized, and subsequently generate heat and electricity. The existing energy solutions are distinguished by such a disadvantage as the impossibility of using associated gas as a fuel due to its contamination with all kinds of impurities. Therefore, for this unit, the variable calorific value of associated petroleum gas and sulfur contamination are not critical and do not affect the performance of the complex. In order to achieve the transition to “green” development and enter the trajectory of sustainable development for the further development of the oil refining industry is deepening oil refining, and increasing the complexity of its use. The environmental factor is of paramount importance for the sustainable development of the oil refining industry. The development of petrochemical industries is a strategically important area, as it can have a significant impact on the structure of the industry in the direction of increasing its processing component. This will allow the production of a wide range of products for the production of ready-to-sell goods. The result will be an increase in resource efficiency in the use of hydrocarbons, which, in turn, will reduce environmental risks. The main task for reducing environmental risks, increasing resource conservation and resource efficiency is the development and implementation of environmentally friendly science-intensive technological solutions in production [7].
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Reducing the resource intensity of industries and the economy as a whole is a prerequisite for the transition to sustainable development. The existing technological level of oil refining industries determines the depletion of natural resources and degradation of ecosystems, which has an extremely negative effect on the economic, environmental and social situation. The development of industries that are not directly related to the exploitation of natural resources and nature protection activities can be called an urgent solution to environmental problems in modern realities. That is, there is a need to implement alternative options. Environmental measures should be implemented only if it is impossible to solve environmental problems at the existing level of development of technological processes on the basis of alternative options or low-waste and non-waste technologies. It should be noted that there is a possibility of a significant improvement in the environmental situation due to structural and technological transformations of the economy, which should be based on the environmentally balanced activities of manufacturing enterprises. The meaning of an environmentally balanced change in the structure of the economy is to stabilize the growth and production volumes of nature-exploiting and resource-extracting industries on an innovative technological basis of interconnected industries in the natural product vertical, associated with the transformation of natural substances and the production of the final product on its basis. What this means is the redistribution of labor, material, financial resources in the national economy in favor of resource-saving, technologically advanced industries and activities. Such a restructuring of the economy will significantly reduce the natural and resource intensity of production, as well as reduce the load on ecosystems. Some estimates show that the structural and technological rationalization of the economy can free up from 20 to 50% of inefficiently used natural resources while increasing economic efficiency, which contributes to the emergence of the decoupling effect [8]. Rational consumption of natural resources implies their efficient use based on innovative technological processes. The technological overconsumption of resources, as a rule, is caused by disproportions in the development of sectors of the national economy, a technological base that does not meet modern requirements, as well as a lack of sufficient motivation to save resources, etc. In economically developed countries, the rational consumption of natural resources is often tied to the concept of “best available technology” setting high scientific and technical standards for the equipment used. So, in the USA and England, such standards are established based on the choice of the most advanced economically acceptable technology. One of the ways of transition to a “green” economy can be a change in the export policy of the state. The orientation of exports mainly to crude oil and gas resources has led to a significant increase in the nature and resource intensity, which has a very negative impact on the environmental situation.
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The predominance of the share of crude oil and natural gas in the export structure has an extremely unfavorable effect on the possibility of creating petrochemical plants capable of producing high-tech products for processing hydrocarbon resources. By itself, the export of raw materials is economically ineffective and leads not only to the deterioration of the ecological parameters of the environment and the depletion of non-renewable resources, but also to the loss of significant commercial results. As a result, there is an urgent need to reorient from raw materials sources of development to innovative and high-tech. The development of oil and gas processing and petrochemical industries is a necessity for the national economy. This is due to the growth of its own requirements for the initial resources of hydrocarbons, as well as the fact that the final product of these industries is a profitable export item, as evidenced by the growing demand for it in world markets. The development of petro-chemistry can become the basis for changing not only the structure of the oil and gas complex, but also the entire national economy. Of course, the export of petrochemical products is much more profitable than the export of raw materials [9]. The priority direction in the development of the petrochemical industry is the production of synthetic fibers based on hydrocarbon raw materials, which can contribute to an increase in resource efficiency and the complexity of its use. Synthetic fibers are made from polymers obtained by synthesis from natural low molecular weight compounds. Gas and oil refined products such as benzene, phenol, ethylene, acetylene and others are used as a feedstock for the production of synthetic fibers. The scope of application of hydrocarbon products – polymeric materials, synthetic fibers, plasticizers – is extremely wide, it is practically all branches of industry, as well as social. It should be noted that the greening of the oil refining industry through the transition from technogenic to sustainable development will provide an opportunity for significant savings and the release of a large amount of raw materials, and will also reduce environmental pollution and the amount of waste while increasing the final results. Thus, combining several processes in one rectification column in the production of gasoline can help save raw materials and improve the environmental friendliness of oil refining, due to a decrease in the amount of waste. Attention should also be paid to the preliminary preparation of raw materials for processing, related to its purification from various impurities, which largely contributes to the reduction in the cost and qualitative improvement of technological processes, and the reduction of environmental risks. Thus, the purification of oil from sulfur and the desulfurization of fuel oil burned in furnaces helps to reduce emissions of sulfur dioxide (SO2 ) into the atmosphere [10]. As for the state regulation of greening processes, the main attention should be paid to the environmental modernization of production. Environmental modernization is associated with a change in the technological base of production in the field of reducing the consumption of energy, water and other resources per unit of production. The introduction of environmental innovations, which are understood as new
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products, technologies and methods of organizing production that contribute to environmental protection, is gaining relevance. We are talking about the need to introduce an environmental management system, environmental marketing, aimed at ensuring the interaction between economic development and environmental safety. However, the measures taken so far to introduce ecological techniques and technologies did not fundamentally solve the problems of resource conservation and resource efficiency [11]. The functioning, for example, of sewage treatment plants is not reliable enough, does not exclude the possibility of emergencies, moreover, their construction is quite expensive, as a result of which it is economically inexpedient. In this regard, the question arises of the reorganization of production technologies on an ecological basis: the transition to low-waste and waste-free production with full utilization. That is, the most expedient are the development and implementation of environmentally friendly biotechnologies, recycling technologies (reuse or recycling production waste), as well as low-waste technologies. The development of environmentally oriented industries will reduce the man-made impact on the natural environment, which will contribute to entering the trajectory of sustainable development and will allow the transition to a “green economy”. Taking into account the non-renewable nature of oil and gas resources, the use of non-waste and low-waste technologies in their processing will contribute to the involvement of production waste in the turnover, the possibility of their recycling, which will significantly expand the raw material base.
4 Conclusion The main direction of solving socio-economic and environmental problems is the rationalization of the use of raw materials, which consists in their complex, costeffective and environmentally friendly, that is, balanced use. The study made it possible to determine the main target areas for the development of the oil refining industry, which will implement the principles of the “green economy” concept. First of all, it is necessary to increase the depth of processing of hydrocarbon resources on the basis of the introduction of innovative technologies aimed at increasing the resource-efficient use of oil and gas and obtaining a wide range of high quality products. An increase in the Nelson index of oil refineries by equipping production facilities with technologies with a high coefficient of complexity will improve the quality of products manufactured by the refineries and process petroleum feedstocks with greater efficiency. In connection with the deterioration of the environmental characteristics of the environment, the question of introducing European quality standards for various kinds of fuels produced by oil refineries is more urgent than ever. Second, it is necessary to pay close attention to the complex processing of natural and associated petroleum gas, which is the most valuable raw material for
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the development of gas chemical enterprises for the production of polyethylene and polypropylene, which will make it possible to use gas not only as a fuel raw material [12]. Third, given the qualitative composition of oil, which contains a wide range of various chemical elements, such as sulfur, vanadium, nickel and others, which are in great demand on world markets, when processing petroleum raw materials, it is necessary to apply technologies for the complex extraction of all useful components. Rational use of raw materials through the transition to resource-efficient innovative technologies that make it possible to process raw materials with quality characteristics, the use of which is advisable only with a multicomponent extraction of products will provide a significant economic effect. Fourth, oil refining and petrochemical facilities consume significant amounts of energy and fuel (the share of fuel is up to 45%, thermal energy – from 40 to 42%, electricity – about 15% in the energy balance). The high energy intensity of a unit of production at the country’s oil refineries depends not only on the use of outdated technologies, but also, to a large extent, on the utilization of the plant’s capacities with the initial petroleum raw material [13]. Fifth, in solving the problem of rational use of hydrocarbon resources, the processing of oily production wastes, which, in particular, include oil sludge, as well as other waste suitable for secondary processing, is of no small importance for increasing the resource efficiency of their use and reducing environmental harm. The processing of oil and gas raw materials using low-waste processes will significantly reduce resource intensity and increase the resource efficiency of products. Thus, in the context of the implementation of the concept of transition to “green” development, the strategy should be aimed at the development of deep complex processing of hydrocarbon resources based on the use of economically viable and environmentally effective innovative technologies. The solution of these problems will make it possible to use valuable hydrocarbon raw materials, to obtain products with high added value.
References 1. Safin ZI, Kemalov AF, Kemalov RA, Terentyeva NA (2016) Comprehensive assessment of oil refineries and plants for the processing of heavy oils and natural bitumen. Bullet Kazan Technol Univ 9:188–191 2. Sternberg A, Makarov A, Sergeeva O (2015) Natural gas will replace the oil. World Energy 1:20–25 3. Davydova SL, Tagasov VI (2014) Oil and oil products in the environment.Instructional medium. Publishing House of RUDN, Moscow. p 163 4. Balandina AG, Khangildin RI, Ibragimov IG, Martyasheva VA (2015) Analysis of the impact of petrochemical enterprises on the hydrosphere and ways to minimize their negative impact. Bashkir Chem J 22(1):115–126 5. Belyaeva VY, Korshak AA, Shammazov AM, at al, (2017) Oil and gas construction. OMEGAL, Moscow, p 774
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6. Abrosimov AA (2015) Ecology of processing of hydrocarbon systems. Chemistry, Moscow, p 608 7. Tetelmin BV, Yazev VA (2019) Environmental protection in the oil and gas complex. Publishing House “Intellect”, Dolgoprudny, p 352 8. Filatov VV, Kulikova NV, Rukina IM, Konotopov PY (2018) Situational analysis of ensuring the innovative development of the Russian economy. Sci J NRU ITMO. Ser “Econ Environ Manag” 2:23–37 9. Muravyov AI (2018) General theory of innovative technologies. IVESEP, Knowledge, SPb, p 84 10. Kozin VG, Solodova NL, Bashkirtseva NY (2016) Modern technologies for the production of components for motor fuels. TARIH, Kazan, p 264 11. Energy Information Administration (EIA) (2002) Office of energy markets and end use, international statistics database and international energy annual 1999, DOE/EIA-0219(99). Washington, DC, Feb 2001. 2010 and 2020: EIA, World Energy Projection System 12. Bessonova TN (2016) Alternative options for solving environmental problems. Bullet Ugra State Univ 5:12–16 13. Cherepovitsyn AE (2019) Modern paradigm of oil and gas complex management as a dominant of sustainable development of hydrocarbon energy. Probl Mod Econ 24(4):35
Long Wave Dynamics in Heavy Wave Gravitating Fluid in Vlasov Type Model Tatyana Krasnoslobodzeva
and Maria Skvortsova
Abstract The article proposes a new integro-differential equation describing longwave dynamics in a layer of a heavy fluid with nonzero vorticity and a free surface. In the limit of infinitely long waves, the system of conservation laws for the integrodifferential equation transforms into the system of conservation laws for the Benny equations, which also describe the motion of a fluid with a free surface. Investigation of the solutions of the obtained equation in the linearized case made it possible to reveal the universality of the proposed equation and obtain very delicate results showing the connection between the wave dynamics of an incompressible fluid and the propagation of electrostatic waves in an electron plasma, namely, to find an analogue of Landau damping in plasma in a vortex fluid. A new dispersion relation is obtained for long waves in a vortex liquid, which generalizes the dispersion relation of a plasma with a self-consistent field to the case of a liquid with a free surface. Keywords Kinetic integro-differential equation · Transport infrastructure · Invariant solutions of the system of equations · An infinite system of conservation laws for hydrodynamic equations · Landau damping for gravitational waves · Analytical continuation of the dispersion relation
1 Introduction Despite the great successes achieved in recent years in the field of mathematical modeling in hydrodynamics, the problem of describing the generation and nonlinear propagation of waves in a liquid and gas is still relevant. For nonlinear processes, where dispersion can be neglected, the main research apparatus is the theory of hyperbolic differential equations describing wave propagation in a homogeneous liquid with a free surface. The main effect in hyperbolic systems is the occurrence of shock waves (jumps) and loss of regularity of motion. When studying this case, T. Krasnoslobodzeva (B) · M. Skvortsova MIREA—Russian Technological University (M.V. Lomonosov Institute of Fine Chemical Technologies), 86 Vernadskogo pr., 119571 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_100
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many classes of exact solutions describing important classes of fluid motions with a free surface were obtained and the group properties of the equations considered were investigated (see, for example, [1, 2]). In addition, models were analyzed and exact solutions using infinite systems of differential equations were constructed [3]. When analyzing wave processes, models were considered that do not take into account the vertical structure of water, i.e. problems averaged over a certain layer of liquid (in our case, a flat one). In addition, potential fluid movements were considered [4]. Among these models, a very general model for long waves on water with a flat bottom and a free surface is somewhat distinguished, first considered by Benny, in which an infinite system of conservation laws turns out to be closely related to the non-dispersive Kadomtsev–Petviashvili equation. The main objectives of this work are to obtain and analyze new equations describing the propagation of long strongly nonlinear waves propagating in a heavy homogeneous liquid with a free surface.
2 Materials and Methods 2.1 Kinetic Equation for Describing Long-Wave Motions in a Swirling Fluid When considering long waves on water in the hydrostatic approximation on a swirling liquid (strongly nonlinear waves), the Benny model is considered: y u t + uu x − u y (
h u x dy) + h x = 0; h t + (
0
udy)x = 0
(1)
0
Here is the time, is the spatial coordinate, is the unknown height of the free surface of a homogeneous heavy liquid, (), is the horizontal component of the velocity of the liquid. The index at the bottom means the derivative of the corresponding variable. In the considered coordinate system, the acceleration of gravity, the density of the fluid is also equal to 1, the dependent and independent variables of the problem are dimensioned. Problems with an unknown free boundary are difficult to solve, so the problem of reducing system (1) to equations that do not contain an unknown free surface, in this case, to some integro-differential equations similar to those that arise in the theory of collisionless plasma, is very important. Let’s introduce an infinite system of moments h(t,x)
A = A (t, x) = n
(u(t, x, y))n dy
n
0
(2)
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Benny showed that the system of Eq. (1) generates the following infinite system of equations for moments: + n An−1 A0x = 0, n = 0, 1, 2, 3, ... Ant + An+1 x
(3)
Kinetic equation of the Vlasov type was proposed, equivalent to an infinite chain of related Eq. (3). We introduce a distribution function (probability density), which for now we will write as, considering variables as parameters. For we define the characteristic function as follows: which for now we will write as f (v), considering variables t, x as parameters. For f (v) we define the characteristic function as follows: fˆ(k) = =
∞ n=0
∞
−∞
(−ik)n n!
f (v)e−ikv dv =
∞
∞
−∞
∞
n −∞ v f dv =
n=0
f (v)
∞ n=0
(−ik)n n v dv n!
An (−ik) n!
n
∞
Here An = −∞ f v n dv. Then the following expression of the function f (v) in terms of the moments of the function f is correct: f (v) =
1 2π
∞
−∞
fˆ(k)eikv dk =
∞ (−1)n n=0
n!
An δ (n) (v).
(4)
The following notation is used here: δ (n) (v) = d dvδ(v) is the derivative of the n Dirac functional of the corresponding order. Thus, according to these moments, the distribution function f (v) is restored uniquely, as a generalized function acting, for example, on functions from the Schwarz space with respect to a variable v. Such ∞ functions have moments An = −∞ f v n dv for any integer n ≥ 0. The following theorem is valid. Theorem. If the distribution function is defined using the formula n
f (t, x, v) =
∞ (−1)n n=0
n!
An (t, x)δ (n) (v)
where the moments An (t, x) satisfy the infinite moment system of Eq. (3), then the distribution function is a regular generalized function and satisfies the integrodifferential equation ∂f ∂f ∂f ∂ +v − · ( ∂t ∂x ∂v ∂ x
∞
−∞
f (t, x, v)dv) = 0
Proof. It consists in a direct verification of the statement of the theorem.
(5)
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2.2 Description of the Classical Shallow Water Theory and Their Vortex Generalizations Let the horizontal component of the fluid velocity u(t, x) be independent of the variable y. Then the characteristic function and the distribution function take the following form: fˆ(k) =
∞ (−ik)n
n!
n=0
1 h(t, x) f (t, x, v) = 2π
+∞ −∞
(u(t, x))n h(t, x) = h(t, x)e−iku(t,x)
(6)
ex p(−iku(t, x) + ikv)dv = h(t, x)δ(v − u(t, x)). (7)
In this case, the functions h(t, x), u(t, x) satisfy the classical system of shallow water equations h t + (uh)x = 0; u t + uu x + h x = 0. Let us now consider a generalization of kinetic Eq. (7), namely, ∂f ∂f ∂f +v − · ∂t ∂x ∂v
∞ −∞
K (x − ξ )
∂ ( ∂ξ
∞
−∞
f (t, ξ, v)dv)dξ = 0
(8)
Here K (x) is either an ordinary or a generalized function of a variable. Let’s consider a specific type of distribution function corresponding to a cold gas (shallow water), namely, f (t, x, v) = h(t, x)δ(v−u(t, x)). Then the kinetic equation will be reduced to the following generalized system of shallow water equations: h t + (uh)x = 0; u t + uu x +
∞
−∞
K (x − ξ )h ξ dξ = 0.
(9)
If we linearize system (9) with respect to a homogeneous state u = u 0 + εu 1 , h = h 0 + εh 1 , we obtain the following system of equations: h 1,t + u 0 h 1,x + h 0 u 1,x = 0; u 1,t + u 0 u 1,x +
∞ −∞
K (x − ξ )h 1,ξ dξ = 0.
(10)
Passing into a moving coordinate system x = x − u 0 t, t = t and denoting new coordinates without strokes, we obtain such a system of equations: h 1,t + h 0 u 1,x = 0; u 1,t +
∞ −∞
K (x − ξ )h 1,ξ dξ = 0.
(11)
To calculate the variance in the system under consideration, consider the particular solutions of system (11) of the following form:
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u 1 = A exp(i(kx − ωt)), h 1 = B exp(i(kx − ωt)) Such that A = 0, B = 0. After standard transformations, we obtain the dispersion relation ∧
ω/k = ± h 0 K (k)
(12)
Therefore, if we have an arbitrary function K (x), it means that we are considering a model with an arbitrary variance, with an arbitrary phase velocity ωk . We consider the dynamics taking into account the following wavelength approximation for shallow water equations. Since for the Benny equation K (x) = δ(x), where δ(x) is the generalized Dirac function, the general case has the following form: K (x) = δ(x) + αδ (x) + βδ (4) (x) + ...
(13)
Even derivatives of the Dirac function arise from the requirement of the materiality of the dispersion relation. After the Fourier transform, the relation (13) will take the following form: ∧
K (k) = 1 + αk 2 + βk 4 + ...
(14)
It is the ratio (16) that will be considered in the future, as a rule, for small k 1.
3 Results 3.1 Group Properties and Some Exact Solutions for the Theory of Shallow Water with Dispersion Kˆ (k) = 1 + αk2 Let’s consider a system of shallow water equations taking into account the dispersion in the first approximation: h t + (uh)x = 0; u t + uu x + h x + αh x x x = 0.
(15)
A test of the naturalness of modeling the modified shallow water theory is the study of the group properties of the system (15) using the technique of group analysis (see [5]). It can be proved that the set of all point transformations (Lie transformations) for system (15) is generated by the following differential operators: X 1 = ∂t , X 2 = ∂x , X 3 = t∂x + ∂u , X 4 = t∂t − u∂u − 2h∂h .
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The operator X 4 generates a group of large-scale transformations. The Galileo group is allowed for all values α, and the operator X 4 is allowed for all α = 0. Note that the type of operator X 4 does not depend on the quantitative value α = 0, which ∧
indicates the universality of the selected decomposition K (k) = 1 + αk 2 . The classical shallow water equations both over a flat bottom and an uneven one are well studied from a group point of view. The solution methods are closely related to the fact that all derivatives in the first-order problem and, in particular, the hodograph method is applicable here. In addition, some problems have been solved (exact solutions have been obtained) that have direct applied significance [2, 3]. Here is an example of an exact solution, which is invariant with respect to the operator X 4 and nontrivially depends on the variance parameter α = 0: ⎧ u0 t u0 t x ⎪ ⎨ u(t, x) = u 0 = const, h(t, x) = h 0 + (h 1 sin( √α ) + h 2 cos( √α )) sin( √α )+ u0 t u0 t ) − h 2 sin( √ )) cos( √xα ) +(h 1 cos( √ α α ⎪ ⎩ . (16) Here u 0 , h 0 , h 1 , h 2 are arbitrary constants. The presence of dispersion generates oscillatory movements. Oscillating solutions in the problem with the third spatial derivative are characteristic, for example, for the Korteweg-de Vries equation [6]. ∧
In the future, the dispersion K (k) can be called longitudinal dispersion, since it is present both in the case of a cold gas (plasma), and in our case in the absence of vertical mixing of the liquid.
3.2 Landau Attenuation for Long Waves on Water in a Liquid with a Free Surface for Arbitrary Dispersion Let us now write down the basic Eq. (8) in the form of a system of equations, so that there is a formal similarity with the one-dimensional Vlasov equations in plasma: ∂f ∂f ∂f +v − · ∂t ∂x ∂v
∞
−∞
K (x − ξ )
∂ h(t, ξ )dξ = 0; h(t, x) = ∂ξ
∞
−∞
f (t, x, v)dv (17)
We linearize the system (17) with respect to the distribution function f 0 (v). This means that we are considering a shear flow u = u 0 (y), h(t, x) = H = const. By setting the shear flow as an infinite number of moments
Long Wave Dynamics in Heavy Wave …
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H An0
=
∞ (u 0 (y)) dy =
f 0 (v)dv
n
−∞
0
you can explicitly represent a function. f 0 (v) =
∞ (−1)n n=0
n!
An0 δ (n) (v).
We consider a regular generalized function f 0 (v), so that an ordinary function f 0 (v) is an analytic function of a variable v. We present the solution in this form: f = f 0 (v) + ε f 1 (t, x, v), ε 1. Then the linearized equation will take the following form: ∞ ∞ ∂ f1 ∂ f1 ∂ f0 ∂ +v − · K (x − ξ ) h 1 (t, ξ )dξ = 0, h 1 (t, x) = f 1 (t, x, v)dv ∂t ∂x ∂v ∂ξ −∞ −∞
(18)
We take the Laplace and Fourier transforms in this form: +∞ +∞ Lu = exp(iωt)u(t)dt, Imω > 0,Fu = Lu = exp(−ikx)u(x)d x. 0
(19)
0
Applying transformations to the system (18), we obtain that ∼
h (ω, k) = 1
g(k, v) =
∞
−∞
+∞ −∞
f 1 (t, x, v)dv ·
+∞ g(k,v) ikv−iω dv −∞ +∞ f0 (v)ik K∧ (k) 1− ikv−iω dv −∞
, (20)
f 1 (t = 0, x, v) exp(−ikx)d x.
The equation +∞ D(ω, k) = 1 + −∞
∧
f 0 (v) K (k) dv = 0 ω/k − v
(21)
Is called the dispersion relation of the system (18). It can be proved that Eq. (22) has a finite number of zeros for any fixed real numbers k, Imω > 0. We fix a real number k = 0. The function D(ω, k) should be continued analytically into a part of the half-plane Imω > 0. +∞ −∞+ia ∧ ∼ 1 Let h (t, k) = exp(−ikx)h(t, x)d x = 2π exp(iωt) h (ω, k)dω, a > 0. 1
0
−∞+ia
1
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T. Krasnoslobodzeva and M. Skvortsova
We will further give some sufficient mathematical conditions under which Landau attenuation occurs. Let the function f 0 (v) belong to the Schwartz space and g(k, v) be analytic with the exception of a finite number of poles ω1 , ..., ωm not lying on the boundary of the domain G. Then. ∧
h (t, k) = i 1
m
∼
r es(eiωt h (ω, k)) + O(e−bt ).
(22)
1
j=1
3.3 Approximate Calculation of the Landau Attenuation Coefficient Near the Long-Wave Limit (k = 0) Considering the number ω = ωr to be real at this stage, we calculate ∧
1 + K (k)V dv = 0
+∞ −∞
f 0 (v) ωr k −v
∧
2
dv = 0, 1 − K (k) ωk 2 r
+∞ −∞
f 0 (v)(1 +
2kv ωr
+
3(kv)2 ωr2
+ ...)
(23)
where the integral is understood in the sense of the main Cauchy value for very small k = 0. Let’s choose a coordinate system so that. +∞ f 0 (v)vdv = 0.
(24)
−∞
Then we obtain the following expression for the group velocity in the case of arbitrary longitudinal dispersion and small vortex dispersion up to the order k 2 : ωr /k =
∧
K (k)/2 ·
A00
+
∧
∧
(A00 )2 + 12 A20 / K (k), K (k) = 1 + αk 2 .
(25)
This means that we consider an arbitrary dispersion in the neighborhood of infinitely long waves. In addition, the universality of representation (22) is clarified in clause Sect. 3.1 Omitting the calculations, we leaving the magnitudes of the order k 2 , that A0 (A0 )5/2 γ = − 18 π 1/2 (A02 )3/2 (A00 + (A00 )2 + 12 A20 )3/2 · exp(− 8A02 0 0 (A00 + (A00 )2 + 12 A20 ))k · p
(26)
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983
Then under condition p = 1/2 A00 + (A00 )2 + 12(A20 ) − 3
A20 (A00 )2 + 12(A20 )
> 0.
(27)
Here H0 A00
= H0 =
+∞ 1 · dy = −∞
0
+∞ f 0 (v)dv,A20
=
H0 f 0 (v)v dv =
(u 0 (y))2 dy.
2
−∞
0
Or amplification of a harmonic wave does not depend on the coefficient of longitudinal dispersion α. It is essential, as in paragraph 3, only the condition α = 0. We present the final result for the case of the Maxwell distribution function. f 0 (v) = c exp(−βv 2 ), c > 0, β > 0. Let’s express all constants through two main points, namely, through A00 and A20 . We will have a damped wave with a damping coefficient exp(γ t), γ < 0, k = 0.. The graph shows the lines of the level of the stability parameter p, are given. The line separates the zones of wave attenuation and wave amplification. The values of parameters p = 1 and p = 2 highlight the stability zone (Fig. 1). Fig. 1 The lines of the level of the function p = p (A00 , A20 ), separating the zones of stability and instability (p = 0), as well as indicating the zone of stability (p = 1, p = 2)
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T. Krasnoslobodzeva and M. Skvortsova
4 Discussion We will briefly describe the main results of the work. First of all, we note that the above equations are kinetic integro-differential equations with a self-consistent field, and in the vortex-free limit they are a generalized system of shallow water equations containing spatial derivatives of the third order. In addition, for the integro-differential equation describing the dynamics of a swirling fluid, the asymptotics of the linearized model is studied, the universality of the mechanism of attenuation of gravitational waves (Landau attenuation) is established, the independence of the attenuation coefficient from the model parameter is established. The classical hyperbolic system differs sharply from our problem [7].
5 Conclusion In this paper, new equations describing the propagation of long waves in a heavy liquid with a free surface are constructed. An important result is the combination of the action of vortex fluid dynamics and the dispersion of the vortex-free limit of the equations of motion of a fluid with a free surface. The results of the analysis of the integro-differential equation, in particular, the time asymptotics of the linearized equation, is universal and is expressed only by two numbers determined by the initial function of the shear velocity and does not depend on the expansion parameter of the longitudinal dispersion α. The results of this work and the methods for obtaining them are new.
References 1. Aksenov AV, Dobrokhotov SY, Druzhkov KP (2018) Exact solutions of “step-function” type for one-dimensional shallow water equations over the inclined bottom. Math Notes 104:930–936. https://doi.org/10.1134/S0001434618110354 2. Anikin AY, Minenkov DS (2018) On the run-up for two-dimentional shallow water in the linear approximation. Math Notes 106:163–171. https://doi.org/10.1134/S0001434619070204 3. Karabut EA, Zhuravleva EN (2020) Construction of exact solutions of the problem of the motion of a fluid with a free boundary using infinite systems of differential equations. Theor Math Phys 202:371–380. https://doi.org/10.1134/S0040577920030095 4. Zhuravleva EN, Zubarev NM, Zubareva OV, Karabut EA (2019) Algorithm for constructing exact solutions of the problem of unsteady plane motion of a fluid with a free surface. JETP Lett 110:452–456. https://doi.org/10.1134/S0021364019190135 5. Arrigo DJ (2018) Symmetry analysis of differential equations: an introduction. Morgan & Claypool, San Rafael 6. Guo B, Pang XF, Wang YF, Liu N (2018) Solitons. Walter de Gruyter GmbH, Berlin-Boston 7. Lebo AI, Simakov IG (2018) Modeling the evolution of whirl structures in a supersonic gas stream. Russ Technol J 6:45–54 https://doi.org/10.32362/2500-316X-2018-6-5-45-54
The System for Modeling and Visualizing 3D Algebraic Functions Andrei Beiresh
and Alexei Razumowsky
Abstract The article describes methodological, scientific and practical approaches to modern 3D modeling, which are based on the application of algebraic R-functions. To create 3D objects the method of functional-voxel modeling is used, which is successfully applied to a wide variety of tasks in the geometric formulation. Model creation is divided into three stages. The initial stage of creating a 3D model is its description in a specialized programming language. With the help of this language it is possible, using the V. L. Rvachev’s functions—R-functions, to define complex and manifold geometric shapes and operations quite easily. The second stage of model creation is its “growing” in the form of voxels, the number of which depends on the degree of required accuracy of the model, its partitioning. Here, the calculation of geometry using parallelism and shader programs on the GPU. The final stage is the visualization of the resulting models in point, voxel and smooth geometric form. The development of such a system of modeling and visualization of 3D objects will expand the horizon of solutions in the field of modern robotics, forecasting under uncertainty, as well as life cycle support systems in industrial production. Keywords 3D functional-voxel object · Voxel · Modeling · Visualization · R-function
1 Introduction For today’s rapidly evolving robotic systems, there is an urgent need to respond quickly to environmental variability. This involves satisfying multiple constraints, such as collision avoidance, communication, prediction, and planning responses to uncertainty. Such problems can be represented by stability and invariance criteria. A. Beiresh Moscow State University of Technology STANKIN, 1 Vadkovsky Lane, Moscow 127055, Russia A. Razumowsky (B) Trapeznikov Institute of Control Science of RAS, 65 Profsoyuznaya, Moscow 117997, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_101
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In modern science, Lyapunov’s functions and barrier functions are used to solve such problems [1]. Algebraic functions and Rvachev’s functions—R-functions [2, 3] can expand the possibilities of modeling robotic systems, multi-criteria solutions, creating digital twins. V. L. Rvachev’s functions have an extensive range of use in various engineering and scientific applications: from modeling of cutting [4, 5], multi-material volumes [6], calculation of optimal packaging [7] to investigation of problems of streamlined bodies [8], light propagation and laser biomedicine [9]. R-functional modeling is a method for describing models using classical functions, for example—f(x, y, z) for three-dimensional space. The main feature of this method is the ability to determine the sign of the function by the values of its arguments. To obtain a given functional domain, it is necessary to calculate the value of the function in some subspace, which is divided into a certain number of points for this purpose. This results in a voxel representation of the function, in which a voxel is a point in three-dimensional space that has a certain color [10], and possibly other characteristics as well. The voxel is most often represented by a cube, whose rendering features are discussed, for example, in [11]. The R-function describes the functional space of the model as three areas: • Negative values—area outside the model; • Zero values—area of the model surface (Fig. 1); • Positive values—internal area of the model.
Fig. 1 Voxel visualization of the sphere zero area
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Fig. 2 Voxel visualization of the conjunction of two spheres
R-functions provide remarkable opportunities for set-theoretic transformations. For example, Rvachev’s special operators are used to combine several functions into one, which preserve the signs of the functional domains: – Conjunction (Fig. 2): x∩y=
(1 + a)(x + y −
1
x 2 + y 2 − 2ax y)
– Disjunction (Fig. 3): x∪y=
(1 + a)(x + y +
1
x 2 + y 2 − 2ax y)
2 Materials and Methods 2.1 Methodology: Description of Modeling Language As methodological tools, it is convenient to use a special language for describing 3D objects, in which the concatenation of color with the algebraic description of R-functions is performed.
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Fig. 3 Voxel visualization of the disjunction of two spheres
Such language will allow to operate with algebra of functions easily and effectively (Fig. 4). R-function operations are represented as: | —disjunction, & —conjunction. The language includes several basic keywords: • arg (argument)—gives a description of the subspace of the calculation. It lists the axes of their dimensions, for example: x(2)—means that on the x-axis the space will lie within (–2, 2). You can also specify an asymmetric interval in parentheses—x(–1, 2). The names of the axes are arbitrary, this is done for the convenience of design; • const (constant)—creates a constant variable. Its purpose is to create parameters that will not participate in the calculation, but will only be numbers. They will reduce the load and increase the efficiency of code execution; • var (variable)—provides the creation of a variable to be calculated. It will be recalculated for each point in the subspace; • return—describes the result of execution, the target R-function.
Fig. 4 Fragment of the R-functional description of the 3D model
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Fig. 5 Excess variable r is not taken into account
The program code written using this language interprets the R-function description as a computation tree which combines all variables into one resultant R-function. A feature of the language is to ignore unnecessary variables and operations. In other words, if a variable is not used to obtain the resulting R-function, it will not participate in the calculation either (Fig. 5).
2.2 Calculation System Depending on the number of discrete voxel points needed to calculate the model, the execution speed will also increase, as well as the amount of resources required to visualize the voxels. For calculating a significant amount of data, it was decided to use a GPU, as it is ideal for this kind of task because of the SIMD (single instruction, multiple data) principle of computer calculations, which allows parallelism at the data level. In this case, there is a single instruction, a function, which needs to be computed on a multiple set of data—discrete points. Since modern graphics processors have considerable computing power, this approach to function space computation gives much faster results than classical computation on a central processor (Table 1). Table 1 Comparison of computation time of sphere function on GPU and CPU Number of points
323 (s)
643 (s)
2563 (s)
10243 (s)
CPU
0.064
0.477
33.611
3144.86
GPU
0.032
0.041
0.360
26.996
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2.3 Visualization After defining the functional areas, the resulting model is visualized. As mentioned above, voxels are used for visualization. Large models require large resources, especially memory. In the classical representation of the geometry through a given set of triangles for each voxel will require 36 voxels, where each vertex contains 28 bytes (Fig. 6). Thus, describing a single voxel requires 1008 bytes, which requires a significant resource. Therefore, in an effort to overcome this barrier, shaders—programs that run on the graphics processor—were used. The positive side of using shaders is the ease of manipulating graphical data during visualization (Fig. 7).
Fig. 6 Data structure of one vertex
Fig. 7 The visualization pipeline on the GPU
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All kinds of modern shaders were used in the formation of the graphical model: • Vertex shader—a vertex shader that works with each vertex, and allows you to transform the model in space to simulate the camera and perspective; • Geometry shader is a geometry shader that handles a set of vertices in a particular order of shapes. It’s a geometry shader that handles a bunch of vertices in a certain order, so you can add some extra facets, for instance, to a shape; • Fragment shader—a fragment shader, which transforms the final geometry. Its application will color parts of shapes with different colors, based on vertex colors and textures. Improving the quality of the voxel model visualization will allow the use of geometric shader. It can turn every point of space into a cube, having only the size of the cube and knowing the position of its center. The use of the main resource— memory—in this case will be reduced by several times. Instead of 1008 bytes for each voxel only 32 bytes are needed (Fig. 8). In the built simulation system we achieved the ability to visualize in threedimensional space in real time 1283 = 2,097,152 voxels on a rather weak system with 2 GB of video memory (Fig. 9).
Fig. 8 Voxel data storage structure
Fig. 9 Visualization of 2 million voxels
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Fig. 10 High-quality visualization of functional-voxel 3D models
3 Results The result of this research is a 3D software system for dynamic visualization of high-definition functional-voxel models (Fig. 10). The present system can be used for educational and research purposes in the field of graphic 3D design and modeling. The presented solution has the ability to visualize not only R-functionally described objects, but also point clouds, which are actively used in 3D-scanning and geoinformation systems (GIS).
4 Conclusions Now more than ever before, functional-voxel models should play a crucial role in research and applied fields of various sciences, as well as in the creation of specialized product lifecycle support systems based on digital twins [12, 13]. Since the power of modern computers allows effortless storage, visualization and processing of largescale functional models, they are more accurate and complete, which is cardinally important for scientific calculations and creation of serious engineering solutions in industry.
References 1. Glotfelter P, Cortes J, Egerstedt M (2020) A Nonsmooth approach to controller synthesis for boolean specifications. IEEE Trans Autom Control 66(11):5160–5174. https://doi.org/10.1109/ TAC.2020.3035467
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2. Sheiko TI, Maksymenko-Sheiko KV, Sirenko VM, Morozova AI (2019) R-functions in the analytical description of the surface of a flying wing unmanned aerial vehicle. J Mech Eng 22(4):61–66. https://doi.org/10.15407/pmach2019.04.061 3. Shapiro V (2007) Semi-analytic geometry with R-functions. ACTA numerica 16:239–303 4. Pecci F, Stoianov I, Ostfeld A (2021) Relax-tighten-round algorithm for optimal placement and control of valves and chlorine boosters in water networks. Eur J Oper Res 295(2):690–698. https://doi.org/10.1016/j.ejor.2021.03.004 5. Avsar ZM, Zijm WH, Rodoplu U (2009) An approximate model for base-stock-controlled assembly systems. IIE Trans 41(3):260–274. https://doi.org/10.1080/07408170802510382 6. Fayolle PA, McLoughlin L, Sanchez M, Pasko G, Pasko A (2021) Modeling and visualization of multi-material volumes. Sci Visual 13(2):117–148 7. Vallepuga-Espinosa J, Ubero-Martínez I, Rodríguez-Tembleque L, Cifuentes-Rodríguez J (2020) A boundary element procedure to analyze the thermomechanical contact problem in 3D microelectronic packaging. Eng Anal Boundary Elem 115:28–39. https://doi.org/10.1016/ j.enganabound.2020.02.011 8. Proskurin AV, Sagalakov AM (2019) Stability of magnetohydrodynamic flow around a circular cylinder. J Phys: Conf Ser 1382(1):012033. https://doi.org/10.1088/1742-6596/1382/1/012033 9. Panchenko VY (2011) Laser and information technologies in biomedicine. Her Russ Acad Sci 81(3):246–251. https://doi.org/10.1134/S1019331611030178 10. Tolok AV, Tolok NB (2018) Mathematical programming problems solving by functional voxel method. Autom Remote Control 79(9):1703–1712. https://doi.org/10.1134/S00051179 18090138 11. Caleb L (2017) Quads all the way down: simple voxel rendering 12. Qi Q, Tao F, Hu T, Anwer N, Liu A, Wei Y, Nee AYC (2021) Enabling technologies and tools for digital twin. J Manuf Syst 58:3–21. https://doi.org/10.1016/j.jmsy.2019.10.001 13. Fei T, Jiangfeng C, Qinglin Q, Zhang M, Zhang H, Fangyuan S (2018) Digital twin-driven product design, manufacturing and service with big data. Int J Adv Manuf Technol 94(9– 12):3563–3576. https://doi.org/10.1007/s00170-017-0233-1
Predictive Assessment of Dynamics Intellectual Activity Index National Innovation-Oriented System Elena Golovchanskaya
and Svetlana Kirilchuk
Abstract The article analyzes the dynamics of the intellectual activity index (IIA) of the national innovation system (NIS) as an object of socio-economic development of the Republic of Belarus. Improving the methodology of strategic development of the NIS, by introducing into the statistical database the methodology for determining the IIA will allow to develop additional guidelines for its development. A predictive comprehensive assessment of NIS is proposed by determining the IIA of NIS performance. The structure of the index and its sub-indexes from the point of view of the organization of activities and efficiency assessment, a set of indicators and their sources, and a calculation methodology are determined. The emphasis is placed on the key importance of intellectual resources, which determines the effectiveness of NIS. The authors give an example of the forecast calculation of the IIA of the NIS of the Republic of Belarus and its subindexes. The dynamics of the IIA and its subindexes up to 2025 are analyzed. The conclusion is made about the growth of the IIA of NIS as a whole. However, the negative trends of the sub-indices: “science” and “intellectual resources” determine the slowdown in the growth of IIA. The problem areas of the NIS of the Republic of Belarus are shown, guidelines for improving the NIS of the Republic of Belarus are proposed. Keywords Intellectual resources · Management · Research and development · Innovation · National innovation system · Index of intellectual activity
E. Golovchanskaya (B) Financial University under the Government of the Russian Federation, 49/2 Leningradsky Avenue, 125167 Moscow, Russian Federation e-mail: [email protected] Moscow State University of Civil Engineering (MGSU), National Research University, 26 Yaroslavskoe shosse, 129337 Moscow, Russian Federation S. Kirilchuk V.I. Vernadsky Crimean Federal University, 4 Acad. Vernadsky Avenue, 295007 Simferopol, Republic of Crimea © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_102
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1 Introduction Modern challenges of the world economy dictate the trajectory and rates of development of the national economic system of the Republic of Belarus. The acceleration of scientific and technological progress, the introduction of Internet technologies, the formation of the sixth technological order, increasing competition, global crisis phenomena determine the priority of the innovative development path, which is based on the intellectualization of all spheres and processes of economic activity. The core of intellectualization is human intelligence, his knowledge, the ability to reproduce them, the use of which in the framework of labor relations takes the form of resources. Fundamental, scientific and applied research on the creation of an object of intellectual property, and further innovative activities to translate innovations into innovative goods and services determine the intellectualization of resources [1]. Intellectual resources are understood by us as a set of abilities (forms) of intellectual resources that develop from basic forms to higher ones in the process of using an innovative product in social reproduction and through transformation into intellectual capital, ensuring the sustainable development of the national innovation system in order to improve the welfare of the population as a whole. The transformation of intellectual resources into intellectual capital occurs through the commercialization of an innovative product, thereby ensuring an increase in labor productivity, an increase in research and innovation performance. In fact, intellectual resources are researchers with higher education, as well as doctoral and candidate degrees, involved in research and innovation. The intellectualization of the national economic system is determined by the intellectualization of resources and the institutional mechanisms of their management and development [2]. The intellectualization of resources is carried out on the basis of their intellectual nature, institutional, economic content, which increases the importance of intellectual resources in the national innovation-oriented economic system of the Republic of Belarus (Fig. 1). Modern trends that change the structure of national economic systems, increasing the role of intellectual resources, are accompanied by the coronavirus pandemic and, as a result, a deep crisis of the world economy and crisis phenomena in the economy of the Republic of Belarus. Thus, the decline in GDP in comparable prices for 2020 amounted to 0.9% by 2019. For example, in the Russian Federation, GDP during this period decreased by 3% [3]. Key indicators of scientific activity are decreasing (Fig. 1). Internal costs for research and development in Belarus are 2 times lower than in Russia, the coefficient of inventive activity is 5 times lower than in Russia. In general, both in Belarus and in Russia this indicator is decreasing. Structural transformations of the national economy, increasing the importance of intellectual resources, a decrease in the rate of economic development of the national economy taking place against the background of the economic crisis caused by the coronavirus pandemic determine the need to improve the methodological foundations for developing directions for the development of the national innovation-oriented economic system. Such a basis can be a methodology for forecasting and assessing
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Fig. 1 Selected indicators of research activities: the coefficient of inventive activity, internal costs of research and development (RB and RF)
the index of intellectual activity of the national innovation-oriented economic system, the structure of which is based on the assessment of intellectual resources (Iia). Many works of scientists are devoted to certain areas of assessment of intellectual resources. We considered them in sufficient detail in previous studies [4]. Of particular interest within the framework of the topic of this work are the studies of the creative abilities of the individual, conducted by O. N. Melnikov, D. A. Esipenko [5]. Propensities for innovation are assessed by N. M. Lebedeva, A. N. Tatarko [6]. Questions of assessing intellectual abilities by the test method, which has already become a classical method, are evaluated in the works of Eysenck G., Rowen J. Questions of the structure of intellectual abilities, significance, assessment can be found, for instance, in resent Cambridge Handbook by R. M. Kaplan, R. J. Sternberg [7, 8]. The emotional component of intellectual abilities is investigated by D. V. Lyusin, V. V. Ovsyannikova [9]. The methodology for assessing sociocultural values was proposed by Shvarts Sh. [10, 11]. The issues of valuing values within the global workforce were investigated in the work D. A. Ralston, C. P. Egri [12]. Thus, the above arguments confirm the importance of the research topic. The purpose of the work is, on the basis of theoretical and empirical aspects, to develop a forecast of the index of intellectual activity of the national economic system as a tool for improving the directions of development of the Republic of Belarus.
2 Materials and Methods To develop a forecast for the index of intellectual activity of the national economy, we will use the linear regression method, the choice of which is due to the ease of
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use and efficiency of use over short forecast periods. To calculate the IIA index, we will rely on the methodology developed earlier, in which the structure of the index, the selection of indicators were determined and assessed using the example of the Republic of Belarus [13]. The peculiarity of the IIA index lies in the grouping of sub-indices characterizing the innovative sector of the economy, and the inclusion of the “intellectual resources” sub-index in its structure, as the most significant resource of economic activity. The Table 1 shows the main provisions of the methodology. The structure of the index is presented in detail, as it is the basis for further forecast calculations.
3 Results Based on the initial data reflected in the previous study, using the linear regression method, we calculated the predictive indicators. Further, using the rationing method, we calculated the sub-index indicators as the average of all indicators until 2025 (Table 2). Next, we defined the sub-indices of the IIA index Based on the values of the subindices, the index of intellectual activity of the national innovation-oriented economic system of the Republic of Belarus was calculated (Fig. 2).
4 Discussion On the basis of the forecasted calculations, it can be argued that the NIS RB, in general, is dynamic and unstable. Throughout the entire period, two sharp drops in the performance of the NIS RB were indicated. In the previous period, up to 2020, the index reached its minimum in 2015: 0.26. However, by 2020, there were tendencies for the recovery of NIS, which led to an increase in the index to 0.66. Also, a significant decrease (by 10%) is expected at the end of 2021, associated with the consequences of the 2018 crisis. In the forecast period, a tendency towards gradual growth is observed. According to the forecast, by 2025 the index will almost reach the level of 2020—0.65. The growth of the IIA index by 2025 is ensured, first of all, by innovative activity— the IA sub-index, which also reflects the negative consequences of the 2018 crisis. From 2018 to 2020, there was a sharp decline in the efficiency of innovative activities (IA3-share of sold innovative products (IA31); share of sold innovative products new to the domestic market (IA32); share of sold innovative products new to the pestilent market (IA33))—almost by 40%. But during this period, the provision of IA (investments, organization) increased, which, from the point of view of the forecast, will determine the growth of efficiency at the end of 2021 by 15% and its further increase.
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Table 1 The content of the predictive assessment methodology the index of intellectual activity of the national innovation-oriented system No
Steps / Content
1
Defining the index structure C—control C1—environment stability C2—management (efficiency of regulation (C21), effective law enforcement (C22)) C3—business (contract enforcement (C31), lending terms (C32), the possibility of starting a business, resolving insolvency (C33)) IR—intellectual resources IR1—abilities (physical resource (health) (IR11)), mental resource (education (IR12)), social resource (IR13) IR2—employment (share of personnel employed in the scientific field (IR21, share of candidates, doctors of science employed in an innovative economy (IR22, IR23) RD—research and development RD1—provision (the number of organizations performing RD(RD11)); expenses for RD (RD 12)) RD2—efficiency (sales proceeds RD (RD 21) profitability RD (RD 22), inventive factor (RD 23), granted patents (RD 24), valid patents (RD 25)) IA—innovation activity IA1—provision: technological innovation (costs for TI (IA11); share of organizations that have invested in TI (IA12); number of organizations, implementing TI (IA13)) IA2—support: industry (the share of innovatively active enterprises (IA21); share of enterprises that spent on technological, organizational, marketing innovations (IA22)) IA3—efficiency (share of sold innovative products (IA31); share of sold innovative products new to the domestic market (IA32); share of sold innovative products new to the pestilence market (IA33))
2
Data selection The selection of indicators was carried out from various sources: statistical databases: Belstat and databases of rating agencies: Global Innovation Index [14], Prosperity Index [15]
3
Determination of the forecast method 1. Linear regression method, y = ax + b, b =
4
(x−Xav.)(y−Y av.) (x−Xav.)2
Determination of the methodology for assessing the forecast index 1. Normalizing values—linear scaling method: j
X ia =
X j −X min X max −X min ,
j
j = 1, n (or X ia =
X max −X j X max −X min
for negative influence)
2. Calculation of sub-indices—average value of all components: j Yia = n1 nj=1 X ia , 3. Calculation of the IIA index: IIA = 5
1 10 (C1 + C2
+ C3 + I R1 + I R2 + R D1 + R D2 + I A1 + I A2 + I A3) ∗ 100%,
Calculations The calculation was carried out using Microsoft Excel (continued)
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Table 1 (continued) No
Steps / Content
6
Study of dynamics and deviations
7
Analysis of calculation results
8
Recommendations for directions of development
Table 2 Forecast values of sub-indices indicators the index of intellectual activity (Iia) 2012
2013
2014
2015
2016
2017
2018
C1
0.24823
0.00000
0.51064
0.31206
0.48440
0.33262
0.58865
C2
0.38245
0.12025
0.37301
0.40672
0.59345
0.20495
0.57066
C3
0.44244
0.39795
0.33190
0.33413
0.30144
0.55144
0.74187
IR1
0.27788
0.50541
0.71935
0.39290
0.53399
0.64720
0.78943
IR2
1.00000
0.66228
0.32881
0.18523
0.30545
0.60235
0.63574
RD1
0.50000
0.34964
0.19037
0.14605
0.13408
0.40732
0.54652
RD2
0.75511
0.77626
0.51902
0.41550
0.46163
0.41600
0.25412
IA1
0.62829
0.58078
0.32983
0.10612
0.07767
0.29101
0.46544
IA2
0.55076
0.43409
0.24015
0.00000
0.11061
0.22273
0.56364
IA3
0.47117
0.46262
0.40404
0.33333
0.32727
0.48966
0.84615
2019
2020
2021
2022
2023
2024
2025
C1
0.78723
1.00000
0.93587
1.00000
1.00000
1.00000
1.00000
C2
0.78804
0.94082
0.82582
0.85764
0.88946
0.92128
0.93822
C3
0.80300
0.68750
0.69812
0.71758
0.73704
0.75000
0.75000
IR1
0.62256
0.77940
0.71992
0.69699
0.67405
0.66667
0.66667
IR2
0.56044
0.10290
0.24845
0.20073
0.17373
0.15720
0.14067
RD1
0.61425
0.60101
0.50098
0.50000
0.50000
0.50000
0.50000
RD2
0.18903
0.24479
0.20000
0.20000
0.20000
0.20000
0.20000
IA1
0.63820
0.77632
0.54676
0.56569
0.58179
0.59788
0.60273
IA2
0.73788
1.00000
0.72704
0.78668
0.84631
0.90594
0.94310
IA3
0.65656
0.50458
0.64582
0.67509
0.70436
0.73362
0.76289
Also, the positive dynamics of the IIA index by 2025 is supported by the management system (C). The expected decrease in 2021 in the indicators of "environmental stability", "business" and "management" by an average of 10% indicates the consequences of the crisis. First of all, these events affected the business of C3 (enforcement of contracts (C31), credit conditions (C32), the possibility of starting a business, resolution of insolvency (C33)), which from 2019 to 2020 reduced its business activity by almost 20%. According to the calculations based on the results of 2021, the decrease in sub-indices: management of C1 and the stability of the environment of C2 (regulation efficiency (C21), efficiency of law enforcement (C22)) will average 10%. In general, the C governance sub-index will reach its maximum 0.89 by 2025.
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0.60
0.64 0.66
1001
0.63 0.640.65 0.60 0.62
0.53 0.43
0.40
0.42
0.39 0.33
0.30
0.26
0.20 0.10 0.00
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Fig. 2 Forecast of the dynamics of the Iia index
Scientific research activities of the research institute are characterized by significant negative trends. Estimated data show a decrease in RD in 2021 by almost 13% and a further lack of dynamics. RD2-efficiency (revenue from the sale of RD(RD21), the profitability of RD(RD22), the coefficient of inventive activity (RD23), issued patents (RD24), existing patents (RD25)) will decrease by 1% by 2021 and will remain in this value—0.2. The provision of SR1 (the number of organizations performing research and development (RD11)), expenditures on RD(RD12)) is also characterized by a negative trend: from 0.6 in 2020 to 0.5 in 2022 and a further lack of dynamics. The subindex intellectual resources (IR) in the forecast period is characterized by a stable decrease from 0.48 in 2020 to 0.41 in 2025. The value of IR1 is the provision of abilities (physical resource (health) (IR11)), mental resource (education (IR12)), the social resource (IR13) from 2020 falls by 8% by 2025. IR2—employment (the share of personnel employed in the scientific field (IR21, the share of candidates, doctors of science employed in the innovative economy (IR22, IR23) also falls significantly: from 2019 to 2020 and remains in a negative forecast trend until 2025.
5 Conclusions An analysis of the predicted values of the IIA intellectual activity index of the national innovation-oriented economic system of the Republic of Belarus until 2025 indicates that the 2018 crisis had a significant negative impact on its efficiency. However, the forecast shows the tendency of the economy to recover. The increase in the level of development is carried out mainly due to the stability of management, the effectiveness of innovative activities and an increase in investment. A slowdown in the growth of the IR sub-index from 2021 and, in particular, a sharp decrease in IR2 will affect a decrease in the growth rate of IR (a sharp decrease in the inventive activity coefficient) and a slowdown in the growth rate of the index of intellectual activity. This negative trend is caused by a drop in the share of personnel employed
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in research and development, a decrease in the share of candidates and doctors of sciences, as well as their low efficiency. Low efficiency is also explained not only by a decrease in the number, but also by the age factor (aging of scientific personnel). 80% of employees with a PhD in innovation are aged 70+. 40% of employees with PhD degrees are aged 60+. The negative aspect of such tendencies is explained by the fact that, according to psychologists, the dynamics of intellectual activity begins to slow down, which negatively affects the dynamics of the reproduction of an intellectual product. A decrease in the indicators of the use of intellectual resources will entail a decrease in the efficiency of research and development: the coefficient of inventive activity, issued patents, valid patents. Despite investment support (cost stability) of research and development, the forecast calculation shows a slowdown in the pace of innovation. The negative forecast dynamics of research activities is determined not only by negative trends in intellectual resources, but also by imperfections in the legislative and regulatory framework that regulates the mechanism for creating intellectual property, insufficiently developed infrastructure of the intellectual property market, insufficient spending on scientific activities (science intensity 0.55), the lack of a support system for start-ups, i. e., venture funding. Thus, the results of this study confirm the authors’ hypothesis about the key role of intellectual resources in the national innovation system of the Republic of Belarus, which determines its level of development. The development and calculation of the integral IIA, as well as the analysis of the dynamics of sub-indices and their deviations from IIA showed that the intellectual abilities of researchers (IR) involved in research activities through the reproduction of innovations and their commercialization create an increase in knowledge and, ultimately, intellectual capital.
References 1. Kirilchuk SP, Dementyev MY (2021) Institutional prerequisites and risks of the spread of the digital economy in Russia: a system analysis. Drukerovskij vestnik 3:30–40. https://doi.org/ 10.17213/2312-6469-2021-3-30-40 2. Yakovleva EA (2018) Management of intellectual resources of employees in the context of innovative development of the digital economy. Creative Econ 12(8):1073–1088. https://doi. org/10.18334/ce.12.8.39292. 3. Stat includes data and metadata for OECD countries and selected non-member economies. [electronic resource]. https://stats.oecd.org/. Accessed 21 Dec 2021 4. Golovchanskaya EE, Strelchenya EI (2017) Approaches to the assessment of forms of intellectual resources of the organization (enterprise) in modern innovative conditions. Bull Perm Nat Res Poly Univ Soc Econ Sci 3:154–169. https://doi.org/10.15593/2224-9354/2017.3.13 5. Melnikov ON, Esipenko DA (2020) Methodology for using the creative capabilities of human resources in managing the innovative activity of the organization. Leadership Manage 7(2):173– 180. https://doi.org/10.18334/lim.7.2.102192 6. Lebedeva NM, Tatarko AN (2018) Basic values in Russia: their dynamics, ethnocultural differences, and relation to economic attitudes. Psychol Russ State Art 11(3):36–52. https://doi.org/ 10.11621/pir.2018.0303
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7. Kaplan RM, Saccuzzo DP (2009) Standardized tests in education, civil service, and the military. Psychological testing: Principles, applications, and issues, 7th edn. Wadsworth, Belmont, CA 8. Sternberg RJ (2020) The Cambridge handbook of intelligence. Cambridge University Press. https://doi.org/10.1017/9781108770422.002 9. Lyusin D, Ovsyannikova V (2016) Measuring two aspects of emotion recognition ability: accuracy vs. sensitivity. Learn Individ Differ 52:129–136. https://doi.org/10.1016/j.lindif.2015. 04.010 10. Schwartz SH, Butenko T, Cieciuch J, Vecchione M, Torres C, Dirilen-Gumus O (2017) Value tradeoffs propel and inhibit behavior: validating the 19 refined values in four countries. Eur J Soc Psychol 47(3):241–258 11. Fontaine JRJ, Poortinga YH, Delbeke L, Schwartz SH (2008) Structural equivalence of the values domain across cultures. J Cross-Cult Psychol 39:345–365. https://doi.org/10.1177/002 2022108318112. 12. Ralston DA, Egri CP, Reynaud E, Srinivasan N, Furrer O, Brock D, Alas R, Wangenheim F, Darder FL, Kuo C et al (2011) A twenty-first century assessment of values across the global workforce. J Bus Ethics 104:1–31. https://doi.org/10.1007/s10551-011-0835-8 13. Golovchanskaya EE, Karachun IA, Petrenko ES (2021) Management of the development of the national innovation-oriented economic system based on the assessment of the index of intellectual activity of the national economy. Russ J Innov Econ 11(1):13–32. https://doi.org/ 10.18334/vinec.11.1.111550 14. Global Innovation Index 2020 [electronic resource]. https://www.wipo.int/global_innovation_i ndex/en/2020/. Accessed 27 Dec 2021 15. The Legatum Prosperity Index 2020 [electronic resource]. https://www.prosperity.com/about/ resources. Accessed 21 Aug 2021
Digital Simulators and Training Devices for Solving Geometric Problems Elmira Galyamova , Semen Matveev , and Boris Kiselev
Abstract Advances in digital technologies give the opportunity to create a variety of simulators that imitate real objects in a virtual environment, and thereby help to reduce the labor and time spent on solving professional problems. This also applies to the modern educational system, where there has emerged a trend to introduce digital educational and methodological complexes, educational simulators, training devices and virtual laboratories. Their application has a significant impact on all aspects of educational strategy, methods of solving pedagogical problems. The article describes an experiment on the implementation of an authentic digital simulator for solving geometric problems and a simulator of pedagogical activity in the process of training future mathematics teachers. We present here a constructive model of the proposed digital simulator, with its plot composition based on the formation of a strategy for finding solutions to geometric problems being described, and reveal the technology of creating a simulator. The experiment was carried out at Naberezhnye Chelny State Pedagogical University (Russia). Its aim was to monitor the formed competencies of mathematics teachers, as well as to study if student trainees are prepared to learn a strategy for solving mathematical problems. We present here an assessment of the implementation of the developed simulator on the basis of statistical processing of the experimental results using the apparatus of statistical analysis. Keywords Digital training device · Solution of a mathematical problem · Learning strategy · Simulator
1 Introduction At present, there are widely used in practice various types of training devices, simulators, including mathematical ones [1, 2]. In the theory of teaching mathematics, the term “training device” is used to describe teaching systems that are different in E. Galyamova (B) · S. Matveev · B. Kiselev Naberezhnye Chelny State Pedagogical University, 28, Nizametdinov Street, Naberezhnye Chelny 423806, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_103
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their purpose. Training devices are not only the means of forming and consolidating professional skills, but also any methods and means of teaching, in one way or another contributing to the acquisition of knowledge and the development of cognitive skills [3, 4]. In English-speaking and Russian-speaking scientific researches computer training devices are called simulators, that is, these terms are considered synonymous. However, despite the fact that, according to B.S. Bell with coauthors, “the current literature on simulation-based training paints a mixed picture as to the effectiveness of simulations as training tools” [5], numerous studies admit the successful use of computer simulators in various fields: in medicine [6–8], including the well-known simulator for endo-surgery SEP SimSurgery [9], in food engineering [10], in transport [11, 12] in the nuclear industry [13–17], etc. These devices make it possible to artificially imitate and recreate the life and professional reality in which the employee will have to act in the future, provide the formation of professional skills in a virtual environment. As it was noted by J.A. Cannon-Bowers and CA Bowers, simulating an industrial or life situation, as well as a certain technological process, computer simulators can not only supplement the real experience of a person, but also significantly contribute to the formation of the students’ experience in their interaction with the external environment [11]. Many foreign and domestic studies noted an interest in the implementation of training devices and simulators in the professional activity of a teacher. In accordance with the requirements of pedagogical educational programs abroad both commercial simulators and training devices, such as SimSchool, and locally developed ones, such as ClassSim, Cook School District, TeachME and TeachLive, have been created. Many works in Russia examine types of training devices, including simulators, existing in the Russian Federation, and the dependence of their choice on the field of their application [18, 19]. The analysis of such works shows that simulators are widely used in the field of training specialists—operators of complex technical systems [20]. As for the approaches and points of view that have developed in the Russian and English literature on the problem of introducing simulators and training devices into the vocational education system, their analysis is quite meaningfully presented in the article by F.F. Dudyreva and O.V. Maksimenkova [15]. It is admitted there that under the name of simulators among other things there are considered computer problem books and workshops, designed to develop skills and abilities for solving typical practical problems, as well as the development of related abilities. Undoubtedly, this is one of the most necessary and important directions in the development of methods of teaching mathematics, both at the level of secondary general education and within the framework of university courses. With the growth of the possibilities of information technologies and technical means, one can observe intensive development of simulation modeling of training and creating of training digital simulators. Testing such training systems is an important component of assessing the capabilities of such digital imitating devices and simulators. And this, in turn, requires the development of theoretical and methodological foundations for assessing the effectiveness of the used training systems. As
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an initial assessment of a simulator, the authors propose a statistical analysis of the final indicators of the users of these systems [16, 17]. It should be acknowledged that at present the share of training devices and simulators in the training of mathematics teachers is extremely small. It is, first of all, due to the insufficient level of gamification of virtual digital simulators that imitate the actions of trainees. The development of simulators, especially complex ones, imitating the activities of a mathematics teacher and students, requires significant investments. Their focus on a narrow circle of users increases the cost of the training system. For many educational institutions and teacher training universities (in comparison with some industries), such training systems are often not available. It should be noted that the methodology of applying technologies of various computer training devices, digital simulators, modeling theory into the system of teaching mathematics has been studied for a long time. Computer simulators of pedagogical activity are not only poorly reflected in domestic studies, but are evidently insufficiently used, although they are actively mastered in foreign practices [21]. Teaching to solve problems is a specially organized interaction between a teacher and students, the purpose of which is to form students’ ability to solve problems. Choosing the right strategy is a key aspect of solving the problem. Solving a problem is a process from the moment of reading the conditions of the problem to the moment of receiving the final answer and its comprehension. By the strategy of teaching the solution of mathematical problems in a university we mean a specially organized process aimed at the formation of new personal qualities (reflection and personalsemantic sphere) and the development of old personal qualities (thinking, imagination, memory, attention, independence, etc.) based on the assimilation of certain knowledge, skills and abilities. Let us apply the theory of modeling to the study of activity, in particular, to the search for a solution of a problem.
2 Materials and Methods Here we describe a method for evaluating the experimental implementation of the authentic model of simulator in the process of training a future mathematics teacher at Naberezhnye Chelny State Pedagogical University. Evaluation of the efficiency of the proposed digital product is investigated by the methods of mathematical statistics [17, 19]. The conclusions are based on the analysis of the statistical data obtained as a result of testing the simulator. The sample consisted of 300 senior students of the Mathematics and Informatics Department of Naberezhnye Chelny State Pedagogical University and university graduates with no more than two years of experience. Thus, the statistical study is aimed at monitoring the indicators of the formed competencies of future teachers and also preparedness of student trainees to carry out educational activities. The statistic basis for analysis includes the main indicators of the actions of a methodological nature (x1 , x2 , x3 , x4 , x5 ) and such indicators as skills in working with a graphic editor, the level of knowledge in constructive geometry
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and the theory of images—x6 , the ability to implement mathematical judgments into geometric problems—x7 . Initially, statistical processing of the results was carried out on the basis of statistical differentiation criteria, since such mathematical methods are most suitable as descriptive and searching methods in pedagogical research. We carried out a statistical analysis of three measurements according to the accepted indicators of a connected sample using the Friedman test. As methods for assessing the effectiveness of a digital simulator, the proposed work also involves elements of multivariate analysis, such as factor analysis by the method of principal components and cluster analysis.
3 Results The plot of the digital simulator is built on the basis of a block of geometric problems of the elementary geometry course. The prerequisites for this work are related to the interest in the experience of the work of French scientists in creating a virtual classroom and familiarity with the work of similar mathematical simulators. The structure of the digital product developed by the authors of the article consists of two modules, intended respectively for two purposes. The first module is aimed at the formation and testing of subject competencies, namely the application of the mathematical apparatus by a user. It is presented in the form of a digital simulator for the formation of various ways and methods for solving geometric problems. The second module is aimed at the formation of pedagogical skills and checking the level of professional competencies of a user in a virtual classroom and is presented by a digital simulator of pedagogical activity. Thus, the authors’ approach has been implemented through a combination of a digital training simulator and a virtual simulator, which play a dual role: teaching and testing. This authors’ product is intended both for the formation of the ability to teach schoolchildren a strategy for solving problems, and for checking the level of formation of the professional competencies of future mathematics teachers. It is aimed to be primarily implemented at the period of students’ practical training. The hypothesis of the research is that the introduction of a digital training devices and simulator in the preparation of a future teacher has a positive effect on the results of practice training. Let us briefly describe the constructive model of the proposed simulator. The initial element in the design of the first module of the digital simulator is some mathematical problem. For example, it has the following content: "The base and side of an isosceles triangle are 34 and 49, respectively, a) prove that the midline of the triangle, parallel to the base, intersects the inscribed circle. b) find the length of the segment of this midline, enclosed inside the circle. " The digital simulator is programmed so that at each entry a user is presented with the above-mentioned task with a different set of data. In particular, the change in
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the metric conditions in the simulator is carried out so that the calculations and the final answer belong to the set of rational numbers. For this purpose, a scheme for enumerating right-angled triangles with integer sides is embedded in the process of modeling the text of the proposed problems in the simulator. Such an organization of tasks gives an opportunity in the future to correctly check the drawings (for problems) performed by users. Obviously, this part of the digital simulator tests geometric knowledge and can be useful not only for students and teachers of mathematics, but also for high school users in the course of preparing for the Unified State Exam in Mathematics. Let’s outline some of the key points of the first module. After getting acquainted with the task a user is offered to do a drawing for it in a certain graphical editor (Fig. 1). For example, it is proposed to apply Geometer’s Sketchpad or GeoGebra to the construction of a drawing. The need to include a graphical editor into the simulator model is justified by the program control function of solving a problem by a user at the construction stage. It is important that in the proposed technology for designing this digital simulator, the choice of any editor, any computer algebra system is allowed. If a mathematical problem of another level is embedded, for example, a problem from a course of higher geometry, then there is selected a computer algebra system that supports methods of calculating higher mathematics, for example, systems such as Rino, Maple, Maxima, Mathematica, etc. The implementation of checking the completed drawing for the proposed task relies on the structure of the solution to the problem itself: it is proposed to the author of the completed drawing to take some measurements and enter the values using the tools of the applied graphical editor. For example, in the considered problem, you need to enter the radius of the inscribed circle, the length of the height and the midline of the triangle from the drawing made in the graphic designer. In the simulator there is preliminarily set a
Fig. 1 Drawings for the problem in Geometer’s Sketchpad
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level of the permissible error of the drawing. If the drawing error is acceptable, then the simulator offers to proceed to the next stage of working with the task. Here we note that if a user does not know the tools for constructing a drawing or is at a loss in geometric constructions, makes a significant error in constructing a drawing, then the digital simulator offers to study the additional necessary material built into the simulator. Such an integrated approach makes it possible to form not only geometric knowledge, but also the skills of working with a graphic editor, dynamic drawings related to the information communicative technologies (ICT) competencies of a future mathematics teacher. The next key point of the proposed digital simulator is the user’s solution to the problem put forward by the simulator. The main variations of the simulator model at this stage are: solving the problem without help or with some accompanying prompts. Among these hints, there may be a choice of the correct solution from a set (at least 5 items) of the proposed solutions (Table 1): The work in the first module is completed by entering the answer to the problem. If a user has solved the problem correctly, then the simulator allows him/her to access the second module—a methodical one, that is, to work in a simulator with a virtual classroom. Let’s move on to a brief description of the second module. Here we also note some of the technical aspects of modeling and some of the capabilities of the developed simulator. After successfully completing the first module, the user is moved to a virtual three-dimensional classroom for direct work with digital, interactive students. Table 1 The main variations of the simulator model The first method
The second method
a) Prove that the midline MN intersects the inscribed circle Proof: (Fig. 1a) the square of the tangent segment from point A to the point of tangency D is equal to the product of the length of the secant line segments from point A to the points of its intersection with the circle: AD2 = AT · AH,
b) Prove that the midline MN intersects the inscribed circle Proof: (Fig. 1b) suppose that the middle line MN only touches the circle inscribed in the triangle ABC, that is, a circle is inscribed in the isosceles trapezoid BCMN, which is possible if and only if BC + MN = BM + CN, or 2 which means AT = AD BC + MN = 2BM AH , where However, for points M and N—the AD = AB − BD = AB − BH == 49 − 17 = 32 midpoints of sides AB and AC, respectively, The AH cathetus in the ABH triangle is found by we have: BC + MN = 2BM, namely 34 + the Pythagorean theorem 17 = 2 49/2, i.e. BC + MN = BM + CN, √ which means that the circle cannot be AH = AB2 − BH2 = 492 − 172 = 8 33 inscribed in the trapezoid BCMN, therefore 2 4·32 √ MN intersects the circle inscribed in the Then AT = 32 = √ . 33 8 33 triangle ABC √ 4·33 . So, AK > AT, AK = 21 · AH = 4 · 33 = √ 33
which means that the radius OT of the circle in question is longer than the distance OK from its center to the midline MN of the triangle ABC
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The simulator has the ability to change the number of students in a virtual classroom, which will allow simulating work with a small group of students or individual work with a student. Programming the structure of the second module in the format of a simulator of pedagogical activity is based on the description of the actions of a virtual novice teacher with digital students in a virtual classroom. Their actions are integrated into the computer environment in the form of three-dimensional models and voiced. A simulator user guides the actions of the virtual teacher. The virtual curator built into the simulator regulates the conditions of a user’s operating the simulator, introduces the program interface and at the end of the program summarizes the passed stages. The results of the performed actions and tasks are drawn up in a tabular form with the indicators presented in the scale of relations, in the points scored and as a percentage of the maximum result. The scheme of checking the user’s knowledge is carried out by a digital training device and a simulator according to the principle of visual, object-oriented programming. The graph of user’s actions is modeled by a plurality of test runs of the program with a previously prepared set of input data. It should be noted that in the process of modeling a digital training device and simulator, each module undergoes a number of different tests, including testing specialists, comparing the results with the theory and practice of teaching. Such tests ensure the reliability of the program and make it possible to correct the course of further development of a digital training device and simulator. As a result of such experimental work, structural graphs are formed, from which the storyline (plot) as a whole is composed. The principle of class inheritance used in simulator programming allows constructing a graph of user’s actions with unlimited variability. For example, at the beginning of the script, a user can be prompted to select the correct answer from a variety of suggested ones, followed by a ramification in the user’s actions. Or he/she can be offered a system of questions, selected by the program from the nested list, also with the subsequent branching of user’s actions. At the same time, repetition of tasks for a virtual teacher in working with a virtual classroom is excluded. An interesting solution is a task where the correct answer is formed by key phrases or within the range of certain numbers. User’s actions to control the virtual teacher are subjected to detailed analysis and evaluation by the program applying modern concepts of theory and practice of teaching. Based on such estimates, as a result, the general indicators of each user are formed. Each grade in the program has its own weight. Thus, the second module is aimed at the formation of professional competencies of a user through his/her management of the actions of the virtual teacher in the virtual classroom. It should be admitted that in the process of such management, a user must demonstrate not only theoretical and practical knowledge, but the ability to make decisions quickly, since the program session is limited in time. The virtual lesson lasts 45 min. These time frames are conditional and are regulated by the program developers or simulator operators. In principle, it is also possible for a user to terminate work ahead of schedule if he/she believes that all training tasks have been completed. The number of concurrent users is not limited. The result of the
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Table 2 Calculated empirical values of the Friedman test χ2
x1
x2
x3
x4
x5
x6
x7
7.7984
9.6532
4.7016
0.2984
18.9677
8.3962
6.2154
work is displayed in the final part after passing all the stages in the form of a table and is announced by the virtual curator. Thus, a user, improving his/her professional skills in the digital simulator, fixes them at the level of reflection, and applies them in real educational practice. The measurements were made in three stages: ascertaining, forming and control. The analysis results are shown in Table 2. Here, the empirical value of the Friedman criterion is calculated using the formula: c 12 · R 2 − 3n · (c + 1), χ = n · c · (c + 1) i=1 i 2
where n is the sample size, c is the number of dimensions in the connected sample, Ri is the sum of the ranks of the i-th dimension. Here the sample size is 300, the number of measurements is 3. To analyze the obtained experimental sample values, we use the critical values χ2 = 7.815 at a significance level of 0.05, and χ2 = 11.345 at a significance level of 0.01. From the above table it can be seen that in the zone of significance there are such indicators as x6 —the indicator of skills in working with a graphic editor and drawing methods;x2 —the indicator of mistakes, that makes it possible for students of a virtual class to find them; x5 —the indicator of the level of the user’s knowledge of didactic units. Indicator x1 —the ability of the user to transfer knowledge or induce thought—is close to the zones of demarcation. For the indicators x4 , x3 characterizing the general methods of controlling the actions of the virtual classroom, the hypothesis H0 is confirmed that means the absence of difference, which is typical for novice teachers of mathematics. It is known that Friedman criterion allows us to establish the level of statistical significance of differences in several measurements, but does not provide an opportunity to identify the direction of changes. To determine the dynamics of indicators for which the hypothesis H1 is confirmed, the criterion of signs G was applied. In this case, positive shifts turned out to be typical ones, which confirms the expediency of using the considered simulator.
4 Discussion The proposed digital product can be updated and improved by developers. Its relevance depends on changes associated, for example, with the federal educational standard of the Russian Federation or on new experience gained during testing in a wider group of professionals. This development is an inherently flexible tool that
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has an integral software core that allows us to quickly respond to changes without spending a lot of time on reworking or reconfiguring a digital product. The dialog shell of the simulator widgets is built on vector graphics. All drawings of geometric problems do not lose quality when resizing and have a small weight in kilobytes, which directly affects the speed of the program. Computer graphics accompany throughout the entire session and complement the visual material. Thus, it includes a user in the gamified learning process. The interface is extremely simple. Almost all actions are performed with a computer mouse. The laconic menu of the program allows us to select the language of the inscriptions, manage virtual objects, select virtual students, control their actions, interact with the whole class or individually with a student, etc. The architecture of the platform allows us to manage uncomplicated databases, to use logical Boolean operations, initialize variables at the discretion of the developers. Automation of processes in programming expands the cross-platform capabilities of the program. At the moment, one of the versions developed in this programming style is posted on the website of Naberezhnye Chelny State Pedagogical University in the Moodle section: http://do.tatngpi.ru/.
5 Conclusions Statistical analysis shows the effectiveness of a digital training device and virtual simulator in the training of mathematics teachers: indicators that affect the acquisition of the required competencies are mainly characterized by positive shifts. In general, we can state the effectiveness of the proposed mathematical simulator in the formation of the initial skills of conducting lessons. The simulator under consideration is as close as possible to real practice and allows one to evaluate actions of a future mathematics teacher in organizing the solution of a geometric problem from the point of view of didactics, psychology, methodology and axiomatics of geometry. The application of this assessment method is successfully implemented in the training program for a mathematics teacher at Naberezhnye Chelny State Pedagogical University. We also considered the possibility of using multivariate statistical analysis to assess the results of using a mathematical simulator in teaching. For assessment a wide range of statistical methods is used, such as a factor analysis by the method of principal components, a cluster analysis, and also criteria of distinction. The assessment methods are implemented using the free software Statistica. However, it should be noted that when teaching only in computer simulators there is always a danger of training not real, but "virtual specialists" who are incapable of professional performance of real tasks. Therefore, the introduction of such digital teaching tools should be considered as an addition to the traditional forms of training future mathematics teachers.
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Acknowledgements The study was carried out under the project "Formation of professional competencies of future teachers and teachers working in rural areas, including small schools, using a Digital Simulator of Pedagogical Activities" within the framework of Agreement No. 073-032022-102 and No. 073-03-2022-102/2 between the Ministry of Education of the Russian Federation and Naberezhnye Chelny State Pedagogical University.
References 1. Galiakberova AA, Galyamova EK, Matveev SN (2020) Methodological foundations for designing a digital simulator of pedagogical activity. Bull Minin Univ 8(3):2. https://doi.org/ 10.26795/2307-1281-2020-8-3-2 2. Emprin F, Sabra H (2019) Les simulateurs informatiques, ressources pour la formation des enseignants de mathématiques. Can J Sci Math Technol Educ 19(2):204–216 3. Zhigalova OP (2021) Educational simulators in the vocational education system: pedagogical aspect. Azimuth Sci Res Pedag Psychol 1(34):109–112. https://doi.org/10.26140/anip-20211001-0026 4. Galyamova EK (2021) Digital simulator for learning how to find solutions to problems. Vestnik MGPU. Inf Inf Educ 2(56): 60–65. https://doi.org/10.25688/2072-9014.2021.56.2.08 5. Bell BS, Kanar AM, Kozlowski SWJ (2008) Current issues and future directions in simulationbased training in North America. Int J Hum Res Manage 19(8):1416–1434 6. Shams P, Ahmed I, Shahab H, Kadani Z, Khan A (2021) Cardiovascular fellow-in-training feedback on virtual and simulator-based learning experience during COVID-19 pandemic in a low to middle income country – a cross-sectional study. Ann Med Surg 69:102786 7. Milcent PAA, Kulcheski AL, Rosa FM, Dau L, Filho ES (2021) Construct validity and experience of using a low-cost arthroscopic knee surgery simulator. J Surg Educ 78(1):292–301 8. Lavoie P, Deschênes M-F, Nolin R, Bélisle MI et al (2020) Beyond technology: a scoping review of features that promote fidelity and authenticity in simulation-based health professional education. Clin Simul Nurs 42(5):22–41 9. Buzink S, Goosens R, de Ridder H, Jakimowicz J (2010) Training of basic laparoscopy skills on SimSurgery SEP. Minim Invas Ther Allied Technol 19(1):35–41 10. Suciu I, Ndiaye A, Baudrit C, Fernandez C, Kondjoyan AI et al (2021) A digital learning tool based on models and simulators for food engineering (MESTRAL). J Food Eng 293:110375 11. Zou X, O’Hern S, Ens B, Coxon S, Pl M et al (2021) On-road virtual reality autonomous vehicle (VRAV) simulator: an empirical study on user experience. Transp Res Part C Emerg Technol 126(33):103090 12. Duan K, Yan X, Li X, Hang J, Yang J (2020) Analysis of driver’s decision distance and merging distance in work zone area based on parametric survival models: with the aid of a driving simulator experiment. Transport Res F: Traffic Psychol Behav 71:31–48 13. Shirley RB, Smidts C (2018) Bridging the simulator gap: measuring motivational bias in digital nuclear power plant environments. Reliab Eng Syst Safety 177(Special Issue):191–209. 14. Malec J, Toškan D, Snoj L (2020) PC-based JSI research reactor simulator. Ann Nucl Energy 146:107630 15. Dudyrev FF, Maksimenkova OV (2020) Simulators and digital training devices in vocational education: pedagogical and technological aspects. Educ Stud 3:255–276. https://doi.org/10. 17323/1814-9545-2020-3-255-276 16. Galiamova E, Kiyamova A, Chernova N, Antropova G, Matveev S (2018) Assessment of the professional competence formation with future teachers in a teacher-training university. Paper presented at the 11th annual International Conference of Education, Research and Innovation, Seville, pp 9640–9645. https://doi.org/10.21125/iceri.2018.0781
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17. Matveev S, Antropova G, Chernova O, Evgrafova N (2019) Key factor analysis influencing the learning activity motivation with first-year and second-year university students. Paper presented at the 13th International Technology, Education and Development, Valencia, pp 1757–1762. https://doi.org/10.21125/inted.2019.0507 18. Galiakberova AA, Galyamova EK, Matveev SN (2020) Methodological foundations for designing a digital simulator of pedagogical activity. Bull Minin Univ 8(4):2. https://doi.org/ 10.26795/2307-1281-2020-8-4-2 19. Antropova G, Matveev S, Shakirov R (2020) Implementation of some problems of differential geometry in the GeoGebra program. Higher Educ Today 6:58–63. https://doi.org/10.25586/ RNU.HET.20.06.P.58 20. Dyachuk PP, Shkerina LV, Shadrin IV, Peregudova IP (2018) Dynamic adaptive testing as a method of students’ self-learning in the electronic problematic environment of mathematical objects. Bull Krasnoyarsk State Pedagog Univ 1(43):48–59. https://doi.org/10.25146/19950861-2018-43-1-40 21. Castel F (2015) Construction d’un simulateur informatique de classe (SIC) pour la formation des enseignants. Actual problems of mathematical education: materials of the scientificpractical conference dedicated to the 25th anniversary of the Faculty of Mathematics and Informatics, 164–175 NISPTR, Naberezhnye Chelny. https://www.elibrary.ru/item.asp?id=367 48241&pff=1
The Effect of Visual Information Contained in Digital Training Courses on the Renewal of Working Memory Elena Romanova
and Dariana Romanova
Abstract Digital technologies in education are gradually replacing traditional teaching methods. Working memory is actively used in digital learning, which leads to cognitive overload and reduced performance. Scientists are looking for technologies that speed up the renewal of working memory. The purpose of this study was to compare the updating of visual information in working memory depending on its affective dimension and familiarity. Familiar affective images were expected to be updated more efficiently than unfamiliar neutral ones. To assess the effectiveness of updating working memory, an affective version of the “n-back” task was used, where positive, negative and neutral images acted as stimuli. The study involved 111 people. The experiment was conducted in a remote format on the computers of the subjects without control by the experimenter. Significant differences were found in the proportion of false alarms, depending on the familiarity of the information, and close to significant differences in the reaction rate. The obtained results did not prove the significance of the influence of the affective dimension factor, as well as the interaction of the affective dimension and familiarity factors on the renewal of working memory. Keywords Digital tools in education · Changing cognitive processes · Negative impact of digital technologies · Updating working memory · N-Back
1 Introduction Digital technologies are becoming more widespread in education, creating new ways of learning, helping students quickly master the knowledge and skills needed in the E. Romanova (B) Moscow State (National Research) University of Civil Engineering, 26 Yaroslavskoye Shosse, 129337 Moscow, Russia e-mail: [email protected] D. Romanova Higher School of Economics, National Research University, 20 Myasnitskaya Street, 101000 Moscow, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_104
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modern world. Digital technologies support and enhance face-to-face training. They are gradually replacing traditional face-to-face classes. Lectures, individual work and knowledge control are moving to a remote format using digital technologies [1, 2]. The replacement of traditional teaching methods with digital ones has led to the need for a deeper study of the impact of various technological tools on the cognitive processes of students, because they have a causal relationship with training outcomes. This paper considers the positive and negative impact of digital technologies on the effectiveness of the educational process. The experimental part describes the study of working memory, which is under increased stress when using digital technologies, the meaning of familiarity and affective dimension of information for working memory in a digital environment. In the final part, conclusions and recommendations for organizing training using digital technologies are considered.
1.1 Positive and Negative Impact Contradictory results can be divided into groups. The first group of results shows that digital technologies have a positive impact on training outcomes. J. Serfaty and R. Serrano developed the Cram.com smartphone program, with the help of which Cambodian students learned English. Using digital cards on a smartphone, they were able to notice and accurately use English grammatical patterns [3]. S. Becker et al. suggested that students use tablets for the study of the movement of bodies. Multilevel regression analysis of the results showed that this approach leads to a significant expansion of conceptual knowledge about physical phenomena [4]. S. Benavides-Varela et al. studied the impact of digital technologies on the educational success of children with difficulties in learning mathematics. Using a meta-analysis of random effects, scientists proved that digital interventions improved mathematical performance [5]. These optimistic studies strengthen the trend of increasing the introduction of digital technologies in the educational process. M. Degner et al. believe that the functions of digital media are not fully used in education. At the moment, they mainly provide information search and occasionally help organize joint work. Digital technologies can support motivational and cognitive learning processes, stimulate interest in acquiring knowledge, as well as collaboration and interaction [6, 7]. The second group of results speaks of a rather negative impact of digital technologies on cognitive processes, and as a result, on the productivity and quality of education. The increased need to use interactive learning systems leads to cognitive overload, which can negatively affect labor productivity [8]. Before the student begins to acquire the necessary information in the digital educational environment, he is forced to perceive and process a large number of interactive information elements, thereby consuming the cognitive resources necessary to process meaningful educational information [9]. N.S. Baron studied the characteristics of working with paper and digital books and found that digital works encourage people to use books rather
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than read them. Reading is gradually supplanted by point-to-point “use” navigation [10]. M. Wimber revealed changes in long-term memory. Instead of remembering information, a modern person turns to external devices (primarily the Internet) for it. Information retrieval without a preliminary attempt to remember it changes the structure of long-term memory and facilitates finer information processing [11]. Storm et al. confirm this modern trend of ‘cognitive offloading’—the use of the Internet instead of the resources of one’s own memory [12]. Thus, digital technologies act on human memory in two directions: they unload long-term memory and at the same time load working memory. That is why the cognitive overload, associated with the limitation of a person’s working memory for processing information when viewing texts with hyperlinks.
1.2 Working Memory Working memory (WM) is a special system of cognitive processes that allows you to temporarily store information and process it through various manipulations aimed at solving actual problems. Classical model distinguishes the following components of working memory: central executive, visuospatial sketchpad, phonological loop, and episodic buffer. The last component combines visual, spatial and auditory signals and provides the linking of the received information with long-term memory. This is what is of interest in this study. WM quickly adds or removes data if it is no longer required for the current task, i.e. updated. The “n-back” task allows assessing the mechanisms of functioning and updating of WM [13, 14]. The subject receives a sequence of stimuli and must respond each time the currently presented stimulus matches the one that was n presentations before. The load on WM increases as n increases. At n = 3, the task is difficult to perform [13]. In addition to the load, the WM update is affected by the affective dimension of visual and verbal information [15]. Lindström & Bohlin found that affectively colored information is updated better than neutral information [16]. However, Grissmann et al., conducting an experiment on the same topic, found that update performance decreases when solving 2-back tasks with negatively colored information [17]. Another factor influencing the work of WM is the familiarity of the information. Familiarity is accompanied by the subject’s confidence that he has already met the presented stimulus, but cannot remember the context of the previous exposure [18]. This is the main difference between familiarity and another memory process, recollection. Familiarity is associated with long-term memory, which indirectly affects working memory through the episodic buffer. Understanding the features of the interaction of different types of memory in the learning process is extremely important. This helps to assess the quality of the processes of processing and storing information, which are manifested in the assessment of training outcomes (does the student
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remember the information or not, whether he knows how to quickly process and apply it). Experiments show that the impact of long-term memory on working memory can be both positive [19–22] and negative [22, 23]. A positive impact is manifested in the fact that a limited amount of WM is used mainly to encode new, unknown information [19], and if it is relevant to that already stored in long-term memory, less WM resources are spent on it [21, 22]. The subject of this study is the problem of the functioning of WM in the context of the use of visual digital technologies in teaching students. Based on the need to extrapolate the results obtained into the practice of developing training courses, we formulated two hypotheses. The first hypothesis is that updating WM is more efficient when working with familiar images, therefore, the subjects will show greater accuracy and less reaction time when performing the “n-back” task. The second hypothesis is that when familiar affectively colored images are presented, the proportion of correct answers will be higher (compared to unfamiliar neutral images), and the proportion of false alarms and reaction time will be lower.
2 Materials and Methods This experiment was built according to a mixed factorial design, where the image familiarity factor is intragroup (2 levels: familiar / unfamiliar image), and the image affective dimension factor is intergroup (3 levels: negative / neutral / positive images). These factors acted as independent variables (IV). The proportion of correct answers, the proportion of “false alarms” (missed correct answers) and reaction time were taken as dependent variables (DV). The experiment was carried out in the program “PsychoPy v. 2021.2.3”. Data collection was carried out online using the Pavlovia platform (pavlovia.org). The subjects were experimented on personal laptops or computers. Images selected from the OASIS database [24] according to the valence principle were used as stimulus material: 35 positive (M = 5.77, SD = 0.348), 35 negative (M = 2.81, SD = 0.592) and 35 neutral (M = 4.34, SD = 0.307). A total of 105 images were selected, 35 for each sample. The training sessions of the “n-back” task included 5 images, and the main ones included 30 images in each category: 15 familiar and 15 unfamiliar. The images used in the training sessions did not appear in the main ones. The images were presented against the standard gray background of the PsychoPy program and had a size of 0.7 × 0.56 in units of height. The experiment began with instructions for a preliminary presentation. Participants were asked to carefully look at the presented images and either aloud or to themselves constantly pronounce “ba” (articulatory suppression). When pressing the space bar, a presentation was launched in which five images were presented for 2000 ms each. After the presentation was over, the next part of the instruction appeared with an explanation of the “n-back” task for n = 2. The subject has to press the key with
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the letter “m” each time the image matches the one shown two images before (i.e., the pre-previous one). In this task, it was also required to constantly pronounce the syllable “ba”. Next, the participants were asked to go through a training session of 10 images, of which 4 were matching (i.e., in total, the subjects were required to press the “m” key 2 times). After the training session, the main session began, consisting of 2 blocks of 30 images each (there was an opportunity to take a break between the blocks). There were 12 matching images in each block (6 presses on the “m” key). The experiment ended with an instruction with gratitude for participating. The study involved 111 people aged 18 to 29 years (M = 20.7, SD = 6.16), including 69 women and 42 men. All subjects received messages with an invitation to go through the experiment through social networks (VKontakte, Instagram, Telegram, etc.). The subjects were randomly divided into three equal groups.
3 Results and Discussion The analysis of the results was carried out in the program “jamovi v. 2.2.2”. A repeated measures analysis of variance was applied, which also included an intergroup component (mixed ANOVA).
3.1 Proportion of Correct Answers The first DV is the proportion of correct answers (the subject correctly identified the matching images presented 2 steps earlier). Evaluation of the equality of variances was made according to the Levene test. The statistics showed non-significant results (Table 1) and allowed the use of repeated measures ANOVA. Mixed ANOVA (Table 2) showed that the intergroup IV “affective dimension of the image” has no statistically significant differences for the DV “percentage of correct answers”. Table 1 Levene’s test for the variable “percentage of correct answers” F
df1
df2
p
Share of correct answers for familiar st
0.292
2
108
0.747
Share of correct answers for non-familiar st
0.753
2
108
0.473
Table 2 Intergroup effects criteria for the variable “percentage of correct answers” Sum of squares
df
Mean square
F
p
η2 p
Affective dimension
0.0168
2
0.00838
0.117
0.890
0.002
Residual
7.7605
108
0.07186
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Table 3 Joint effects criteria for the variable “percentage of correct answers” Sum of squares
df
Mean square
F
p
η2 p
Familiarity st
5.01e–4
1
5.01e–4
0.0506
0.822
0.000
Familiarity st & Affective dimension
0.0423
2
0.02115
2.1377
0.123
0.038
Residual
1.0683
108
0.00989
Table 3 shows that the intragroup IV “image familiarity” as well as the interaction between the intragroup and intergroup IV did not give statistically significant results.
3.2 False Alarm Rate The second DV is the proportion of false alarms—situations in which the subject incorrectly identified the stimulus as presented 2 steps back. The statistics of the Levene test for the proportion of false alarms (Table 4) allows us to conclude that the variance of both samples is equal and use repeated measures ANOVA. Mixed ANOVA (Table 5) showed statistically significant differences in the intragroup factor “image familiarity”, while no significant differences were observed for the intergroup factor “affective dimension of the image”. The interaction of intergroup and intragroup factors gives a result that is close to significant, but not significant (Table 6). Table 4 Levene’s test for the variable “false alarm rate” F
df1
df2
p
Share of correct answers for familiar st
0.215
2
108
0.807
Share of correct answers for non-familiar st
0.407
2
108
0.667
Table 5 Intergroup effects criteria for the variable “false alarm rate” Sum of squares
df
Mean square
F
p
η2 p
Affective dimension
2.62e–4
2
1.31e–4
0.0425
0.958
0.001
Residual
0.333
108
0.00308
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Table 6 Joint effects criteria for the variable “false alarm rate” Sum of squares
df
Mean square
F
p
η2 p
Familiarity st
0.00379
1
0.00379
12.38
< 0.001
0.103
Familiarity st & Affective dimension
0.00183
2
9.17e-4
3.00
0.054
0.053
Residual
0.03301
108
3.06e-4
3.3 Response Time When calculating the response time (third DV), all measurements were taken into account when the subject pressed the “m” key. Levene statistics (Table 7) shows the insignificance of the criterion of equality of variances. The mixed ANOVA showed similar results to the “false alarm” variable (Table 3). The familiarity factor was close to statistically significant (Table 8). According to the factor “affective dimension” and the interaction of intergroup and intragroup factors, statistically insignificant results were obtained (Table 9). In the course of the study, close to significant results of the influence of the familiarity factor on the reaction time of the subjects were obtained. Based on previous research [15, 19–21], which stated that the use of long-term memory when performing tasks on WM allows spending less resources of the latter, we can conclude that the efficiency of updating WM rather depends on the stimulus familiarity. Table 7 Levene’s test for the variable “response time” F
df1
df2
p
Share of correct answers for familiar st
0.678
2
108
0.510
Share of correct answers for non-familiar st
0.398
2
108
0.673
Table 8 Intergroup effects criteria for the variable “response time” Sum of squares Affective dimension Residual
0.124 13.045
df
Mean square
F
p
η2 p
2
0.0622
0.515
0.599
0.009
108
0.1208
Table 9 Joint effects criteria for the variable “response time” Sum of squares
df
Mean square
F
p
η2 p
Familiarity st
0.1115
1
0.1115
3.941
0.050
0.035
Familiarity st & Affective dimension
0.0201
2
0.0100
0.355
0.702
0.007
Residual
3.0563
108
0.0283
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Significant results on the influence of the stimulus familiarity factor on the percentage of false alarms in the “n-back” task were obtained. It has been established that the proportion of false alarms decreases with the presentation of familiar stimuli and increases with the presentation of unfamiliar ones. This partly confirms our hypothesis about the positive impact of familiarity and can also be explained by relevant representations in long-term memory, which facilitate recognition and allow fewer errors [21]. When applied to the digital educational environment, the obtained results can be transformed into a recommendation to use the same visual stimuli when developing interconnected educational materials. This will reduce the excessive cognitive load on working memory and use its resources to process new material. There were no significant differences in the speed and correctness of the answers of the subjects depending on the different affective dimension of the images. The influence of a combination of familiarity and emotional coloring of images also turned out to be insignificant, which allows us to refute our main hypothesis about the mutual influence of these two factors on the efficiency of working memory updating. These results are not consistent with previous studies [16, 17], where the affective dimension of stimuli turned out to be significant. One possible explanation could be the difference in study designs. In contrast to the above experiments, where the variable of the emotional coloring of the stimuli was within the group, in our experiment, it was between the groups. The subjects worked with images of only one affective dimension, as a result of which the effectiveness of the emotional impact could insignificantly decrease. There is another difference in the design of experiments. Our test was conducted entirely in a remote format, in which the experimenter has no control over the behavior of the subject. It is in such conditions that distance learning takes place, so the results obtained can be considered relevant for the purposes of our study. The differences in the results with previous studies confirm the need for a reassessment of cognitive processes and knowledge that should be assessed in tests in disciplines mastered in the digital educational environment. The same was said in the work by Virranmäkia, E. et al., comparing the results of a traditional and digital test in geography [25].
4 Conclusion Digital technologies in the educational process have a different impact on learning outcomes. On the one hand, they speed up and improve the quality of learning, but on the other hand, they cause changes in the cognitive sphere of students. When using digital technologies, working memory experiences an increased load, which causes fatigue and decreased performance. It is possible to reduce the negative impact and accelerate the renewal of working memory through the use of educational material with a large number of familiar stimuli. Affective dimension of learning content has an insignificant effect on the renewal of working memory, but may affect overall performance. This requires additional verification. Evaluation tools for determining
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the results of learning using digital technologies should be designed taking into account the changes in cognitive processes occurring in connection with the use of these technologies.
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Soft Skills Development by Means of Digital Pedagogical Cues Elena Chirkova , Elena Zorina , and Abram Maron
Abstract The article deals with the importance of identifying, developing and shaping soft skills that allow for success in professional activities. With the digitalization of adult education, including upskilling for school leaders, attention needs to be paid to the development of certain soft digital skills. This can be facilitated by the use of digital pedagogical cues, which allows working both individually and in a group. It has been experimentally proved that the obvious necessity of the modern educational paradigm is the use of interactive pedagogical tools, which include pedagogical cues, and digital ones as well. As part of the experiment described in the article, possible cues for the development of critical, systemic and creative thinking, as well as emotional intelligence (EQ), are shown. For each presented soft skill, three digital cues are given, which make it possible to understand the principle of selection of pedagogical tools for the development and formation of a certain skill. Keywords Soft skills · Director · Manager · Digital pedagogical cues · Ways of thinking
1 Introduction Within the framework of the modern view of education, professional and personal development will be considered as a combination of various skills. It is believed that 85% of success in any professional field is soft skills, hard skills make only 15%. Soft skills are competencies that can be called personal, because they are directly related to the development of a human being as a person and his/her interaction with E. Chirkova (B) · E. Zorina Saint Petersburg State University of Architecture and Civil Engineering, Vtoraya Krasnoarmeiskaya, 4, Saint Petersburg 190005, Russia e-mail: [email protected] A. Maron Institute of Education Management of the Russian Academy of Education, Zhukovsky Street, 16, Moscow 105062, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_105
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the outside world. It is soft skills that make the basis of the choice of a profession. A person is guided by them when choosing a specialty or job. Hard skills are professional skills required to complete work tasks. Each specialty has its own list of hard skills. Sometimes in scientific literature they are combined into the term “professionally important qualities” [1] or divided into personal characteristics (critical thinking, morality and social responsibility, leadership, the ability to collaborate and cooperate, the ability to solve various kinds of problems, public speaking skills, business and digital communication, etc.) and cognitive competencies (the ability to solve problems arising in the workplace; the ability to consider several alternatives when making decisions; the ability to identify current and future needs in the work process; the ability to evaluate the working process effectiveness result; events prediction; work organization) [2]. Learning twenty-first century skills takes up several questions [3]: What skills have become obsolete after 2015? What new skills are becoming essential in the twentyfirst century? What educational transformations are needed to effectively transfer and develop relevant skills? These questions were partially answered in 2016 by Klaus Schwab who said that the Fourth Technological Revolution had begun and listed the 10 most essential skills that every in-demand employee should possess by 2020: Complex Problem Solving; Critical Thinking; Creativity; People Management; Coordinating with Others; Emotional Intelligence; Judgment and Decision Making; Service Orientation; Negotiation;10. Cognitive Flexibility [4]. They partly coincide with target competencies, which have their own national specifics, including, for example, knowledge of a foreign language and programming language, that is, an increasingly close intertwining of the humanities and technical sciences. This model, helps conclude that most of the above skills and competencies relate both to the professional and personal development of a future specialist and to the development of metasubject competence. In the scientific literature, the issue of skill requirements in various companies and industries is widely discussed [5–8], however, a detailed analysis of skill requirements for different professions in a particular sector remains underestimated. In our case, these are the soft skills of school principals/directors as education managers. These skills are considered by us in the framework of the training of principals/directors of various educational institutions, graduates of pedagogical universities. The problem is what skills a future principal/director needs to possess and whether his/her activities will be related to the professional training of a manager. Taking into account the fact that in Russia the need to introduce professional managers into the field of education is associated with general changes in educational paradigms, significant changes have been made to the reforms of the educational system aimed at innovative transformations, the implementation of which is achieved more successfully on the principles of management. The country is undergoing a process of democratization and decentralization of the management of the education system with the provision of broad independence to educational institutions, including educational and economic issues. At the same
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time, universities and academies of postgraduate education are actively and successfully developing their commercial, intermediary and economic activities to generate new sources of income in order to preserve their intellectual potential. The attitude towards education has also changed among students. They got the opportunity to choose educational institutions, including those for advanced training, to make demands on them in connection with their expectations and requests. All these large-scale changes have led to the problem of using managerial skills among principals of educational institutions, including schools. In the performance of the professional duties of a director these skills proved to be essential. To separate the concepts closely related to the point: manager, education manager and director is of high importance. In a general sense, a manager is a specialist who organizes processes in a certain area of an enterprise or organization, in our case, a school. The main function of a manager is of course management, which includes various processes: planning, organization, motivation and control of activities. An education manager is a professional who carries out the functions of education management. Such a specialist forms up his work on the basis of modern scientific management methods. This is a manager who performs a multidisciplinary activity and is responsible for personnel, documents, pedagogical process and its quality, as well as the competitiveness of the educational institution that is subordinate to him/her. Director is the highest management position of a company, enterprise or educational institution, endowed with almost unlimited opportunities for carrying out economic and financial activities: working out a development strategy, managing finances and implementing personnel changes, purchasing office supplies and organizing corporate events. You cannot say that the functions of a manager, education manager and director differ much. They are in one way or another related to the function of leadership and organization of activities. However, it must be clearly understood that the director/principal is the appointed position. Therefore, on the one hand, he/she is the main one in the educational institution, and on the other hand, he/she remains subordinate. The work of a school director means the presence of such personal qualities (soft skills) as responsibility and organizational skills. These skills are at the core of a leader’s performance. A modern school principal/director should find ways to solve the main task meaning to ensure the innovative nature of education: to set tasks that are important today and may become dominant in further ages. School principals/directors are professional and skillful innovative managers. In addition, the director will not be able to effectively perform his/her duties if he/she does not have intuition, a sense of justice, an analytical mindset, stress resistance [9], communication skills, etc. If we talk about the professional qualities (hard skills) of the director/principal, then it is worth highlighting the need for deep knowledge in the main legal acts regulating the financial and economic activities of the school; modern management methods, etc.
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The director/principal provides internal guidance to the school; establishes and maintains its vision, mission and values of the work of an educational institution, taking into account the opinion of the team. This is the leading role of the headmaster. The director makes a decision, taking into account the regulatory framework, and implements this decision together with the colleagues. The skills listed above are inherent in managers of any level; they are developed at the stage of training or retraining of directors/principals. A modern school director should possess the above human qualities and have the traits of a manager-leader: the principle of respect and trust in a person, the principle of a holistic view, cooperation and social justice, the principle of an individual approach in intra-school management, the principle of permanent professional development and similar principles that determine technology for successful school management. The director is the main person in the school, and this post makes him possess strategic thinking, be clear-sighted, and make a good manager. This formulation of the problem means that school principals are innovation managers [10]. The last thesis also means that a modern specialist should have all the hard skills. Without mastering them, he/she will not be able to effectively carry out his/her activities. Accordingly, they need to be taught. In this case, digital pedagogical cues come to the rescue. They are relevant especially at the present stage, when the whole society is faced with a special way of learning online. The modern teacher had to study digital methods of organizing educational activities, and the director should lead this process. We believe that pedagogical cues are information landmarks in a digital society (verbal or non-verbal), a multifunctional pedagogical tool for generalizing and systematizing knowledge, developing various types of thinking, metasubject competence, implementing ideas of complexity, interactivity, and personalizing the educational process. Also, within the framework of the widespread digitalization of the educational space, we introduced the term "digital pedagogical cue", which is not just a digital copy of the pedagogical cue, but is used with information and communication technologies (ICT).
2 Materials and Methods Being the part of the advanced training of school leaders in the Leningrad Region, an experiment was conducted to prove the hypothesis "Soft skills are formed and developed more quickly if digital pedagogical cues are used for trainings." The participants in the experiment were divided into control and experimental groups. The “upskilling” trend in the labor market is most often accompanied by an increase in education and experience demand [11]. That is why the experimental group included participants who were younger in age and inexperienced in teaching, who wanted to actively develop their digital skills. There were 14 directors in the control group, and 10 directors in the experimental group.
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3 Results All members in the experiment were asked to pass a preliminary survey and calculate which of the selected 4 soft skills (critical, systemic, creative thinking and emotional intelligence) they have developed and to what extent. For this, the materials of the book by Sharma Prashant [12] and the Likert scale adopted in most questionnaires were used, because the recipients had to evaluate each skill in five subsections, putting scores from 0 to 10 (Figs. 1 and 2). Self-diagnosis of emotional intelligence turned out to be the most difficult one, because any educational worker is constantly in a stressful situation. Then the control group was asked to listen to lectures on the development of soft skills, and the experimental group was shown how to develop a certain soft skill with the help of certain digital cues. For the development of critical thinking, it was proposed: • After watching the webinar, fill out the joint digital pedagogical cues “KWL chart” in Google, consisting of three columns (Know-Want-Learnt) and 10 rows according to the number of participants in the experiment. Everyone was able to take an introspection, and to see how the other members of the group did it, as well; 50 40 30 20 10 0
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• Solving a problematic task using the "Fishbone" cue on the classtools.net website in a special section; • To develop communication skills using the "SWOT matrix" cue on a virtual board, where each member of the group had to offer their ideas to each of the 4 cells of the matrix. • For the development of system thinking, it was proposed to use: • “Gantt chart”, which is drawn in spreadsheets and helps to visually display the project schedule; • “Decision tree”, built in a graphical or online text editor and showing a model of decision-making on a problem. The whole group was working on one problem at the same time; • “G.S. Altshuller System operator”, which is a matrix of 9 cells, in the center of which is the object under study (for example, a school), and in the rest you can analyze its past, see the future, find resources and predict the results. • For the development of creative thinking, it was proposed to use: • “Brainstorming” jointly by the whole group on the Linoit.com Internet site; • "6 Thinking Hats", with the help of which it was necessary to make a presentation about yourself; • “Mind Maps” at www.mindmup.com on school development. • To develop emotional intelligence, the group used: • "Emoji" on the translate.yandex.ru website, the members of the group translated the text into emoji and invited the whole group to chat in this way. It was necessary to grasp everyone’s mood and try to improve it among those who lacked optimism. • “Puzzle” on the sites puzzleit.org and www.jigsawplanet.com. We invited the participants to create their own puzzles and share with others, as folding puzzles relieves stress; • “Comic”, which was proposed to create on the site www.toondoo.com on: how to solve one of the difficult situations in the team. After two months of experimental work, a repeated self-questioning of all the participants in the experiment was carried out (Fig. 3). The values of the control group changed insignificantly (plus 1–2 points). The results obtained clearly showed that the results on the development of soft skills in the experimental group were significantly higher than in the control group. In addition, members of the experimental group were asked two additional questions: “Working with which digital pedagogical cues did you find the most productive for each skill?” (Fig. 4) and “Would you like to replace the proposed digital pedagogical cues with a paper analogue as much as possible?” (Fig. 5).
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4 Discussion It must be admitted that agile skills are a prerequisite for success in the information society. Research by Finnish scholars [13] on twenty-first century skills has shown that digital skills develop sequentially, they are based on information skills that teachers must acquire themselves and be able to pass on to future generations. The analysis of the experiment described above, as well as the Finnish survey, showed that the age and digital activity of both directors and teachers affect not only the choice of preferred pedagogical cues (digital pedagogical cues), but also explain the speed of formation of digital skills or soft skills in digital format.
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Fig. 5 Answer question results about replacing digital pedagogical cues with a paper analogue
According to research by scientists from the Netherlands [14], the so-called skills of the twenty-first century consist of technical, information, communication, collaboration skills, as well as critical thinking skills, creative skills, and problem-solving skills, and for each of them there is a digital equivalent. The ability to transmit information online (i.e., use social media, chat and email) is included into digital communication skills. The above experiment also confirms the need to develop digital equivalents of soft skills for productive work in a digital society. If such an opportunity does not exist, then digital pedagogical cues should be used in upskilling. According to the experiment, the most difficult thing was to develop emotional intelligence, because it requires active interaction with people and the presence of an understanding of each other’s emotions and desires. Undoubtedly, this is very important for the leader, who must create a friendly collective body, ready for cooperation. All three digital pedagogical cues that have been proposed have a small playful dimension because, according to Tang, Vezzani, and Eriksson [15], playful elements support the development of positive interdependence in team activities.
5 Conclusions Analysis of the literature has shown that there are many conflicting opinions about what soft skills are, what skills are needed for a school principal and how to develop them in a digital society. The pandemic environment and mandatory e-learning have provided additional opportunities for the digital development of leaders through continuing education courses using ICT resources and tools.
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The result of the experiment confirmed the idea that at present there is a growing demand for creative, non-standard-thinking directors-managers who are ready to respond quickly to changing working conditions and solve professional pedagogical problems creatively. Justification of the need for the formation of soft skills in the context of the implementation of the professional standard of the director/principal is one of the conditions for ensuring the quality of professional training in general.
References 1. Andreevsky E, Akhmedkhanov M, Lavina T, Streltsov R (2015) Improving professional and psychological selection and further development of professionally important qualities of specialists on the protection of important state facilities in the course of educational activities with the use of information and communication technologies. Proc Soc Behav Sci 214:497–504. https://doi.org/10.1016/j.sbspro.2015.11.749 2. Podolsky OA, Pogozhina VA (2016) Meeting tomorrow’s expectations: In Search of Core Competencies and Ways of Assessing Them. Russ Educ Soc 58(9–10):623–641. https://doi. org/10.1080/10609393.2016.1315272 3. Lavi R, Tal M, Dori YJ (2021) Perceptions of STEM alumni and students on developing 21st century skills through methods of teaching and learning. Stud Educ Eval 70:101002. https:// doi.org/10.1016/j.stueduc.2021.101002 4. Schwab K (2017) The fourth industrial revolution. Crown Business, New York 5. Lyu W, Liu J (2021) Soft skills, hard skills: What matters most? Evidence from job postings. Appl Energy 300:117307. https://doi.org/10.1016/j.apenergy.2021.117307 6. Deming D, Kahn LB (2018) Skill requirements across firms and labor markets: evidence from job postings for professionals. J Labor Econ 36(1):337–369. https://doi.org/10.1086/711490 7. Acemoglu D, Autor DH (2010) Skills, tasks and technologies: implications for employment and earnings. NBER Working Paper No. w16082. https://ssrn.com/abstract=1624142 8. Autor DH, Dorn D (2013) The growth of low-skill service jobs and the polarization of the US labor market. Am Econ Rev 103(5):1553–1597. https://doi.org/10.1257/aer.103.5.1553 9. Chirkova EI, Zorina EM, Rezinkina LV (2022) Digital pedagogical cues for the development of creativity in high school. technology, innovation and creativity in digital society. Springer Nature Switzerland, St. Petersburg, p 858–867. https://doi.org/10.1007/978-3-03089708-6_69. 10. Hsieh TS, Kim JB, Wang RR, Wang Z (2022) Educate to innovate: STEM directors and corporate innovation. J Bus Res 138:229–238. https://doi.org/10.1016/j.jbusres.2021.09.022 11. Hershbein B, Kahn LB (2018) Do recessions accelerate routine-biased technological change? Evidence from vacancy postings. Am Econ Rev 108(7):1737–1772. https://doi.org/10.1257/ aer.20161570 12. Prashant S (2019) Soft skills: personality development for life success. BPB Publication, New Dehli 13. Saikkonen L, Kaarakainen M-T (2021) Multivariate analysis of teachers’ digital information skills – the importance of available resources. Comput Educ 168:104206. https://doi.org/10. 1016/j.compedu.2021.104206 14. Laar E, Deursen A, Dijk J, Haan J (2020) Determinants of 21st-century skills and 21st-century digital skills for workers: a systematic literature review. SAGE Open 10:1–14. https://doi.org/ 10.1177/2158244019900176 15. Tang T, Vezzani V, Eriksson V (2020) Developing critical thinking, collective creativity skills and problem solving through playful design jams. Think Skills Creat 37:100696. https://doi. org/10.1016/j.tsc.2020.100696
Methodological Approaches to Modeling Dynamic Development of Regional Ecological and Socio-Economic Systems Natalia Ivanova
Abstract The relevance of the article is due to the problem of maintaining stable parameters of ecosystems, which will make it possible to make the transition to “green” development, reduce production costs and increase the competitiveness of the national economy. In the context of a growing shortage of non-renewable resources, exacerbation of environmental problems, it is necessary to introduce resource-saving and resource-saving innovative “green” technologies aimed at the production of new types of “green” products, which is a prerequisite for successful economic development and environmental conservation. The manifestation of increased attention to the problem under study is based on an increase in the complexity of the use of raw materials, an increase in the depth of processing, i.e. the most complete, economically justified extraction of all useful components. contained in raw materials and production wastes extracted from hydrocarbon raw materials. The integrated use of raw materials also involves the processing and disposal of by-products, industrial waste through their recycling. The main factor in reducing the burden on the environment, reducing resource intensity are innovative transformations based on the integrated use of environmentally friendly low-waste technologies. The main components of the scientific novelty is the need for the transition of sectors of the national economy from technogenic to sustainable environmentally balanced development, which will contribute to the greening of the economy through the modernization of processing industries, as well as increase the resource efficiency of the use of hydrocarbons. raw materials, as well as reduce environmental risks. Keywords Hydrocarbon resources · Green economy · Resource efficiency · Sustainable development · Integrated use · Environmental and economic efficiency · Decoupling
N. Ivanova (B) Saint Petersburg State University Aerospace Instrumentation, 67, Bolshaya Morskaya, St. Petersburg 190000, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_106
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1 Introduction At the present stage of economic development, it is necessary to solve the problems of increasing production volumes with a simultaneous decrease in the load on the environment, that is, to achieve the “decoupling” effect. It can be achieved through the widespread introduction of innovative technologies for deep processing of oil and gas resources, aimed at resource-efficient use of raw materials based on complexity, rationality and zero-waste. The implementation of these measures will reduce environmental risks significantly and enter the trajectory of sustainable development of the national economy, which will contribute to the transition to “green” development of not only the oil and gas complex, but also the national economy [1]. The current ecological situation predetermines the need to regulate the technogenic impact on the environment, which is impossible without the introduction of rational and resource-efficient use of hydrocarbons; it means that a comprehensive greening of all production processes of the oil and gas complex is required. Greening within the framework of the concept of sustainable development involves increasing their efficiency and reducing resource intensity, i.e. achieving a decoupling effect, in which production should be aimed at increasing resource efficiency and at the same time reducing waste and emissions, i.e. to minimize environmental risks.
2 Methods In the theoretical aspect, the use of economic mechanisms can be represented in the form of a hierarchically formalized complex of economic and mathematical models and methods, the combination of which should ensure socio-economic efficiency as the achievement of strategic goals and tactical tasks of interstate, national and regional development [2]. The model of the functioning of the economic mechanisms of state and interstate management of the processes of reindustrialization, the use of natural resources and the social sphere can be represented graphically in a two-dimensional coordinate system that characterizes the relationship between public and corporate interests and responsibilities (Fig. 1).
Corporate spending
Public benefits (PB) Corporate income (CI)
Damage to society Fig. 1 Coordinate system of the relationship between public and corporate interests
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The axes of the coordinate system are: – a public interest axis reflecting public benefits and harms, – axis of corporate interests, reflecting corporate losses and gains. Corporate spending includes operating costs associated with ongoing environmental management and equipment maintenance; investments in environmental technologies and equipment; payments for the use of natural resources; fines for violation of established environmental requirements. Corporate income includes income from natural resources; reputation of the corporation; income from other activities. Social benefits: improved quality of life through improved environmental conditions; growth of population incomes and creation of new job places; an increase in budget revenues for the use of natural resources; receipt of fines into the budget for violation of environmental legislation [3] (Fig. 2). Damage to society: as a result of a decrease in the quality of life; as a result of the loss of natural resources and a decrease in payments to the budget for the use of natural resources. The relationship between the interests of society and corporations in the field of environmental management can be represented in the form of curves located in the corresponding quadrants of the coordinate system [4]. The system of interrelations between the interests and responsibilities of society and corporations essentially constitutes the content of the economic mechanisms of state and interstate management of rational environmental management, determining the effectiveness of their functioning. On the other hand, a specific economic mechanism can modify the system of individual interrelationships of interests and responsibilities of society and corporations that use natural resources.
Fig. 2 The system of interconnection of interests and responsibilities of society and corporations
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Fig. 3 Modeling the application of economic instruments that regulate the division of responsibility between society and corporations that use natural resources
Modeling the application of economic instruments regulating the division of responsibility between society and corporations that use natural resources [5]. In Fig. 3, the curve P0 reflects a certain division of responsibility between society and the corporation at a given level of intensity of use of a particular type of natural resources, which means that the costs of implementing environmental protection measures reduce the environmental damage caused to society. This dependency can be represented as a function: DS = f (CS, if I = const) Straight line C0 characterizes the dependence of the environmental damage caused to society on the intensity of nature management and the scale of environmental protection measures implemented by the corporation. This dependence essentially means the distribution of responsibility between society and the corporation-user of natural resources and can be defined as the cost of damage (C). The angle of inclination of the straight line (C) reflects what part of the responsibility for the results of environmental management is borne by the corporation. For example, in state C1 , a corporation-user of natural resources bears greater responsibility at the same level of damage than C0 . In practice, the angle of inclination is determined by the rates of payments for negative impact on the environment, payments for pollution, compensation payments, etc. With an increase in the intensity of the use of a natural resource, the P0 curve moves along the straight line C0 to the P1 state, which corresponds to an increase in damage to society (DS1 ) and an increase in the cost of environmental protection measures or payments (CS1 ). An example of such a situation can be considered compensation
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Fig. 4 Modeling the application of economic instruments that regulate the distribution of benefits and incomes between society and corporations that use natural resources
for damage caused to the natural environment through the application of a system of fines. In this case, the choice of a scenario for the behavior of a corporation of a natural resource user will be determined by the ratio, on the one hand, of the size of fines for, for example, excess emissions, and the cost of environmental protection measures, on the other. The intersection points of the straight line (C) and the curve (P) in specific conditions can characterize the optimal division of responsibility between society and corporations that use natural resources [6]. Modeling the application of economic instruments that regulate the distribution of benefits and incomes between society and corporations that use natural resources. In Fig. 4, the P0 curve reflects the distribution of benefits and incomes between society and the corporation for a given level of intensity of use of a particular type of natural resources. This means that the state must regulate the amount of income received by corporations from the use of natural resources in public ownership. The ratio of distribution of benefits and incomes at a given level of intensity of natural resource use can be described by the curve P0 . Straight line C0 characterizes the ratio of interests expressed in the distribution of benefits received by society and corporate incomes when the intensity of the use of natural resources changes. This dependence essentially reflects the value of a certain type of natural resources [7]. The angle of inclination of the straight line (C) reflects how the value of natural resources (the results of environmental management) is distributed between society and corporations. For example, in state C1 , the corporation-user of natural resources will receive most of its income, while society will receive less than in state C0 . In practice, the angle of inclination is determined by the terms of environmental agreements, assessment results, and government programs. With an increase in the intensity of the use of natural resources, the P0 curve moves along the straight line C0 to the P1 state, which corresponds to an increase in the
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corporation’s income (CI1 ) and the benefits received by society (PB1 ). An example of such a situation can be considered the development of highly profitable deposits or the improvement of the market conditions for certain types of minerals. Moreover, conversely, in the event of further development of deposits due to depletion of reserves and deterioration of mining and geological conditions, the state may change the distribution of income and benefits in favor of corporations that use natural resources. The intersection points of the straight line (C) and the curve (P) in specific conditions can characterize the optimal division of responsibility between society and corporations that use natural resources [8]. Modeling the application of economic instruments that ensure the alignment of public interests and corporate responsibility. In Fig. 5, the straight line C0 reflects D the alignment of the interests of society and the responsibility of corporations at a given level of intensity of use of a specific type of natural resources. This means that the state must correlate the benefits received by society with the responsibility of corporations, expressed by their financial obligations related to the implementation of established norms and limits for rational use of natural resources and impact on the environment. According to the straight line C0 shown in the figure, the benefits received by society are proportionally dependent on the expenses of corporations for environmental protection measures and the elimination of the consequences of negative impact on the environment. On the other hand, the P0 curve reflects the relationship between the benefits received by society from the costs of corporations to protect the environment. Society limits and regulates environmental emissions and requires corporations to spend on environmental protection measures.
Fig. 5 Modeling the application of economic instruments that ensure the alignment of public interests and corporate responsibility
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The society, establishing the appropriate requirements for the impact on the environment, on the one hand, affects the amount of environmental expenditures of corporations; on the other hand, it agrees to partially reduce the benefits from changes in the quality of the environment [9]. At the same time, an increase in environmental requirements for users of natural resources leads to additional expenses of corporations for measures in the field of rational use of natural resources and environmental protection. For example, the government may impose excessive environmental requirements on emissions, which would require huge expenses from corporations and lead to bankruptcy. This is the value of public goods, expressed by direct C0 and C1 , which are paid for by corporations and is determined by the ratio: on the one hand, the additional benefits of society (PB = PB1 – PB0 ), achieved by increasing environmental requirements; on the other hand, additional costs for corporations necessary to meet stricter environmental requirements (CS = CS1 – CS0 ). The angle of inclination of the straight line C is determined by the ratio of the value of social benefits and the costs of corporations for environmental protection measures. Curves P0 and P1 characterize different degrees of intensity of use of natural resources [10]. The intersection points of the straight line (C) and the curve (P) in specific conditions can characterize the optimal coordination of the interests of society and responsibility and corporations-users of natural resources. Modeling the application of economic instruments that ensure the alignment of corporate interests and public responsibility. In Fig. 6, straight line C0 reflects the alignment of the interests of corporations and the responsibility of society at a given level of intensity of use of a particular type of natural resources. This means that the state must regulate the income received by the corporation, taking into account the damage caused to society on the basis of established norms and limits for rational use of natural resources and impact on the environment. At the same time, according to the straight line C0 shown in the figure, the damage caused to society depends on the financing of environmental activities by corporations and, in this regard, is reflected in their income. Corporations strive to increase their profitability by reducing environmental costs [11]. However, society limits the ratio of damage, on the one hand, and corporate income, on the other. At the same time, the more a corporation reduces the damage to society, the more preferences it receives from society. It is the social value of corporate income, which is “paid for” by the society by agreeing to the deterioration of environmental conditions (standards). Curve P0 reflects the relationship between the damage to society from corporate incomes for environmental protection. The society encourages corporations to reduce their environmental emissions, at the expense of the corresponding expenditures of corporations for environmental protection measures.
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Fig. 6 Modeling the application of economic instruments that ensure the alignment of corporate interests and responsibilities
The society, offering natural resource corporations additional preferences in the form of soft loans, tax and payment benefits, aims to reduce the impact on the environment. At the same time, various economic incentives for users of natural resources lead to additional expenses of corporations for measures in the field of rational use of natural resources and environmental protection and, as a result, a decrease in their income, which is reflected in the form of curves P0 and P1 . Straight lines C0 and C1 represent the value of measures of economic incentives for corporations-users of natural resources in the field of environmental management. It is expressed by the ratio of the cost of government preferences ( PB = PB1 – PB0 ), on the one hand, and a change in the profitability of corporations (CI = CI1 – CI0 ) – on the other. The angle of inclination of the straight line C is determined by the ratio of the value of social benefits and the costs of corporations for environmental protection measures. Curves P0 and P1 characterize different degrees of susceptibility (elasticity) of state incentives by corporations [12]. The intersection points of the straight line (C) and the curve (P) in specific conditions can characterize the optimal coordination of the interests of corporations-users of natural resources and the responsibility of society. Functioning of the main mechanisms of public administration in the field of environmental management V.A. Trapeznikov substantiated the dependence of the effectiveness of public administration on scientific research. Based on this approach, graphically, the dependence of the effectiveness of public administration in the field of rational use of natural resources and environmental protection on the volume of investments can be expressed exponentially (Fig. 7). At the same time, under the effectiveness of public administration we mean the totality of benefits received by
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Fig. 7 Graph of the dependence of the effectiveness of public administration in the field of rational use of natural resources and environmental protection on the volume of investments
society, which in practice can be expressed in the form of the degree of achievement of the set goals and objectives. As the volume of investments (I) in environmental protection increases, its effectiveness (P) also increases, represented by points on exponents 1, 2, 3: I3 > I2 > I1 , while P3 > P2 > P1 . As shown in the graph, with a certain amount of funding, the effectiveness of environmental protection initially rises sharply. However, growth continues up to a certain limit, after which, with the previous structure of financing of investments in environmental protection, due to the previously adopted priorities of public administration, it slows down [13]. A lot of works have been devoted to the role of public investments, but traditionally they are considered as a source of economic growth. At this moment, a change in the priorities of public administration becomes especially urgent, as a rule, accompanied not only by an increase in the volume of investments, but also by a change in their structure with a concentration on breakthrough areas. This process is shown in the graph as a sequential transition: A1 → A2 → A3 . At the present stage, such changes are due to the transition of environmental activities to an innovative basis for development. In practice, this transition is based on further improvement of the existing system of state management of rational use of natural resources and environmental protection. Attempts to simulate these processes using traditional linear programming models, balance models and others have shown
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their low efficiency, due to the nonlinear and complex nature of the dependences of the analyzed parameters. Therefore, the search for new approaches to forecasting ecological-socio-economic systems has become an independent task of this study. From this point of view, it is of interest to use models built based on T. Kohonen’s neural networks, based on self-learning and clear clustering of input influences. To use them, it is necessary to have a voluminous database on the states and changes of the analyzed object. Modern attempts to stimulate environmental protection and rational use of natural resources are associated in a broad sense with the reform of the international financial system, and in a narrow sense, with the prospect of introducing an ecological currency, the so-called green currency.
3 Discussions Greening through the transition from technogenic to sustainable development will reduce environmental pollution and the amount of waste while increasing the results. The attention should also be paid to the preliminary preparation of raw materials for processing, related to its purification from various impurities, which largely contributes to the reduction in the cost and qualitative improvement of technological processes, and the reduction of environmental risks. Thus, the purification of oil from sulfur and the desulfurization of fuel oil burned in furnaces helps to reduce emissions of sulfur dioxide (SO2 ) into the atmosphere. As for the state regulation of greening processes, the main attention should be paid to the environmental modernization of production. However, the measures taken so far to introduce ecological techniques and technologies did not fundamentally solve the problems of resource conservation and resource efficiency [14]. Thus, the most expedient are the development and implementation of environmentally friendly biotechnologies, recycling technologies (reuse or recycling production waste), as well as low-waste technologies. The development of environmentally friendly industries will reduce the man-made impact on the natural environment, which will contribute to entering the trajectory of sustainable development and will allow Russia to make the transition to a “green economy”.
References 1. Abrosimov AA (2018) Ecology of processing hydrocarbon systems. Chemistry, p 608 2. Astafieva OE et al (2017) Ecological foundations of nature management: a textbook for secondary vocational education. Yurayt Publishing House, Moscow, p 354 3. Gurova TF et al (2019) Ecology and rational use of natural resources: textbook and workshop for academic bachelor’s degree, 3rd edn, revised and supplemented. Yurayt Publishing House, Moscow, p 188
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4. Danilov-Danilyan VI (ed) (2019) Ecology: textbook and workshop for academic bachelor’s degree. Yurayt Publishing House, Moscow, p 363 5. Kolesnikov EY, Kolesnikova TM (2017) Environmental impact assessment. Security expertise: textbook and workshop for undergraduate and graduate programs, 2nd edition, revised and enlarged. Yurayt Publishing House, Moscow, p 469 6. Riznichenko GY (2019) Mathematical modeling of biological processes. Models in biophysics and ecology: textbook for undergraduate and graduate programs, 2nd edition, revised and enlarged. Yurayt Publishing House, Moscow, p 181 7. Potapov AD (2016) Ecology: textbook for universities, 2nd edition, revised and enlarged. Higher School, Moscow, p 528 8. Baklanov PY (ed) (2017) Regional nature management. Logos, Moscow, p 160 9. Stepanovskikh AS (2015) Applied ecology: environmental protection. Unity, Moscow, p 751 10. Chelnokov AA, Yushchenko LF (2018) Fundamentals of industrial ecology: Textbook. Higher School, Minsk, p 343 11. Protasov VF (2000) Ecology, health and environmental protection in Russia: training and reference manual. Finance and Statistics, Moscow, p 672
Icebreaker Fleet Management in Simulation Models of the Arctic Marine Transport Systems Alex Topaj , Alexander Buyanov , Alexander Karpenko , and Andrey Malykhanov
Abstract The report raises the issue of reflecting the processes of planning and dispatching the icebreaker fleet exploitation in the simulation models of the Arctic transport systems. Due to the theory of agent and discrete-event simulation, icebreakers can be considered as resources that help entities (cargo vessels) to move along to the process diagram. It means, that any such simulation model must include a certain intelligent algorithm for operational planning of icebreakers’ work, which would adequately reflect the logic of their dispatching in real icebreaking fleet management practice. Several alternative approaches for assigning support tasks to icebreakers are considered: ad hoc “greedy” algorithms, a heuristic algorithm for placing icebreakers on areas of responsibility, the use of built–in as well as third party optimization engines. So, we attempt to view the subject from different points of view and to present a range of specific solutions from different development teams. The analysis and comparison of these methods are carried out on test scenarios and configurations of the simulated transport system. Keywords Arctic shipping · Icebreaker escorting · Convoy · Combinatorial optimization · Fleet management · Simulation of transport systems
1 Introduction Computer simulation is a powerful tool for analyzing strategic and design solutions in the development of the regions of the Far North. Existing in Russia and beyond A. Topaj (B) Bureau Hyperborea Ltd., 6 Kavalergardskaya Street, 191015 Saint-Petersburg, Russia e-mail: [email protected] A. Buyanov · A. Karpenko Central Marine Research and Design Institute, 6 Kavalergardskaya Street, 191015 Saint-Petersburg, Russia A. Malykhanov Amalgama Ltd., Office 75, 24/5A Karla Libknehta Street, 432017 Ulyanovsk, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_107
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experience in the field of creating such models can serve as the basis for planning shipping on the Northern Sea Route [1]. An important logical element of the simulation model should be a module describing the icebreaker fleet management system. Due to the theory of agent and discrete-event simulation, icebreakers can be considered as resources that help entities (cargo vessels) to move along to the process diagram. However, icebreaking assistance has a number of fundamental features that do not allow it to be unambiguously described in the terms of standard procedures for the seize, use and release of an “ordinary” resource. These features are as follows: 1. An icebreaker is a moving resource, and it can move independently to its place of use according to its own movement pattern. 2. An icebreaker is a shared resource, thus one icebreaker can be used to support the movement of several cargo vessels (a caravan) on one section of the voyage. 3. An icebreaker is an optional resource, since modern ice class cargo vessels are capable of moving independently in a fairly wide range of ice conditions. 4. An icebreaker is a limited and expensive resource. Icebreaking assistance can significantly increase the speed of passing through a heavy ice section, but this service is quite expensive [2]. At the same time, the limited number of nuclear icebreakers (by 2025 there should be 6–8 Russian nuclear icebreakers in operation) together with a sharp increase in cargo traffic will inevitably lead to the service shortages. Therefore, any simulation model of the NSR transport system must include a certain intelligent algorithm for operational planning of icebreakers’ work, which would adequately reflect the logic of their dispatching in real icebreaking fleet management practice [3]. While executing the simulation model within the selected planning time horizon, this algorithm should provide answers to the following questions: • • • •
What is the optimal order of vessels in an icebreaking escort? Which vessels will join each icebreaker caravan of? Where should the caravan gathering and release points be located? What vessels will be able to pass the whole or part of the voyage route independently, at what time and fuel costs?
The use of the block of intelligent management of objects and processes in such “strategic” simulation models makes them more valuable for research, planning and forecasting. It is typical of the mathematical simulation modeling problem in many other related subject areas [4]. Icebreaker assistance planning can be referred to the level of tactical fleet planning, for the solution of which various mathematical methods are used, such as the brute force method, the use of “greedy” type heuristics, full or semi-heuristic combinatorial optimization [5, 6]. The implementation of combinatorial optimization algorithms in a simulation model can be done in two ways: the first one implies using functions of external software tools—specialized problem solvers, the second method involves creation and development of a fundamentally new class of solutions in the field of
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information technologies, such as simulation modeling environments and platforms with integrated combinatorial planning and discrete optimization tools. The article describes and compares several alternative approaches to solving the problem of describing the logic of icebreaker support within the selected test simulation model of an extremely simplified Arctic shipping transport system. This study attempts to view the subject from different points of view and to present a range of specific solutions from different development teams.
2 Materials and Methods A very simple simulation model in the AnyLogic framework was created as a testing ground for comparing alternative algorithms for operational management of the icebreaker fleet as part of the Arctic transport system. This model describes carriages of ice-going cargo vessels along the simulated Northern Sea Route. The geographical environment for the movement of model vessels is a one-dimensional graph containing six nodes and five consecutive edges (sections). The length of each section is assumed to be 300 nautical miles, and the total length of a single voyage is, respectively, 1500 miles. Ice conditions in each separate section change at a specified update rate. Within each section ice conditions are assumed to be the same. A single characteristic chosen as an indicator of ice conditions in the section is the severity, ranging from 0 (open water) to 5 (extremely heavy ice). “The entities” represent cargo vessels voyages to be carried out in two directions: from east to west or from west to east. Only one vessel size is considered. Vessels can pass voyage sections either independently or with icebreaker assistance. The number of available icebreakers in the transport system and their initial location are set by the configuration parameters (the basic configuration supposes the operation of two icebreakers). Dependence of vessel’s own speed on severity of ice conditions at the location area is a predefined table function, where the maximum speed is 10 knots for open water and 0.2 knots for extremely severe ice conditions. The speed of an icebreaker movement and the speed of a vessel in a convoy are assumed to be 10 knots regardless of the current severity of ice conditions at a given section. A caravan of vessels being escorted by an icebreaker can be composed and released only at the nodes at the section boundaries. The maximum number of cargo vessels in a caravan is limited by the specific model parameter. The following options were considered as alternative approaches to form an icebreaker operation plan in the described test simulation model: • Several implementations of simple ad hoc “greedy” algorithms formulated as a predefined set of rules (decision tree). By these rules, there determined the need for icebreaker support of the current vessel on the next voyage section and selected a suitable icebreaker. • An extended version of the ad hoc algorithm based on determining areas of responsibility and optimal arrangement of icebreakers at each time interval that is equal
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to a given planning horizon. This logic of icebreaker fleet management is in many aspects similar to the existing actual practice. • Development of an icebreaker operation schedule at each re-planning cycle by accessing an external combinatorial optimization engine—the OptaPlanner library [7]. • Implementation and study of the described model in an alternative high-level information framework Amalgama Platform [8], developed by Amalgama Software company and combining the functionality of simulation modeling and combinatorial optimization. Further down there is a brief description of the logic and implementation principles for each of the above mentioned approaches.
2.1 “Greedy” Ad hoc Algorithms Two ad hoc algorithms were considered as reference variants of primitive icebreaker control logic. The first corresponds to the most elementary case, when regardless of the presence or proximity of an escort icebreaker and the severity of ice conditions on the next section of the route, all vessels move independently. The second simple ad hoc planning algorithm implies that the vessel calls the nearest available icebreaker for the passage through the next section of the route only if the speed of independent movement on it does not exceed the critical speed Vcr.
2.2 Method for Determining Areas of Responsibility (Support) and Optimal Placement of Icebreakers Organization of icebreaking assistance for the transport fleet on the principle of icebreakers duty in certain sections of the route consists of two successive tasks: clustering of ice areas and placement of icebreakers between them. Clusterization of ice areas is made upon criterion of the severity of ice navigation conditions. This procedure is executed as follows: • multiple areas are sorted by clustering criterion in descending order; • the area with the highest criterion value becomes the first element of the first cluster; • the areas with less than (1 – k) times (0 ≤ k ≤ 1) criterion difference fall in the same cluster and are sorted in descending order of the criterion value; • the first area that does not fit into the cluster of the section with the highest criterion value becomes the first element of the second cluster, etc. Upon the results of ice areas clustering, there solved the task of icebreakers placement on ice sections (Fig. 1).
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Fig. 1 Algorithm of icebreakers placement by areas of responsibility
Choice of a particular icebreaker to be on duty in a certain ice area is based on the criterion of the minimum distance from the icebreaker to the area. For this purpose, a matrix of distances from each icebreaker to each sea area is built. It is used to determine, in descending order of clustering criterion, which icebreaker should be sent on duty to the considered ice area. Periodicity of icebreakers placement as well as ice area clustering tasks are the same and depend on the frequency of data for clustering criterion calculation. During the voyage, when passing the route, the model vessel considers the possibility of attracting an icebreaker only in the vicinity of the duty ice areas. The following algorithm is used to determine the need for icebreaking escort. It is considered that a vessel does NOT NEED icebreaking assistance on the ice area if: • the own speed of the vessel is not less than the allowable speed on the area; • it is a duty area, but the waiting time for the escort is not reasonable, i.e. it will be faster to pass the section on its own; • the area is off-duty and after the change of weather conditions the most severe ice conditions are not expected at the site. • And on the contrary, a vessel NEEDS icebreaking escort if: • it is a duty area and it is more profitable to wait for an icebreaker and pass the section under the escort, rather than without it; • the area is off-duty, but after the change in weather conditions, the most severe ice conditions are expected at this site. The selection of the best parameter values of the described algorithms is carried out within the AnyLogic optimization experiment with several stochastic replications per one simulation (Monte Carlo method). Random variables in the experiment are: time interval between vessel arrivals (exponential distribution), direction of movement of newly arrived vessels (uniform distribution). Parameters defined within optimization are: limit deviation rate of clustering criterion when comparing pairs of areas (k),
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limit number of duty icebreakers in the area (l), allowable speed of independent vessel passage through the ice area Vcr, necessity to leave by time-out, logical type (iTO), time-out duration, hour (kTO). The described principle of icebreaker duty in the ice areas meets the following requirements: • insurance of navigation safety—at least one icebreaker will always be on duty in the most difficult sections of the sea route; • performance of high-priority tasks; • when changing the placement, icebreakers will first enter on duty in the most difficult route sections.
2.3 Usage of the External Combinatorial Optimization Solver OptaPlanner for the Simulation The key point of the described implementation variant is that right within the execution of a simulation model there carried out a continuous operational rescheduling of cargo vessel voyages and icebreaker assignments. This issue is solved by the access to a specially developed library based on the external optimization engine OptaPlanner. OptaPlanner is a freely distributed, as a Java class library, set of software tools designed to solve a wide range of combinatorial optimization problems [7]. OptaPlanner engine contains a large set of built-in tools both for forming correct initial approximation, such as “first fit” and “best fit”, and local search algorithms, such as “tabu search”, “simulated annealing”, “hill climbing search”, etc. The main task to be solved to connect external combinatorial optimization algorithms to the simulation model was to create a special adapter, that is, to reduce model descriptions to the entities and terminology of the used solver. It should be noted that the OptaPlanner library is a high-level add-in extending the standard Java syntax, which allows describing a particular problem in the usual terms of the considered subject area. The essence of the optimization problem is technically expressed in special annotation of certain classes of domain information model, i.e. specifying what associative links (planning variables) for what instances of entities (planning objects) should be varied and selected from the pre-defined sets of options to achieve a given quality criterion of the whole system. A detailed view of the object information model for the given task (determining voyage sections needed in icebreaking assistance under conditions of limited icebreaker resource) is shown in Fig. 2. It is clear that the variables to be iterated over and optimized in this case are the links of voyage sections to the exemplars of the “Support Task” class, which describe ordered icebreaker tasks to escort cargo vessels. If the corresponding field in the “Route Section” entity class is set to null, it means that this voyage segment is passed by the vessel independently. And if several segments of different voyages with the same absolute sequence identifier point to the same icebreaker task, this corresponds to the case of one icebreaker escort of a caravan.
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Fig. 2 Object model of the data domain for planning icebreaker assistance of cargo vessels in the OptaPlanner solver
In the logic of the simulation model, communication with the external module of operational planning is organized through a special proxy component. The total duration of all considered voyages is chosen as the minimized value (optimality criterion). Limitation on the number of iterations in the guided search algorithms is defined by setting the total calculation time, so the best plan found during this time is issued as the current quasi-optimal solution. Such technology of interaction with external optimization engine allows us to avoid critical slowdown of the simulation model. The result of the planning module’s work is a formal description of voyage tasks for cargo vessels and assistance tasks for icebreakers. The resulting plan is executed in a directive way in the simulation model until the next call of the rescheduling procedure, after which all incomplete and newly received requests for the voyage are carried out in accordance with the updated execution plan. Integrated Model with Built-in Optimization Engine on Amalgama Platform The model was developed on the high-level simulation platform Amalgama Platform [8]. The model exactly reproduces the above-described logic of the icebreaker work to assist cargo vessels on their voyages. Icebreaking assistance is presented as a sequence of tasks. Each task determines the icebreaker’s escort of one or several cargo vessels on the edge of the transport network (route section). The escort tasks are carried out simultaneously by the icebreaker and the escorted cargo vessels; the task sequence of both types of vessels is illustrated in Fig. 3.
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Fig. 3 Icebreaker and cargo vessel status diagrams
Thus, the icebreaker’s task to assist cargo vessels is divided into 3 phases (Fig. 4), while phases 1 and 2 can be missing, and phase 2 can have options A or B, but not A and B together. Every time one or more vessels arrive at any node of the transport network, a procedure of the fleet rescheduling is performed. Planning involves escort task sequencing for each icebreaker and cargo vessel to be performed at a given horizon of model time. The horizon is an input parameter of the model and equals to 7 days for all mentioned calculations. The sequence of tasks is called a schedule. The procedure for generating each schedule depends on the following parameters: • T ib —maximum arrival time of an icebreaker to the meeting node, set in days. Time limit prevents the assign of icebreakers to too distant tasks. • T tv —maximum arrival time of a cargo vessel to the meeting node, set in days. Due to the limits, the escort can be organized only from the nodes close enough to the current position of the cargo vessel.
Fig. 4 Phases of cargo vessels escort by an icebreaker
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• N max —maximum possible number of vessels in a caravan. • Each parameter value set < T ib , T tv , N max > corresponds to a certain schedule. Before the beginning of the simulation experiment these parameters’ value sets P, made of 168 elements, are specified. The set P is obtained by iterating over parameters of the schedule generation in the following ranges with discreteness 1: Tib = {0, 1, . . . , 7}, Ttv = {1, 2, . . . , 7}, Nmax = {1, 2, 3} The procedure of scheduling vessel operation consists of two steps. At the first step, a schedule s is generated for each element p of P. Let us denote the set of all generated schedules as S. At the second step, from all the elements S there selected a schedule with the largest non-negative total time gain of cargo vessels. The vessel time gain is calculated as follows: • defining of the position x that the vessel will reach, with all scheduled escorting tasks considered at the time t, where t is the minimum of two values: the end moment of the planning horizon and the moment the vessel reaches the end node of the transport network; • determining of the time point t 0 , when the vessel would reach position x without an escort; • calculation of the difference t 0 -t. In the general case the gain can be negative, for example, if it turns out that it is faster for a cargo vessel to reach the end of the route rather than wait for an icebreaker for a long time. When calculating vessels placement, it is assumed that the schedule of ice situation changes is fully known within the planning horizon, and beyond the horizon there used an extrapolation of the last known value. The cargo vessels appearance is also supposed to be known by the system within the planning horizon. The planning procedure having been completed, the yielded schedule tasks are sequentially executed by the icebreakers and the cargo vessels. If the planning horizon is big enough (compared to the task execution time), it is likely that not all of the scheduled tasks will be executed, as the next moment of the planning procedure will take place before the start time of the last task. However, such tasks can still be useful, for example, for the cargo vessels to wait for the icebreakers completing their previous escorting tasks.
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3 Results The comparison of the proposed approaches to icebreaker fleet management in simulation models of the Arctic marine transport system was carried out for a set of test scenarios describing ice condition dynamics on the selected sections of the route and a predetermined schedule of cargo vessel voyages. Table 1 shows sample results of this comparison for three reference scenarios. • Scenario 1. Regular vessel arrivals (1 voyage per day) and uniform random distribution of the supposed severity of ice conditions (with no temporal and spatial correlation of this random process). A total of 150 voyages of cargo vessels, two icebreakers. • Scenario 2. Random schedule of vessel arrivals (Poisson flow of requests with 1 voyage per day intensity) and ice condition dynamics on the route sections of significant temporal coherence and high value of average severity. A total of 156 cargo vessel voyages, 2 icebreakers. • Scenario 3. Random schedule of vessel arrivals (Poisson flow of requests with 1 voyage per day intensity), relatively light ice conditions on the route sections with significant spatial correlation. A total of 141 cargo vessel voyages, 2 icebreakers. The criterion of the average voyage time in hours was chosen as a quality factor of the employed planning algorithm (Table 1). The results of the icebreaker fleet operation management simulation with the use of different methods have shown that scenario conditions significantly affect the choice of the algorithm to be used. For example, Scenario 1, with regular vessel arrivals, is most suitable for the algorithm of icebreakers placement by areas of responsibility. In this case cargo vessels will nearly have to operate according to the icebreakers’ schedule in some sections of the route. Scenario 2, with non-regular arrivals schedule and more difficult ice conditions, requires a more intelligent approach to icebreaker fleet planning (Amalgama Platform, OptaPlanner). In the light ice conditions of Scenario 3 even a simple “greedy” algorithm shows good results. On the whole, the analysis of the obtained results proves that the use of intellectual management algorithms for icebreaker fleet operation in the logic of Arctic Table 1 Comparison results of the icebreakers management algorithms Management algorithms
Average voyage time, hour Scenario 1
Scenario 2
Scenario 3
Independent movement of vessels
603.4
792.0
358.5
“Greedy” ad hoc algorithm
427.7
717.8
350.5
Algorithm of icebreakers placement by areas of responsibility
321.9
644.3
306.9
Combinatorial optimization OptaPlanner
324.6
547.6
286.3
Integrated simulation model with an optimizer
309.7
421.1
259.4
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marine transportation systems simulation significantly increases model performance of this transportation system. In fact, the more complex are both the structure of the examining system (the number of cargo vessel voyages and the volume of icebreaker support) and the external conditions of its functioning (the severity of ice conditions in various parts of the route), the higher is the effect. The benefit deriving from the application of specialized methods of operational combinatorial planning in the course of simulation model execution is approximately comparable with the heuristic algorithm based on dynamic assignment of areas of responsibility and icebreakers placement on them. In order to make more profound conclusions about the effectiveness of the compared approaches, it is necessary to bring the considered test simulation model closer to the real practice of the Arctic shipping. This requires taking into account additional factors both in transport system description (adequate reproduction of ice conditions and actual navigation geography) and in stating of optimization criterion (taking into account limitations on cargo vessels’ arrival time to destination ports, requirement for regularity of voyages, cost of icebreaking assistance, etc.) [9, 10].
4 Conclusions Therefore, it is fair to conclude that simulation models, as well as integrated platforms that combine simulation modeling and operations research functionality, appear to be the most adequate tool for comparing several alternative management strategies, as well as for predictive and pre-design analysis of such prospective transportation systems.
References 1. Timofeev OYa, Tarovik OV, Topaj AG, Mironov EU, Frolov SV, Buyanov AS, Gorbachev MA, Bengert AA (2019) The concept of an integrated information system for planning of fleet operation in the Arctic. Arctic Ecol Econ 33:129–143. https://doi.org/10.25283/2223-45942019-1-129-143 (In Russian) 2. Hua X, Yin Z (2021) The optimal icebreaking tariffs and the economic performance of tramp shipping on the Northern Sea route. Transp Res Part A Pol Pract 149:76–97. https://doi.org/ 10.1016/j.tra.2021.04.017 3. Moe A, Brigham L (2017) Organization and management challenges of Russia’s icebreaker fleet. Geogr Rev 107:48–68. https://doi.org/10.1111/j.1931-0846.2016.12209.x 4. Eskandari H, Darayi M, Geiger DC (2010) Using simulation optimization as a decision support tool for supply chain coordination with contracts. In: Proceedings of the 2010 Winter Simulation Conference, p 1306–1317. https://doi.org/10.1109/WSC.2010.5679062 5. Bachelet B, Yon L (2007) Model enhancement: improving theoretical optimization with simulation. Simul Model Pract Theory 15:703–715. https://doi.org/10.1016/j.simpat.2007. 02.003 6. Fu MC (2002) Optimization for simulation: theory vs. practice. INFORMS J Comput 14:192– 215. https://doi.org/10.1287/ijoc.14.3.192.113
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7. https://www.optaplanner.org 8. https://amalgamasimulation.ru 9. Tarovik OV, Topaj AG, Bakharev AA, Kosorotov AV, Krestyantsev AB, Kondratenko AA (2017) Multidisciplinary approach to design and analysis of arctic marine transport systems. In: Proceedings of the 36th International Conference on Ocean, Offshore & Arctic Engineering (OMAE 2017). https://doi.org/10.1115/OMAE2017-61951 10. Wang Y, Liu K, Zhang R, Qian L, Shan Y (2021) Feasibility of the Northeast passage: the role of vessel speed, route planning, and icebreaking assistance determined by sea-ice conditions for the container shipping market during 2020–2030. Transp Res Part E: Logist Transp Rev 149:102235. https://doi.org/10.1016/j.tre.2021.102235
Forecasting Temperature Change in Mine Workings at Change in Air Flow Aleksandr Galkin
and Vladimir Pankov
Abstract The aim of this article is to assess the impact of change in base air flow, the assumed amount of air flow set during design phase of a structure, on the accuracy of air temperature forecasting at specific locations in a network of underground mine workings in the cryolithic zone. A simple analytical relationship to determine the correction coefficient was obtained as a result of data analysis. It allows to assess the degree to which change in base air flow affects air temperature change. A comparison of accuracy and reliability of the proposed approach towards assessing the air temperature changes in mine workings when airflow within them changes was conducted. In particular, it was shown that this approach allows to obtain sufficiently reliable data to assess the air temperature change in a specific location in the mine working network without requiring a demanding analysis of the status of the entire network. The value of error in the data does not exceed 10%, a boundary of error usually permitted in engineering calculations. It was determined that the correction coefficient largely changes depending on the relative increase in air flow, rather than absolute increase. At that, the larger the area of mine working’s section, the lower is the permissible increase in base airflow, regardless of initial air flow volume. The lower the base temperature in the terminal point, the stronger is the impact of increase in base air flow on air temperature. The results of variant calculations are presented in the form of 2D and 3D charts. The use of charts allows to quickly assess the values of the correction coefficient for a wide range of ventilation conditions of the underground mine workings in the cryolithic zone. Keywords Cryolithic zone · Mine working · Air flow · Temperature · Forecasting · Ventilation · Calculation error
A. Galkin (B) Melnikov Permafrost Institute of the Siberian Branch of the Russian Academy of Sciences, Merzlotnaya Street, 36, Yakutsk 677010, Russia e-mail: [email protected] V. Pankov North-Eastern Federal University, Belinsky Street, 58, Yakutsk 677027, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_108
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1 Introduction Thermal regime of the underground structures in the cryolithic zone, both those intended for mining [1–3] and other types of underground mine workings—for example, storages, cooling chambers, protective structures [4–6]—is often the crucial factor in reliability and safety of their exploitation. The two ways thermal regime impacts safety is the dependence of robustness of the surrounding rocks within which the mine workings are built on temperature [7–9] and dependence of comfort and labor safety of the workers within the mines on the microclimate [10–12]. Forecasting the thermal regime—determining the thawing depth—of the rocks and assessment of the regularities of formation of the thermal regime in the main ventilation mine workings and on the workplaces are aspects gathering significant attention during design of underground structures [11, 13, 14]. The precision of the forecast and the reliability of assessment largely depends on the precision of initial data and conditions [14, 15]. In particular, the most important data about the mine workings are the air flow and their geometric characterists: cross-section, circumference, and length. If for a specific mine working the geometric characterists are entered during design stage and do not change during its exploitation, actual air flow is a changing value over the year. Its real volume can change by multiples from the base values set at design stage. This difference is caused by natural draft which can significantly change the entire designed ventilation structure, up to reversion of the air flow direction. The purpose of the present research is to determine the correction coefficient to assess the changes in air temperature at specific locations (points) of the mine workings network when the air flow diverges from the volumes set at design stage.
2 Methods To determine the air temperature in the mine working after the actual air flow diverges from the base air flow k times, a simple formula will be used: t2 = qt 1
(1)
where t2 is the temperature after the change in air flow, °C. t1 is the temperature at the initial (base) value of the air flow, °C. q is the correction coefficient, unitless. The correction coefficient can be found using the formula obtained as a result of data analysis of numerical calculations for forecast of thermal regime at a section of a mine working. q = exp( f (1 − 1/k 0,2 )/Q 0,2 )), f = mlu/1000
(2)
In the formula (2), the following notions are introducted. f is the ventilated surface area, m0.6 /C0.2 . u is the circumference of the mine working at the section, m. l is the
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length of the mine working section, m. m is the coefficient depending on the form and type of supports in the mine working, unitless. k is the degree of change in the air flow, unitless. Q is the base air expenditure, m3 /s. Using the formulas (1) and (2) it is possible to assess the degree of change in air temperature during the winter period at the end of an individual mine working when the air flow changes, without using demanding calculations. It is of interest to assess the error occuring when determining the temperature at the terminal point when the air flow in the mine working changes. A relative error, expressed in percent, can be determined using the formula: ε = 100ab(1 − q), %
(3)
The permitted value of error in engineering practice calculations is usually less than 10%, or 0.1. Conscious of this rule, the formula (3), after plugging in formula (2) into it, yields a relationship to determine the relation between the base air flow and the degree of its change for a specific mine working. k ≥ 1/(1 − 0, 095Q 0,2 / f )5
(4)
3 Discussion of Results First of all, it should be noted that when the air flow changes, the thermal balance of the mine working remains constant. The increase in cold accumulated by the rocks over the cold period of the year will be compensated by the increase in warmth accumulated over the warm period of the year. A small difference will occur because the reflectance will be slightly higher in the winter period than in the summer period [12]. Additionally, a simple analysis of the formula (2) shows that the dependence of the correction coefficient on the air flow has an exponential characteristic, with one step being 0.2. This means that an increase in base air flow (before the schema of mine working’s ventilation is corrected), for example, by 1.5×, will cause the factor to change by 1.08×. As follows from the formula, the correction coefficient itself will be 1.02 (at base air flow of 20 m3 /s with its increase to 30 m3 /s, for example). The maximum value of the degree of change of their flow in the mine workings will not exceed 2.0. This corresponds to a correction coefficient of 1.04. This way, it can be expected that changes at the terminal points (locations in a mine working) will be insignificant even at high variations in base air flow. However, it is only possible to support this claim by a multifaceted quantiative analysis. To verify the assumption, variant calculations were done, whose results are presented in the form of charts in Figs. 1, 2, 3, 4 and 5. Figure 1 shows the variation in correction coefficient depending on the increase k of the base air flow (two values were chosen: 100 m3 /s and 50 m3 /s) for various values of the parameter f, which denotes the area of the mine working.
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Fig. 1 Correction coefficient at base air flow of 50 m3 /s and 100 m3 /s for different sections of the mine working with areas: A—2.0; B—1.0; C—0.5
Fig. 2 Change in correction coefficient depending on the increase in air flow
Fig. 3 Change in temperature (–20 °C) at different degree of increase in base air flow for a section of mine working with ventilated surface area equal to 2.0
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Fig. 4 Change in temperature (10 °C) at different levels of increase in base air flow for a section of mine wortking with ventilated surface area equal to 2.0
Fig. 5 The permitted value of coefficient of base air flow increase for a section of mine working with different ventilated surface area
As can be seen from the charts on Fig. 1, an increase in base air flow by a factor of 2, from 50 m3 /s to 100 m3 /s, leads to an insignificant change in the correction coefficient. The ventilated surface area plays a bigger role, even though in the absolute, the numbers are not too large. For example, a twofold increase in ventilated area, from 1 to 2 (curves A, B) causes an increase in the correction coefficient by 1.05×. An increase in ventilated surface area 2×, from 0.5. to 1.0 (curves B, C) leads to an increase of the correction coefficient by 1.02×. However, if curves A, B and C are compared, the impact of area on the correction coefficient is obvious: the smaller the ventilated surface area, the flatter the curves. That is, the degree in change of the correction coefficient at a constant increase of the base air flow, independent on its volume, increases when the mine working ‘s ventilated surface area increases. If a horizontal line, parallel to X axis, is introduced, at the level of the correction
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coefficient of 1.1, the result is that at base air flow less than 100 m3 /s and change in area less than 2×, an increase in air flow by a factor smaller than 1.65× will not lead to introduction of an error larger than permitted in engineering practice in determination of termperature. Further, we will consider this question in more detail. On Fig. 2, a change in correction coefficient depending on the increase in base air flow for a mine working section with area of 2.0 is shown. The image shows that the correction coefficient largely changes depending on the increase in base air flow than on the base air flow absolute volume itself. A different tilt of the plane relative to axes X (k) and Y (Q) testifies. Additionally, as was already noted, the absolute values of the correction coefficient are not too high and are close or lower than values of error permitted in the engineering practice. For illustration, on Figs. 3 and 4 charts depicting change in temperature in the terminal point of the mine working at different levels of increase in base air flow for a section of mine working with a ventilation surface area of 2.0. On picture 3, the charts are for a base temperature of –20 °C and on picture 4 for a base temperature of –10 °C. The charts support a previously made conclusion: the lower the base temperature in the terminal point, the higher is the influence of degree of increase in base air flow on temperature change. This applies largely to the air flow increase coefficient, not to the absolute value of base air flow. Figure 5 shows a chart characterizing the value of the air flow increase coefficient for a section of mine working with different ventilated air surfaces. As can be discerned from the chart, the higher the ventilated surface area of the mine working, the lower is the permissible base air flow increase, independent of the air flow itself. If the value of the coefficient is higher than the value determined from the chart, the error of final temperature will be higher than permissible in engineering practice (10%). In all other cases it will be lower and it is not required to provide a correction of the temperature regime.
4 Conclusion On the basis of data analysis of numerical calculations, a simple analytical relationship was obtained, allowing to determine the correction coefficient for temperature determination at the terminal point of the mine working when base air flow changes. A comparison of precision and reliability of the proposed approach towards assessment of change in temperature in mine workings in relation to change in air flow was conducted. The proposed approach allows to receive sufficiently reliable data to assess the temperature changes in a specific location in the mine working without having to start a new, demanding calculation for the whole mine working network and a new data analysis. It was demonstrated that the degree of error in the data does not exceed the error value permitted in engineering practice. The research determined that the correction coefficient largely changes depending on the increase in base air flow than on the volume of base air flow itself. At that, the larger the ventilated surface area, the lower is the degree of increase in air flow, regardless of what the initial value
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of air flow was. The results of variant calculations are presented in the form of 2D and 3D charts which allow determining the correction coefficient values for typical ventilation conditions of gold mines in the cryolithic zone. Further research in this area should be directed towards comparison of results obtained with the help of the proposed approach with results obtained using numerical analysis of temperature in the terminal point of the mine working when base air flow increases.
References 1. Galkin AF (2016) Thermal regime of cryolithozone mines. Bull Mining Inst 219:377–381. https://doi.org/10.18454/pmi.2016.3.377 2. Zaitsev AV. Semin MA. Parshakov OS (2021) Features of the thermal regime formation in the downcast shafts in the cold period of the year. Bull Mining Inst 250:562–568. https://doi.org/ 10.31897/PMI.2021.4.9 3. Vernigor VM, Morozov KV, Bobrovnikov VN (2013) About approaches to designing the thermal regime of mines in permafros. Bull Mining Inst 205:139–140. https://doi.org/10.31897/ PMI.2013.6.9 4. Gorelik JB, Soldatov PV (2018) Method of calculation of axial load on the well’s casing during thawing of frozen host sediments. Kriosfera Zemli (Earth Cryosphere)- XXII 2:50–60. https:// doi.org/10.21782/KZ1560-7496-2018-2(50-60) 5. Krasnoshtein AE, Kazakov BP, Shalimov AV (2007) Modeling phenomena of non-stationary heat exchange between mine air and a rock mass. J Mining Sci 5:522–529. https://doi.org/10. 1007/s10913-007-0055-x 6. Galkin AF, Kurta IV, Pankov VY (2020) Comparison of heat flux in mine workings of flat and spherical symmetry. Mining Inf Anal Bull 10:133–141. https://doi.org/10.25018/0236-14932020-10-0-133-141 7. Galkin AF (2015) Thermal conditions of the underground town collector tunnel. Metall Mining Ind 8:70–73 8. Guo fang Xu, Jilin Qi, Wei Wu (2019) Temperature effect on the compressive strength of frozen soils: a review. Recent Adv Geotech Res 227–236. https://doi.org/10.1007/978-3-319-896717_19 9. Teng J, Shan F, He Z, Zhang S, Sheng D (2018) Experimental study of ice accumulation in unsaturated clean sand. Géotechnique 208–225. https://doi.org/10.1680/jgeot.17.P.208 10. Semin MA, Brovka GP, Pugin AV, Bublik SA, Zhelnin MS (2021) Effects of temperature field nonuniformity on strength of frozen wall in mine shafts. Mining Inf Anal Bull 9:79–93. https:// doi.org/10.25018/0236_1493_2021_9_0_79 11. Greth A, Roghanchi P, Kocsis K (2017) A review of cooling system practices and their applicability to deep ad hot underground US mines. 16th North American Mine Ventilation Symposium, Golden, CO, June 17–22, 2017, vol.11, pp. 1–9 12. Danko G (2012) Ventilation and climate control of deep mines. McGraw-Hill Yearbook of Science and Technology, p 296–299 13. Galkin AF, Kurta IV (2020) Effect of temperature on thawing depth frozen rocks. Mining Inf Anal Bull 2:82–91. https://doi.org/10.25018/0236-1493-2020-2-0-82-91. 14. Zeeshan Khalid M, ZubairM MA (2019) An analytical method for the solution of two-phase Stefan problem in cylindrical geometry. Appl Math Comput 342:295–308 15. Gorelik YB, Pazderin DS (2017) Correctness of formulation and solution of thermomechanical problems in forecasting temperature field dynamics in the foundations of constructions on permafrost. Kriosfera Zemli (Earth Cryosphere), V. XXI3:49–59. https://doi.org/10.21782/ KZ1560-7496-2017-3(49-59)
Modeling a Repertoire of Pilots’ Professional Communication Skills for Meeting Flight Safety and Aviation Security Challenges Olena Kovtun , Anzhelika Kokarieva , and Nataliia Khaidari
Abstract Communication in aviation is both a key tool in the efficient use of available resources and a contributing factor in developing a safer and more secure flight environment. When operating a flight, pilots are obsessed and overburden with paying attention to problems of technical (equipment failure) or environmental (adverse weather conditions) character. However, poor radio communication of aircrew with air traffic control personnel or face-to-face communication within cockpit may also severely impede smooth and safe flight operation and lead to accidents or near-accidents. In-depth study of scientific researches on aviation communication, ICAO language proficiency requirements, analysis of linguistic and psycholinguistic features of pilots’ radio voice and ground communication, multidirectional observations of flight work, interviews with pilots, aviation experts, and teachers of aviation schools allowed us to model a range of pilots’ communication skills necessary for ensuring flight safety and contributing to aviation security. Linguistic and functional aspects of oral (speaking and hearing) and written (writing and reading) aircrew speech activity when operating a flight and when preparing for it (communication with ground personnel) were outlined. As a result, the repertoire of pilots’ professional communication skills, necessary and sufficient for flight safety, was compiled. Since circulation and processing of information is of fundamental importance in aviation, we classified pilots’ professional communication skills by the criterion “information processes” and divided them into three groups: skills in receiving, processing and sending/transferring information. Keywords Pilots’ professional communication skills · Radio communication · Flight safety · Aviation security · Repertoire of pilots’ professional communication skills
O. Kovtun · A. Kokarieva (B) · N. Khaidari National Aviation University, Lubomyr Huzar Avenue, 1, Kyiv 03058, Ukraine e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_109
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1 Introduction At the present stage of its development, aviation faces a great amount of challenges. Safety is the number one goal of all airmen and instructors. Air traffic on many routes nowadays resembles the traffic on big freeways, and to ensure safety of its participants it is necessary to observe the rules of professional communication, viewed as a mandatory competence and a component of pilots’ and air traffic controllers (ATCOs’) professional reliability. Sexton and Helmreich posit that communication is critical in aviation not because it can overcome inadequate technical flying proficiency, but rather the contrary, that good “stick & rudder” skills cannot overcome the adverse effects of poor communication. Klampfer et al. stress the importance of interpersonal communication in technological environments and the need for training non-technical (communication) skills to complement the technical education [1]. Thus, pilots’ communication skills make the core of pilots’ professional communication competence and play an important role in the process of flight operation, contributing not only to flight safety, but to aviation security as well [2–7]. Despite the long-standing interest of scientists in professional aviation communication and communicative reliability of pilots [8], the exact range of communication skills necessary for pilots to ensure flight safety has not been compiled yet. Analysis of the recent Aviation Authorities’ requirements to pilots’ English language proficiency shows that the repertoire of skills cannot be limited to those necessary for conducting oral radio communication. In this regard, the objective of the current study was to analyze modern aviation environment, assess changes in communications between ATC personnel and pilots due to equipment advancement, and determine the range of pilots’ professional communication skills necessary for ensuring flight safety and contributing to aviation security.
2 Materials and Methods The following methods were applied in the research: • theoretical methods (analysis of philosophical, psychological, linguistic, etc. literature) to define the nature and features of the notions “skills” and “communication skills”; • abstract-logical method (analysis, synthesis, comparison, classification, etc.) to synthesize theoretical materials and clarify psychophysiological provisions of pilots’ professional activity; • descriptive method to portray communication in Civil Aviation as a specific professional discourse; • review of ICAO and FAA documents on pilots’ English language proficiency and international requirements for training Aviation English and RTF communication; • interviewing of pilots, experts on aviation security and flight safety, and teachers of aviation schools in order to clarify the range of pilots’ communication functions;
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• modeling a repertoire of pilots’ communication skills aimed to develop a safer and more secure flight environment.
3 Results and Discussion 3.1 Communication Skills in Civil Aviation: Psychological and Functional Aspects Skills as Psychological Phenomena. The urgency of the problem of skills is determined by the fact that they underlie any training. Milrud notes that if skills and habits ‘were not foreseen’ in the human psyche, then even the smallest step in human activity would require conscious approach and extra energy resources of the body. Attempts to define the term “skills” proliferate within the literature. In order to illustrate this point it is useful to examine some of the definitions that have been put forward by different researchers. Skills are defined as expertise or accomplishment in any field; specifically, any complex, organized pattern of behaviour acquired through training and practice [9, 10]; the method of action performance that is based on previously acquired knowledge and habits [11]; abilities necessary for producing behaviour that will accomplish the objectives of the task. Analysis of the definitions allows one to conclude that the term “skills” signifies practical expertise, ability to do something. The Nature of Communication Skills. Communication skills take a special place among human skills. A review of literature regarding views on communication skills shows that perceptions vary widely among researchers. According to Passov, within the theory of speech activity skills should be defined as conscious activity based on a system of subconsciously performed actions and aimed at solving communicative issues. In academic and professional spheres, the term “communication skills” reflects the verbal and nonverbal competence, written and social strategies, used to interact, influence and solve problems within the group [12, 13]. There are four main types of communication (speech) skills: 1) skills to speak, i.e. to express thoughts in oral form; 2) skills to write, i.e. to present ideas in written form; 3) skills to listen, i.e. to comprehend speech in its sound expression; 4) skills to read, i.e. to understand speech in its graphic expression. Pilots’ Professional Communication Skills. Within the framework of our research, it is necessary to define the notion pilots’ professional communication skills, which means the ability of pilots to effective oral (hearing and speaking) and written (reading and writing) speech activities related to performing professional communication functions. We believe that professional communication skills, formed on the basis of the native language (in our case – Ukrainian) are the basis for the formation of corresponding communication skills in the target language (in our case – English).
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According to Kovtun [11], the following types of aviation communication should be differentiated: • specific communication between ATCOs and pilots that is realized in the form of radiotelephony (RTF) communication in order to operate a safe flight (flight communication); • communication of aircrew and ATC personnel with other aviation professionals (administrative personnel, aircraft maintenance specialists, ground support crews, airline operations agents, aviation security experts, etc.) in order to ensure organization of the flight and its safety (ground communication); • communication with passengers that is carried out indirectly as aircrew announcements or directly in certain flights if there arise situations that require aircrew intervention to ensure flight safety.
3.2 Prerequisites for Pilots’ Professional Communication Skills Typology Psychophysiological Provisions of Pilots’ Professional Activity. Kovtun at el. [11] concluded that pilots’ professional activity is characterized by a set of specific features, which differentiate it from other jobs from social, philosophical, psychological, physiological points of view. The following positions are worth to be mentioned: 1) a pilot plays a leading, integral role in the system “man – machine – environment”, s/he organizes the whole system and directs it to achieve a clear-cut, predetermined result; 2) flying activity is one of the most complex and dynamic, the crew of modern aircraft operates at the limits of human capabilities; 3) flying activity as a profession is referred to the category of “dangerous professions”; 4) the course of pilot’s mental processes in flight is impacted by specificity of flying activity (unusual for a human being conditions of lifting-off the ground; fast movement in space; high pace of activity; multitasking at certain stages of flight, etc.); 5) cockpit crew of modern aircraft manages not so much a physical object as its information model, therefore circulation and processing of information is fundamental in aviation; 6) speed, correctness and reliability of the whole system “man – machine” depend on the accuracy and timeliness of information processing; incompleteness, ambiguity, uncertainty of information can worsen pilots’ activity, cause stress and action errors; 7) features of pilots’ activity (high tempo of work due to time limits, information overloading, work in stressful conditions) are strengthened by the fact that a human as a link of the complex system “aircraft – pilot – environment” has its limitations, which lead to errors and provoke emergencies; 8) one of the main attributes of pilots’ “professional reliability” is absence of communication failures. Specific Features of Cockpit Communication. Specific problems of communication in the cockpit are associated with a number of interpersonal, operational features of this type of professional discourse.
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Kanki and Smith differentiate operational aviation communication from other communications emphasizing that “1) most aviation communication is confined to small audience; 2) it is usually time-sensitive and expeditious; 3) it is constrained or limited in some way by the physical environment; 4) circumstantial factors (noise, static, vibration, weather, etc.) are combined with barriers (cockpit doors, workstations, distances, etc.) to limit, restrict, and confound the channels used in everyday communication” [13]. Flight communication is always goal-directed, as the crew has to convey information, communicate to issue orders, acknowledge commands or clearances, conduct briefings, handle callouts, etc. The aircrew communicates with ATCOs to share information that is essential for safe flight operation. Cockpit communication in standard conditions is associated with implementation of the decision. Decision-making becomes the main point of the aircrew activity under stress conditions [12]. Thus, we emphasize the role of interpersonal communication skills for safe and efficient aircrew performance.
3.3 Functional Aspects of Pilots’ Professional Communication Aviation authorities (ICAO, FAA, etc.) require an applicant for a language proficiency certificate to be able to read, speak, write, and understand the English language [13]. Flight Communication. It is mainly realized as radiotelephony communication between pilots and ATC bodies in the controlled airspace. RTF is carried out so that ATCOs could 1) inform the aircrew about the situation in the flight area, conditions of the aerodrome, technical performance of communication and radio equipment, about emergencies; 2) control maneuvers of the aircraft, separate them at safe intervals in order to prevent dangerous approaches and collisions with each other and with obstacles at the aerodrome and in flight; 3) request information about the status and location of aircraft. The aircrew uses RTF in order to 1) inform about the flight operation, report on the status of aircraft and the situation in which the flight is going on; 2) receive permissions (advisories, clearances) to perform certain phases of the flight, etc. Thus, communicative goals of RTF communication are informing, requesting, controlling and supporting of aircraft by ground services. Speech interaction during the flight is not limited to “pilot – air traffic controller” radio voice communication. It is also realized as a face-to-face communication between pilots in the cockpit. The following main speech forms are differentiated within cockpit crew communication: 1) commands to perform some actions/maneuvers (“Landing gear up”, “Flaps 20”); 2) reports about commands’ execution, confirmation of information receiving (“Gear down”, “…up to 4 nm, speed 160”); 3) requests for information (“Request heading”); 4) remarks that do not carry any command or executive information: objections, comments, exclamations, etc.
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Ground Communication. This type of pilots’ communication takes place each time at pre- and post-flight stages of the aircrew’s flight work. Main functions of speech communication between pilots and ground personnel are informative and regulatory. In this regard, ground communication is similar to the above-mentioned flight communication, but it differs significantly in genres, forms, and styles of speech. Pilots’ ground communication is realized in the following functional styles: official, scientific, and conversational (the choice depends on the situation, communicative tasks, and relationships (formal/informal) between/among interlocutors). Oral speech is used in both dialogue and monologue varieties in a wide range of genres: reports, messages, briefings, discussions, etc. Communication with Passengers. This type of pilots’ communication is usually implemented indirectly, in the announcements made by cockpit crew onboard the aircraft. Direct interaction of cockpit crew members with passengers occurs occasionally in some non-standard flight situations, only if it is required by safety issues. Aviation psychologists note that inability of cockpit crew and cabin crew to make announcements can cause passenger aggression and become a safety hazard.
3.4 Written Communication Taking into account the fact that flying activities of pilots are associated with information overloading, time shortages, work under stress, and due to limited human capabilities, aviation experts have concluded that relying entirely on memory of a human operating an aircraft, is not sufficient to ensure flight safety. Therefore, special technologies aimed to minimize these risks are introduced into pilot’s work and these technologies require well-developed written skills. Reading Activity of the Flight Crew. Modern aircraft is equipped with onboard electronic library (Electronic Flight Bag), which, for instance, for Airbus aircraft family encompasses more than ten manuals and reference guides. One of the first to be mentioned is Flight Crew Operating Manual (FCOM) the objective of which is to: 1) provide all necessary limitations, procedures and system information the aircrew needs to safely and efficiently operate aircraft during normal, abnormal and emergency situations; 2) serve directly as Flight Crew Operating Manual, or as a basis for Operators to develop their own customized Airline Operation Manual in accordance with applicable requirements; 3) serve as a comprehensive reference guide during initial and refresh aircrew training. The Flight Crew Technique Manual (FCTM) provides additional information that the aircrew may consult with in conjunction with FCOM. The FCTM provides the aircrew with the following information: the general Airbus operational philosophy (e.g., design and utilization principles, golden rules for pilots); additional information to FCOM procedures (the “Why” to do and the “How” to do); best practices, operating techniques on maneuvers, and handling; information on situation awareness.
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Writing in the Cockpit. ATCOs traditionally have used radio voice (oral) communication to give clearances and other flight information to pilots. Aviation experts have concluded that voice communication is time consuming and labour intensive, it slows operations and can lead to miscommunications between ATCOs and pilots. In order to minimize the risks imposed to air safety by radio voice (oral) communication Aviation Authorities require the aircraft to be equipped with advanced technologies, such as Data Communications (Data Comm). Federal Aviation Administration states that this technology gives ATCOs and pilots the ability to transmit flight plans, clearances, instructions, advisories, flight crew requests, reports and other essential messages with the mere touch of a button. The above-mentioned enhances the role of written skills in flight communication which traditionally was viewed as voice (oral) only. The use of written skills by cockpit crew is specified in normative documents: a captain, for instance, has to ensure “timely putting down to the relevant technical documentation the information concerning detected malfunctions of aircraft on the ground and in flight, and deviations in the operation of aircraft or its systems” [12]. Parke, Patankar and Kanki in their study on shift turnover related errors in aviation showed the work cards as a contributing factor in a much higher proportion of incidents involving turnover communication problems [11]. Vieira and Santos suggest that increasing the completeness and correctness in writing will result in a significant reduction in shift turnover communication problems [13].
3.5 The Repertoire of Pilots’ Professional Communication Skills Analysis of modern aviation environment, functions and features of pilots’ professional (flight and ground) communication allows us to determine the range of pilots’ professional communication skills, which are both necessary and sufficient for flight safety. Since circulation and processing of information is of fundamental importance in aviation, since correctness and reliability of the entire aviation system depends on the accuracy, efficiency and timeliness of pilot’s receiving and processing information, it is reasonable to classify professional communication skills of these professionals according to criterion “information processes” and divide them into three groups: skills in receiving, processing and transferring information (see Table 1).
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Table 1 The repertoire of pilots’ professional communication skills Group of skills
Sub-skills
Skills to receive information:
1. Skills to comprehend/perceive professionally oriented information in radio voice (RTF) and face-to-face communications (skills to understand the topic and subtopic of the message; to define the gist of the message; to get numerical information); 2. Skills to read/perceive professionally oriented information (alphabetic, numeric, and graphic) from pap er and electronic data storage
Skills to process information:
3. Skills to process aurally perceived professionally oriented information (skills to differentiate information; to select basic facts; to analyze, compare, contrast, classify, interpret information); 4. Skills to look up/sort out information in the Electronic Flight Bag
Skills to transfer information:
5. Skills to interact: – Skills to navigate in the conditions of communication (skills to define formality/informality of the communicative situation, to project a communicative portrait of the communication partner, etc.);; – Skills to plan speech in accordance with speech intention and conditions of communication (skills to define the purpose and content of the communication act); – Skills to select adequate means for disclosing the content of utterances (skills to produce utterances of the appropriate functional style, skills to initiate/keep up/finish the dialogue, take the initiative, change the topic of conversation; skills to adhere to procedures and techniques of RTF communication, etc.); – Skills to provide feedback (to clarify, ask, verify, confirm, comment information) 6. Skills to write: – Skills to convey professionally oriented alphabetic, numeric, and graphic information in the written form; – Skills to draw up the relevant professional documentation; – Skills to write a coherent text
4 Conclusions Technical and non-technical skills of pilots are interrelated and strongly influence each other. Communication competence being one of pilots’ non-technical skills is viewed is a key component of their professional reliability. The main factor that contributes to flight safety in regard to communicative aspects of pilots’ activity is their strict adherence to procedures and techniques of RTF communication and competent use of standard phraseology of radio exchange. However,
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pilots’ professional speech is not limited to radio voice communication. In nonflight time pilots refer to professional aviation sublanguage, which is realized in a range of language codes (native, English), types of speech activity (reading, speaking, listening, writing), functional styles (official, scientific, conversational), genres (requests, reports, messages, clearances, instructions, advisories), forms of speech (oral (dialogue/monologue), written). Pilots’ professional communication skills are classified according to the criterion “information processes”, they cover both traditional speech skills (speaking, listening, etc.) and skills related to the usage of information and communication technologies. The repertoire of pilots’ professional communication skills encompasses skills to receive, process and transfer information. Our suggestion is that this repertoire of communication skills should be integrated in the curriculum of all schools focused on aviation, become a requirement for pilots’ certification in order to mitigate the errors related to communication.
References 1. Certification: Pilots and Flight and Ground Instructors, AC No: 61-65H (2018). https://www. faa.gov/documentlibrary/media/advisory_circular/ac_61-65h.pdf 2. Gnatyuk S (2016) Critical aviation information systems cybersecurity. In: Shahbazian E, Rogova G (ed) Meeting security challenges through data analytics and decision support, vol 47: NATO Science for Peace and Security Series – D: Information and Communication Security, IOS Press Ebooks, p 308–316. https://doi.org/10.3233/978-1-61499-716-0-308 3. Gnatyuk S (2019) Multilevel unified data model for critical aviation information systems cybersecurity. In: Proceedings of 2019 IEEE 5th International Conference on Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD 2019), p 242–247. https://doi.org/10. 1109/apuavd47061.2019.8943833 4. Danik Y, Hryschuk R, Gnatyuk S (2016) Synergistic effects of information and cybernetic interaction in civil aviation. Aviation 20(3):137–144. https://doi.org/10.3846/16487788.2016. 1237787 5. Odarchenko R, Abakumova A, Polihenko O, Gnatyuk S (2018) Traffic offload improved method for 4G/5G mobile network operator. In: Proceedings of 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET-2018), p 1051–1054. https://doi.org/10.1109/TCSET.2018.8336375 6. Fedushko S, Davidekova M (2019) Analytical service for processing behavioral, psychological and communicative features in the online communication. In: The International Workshop on Digitalization and Servitization within Factory-Free Economy (D&SwFFE 2019), Procedia Computer Science, vol 160, p 509–514. https://doi.org/10.1016/j.procs.2019.11.056 7. Pomytkina L, Pomytkin E, Yahodzinskyi S, Kokarieva A, Nazarenko N (2020) Features of formation of constructive life position of air transport specialists. IOP Conf Ser Mater Sci Eng 918(1):012174. https://doi.org/10.1088/1757-899X/918/1/012174 8. Barshi I, Farris C (2013) Misunderstanding in ATC communication: language, cognition, and experimental methodology. Ashgate VT, Burlington 9. FAA English Language Standard for an FAA Certificate Issued under 14 CFR Parts 61, 63, 65, and 107, AC No: 60-28B (2017). https://www.faa.gov/documentlibrary/media/advisory_ circular/ac_60-28b.pdf 10. Colman AM (2015) A dictionary of psychology, 4th edn. Oxford University Press. https://doi. org/10.1093/acref/9780199657681.001.0001
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11. Kovtun O, Khaidari N, Harmash T, Melnyk N, Gnatyuk S (2019) Communication in civil aviation: Linguistic analysis for educational purposes. In: CEUR Workshop Proceedings, p 2588 12. Vieira AM, Santos IC (2010) Communication skills: a mandatory competence for ground and airplane crew to reduce tension in extreme situations. J Aerosp Technol Manag 2(3):361–370 13. United States Department of Transportation (2021) Data communication. https://www.faa.gov/ news/fact_sheets/news_story.cfm?newsId=21994
Rational Use of Hydrocarbon Resources in the Context of Environmental Sustainability of the Country Oleg Andreev
Abstract The relevance of the proposed article is caused by the lack of a wellformed mechanism for the transition to the rational use of hydrocarbon resources, in which there are growing multifactorial crisis phenomena of both global and intraindustry nature. The increase in negative environmental factors, i.e. the change in the Earth’s climate due to excessive emissions of pollutants into the atmosphere, which are caused by energy companies when burning fossil fuels—coal, oil and gas. This is the main contradiction, which in the near future may negatively affect the sustainable development of the country’s economy. The environmental protection system in force in the country is ineffective: deductions to the state budget of payments and fines for environmental pollution are insufficient to restore the natural environment. In this regard, it is necessary to conduct an effective environmental policy in the industries, to develop economic mechanisms to reduce the negative impact of the complex enterprises on the environment. The dynamically developing economy of Russia is ensured by the sustainable functioning and development of electricity production, which occurs due to the enormous damage to the environment. The novelty of the research is determined by the implementation of the concept of Russia’s transition to sustainable development, which will ensure the gradual introduction into the economy of an ecologically ideal industrial production structure that excludes environmental pollution. Keywords Ecology · Ecologization of the country · Resource conservation · Hydrocarbon resources · Environmental protection system
1 Literature Review The study of the problems of greening the global economy and sustainable development began in the late 60s–early 70s of the XX century with reports to the Club of Rome and was continued in special programs and projects of the United Nations. O. Andreev (B) Samara State Economic University, 141, Soviet Army Street, Samara 443090, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_110
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A significant contribution to the genesis and evolution of theoretical and methodological approaches to the definition of country greening was made by D. Meadows, M. Mesarovich, E. Pestel, J. Tinbergen, M. Todaro, G. H. Bruntland, A. Gore, K. Annan, N. Desai, and many other scientists, public and political figures. The development problems of countries specializing in the extraction and export of mineral raw materials and other natural resources were studied by A. Gelb, T. Gilfason, K. Matsuyama, J. Sachs, E. Warner, M. Alekseev, R. Conrad, R. Solow, D. Hartwick, H. Hotteling, M. Fardmanesh, et al. Nevertheless, such important components of the sustainable development of the national economy as country greening, improving the quality of economic growth, energy efficiency, energy security and others require, in our opinion, a more in-depth study.
2 Methods Today, the world is faced with a systemic dilemma, an unambiguous solution of which, in our opinion, is impossible. It is necessary to find a way to adapt the increasing needs of humanity to the increasing scarcity of natural resources. Assumptions are becoming real that limited reserves of raw materials will not be able to fully ensure the development of modern civilization soon. It should be recognized that an effective substitute for hydrocarbon energy sources has not yet been found, despite many developments on the use of alternative renewable energy. One of the main challenges to global security is that non-renewable energy sources are declining, and energy needs are increasing. Irrational use of traditional sources with increasing consumption leads to severe, often irreversible consequences for the environment. The more efficient the use of energy-saving technologies and alternative fuels in all spheres, the more chances there are to save the planet [1]. The creation of a modern petrochemical industry will allow Russia to receive not only significant profits, but also eliminate long-term production waste, minimize the loss of raw materials, harmful emissions, and thereby improve the environmental situation in the country. The imperfection of the existing environmental protection system continues to aggravate severe environmental problems. There are still shortcomings in the country’s environmental protection system. Most enterprises, including energy-producing ones, control their activities in the field of environmental protection, but such control is an internal activity and is always sufficient to characterize the activities of enterprises as meeting the requirements of sustainable development. To ensure a guaranteed level of environmental protection activity that meets international requirements and the requirements of national legislation, it is necessary to build structured environmental management systems according to certain principles, which should be integrated into the overall management activities ensuring the
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competitiveness of products, financial stability, and the achievement of other goals of economic well-being of enterprises in an open market economy. The existing systems must guarantee the sustainable development of enterprises in terms of environmental impact [2]. For the formation and functioning of the organizational and economic mechanism for ensuring sustainable development, the following is necessary: – greening the economy by expanding the pollution licenses market (city, region, enterprise); – improvement of environmental insurance system; – improvement of environmental management system; – implementation of environmental consulting system; – improvement of innovation management; – implementation of eco-rating system; – improving activities of environmental funds. The new economic mechanism should stimulate the introduction of waste-free and low-waste environmentally friendly technologies, stimulate interest in carrying out nature restoration and environmental protection measures, as well as competently manage the processes of placing newly created industrial facilities in conditions of tightening environmental restrictions. The ecological situation in the country requires real practical actions to improve it. In this connection, it is necessary to form an environmentally oriented policy. The disadvantages of the existing mechanism of nature management and environmental protection can be as follows: 1) assessment of natural resource potential, irrational use of resources is not transparent enough; 2) the approach to determining payment rates does not provide incentives for the activation of environmental activities of enterprises; 3) insufficient use of economic instruments; 4) the existing procedure for the distribution of funds received through payments does not provide funding for environmental protection measures, programs; 5) use of money of environmental protection funds for other purposes. For all states striving for sustainable development, the most important task is to improve the system of measures aimed at the harmonious interaction of nature and all state and non-state actors, individuals, as well as the reproduction and rational use of natural resources, improving the quality of the environment. It is important to consider all possible means to achieve results in the short term [3]. The state should regulate, in the interests of the whole society, the excessive use of natural resources, that is, a certain region or a certain industry can use natural resources only within the limits of the established indicators given by the state. The general trend of the modern economy is to increase the role of finance in the mechanism of state regulation of the national economy in general and on the
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ecological environment. This is due to the need to increase government expenditure for the economy, including in financing of priority sectors of the economy and environmental protection measures. One of the most important areas in financial regulation is tax—the main source of budget funds. From the standpoint of economy transition to a sustainable type of development, its greening and structural adjustment, the tax system should provide for increased taxes on nature-exploiting industries and sectors located at the beginning of the natural product vertical, which will reduce the profitability of their development costs. One of the biggest environmental problems is the pollution of the natural environment by oil and petroleum products. The rates of waste disposal remain low, plans for large-scale waste use are not being implemented. Mining industries are destructive to nature, mining regions are always areas of the most acute manifestation of environmental problems. Irreparable damage is being done to the ecosystems of the region [4]. The threat of global warming caused using fossil fuels comes to the fore. According to the IEA forecast, by 2030 the growth rate of CO2 emissions will equal the growth rate of global energy consumption. The regional aspect is also important in this problem. Over the past 150 years, industrial countries have accounted for approximately 75% of total greenhouse gas emissions. Thus, although only 4% of the world’s inhabitants live in the USA, they account for 25% of carbon dioxide emissions, and energy consumption per capita is immeasurably higher than in developing countries. Industrial countries emit greenhouse gases per capita 5 times more than developing countries, which currently face the most difficult task of intensifying energy consumption and at the same time preserving the environment. At the same time, the least developed regions of the world are particularly vulnerable to the expected consequences of global climate change. In recent decades, the practice of applying taxes related to environmental protection has expanded in European countries. Many of the introduced taxes indirectly contribute to the structural reorganization of the economy. Thus, due to higher taxes, the use of energy carriers and some raw materials becomes more expensive, because of which manufacturers are forced to introduce more economical technologies or reorient investments in industries that are not associated with the use of large volumes of raw materials. In these conditions, an organizational and economic mechanism is needed to ensure the profitability of environmental protection activities for the enterprise. Conditions should be set for enterprises under which the economic results of their activities will directly depend on the degree of their environmental friendliness. Specifying the objective function of the enterprise will allow to concretize this statement of the problem to a level that provides the possibility of its practical application [5]. The goal of the enterprise in this case is formulated as follows:
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– focus on minimizing its total environmental costs (consisting of pollution prevention costs and costs caused by the direct action of the economic mechanism— pollution charges and license fees); – critical maximization of the net profit of the enterprise. The company sets its target, which is to minimize the damage caused to the environment while simultaneously reducing the man-made impact to the regulatory level. The required economic mechanism should ensure the coincidence (in the limit) of technogenic impact levels corresponding to the goal of the enterprise and society. Graphically, it can be expressed in accordance with Fig. 1, where, Epot —economic optimum of environmental quality; SOCpož —socially desirable environmental quality (considering economic opportunities); Smin —necessary minimum of public losses and costs associated with environmental pollution; dS—increase in social losses and costs due to the movement towards socially desirable environmental quality; dNZ—increase in pollution control costs in connection with ensuring a socially desirable quality of the environment; dŠ—reduction of economic damage from pollution in connection with ensuring socially desirable quality of the environment; Sopt —socially optimal level of losses and costs associated with environmental pollution and its protection; Zn —undesirable level of environmental pollution; Šm —maximum possible economic damage from environmental pollution (in these model conditions); Social costs associated with environmental degradation
Fig. 1 Optimum environmental quality
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M—maximum possible level of environmental pollution (in these model conditions). In accordance with Fig. 1, at a certain point in time, in a certain territory with a certain level and structure of use, a reproduction process is carried out that has a certain degree of technical and environmental advantage [6]. In the absence of measures to combat environmental pollution in the conditions of the model, the pollution will reach the maximum possible level (M), which corresponds to a certain final value of economic damage, known or not yet established, Šm . If it is necessary to reduce the level of environmental pollution under the same conditions, then the costs of combating will increase accordingly, moreover, in direct proportion to the level of environmental quality requirements in its various spheres. The ratio of costs and their changes will depend primarily on the degree of scientific and technological development in the relevant field. This leads to the conclusion that, in parallel with the improvement of the environment quality, the damage from its pollution also decreases. Summing up the total damage from environmental pollution and the costs of combating it, we get a total curve in accordance with Fig. 1. Where the curve values are minimal, the so-called “economic optimum” of environmental quality is located. By optimality is meant minimizing public costs and losses associated with environmental pollution and its protection [7]. If the economically optimal quality of the environment does not meet the external economic requirements, condition can be changed for improvements. At the same time, the amount of public costs and losses associated with the environmental problem increases. The conditions of a compromise between foreign economic requirements and economic opportunities will determine the so-called socially desirable quality of the environment (SOCpož ), which corresponds to the socially optimal value of social costs and losses (Sopt ). A dynamic model reflecting trends in the economically optimal quality of the environment depending on changes in the influencing factors is given in accordance with Fig. 2. where: —final value of the minimum necessary social costs and losses associated with Smin environment problem, when using the opportunities of scientific and technological development; Eopt —final value of the economically optimal quality of the environment when using the possibilities of scientific and technological development; Š’—resulting trend of changes in the magnitude of economic damage associated with environmental pollution; Šm —increasing the maximum possible economic damage from environmental pollution; NZ—resulting trend in change in the costs of combating environmental pollution when using the opportunities of scientific and technological development.
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Fig. 2 Changes in economically optimal environmental quality
The presented model, in accordance with Fig. 2, reflects the expected changes that occurred in different periods indicated by the lines (S) and (S ). A marked reduction of the social costs of environmental pollution (curve NZ to curve NZ ) affects the reduction of economic damage from environmental pollution (curve Š to curve Š ), the economic optimum shifted to lower the level of pollution (from Eopt to Eopt ) and decreased public expenditures and losses associated with the protection of the environment (from Smin to S min ). The difference between the pollution levels Eopt – Eopt is the emission quotas that are developing in Russia. When using this economic mechanism, the positive effect of environmental protection activities acts for enterprises in the form of a reduction in payments, especially excess payments paid out of profit [8]. The profitability of a particular environmental protection measure can be clarified only after comparing the amount of reduced payments with the corresponding costs of pollution prevention. In case of market mechanisms, it is necessary to compare the funds for the purchase of emission rights with the costs of pollution prevention. Sufficiently accurate estimates of pollution prevention costs are necessary to compare different options for “environmental policy” both at the level of an individual enterprise and the region. To assess the effectiveness of several sources, it is proposed to use criteria of absolute and comparative efficiency of capital investments in environmental protection measures. Nevertheless, they do not fully reflect the dynamics of the implementation of measures, do not give an idea of the losses prevented in the national economy, do not reflect the magnitude of the effect of environmental protection activities. The program of measures is considered as the sum of events without considering the sequence of investments [9]. It is obvious that the collection of payments for emissions will encourage the company to reduce pollution if the amount of actual emission of harmful substances into the atmosphere is more than optimal. It is advantageous for the company to strive
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for the optimal value. The resulting optimal value is slightly less than the standard for emissions of harmful substances into the atmosphere, therefore, the resulting optimum is the social optimum of environmental quality. A typical situation is when there is a need to build a new production facility at an existing enterprise or a new enterprise in a region with difficult environmental situation. For the project of a new production to successfully pass environmental expertise in the territorial environmental protection department, it is necessary to provide for several environmental measures that ensure at least the preservation of the state of the environment [10]. The bottom line is that a new enterprise (or an enterprise where a new production is being introduced) pays one (or several) operating enterprises the costs of reducing emissions to such values that, considering the emissions of the new enterprise (production), the environmental situation in the region meets the necessary requirements.
3 Conclusion The result of the implementation of the proposed measures in practice should be the creation of an effective organizational and economic mechanism to ensure the greening of the country. One of the reasons for wrong decisions in the country greening is unreliable information about the environment. The algorithm for making decisions that bring changes to the development of production systems should include both economic and environmental protection criteria, consider the consequences of the impact of decisions on the environment quality. The change in the structure of the fuel and energy balance of the Russian Federation towards an increase in the share of renewable energy sources, and the mass introduction of energy-saving technologies, which requires the inclusion of energy conservation requirements in the activation of investment and financial policy, will contribute to achieving the goals of sustainable development of the country through the preservation of the resource base and ecological balance [11]. It is necessary to justify the choice of two functions of Russia’s natural capital: resource-based, providing internal consumption and export of energy resources, and ecosystem-based, supporting the stability of the biosphere of the region, or a combination of them. Unbalanced investment policy leading to an increase in disproportions between the nature-exploiting and manufacturing sectors of the economy exacerbates environmental problems. In the absence of environmental and economic barriers and incentives, the efficiency criterion is the same—obtaining substantial profits at a rapid pace, which is most easily achieved through the exploitation and sale of natural resources [12].
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As a result of the study, new scientific results were obtained that establish the nature of the mutual influence of the processes of sustainable development, hydrocarbon development, and the country’s ecology.
References 1. Bobylev SN, Khodzhaev AS (2013) Economics of environmental management. Publishing House of Moscow State University, Moscow, p 567 2. Shimova O, Sokolovsky N (2015) Economics of environmental management. INFRA-M, Moscow, p 377 3. Valyansky SI, Kalyuzhny DV (2016) The third way of civilization, or will Russia save the world? Algorithm, Moscow, p 496 4. Lyubimtseva S, Chuprik Y (2015) The concept of neo-industrialism and the economic development of Russia. Economist 4:11–21 5. Danilov-Danilyan VI, Losev KS (2017) Ecological challenge and sustainable development. Textbook. Progress-Tradition, Moscow, p 416 6. Kazantsev E, Eliseev A (2015) Energy, economics and ecology. J Ener Service Comp Ecol Syst 7 7. Belyaev LS, Marchenko OV, Filippov SP (2018) World energy as a factor of sustainable development. Energy Econ Technol Ecol 11:2–11 8. Rogoff K (2016) In the next 5–7 years, oil will cost $ 20 per barrel. Beyond Trans 10:3–4 9. Polterovich V, Popov V, Tonis A (2017) Mechanisms of the resource curse and economic policy. Econ Issues 6:4–27 10. Hausmann R, Rigobon R (2013) An alternative interpretation of the “resource curse”: theory and policy implications. NBER Working Paper № 9424. Cambridge: National Bureau of Economic Research, p 59 11. Matsuyama K (2012) Agricultural productivity, comparative advantage and economic growth. J Econ Theory 58:317–334 12. Torvik R (2017) Learning by doing and the Dutch disease. Eur Econ Rev 45:285–306
E-Learning Online Platforms for Educational Approach Anna Kononenko , Mikhail Kravchenko , Larisa Nedospasova , and Ekaterina Fedorovich
Abstract The research describes the e-learning online platforms such as MS Teams, BigBlueButton, Zoom and Rostov State Transport Online University which have the same characteristics of the content and functions for conducting the scientific conferences, designing the project, working in a team and consequently, providing educational process. The purpose of this research paper is to analyze different e-learning platforms, to compare their functions, to underline pros and cons of distant learning and to survey the students‘ online platform preferences. At the development of the distance technologies and appearance of the online platforms, the aim for teaching staff is to organize the educational process using e-learning online platforms as the additional tool for different purposes. Moreover, there are many questions related to methods of measuring online learning effectiveness, as it provides an opportunity for continuous learning and improvement of the professional activities. Convincingly, the education system is changing and developing according to the human needs. The application of the most suitable MS Teams, BigBlueButton, Zoom and Rostov State Transport Online University platforms for implementing the educational process and mastering the necessary competencies is considered in this paper. The benefits and drawbacks of using them in the educational process are described. Keywords E-learning online platforms · MS teams · Bigbluebutton · Zoom · Rostov State Transport Online University · Effective resource · Distant learning
A. Kononenko (B) · M. Kravchenko · L. Nedospasova Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya sq., 344038 Rostov-on-Don, Russia e-mail: [email protected] E. Fedorovich Rostov Law Institute, Ministry of Internal Affairs of Russia, 83 Eremenko, 344015 Rostov-on-Don, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_111
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1 Introduction The main purpose of using e-learning online platforms such as MS Teams, BigBlueButton, Zoom and Rostov State Transport Online University is to show and organize the education process with using the online platforms for both natural and humanitarian sciences which have unique tools for creating the online classes, lectures and seminars. The purpose of this paper is to analyze different e-learning online platforms with their scope of functions and possibilities used for educational approach. The average level of proficiency in teaching by online platforms is minimizing and it is enough for solving social and communicative problems in various areas of the social, cultural and study activities as well as the scientific activity on the Internet. The educational establishments have gained experience in conducting training in a distance format, which revealed the various potential of using educational materials with the use of programs permitted in the country. Now, the distance learning is no longer surprising as a number of the educational institutions, from professional to secondary professional in Russia and abroad, to one degree or another use distance technologies in the pedagogical process. A lot of students are the professional users today and choose this form of education as an opportunity to obtain higher education or to obtain a second education as the advanced training. Modern trends have to be accepted, and many educational establishments understand this and they are developing in this direction. The authors underline the importance to combine the professional and creative abilities together for getting a new vivid educational process through screen as it is just a different way of forming a student’s knowledge and skills, while the education content remains unchanged [1–10]. Some researchers tried to describe the process of such form of education, while the authors try to support using such online platforms as the effective resource to provide and choose various teaching materials [11–15].
2 Materials and Methods The research methodology is based on the method of comparison and generalization, which makes it possible to draw more accurate conclusion. Every educational institution quickly and efficiently resolved the issue of using and developing the distance learning. The universities have different points of view regarding distance learning, especially the capabilities of the students are accepted, and also nobody should forget about the academic performance and the need for professional skills of the tutors to provide really high-quality teaching, and it is necessary to improve the pedagogical culture of the teacher himself [16]. The obtained experience of distance learning based on some online platforms which weren‘t firstly designed for educational purposes and to be acquired many factors such as the convenience, characteristics and audience. The universities chose them, but there were doubts about the form of conducting classes and the interaction between students and teaching staff:
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in the field of listening, reading, speaking and writing. The universities managed to implement e-learning system, which remain the convenient and practical application. MS Teams is the more practical platform for communication with students and getting feedback of them. As the other online platform such as BigBlueButton and Zoom, it consists of different useful tools for providing the same functions and possibilities in Table 1. The unique application is the Rostov State Transport Online University which gives more functions for the main and additional learning and teaching, the necessary teaching materials, tests, books and different online applications are formed in it. The preferences of such online platform are obvious as it is the unique space where everybody can find any information, educational resources and course for improving professional skills in Table 2. It is convenient for every person who signed in this educational website. The teaching staff has opportunity to improve knowledge in various ways and for different purposes and the students can choose the most suitable learning course with online materials like lectures and necessary books and at the end of the learning to complete the test and get the results with detailed description. The students of the Humanitarian Department took part in survey about online platforms: Zoom, BigBlueButton, MS Teams and Online University. It took about a month for teachers and students to get used such online platform and fully adjusted it properly. While studying or working online, minimum requirements for the computer knowledge and skills are used as these online platforms and their content are so practically created that everyone can apply it easily. The learning process is designed using modern requirements for the formation of the communicative competence. As a result of mastering the educational material, the student has mastered the competencies which are developed according to the proficiency. The way the students study online is not special or difficult, the students master knowledge of the sciences in usual way but the class space is the Table 1 Main e-learning functions of the online platforms Online platforms E-learning functions MS teams
Teams provides a fully decked out document storage, chat, and online meeting environment. Teams are Microsoft’s answer to programs like Slack or Google Hangouts. If you’ve ever needed to participate in a team project at work, you’ll fully appreciate the need for such a tool. Each program is designed for work collaboration and has a slightly different set of features, some you may need, and some you may not. Microsoft Teams is your new best friend for group projects
Zoom
It is a video conferencing service used by companies and universities for remote communication. The service is similar to competitors such as Google Hangout and Skype. Its basic functions include the ability to chat and call individual contacts as well as schedule meetings for future events
BigBlueButton
In its session, the users join either as a viewer or moderator. A viewer (a student) can chat, send/receive audio and video, respond and display the emotions. They can also draw on the whiteboard (if given permission by the presenter) and join a breakout room
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Table 2 Main e-learning functions of the Rostov State Transport Online University The purpose of the Online University is a learning management system
Modern system is organized as a center on the Internet, which maintains the educational and working process of distance or blended learning
Registration for different events, courses and Studying materials for teaching staff, tests, studying reports Online library
Published proceedings, books, scientific papers, Journals, articles and so on
Identified information
Keeping their personal documents, information, achievements
Formation and maintenance of the educational process
Timetable, sessions, seminars, tutorials
Conducting education in synchronous and asynchronous
Chats, video seminars
Providing conferences, reports and different competitions
Synchronization and integration with various information systems
Administrative service
Formation of different reports
student‘s room and online platform is the helping conductor to develop the culture of thinking, the ability to generalize analysis, perception of information, goal setting and the choice of ways to achieve it.
3 Results To obtain the necessary skills and competencies using educational materials, the process was organized as follows: instead of the usual room numbers, links to the webinar in the MS Teams, BigBlueButton and Zoom application are added to the timetable for each lesson, the teacher and students of a certain group follow this link and get into the conference with the possibilities of audio–video interaction, where the education process take place. Microsoft Teams has become the most suitable platform for delivering learning materials and developing the required competencies. Both the teacher and the students can talk, see each other and exchange the necessary text, pictures and files in the chat application. Zoom gives the same possibilities, but the main difference is the Internet access, as this online platform has limit of time and it is not convenient for the educational process. Students of the Humanitarian Department of the Rostov State Transport University were asked about preferences in using online platforms, as they have the preliminary experience in this sphere. There were 270 students of the first and second year studying who participated in this survey. The obtained results can be accumulated in the educational process as the foundation for special situations in Table 3. Initially, the teachers are obliged to record the lessons being conducted for the control purpose, but such task lost its mandatory function. Anyone who enters the
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Table 3 Common educational functions for using e-learning online platforms Online platforms
Main educational purposes
MS teams
Document storage • Online meeting and conversation • Screen demonstration and sharing with others • Chat function • Video and audio accompany
Zoom
Document storage • Online meeting and conversation • Screen demonstration and sharing with others • Chat function • Video and audio accompany
BigBlueButton
Document storage • Online meeting and conversation • Screen demonstration and sharing with others • Chat function • Video and audio accompany
Rostov State Transport Online University Document storage • Online discussion • Educational, scientific materials in various forms; • Educational board and timetable with synchronized in time between the participants of the educational process • Synchronization and integration with various information systems
meeting can view it again after completion, which is a clear benefit to the students. In addition, the teaching staff continues to use e-mail to distribute necessary materials and information such as submitting home assignment. In order to control the mastering educational material, the students also send all the completed assignments to the teachers by mail or in the interaction chat, which is created in the electronic information educational environment of the university. As a result of e-learning online platforms, the following tasks have been emerged for mastering the curriculum and the teachers have to: • to form the competencies relevant for communication in real communication conditions; • to definite a set of competencies that ensure successful professional communication; • to focus on the effective component of the course; • to develop the communication skills with generally recognized proficiency; • to correspond the teaching content to the modern educational paradigm.
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Students` survey MS Teams Zoom Online University BigBlueButton
The form of e-learning online platforms MS Teams, BigBlueButton, Zoom and Rostov State Transport Online University presented its advantages and disadvantages for students and teaching staff in Fig. 1. It is shown that the preference in choosing the MS Teams is very high, as students explained that online platform didn‘t have time limit and group work was combined and uncomplicated with applications and tools in it. Moreover, the necessity of highlevel computer knowledge was not used and the variety of functions was impressed. Zoom has the same functions and tools, but for the group work it supported the time limit, and it was not useful and practical for whole group. For tutorials when the tutor can consult students, discuss some aspects according to the educational process, it is indispensable for such work. Online University is used by students in any situation as the essential and additional application for educational process. Students got accustomed to this online platform as common practice. BigBlueButton was not so popular with students as teaching staff didn‘t use it for different educational purposes, it only used for lectures without discussions as it can be done at seminars, tutorials, group work and others.
4 Discussion The advantages include time consuming that is previously spent on moving, the ability to review the recording of the lesson, learning and teaching in a comfortable educational environment. Among some disadvantages, one should identify the lack of live communication, the difficulty of monitoring attendance and student interest, the need for a teacher to develop a suitable strategy for teaching and monitoring, a low level of adaptation the given information by students due to low concentration. The e-learning online platforms are conducted with cameras which are turning on all time during working process for regulating and controlling behavior. Consequently, the elearning online with its advantages and disadvantages has become commonplace for the students and teachers in modern world. The problem for effective interaction in elearning between teaching staff and students should be investigated more thoroughly in the nearest future.
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5 Conclusion The obtained results are intended to improve the e-learning efficiency of the online platform implementation for studying activities related to the communication competence as modern professionals should participate in discussions, consulting, conferences and conversations with foreign experts in their processional field. It is assumed that a graduate of the university must have good computer skills and can communicate and establish important contacts at the sessions and seminars; participate at the international conferences and publish in foreign journals.
References 1. Ngampornchai A, Adams J (2016) Students’ acceptance and readiness for e-learning in Northeastern Thailand. Int J Educ Technol Higher Educ 13(1):1–3. https://doi.org/10.1186/s41239016-0034-x 2. Palvia S, Aeron P, Gupta P, Mahapatra D, Parida R, Rosner R, Sindhi S (2018) Online education: worldwide status, challenges, trends, and implications. J Global Inf Technol Manage 21(4):233– 241. https://doi.org/10.1080/1097198X.2018.1542262 3. Tashchian A, Forrester WR, Kalamas M (2014) The effects of extroversion on conflict resolution in student teams: a cross-cultural comparison. J Int Educ Res 10(1):29–36. https://doi.org/10. 19030/jier.v10i1.8348 4. Ward AK, Ravlin EC, Klaas BS, Ployhart RE, Buchan NR (2016) When do high-context communicators speak up? Exploring contextual communication orientation and employee voice. J Appl Psychol 101(10):1498. https://doi.org/10.1037/apl0000144 5. Taylor-Leech K, Liddicoat AJ (2014) Macro-language planning for multilingual education: focus on programmes and provision. Curr Iss Lang Plan 15(4):353–360. https://doi.org/10. 1080/14664208.2014.927956 6. Benta D, Bologa G, Dzitac I (2014) E-learning platforms in higher education. Case study. Proc Comput Sci 31:1170–1176. https://doi.org/10.1016/j.procs.2014.05.373 7. Alkhalaf S, Drew S, Alhussain T (2012) Assessing the impact of e-learning systems on learners: a survey study in the KSA. Proc Soc Behav Sci 47:98–104. https://doi.org/10.1016/j.sbspro. 2012.06.620 8. Nguyen PT, Nguyen QL (2019) Critical factors affecting construction price index: an integrated fuzzy logic and analytical hierarchy process. J Asian Financ Econ Bus 7(8):197–204. https:// doi.org/10.22159/jcr.06.04.02 9. Rodrigues H, Almeida F, Figueiredo V, Lopes S (2018) Mapping key concepts of e-learning and educational-systematic review through published papers. In: ICERI2018 Proceedings, p 8949–8952. https://doi.org/10.21125/iceri.2018.0649 10. Abrami PC, Bernard RM, Bures EM, Borokhovski E, Tamim RM. Interaction in distance education and online learning: using evidence and theory to improve practice. J Comput Higher Educ 23(2–3):82–103. https://doi.org/10.1007/s12528-011-9043-x 11. Anshari M, Alas Y, Guan LS (2015) Developing online learning resources: Big data, social networks, and cloud computing to support pervasive knowledge. Educ Inf Technol 21(6):1663– 1677.https://doi.org/10.1007/s10639-015-9407-3 12. Diniz GL, Noels KA (2021) Approaches to studying abroad in Brazil and their effects on language learning and intercultural contact. System 97:102443. https://doi.org/10.1016/j.sys tem.2020.102443 13. Chen PS, Lambert AD, Guidry KR (2010) Engaging online learners: the impact of Web-based learning technology on college student engagement. Comput Educ 54(4):1222–1232.. https:// doi.org/10.1016/j.compedu.2009.11.008
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14. Burac MA, Fernandez JM, Cruz MM, Cruz JD (2019) Assessing the impact of e-learning system of higher education institution’s instructors and students. Mater Sci Eng 482(1):012009. https:// doi.org/10.1088/1757-899X/482/1/012009 15. Tanis CJ (2020) The seven principles of online learning: feedback from faculty and alumni on its importance for teaching and learning. Res Learn Technol 28. https://doi.org/10.25304/rlt. v28.2319 16. Bessarabova ON, Shefieva ESh, Churikov MP (2016) Engineering education and training systems for graduates of technical universities for carrying out professional activities in the leading countries of the world. RSTU
Numerical Study of the Intake Chambers of a Cotton Picker Zafar Malikov , Abdurahim Yuldashev , Davronbek Kuldoshev , and Bekhzod Malikov
Abstract The article presents a numerical analysis of the receiving chambers of the picking device of vertical-spindle cotton harvesters. The receiving chamber is one of the important devices in cotton pickers. Because the design of the receiving chamber depends on such indicators as the energy consumption for pneumatic transport, and the contamination of the harvested cotton. In this work, the analysis of the receiving chamber was carried out on the basis of a numerical study of aerodynamics using the ANSYS FLUENT software package. The well-known and reliable k–ω SST turbulence model was chosen to calculate the turbulent air flow. The results showed that the receiving chamber in mass-produced cotton harvesters in the Republic of Uzbekistan is not reliable enough and can lead to the fall of the picked cotton from the receiving chamber to the ground. To eliminate this negative phenomenon, in practice, the speed of the suction fan is often increased, which leads to cottonseed damage. Therefore, the article proposes a new design of the receiving chamber of the cotton harvester. Numerical studies showed that the proposed receiving chamber is more efficient than the existing one. Keywords Cotton picker · Cotton · Pneumatic conveying · Intake chamber · Numerical studies · Suction flow · Discharge flow
1 Introduction In cotton harvesting machines, cotton collected by the picking devices is transported by air flow to the storage hopper. In a pneumatic conveying system, the most important unit is the receiving chamber for the harvested raw cotton. The quality and loss of cotton during picking and the productivity are directly dependent on the design of the receiving chamber. In this regard, the analysis of the receiving chambers of picking devices, from the point of view of aerodynamics, is of great importance. Currently Z. Malikov (B) · A. Yuldashev · D. Kuldoshev · B. Malikov Institute of Mechanics and Seismic Stability of Structures of the Academy of Sciences of the Republic of Uzbekistan, 33, Durmon Yuli Street, 100125 Tashkent, Uzbekistan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_112
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a serial cotton harvester produced at the plants of the Republic of Uzbekistanis equipped with a slotted receiving chamber—a vertical pipe with a slot along the generatrix equal in height to the brush doffers [1]. The doffer is located at the entrance to the slot so that the gap for the passage of raw cotton between the ends of the brush and the wall of the entrance slot S is 5 … 8 mm, and the lower part of the pipe is open for intake of clean air [2]. Consequently, a certain amount of contaminated air from the inter-drum space will pass through the gap between the ends of the doffer brushes and the material, somewhat reducing the quality of the cotton being picked; i.e. an aspiration of the inter-drum space of the device occurs. A vacuum fan powers receiving chambers of cotton harvesters with vertical spindles. Therefore, the receiving chambers must be reliable in operation and have low aerodynamic resistance. The author [1] was the first who determined the aerodynamic resistance of the receiving chambers of cotton harvesters; they described various receiving chambers operating in clean air, without considering the raw cotton effect. At the same time, it is known that the presence of the conveying material in the air flow significantly affects the resistance of the pneumatic transport system. Studies have shown that the highest loss of pressure occurs in the receiving chamber when clean air and mixture move in it. The total pressure loss in the pneumatic transport system is 1188 Pa. Of these, 800.6 Pa falls to the share of the receiving chamber, i.e. 67% of the total pressure loss [3]. As a result, the fan is forced to run over 1450 rpm. This leads to an increase in the cottonseed’s damageability in excess of the permissible norm, i.e. >1.0% due to collision with fan impellers. To eliminate damage to raw cottonseeds, a V-shaped slot injection chamber of a cotton harvester was developed (see Fig. 1; [4]). The norm of cottonseeds damage is up to 1%. However, the power consumption of the fan drive is high. According to the author [4], when testing cotton harvester KhVN-1.2 at a fan impeller speed of n = 1640 rpm, the power consumption of the drive for two fans was 12.7 kW, and at idle it was 9.9 kW. In [5], when testing cotton harvester 14XV-2.4 V, the power consumption of the fan drive was 9.51 kW. In addition, in the receiving chambers, the air is taken from the lower part of the chamber, close to the ground surface. Thus, the suction of debris is not excluded. However, the main disadvantage of such a receiving chamber is that in its lower part, the average flow rate can drop to critical values at which cotton falls from the receiving chamber to the ground. Many designs of receiving chambers, developed in [6–17], did not find practical implementation in industry. There are also a number of studies aimed at modifying the existing pneumatic transport system of the cotton harvesting machine [18, 19]. Therefore, to solve the problems related to a receiving chamber, a numerical 3D modeling of the dynamics of cotton lobules was conducted based on the ANSYS FLUENT software package. This software was developed in the 80 s of the XX century and today is globally recognized as a powerful tool for the study of aerodynamic processes, as well as for the design of efficient equipment structures since it includes all scientific achievements in the field of turbulent hydrodynamics, multiphase flows, heat and mass transfer, etc. It is known that flows at Reynolds numbers higher than 2000 become turbulent.
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Fig. 1 Cotton harvester receiving chamber: the receiving chamber contains pipe 1 for air supply, rotary bottom 2 with deflectors 3, guide 4, housing 5 with a receiving window, in which the lower part of the front wall is made in an arc and exhaust air conduit 7 is connected to housing 5. Guide 4 is installed at an angle alpha to the horizontal plane; the rotary bottom 2 is inclined to the horizontal plane at an angle beta. The alpha angle is greater than the beta angle. As a result of improving the design of the receiving chamber, a new receiving chamber [6] was developed, installed on cotton harvesters KhVN-1,2
2 Materials and Methods In this article, to study the aerodynamic processes in the receiving chamber of a cotton harvester, a numerical method was used to solve the hydrodynamic equations of a two-phase flow based on the ANSYS FLUENT software. An incompressible turbulent flow is considered, using the well-known and tested k–ω SST turbulence model [20]. The authors used this model, because it combines all the advantages of the k-ε and k–ω models, therefore, it is quite reliable and effective in predicting complex turbulent phenomena. When modeling the kinematics of cotton lobules, their influence on air dynamics was ignored because the mass flow of cotton is significantly less than the air flow. To calculate the dynamics of the lobules, the interaction model was used. In addition, the Saffman lift force and the pressure gradient force were taken into account.
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3 Results and Discussion Figure 2 shows a 3D model of the receiving chamber. Figure 3 shows the computational 3D mesh for the receiving chamber; the number of computational cells is 375,000. To perform the calculation, the air flow rate Q1 = 0.47 m3 /s was set at the outlet. The velocity distribution along the height of the flow incoming into the chamber from the side slot was determined empirically (see Fig. 4). The calculation results are presented in Figs. 5 and 6. Figure 5 shows the airflow current lines. As the figure shows, the air velocity in the lower part of the chamber is no more than 6–7 m/s. Consequently, such a design of the receiving chamber can be considered ineffective since there is a high probability that cotton from the lower parts of the chamber will fall to the ground. To confirm the above, a study of the kinematics of cotton lobules was also conducted. Figure 6 shows the velocities of the cotton lobules. The sizes of the cotton lobules varied from 40 to 60 mm. As seen from this figure, the cotton lobules in the lower part of the chamber have low velocities. This circumstance implies that the receiving chambers of mass production have low efficiency. The experimental measurements performed, showed that the velocity of air flow from the slot is practically independent of the air flow rate at the outlet. Figure 7 shows the losses at a different specific gravity of cotton lobules depending on the air flow rate at the outlet.
Fig. 2 D model of the receiving chamber
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Fig. 3 Calculated 3D mesh of the receiving chamber 18 16 14
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Analysis of Fig. 7 shows that the air flow rate for one receiving chamber should be more than 0.5 m3 /s. For example, at a productivity of 0.47 m3 /s, the fall of raw cotton from the receiving chamber to the ground is: at a specific gravity of a cotton lobules at γ = 15 kg/m3 —0.56%, γ = 25 kg/m3 —1.72%, γ = 35 kg/m3 —3.04% and at γ = 45 kg/m3 —4.61%.
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Fig. 5 Flow rates in the receiving chamber
Fig. 6 Velocity distribution of cotton lobules
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The analysis of the above graphs shows that the serial receiving chamber does not allow picking raw cotton without losses on the ground. To pick the cotton without loss, it is necessary to increase the air flow production, which is associated with an increase in the fan impeller revolution over 1450 rpm. However, at that, as mentioned above, damage to cottonseeds increases, as well as energy consumption for the pneumatic transport system of the cotton harvester. In order to eliminate the aforementioned drawbacks of the receiving chamber of a cotton harvester, a new chamber design was proposed. The design and dimensions of the modified receiving chamber are shown in Figs. 8 and 9.
Fig. 8 Modified receiving chamber of a cotton harvester
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Fig. 9 Calculated 3D mesh
From this figure shown that in the modified receiving chamber, air intake is realized from above, which eliminates the fall of cotton globules on the ground. To minimize hydrodynamic losses, the optimal dimensions of the fairing were found by numerical experiment using the ANSYS FLUENT software. Figure 11 shows a computational 3D mesh. The number of computational cells was 850,000, and in this case, as in the previous problem, the k–ω SST turbulence model was used to calculate the air dynamics. Figure 10 shows the results of a numerical calculation for the air velocity. As seen from this figure, in the expanding part of the chamber the flow occurs without flow separation. Therefore, it can be expected that the chamber has minimal resistance to airflow. Figure 11 shows the velocities of cotton lobule sat a specific gravity of 15 kg/m3 . As seen from this figure; the lobules located on the lower surface of the chamber have velocities of more than 10 m/s. A similar picture is obtained at a specific gravity of 45 kg/m3 . At such velocities, the lobules do not accumulate on surfaces and are completely carried away by the air flow. Therefore, the modified receiving chamber can be considered an efficient device.
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Fig. 10 Air flow rates in the modified chamber
Fig. 11 Velocity of the cotton lobules
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4 Conclusion Numerical studies conducted on the basis of the ANSYS FLUENT software showed that the use of a serial receiving chamber does not allow the effective use of the pneumatic transport system of the cotton harvester because there is a noticeable loss of raw cotton due to falling on the ground. Therefore, the article proposes a new design of the receiving chamber for which the described problems are absent.
References 1. Matchanov RD (2011) Cotton pickers 1929–2010. Tashkent 2. Jing-shan T, Xu-Yi Z, Wang-Feng Z, Jian-Feng L, Yan-Long Y, et al (2018) Fiber damage of machine-harvested cotton before ginning and after lint cleaning. J Integr Agri 17(5):1120–1127 3. Rizaev AA (2017) Research and creation of working bodies of a cotton picker with high efficiency. Fan, Tashkent 4. Abdazimov AD, Radjabov SS, Omonov NN (2019) Automation of agro technical assessment of cotton harvesting machines. J Phys: Conf Ser 1260(3):032001. https://doi.org/10.1088/17426596/1260/3/032001 5. Act No.3-2019 (MV-Atex-2018-92+ BV-Atech-2018-13) laboratory and field tests of the MX2,4 cotton harvesting machine in the Gulbakhor season (2019) 6. Turanov K, Abdazimov A, Shaumarova M, Siddikov S (2021) Type analysis of a multiloop coulisse mechanism of a cotton harvester. Adv Intell Syst Comput 1258:290–305. https://doi. org/10.1007/978-3-030-57450-5_27 7. Ntogkoulis PA, Bochtis DD, Fountas S, Berruto R, Gemtos ThA (2014) Performance of cotton residue collection machinery. Biosys Eng 119:25–34 8. Abdazimov A, Uljaev E, Omonov N, Radjabov S (2014) Application of computer vision algorithms for evaluating the performance of cotton pickers. Adv Sci J 12:49–51 9. Matchanov RD, Rizaev AA, Yuldashev AT, Kuldoshev DA, Akhmedov ShA (2020) Pneumatic transport system of a cotton picker. Int J Innov Technol Explor Eng 9(4):2267–2270 10. Ampatzidis YG, Vougioukas SG, Whiting MD, Zhang Q (2014) Applying the machine repair model to improve efficiency of harvesting fruit. Biosys Eng 120:25–33 11. Mukhammadiev DM, Akhmedov KA, Abzoirov OK, Mallaev OS, Esanova NB (2021) Study of the machine unit of the saw gin seed-retracting device. J Phys: Conf Ser 1889:042019. https:// doi.org/10.1088/1742-6596/1889/4/042019 12. Drai AA, Balabanov VI (2015) The technology of mechanized cotton harvesting using the MX-1,8 cotton harvesting machine. Bull 6:7–11 13. Teng L, Fuping H, Zengde H, Xianfa F, Keli H, Xiaodong L (2018) Theoretical analysis and experiment of picking cotton with horizontal spindle. Trans Chin Soc Agri Mach 49(s1):233– 238.https://doi.org/10.6041/j.issn.1000-1298.2018.S0.031 14. Tian J, Zhang X, Zhang W, Dong H, Zhao Z (2017) Leaf adhesiveness affects damage to fiber strength during seed cotton cleaning of machine-harvested cotton. Industrial Crops and Products 107, 211–216 15. Matchanov RD (2013) Cotton harvesters from 1929 to 2010. Fan va tekhnologiyalari bosmakhonasi, Tashkent 16. Matchanov RD, Rizaev AA, Yuldashev AT, Kuldoshev DA et al (2021) The program for calculating the pneumatic transport system of the cotton harvesting machine. Patent No. 10230 17. Matchanov R, Rizaev A, Yuldashev A, Kuldoshev D, Mirzaeva M (2021) Methods for calculating the pressure loss of the air flow and energy consumed by the fan of the cotton harvester. E3S Web Conf 264:04011. https://doi.org/10.1051/e3sconf/202126404011
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18. Rizaev AA, Malikov ZM, Yuldashev AT Borotov AN (2021) Bench-scale study of centrifugal fan parameters. Mater Sci Eng 1030:012175. https://doi.org/10.1088/1757-899X/1030/1/ 012175 19. Rizaev AA, Matchanov RD, Yuldashev AT, Djuraeva NB (2021) Cotton harvesters for onetime cotton-picking. Mater Sci Eng 1030:012173. https://doi.org/10.1088/1757-899X/1030/1/ 012173 20. Malikov ZM, Yuldashev AT, Kuldoshev DA, Malikov BZ (2021) The influence of the mass concentration of cotton on the efficiency of the pneumatic transport system of a cotton harvesting machine. Prob Mech J 1:73–80
Particular Features of Call Tracking Technologies Application in Certain Industries Elena Torosyan , Tatyana Feiling , Aleksandr Khan , and Alisa Torosyan
Abstract Evaluating the effectiveness of marketing communications is a recognized problem in marketing activities in general. Having proven technologies and modern tools, however, many companies ignore marketing analytics, including the reason of complexity and labor intensity of the process. However, the evaluation of the effectiveness of communication activities directly affects the competitiveness of the company. The article discusses the modern technology of call tracking, which allows to link the number of incoming calls with the effectiveness of the advertising channel, show a reliable picture of the consumer’s actions, and evaluate the quality of the company’s call center. This technology has limitations in its application, mainly in companies where sales or appointments are made by phone, as well as enterprises with complex or expensive products and services that require a long purchase cycle. The authors analyzed the main business sectors, the indicators of which need to be tracked through call tracking technology. What is more, key metrics were identified that should be guided by when choosing a call tracking service to ensure the effectiveness of advertising campaigns. Keywords Call tracking · Transportation safety systems · Analytics · Advertising · Marketing · Metrics · Internet technology · Efficiency
1 Introduction In the era of the digital economy, the natural processes in most companies are the handling of large amounts of data, including customer bases, which greatly facilitates the company’s marketing activities. First of all, it concerns marketing E. Torosyan (B) · A. Khan · A. Torosyan ITMO (Information Technology, Mechanics and Optics) University, 49 bldg. A, Kronverksky Pr, 197101 St. Petersburg, Russia e-mail: [email protected] T. Feiling Russian State Hydrometeorological University, 98 Malookhtinsky Prospect, 195196 St. Petersburg, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_113
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communications, assessment and analysis of the potential that the campaign has when interacting with target audiences and stakeholders. Companies invest heavily in business communications, both in operations and in solving strategic problems. It should be noted that the effectiveness of the advertising campaign is reflected in the effectiveness of the marketing mix as a whole. It should be noted that in the era of digital technologies and extensive communication programs, one of the ways the company interacts with customers is direct communication via telephone—incoming calls. Given this fact, a full-fledged analytics system in a company should be built taking into account incoming telephone calls from customers.
2 Materials and Methods Before the advent of automatic call tracking services, marketers have used various methods of analysis, some of which are still used today. Let’s consider the most famous of them.
2.1 Customer Survey The essence of this method allows you to track the source of advertising. The consumer, when calling the company, gets to the contact center, from which distribution is made to the office and divisions. It is needed to mention that call center acts as an interface between the customers and the company [1]. Then, in order to clarify the necessary information, he is asked additional questions, such as: “How did you hear about us?”, “Where did you see our advertisement?” to find out which advertising media led him to action. The answer is tied by the operator to the designated source. This method is simple, but has significant drawbacks: firstly, consumers often cannot answer the question or give too broad answer (for example, on the Internet), and secondly, questions of this type cause them to have a negative attitude towards the company.
2.2 Method of Promotional Codes This method is more advanced, it is aimed at improving the accuracy of data of incoming calls. First of all, this method is used by online stores. They see which platforms generate the most calls and lead them to deals. Marketers use the names of advertising channels in the form of a promotional code (for example, Google, Facebook, etc.). Promo codes provide a certain incentive for customers that encouraged
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them to make purchases. If a valid code is entered, charges are amended to reduced price [2]. This method has its drawbacks. Incorrect promotional code entered by the client or a mistake of the company’s operator will distort the overall statistics of phone calls. Also, the use of this method affects the increase in the advertising budget.
2.3 Hidden Number The essence of this method is that a script is installed on the site that hides the last few digits of the number. The site visitor must click on the number for it to appear in full format. After that, the installed web analytics system receives information about the contact, which is combined with the advertising source. The advantages of this method are that it is cost-effective and minimizes user errors. At the same time, the calls themselves are not recorded, and this method is difficult to associate with the company’s information systems. Extra actions and transitions can negatively affect the reaction of users. This method of call analytics is relevant and is used in micro-enterprises. Using these methods, marketers often encountered incorrect information about advertising sources, which created a problem in assessing the effectiveness of advertising channels and, as a result, the return on investment in marketing. To solve these problems, new approaches and technologies were required. So, in 2014, Google released a call tracking tool from the Google Adwords advertising channel. Google Adwords is an online advertising from Google which uses a bidding system so that the advertisement made by the owner of e-commerce appears in the Google webpage search [3, 4]. This solution quickly became popular as it allowed multiple numbers to be used at the same time and was provided free of charge. However, this tool turned out to have many shortcomings, one of the most significant was that this tool could only be used to analyze Google’s own product. This was the impetus for finding a solution to the problem of collecting distorted information on calls. This is how the term “call tracking” appeared. According to A. Ismailova et al. (2018) «call-tracking—is a method of tracking offline conversions (calls) from the site» [5]. This is achieved by combining the call and the advertising source that should be tracked. Today, there are three types of call tracking: static, dynamic and combined. Let’s consider them in more details.
2.4 Static or Classic Call Tracking It uses standard call tracking software that associates an ad campaign with a single business phone number [6]. This allows businesses to automatically track phone
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Fig. 1 Classic call tracking schema
metrics such as number of calls, call source, and call duration. Classic call tracking allows companies to determine which offline interactions bring the most value. If earlier for each advertising source it was necessary to come up with separate promotional codes, increasing the promotional budget, now it is necessary to allocate several static numbers. For example, a company ran ads on two radio stations and one TV channel. To track the effectiveness of an advertising channel, this company buys three static numbers, and the call tracking service will show which of the three channels worked better than the others and provided the largest sales volume (Fig. 1). This type of call tracking is suitable for tracking offline advertising (radio, television, print media, etc.) or for direct calls (bulletin boards, forums) when more detailed statistics are not required.
2.5 Dynamic Call Tracking This is a technology that allows you to determine a large amount of data on a specific user during his visit to a website linked to a call tracking service. By adding a dynamic spoofing technology script to a company’s website, each user session is assigned a specific virtual phone number from the pool of call tracking phone numbers [6]. After making a call, the system indicates the source of each call (Fig. 2). For example, a visitor who clicked from an ad to Google will see a different phone number than a visitor who accessed the site via Facebook. This type of call spoofing provides much better tracking dynamics for incoming phone calls and allows you to see and get more information about the customer journey—right down to the key phrase.
2.6 Combined Call Tracking Static and dynamic call tracking complement each other, covering the weaknesses of each method.
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Fig. 2 Dynamic call tracking schema
Real Estate Investor Real Estate Software & Technology Education Financial Services Automotive Other Healthcare Home Services Travel Legal Advertising & Marketing
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Fig. 3 The ratio of targeted calls to the total number of calls by industry
The use of call tracking technology is most relevant for companies with complex, long-term or expensive products and services, as well as for online commerce. Let’s consider the work of a call tracking service on the example of CallRail. The developer of the call tracking service CallRail analyzed 129,393,520 calls made in 10 months of 2020 [7]. These calls came from CallRail’s customer base of 150,000 small businesses and agencies. Figure 3 shows the distribution of targeted calls from the total number.
3 Results and Discussions Based on the results of the study, we can identify 10 key industries for which call tracking technology is most relevant:
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3.1 Marketing Agencies Using call tracking for attribution and optimization of their own marketing, agencies can significantly improve their services for client companies. Thus, in case of incorrect tracking of the communication channels of their clients, agencies may lose their trust, as companies may make incorrect strategic decisions based on inaccurate data. Taking this fact into account, agencies optimize the work with call tracking services, based on the task of a particular client. No matter how big or small an agency is, call tracking helps provide agency clients with useful information and at the same time reduce their acquisition costs.
3.2 Tourism and Hotel Business Tour operators, car rental services, resorts offer their customers booking by phone. In line with this, call tracking is relevant for improving website conversions and budgeting for advertising channels. In addition, call tracking allows businesses to improve customer interactions by offering a personalized experience. According to the international research company Ipsos (2017), 78% of business customers are more loyal to travel companies that personalize their online and offline experience [8].
3.3 Education Currently, for educational institutions, measuring the profitability of spending on advertising educational services is also becoming problematic. The relevance of using call tracking technologies becomes obvious. With the help of call tracking, educational organizations can track the profitability of communication channels with potential consumers, adapt their strategy for interacting with public groups and stakeholders.
3.4 Private Medicine Consumers of medical services, primarily paid ones, need initial consultations regarding medical specialists and services provided by the clinic. In the digital age, people want to hear the voice of a real person. Patients have a variety of questions, from recording or rescheduling a visit to a particular clinic specialist, treatment options available to them, including telemedicine, to employment opportunities with certain diseases. In a rapidly changing reality, many people choose to call and speak
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to an administrator because they don’t have the confidence that Google’s websites and listings are accurate and up-to-date. One of the main technologies for attracting potential customers and keeping them as consumers is digital marketing. For these purposes, you need to connect a call tracking service with an analytics and CRM systems.
3.5 Legal Services The initial appeal to the law firm is still carried out by a phone call. It is quite difficult for a person to describe his problem in writing without talking to a specialist. One of the most popular advertising slogans for law firms says: “The first call is absolutely free.“ When running ads with similar calls, companies should perform call analytics. Just like in the case of medical clinics, for small law firms, one call tracking service is often enough to fully analyze the quality of channels and weak points in communication.
3.6 Financial Products Purchasing financial products is one of the most difficult decisions for a consumer. According to these products (mortgage, loans, insurance, deposits, etc.), there is a lot of advertising information on the market, with which the potential consumer had previously had contact. In this regard, when deciding to make a purchase, the consumer has a number of questions that need to be discussed with a financial company specialist by phone in order to get answers and clarify the nuances. Also, a feature of this industry is the need for constant feedback from the consumer of a financial product, accompanied by the execution of a large number of documents. Therefore, to track the client’s history not only in the external environment, but also to record his actions within the company, it is relevant to use a call tracking service with a CRM function.
3.7 Automotive Industry Most of buyers of auto parts and car services, using mobile search, tend to call the company based on the results of search engines, respectively, in this case, it is also necessary to connect call tracking. The initial contact with car dealers can be carried out through various formats, for example, using an online form, so here the role of call tracking fades into the background, but it is also important, since a potential buyer can call and clarify
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questions with the dealer already when they call again from another advertising channel.
3.8 Real Estate It is the industry with the longest customer lifecycle. In this industry, visitors use various types of channels and interaction tools, and over the entire period of the transaction, they can be in the tens. In this area, large budget funds are spent on marketing activities. In this regard, the call tracking service is one of the first tools in a company that operates in the field of development. Due to the specifics of this area, the choice of call tracking should be taken extremely responsibly, since in case of an error, it will be difficult to rebuild business processes in the company.
3.9 Household Services This category includes various types of work: repair of equipment, plumbing, photo services, hairdressing, dry cleaning, etc. The main way to attract customers in this industry are billboards and social networks on the Internet. If this is a private master, then he can publish his personal phone number, and if it is a small organization consisting of several people, then it is more relevant to post the organization’s phone number. In this case, static call tracking is ideal, it is enough to allocate several numbers for different advertising channels, and the company will know the number and cost of calls from each channel.
3.10 Business-to-Business This industry includes companies that are intermediaries between a seller or a buyer (for example, a marketplace or an online storefront). A company that sells potential buyers must provide its customers with detailed statistics on the number and quality of requests. In this case, the call tracking functionality is the most preferable.
4 Results and Discussion You can evaluate the effectiveness of marketing activities using dedicated metrics that are tracked in the call tracking service. Consider below the main metrics.
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1. Unique call—the first call of the client to the company. Uniqueness is fixed by the phone number of the client from which the appeal follows. Uniqueness is determined for the entire period from the moment the product was launched. The call tracking service shows the number of unique calls, as well as their share (formula 1). share of unique calls =
unique calls all calls
(1)
You can also analyze the behavior of new subscribers on the site: what pages they viewed before contacting directly. Afterwards, you can optimize these pages to increase conversions. 2. Percentage of blocked calls. Call tracking services analyze how many missed or blocked calls there were, and the reasons can be both technical and behavioral. The share of such calls (formula 2) is very important to track, since the average callback time is an important factor in building customer loyalty. Modern services provide information about missed calls and even automatically call back the client after a certain time. share of missed calls =
missed (blocked) calls all calls
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3. Targeted calls—have a number of characteristics that vary depending on the call tracking service. Targeted calls imply that the customer is interested in the product or service of the company. In areas with a long purchase cycle, only unique calls are classified as targeted calls, since one client can call several times from different advertising channels (for example, real estate). Marketers recommend to pay attention to the share of unique targeted calls in the total number of unique calls (formula 3). Depending on the advertising channel, this metric will be very different. Share of targeted calls =
unique targeted calls unique calls
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4. Call source. The metric shows how many calls each channel brings. Data is detailed from general to specific. That is, the traffic channel is shown first, then the source of clicks to the site, then the campaign, ad, and keyword (query). This information will help allocate the budget for promotion: it is better to invest in what works to attract customers. 5. Average Call Duration (ACD) shows how long a phone conversation lasts between a customer and a company employee. This is a particularly important metrics for measuring sales and support teams as it provides insight into how efficient employees are during calls. Marketers from different fields have identified a pattern: the longer the phone conversation lasts, the higher the likelihood of transferring the interlocutor to the status of a client. Long phone conversations are usually the result of all customer acquisition activities: SEO, contextual
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advertising, social media management, as well as the ability to conduct a dialogue of a manager or a call center employee.
5 Conclusion All in all, having considered the features of using call tracking technology, we can conclude that, unlike other marketing tools, call tracking services do not impose certain behavior patterns. This is due to the fact that the specifics of different industries can be radically different and it is very problematic to develop universal algorithms. Therefore, each company chooses exactly those metrics that it needs. In some areas, it is advisable to calculate the cost of each call, somewhere—only the target call, in some cases, they consider the financial losses associated with missed calls. Call tracking service allows you to: evaluate the effectiveness of each advertising channel, optimize marketing activities, control the quality of incoming calls, identify drawbacks in the work of company employees and their further optimization. As a result, the use of a call tracking service is an essential activity in companies that actively conduct advertising activities, since one of the main communication channels for them is a phone call.
References 1. Kurniali K, Sartika T (2015) Customer service information system for a call center. Proc Comput Sci 59:298–304. https://doi.org/10.1016/j.procs.2015.07.569 2. Oliver RL, Shor M (2003) Digital redemption of coupons: satisfying and dissatisfying effects of promotion codes. J Prod Brand Manage 12:121–134. https://doi.org/10.1108/106104203104 69805 3. Case: tracking calls from a website without call tracking. http://bzm.me/casebox/2597-keys-ots lezhivanie-zvonkov-s-sayta-bez-podmeny-nomera.html. Accessed 6 Sept 2021 4. Za Z, Saida TI (2017) An analysis on the use of Google AdWords to increase e-commerce sales. Int J Soc Sci Manage 4:60. https://doi.org/10.3126/ijssm.v4i1.16433 5. Ismailova A et al (2018) The use “Call-Tracking” technology in the modern world. Bull Nat Acad Sci Repub Kazakhstan 3:15–22. https://libeldoc.bsuir.by/bitstream/123456789/34312/1/ Ismailova_The.PDF 6. Konks VY, Krasnov EV, Sumarokova EV (2019) Digital marketing and sales technologies: big data and the synergy effect. Univ Bull 8:46–54. https://doi.org/10.26425/1816-4277-2019-846-54 7. CallRail (2020) What can 129 million calls tell us about inbound marketing? A lot, it turns out. https://martechtoday.com/what-can-129-million-calls-tell-us-about-inbound-marketing-alot-it-turns-out-245782 8. Ipsos US (2017) Affluent traveler segmentation
Improved Method and Algorithm of Railway Crossing Automatic Signaling System Sohibjamol Valiyev , Qamara Kosimova , Sunnatillo Boltayev , and Bekhruz Ergashov
Abstract Currently, the most important issues at JSC “Uzbekistan Railways” are: full electrification of railway sections, reliable provision of train safety. To do this, large-scale work is being carried out on the gradual modernization of automation and telemechanics systems to electrify railway sections and ensure the safety of train traffic. The solution of these problems will serve to increase the speed of rail transport and increase the number of passenger and freight operations. This, in turn, has a direct impact on the operation of the automatic railway crossing signaling of the railway crossing, i.e. leads to an increase in the length of the approach section to the intersection, which signals the approach of trains to the railway crossing. The scientific article proposes a new method using modern technologies aimed at ensuring safety at railway crossings and reducing the waiting time for road transport participants at the intersection and avoiding congestion. Two sensors were used to send the train approaching message, one to check and back each other, and one to open the intersection, and radio modules were used instead of cables to transmit messages. According to this method, at the same time, the algorithm of the principle of operation of the guarded railway crossing in JSC “Uzbekistan Railways” integrated version with the automatic railway crossing alarm system is presented. Keywords Crossing automatic signaling · System · Sensor · Alarm · Roadblock · Barrier device · Stoplight · Wireless communication
1 Introduction Today, due to the obsolescence of most of the railway automation and telemechanics systems that ensure the safety of trains in railway transport, these systems cannot meet the requirements of the present time. This is because the internal production capacity of these systems does not allow it, or to do so will require major changes to S. Valiyev · Q. Kosimova · S. Boltayev (B) · B. Ergashov Tashkent State Transport University, house 1, Odilkhodzhaev Street, Tashkent, Mirabad District of Tashkent City 100167, Uzbekistan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_114
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the existing system. These changes are not economically justified in the first place, and they cannot be a long-term solution [1–11]. However, at a time when the economy of the Republic of Uzbekistan is developing rapidly, JSC “Uzbekistan Railways” is trying not to lag behind in this development process and not to lose its place in the economy of Uzbekistan [1, 2]. In order to do this, they have set themselves a number of important issues, taking into account modern requirements. The most important of these: – Full electrification of all railway sections within JSC “Uzbekistan Railways”; – Construction and electrification of new railway sections; – Upgrading of automation and telemechanics systems to ensure the safety of train traffic; – Establishment of its own logistics center. The solution of these issues will serve to strengthen the position of JSC “Uzbekistan Railways” in the economy of Uzbekistan. In other words, by reducing the consumption of fuel by electrifying all railway sections of JSC “Uzbekistan Railways”, reducing the cost of transportation of goods by rail, attracting new customers by building new ones, creating convenience for its customers and users of this service by opening its own logistics center and by upgrading automation and telemechanics systems, will be able to increase the safety of trains and fully control the movement of workers involved in the organization of train traffic. All this together serves to increase the speed of passenger and freight traffic, to ensure the safety of trains and the timely safe and quality delivery of passengers and cargo to their destinations [1, 2]. In the modernization of automation and telemechanics systems, which serve to organize and manage the movement of trains on railway sections and ensure their safety, it is important to take into account the current trends in the development of machinery and technology. Updates on railway transport, in turn, will lead to an increase in the speed of trains on the railway. This, in turn, leads to a change in the category of the railway crossing and, as a result, the lengthening of the section approaching the railway crossing and the increase in the waiting time of road transport participants at the intersection. Among railway facilities, the railway crossing is the most high-risk facility. This is because railways and highways intersect at the same level. Because of the large number of human factors here, traffic safety at railway crossings remains a pressing issue even today [12–17]. In addition to ensuring traffic safety at the railway crossing, the reduction of waiting times for road transport participants in front of the railway crossing and the prevention of congestion is also the contribution of railway automation and telemechanics systems.
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2 An Improved Method of Transmitting Data to a Railway Crossing Signaling System As a solution to the above-mentioned problems, a new way of operating the automatic railway crossing automatic signaling (CAS) system using modern technologies to reduce the waiting time of road transport participants at the haul and prevent possible congestion and ensure train safety (Fig. 1) and its processing algorithm (Fig. 2) are proposed. In the proposed method for the operation of the CAS system, modern axle count sensors were used instead of rail chains, and radio modules were used instead of cables to send a message about the approach of the train to the intersection to the CAS system. Today, the internal power of the elements of radio control systems allows us to transmit data over long distances reliably and securely via wireless communication. Using these modern technologies, we will be able to avoid laborintensive and expensive cables and improve the quality of service in the process of upgrading or improving the automation and telemechanics systems of railway transport. Depending on the category of railway crossing, it can be equipped with sound and traffic light signaling, auto-barrier, barrier device (UZP), barrier traffic light, road signs and video surveillance systems. Currently, rail chains are used to transmit the approach of trains to the approach section of the railway crossing. Rail chains are made up of many elements, and these elements are sensitive to external influences. Every simple failure that occurs in these elements will result in the operation of the CAS system of the railway crossing and the closure of the intersection, as well as artificial congestion in front of the intersection. Therefore, it is the most appropriate decision to use axle count sensors instead of rail chains. Here, sensors 1, 3, and 2, 4 detect that a train is approaching a railway intersection on an odd or even side, while sensors 5 and 6 serve to open the intersection for motor vehicles once the train has left the intersection completely. In addition, sensors 1, 3 and 2, 4 monitor each other’s operating status.
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Fig. 1 Method of installation of sensors. Where: lc is the calculated length of the section approaching the intersection
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Fig. 2 Algorithm of operation of the railway crossing according to the proposed method
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Radio modules that transmit commands from sensors transmit the command when there is a command, and constantly monitor the configuration of radio modules and data transmission channels when there is no command by transmitting discrete data.
3 Algorithm of Operation of Railway Crossing on the Improved Method of Data Transmission to the Railway Crossing Signaling System The operating algorithm of the railway crossing according to the proposed method is given for the current state of the railway crossing integrated with the relay CAS system. This is due to the fact that this may be an optimal solution at a time when the process of upgrading safety devices and systems in railway transport is underway [11, 14–17]. In this method, the normal condition of a rail crossing is that the sensors and modules that count all axes are in working condition and the rail crossing is open. All the circumstances that may occur in the issuance of the order to close the railway crossing, i.e. the full rolling stock, single rolling stock (motor vehicles, trolleys, motor cars, etc.) and two-axle carts of road workers are also taken into account [1–11]. Before entering the approach section of the railway crossing, a protective block section “ZP” was established by installing sensors “d1” and “d3” at a distance of 15 m from each other. The function of this protection block is to detect moving content. The mounting locations of the sensors are shown in Fig. 1. According to the proposed method, the railway crossing works in the following order: There are two different modes of transmission of the closing command at a railway crossing, these are: • normal, there are signals on sensors “d1” and “d3”; • fault condition, fault condition of one of the sensors “d1” and “d3”. The normal case is also considered for two different situations, respectively: In the first case, the sensors “d1” and “d3” begin to count the arrows when the moving long-acting unit enters the defensive block “ZP”. If d1 ≥ 4 va d3 ≥ 4 the order to close the railway crossing if the conditions are satisfied in series 1M (signal receiver module) from the module to the MUM (data transfer module) module; In the second case, the sensors “d1” and “d3” begin to count the arrows when the moving autotris or trolley (two-axle) enters the protective block section “ZP”. If the conditions d1 = 2 and d3 = 2 are satisfied in series and the time difference of the signals received from the sensors in order to distinguish the autotris or dresina from the two-axle cart of the road workers td1 ÷ td3 ≤ 6c condition is entered and if this condition is met, the command to close the railway crossing is given from module 1M to module MUM.
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In both cases, the MUM module is transmitted wirelessly via an attached radio channel at an open frequency of 410–441 MHz to the MQM (data receiving module) module located at the railway crossing. The defective condition is also considered for several situations in turn: In the first case, the sensors “d1” and “d3” begin to count the arrows when the moving long-acting unit enters the defensive block “ZP”. If d1 ≥ 4 condition fulfilled d3 ≥ 4 if the condition is not met, d3 ≥ 1 condition is checked. If this condition is not met, the sensor “d3” is considered faulty, and the command “sensor d3” is given as faulty, together with the command to close the railway crossing, from module 1M (signal receiving module) to module MUM (data transmission module); In the second case, the sensors “d1” and “d3” begin to count the arrows when the moving autotris or trolley (two-axle) enters the protective block section “ZP”. If condition d1 = 2 is satisfied and condition d3 = 2 is not satisfied, then the condition d3 > 1 is checked. If this condition is also not met, the sensor “d3” is considered to be faulty, and the command “sensor d3” is faulty, together with the command to close the railway crossing, from module 1M to module MUM; In the third case, the fault condition of the sensor “d1” is checked, i.e. if the condition d1 ≥ 4 is not fulfilled, then the condition d1 = 2 is checked. If this condition is not satisfied, the condition d3 ≥ 2 is checked for the presence of a signal on the sensor “d3”. If this condition is met, the sensor “d1” is considered to be faulty, and the command “sensor d1” is given as faulty from module 1M to module MUM together with the command to close the railway crossing. If the condition d3 ≥ 2 in the third state of the fault condition is not met, then it returns to the variables, i.e., “d1” and “d3”. This indicates that there is no moving content in the ZP protection block, and this will be repeated until the moving content appears in the ZP protection block. In this order, the working condition of sensors “d1” and “d3” is constantly checked. In all cases of both normal and faulty conditions, the commands transmitted from the MUM module via the attached radio channels are received by the MQM (data receiving module) module located at the railway crossing and transmitted to the correct MTQM (data analysis module) module. The MTQM module analyzes the command to close the railway crossing from the sensor “d1” or “d3” and gives the command to close the intersection to the CAS (automatic railway crossing signaling) system to start it and close the intersection. Then the activation condition of the CAS system (operation of audible and stoplight alarm V, open position of the PV relay) is checked. If the condition is met, the intersection board will turn on an indicator indicating that the train is approaching the intersection in an odd direction and will give an audible message. If a fault in one of the sensors “d1” or “d3” is noted, it changes the indication of the operation control of the sensors located on the intersection board from green to red. This indicates that the sensor is faulty. In the next step, the MTQM module checks whether the intersection is closed (the current status of the zU relay controlling the barrier closure). If the condition is not satisfied, then the CAS system returns to the condition that it starts. If the condition is satisfied, then the presence of a signal on the sensor “d5”, which serves to open the railway crossing, is checked for the condition d5 ≥ 2. If this condition is not
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satisfied, then the condition d1 = d3 is checked. Fulfillment of this condition means that the moving content has passed through sensors “d1” and “d3” and the data of sensor “d1” or “d3” is passed from module 1M to MUM module as a command to open the railway crossing. If the condition d1 = d3 is not met, it means that one of the sensors is faulty and the condition d1 > d3 is checked. Fulfillment of this condition means that the sensor “d3” is faulty and the data of the sensor “d1” is faulty, if not, the sensor “d1” is faulty and the data of the sensor “d3” is transferred from module 1M to the module MUM. The MUM module, in turn, transmits this command to the MQM module located. At the intersection via the attached radio channel. The MQM module receives the transmitted command and transmits it to the MTQM module, and this loop to d1; continues until the condition d3 = d5 is satisfied. If the condition d1; d3 = d5 is met, it means that the rolling stock has vacated the railway crossing. The MTQM module gives the command to open the intersection to the CAS system and checks whether the intersection is open (non-toxic state of the zU relay controlling the opening of the barrier). This cycle continues until the zU relay is de-energized. Upon fulfillment of the condition, the railway crossing will be fully open for the movement of motor vehicles and the system will return to its normal operating mode.
4 Modeling of the Method of Control of Approach Sections of Railway Crossings Today, the rapid development of techniques and technologies in the field of wireless communication has brought the process of data acquisition and transmission to a new level. As a result, as in other areas, the use of wireless communications in some directions of railway transport has begun, and this is justifying itself. The development of these technologies allows the use of wireless means in the process of receiving and transmitting data, even in railway safety systems [3, 4, 8, 9, 16, 17]. In the CAS system, which provides security at a railway crossing, it is important to know their reliability and safety when using wireless radios during data acquisition and transmission. Therefore, in order to ensure safety at the railway crossing and increase the reliability of CAS devices, we consider the proposed method of controlling the approach sections of railway crossings and mathematical modeling of potential hazards in their operation in close connection with CAS devices. In studying the safety of wireless transmission of information about the approach of trains to railway crossings to CAS systems, it is possible to check several crossing cases with Markov chains [16, 17]. Theoretically, train motion can be represented by a stochastic process. It will be necessary to include several cases in accordance with the process of sending the message of approach of trains to railway crossings (Fig. 3): 1. In the CAS system, information about the approach of trains is sent wirelessly to the CAS system.
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Fig. 3 Approach model of approaching trains to railway crossings
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2. In the case of the CAS system, information about the approach of trains will not be sent to the CAS system without your connection. 3. If the CAS system is faulty, information about the approach of trains will not be sent to the CAS system wirelessly. In accordance with the processes of sending the message of approach of trains to railway crossings, we can determine the indicators of the processes that connect several cases. We, as indicators of connecting processes, vary the speed of trains on the maximum section and the distance of data transmission depending on the maximum and shortest distances, and accept the following notation: λ2 μ2 λ3 μ3 λ23 λ32
Intensity of switching the wireless device to fault mode; The average time it takes for a wireless device to be restored to its original state; Intensity of transition of CAS system to failure mode; The average time it takes for the CAS system to recover to its default state; Intensity of transition from CAS system configuration and wireless device failure to CAS system failure and wireless device configuration; Intensity of transition from CAS system fault and wireless device failure to CAS system word and wireless device failure.
We create the Fokker–Planck (Kolmogorov) equation by writing the semi-Markov processes using differential equations in accordance with the connections between the cases of wireless data transmission to the CAS system: ⎧ d P1 (t) ⎨ dt = −λ2 · P1 (t) + μ2 · P2 (t) − λ3 · P1 (t) + μ3 · P3 (t) d P2 (t) = λ2 · P1 (t) + λ32 · P3 (t) − λ23 · P2 (t) − μ2 · P2 (t) ⎩ d Pdt3 (t) = λ23 · P2 (t) − λ32 · P3 (t) − μ3 · P3 (t) + λ3 · P1 (t) dt
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P1 (t) + P2 (t) + P3 (t) = 1 where: P1, P2, P3—Probabilities of occurrence of 1, 2, 3 cases. By changing the expression of Eq. (1) above to the Laplace equation, we obtain the following expression.
Improved Method and Algorithm of Railway Crossing Automatic
⎧ ⎨ s · P1 − 1 = μ2 · P2 − λ2 · P1 − λ3 · P1 + μ3 · P3 s · P2 = λ2 · P1 + λ32 · P3 − λ23 · P2 − μ2 · P2 ⎩ s · P3 = λ23 · P2 − λ32 · P3 − μ3 · P3 + λ3 · P1
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This means that if we change the expression of Eq. (2) to the Laplace table F(s) = 1/s → f (t) = 1 we get the following expression: ⎧ ⎨ λ2 P1 + λ3 P1 − μ2 P2 − μ3 P3 = 1 λ P − λ23 P2 − μ2 P2 + λ32 P3 = 0 ⎩ 2 1 λ3 P1 + λ23 P2 − λ32 P3 − μ3 P3 = 0
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We calculate the system of equations using the Krammer method to express the resulting equations (3). The following boundary condition in the mathematical calculation of the probability of occurrence of cases in the resulting expressions Pi (t)|t → ∞ we put (4) as a solution: P1 = P1 (t)lt→∞= λ23 μ3 +λ32 μ2 +μ2 μ3 λ2 +λ3 λ23 +μ2 λ32 −μ3 −λ3 λ32 μ2 −λ2 λ23 μ3 −λ3 μ3 λ23 +μ2 −λ23 λ32 λ2 +λ3 −λ2 μ2 λ32 +μ3 P2 = P2 (t)lt→∞ = λ3 λ32 +λ2 λ32 +λ2 μ3 λ2 +λ3 λ23 +μ2 λ32 −μ3 −λ3 λ32 μ2 −λ2 λ23 μ3 −λ3 μ3 λ23 +μ2 −λ23 λ32 λ2 +λ3 −λ2 μ2 λ32 +μ3 P3 = P3 (t)lt→∞ = λ3 λ23 +λ3 λ23 +λ3 μ2 λ2 +λ3 λ23 +μ2 λ32 −μ3 −λ3 λ32 μ2 −λ2 λ23 μ3 −λ3 μ3 λ23 +μ2 −λ23 λ32 λ2 +λ3 −λ2 μ2 λ32 +μ3
(4)
5 Conclusion It is no secret that today, as a result of the increase in the number of freight and passenger transportation and organization works and road transport in railway transport, security at railway crossings is becoming a topical issue. Ensuring security at railway crossings and shortening the waiting time for road transport participants requires railway transport workers to take a new approach to solving these problems. In this article, using the currently advanced technology, the application of the proposed method at the railway crossing will help to solve the above-mentioned problems. In determining rolling stock, using a modern axis counting system instead of rail chains and transmitting a message that a train is approaching the crossing to the CAS system of the intersection using a protected wireless type of communication instead of cables will increase the reliability of data acquisition and transmission. The scientific article presents the algorithm of operation of the CAS system and devices of the intersection according to the proposed method. When the CAS system of the intersection works with this algorithm, the microcontroller transmits the message of the approach of the train to the intersection, at least 4 signals from the sensor when the long train is moving and 2 signals when the individual motor is
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moving. This method, unlike the operation of other types of alternative CAS systems at the railway crossing, prevents false operation when a single signal is received from the sensor and eliminates the occurrence of excessive congestion. The advantage of the proposed method is that it can be integrated with the existing relay control systems of the existing railway crossing, as well as to determine the speed of the rolling stock by comparing the time of signals from sensors “d1” and “d3” and is the ability to send a train approaching message to the intersection. It is more cost-effective, both in terms of energy consumption and in terms of maintenance and improvement of working conditions. The reliability of the proposed method is theoretically considered using the Markov chain, its safety and resistance to damage.
References 1. Nikitin AB, Boltaev ST (2016) Ensuring safety at station level crossings when organising highspeed traffic on existing lines. Proc Petersburg Transp Univ 13(2):206–214. https://doi.org/10. 20295/1815-588x-2016-2-106-114 2. Saitov A, Kurbanov J, Toshboyev Z, Boltayev S (2021) Improvement of control devices for road sections of railway automation and telemechanics. E3S Web of Conf 264:05031:1–9. https://doi.org/10.1051/e3sconf/202126405031 3. Mieloszyk E, Milewska A, Grulkowski S (2021) Safety at railway level crossings and vision zero. Arch Civil Eng 67(2):117–132. https://doi.org/10.24425/ace.2021.137158 4. Popov AN, Grishaev SYu (2021) Assessment of emergency probability at the time of vehicle involuntary stop on the railway crossing. Autom Transp 7(1):21–38. https://doi.org/10.20295/ 2412-9186-2021-7-1-21-38 5. Fayyaz MAB, Alexoulis-Chrysovergis AC, Southgate MJ, Johnson C (2021) A review of the technological developments for interlocking at level crossing. Proc Inst Mech Eng 235:529– 539. https://doi.org/10.1177/0954409720941726 6. Fayyaz MAB, Johnson C (2020) Object detection at level crossing using deep learning. Micromachines 11(12):1–16. https://doi.org/10.3390/mi11121055 7. Ambros J, Per˚utka J, Skládaný P, Tuˇcka P (2020) Enhancing the insight into Czech railway level crossings’ safety performance. Int J Rail Transp 8(1):99–108. https://doi.org/10.1080/232 48378.2019.1612791 8. Durmu MS, Yildirim U, Kur A, Söylemez MT (2010) Fail-safe signalization design for a railway yard: a level crossing case. IFAC Proc 10:337–342. https://doi.org/10.3182/201008303-de-4013.00056 9. Nowakowski W, Ciszewski T, Mły´nczak J, Łukasik Z (2018) Failure evaluation of the level crossing protection system based on fault tree analysis. Lect Notes Netw Syst 21:107–115. https://doi.org/10.1007/978-3-319-64084-6_10 10. Lukasik Z, Nowakowski W, Ciszewski T et al (2019) A fault diagnostic methodology for railway automatics systems. Procedia Comput Sci 149:159–166. https://doi.org/10.1016/j.procs.2019. 01.119 11. Sikora P, Malina L, Kiac M et al (2021) Artificial intelligence-based surveillance system for railway crossing traffic. IEEE Sens J 21(14):15515–15526. https://doi.org/10.1109/JSEN.2020. 3031861 12. Lukasik J (2021) Relation between pre-warning time and actual train velocity in automatic level crossing signalling systems at level crossings. Diagnostyka 22(2):39–46. https://doi.org/ 10.29354/DIAG/133700
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13. Djordjevic B, Krmach E, Mlinaric TJ (2018) The non-radial DEA model: a new approach to assessing safety at railway crossings. Secur Sci 103:234–246. https://doi.org/10.1016/j.ssci. 2017.12.001 14. Liang C, Ghazel M, Cazier O, El-Koursi EM (2017) Risk analysis on level crossings using a causal Bayesian network based approach. Transp Res Procedia 25:2167–2181. https://doi.org/ 10.1016/j.trpro.2017.05.418 15. Morant A, Gustafson A, Söderholm P et al (2016) Safety and availability evaluation of railway operation based on the state of signaling systems. Proc Inst Mech Eng F J Rail Rapid Transit. 231:226–238. https://doi.org/10.1177/0954409715624466 16. Toru A, Lewi A, Gradowski P (2014) Modeling of ETCS levels with respect to functionality and safety including polish railways conditions. Commun Comput Inf Sci 471:11–18. https:// doi.org/10.1007/978-3-662-45317-9_2 17. Bester L, Toru´n A (2014) Modeling of reliability and safety at level crossing including in Polish railway conditions. Commun Comput Inf Sci 471:38–47. https://doi.org/10.1007/978-3-66245317-9_5
Formation a Sustainable Supply Chain Strategy Svetlana Suvorova , Oksana Kulikova , Tatyana Kirillova , Galina Fedotova , and Evgenya Melikova
Abstract The functioning of existing logistics supply chains was disrupted by the COVID-19 pandemic, the consequences of which have not been overcome yet. The crisis was caused by the termination of logistics operations as a result of lack of resources, as well as long delays in the supply of products from suppliers and logistics partners. The cardinal transformations which are taking place in the supply chains are also associated with the transition of all logistics operations to the digital environment. The purpose of the study is to develop a strategy for the formation of a sustainable supply chain that more comprehensive responds and effectively overcomes external influences. Redesigning of the global network, setting of the new parameters for supply chain buffers, and proactive supplier’s management are aimed to overcome external influences. Rapid response to emerging logistics chain failures is achieved through end-to-end supply management, the use of an artificial intelligence-based risk management system, and planning based on forecasting, modeling and scenario development. The application of the proposed strategy for the creating of a sustainable supply chain will improve the level and quality of customer service, increase the revenue and reduce risks through the cost savings. The developed strategy for the formation of a sustainable supply chain will allow not only to monitor ongoing processes at any time, but also to correct possible changes in order to maintain the sustainability of the supply chain. Keywords Supply chain sustainability · Intelligent planning and execution · Supply chain segmentation · Generalized assessment of demand
S. Suvorova (B) · T. Kirillova · G. Fedotova · E. Melikova Peter the Great St. Petersburg Polytechnic University, 29, Polytechnicheskaya Street, Saint Petersburg 195251, Russian Federation e-mail: [email protected] O. Kulikova St. Petersburg State University of Industrial Technologies and Design, 18, Bolshaya Morskaya Street, Saint Petersburg 191186, Russian Federation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_115
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1 Introduction Over recent years, the idea has formed that the logistics companies should prioritize the efficiency over the range of activity when organizing the supply chains [1]. Consolidation of the facilities with the suppliers in order to reduce unit costs and introduce the “just in time” model should be aimed at reducing of all types of costs [2]. Prior to the pandemic, logistics entities experienced minor disruptions caused by the tariff increases and the tighter shipping regulations [3]. At the same time, the efficiency of the supply chain was reduced due to a lack of spare capacity and stocks, as well as the overdependance on suppliers [4]. The COVID-19 crisis posed an unprecedented strain on the global supply chains. Companies faced uncertainties, prolonged delays from suppliers and logistics partners, and the termination caused by lack of resources [5]. There is a high probability that even after the global economy recovery from the pandemic, supply chains will still face a number of serious challenges. Therefore, in the process of digital transformation, the market entities involved in the exchange of goods, must coordinate the distribution and exchange functions, tracking the dynamics of resource flows [6]. In connection with, the participants in the supply chain should pay attention not only to the internal integration of flow processes, but also to the establishment of long-term business linkages within the chain. Supply chains should be as effective as possible, reliable and stable, especially in the context of the transition to a digital economy [7]. Although all industries require the sustainable supply chains, the specific business cases associated with their formation are not well developed [8]. In this regard, the ability of the supply chain to maintain sustainability, which depends on the chosen strategy, is of especially relevance. This study is intended to develop an algorithm for the formation of a sustainable supply chain that can be flexible in response to both minor and serious external influences. To achieve the strategic results the sustainable supply chain formation must be based on the consolidation of market, production, procurement and distribution [9]. Sustainability is the ability of market actors to manage with stress, restore meaningful functions, and evolve in changing circumstances [8]. A sustainable supply chain strategy smooths out external impacts on productivity and increases the speed and degree of the productivity recovery, both in normal times and times of crisis [10].
2 Materials and Methods The sustainable supply chain strategy should be based on the methods that enable cope effectively with both external influences and respond flexibly to emerging failures (Fig. 1).
Formation a Sustainable Supply Chain Strategy Effective management of external influences: - redesign of the global network; - setting new parameters for the supply chain buffers; - supplier management
Sustainability
1133 Quick response to disruptions: - end-to-end supply chain management; - risk management; - planning based on system analysis
Fig. 1 Methods for building a sustainable supply chain
Helping to support coping external influences are redesigning of the global network, setting of new parameters for supply chain buffers, and actively supplier management [11]. Redesign of the global logistics network. A sustainable supply chain provides flexibility through the selective application of reservation such as dual provisioning [12]. Other approaches involve the location of the delivery entities “nearby” so as to reduce dependency on the complex global logistics and vertical integration to ensure the production of critical components in-house (including those related to IT). A comprehensive risk assessment could serve as a basis for the determining how to balance flexibility, efficiency and effectiveness in the reorganization of the global logistics network. Setting new parameters for the supply chain buffers. To increase the sustainability, an efficient multi-level inventory system should be developed. It will provide more accurate results at nodes in the supply chains with high volatility [13]. More over the change in capacity utilization targets should be evaluated and the triggers that indicate the need to add or activate additional capacity based on the consumption trends should be identified. The order fulfillment strategies (“make it yourself” or “buy”) with customer needs are also important to align. Active supplier management. The assessment of possible risks in dealing with suppliers and adjusting relationships will ensure the availability of resources and the transparency of several levels of delivery. It is required to monitor performance (time and quantity of delivery) and risk indicators (credit ratings and geographic concentration), share up-to-date information in a timely manner to get a sense of the reliability of the suppliers [14]. Rapid response to disruptions in the chain is achieved by the end-to-end supply management, risk management and planning based on systems analysis. End-to-end supply chain management. Delayed response to unforeseen events often occurs in third party assets that perform a supporting function. To speed up the response the end-to-end visibility should be set up and the high degree of cooperation should be provided. The visibility includes not only suppliers at different levels, but also logistics intermediaries (the analytical systems based on artificial intelligence to issue decisions and coordinate operations are used) [15]. In order to adapt to supply and demand changes the uniform sales methods, the same technologies for performing operations, supplementing plans with time horizons should be used.
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End-to-end risk management. Comprehensive monitoring of possible risks helps to form a rapid response system consisting of data that monitors external indicators and combines them with traditional operational data in a central repository [16]. The development of the leading risk indicators require the loading of the data into an artificial intelligence-based, risk-focused analytics system to mitigate potential impacts [17]. Planning based on forecasting, modeling and scenarios. The ability to cope with crises as well as to cope with day-to-day instability can be improved by the implementing of the advanced solutions such as “digital twins or copies”. “Digital Twins” model the performance across the entire supply chain for several weeks ahead, pinpointing the consumers who may be affected by disruptions [18–20]. The use of analytical data makes it possible to develop mitigation measures in advance and to eliminate problematic situations. In addition, to understand the degree of influence of many potential risks the scenario-based planning should be applied. It will allow them to be predicted and balanced [21]. The logistics strategy includes plans, techniques and decisions based on analysis, analytics and digitalization. At the same time, the observed level of transformation of supply chains into the digital environment is insignificant, due to the lack of necessary investments in the transport and hub infrastructure. Therefore, this issue is receiving increased attention from both the business sector and governments of different countries.
3 Results The development of a sustainable logistics supply chain strategy is based on such elements of the supply chain strategy as a single demand assessment, segmentation, planning and execution (Fig. 2). Summary demand assessment. The data from four different sources should be obtained to create a unified understanding of the demand (Table 1). For the generalization of which the development of a demand planning mechanism focused on understanding the market and predicting the pricing strategy is required.
Summary demand assessment Supply chain segmentation Intellectual planning and execution
Fig. 2 Elements of supply chain strategy
Supply chain strategy
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Table 1 Sources of consumer demand Sources
Content
Internal data
– retail deliveries; – price, discount, action; – product attributes (brand, characteristics, etc.)
Consumer database
– retail results; – POS technology or syndicated data usage
Socio-economic data *
– quarterly GDP; – consumer price index (CPI); – unemployment rate, inflation rate
External data
– consumer reviews in social networks; – number of holidays in a calendar year; – competitor prices affecting demand
Note * Helps to increase the understanding the motivation of the consumer behavior, the impact of seasonality in the consumption of goods, to identify current and future market trends and to predict possible supply chain patterns
The data presented in Table 1 is used to form a cyclical demand planning process (Fig. 3) with references to the supply plan, financial plan and sales plan for the forecast period. At the first step, the information is collected for the sales planning. In order to form a plan on the base of forecast of market demand the future promotions, discounts, marketing investments, work reports for the previous period are taken into account. When setting the planning horizon, it also should be taken into account that its value must be sufficient for the implementation of the developed plan. The second step is to apply the demand forecast generated in the first step. It is to predict future orders from retailers at the item number and week levels (detailing the sales plan to better understand future orders from manufacturers from retailers). The third step is to determine the compliance of the shipment forecast and the supply plan. The supply plan is a plan that considers the resources of the participants Sales plan Step 1 Demand forecast Step 2 Step 5
Retail order forecast Step 3 Supply plan Step 4 Financial plan
Fig. 3 Cyclical demand planning process
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in the supply chain (stocks of raw materials and finished products, including safety stocks; production capacities, and other restrictions) and maximizes key performance indicators (profit, profitability, etc.). The fourth step is to aggregate retail orders, weekly forecasts and generate a financial forecast at the brand or item number level for each month of the planning period. In the fifth step of the cyclical demand planning process, the financial forecast is compared with the business objectives and supply chain sales plan. Thus, the cyclical process is reduced to a single forecast generated throughout the delivery process. After which the accuracy of the forecast, ways of interpreting and the launch frequency are determined. Consumption forecasting is a simpler task than retail order forecasting. The accuracy of the forecast at the end of the first step should be fairly high. The use of a cyclic demand planning process makes it possible to provide the forecast accuracy at 85%. This level of accuracy is achieved through the use of data collected from four sources and their analytics. This approach improves the forecast accuracy by 15–20% compared to the standard one. Compared to other technical challenges associated with generating a unified view of demand, the ability to interpret the forecast data is the most important point. The interpretation should be carried out considering the determining: – reasons affecting the prognosis; – changes occurring in the forecast formed in the different periods of time for a specific number; – deviations between the forecast and actual sales. The frequency of the demand planning cycle depends on the stage of the life cycle of companies and brands. For most businesses, the steps 1–3 should be completed weekly. While the steps 4–5 on financial planning and trading should be completed monthly. Supply chain segmentation. The basics of the supply chain segmentation are the efficiency or the effectiveness. In the first case, the concentration of efforts is aimed at the quality of operations performed in functional areas (supplier selection, production processes, product sales, product distribution). The decisions on production and distribution of products are based on long-term forecasts. At the same time, stocks of finished products should be located in close proximity to the end consumer. The cost of the product should be used as a supplier selection criterion. In the second case, the segmentation of the supply chain is based on the speed of order fulfillment, the level of service and customer satisfaction, by optimizing all types of costs [22]. This approach assumes the presence of a wide range of rapid turnover goods, the production of which is based on the realized demand, and not on the forecast. At the same time, the search strategies, supplier selection and transportation depend on the speed of delivery, and not on the cost of products. In both cases, the value proposition, the entry channels to market, and the product features are the key criteria for the supply chain segmentation that should not be ignored. At the same time, the logistics segmentation allows you to: create a complex
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Table 2 Characteristics of intellectual planning and execution processes Planning
Execution
Main objective
Formation the plan of supply and determining the volume of necessary resources
Rapid response to plan deviation or demand/supply changes
Planning horizon
Medium-term (40–50 weeks)
Short-term (up to 6 weeks)
Process
Discrete-mode
Heppepyvny
Date of reference
Setting the order point
Real time
Purpose of delivery
Forecasting retail order
Ensuring the forecast accuracy
structure of the chain in order to serve consumers of different segments and to increase the work efficiency by applying a differentiated approach to the supply management in a particular segment. Intellectual planning and execution. After collecting and systematizing the input data, the analysts form a supply plan. Therefore, the intellectual planning starts at the beginning of the 3rd step (Fig. 3) from the time of matching the data and input parameters (for example, equity investments and marketing in a particular region, or sales figures for a particular brand or market). Automation of the functions performed by the supply chain links will significantly reduce the planning process (Table 2). This is especially important when organizing the supply of goods with high demand volatility. Regardless of the frequency, the planning process must be accompanied by the systematic monitoring of the supply chain. For example, the monitoring of the productivity indicators only (capacity, stock status, and service level) is insufficient as it may indicate that business process reengineering is not required. However, the additional analysis of the shipment tracking data may indicate the presence of certain problems that reduce the probability of a predicted order being fulfilled. Intellectual planning [23] and supply chain execution complements research and development by combining three functions: – implementation of execution in real time, taking into account internal and external data to identify the possible deviations from the plan; – application of analytics and artificial intelligence to assess the effectiveness of the supply chain; – optimization of the decision on the choice of the method of order execution in the supply chain, taking into account the compromise agreement and the existing tasks.
4 Discussion Evolution of customer needs, attitudes and values have influenced both a significant change in demand and the need to inject investment into the digital transformation of
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supply chains, enabling businesses to choose the most appropriate strategy for each chain. The resulting balance between delivery efficiency and responsiveness reduces risk and improves the customer focusing. While the benefits of economies on the scale retain in the sectors such as supply chain, infrastructure and manufacturing capacity. Modern supply chain management is associated not only with the organization of the logistics process, but also with the creation of additional competitive advantages. Therefore, a sustainable supply chain strategy should cover business processes occurring in the functional links. The ability of a supply chain to regenerate, reroute or replace resources while maintaining its efficiency depends directly on the strategy used. The traditional approach to demand forecasting, based on consensus and then negotiated, does not identify differences between products and channels. Deviations from the plan and supply disruptions that occur are managed as they occur. Even with increasing operational efficiency, continuous improvement of production, packaging, distribution processes, the level of order fulfillment does not fully correspond to the prevailing competitive conditions and market realities [24]. Use of the cyclic demand planning process based on data, analytics and automation allows you to reduce the time of planning and order fulfillment by optimizing business goals, restrictions on retailers, regions and product categories, and makes it possible to form the most progressive supply plan. At the same time, intellectual execution complements the intellectual planning by providing up-to-date information in real time to assess the future state of the supply chain and to make the necessary decision. As a result of applying a supply chain sustainability strategy includes three main components: a single view of demand; supply chain segmentation; intellectual planning and execution. It allows to increase the level of service by 5–10% and implies an improvement of customer services, reducing unfulfilled sales by up to 10%, which leads to an increase in revenue and a reduction in risks by 10–20%, due to the cost savings. In combination with real-time key performance indicators, the business gets the opportunity to monitor not only the ongoing processes in the supply chain at any time, but also to anticipate and correct possible changes to the forecast planning horizon.
5 Conclusions The transition of the industry to the digital environment is aimed at improving the efficiency of the designed supply chains in order to: – providing assistance to partners and consumers in the acquisition of safe and high-quality products; – being able to track returns, defects and manage reviews;
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– concentration of efforts to improve the stability and reliability of the country’s logistics system in the near future. In the process of digital transformation, market entities involved in the exchange of goods need to coordinate the functions of distribution and exchange, tracking the dynamics of the resource flows. That is why supply chain participants need to pay special attention to issues related to the choice of a logistics strategy. When forming a supply chain strategy, methods effectively cope with both external influences and respond more quickly when disruptions occur should be used. Helping to support coping efforts are redesigning of the global network, setting new parameters for supply chain buffers, and proactively managing suppliers. Rapid response to disruptions in the chain is achieved through end-to-end supply management, risk management and planning based on system analysis. A sustainable supply chain strategy should be based on three key components: a generalized assessment of demand; supply chain segmentation; intellectual planning and execution. To create a single view of demand an advanced analytics to a range of internal and external data sources is necessary to apply. It provides the automation and improve the accuracy of forecasts. Segmentation of the supply chain allows to create a complex design of the chain, in order to serve consumers of different segments and increase efficiency by applying a differentiated approach to the supply management in a particular segment, combining effectiveness, efficiency and value for customers. Intellectual planning and execution should shift from traditional planning to analytics-driven decision making with a higher level of automation of order fulfillment in the supply chain, taking into account the compromise agreement and the existing tasks. A three-pillar supply chain strategy provide the improving of customer service, reducing the number of unfulfilled sales, increasing the revenue, and reducing risks through the cost savings. Acknowledgements The research is partially funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program ‘Priority 2030’ (Agreement 075-15-2021-1333 dated 30.09.2021).
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Mathematical Model of the Radial Bearing with a Fusible Metal Porous Coating Murman Mukutadze
and Aleksandr Mukutadze
Abstract The article is devoted to the development of a refined design of a mathematical model and method of solution of the problem of the classical hydrodynamics using liquid lubricating material and melt fusible metal coating surface of the shaft with a laminar flow regime truly viscous rheological properties, as well as in the flow of lubricant in the porous body surface finish of the bearing sleeve and axial force feed lubricating material that provides hydrodynamic regime of lubrication in bearing of finite length. On the basis of the equation of the true flow of a viscous incompressible fluid for a “thin layer” of the continuity equation, the equation for the lubricant in the body of the porous coatings, as well as the equation describing the radius of the molten surface of the shaft in a cylindrical coordinate system with the relevant boundary conditions, given standard assumptions exact self-similar solution. The result for the velocity field and pressure, the formulas for calculating zero (without melting) and a first approximation (including melt), as well as the function that determines the radius of the molten contour of the shaft in lube and porous layers, allowing to determine the bearing capacity and the friction force. Numerical analysis shows a significant influence of the parameters that characterize: the melt, the damping properties of the porous coating, the thickness of the porous coating and the supply of lubricant in the axial direction. Keywords Transport infrastructure · Radial bearing of finite length · Metal coatings · Hydrodynamic friction mode · Porous coating · Melt coating · Cylindrical coordinate system · Lubrication in the axial direction · Self-sustaining process · Stable fluid friction mode
M. Mukutadze (B) · A. Mukutadze Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Square, Rostov-on-Don 344038, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_116
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1 Introduction To ensure the hydrodynamic mode [1–8] of sliding bearings operating, the constant availability of lubricant is necessary. The analysis of works [9–20] devoted to ensuring the hydrodynamic flow regime of liquid lubricant in the presence of one of the low-melting metal or porous coating surfaces, as well as with simultaneous coating of mobile and stationary working porous and low-melting metal surfaces and shows that a significant drawback is that in such bearing designs the lubrication process is not self-supporting. It is necessary to have a porous and low-malting metal coating, as well as regular forced feed of lubricant in the axial and radial directions, to ensure a stable liquid mode of friction of the bearing structure. This work presents a design model of a radial bearing of finite length with a low-melting metal and porous coating on the surface of the bearing sleeve and shaft, respectively, as well as an axial forced feed of lubricant.
2 Problem Statement The steady motion of a viscous incompressible fluid between an eccentrically positioned spike and a bearing is considered. A finite-length bearing with a porous layer on the working surface is stationary, and a shaft with a low-melting metal coating on the working surface rotates at an angular velocity of , while the lubricant is fed into the bearing gap in the axial direction. To write the equation of the bearing and shaft contours, we will use a cylindrical coordinate system with the origin in the center of the bearing (Fig. 1). C2 : r = b, C3 :r = b + h, O1 M = a − β f (θ ) is the radius of the molten shaft contour, a is the radius of the shaft before the melting. For the points of the molten contour of the shaft C 0 we have: O M = O O1 cos θ + O1 M cos ϕ, where O1 is the center of the shaft, O is the center of the bearing, OO1 = e is the eccentricity, θ is the polar angle of the point M of the contour C 0 , ϕ is the angle between OM and O1 M. From the triangle OO1 M, by the sine theorem, we find sin ϕ, and then cosϕ: e sin θ β O O1 sin θ = = ε 1 + f (θ ) sin θ, O1 M a − β f (θ ) a 2 β 2 β 2 2 cos ϕ = 1 − ε 1 + f (θ ) sin θ ≈ 1 + O ε , a a
sin ϕ =
where ε =
e a
is the relative eccentricity.
(1)
Mathematical Model of the Radial Bearing with a Fusible Metal …
1145
Fig. 1 Design model
Given (1) for the contour C 0 in the approximation we have adopted, we obtain the equation: β O M = a 1 + ε cos θ − f (θ ) . a
(2)
The initial basic equations are: equations for the flow of a viscous incompressible liquid for the case of a “thin layer”, the continuity equation, the equation describing the flow of lubricant in the body of a porous liner, and the equation describing the radius of the molten contour of the shaft surface. In the cylindrical coordinate system, the above system of equations is written as: 2 ∂ vθ 1 dp ∂vr 1 ∂ 2 vθ vr 1 ∂vθ μ = , = 0, + + + ∂r 2 r ∂r 2 r dθ ∂r r r ∂θ 2 ∂ vz 1 dp 1 ∂ vr μ = + , ∂r 2 r ∂r r dz b 2μ d β ∂vθ 2 ∂vz 2 a 1 + ε cos θ − f (θ ) = + dr , dθ a L ∗ ∂r ∂r H (θ)
∂2 P ∂2 P 1 ∂P 1 ∂ P + + + = 0. 2 ∂r r ∂r r ∂θ ∂z 2
(3)
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Here vr , vθ , vz are the components of the velocity vector, p is the hydrodynamic pressure in the lubricating layer, P is the pressure in the pores of the liner, a is the radius of the molten shaft, a − βa f (θ ) is the molten radius of the contour of the shaft, μ is viscosity of lubricant, L ∗ is specific heat of melting per unit volume. When writing the boundary conditions we assume that the surface of the shaft meets condition of adhesion of the lubricant on the inner surface of the liner normal component of velocity is determined by Darcy’s law. And there is no slip of the fluid, when passing through the porous boundary pressure continuously on the outer surface of the porous layer, the normal component of velocity is zero, when θ = 0; the pressure is set at the start and end sections. Thus, the boundary conditions for speeds and pressure in the lubricant layer between the shaft and the bearing are written as:
v = ∗ O1 M, vz = 0 on C0 ; vr = − μk ∂∂rP , vθ = 0, vz = 0 on C2 ,
∂ P = 0 on C3 , p 0, z = p 2π, z , p = P on C3 , ∂r p = P = p H at θ = 0, z = 0, p = P = p K at θ = 0, z = l a − β f (θ ) = h ∗0 at θ = 0, θ = 2π.
(4)
If we project the velocity vector v = ∗ O1 M of the shaft neck on the coordinate axis, we get: vr = −(a − β f (θ )) sin ϕ, vθ = (a − β f (θ )) cos ϕ, vz = 0 on C0 .
(5)
Taking into account (1): vr = −εa sin θ + O
β β ε , vθ = a 1 − f (θ ) , a a
vz = 0 on C0 .
(6)
Before we formulate an exact self-similar solution of the system of equations (3) ∂v θ and ∂rz , we average integrally over the satisfying the boundary conditions (6) ∂v ∂r interval [b, H (θ )]: ∂vθ ≈ ∂r
a 1 −
f (θ ) ∂v z ; ≈ 0. H (θ ) − b ∂r β a
(7)
Mathematical Model of the Radial Bearing with a Fusible Metal …
1147
Taking into account (7) for the definition a − β f (θ ), we come to the following equation: d 1−
β a
f (θ )
dθ
2 2μ 1 − βa f (θ ) e . = sin θ + a L ∗ 1 + ε cos θ − βa f (θ ) − ab
Integrating this equation, we get: 2μ h∗
= 0 + ε cos θ + ∗ a L
θ 0
2 (θ )dθ .
(θ ) + ε cos θ − ab
Solving this equation by the method of successive approximations, we have:
0 =
h ∗0 a
+ ε, 1 =
h ∗0 a
θ + ε cos θ + K 0
h ∗0 a
h ∗0 a
2 + ε dθ
+ ε + ε cos θ −
b a
.
(8)
Integrally averaging 1 (θ ) over the interval [0, 2π ] for the averaged radius of a shaft with a molten surface, we get: 1 α = 2π ∗
2π a 1 (θ )dθ,
O M = α ∗ (1 + ε˜ cos θ ), ε˜ =
0
e . α∗
(9)
In the lubricant layer, let’s move on to dimensionless variables using the formulas: μα ∗ b vr = δu, vθ = α ∗ v, p = p ∗ p, r = b − δr, δ = b − α ∗ , p ∗ = , z = zb, vz = α ∗ w δ2
(10)
In a porous layer, we proceed to dimensionless variables using the formulas: P == p ∗ P, r = br ∗
(11)
Substituting (10) and (11), respectively, in (3) and (5), we arrive at the following system of and boundary conditions for them (with an accuracy up to the
equations terms O bδ ): ∂ 2v ∂p , = 2 ∂r ∂θ
∂u ∂v + = 0, ∂r ∂θ
∂ 2w ∂2 P ∂ p ∂2 P 1 ∂P 1 ∂P , + = + + = 0, ∂r 2 ∂z ∂r ∗2 r ∗ ∂r ∗ r ∗ ∂θ ∂z 2 (12)
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v = 1, u = −η˜ sin θ, w = 0 at r = 1 − η˜ cos θ,
∂P v = 0, w = 0, u
r =0 = − K˜ ∗
, ∂r r ∗ =1
∂ p
pk l = 0, p = P = ∗ at θ = 0, z = . ∂r ∗ r ∗ =1+ h p b b
pH p = P = ∗ at z = 0, θ = 0, p
(13)
∗ where η˜ = δe , , K˜ = αhδkb 3 . We will look for an exact self-similar solution of problem (12)–(13) in the form:
v=
∂ψ ∂ψ ˜ ), V (r, θ ) = v(ξ + V (r, θ ), u = − + U (r, θ), ψ = ψ(ξ ˜ ), U (r, θ) = u(ξ ˜ )η˜ sin θ ∂r ∂θ
r , ξ= 1 − η˜ cos θ
θ P= 0
C˜ 1 dθ C˜ 2 + Az + B + (1 − η cos θ ) (1 − η cos θ )2 θ
0
P = R r ∗ η˜ C˜ 1 sin θ + Az + B, w = w(ξ, ˜ θ)
(14)
Substituting (14) in (12) and (13), we get:
d 2 v˜ = C˜ 1 , dξ 2
d 3 ψ˜ = C˜ 2 , dξ 3
∗
∗
d2 R r
d v˜ d u˜ +ξ = 0, dξ dξ
+
dr ∗2
dR r R2 r ∗ ∂ w˜ − = 0, = A(1 − η˜ cos θ)2 r ∗ dr ∗ r ∗2 ∂ξ 2
(15)
v˜ = 0, w = 0 at ξ = 0; u˜ ξ =0 = − K˜ 1, u˜ = −1, at ξ = 1,
dR , dr ∗ r ∗ =1
1
ψ = 0 at ξ = 0, ξ = 1, 0
dR dr ∗ r ∗ =1+ hb
R(1) = 1,
d R
˜ vdξ ˜ = −K ∗ , dr r ∗ =1
B=
= 0, w˜ = 0, v˜ =
ph , p∗
A=
pk − ph b . p∗ l (16)
The solution of the problem (15)–(16) in the approximation we have adopted is found by direct integration. As a result, we will have: ψ =
2 2 2
C 1 ξ + 1 − C1 ξ, ξ −ξ , v=C 2 2 2
R r∗ =
p = C˜ 1 η˜ sin θ + Az + B, C˜ 1 = 6 − 12 K˜ , C˜ 2 = −C˜ 1 ,
2 1 + hb
2 +
2 1 + 1 + hb 1 + 1 + hb r ∗ r∗
Mathematical Model of the Radial Bearing with a Fusible Metal …
w˜ = A(1 − η˜ cos θ)2
1149
ξ ξ2 − A(1 − η˜ cos θ ) . 2 2
(17)
Using the formula (17) for the bearing capacity and the friction force in the approximation we have adopted, we will have: Ry =
μα ∗ b ˜ ˜ C1 π η, δ2
L T P = 2π α ∗
L T P.oceB. = −Aπ, where A=
pk − ph γ α2 α∗ ( pk − ph )δ 2 , let = . ⇒ A = − lμα ∗ l δ2 μγ
(18)
From the relationships given in (18) for the main performance characteristics of the bearing at issue, the following is true. According to the results of theoretical studies, it is proved that a radial bearing of finite length with a low-melting metal coating on the shaft surface and a porous coating on the bearing sleeve surface with a constant feed of lubricant in the axial direction, the bearing capacity increases by about 9–11% compared to the situation without the feed of lubricant. And the coefficient of friction decreases by about 13–16%. An experimental study was also conducted, which confirmed the conclusions of theoretical studies (Table 1). Table 1 Experimental study The radial bearing of finite length
Coefficient of friction
No.
Standard
Low-melting metal coating
Low-melting metal Low-melting metal and porous coating coating for axial feed of lubricant
1
0.0041
0.0031
0.0019
0.0002
2
0.0045
0.0033
0.0020
0.003
3
0.0046
0.0034
0.0019
0.0008
4
0.0049
0.0038
0.0021
0.0007
5
0.0055
0.0041
0.0022
0.0006
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3 Conclusion A new expression is developed for the load capacity and friction force for a radial bearing of finite length with a low-melting metal and porous coating of the shaft and bearing sleeve surfaces, respectively, with a constant feed of lubricant. The influence of parameters characterizing the melt of a low-melting metal coating, the permeability of a porous coating, and the feed of lubricant in the axial direction are estimated.
References 1. Zakovorotny VL, Shapovalov VV, Kolesnikov VI (2006) Transport tribotechnics. Rostov State Transport University, Rostov-on-don 2. Shapovalov VV, Chelokhyan AV, Kolesnikov IV, Ozyabkin AL, Kharlamov PV (2010) Amplitude-phase-frequency analysis of critical states of friction systems. Monograph, Moscow 3. Zadorozhnaya EA, Hudyakov V, Dolgushin I (2020) Evaluation of thermal condition of turbocharger rotor bearing. In: Lecture notes in mechanical engineering, pp 1183–1193. https:// doi.org/10.1007/978-3-030-22041-9_123 4. Levanov IG, Zadorozhnaya EA, Mukhortov IV, Eschiganov MO (2020) Study of effect of metal oleates on mixed and boundary lubrication. Tribol Ind 42(3):461–467. https://doi.org/ 10.24874/ti.708.06.19.08 5. Kandeva M, Rozhdestvensky YV, Svoboda P, Kalitchin Z, Zadorozhnaya EA (2020) Influence of the size of silicon carbide nanoparticles on the abrasive wear of electroless nickel coatings. Part 2. J Environ Prot Ecol 21(1):222–233 6. Zadorozhnaya EA, Levanov IG, Kandeva M (2019) Tribological research of biodegradable lubricants for friction units of machines and mechanisms: current state of research. In: Lecture notes in mechanical engineering, pp 939–947. https://doi.org/10.1007/978-3-319-95630-5_98 7. Levanov IG, Zadorozhnaya EA, Vichnyakov D (2019) Influence of friction geo-modifiers on HTHS viscosity of motor oils. In: Lecture notes in mechanical engineering, pp 967–972. https:// doi.org/10.1007/978-3-319-95630-5_101 8. Mukhortov I, Zadorozhnaya EA, Kandeva M, Levanov IG (2019) Studying the possibility of using complex esters as AW/EP additives. Tribol Ind 41(3):355–364. https://doi.org/10.24874/ ti.2019.41.03.05 9. Kolesnikov IV, Mukutadze AM, Avilov VV (2018) Ways of increasing wear resistance and damping properties of radial bearings with forced lubricant supply. In: Proceedings of the 4th international conference on industrial engineering. Lecture notes in mechanical engineering (ICIE 2018), pp 1049–1062 10. Mukutadze MA (2016) Radial bearing with porous elements. Procedia Eng 150:559–570 11. Mukutadze AM (2016) Coefficient of a rolling motion bearing drive. Procedia Eng 150:547–558 12. Lie KN, Jerry CTSu (2013) A numerical analysis of optimum air journal bearings. J Appl Mech Eng 2. https://doi.org/10.4172/2168-9873.1000122 13. Akhverdiev KS, Alexandrova EV, Kruchinina EV, Mukutadze MA (2010) Stratified flow of two-layer lubrication in the gap of a thrust bearing with increased bearing capacity. Vestnik DSTU 2(44):529–536 14. Akhverdiev KS, Alexandrova EE, Mukutadze MA, Kopotun BE (2009) Stratified flow of twolayer lubrication in the gap of a radial bearing with increased bearing capacity and damping properties. Vestnik RSTU 4(36):133–139 15. Akhverdiev KS, Alexandrova EE, Mukutadze MA (2010) Stratified flow of two-layer lubrication in the gap of a complex-loaded radial bearing of finite length with increased bearing capacity. Vestnik RSTU 1(37):132–137
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16. Akhverdiev KS, Mukutadze MA, Alexandrova EE, Erkenov AC (2011) Mathematical model of stratified flow of a two-layer lubricant composition in a radial bearing with increased bearing capacity, taking into account heat transfer. Vestnik RSTU 1(41):160–165 17. Akhverdiev KS, Mukutadze MA, Kolobov IA, Garmonina AN (2016) Development of a design model of a radial bearing taking into account the relationship of the permeability, electrical conductivity and viscosity of a liquid lubricant on pressure. Online J Naukovedeniye 6(37):74 18. Akhverdiev KS, Mukutadze MA, Lagunova EO, Vasilenko VV (2017) Wedge-shaped sliding supports operating on a micropolar lubricant caused by a melt. Vestnik RSTU 3(67):8–15 19. Akhverdiev KS, Mukutadze MA, Lagunova EO, Vasilenko VV (2017) Hydrodynamic calculation of a radial bearing lubricated by the melt of a low-melting coating in the presence of a lubricant. Vestnik RSTU 2(66):129–135 20. Akhverdiev KS, Vovk AY, Mukutadze MA, Savenkova MA (2008) Analytical method for predicting the values of micropolar lubrication criteria that ensure stable operation of a radial sliding bearing. Friction Runout 29:184–191
Mathematical Model of a Radial Bearing with Increased Bearing Capacity Operating on Lubrication with Melt on Shaft Surface Murman Mukutadze
and Aleksandr Mukutadze
Abstract The paper studies the steady flow of the lubricant and the melt of a lowmelting metal coating of the shaft surface, which have viscoplastic rheological properties in the operating clearance of a radial sliding bearing, adapted to the friction conditions of the bearing surface of the bearing bush. In order to solve this problem, the authors used the equation of the movement of a viscoplastic lubricant (Genky— Ilyushin equation), the continuity equation and also the equation describing the radius of the molten contour of the fusible coating of the shaft surface, taking into account the rate of dissipation of mechanical energy. Having averaged the acceleration of the movement of the liquid lubricant in the operating clearance, the dependence for the contour of the molten coating of the shaft surface was obtained. As a result of the integration of the obtained dependence, the authors found the expression that allowed solving the function characterizing the contour of the molten surface of the coating by the method of successive approximations. As a result, using the method of the assessment of the original system of equations the authors obtained a system of equations at which the equations of the movement of viscoplastic lubricant and the continuity equation were reduced to an analogue of the Reynolds equation for a viscoplastic lubricant without taking into account inertia forces. Applying the wellknown method of finding the exact self-modal solution, the velocity field and pressure in the lubricating layer, as well as the load capacity and friction force, were found. On the basis of the performed theoretical studies, the experimental study was carried out while taking into account the parameters characterizing the melt of a low-melting metal coating adapted to the friction conditions of the bearing surface of the bearing bush and the rheological properties of a viscoplastic lubricant. As a result, the original expression was obtained for the calculation of the bearing load capacity and the magnitude of the friction force in the range under the following loading conditions v = 0.5 ÷ 3m/c, σ = 2 ÷ 7 MPa.
M. Mukutadze (B) · A. Mukutadze Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya sq., Rostov-on-Don 344038, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_117
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M. Mukutadze and A. Mukutadze
Keywords Transport infrastructure · Radial bearing of infinite length · Fusible metal coating · Melt coating · Lubricant and melt coating with viscoplastic rheological properties · Support profile adapted to friction conditions · Estimation method · Exact self-similar solution · Analogue of the Reynolds equation · Velocity field · Pressure in the lubricating layer
1 Introduction Many research works are devoted to the development of design models of sliding bearings with increased bearing capacity. First of all, we should note the works [1– 6], in which the computational models of the hydrodynamic theory of lubrication of sliding bearings do not take into account the non-Newtonian properties of lubricants, in the presence of a melt of a low-melting metal surface coating. In the works devoted to the design model of sliding bearings with a low-melting metal coating on moving and stationary operating surfaces, taking into account the rheological properties of the lubricant and the coating melt, which have Newtonian and non-Newtonian properties [7–13], the bearing surface of the bearing bush adapted to friction conditions is not taken into account, as well as rheological properties of a lubricant and a melt with viscoplastic properties. In this paper, we present a mathematical design model of the hydrodynamic lubrication regime for sliding bearings of increased bearing capacity operating on a viscoplastic lubricant in the presence of a low-melting metal coating on the shaft surface and adapted to the friction conditions of the bearing surface of the bearing bush.
2 Results We consider a steady-state movement of a viscoplastic fluid between an eccentrically located shaft and a bearing. A bearing without a circular profile of the bearing surface is stationary and the shaft, in the presence of a fusible coating on its surface, rotates at an angular velocity . In a polar coordinate system r , θ with a pole in the center of the shaft, we write the equation of the contours C0 , C1 , C2 as (Fig. 1): C0 : r = a − β f (θ), C1 = r = a,
O1 M = b − a sin ωθ,
O M = O O1 cos θ + O1 M cos ϕ
where O O1 = e—eccentricity, θ—polar angle of point M of C 0 contour, ϕ – angle between OM and O1 M, from the triangle OO1M by the sine theorem we get: sin ϕ =
e cos θ a O O1 cos θ = = ε 1 + sin ωθ sin θ, O1 M b − a sin ωθ b
Mathematical Model of a Radial Bearing with Increased Bearing …
1155
Fig. 1 Design model
cos ϕ =
2 a 1 − ε2 1 + sin ωθ sin2 θ ≈ 1 + O ε2 b
(1)
where ε = be —eccentricity ratio Taking into account (1) for C2 contour in the adopted approximation, we get the following equation: a O M = e cos θ + b − a sin ωθ = b 1 + ε cos θ − sin ωθ b
(2)
Here ω—is determined (determined from the condition of the maximum bearing capacity) The initial basic equations are: the equation of the movement of an incompressible viscoplastic fluid (Genky–Ilyushin equation), the continuity equation and also the equation describing the radius of the molten contour of the shaft surface. τ0 2τ0 ρ v ∇ v = −∇ p + μ + ∇ 2 V − 2 Tε ∇ H , ∇ v˜ = 0, H H 2 ∂vθ vθ 1 ∂vr ∂vr 2 H = − + + 4 ∂r r r ∂θ ∂r 2μ d(O M) = dθ L ∗
O M a−β f (θ)
∂vθ ∂r
2
dr
(3)
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M. Mukutadze and A. Mukutadze
Here vθ , vr —velocity vector components, p —hydrodynamic pressure in the lubricating layer, μ—viscosity, H —deformation rate intensity, Tε —strain velocity tensor, τ0 —ultimate shear stress, L ∗ —specific heat of fusion per the unit of volume, a—shaft radius to the melt, b—radius of circular bearing, ρ—density, ∇—Hamilton operator. The system of equations (3) is solved under the following boundary conditions: vr = 0, vθ = 0 at r = O M, vr = 0, vθ = (a − β f (θ)) at r = a − β f (θ), p(0) = p(2π), a − β f (θ) = h ∗0 at θ = 0, θ = 2π Before solving the problem through (3)–(4) interval [a − β f (θ); O M]. And get:
∂vθ ∂r
(4) we average integrally in the
(a − β f (θ)) ∂vθ ≈− ∂r (b + e cos θ − a sin ωθ) − a − β f (θ) Then: O M a−β f (θ)
∂vθ ∂r
2
dr =
2 (a − β f (θ))2 b + e cos θ − a sin ωθ − a − β f (θ)
Taking into account (5) for the determination of a (θ) = a 1 − to the following equation
β a
(5)
f (θ) we move
2 a 2 2 (θ) 2μ d
= a =0 dθ L ∗ b 1 + η cos θ − ab sin ωθ − a (θ)
(6)
Integrating this equation, we get: 2μa h∗
= 0 + ∗ a L b
θ 0
2 (θ)dθ 1 + η cos θ − η1 sin ωθ − ab (θ)
η=
e a , η1 = , b b
(7)
Mathematical Model of a Radial Bearing with Increased Bearing …
1157
Solving Eq. (7) by the method of successive approximations and subsequently integrally averaging the obtained solution in the interval [0, 2π], we get: 1 2π
2π
a 1 (θ)dθ = α∗
0
h ∗0
2μ +
1 (θ) = a L ∗ b
∗
θ 0
h0 a
dθ
1 + η cos θ − η1 sin ωθ −
(8)
h ∗0 b
Taking into account (3), we move to dimensionless variables by the formulas: vr = δu, vθ = α∗ v, p = p ∗ p, p ∗ =
μα∗2 , δ = b − α∗ , r = α∗ + δr δ2 (9)
Using the estimation method taking into account (9), we have:
∂v α∗ − + rv + O r 2 , H = δ ∂r
∂H α = 2 ∂r δ
∗
∂ v ∂v − 2 +r + O r2 , ∂r ∂r 2
1 δ =− H α ∗
α ∂H = ∂θ δ
1 ∂v ∂r
∗
−
rv 2 2 + 2 + O r ∂v ∂r
∂ v ∂v +r + O r2 ∂r ∂θ ∂θ (10) 2
The equation of the movement and the equation of continuity with regard to (10), are reduced to the analogs of Reynolds equation for viscoplastic lubrication without taking into account the forces of inertia: ∂ 2v ∂v 2τδ dp ∂u ∂p = 0, 2 = A + , + = 0, A = ∂r ∂r dθ ∂r ∂θ μα∗2
(11)
In this case, we write the boundary conditions in the following form: u = 0, v = 1 at r = 0, u = 0, v = 0 at r = 1 + η cos θ − η1 sin ωθ, p(0) = p(2π),
(12)
The exact self-similar solution of problem (11)–(12) will be found in the following form: v=
∂ψ ∂ψ ˜ + V (r, θ), u = − + U (r, θ ), ψ = ψ(ξ) ∂r ∂r
V = v(ξ), ˜ U = u(ξ)h ˜ θ , h(θ ) = 1 + η cos θ − η1 sin ωθ,
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M. Mukutadze and A. Mukutadze
ξ=
dp C˜ 1 C˜ 2 r , A+ = 2 + 3 h(θ) dθ h (θ) h (θ)
(13)
Substituting (13) into (11) and (12), we have: 2 d 3 ψ˜ ˜ 2 , d v˜ = C˜ 1 , d u˜ + ξ d v˜ = 0 = C dξ3 dξ2 dξ dξ
ψ˜ = 0 at ξ = 0, ξ = 1, u˜ = 0, v˜ = 1 at ξ = 0, u˜ = 0, v˜ = 0 at ξ = 1
(14) (15)
Solving the tasks (14)–(15), we get: ψ˜ =
2 2 1 2 C 1 C C 1 = 6 ξ − ξ , v(ξ ξ − + 1 ξ + 1, C ˜ )= 2 2 2
(16)
2 is determined from the condition p(0) = p(2π). The constant C After the necessary calculations, we get: η1 C2 = −C1 1 + A + (cos 2π ω − 1)(1 + 3A) 2π ω 1 + 3A η sin θ − η1 (cos ωθ − 1) + η1 − (cos 2π ω − 1) P= C ω 2π ω
(17)
Taking into account (16) and (17) for the dimensionless bearing capacity and friction force, we get the following expression: Ry =
3η1 cos 2π (1 + ω) − 1 A μr α ∗ b cos 2π (1 − ω) − 1 3π η(2 + A) + × 1 − + δ2 ω 1+ω 1−ω 2
A μr α ∗ b 3η1 sin 2π (1 + ω) sin 2π (1 − ω) + 1 − δ2 ω 1+ω 1+ω 2 3η1 A A − L T P = 2π α ∗ (cos 2π ω − 1) 1 − 2π ω 2 2
Rx =
(18)
As a result from the dependences obtained (18) for the main operating characteristics of the studied bearing it was proved that a radial bearing of finite length with a low-melting metal coating on the shaft surface was adapted to the conditions of friction of the bearing surface of the bearing bush on a viscoplastic lubricant material. Moreover it was found that the bearing capacity increased by 9–11%, while the coefficient of friction decreased by 13–16%. These results were obtained according to the results of theoretical studies and data of numerical analysis. In addition, the experimental studies were carried out to confirm the conclusions of theoretical studies (Table 1).
Mathematical Model of a Radial Bearing with Increased Bearing …
1159
Table 1 Experimental studies Coefficient of friction Radial bearing Parallel experiments
Standard Low-melting metal coating Low-melting metal and porous coating
1
0.001
0.0032
0.0018
2
0.0049
0.0034
0.0017
3
0.0048
0.0036
0.0020
4
0.0045
0.0037
0.0019
5
0.0044
0.0039
0.0021
Average
0.0039
0.0035
0.0019
3 Conclusion As a result of the research new expression was developed for the load capacity and friction force for a radial bearing with a low-melting metal coating of the shaft surface adapted to the frictional conditions of the bearing surface of the bearing bush on a viscoplastic lubricant. The authors made the assessment of the influence of parameters characterizing the melt of a low-melting metal coating adapted to the friction conditions of the bearing surface of the bearing bush and the rheological properties of a viscoplastic lubricant.
References 1. Zadorozhnaya E, Hudyakov V, Dolgushin I (2020) Evaluation of thermal condition of turbocharger rotor bearing. Lect Notes Mech Eng 1183–1193. https://doi.org/10.1007/9783-030-22041-9_123 2. Levanov IG, Zadorozhnaya EA, Mukhortov IV, Eschiganov MO (2020) Study of effect of metal oleates on mixed and boundary lubrication. Tribol Ind 42(3):461–467. https://doi.org/ 10.24874/ti.708.06.19.08 3. Kandeva M, Rozhdestvensky YV, Svoboda P, Kalitchin Z, Zadorozhnaya E (2020) Influence of the size of silicon carbide nanoparticles on the abrasive wear of electroless nickel coatings. Part 2. J Environ Prot Ecol 21(1):222–233 4. Zadorozhnaya E, Levanov I, Kandeva M (2019) Tribological research of biodegradable lubricants for friction units of machines and mechanisms: current state of research. Lect Notes Mech Eng 0(9783319956299):939–947. https://doi.org/10.1007/978-3-319-95630-5_98 5. Levanov I, Zadorozhnaya E, Vichnyakov D (2019) Influence of friction geo-modifiers on HTHS viscosity of motor oils. Lect Notes Mech Eng 0(9783319956299):967–972.https://doi.org/10. 1007/978-3-319-95630-5_101 6. Mukhortov I, Zadorozhnaya E, Kandeva M, Levanov I (2019) Studying the possibility of using complex esters as AW/EP additives. Tribol Ind 41(3):355–364. https://doi.org/10.24874/ ti.2019.41.03.05 7. Akhverdiev KS, Alexandrova EV, Kruchinina EV, Mukutadze MA (2010) Stratified flow of two-layer lubricant in the clearance of a thrust bearing with increased bearing capacity. Bull DSTU 10(2(44)):529–536
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8. Akhverdiev KS, Alexandrova EE, Mukutadze MA, Kopotun BE (2009) Stratified flow of twolayer lubricant in the clearance of a radial bearing with increased load-carrying capacity and damping properties. Bull RSTU 4(36):133–139 9. Akhverdiev KS, Alexandrova EE, Mukutadze MA (2010) Stratified flow of a two-layer lubricant in the gap of a complexly loaded radial bearing of finite length with increased load-carrying capacity. Bull RGUPS 1(37):132–137 10. Akhverdiev KS, Mukutadze MA, Alexandrova EE, Erkenov ACh (2011) Mathematical model of the stratified flow of a two-layer lubricant composition in a radial bearing with an increased bearing capacity, taking into account heat transfer. Bull RSTU 1(41):160–165 11. Akhverdiev KS, Vovk AYu, Mukutadze MA, Savenkova MA (2008) Analytical method for predicting the values of criteria for micropolar lubrication, providing a stable operating mode of a radial sliding bearing. Friction wear 29:184–191 12. Akhverdiev KS, Mukutadze MA, Lagunova EO, Vasilenko VV (2017) Wedge-shaped sliding bearings operating on a micropolar lubricant caused by melt. Bull RSTU 3(67):8–15 13. Akhverdiev KS, Mukutadze MA, Lagunova EO, Vasilenko VV (2017) Hydrodynamic calculation of a radial bearing lubricated by a melt of a low-melting coating in the presence of a lubricant. Bull RSTU 2(66):129–135
Leadership Vision in Advanced Technology Mustafa Günay
Abstract The technology knowledge of enterprises is the most crucial factor that determines their position and status in the market in today’s age. Considering that knowledge and technology bring along innovations in product and service production, development, it clearly reveals that it should be dealt with in depth again. The fact that businesses change and develop their own undertakings and organizations within this consciousness necessitates a transformation to be experienced. Therefore, the training of the employees of the enterprises that use technology, produce the technology and direct the technology, the information sharing in the organization and the activities related to developing the existing technology, transferring the technology or producing the technology are not a necessity in the process as a success of their skills infrastructure. In this process, improving the skills of the human resources who produce and develop technology should take its place as the most crucial factor increasing the success of the enterprise. Because in the environment of change, companies that want to exist in the future can only maintain their competitive positions by acting in the strategic direction determined by the technology leader. Keywords Technology · Leader · Technological management · Leadership vision
1 Introduction In the globalized world, companies are turning to technology investment at a large and prohibitive cost to gain a competitive advantage. This situation increases the importance of technology management day by day. Technology is vital especially for companies that want to gain a competitive advantage in the global market. There are many factors that influence the success of Technology Management (TM) in the organization. Leadership is the most effective one of these variables. In M. Günay (B) Istanbul Geli¸sim University, 1 Cihangir Dist. Sehit Jandarma Komando Er Hakan Oner Str., 34310 Avcilar, Istanbul, Turkey e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_118
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this context, the role of leadership skills in Technology Management further increases the importance of the leader over financial and engineering factors in terms of being capable of managing and guiding other resources. Today’s research has found many findings that support the clear and obvious effects of the leader’s success in the organization. In Technology Management, knowledge is limited in what are the critical skills of technology leaders and what skills should help them with how they should behave according to the type of technology to understand effective leadership. Constantly changing environmental conditions develop new methods and new perspectives in production and management processes; it also changes the shaping of organizations. These new developments reveal new types of leadership and skills. It is obvious that the crucial factor based on these developments is rapid developments in technology. In terms of effectiveness in technology, it is taken from a new perspective that production technologies should now be developed instead of the concept of installing production systems in the old system, which is evaluated as the ratio between input and output, which is carried out only with efficient production in terms of competition. It is envisaged that the most important investments to be made shall also be the human factor that uses and manages technology in the formulation of materials, labor, time, land and energy factors used effectively at the lowest cost. One of the factors that makes it possible for companies to produce an effective technology is the ability to manage the technology, and these skills should be learned and researched in such a way that they can identify and develop other factors. While technology is a complex process, it is easily understood that improvements and innovations can be realized through self-aware work in relation to service and product, considering that it is a method that takes shape with systematic and development activities.
1.1 Leadership As with all social sciences, it is unlikely to bring only one definition to concepts in management science. An analogous situation can be considered to apply to the concept of leadership. When the literature on management science is reviewed, it is not possible to encounter a meaning or definition that is accepted by everyone for leadership. In this context, each definition expresses different dimensions and aspects of the concept of leadership and sheds light on different angles. In order to realize the goals of two or more people, it can be stated that it is imperative to mention the phenomenon of leader, leadership and follower in each group of communities they create by interacting with each other, harmoniously combining their strengths, times, financial resources and efforts [1]. The definition of leadership has been tried to be explained with many concepts to date and has been discussed in different dimensions. To explain it broadly, the leader can be defined as a person who “trusts and gains their trust in the quality team
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he has gathered around him insofar as his self-belief; knows how to always strain himself and those in the field of management to learn something new; knows how to do the right thing by not forgetting the lessons he has learned; work with not only his side but also his environment in mind; being self-motivated as well as that he can do this in the lower ranks in a viewer position; knows how to be a mirror of the people he manages insofar as has the courage to see himself in the mirror; being undeterred for any defeat and provides lower level managers to adopt this feature; knows how to listen and remember rather than talk; praises the good doer and shows the truth to the wrong doer; is not afraid to take risks after calculating with his return and his benefits; be able to assume and distribute its obligations; can set an example around with his sound and healthy body and mind; not considers defeats as results and achievements as goals; use his time well as well that the timing is perfect; can respect himself as well as his environment and even his opponents; go down to the source of information and use it in the best way; understand the need to head the follower he drags insofar as the need to go after them; can decide when necessary; prepares the environment for him to be creative in the people he works with as well as himself; and create and be proud of the opportunities, desires and conditions of raising many people who can take over after himself” [2]. The spread of leadership to such a wide area and the need to become a leader or connect with the leader in public has led to numerous research on the subject, and many branches of science have tried to define leadership from their point of view. This has led to the concept of leadership having a parallel definition of each number of studies [3]. Leadership has been one of the most researched subjects in the 20th century. During this period, both researchers and theorists carried out much research in many fields to analyze leadership. As a result of this intensive effort, it was possible to reveal more than 5.000 studies and more than 350 definitions in the literature [4]. Among the most important reasons why the phenomenon of leadership is important for organizations, features are shown such as the inability of organizational plans or programs to predict everything, the environment in which the organizations are located is extremely dynamic and slippery, the faces of organizational structures are inherently forward-looking, and the most important element of organizations has a variable, unpredictable and complex structure [5]. The leader is the one who encourages people to voluntarily strive to achieve organizational goals on a group under a certain situation, time and conditions, helps them achieve common goals, conveys his experiences, and ensures that their followers are satisfied with the type of leadership implemented [6], while leadership is the process of influencing group activities to achieve the goals [3]. Another definition of leadership is the effort to get organized members to achieve what one desires [7]. It can be stated that this definition defines the concept of leadership from a different dimension, that is, from a leader’s perspective, and includes the meaning of “attempting to take leadership from the hand of the person leading any group” [3].
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1.2 Leadership Skills Leadership skills can be considered as innate and later skills as the basic skills of the leader, and many studies have researched what are the leadership skills related to this subject. As an inventory of skills, the study of Thamhain (1992), obtained by asking 355 technical managers, is included in the literature as a sequential list of skills. Skills are most divided into three classes. These are: managerial, technical and individual skills.
1.2.1
Managerial Skills
These skills, which are in the category of important skills in leadership skills, include the following skills: • Technical planning, programming, budgeting, organizing and employee management on management-related tasks, • Effective determination and estimation of resources, • Being able to measure and report on performance and business status, • Being able to see the procedures and policies as guidance on all kinds of activities of the leader, • Having no problems with handing over jobs, when necessary, • Good meeting preparation and report writing skills, • Be able to perform effectively when there is a need for change or to complete an interrupted job, • Organizing social events, • Support for management within the company and being able to work effectively with all groups can be counted as the skills of the technology leader as the main managerial skills. 1.2.2
Technical Skills
The following skills can be listed as technical skills that are the skills the leader needs most in the use and management of technology: • Being able to understand and follow technological trends in all areas of responsibility of the company and the company’s business circle, • Knowing the product applications, market and economic conditions related to its field well, • Being able to communicate effectively with employees in other technical branches, • Being able to establish a technical team in line with the project objectives and to provide opportunities for group decision making, • Having a system approach in the field of technical work, • Reliance on the technical knowledge of the employees in the business circle,
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• Being able to use the latest design techniques and engineering tools, • Being able to recognize and work with technological inventions and developments, • Measuring the technical performance and project status of other people on the team • Integrating the technical work of team members. 1.2.3
Individual Skills
Lastly, leadership skills, which are the most individual skills of all skills, can be summarized as follows: • • • • • • • • •
How to get contact with other technical and management-related units, Being able to solve conflicts on technical and individual issues effectively, Being able to work with all units in the organization, Success in connecting with units outside the organization and other departments, Socializing with people, Being able to convince people about things they do not want to do, Loyalty to its employees who are not directly affiliated with the leader, People like to work together and consider the leader’s recommendations Frequently receiving opinions of colleagues in decisions taken to present them to senior management, • Showing team leader by group members within the section where the leader is working.
2 Methods 2.1 Technology Technology is scientific applications to achieve commercial value [8] or technology can be defined as the ways and methods used by people when engaged in manufacturing activities, or all the techniques that people have and use to change their environment. The history and development of technology, which can be described as the method of production in the simplest sense, dates to the ages when humanity fought for existence and created its first intellectual equipment for this sake [9]. According to the understanding of social determinism, social development is determined entirely by the type of technology that society invented, developed or promoted. Technology is all the information that one has and uses to change the environment in which one lives in general with the aim of making it more useful to him [3].
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In other words, technology is scientific and engineering information that can be applied to the design of products or processes or to research of newly processed information [10]. There are three elements in technology. These are as follows: • Material element: Machinery and equipment, • Intellectual element: Technical knowledge (Know-how), • Referral and administrative element. Technology is a perishable resource consisting of information, capabilities and tools necessary for the production, distribution and maintenance of goods and services with economic or social demand, use and control of production factors for distribution and maintenance [11]. Technology can be defined as the sum of the information that people apply when engaged in production activities to create benefits. Technology such as natural resources, labor and capital is also a production factor. Technology is a collection of information that increases the amount of production, improves its quality, changes its form and quality, that is, helps to realize human needs in the best way. The selection, development and shaping of any technology is directly a human activity and the active party is people. The active acceptance of humans will prevent the technological level from being accepted as data, so that the creation of alternative technologies can be considered as a human activity since technology is designated as a human activity [12].
2.2 Technological Management and Competitive Advantage The concept of competitive superiority means that a business gains an advantage in the market against its competitors by creating good customers. There are many ways to gain competitive advantage. Gaining price and quality advantage over competitors, obtaining new market opportunities that will create customer value before competitors, being able to respond quickly to changing customer demands and needs are among the methods of gaining competitive advantage. In today’s market environment, where competitive factors are similar, companies should use high technology as a factor that will differentiate from each other and provide a competitive advantage. Aware of this, businesses are moving towards employing people with visions who can use technology with knowledge and direct technology with creative personality traits. In the business world, studies have started to be conducted on the development and management of competencies in relation to the progress of this trend in human resources planning [13]. The modern technology and the resulting criteria depend on the product team as well as the criteria within the organization. The benefits of modern technology should be supported in the right decisions and spread throughout the organization. In this case, the technology leader plays a key role in managing technology as the
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Technology Leadership Infrastructure • Net Usage • Technology Integration • Use of Means
• Technology Committee • Technology Budget • Region Support • Manager Email • Manager Days • Personnel Development Policy • Funds
Technology Outputs • Net Email and Web Use • Technology Integration • Use of Means
Fig. 1 Technology leadership model [14]
person who assumes this responsibility. It is important for the leader to have the most effective knowledge about what basic skills and competencies the individuals in the organization should have as a team as a decision maker. The features that the technology leader must have and manage, and the issues that should be specifically addressed in the company in which he is employed, are specified in Fig. 1 [14]. Technology also covers all production and sales processes starting from research in enterprises and reaching the customer from manufacturing. Technology is one of the most obvious factors affecting the performance of the enterprise. Modern technology includes information and methods to save raw materials, materials, labor and time used. Other factors of the enterprise, human resource contributes with the elements such as innovation, invention, knowledge and ability level, value judgments about the use of technology and the production of modern technology. In this context, an understanding and knowledge of management skills are required to provide a mutual understanding between these factors in technology management. The technology leader should be able to analyze in budget planning, sourcing, technology policy setting, future research, and be a guide on issues such as long-term investment and growth. The potential use of workforce physically, intellectually, wholeheartedly depends on an effective leadership style. Managers need to be constantly trained for the business to gain dynamism and managers to achieve the expected performance. The complexity of businesses and the way they do business, the uncertainty of technology, sudden changes necessitate conscious management. Ensuring the best use of human resources and instilling creative and innovative individuals in team spirit should be adopted by starting from the highest level in cooperation [15].
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3 Results 3.1 Technology Management Technology Management can be defined as a collection of activities related to the launch of new or innovative products [16]. Technology Management is the planning, development and implementation of the technological capacity needed to shape and achieve the strategic and tactical objectives of an organization. It is to establish the connection between management and technical expertise and increase the efficiency with the technology used, and all activities related to planning, organizing, coordinating and controlling activities for technology transfer, technology marketing, technological planning, R&D, design, manufacturing, sampling, testing, as well as technology procurement and technology development [17]. Since technology management, as it can be seen, has different activities, it takes a lot of effort to examine them together [17]. Technology management is a process that involves different disciplines and requires effective knowledge about developing technical, conceptual and scientific models. Technology management covers research method, product and process development and manufacturing engineering. From this definition, three important results emerge: • Technology is divided into a matter and an information part, • It is the information part that really represents the technology, • Dispatch and management techniques are also included in the technological information part. In this case, the social sciences examining the management part and the engineering sciences examining the matter part are synthesized together within the scope of technology management. Having technological developments and technological innovations is especially important in increasing productivity and competition. R&D and technology development investments are investments that require profitable and qualified personnel in the long term. Successful businesses focus more on technology management than their less successful competitors, for example, integration of design and production, the balance between product and R&D process, and the integration and development of technology developed outside. It is important to manage the technology management and R&D strategies of enterprises through technological leaders as specified in Fig. 2. Technological innovation and R&D strategies implemented by enterprises, technology management are all activities related to planning, organizing, coordinating and controlling activities for the provision and development of technology such as technology transfer, technology marketing, technological planning, R&D, design, manufacturing, prototyping, testing, and to establish the connection between management and expertise.
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Economic Technology Social Policy
Capital Technological Infrastructure Power
Business Strategies
Competitive Strategies
Product/Market Strategy
Technological Innovation and R&D Strategy
New Products, Services and Missions
Fig. 2 Technological innovation and R&D strategy of enterprises [18]
3.2 Technological Management and Competitive Superiority Skills A manager equipped with adequate and technically competent and effective skills can select more advanced technologies. First, the choice of capital-intensive technology brings with it various problems as well as reducing economic effectiveness. In addition, technology causes unemployment. In the early years of development, it would be more accurate to import laborintensive technology, use appropriate personnel and then reveal the necessary techniques for technology and gradually move to capital intensive technology [19]. Countries or businesses that transfer technology need to make much more efforts to develop imported technology as well with the help of domestic experts who have adopted these problems about which technologies will be useful and which will be harmful [20]. At this point, businesses need to determine the position in which their awareness of technology is present. Awareness of technology acquisition is an ongoing process starting from society.
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4 Conclusion Leadership conceptual and practical definition is an ever-changing and increasingly critical issue. The need for leaders comes across as a unit where companies that want to be the business of the future spend large investment amounts as training and development in the relevant units where leaders constantly update their knowledge and skills to maintain their presence in the business world with flexible, changeable features. In addition, companies that are in the race to have leaders who will make their businesses successful are in a race to add added value to their companies with this awareness and to recruit young leaders with potentially high leadership skills. The necessity and importance of the leaders in achieving the desired lofty goals of all organizations and countries, companies, is clear. Highly skilled and effectively skilled leaders will gain a competitive advantage with their changes and creativity in the way business life included in the business world and effective management methods in the effective shaping of the organization. Although the decisions of the leader on where the technology will go are shaped by customer requests and expectations, the importance of the human direction that governs the technology depends on the skills of the leader and his team in developing new products, modern technologies in this technological environment, since the technology progressor is the employees in the enterprise. One of the reasons why the technology leader is so important and influential is his contributions directly to the future of the business. Today, people no longer have a firm idea of where the technology will go, but the place where the rapidly developing technology will arrive in this process has a dimension that concerns the society. However, the enterprises that manage the technology can work on how innovations and changes can be made, which is the other dimension of technology, questioning what can be done and even predicting with technology maps. Businesses operating in the success of technology can explain this result with the dependence between the best organizational units. The technological environment is especially important, as the classifications can be used for all environmental factors, according to research by Perrow and Thopmson. The leader is also of immense importance in terms of managing the organization organized in the face of the technological environment.
References 1. Güney S (2017) Örgütsel Davranı¸s, 4th edn. Nobel Yayıncılık, Ankara 2. Jaipal JK, Figg C, Collier D, Gallagher T, Winters K, Ciampa K (2018) Developing TPACK of university faculty through technology leadership roles. Ital J Educ Technol 26(1):39–55 3. Kıral E, Ba¸saran R (2019) Academic leadership. In Fidan T (ed) Vocational Identity and Career Construction in Education içinde (pp 238–257). IGI Global, Hershey, PA 4. Molina OA (2018) Visionary leadership in the administrative staff of the Guapan educational unit. J Technol Sci Educ 8(2):115–125
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5. Önen SM, Kanayran HG (2015) Liderlik ve Motivasyon: Kuramsal Bir De˘gerlendirme. Birey ve Toplum Sosyal Bilimler Dergisi 5(2):43–64 6. Cemalo N (2019) Yönetimin Pin Kodu. Pegem Akademi Yayıncılık, Ankara 7. Genç A, Atasoy A (2010) Ar-Ge Harcamaları ve Ekonomik Büyüme ˙Ili¸skisi: Panel Veri Analizi. Bilgi Ekonomisi ve Yönetimi Dergisi 5(2):27–34 8. Srivastava A, Dhar R (2016) Technology leadership and predicting travel agent performance. Tour Manage Perspect 20:77–86 9. Göko˘glu S, Çakıro˘glu Ü (2014) Information technology teacher as a technology leader. II. International instructional technologies & teacher education symposium proceedings 1(3), pp 15–29 10. Alenezi A (2017) Technology leadership in Saudi Schools. Educ Inf Technol 22:1121–1132 11. Türk M, Karadal F (2008) ˙I¸sletmelerde Teknoloji Yönetiminin Gelece˘gi. Ni˘gde Üniversitesi ˙I˙IBF Dergisi 1(1):59–71 12. Gökten K (2010) Evolutionary thinking in economics and evolutionary economics’s approach to technology. Akdeniz FEAS J 1(2):1–15 13. Karaca Y (2006) Effects of technology management on corporate competition in the IT sector. Master’s Project, GYTE, Gebze 14. Balta A (2017) Ekip Çalı¸sması ve Liderlik. Remzi Kitabevi, ˙Istanbul 15. Bolat T, Seymen OA, Bolat O˙I, Erdem B (2018) Yönetim ve Organizasyon. Detay Yayınları, Ankara 16. Browne W, Dreitlein S, Ha M, Manzoni J, Mere A (2016) Two key success factors for global project team leadership: communications and human resource management. J Inf Technol Econ Develop 7(2):40–48 17. Akola¸s D (2009) Teknoloji Yönetimi ve Teknoloji Yönetim Süreci. Aksaray Üniversitesi ˙Iktisadi ve ˙Idari Bilimler Fakültesi Dergisi 1(2):203–218 18. Y H (2011) Güçlendirici Liderlik. Beta Basım Yayın, ˙Istanbul 19. ܸsür ˙I (2002) On the philosophy of technology or is the god of history technology? Mülkiye J 25(230):1–19 20. Yukl G (2010) Leadership in organizations, 7th edn. Pearson Education Inc., New Jersey
Architecture of Software Complex for Multicriteria Synthesis of Composite Materials Alexei Bormotov
Abstract The objective of the work was to develop a computer simulation system that allows solving two problems: the analysis problem—when the structure and properties of already existing composites are researched using software tools and a numerical experiment, and the synthesis problem—when, based on the proposed methodological principles, mathematical models and numerical-analytical methods, the synthesis of new composite materials with specified structure parameters and special-purpose properties is carried out. The developed software package is based on numerical methods and algorithms for the structural-parametric synthesis of mathematical models of composites based on experimental data, which are based on multilevel transformations and systematization of mathematical models by types of non-linear coordinate transformation, providing an increase in the speed and accuracy of mathematical modeling composites. Keywords Transport infrastructure · Mathematical modeling · Multicriteria synthesis · Integrated software package · Composite materials · System analysis
1 Introduction The integrated complex of mathematical modeling was developed on the basis of numerical methods and algorithms for the structural-parametric synthesis of mathematical models of composites based on experimental data, which are based on multilevel transformations and systematization of mathematical models by types of nonlinear transformation of coordinates, providing an increase in the speed and accuracy of mathematical modeling of composites [1, 2].
A. Bormotov (B) Penza State Technological University, Building 1a/11, Baydukov’s Passage/Gagarina Street, Penza 440039, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_119
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2 Research Methods and Principles While developing an integrated system for computer and simulation modeling of composite materials, the operating conditions, methods of application, personnel qualifications, technical means used, and the cost of developing a software package were taken into account [3–6]. Table 1 shows the minimum characteristics of a PC on which the developed software package can be installed. When developing a software complex for modeling composites, the features of the operating system (OS) under which the computer is controlled were taken into account. Modern operating systems have basically the same functional characteristics. The developed software package can run on a computer running Windows XP/Vista/7/8/10/ Server 2008 and Linux Ubuntu 10.04/ Linux Mandriva 2011. The integrated system for computer and simulation modeling of composite materials uses a DBMS to store reference data, experimental data, simulation results. The SQL Server 2008 R2 Standard environment was used to develop the DBMS. It is Table 1 Minimum characteristics of a PC No s.p
Name
Characteristic
Note Use from another manufacturer with similar characteristics is acceptable
The working station 1
CPU
Intel Pentium 2.0 GHz
2
RAM
1 GB
3
HDD
40 GB
4
Video system (video controller + monitor)
1680 × 1050 32 bit
5
Network Controller
Ethernet (IEEE 802.3), 100 MB/s
1
CPU
Intel Pentium Core Duo 2.4 GHz
2
RAM
4 GB
3
HDD
RAID 5, 400 GB
4
Video system
1280 × 1024 32 bit
5
Backup system
DVD RW
6
Network controller
Ethernet (IEEE 802.3), 100 MB/s
Server Use from another manufacturer with similar characteristics is acceptable It is acceptable to use other schemes of organizing RAID arrays Other backup systems can be used
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possible to use other tools (MySQL 5.5, PostgreSQL 9.0, SQLite 3.7.7), as well as later versions. As an integrated development environment (IDE)—a system of software tools used to develop software—C++ programming language, a compiled statically typed general-purpose programming language, was chosen. Programs developed in C++ are characterized by high speed, which is important for an integrated system of computer-simulation modeling of composite materials. The compiler for C++ is GCC 4.0, which is available free of charge for the selected hardware and software platform. When developing an integrated system for computer-simulation modeling of composite materials, the following software and hardware tools were chosen: • • • • •
hardware platform—Intel Pentium; operating system—Microsoft Windows XP/7/8/10, Linux; database management system—MySQL, SQLite; GCC compiler for the C++ programming language; integrated development environment—Nokia QT Creator.
The use of these software and hardware means creates a scalable, platformindependent integrated computer simulation system with minimal development and operation costs. The use of the modern QT library made it possible to create a friendly user interface, which expands the scope of the software package and allows it to be used in the educational process.
3 Results Structure of the integrated system of computer-simulation modeling of composite materials. A computer modeling system and a software package that implements all methodological principles, methods for constructing mathematical models and structural-parametric synthesis of multifactorial CM models based on multi-level coordinate transformations are an easily expandable and upgradable application that works in various operating systems. The high modularity of the application makes it easy to maintain and update this system. The application has a three-layer structure: the zero-level layer is represented by an extensible software shell (ESS), which encapsulates the main “minimal” set of functions, as well as a common graphical interface required for operation; at the first level there are modules that represent graphical and functional shells for additional modules of the second level; the second level contains modules with calculation workflows that are activated by the first level to perform the general “target” functionality of the application. General algorithm and basic procedures. Figure 1 shows the UML diagram of the operator’s activity on the use of an integrated system for computer and simulation modeling of CM.
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Choosing of composite desƟnaƟon
Choosing of binder
Choosing of modifier
Choosing of filler
Choosing of aggregate
Choosing of performance properƟes of the composite ProperƟes are not reachable
ProperƟes are reachable
Binder opƟmizaƟon No
Only glue selecƟon
MasƟc compound selecƟon No
Only masƟc selecƟon
Composite compound selecƟon
Structure parameters selecƟon
Recipe selecƟon
Technology selecƟon
Fig. 1 Software package activity diagram
The operator, for the purpose of documentation, enters the purpose of the composite. Then he selects the components: binder, modifier, filler, aggregate. Information about the properties of the component is stored in the database, if there are not enough of them, then the operator must conduct a full-scale experiment and enter the result into the database. Having chosen the required characteristics (protective, strength, technological, etc.), the operator performs the simulation. The possibility
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of obtaining a composite material according to the initial data is checked. If the specified properties of the CM are unattainable, then the necessary components are selected from the database, and the option is offered to the operator. The operator must accept or make the required changes and repeat the simulation. Next, the software package executes the binder optimization algorithm. If only glue modeling is specified, the task ends, otherwise the mastic composition is selected. The task is also completed if only mastic selection is selected. In full, the software package selects the composition of the composite, the parameters of the structure, formulation and manufacturing technology of the composite material.
4 Discussion Architecture of an integrated system for computer simulation of composite materials. The control program implements the main menu of the program, maintaining reference information, entering the purpose, composition, characteristics of the CM, entering the results of research (field experiments, measurements) of the properties of materials. It also implements the display of 2D and 3D graphs that display the progress of building the model and the resulting properties. Simulation modeling itself is carried out by calling modules implemented as a dynamically loaded library. Modules implement individual algorithms that simulate the development of particular process in a composite material. Figure 2 shows the enlarged architecture of the integrated system for computer simulation of composite materials. The integrated system for computer-simulation modeling of composite materials combines the Nokia QT 4.7, QWT standard libraries and software modules developed on the basis of the mathematical modeling methods proposed by the authors that implement the methodology for mathematical modeling of special-purpose composites. The logical structure of the database. The database serves as a repository of knowledge about the properties of materials (binders, modifiers, fillers and aggre-gates). The database also stores the simulation results. Knowledge about the properties of materials can be replenished by the operator by entering the results of field studies, modeling, and entering reference data. The physical structure is implemented for MySQL and SQLite DBMS. Figure 3 shows the logical structure of the database of an integrated system for computer and simulation modeling of composite materials, containing links between tables. The database structure is presented in 3rd normal form.
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QWT 5.2 Library
Graphical interface Open GL Classes for working with data DBMS MySQL 5.5
Building 2D-graphs QWTPlot3D library
Structure formaon of dispersed systems
Building 3D-graphs
Structure formaon of lyophobic systems Structure formaon of lyophilic systems with a solvate layer
Database Driver
Metastructure and synthesis of masc
Control program (main menu)
Calculaon of binary and unary interacons
Maintaining reference informaon Entering the purpose, composion and characteriscs of the CM Entering material properes study results
Modules Microstructures and binder synthesis
Structure formaon of the macrostructure Temperature distribuons
Solving a system of ordinary differenal equaons
Internal stresses Porosity and Density Durability
Visualizaon of results
Destrucon Synthesis of a structural model
Fig. 2 The enlarged architecture of the computer simulation system composite modeling
Fig. 3 The logical structure of the database
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5 Conclusion The developed integrated set of software for modeling special-purpose composites combines the following modules: processing of experimental data, synthesis of sets and packages of nonlinear models of structural levels of composites, analysis and evaluation of mathematical models, numerical optimization, providing the solution of problems of mathematical modeling and multicriteria synthesis composites with specified parameters of structure and properties. The advantages and novelty of the developed system for computer and simulation modeling of composites lies in the fact that the system combines methods for conducting numerical and full-scale experiments, methods for modeling macrolevels of a composite, taking into account the modeling of microlevels, as well as algorithms and software packages that provide an effective technology synthesis of composites for special purposes. Using the developed integrated software package, the authors found that the principles, techniques and algorithms implemented in the system of computer and simulation modeling provide modeling of the physicochemical processes of structure formation in the boundary layer of the dispersed phases of composites and allow 3–5 times to reduce the volume of a full-scale experiment, to increase the accuracy of modeling by a factor of 2, and to use the already accumulated single-factor experimental-statistical material in modeling [2, 7]. The results of mathematical modeling of multi-criteria synthesis of specialpurpose composites are introduced in the educational process and at enterprises of the defense complex in the form of methods and techniques for analysis and synthesis, application software packages and software systems. The experimental studies, industrial testing and operation of the created methods and software by various teams of scientists confirm the high efficiency of the developed theoretical foundations and methodology for modeling special-purpose composite materials [8–11].
References 1. Neetesh Sh, Gardoni P (2022) Mathematical modeling of interdependent infrastructure: an object-oriented approach for generalized network-system analysis. Reliab Eng Syst Saf 217:108042. https://doi.org/10.1016/j.ress.2021.108042 2. Bormotov AN (2020) Development of quality functionals of kinetic processes for the synthesis of composite materials with specified parameters of structure and properties. E3S web of conferences, Volume 224, 02019, “Topical problems of agriculture, civil and environmental engineering, TPACEE 2020”. https://doi.org/10.1051/e3sconf/202022402019 3. Gladkikh V, Korolev E, Husid D, Sukhachev I (2016) Properties of sulfur-extended asphalt concrete. MATEC Web Conf. 86:04024. https://doi.org/10.1051/matecconf/20168604024 4. Wang X et al (2021) Properties of epoxy-resin binders and feasibility of their application in pavement mixtures. Constr Build Mater 295:123531. https://doi.org/10.1016/j.conbuildmat. 2021.123531 5. Bormotov AN et al (2006) Composition for the manufacture of radiation-protective building materials, US Pat. 2319676 RF: IPC C04B28 / 00, G21F1 / 04 / applicant and patentee
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of the Penza state un-tet. arch. and builds. No. 2006102633/03; declared 01/30/2006; publ. 03/20/2008, Bul. No. 28.—4 p Bormotov AN et al (2006) Rapid-hardening radiation-protective construction composites, US Pat. 2319675 RF: IPC C04B28 / 00, G21F1 / 04 / applicant and patentee of the Penza state un-tet. arch. and builds. No. 2006102635/03; declared 01/30/2006; publ. 03/20/2008, Bul. No. 28.—4 p Bormotov AN et al (2021) Exploration of the effect of complex plasticization on the rheological parameters of polymer composites. AIP Conf Proc 2402:020011. https://doi.org/10. 1063/5.0071370 Bellomo N et al (2008) From the mathematical kinetic theory of active particles to multiscale modelling of complex biological systems. Math Comput Model 47(7–8):687–698. https://doi. org/10.1016/j.mcm.2007.06.004 Zaitsev V, Konovalov V (2022) Simulation of particle motion in a cylindrical grain separator. Smart Innov Syst Tech 247:427–436. https://doi.org/10.1007/978-981-16-3844-2_39 Al-Maidi AAH, Himoud MS, Kaliganov AC, Konovalov VV, Rodionov YV (2021) Modelling the quality of the mixture in a continuous paddle mixer. Int J Agric Stat Sci 16:1769–1774. https://doi.org/10.1051/e3sconf/202016408009 Kaliganov A, Konovalov V, Chupshev A, Teryushkov V (2020) Modelling the effect of continuous mixer operating parameters on mixture quality. E3S Web Conf 164:08009. https://doi. org/10.1051/e3sconf/202016408009
Assessment of Heavy Metal Pollution in the Roadside Area of Motorways Margarita Zhuravleva , Soniya Efremova , Vladimir Konovalov , Nikolai Zubrev , Marina Panfilova , and Anna Goryacheva
Abstract The paper presents the distribution of heavy metals in the roadside zone, using the example of sections of Russian railway lines with different intensity of train traffic. The research methodology involved constructing a mathematical model on the basis of experimental data, which makes it possible to estimate the distribution of pollutants over the zone. Mass transfer of dust particles during train passage is represented on the model of snow structures. The functional dependence for construction of the complete curve of contamination of the roadside zone depending on the coordinate of distance from the track axis was obtained. The model of mass transfer of dust particles makes it possible to estimate soil contamination in the roadside zone. It was established that on the basis of correlation of theoretical surface contamination with actual contamination, it is possible to draw a complete contamination curve by sampling points using the functional dependence of mass transfer obtained in the modeling. It was revealed that 70% of dust surface pollution accounts for the right-of-way, providing further maximum contamination with heavy metals of the upper layer of soils. Other 30% are distributed on a sanitary-protective zone and city soils. At the same time it is worth noting that the share of metals of the 1st class is insignificant in this distribution. Keywords Heavy metals · Energy efficiency in transportation · Roadside · Soil pollution modelling · Pollution toxicity
M. Zhuravleva · N. Zubrev Russian University of Transport (MIIT), 22/2, Chasovaya Street, Moscow 125315, Russia S. Efremova · V. Konovalov (B) · A. Goryacheva Penza State Technological University, 1A/11, Proezd Baydukova/Gagarina Street, Penza 440039, Russia e-mail: [email protected] M. Panfilova National Research Moscow State University of Civil Engineering, 26, Yaroslavskoe shosse, Moscow 129337, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_120
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1 Introduction The negative impact of industrial enterprises on the quality of the environment of adjacent areas has been confirmed by numerous studies. The transport system used by modern society for its development contributes just as much [1, 2]. And the infrastructure that facilitates the smooth movement of vehicles [3]. Newly developed infrastructure, however, has a negative impact on wildlife [3, 4] and the environment in general [2, 5]. It is important to consider not only the state of the ecosystem but also the economic costs of both transport and environmental improvement [6]. At the same time, proper reliability of rolling stock and infrastructure, no accidents leading to abnormal situations of introduction of foreign hazardous substances [7] should be ensured [8]. This is largely determined by the design of the roadway and its base [9], especially under difficult conditions [10]. Exhaust gases from transport produce the majority of pollutants (lead, cadmium, zinc), are strong toxins and, when released into the air, are eventually deposited on the surface of soils. Therefore, the ecological environment is subject to a comprehensive study and modelling [11]. Such models are significantly different from those used in engineering [12, 13]. Not only aspects of the direct impact on the environment must be considered, but also the secondary impacts associated with the accumulation of harmful substances [14]. In addition to noise, such impacts not only affect living beings in the environment, but also negatively affect people [15, 16] serving railway vehicles, travelling by them, and staying in their vicinity for some time [17]. The roadside area and its surroundings experience various anthropogenic pressures from passenger and freight traffic [18, 19]. The risk of pollution by heavy metals (HM) is that soils are a special component of the techno-sphere environment from which chemical elements in various forms move into the lithosphere and hydrosphere, as well as into the atmosphere, entering from them into the urban environment, residential areas, where they are absorbed by plants and, therefore, get into the human food chain. In the soils of the technical strip it is heavy metals that contribute to the formation of contamination [18, 19], and petroleum products often ensure the maintenance of the microcosm, creating conditions for the development of occupational diseases in railway workers. At the same time, acid rains (pH = 5.5–6.5) are able to wash out, i.e. convert HM into a mobile soluble form, which migrate from the soil to groundwater and the territories adjacent to these areas. Also in this direction there is an additional migration of dust fraction, where their bulk form is concentrated, as a rule, exceeding the background content. The aim of the work is mathematical modelling of HM content in roadside soils, taking into account the distance from the railway line, in order to estimate the distribution of the proportion of contamination over the area.
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2 Research Methods The research methodology involved constructing a mathematical model based on the experimental data, which describes the experimental data and makes it possible to estimate the distribution of pollutants over the zone. As a result of snow melting and rains, salts and HM oxides, dust-like particles penetrate into the pore space of soils, increasing HM concentration in their upper layer. Ecological assessment of surface distribution of pollutant particles in urban areas is recently carried out by studying temporal layers for the whole thickness of snow that fell on the ground, using the methodology of the All-Russian ScientificResearch Institute of Mineral Resources named after N.M. Fedorovsky. The objects of the study were sections of highways between stops of the Moscow Railway (MZhD) in the city area: № 1—Pokrovskoye—Streshnevo—Leningradskaya (Riga direction, 1.4 km in length); № 2—Sortirovochnaya—Kosino (Kazan direction, 11 km); № 3—Kalitniki-Moskvorechye (Kursk direction, 12 km). This choice was based on the need to assess roadside areas in the Moscow metropolitan area with or without the presence of industrial enterprises. Moreover, the Riga direction is less intensive in terms of train traffic as compared to the Kursk and Kazan directions of the Moscow Railway. A series of soil samples were taken from the object №1 at every 50 m, and from the objects 2 and 3—100 m. The sampling was carried out at a depth of up to 20 cm of the top layer, using the envelope method along the railway line from the side of the 1st track of the main course of each direction at a distance of 3 m from the axis of the outermost track. And at a distance of 50, 100, 150 and 200 m from it, provided the roadside area is unsealed.
3 Experiment and Calculations Data on the level of contamination of soils with heavy metals are presented in Table 1. The estimated parameters are: concentration (C, mg/kg soil) and concentration coefficient (Kc) of each metal (ratio of C to its background concentration Cf). During passing of an electric train the formed area of deposition of particles with initial metal concentration C0 = const can be limited by a parallelepiped with certain dimensions: the width 2a (considering the distribution on both sides of the railway) and the height H. In this case the velocity regime of dust particles sedimentation from collapsing vortex tube can be defined by Stokes’s law by assuming the restrictions— particles and vortices sedimentation velocity should be constant V z = const, then time characteristics for stopping each vortex to form the i-th layer is defined by the
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Table 1 HM content in roadside soils (maximum: concentration C max and concentration coefficient Kc) Objects №1
Parameters Metal content (mg/kg) Ni
Cu
Cr
Co
Pb
Zn
Kc
53
16
10
5
10
19
Cmax
800
800
500
30
400
2000
Background Cf №3 №2
15
50
50
6
40
100
Kc
47–76
15–23
48–74
16–24
3.1–7.6
2.2–9.5
Cmax
1880–3040 750–1150 3840–5920 192–288 124–304 440–1900
Kc
70–120
Cmax
2800–4800 550–1150 1920–2960 288–492 112–248 820–1520
Background Cf
40
11–23 50
24–37 80
24–41 12
2.8–6.2 40
4.1–7.6 200
equation: τi =
(h o + i · h) Vz
(1)
where h0 —the average level of the rail centre point above the roadside surface next to the railway track. The successive attachment of each additional dust layer as they fall, ensures an increase in the HM concentration on the surface of the soil. The number of snow (dust) layers k depends on the height H of the parallelepiped. Each i—layer is in the limit of 1 < i < k. Consequently, if we add up the metal concentrations of each layer C i , assuming that the layer of particles formed above the railway bed in the centre is distributed on both sides of the track axis by h/2, then the total metal contamination concentration on the soil surface depending on the coordinate X is: 1+ξ 1−ξ kC0 + er f 0, 9 √ er f 0, 9 √ C (X ) = 2 2 2
(2)
where C 0 —average initial concentration of metal in the layer of the parallelepiped, k = H/h—the number of layers; ξ = X/a—the relative distance of the selected distance from the axis of the outermost track; λ = 0.5h/ h 0 —ratio of half of the dust particle deposition layer to the level of the rail head above the surface of the roadside adjacent to the road; = (Dt ·h 0 )/(Vz ·a 2 )—a contingent value to simplify the formula (2), where Dt —the turbulent diffusion coefficient. It should be noted that in modeling for dust particles from 0.00001 to 1 mm size the diffusion coefficient (in range 10–20 cm2 /s) and their sedimentation rate (in the range 1·10–3 —1.0 m/s) at dynamic air viscosity 18.1 μPa·s under standard conditions (200 °C) were used. Then, knowing that dust size distribution will be logarithmically normal, the model limits the median dust particle size to about 0.001 mm, in which case the sedimentation rate will be at the level of V z = 5·10−3 m/s.
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An experimental curve was constructed and the area under the curve was integrated using the weighted area method to obtain the average total initial concentration C0 of metals, being limited to coordinates in the range of (−a < X < a). Moreover, to obtain the total relative concentration of metals in the dust in the experimental points of measurements it is necessary to divide the total received value C outside the range (−a < X < a) by the total initial concentration C0, which was determined by summing over all the layers kC0. For the reference point 3 m from the track axis, the relative concentration is 1.15 g/kg of surface dust, and the value ξ1 = X/a is 0.3 at the half-width of the turbulent region, a = 10 m. For a reference point 50 m from the track axis, the relative concentration is 0.52 g/kg and the value ξ2 is five. Applying the values ξ1 and ξ2 in the Eq. (2), an expression for the ratio of concentrations at the selected benchmark points C (ξ1 )/C (ξ2 ) = 2.5 was derived and solved, determining that = 6.2. Figure 1 shows theoretical full curve of distribution of HM concentration (blue line) in surface contamination of roadside area as a function (2) with = 6.2. It correlates with experimentally obtained relative concentrations in deposited dust on the surface of roadside area, which are presented as red points. Analyzing the curve it is necessary to note that the surface HM content on the roadside area decreases and reaches a background value outside the right-of-way and the sanitary protection zone of the railway at coordinate ξ = X/a = 13 (corresponding to 130 m). The area under the whole theoretical curve is equal to the relative metal concentration N /kC0 = 0.5. The surface transport of dust is ensured by the vortex tubes capturing it into the air from the fine fraction of the ballast layer, which contains more than 80% of HM. The dust contains mainly nickel, chrome, copper and cobalt and is redistributed by settling over 130 m of the roadside area of the railway line when the tubes are destroyed. With time and precipitation, the metals move into the soil pores, where they are mainly trapped in the upper layer (20 cm). 0.25
theory experiment
C / kCo
0.2
0.15
0.1
0.05
0 0
2
4
6
8
10
12
14
16
l = Х/a
Fig. 1 Surface distribution of metal in the roadside zone as a function of the relative coordinate of distance from the track axis ξ = X/a
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Fig. 2 Distribution of the relative concentrations of heavy metals CG/C0G in the top layer of roadside soils
Relative HM concentrations calculated for the beginning of braking of electric trains on Pokrovskoe-Streshnevo I track at the mark of 300 m for soil, Cg/kC0G (Fig. 1), are by 10–23% higher than the surface relative concentrations C/kC0 for this mark (Fig. 2). Relative concentration values at distances of 3, 50, 100 and 150 m were determined by dividing their true CG concentrations by the total metal concentration, which was obtained by summing over all C0G sampling points. During multiyear settling of dust layers, metals migrated to this depth when distributed over a band of 150 m. By interpolating the experimental curve obtained, it can be stated that the background HM concentrations in the soils at this depth would already be attributed to a distance of 200 m from the railway. It was revealed that the nature of metal pollution of 0–20 cm layer of soils by relative depth concentrations of CG/C0G (Fig. 2) for the roadside zone with low and high intensity of trains of Riga, Kursk and Kazan directions of MZhD correlates with the nature of the relative surface theoretical distribution of HM (Fig. 1). The curve of pollution distribution is plotted according to the average relative depth concentrations of metals CG/C0G for the line segments of Riga, Kursk and Kazan directions of MZhD and follows the function (2), which indicates the dust mechanism of pollution of the entire roadside area. If wind velocity is significant, a turbulent layer is formed in the near-ground area, as a result the curve (Fig. 2) changes, and it is extremely difficult to solve numerically how these changes will occur. The maximum concentrations are in the soils near the main railway track of all study objects, which follows from the distribution shown in Fig. 2. Nickel is the largest contributor to roadside pollution (Table 1). Chrome, copper and cobalt contribute a little less to the contamination of roadside soils. Chrome, like nickel, is an alloying agent in structures and parts (wheels, rails, brake pads) involved in tribological contacts [18]. Cobalt is an alloying agent in
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cutting parts for hardening, and the main source of copper in soils is the contact network. Thus, concentrated in the surface layers mainly in the technical part of the rightof-way, where railway workers work, HM form a factor of serious danger to their health and development of occupational diseases.
4 Conclusion The considered model of mass transfer of HM-containing dust particles makes it possible to assess soil contamination in the roadside zone. It was found that based on the correlation of theoretical surface contamination with actual contamination at a depth of up to 20 cm, a complete contamination curve can be constructed for sampling points at a distance of 3 and 50 m from the track axis, using the functional dependence of mass transfer obtained during modelling. It has been revealed that 70% of the dust surface contamination captured by whirlwinds from the railway bed and ballast is located exactly on the right-of-way (Fig. 1, 2), providing further maximum contamination of the upper layer of soils with HM. The remaining 30% of pollution is distributed on sanitary-protection zone and urban soils. It should be noted that the share of class 1 metals in this distribution is insignificant.
References 1. Neumann T (2020) Comparative analysis of long-distance transportation with the example of sea and rail transport. Energies 14(6):1689. https://doi.org/10.3390/en14061689 2. Esbulatova AZh, Yuehany S, Voinov KN (2021) Railway transport is the potential source of pollutions. AIP Conf Proc 2389:020003. https://doi.org/10.1063/5.0063940 3. Karlson M, Karlsson CSJ, Mörtberg U, Olofsson B, Balfors B (2016) Design and evaluation of railway corridors based on spatial ecological and geological criteria. Transp Res Part D Transp Environ 46:207–228. https://doi.org/10.1016/j.trd.2016.03.012 4. Short MT, Chase KD, Feeley TE, Kees AM, Wittman JT, Aukema BH (2020) Rail transport as a vector of emerald ash borer. Agric Forest Entomol 22(1):92–97. https://doi.org/10.1111/ afe.12360 5. Keken Z, Kušta T (2017) Railway ecology-experiences and examples in the Czech Republic (Book Chapter). Railway Ecol 247–260. https://doi.org/10.1007/978-3-319-57496-7 6. Tagiltseva JA, Kuzina EL (2017) The railway enterprises activity environmental and economic results planning. In: Proceedings of the 2017 IEEE Russia section young researchers in electrical and electronic engineering conference, ElConRus 7910811, p 1321–1325. https://doi. org/10.1109/EIConRus.2017.7910811 7. Bureika G, Bielousova L, Nozhenko V (2019) Estimation of ecological effectiveness of rail vehicle operation in Eurasian railway corridors. In: Transport means—proceedings of the international conference 2019-October, p 460–465. ISSN 2351-7034. https://transportmeans.ktu. edu/wp-content/uploads/sites/307/2018/02/Transport-means-2019-Part-1.pdf
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8. Blaho P, Peceny L, Gasparik J (2020) Causality of accidents at railway-crossings in Slovakia and its prevention. In: 2020 12th International science-technical conference automotive safety, automotive safety 2020, 9293528. https://doi.org/10.1109/AUTOMOTIVESAFETY47494.2020. 9293528 9. Pinka M, Martin S (2017) Dynamic impact of the rail traffic on geotechnical constructions. Int Multidiscip Sci Geo Conf Surv Geol Min Ecol Manage SGEM 17(12):263–270. https://doi. org/10.5593/sgem2017/12 10. Merzlikin VG, Bolkina GI, Ignatova LN (2018) Effective and ecological technologies of application of structured materials for roadbed in the permafrost regions. Solid State Phenom 284:950–955. https://doi.org/10.4028/www.scientific.net/SSP.284.950 11. Obshta A, Bubela T, Ruda M, Kochan R (2018) The model of environmental assessment of complex landscape systems. Int Multidiscip Sci Geo Conf Surv Geol Min Ecol Manage SGEM 18(3.2):973–980. https://doi.org/10.5593/sgem2018/3.2/S14.125 12. Bormotov A (2020) Development of quality functionals of kinetic processes for the synthesis of composite materials with specified parameters of structure and properties. E3S Web Conf 224(23):020192020. https://doi.org/10.1051/e3sconf/202022402019 13. Bormotov A, Gorokhova A (2022) Modeling the clustering of dispersed systems using dynamic models. Lect Notes Civil Eng 180:61–70. https://doi.org/10.1007/978-3-030-83917-8_6 14. Cao S, Li Y, Li Z, Qian X, Xia L, Xu W (2012) Feasibility of railway washing wastewater disposal by improved CRI. Adv Mater Res 356–360:1947–1950. https://doi.org/10.4028/www. scientific.net/AMR.356-360.1947 15. Schalkwyk MCI, Mindell JS (2018) Current issues in the impacts of transport on health. Br Med Bull 125(1):67–77. https://doi.org/10.1093/bmb/ldx048 16. Hegewald J, Schubert M, Wagner M, Dröge P, Prote U, Swart E, Möhler U, Zeeb H, Seidler A (2017) Breast cancer and exposure to aircraft, road, and railway noise: a case-control study based on health insurance records. Scand J Work Environ Health 43(6):509–518. https://doi. org/10.5271/sjweh.3665 17. Cakir HK, Ovali PK (2008) Analysis of sustainability of the railway transport in the trace subregion under the extent of ecological tourism. J Environ Prot Ecol 9(3):643–651. http:// www.jepe-journal.info/vol-9-no-3 18. Zhuravleva MA, Zubrev NI, Panfilova MI, Efremova SYu (2018) Impact of enterprises on the distribution of heavy metals in the sanitary protection zone of the railway track. Ecol Ind Russia 22(2):52–57. https://doi.org/10.18412/1816-0395-2018-2-52-57 19. Zhuravleva MA, Zubrev NI, Panfilova MI, Novoselova OV, Efremova SYu (2018) Features of heavy metals distribution in soils of railway marshalling yard. Ecol Ind Russia 22(9):23–27. https://doi.org/10.18412/1816-0395-2018-9-23-27
Optimization of the Field Development Mode by the Criterion of Maximizing Economic Efficiency Irina Filimonova , Anastasia Ivershin , and Irina Provornaya
Abstract The article proposes the construction of an optimization mathematical model of the oil production process to assess the economic efficiency of field development. On the basis of the studied methods of geological and economic modeling, two optimization problems are formulated to maximize the economic efficiency of the project and the search for the minimum profitable initial flow rate, and algorithms for their solution are proposed. As a result of the application of the developed algorithm for solving optimization problems, it was possible to find a field development mode that increases the economic efficiency of the project by 28%, as well as to justify the minimum profitable initial flow rate. The author has developed practical recommendations for choosing a field development mode for making decisions when planning and optimizing oil production strategies. Keywords Production forecast · Economic efficiency · Minimum profitable production rate · Field development optimization · Mathematical modeling
1 Introduction In accordance with the Plan for import substitution in the oil and gas engineering industry of the Russian Federation, approved by Order of the Ministry of Industry and Trade of Russia No. 1329 dated April 16, 2019, the share of software imports for visualizing production information and designing subsoil use infrastructure should decrease from 90% in 2018 to 20% by 2024. The high degree of dependence of the industries of the oil and gas complex on foreign software determines the risks of information security and technical equipment. I. Filimonova (B) · A. Ivershin · I. Provornaya Novosibirsk State University, 1 Pirogova Street, 630090 Novosibirsk, Russia e-mail: [email protected] I. Filimonova · I. Provornaya Trofimuk Institute of Petroleum Geology and Geophysics of SB RAS, 3 Koptug Avenue, 630090 Novosibirsk, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_121
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The advantage of foreign software systems is their complexity—decision-making management at different stages of subsoil development based not only on geological or production information, but also on the economic assessment of the effectiveness of measures. At the same time, many of them are “closed” for improving the calculation algorithms, changing the input and output parameters in accordance with the tasks to be solved and the characteristics of the research object. In addition, in most works that consider the optimization of the oil recovery process, estimates are performed for specific objects, which does not allow them to be used as a universal technique that allows one to fully establish the relationship between technological parameters and economic indicators. Therefore, the development of a mathematical model and software for optimizing the oil production process is of high practical importance. The relevance is due to the need to develop an integrated field development model that can take into account many factors affecting economic results, as well as adapt to solving problems arising in the process of optimization and forecasting of production indicators. The use of such an integrated model for managing field development parameters at the design stage will allow the company to automate the process of selecting optimal solutions and carry out long-term planning. Therefore, the aim of the work was to build an optimization mathematical model for predicting the oil production profile of a field based on the criterion of maximizing the economic efficiency of its development, as well as finding the minimum profitable well flow rate as one of the criteria for ranking oil production projects. Geological and economic assessment of oil and gas reserves and resources is an important decision-making tool on the feasibility of investing in subsoil use facilities, as well as justifying the pace and methods of their development. The object of the geological and economic assessment can be oil and gas objects of different scales at different degrees of geological exploration, which determines the choice of methodological approaches to forecasting field and technical and economic development parameters. The basic element for starting economic calculations is forecasting the oil production profile and the dynamics of the production wells commissioning. In the future, many indicators of capital and operating costs are calculated in proportion to these elements. The oil production forecast is formed based on the stock of wells drilled in the field and the flow rate of a single well. There are four main stages of field development: (1) the stage of intensive development of an oil field; (2) the maximum level of oil production (“shelf”); (3) stage of decline in oil production; (4) late, final stage of field development. The stages of a deposit and their duration can be described formally using various functions. The classical approach to describing oil production is “bottom-up”, which involves the superposition of the production curves of individual wells. Sometimes a piecewise construction of a function is implemented that combines different types of models. The main disadvantage of this approach is the need to determine the break point (transition from one function to another).
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The only a priori information about oil production at the field is the value of total reserves. Therefore, it is possible to draw a family of possible oil production curves, all of which would have in common the property of starting at zero, and the area under the curve must be less than or at most equal to the amount of the resource originally present. Models for describing the oil production profile curve implemented in practice for predicting indicators should be based on the geological and economic characteristics of the field, including the mode of its development.
2 Materials and Methods 2.1 Materials The object of the study is a typical license area in the Republic of Sakha (Yakutia), located in close proximity to the main oil pipeline “Eastern Siberia—Pacific Ocean”. Oil resources are localized at the site, and as a result of the exploration program, a field with recoverable reserves of 29.7 million tons is forecasted to be discovered. The planning horizon for the development of the license area includes geological exploration, well drilling, field facilities construction and construction of pipeline infrastructure. Capital investments and operating costs are calculated for each type of work and services using cost standards for analogous fields located in the regions of Eastern Siberia and the Republic of Sakha (Yakutia). It is assumed that the subsoil user pays all taxes and fees stipulated by the Tax Code, and is also exempted from the payment of mineral extraction tax for the first 15 years in accordance with the Tax Code of the Russian Federation. The discount rate for cash flows is adopted at the level of 12%. Calculations are made at constant prices. The oil sales price was calculated using the netback method, taking into account the sale of raw materials to the markets of the Asia–Pacific region through the ESPO trunk pipeline system.
2.2 Methods The basic element for starting economic calculations is forecasting the oil production profile and the dynamics of the commissioning of production wells. In the future, many indicators of capital and operating costs are calculated depending on these elements. The only a priori information on oil production in the field is the total reserves. Therefore, a family of possible oil production curves can be drawn, all of which would all have a common property of starting at zero, and the area under the curve should be less than or at most equal to the amount of initially present resource.
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Models for describing the oil production profile curve implemented in practice for predicting indicators should be based on the geological and economic characteristics of the field, including the mode of its development. The initial well production rate is predicted taking into account the reservoir characteristics of formation and drainage parameters based on the Dupuis formula. The forecast of the current oil production rate of wells is based on the fall function, which can be justified by analogous fields or described by an exponential function: t − T1 , 0 ≤ t ≤ T2 q(t) = q0 exp − k
(1)
where q0 is the initial oil flow rate of the well, q(t) is the current flow rate of the well, T1 is the time of waterless well operation, T2 is the time of well completion, k is the coefficient responsible for the mode and life of the well [1]. The form of the oil production curve from wells q(t) is set by the Skewed-normal production-profile model (SNPP) [1, 2]. The curve has a flat peak, indicating a long plateau, consistent with the actual production dynamics of some oil fields. Sequential wells commissioning by years nt can be described by a piecewise function reflecting the periods of intensive drilling, reaching the production plateau and completion of well drilling: ⎧ α ⎨ At exp(−ϑt), 0 ≤ t ≤ r n t = nconst, r < t ≤r +l ⎩ α At exp(−ϑt), r + l < t ≤ T
(2)
where A is the scaling factor, r is the time to reach constant production, l is the time of constant oil production, ϑ, α are constants. Based on the above formulas, we can calculate the annual level of oil production. Qt =
t
n j qt+1− j
(3)
j=1
Then the amount of oil produced for all years of field development HT is calculated as follows: HT =
T t
n j qt+1− j
(4)
t=1 j=1
After making a forecast of oil production at the field and determining the dynamics of the annually commissioned production wells, the assessment of capital and operating costs, tax deductions is carried out, followed by the calculation of indicators of the economic efficiency of the development of the field. The calculation of capital investments in the development of the field includes the justification of the
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volume, timing and cost of geological exploration, drilling wells, field facilities and the creation of transport infrastructure. Assessment of the economic efficiency of projects is based on the methodology for assessing the effectiveness of investment projects, developed in accordance with the Methodological Recommendations for assessing the effectiveness of investment projects [3]. To assess efficiency, one of the recommended indicators is used as a key indicator—net discounted cash flow (Net Present Value, NPV), the value of which is usually compared with zero. NPV =
T NPt + Dt − Ct t=1
(1 + r)t
(5)
where NPt —cash flow, Dt —depreciation, Ct —capital investments, r—discount rate, T—field development time. Having estimated the initial indicators of the field development project and having received the initial values, we will proceed directly to the optimization tasks. To assess the economic efficiency of the project, it is necessary to formulate a mathematical problem of finding the optimal oil production profile, taking into account the limitation on the number of reserves in a particular field, parameterizing the required number of wells and the method of oil production from a single well. Thus, Task 1 is a search for an oil production regime with the highest NPV, i.e. the most cost effective project. The limitation indicates that the value of production for all years of development of the field HT cannot exceed the potentially recoverable reserves of industrial categories (R). The variables on which the maximization takes place are the parameters k (the coefficient responsible for the mode and life of the well from formula (1) and A (the scaling factor that determines the number of wells according to formula (2). The task of finding the optimal field development mode is represented by the system: ⎧ Max N P V (qt , n t ) ⎪ ⎪ 0≤k ⎪ ⎨ 0≤ A ⎪ ⎪ ⎪ ⎩ HT ≤ R,
(6)
where qt is a flow rate in the period t, n t —well commissioning in the period t, HT is the accumulated oil production for the entire period under review, R is the recoverable oil reserves. The solution for Task 1 makes it possible to subsequently build various scenarios and obtain estimates of the economic results of project implementation, calculate the economic efficiency of field development, depending on changes in various geological, field, economic and other production parameters. As Task 2, consider the search for the minimum cost-effective initial oil production. When predicting the economic efficiency of oil production projects, it often becomes necessary to assess the lower level of marginally profitable oil production
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rates. As the objective function, we take the value q0—the initial oil production rate. The constraint in Task 2 is zero net discounted cash flow (NPV). The formulation of Task 2 with three arguments (q0, k, A) for the objective function NPV does not make sense for research, because has a trivial solution.
minq0 N P V (qt (q0 ), n t ) = 0
(7)
This indicator is analogous to the break-even point, but specific to field development projects. By determining the minimum cost-effective value of the initial flow rate, it is possible to assess the potential economic efficiency of field development in comparison with other projects. This model can be modified by setting the level of the desired profitability of the project, replacing the restriction of NPV equal to zero. Thus, the study posed the problem of finding a global optimum with a nonsmooth function in the constraints, so all the functions of software systems that use differentiation to find local extrema are not applicable for solving problems. Therefore, the Matlab environment with a specialized Global Optimization Toolbox package, which includes the Direct Search method, was chosen to write the program code. The problem is solved using the extended Lagrange function. The solution of Task 2 is the value of the minimum profitable initial flow rate for given parameters of oil production concavity and the number of wells, however, in the original problem of maximizing NPV (Task 1), this parameter is exogenous. Therefore, the following algorithm is proposed: 1. The initial parameters A and k are set to the values that are the solution for Task 1 (for which the NPV value is maximized). 2. Finding the minimum profitable initial flow rate for given values—solutions of the first iteration. 3. Solution for Task 1 with a new exogenously given parameter of the initial flow rate q0 , obtaining new values of k and A. 4. Solving Task 2 with new values of the parameters k and A, obtaining the value of q0 at the second iteration, etc. This algorithm converges—with each new iteration, the value of the maximum NPV of the project decreases and tends to 0, while at the same time the value of the minimum cost-effective q0 decreases, tending to the true value. At the same time, the limitation of cumulative oil production by initial recoverable reserves is not violated.
3 Results and Discussion As a result of the initial calculations, the cumulative volume of oil production in the field for the entire development period amounted to 29.7 million tons with a well stock of 69 wells. To predict the oil production profile, a number of initial parameters
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3000
Wells commissioning, pcs/year
Oil production, thousand tons/year
were set: the initial well flow rate (150 tons/day), the dynamics of their productivity. The initial parameter of the concavity of the oil production curve (k) was 8.5, and the parameter (A), which determines the number of wells, was 29. The solution for Task 1 is the following parameter values: k = 7.2644, A = 53.3128. The optimized value of the number of production wells was 78, which is 13% more than in the original model. There is a deviation of the peak of oil production in the optimization model to the left relative to the original model (Fig. 1). The shift to the left of the oil production curve allows the subsoil user to generate a large amount of income in the first years of field development. This has a positive effect on the formation of net discounted cash flow and leads to an increase in NPV by 28% with an increase in capital investments by only 9% (Table 1). Obtaining a positive economic effect is associated with the intensification of oil production in the optimization model in an earlier period of field operation compared to the original model due to the introduction of a larger number of wells. At the same time, the growth of capital costs affects the performance indicators insignificantly due to their depreciation in subsequent years. This also contributes to the growth of
2500 2000 1500 1000 500
25 20 15 10 5 0
0 1
6
11
16
Original model
21
1
Year
Optimal model
Year 11 Optimal model
6 Original model
a)
b)
Fig. 1 a oil production profile; b well commissioning dynamics
Table 1 Growth indicators of the economic efficiency of the project Indicator
Value in the original model
Value in the optimized model
Change in indicator (%)
Number of wells
69
78
13
Capital investments, million rubles
64 452
70 269
9
Operating costs, million rubles
202 153
197 974
−2
Net profit, million rubles
69 094
72 459
5
NPV, million rubles
5 992
7 643
28
IRR, %
19.5
21.1
8
Profitability index
1.276
1.314
3
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the economic efficiency of the project, mainly due to the consideration of the time factor when assessing the net discounted cash flow. Thus, having solved the optimization Task 1, such an oil production mode is justified, in which NPV increases by 28% compared to the initial value, which indicates a significant increase in the economic efficiency of field development. As a result of solving Task 2, it was obtained that for this field the value of the minimum cost-effective initial flow rate is 93.7 tons/day with the coefficients k equal to 16.54 and A equal to 51.69. The results of solving the optimization problem of finding the optimal profile of oil production at the field, depending on the technical and economic parameters of its development (Task 1), make it possible to give recommendations on the choice of the number of annually commissioned wells and the dynamics of their commissioning, as well as to control the production curve. The authors found that the economic efficiency of the development of the deposit is the higher, the more intensively the deposit is developed in the first years. This is reflected in the change in the oil production dynamics curve—the optimal oil production curve, which provides the maximum NPV, has shifted to the left of the original graph, i.e. left-handed distribution prevails. The main reason for this dependence is the consideration of the time factor when discounting cash flows, as a result of which the income received from the development of a field in the first years of its development contributes more to NPV, compared with income at later stages of operation. However, due to technological limitations and the likelihood of violating the principles of rational subsoil use, it is impossible to strongly shift the peak of the oil production curve to the left and drill a large number of wells in the early years to intensify oil production. A striking example of non-compliance with such a recommendation is the operation of the Samotlor field, when from the first days of putting into development, rapid intensification and forcing the rate of oil production began, which led to the flooding of productive oil reservoirs [4]. In this regard, it became necessary to consolidate the principle of rational subsoil use in the legislation on subsoil use, primarily in the Law of the Russian Federation “On Subsoil”. The principle includes the following requirements: conducting a full geological study to obtain reliable estimates, rational integrated use of subsoil, ensuring the full extraction of minerals, and a number of others [5]. Solving the problem of finding the minimum cost-effective initial flow rate (Task 2) makes it possible to assess the feasibility of field development when the development parameters change [6, 7], as well as to justify the threshold value of well productivity, below which the project becomes unprofitable. If the estimated initial rate is greater than or equal to the calculated minimum economic rate, then the project can be included in the company’s program of work. At the same time, for the obtained value, new recommendations can be given to the mode of operation of wells in the field and their number.
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This indicator allows you to compare several field development projects, evaluate their potential economic efficiency and rank projects in order of priority for implementation [8–10]. The application of the model creates the possibility of making more informed investment decisions and reducing inefficient projects in the company’s portfolio.
4 Conclusion The authors have developed a model and algorithm for poetizing the parameters of the development of an oil field in the framework of geological and economic modeling. Recommendations for choosing a field development mode are of practical importance in planning and optimizing an oil production strategy in order to achieve the maximum economic effect in the context of limited information about the subsoil use object. The main methodological results obtained in the work are as follows: 1. An economic-mathematical model of the field development is proposed, which makes it possible to evaluate the influence of the development technological parameters on the criteria for the economic efficiency of oil production; 2. Two optimization tasks were formulated and formalized: maximizing the economic efficiency of the field development project (NPV) in terms of two parameters—the concavity of the well flow rate and the production well stock, as well as the search for the minimum cost-effective initial well flow rate for the same parameters. The proposed models and algorithms can be used to make managerial decisions taken when planning the development of oil and gas fields. The results obtained serve as a theoretical and methodological basis for the economic and mathematical support of decision-making on the formation of optimal strategies for the development of deposits in conditions of limited information about the object of subsoil use. Acknowledgements The article was prepared with the financial support of the Council for Grants of the President of the Russian Federation in the framework of projects № NSh-1280.2022.2 and SP-3030.2022.1.
References 1. Eder LV, Provornaya IV, Filimonova IV, Kozhevin VD, Komarova AV (2018) World energy market in the conditions of low oil prices, the role of renewable energy sources. Energy Procedia 153:112–117. https://doi.org/10.1016/j.egypro.2018.10.068 2. Wang J, Feng L, Zhao L, Snowden S (2013) China’s natural gas: resources, production and its impacts. Energy Policy 55:690–698. https://doi.org/10.1016/j.enpol.2012.12.034 3. Issatayeva GB, Galizhanuly AA (2021) Methodological approaches to assessing the economic efficiency of investment projects. Editorial Board 4:119
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4. Karpov VP (2013) Oil, politics and scientific and technological progress. ECO 9:51–61 5. Mai A et al (2009) Insights into non-thermal recovery of heavy oil. J Can Pet Technol 48:27–35 6. Moradi A (2020) Cost-effective and safe oil production from existing and near-future oil fields. Master’s thesis, University of South-Eastern Norway 7. Vimolsubsin P, Wasanapradit T, Khunmek T (2020) Cost-effective adaptive inflow technology for sand prevention. an injection well. Abu Dhabi international petroleum exhibition & conference. One Petro 3:107–134 8. Provornaya IV, Filimonova IV, Eder LV, Nemov VY, Zemnukhova EA (2020) Formation of energy policy in Europe, taking into account trends in the global market. Energy Rep 6:599–603. https://doi.org/10.1016/j.egyr.2019.09.032 9. Filimonova IV, Nemov VY, Komarova AV, Mishenin MV, Kozhevin VD (2021) Relationship of renewable energy consumption to economic, environmental and institutional factors in Europe. Energy Rep 7:358–365. https://doi.org/10.1016/j.egyr.2021.07.115 10. Filimonova IV, Provornaya IV, Komarova AV, Zemnukhova EA, Mishenin MV (2020) Influence of economic factors on the environment in countries with different levels of development. Energy Rep 6:27–31. https://doi.org/10.1016/j.egyr.2019.08.013
Models of Recognition Algorithms Based on Construction of Two-Dimensional Logical Classifiers Gulmira Mirzaeva
Abstract The paper considers issues related to the construction of a model of recognition algorithms (MRA) designed to solve the problem of object classification in conditions of interconnectedness of features. A new approach to the construction of the MRA is proposed on the basis of the construction of two-dimensional threshold classifiers (TDTC). The main idea of the proposed MRAs is to form a set of preferred two-dimensional classifiers. A distinctive feature of the proposed model is to determine a suitable set of TDTCs when constructing an extreme recognition algorithm (RA). The purpose of this paper is to develop MRAs based on the construction of a TDTC in the subspace of representative features. In scientific terms, the results of this work together represent a new solution to a scientific problem related to the issues of increasing the reliability of RA based on the construction of two-dimensional threshold classifiers. The practical significance of the results lies in the fact that the developed MRAs can expand the area of their application in the context of the interconnectedness of characteristics. Keywords Pattern recognition · MRA · Reference sets · Basic TDTC · Preferred TDTC
1 Introduction Nowadays, a number of MRAs have been developed and studied in detail [1–3]. These include the following fairly well-known MRAs based on: separating functions (R-models) [4–8]; base of mathematical statistics (S-models) [8–10]; method of potential functions (P-model) [2, 11–15]; the base of mathematical logic (L-model) [1, 3, 16–18]; calculation of estimates (G-model) [1, 19–22].
G. Mirzaeva (B) Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi, Yunusabadsky District, Amir Temur Avenue, 108, Tashkent 100084, Uzbekistan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_122
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Analysis of the literature shows that MRA is mainly intended for solving such problems of pattern recognition, where objects are described in the space of independent features (or the relationship between features is rather weak) [23, 24]. It is known [2, 25–28] that in practice, there are often applied problems of classifying objects described in a high-dimensional feature space. When solving such problems, the assumption about the independence of features is often not fulfilled. The study of available publications on pattern recognition, as well as the accumulated experience in solving a number of applied and model problems, shows that in conditions of violation of this assumption, many known RAs work incorrectly [2, 26–30]. This circumstance dictates that the issues of developing MRAs designed to solve the problems of forecasting and classifying objects in conditions of a large dimension of the feature space remain relevant. The aim of this work is the development of MRAs based on the construction of two-dimensional threshold classifiers (TDTC) and providing a solution to the problems of recognizing objects represented in a high-dimensional feature space.
2 Statement of the Problem In order to formulate the research problem, we introduce the necessary concepts and designations borrowed from [1–3]. Let a set of valid objects M to be given in the feature space X(X = {x1 , . . . , xi , . . . , xn }). Then an arbitrary object S, included in the set M, can be associated with the n-dimensional description vector I(S)(I(S) = (a1 , . . . , ai , . . . , an )). It is assumed that M consists of l subsets (classes) C1 , . . . , C j , . . . , Cl : M=
l
C j , Ci ∩ C j = ∅, i = j, i, j ∈ {1, 2, . . . , l}.
(1)
j=1
In this case, it is assumed that the partition (1) is not completely defined. Only some initial information I0 about the classes is known about the partition C1 , . . . , C j , . . . , Cl . Usually I0 is specified as a set of classified objects. In order to determine I0 , select m objects from the set of valid objects M: S˜ m = {S1 , . . . , Su , . . . , Sm }, Su ∈ M. Let K j —subsets of the selected set S˜ m , consisting of objects belonging to the class C j . K j —subsetsS˜ m , consisting of objects not belonging to the class − C j K j ∩ K j = ∅, j =1, l . Then I0 can be defined as a set of pairs consisting ∼
of Su and α (Su ) [2]:
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∼ ∼ ∼ I0 = S1 , α (S1 ), . . . , Su , α (Su ), . . . , Sm , α (Sm )
(2)
∼ Here α (Su )—zero vector of object of which Su (Su ∈ S˜ m ), each component consists of a predicate value P j (Su ) αu j = P j (Su ) = "Su ∈ C j " : ∼
α (Su ) = (αu1 , . . . , αu j , . . . , αu ). The task is to construct an algorithm A that computes the values of the predicate P j (Su ) according to initial information (2): A S˜ m = βuv m×l , βuv ∈ {0, 1, }. Here βi j is interpreted in the same way as in works [31]: ⎧ ⎨ 1, if object Oi belongs to class Cj ; βij = 0, if object Oi doesn’t belong to class Cj ; ⎩ , if the model has not computed the values of the predicate Pj Oi . It should be noted that a distinctive feature of this problem is that the number of features (n) involved in the description of recognition objects is quite large. Under these conditions, most of the features are interconnected, which complicates the use of many RAs. The development of RA is carried out precisely in conditions of a large dimension of the feature space.
3 Proposed Solution of Method A new approach is proposed for solving the formulated problem of constructing a RA. It should be noted that the proposed approach is a logical continuation of the work of Academician of the RAS Yu. I. Zhuravlev. On the basis of this approach, an MRA has been developed based on the construction of a TDTC. A distinctive feature of the developed MRA is to highlight the preferred two-dimensional classifiers. The assignment of these MRAs includes the following main steps. 1. Formation of support sets of features. Let’s consider all possible subsets X w of the set of features X. Let’s denote the collection of all such subsets by X. The first step in defining the proposed MRA is to specify the set of subsets XA (XA ⊂ X), which Yu. I. Zhuravlev called the system of support sets of MRA A. A distinctive feature of the considered support sets is that the elements of these sets belonging to the same set are strongly connected. Moreover, elements belonging to different sets are “independent” or weakly dependent [28, 29]. 2. Selection of a set of representatives of support sets of features. At the second stage of the task, the set of representatives of the support sets, which were formed
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at the previous stage, is determined. When determining the set of representatives, the following conditions are used: 1) the representatives of the support sets must be strongly connected in their set of features; 2) all elements of the selected set of representatives must be independent. In the process of performing this stage, the dimension of the considered space X is reduced. The generated feature space is denoted by X :X = (xi1 , . . . , xiq , . . . , xin ), where n < n. It should be noted that in space X , each object S corresponds to n -dimensional vector (ai1 , . . . , aiq , . . . , ain ). Sometimes instead of a vector (ai1 , . . . , aiq , . . . , ain ), it is more convenient to use the same vector, but with a simpler index: (a1 , . . . , ai , . . . , an ) [30, 31]. 3. Construction of two-dimensional threshold classifiers. At the third stage of setting the MRA, a TDTC is determined, which classifies objects in a two dimensional subspace of features. Let a set D be defined in the space X consisting of n elements, i.e. D = (D1 , . . . , Dv , . . . , Dn ), where Dv = xv1 , x v2 , xv1 , xv2 ∈ X . Then the difference between objects Su Su = (auv1 , auv2 ) and S S = (av1 , av2 ) in subspace Dv is defined as follows [25]: dv (Su , S) =
2
γvi (auvi − avi )2 .
(3)
i=1
Then, using (3), we introduce the concept of a TDTC given in the two-dimensional subspace Dv : δv (Su , S) =
1, i f dv (Su , S) ≤ εv , 0, i f dv (Su , S) > εv ,
(4)
where εv —parameter of the algorithm used in the construction of the TDTC. 4. Formation of subsets of strongly coupled TDTCs. At the fourth stage of the assignment of the MRA, n “independent” subsets of tightly coupled TDTCs are determined. The formation of subsets of tightly coupled TDTCs is performed based on an assessment of the proximity of the results of the work of the TDTC. The main idea behind the formation of subsets of tightly coupled TDTCs is as follows. The considered set of TDTCs is combined into one subset if they give sufficiently similar classification results within the training sample (TS). Otherwise, they are considered to be different, and they are assigned to different subsets. As a result of this stage, a system of n “independent” subsets of tightly coupled TDTCs is distinguished. 5. Allocation of a set of basic TDTCs. At the fifth stage of the MRA assignment, a set of basic TDTCs is determined. The main idea behind the choice of basic TDTCs is to select a set of the most typical representatives from each subset of strongly connected TDTCs. When it is formed, the following conditions are used: 1) the basic TDTC must be tightly coupled in its subset of TDTC; 2) the results of the work of the basic TDTC should be independent. In the process of performing this stage, a set of basic TDTCs is formed, the power of which is much less than the power of many TDTCs.
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6. Isolation of a set of preferred basic TDTCs. At the sixth stage of the MRA assignment, a set of preferred basic TDTCs is determined within the set of basic TDTCs. Moreover, any basic TDTC from the selected set is the best in a sense. Let’s consider finding the preferred base TDTCs built for each element of the set D. The search for the preferred base TDTCs in Dv (Dv ∈ D, v = 1, n) is based on the estimate: Tv = v /Hv , ⎛ ⎞ δv (Su , S)⎠, Hv = K j × K j ⎝ Su ∈K j S∈K j
⎞⎛ ⎞ l
1 K j K j − 1 ⎠⎝ v = ⎝ δv (Su , S)⎠. 2 j=1 S ∈K ⎛
u
j
S∈K j
The larger the value of Tv , the more preference is given to the v-th basic TDTC built in the subspace Dv . If several features get the same preference, then either one is selected. As a result of this stage, n basic TDTCs are selected, which are preferable. 7. Construction of an integral recognizing operator based on basic TDTCs. At this stage, an integral recognizing operator B is specified in the form of a linear polynomial from the preferred basic TDTC:
B K j, S =
n
γu di K j , S ,
(5)
u=1
where γu —model parameter (u = 1, . . . , n ). 8. Decisive rule. The decisive rule is given as follows [2, 25]:
⎧
⎨ 0, if B K j , S < c1 ; C B K j , S = , if c1 ≤ B K j , S ≤ c2 ;
⎩ 1, if B K j , S > c2 , where c1 , c2 —decisive rule parameters. Thus, we have identified the MRA based on the construction of the TDTC. Any algorithm A from this model is completely determined by specifying a set of parameters ϒ. The set of all RAs from the proposed model will be denoted by A(ϒ, S). The search for the best algorithm is carried out in the parameter space ϒ [31, 32].
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4 Experiments and Results An experimental study of the performance of the proposed MRA was carried out using the example of solving a model problem. The initial data for the model problem are generated in the space of dependent features. The number of classes in this experiment is two. The number of features in the model example is 300. The number of subsets of tightly coupled features is 4. The size of the initial sample is 500 realizations (250 realizations for objects of each class). These objects are divided into two parts: a TS consisting of 450 objects and a control sample (CS) consisting of 50 objects. The following MRAs were considered: classical MRA (P-model) based on potential functions (A1 ), MRA (A2 ) proposed in this work. A comparative analysis of the listed MRAs when solving the considered problem was carried out according to the following criteria: 1) accuracy in recognizing CS objects; 2) the time spent on processing and recognizing TS objects; 3) the time spent on the recognition of CS objects. In order to exclude a successful (or unsuccessful) division of the initial sample into TS and CS, the sliding control method is used [33]: 10 random divisions of the sample into 10 blocks of approximately equal length and equal shares of classes are generated, and each block alternately becomes CS, the rest—TS. The accuracy in the process of recognizing TS objects for A1 is 96.9%, and for A2 − 98.2%. The results of solving the problem under consideration using A1 and A2 in the process of recognizing CS objects are given in Table. 1. Comparison of these results shows (see Table 1) that the proposed MRA (A2 ) provides a higher accuracy of object recognition when solving the considered model problem with respect to the P-model (A1 ). The high accuracy of the recognition results obtained using the proposed MRA (A2 ) when solving the considered model problem is explained by the fact that model A1 does not use those additional procedures for forming subsets of interconnected TDTCs, and the selection of a set of preferred TDTCs that are provided for in model A2 . However, for the A2 model, there is a slight increase in the training time due to the implementation of a number of additional procedures. Table 1 Results of solving the problem using various Ras MRAs
Time (in s)
Accuracy of recognition (in percentage form)
Learning
Recognition
A1
1.21762
0.0109
79.6
A2
3.9798
0.0015
93.6
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5 Conclusions A new approach to the problem of constructing MRA based on TDTC is proposed. The construction of the proposed model is based on: identifying support sets of features; the selection of a set of representatives of the reference sets of features; building a TDTC; allocation of subsets of interrelated TDTCs; highlighting a set of basic TDTCs; highlighting a set of preferred basic TDTCs; construction of an integral recognizing operator based on basic TDTCs. This model is focused on solving the problem of recognizing objects specified in the space of interrelated features. The analysis of the results obtained when solving the model problem showed that the proposed MRA improves the accuracy and significantly reduces the number of computational operations when recognizing CS objects. It can be used to compile various software systems focused on solving the problem of object recognition described in the space of interrelated features. In the process of solving the considered model problem, it was determined that the stages of forming subsets of interconnected TDTCs, namely, the issues of determining the number of these subsets and the set of preferred TDTCs, are important when solving similar problems. Therefore, it is advisable to continue further research in the indicated areas.
References 1. Ablameyko SV et al (2014) Practical algorithms for algebraic and logical correction in precedent-based recognition problems. Comput Math Math Phys 54(12):1915–1928. https:// doi.org/10.1134/S0965542514120033 2. Fazylov ShH, Mirzaev NM, Mirzaev ON (2016) Building of recognition operators in condition of features’ correlations. Radio Electron Comput Sci Control 1:58–63. https://doi.org/10. 15588/1607-3274-2016-1-7 3. Fazilov SK, Khamdamov RK et al (2020) Models of recognition algorithms based on linear threshold functions. J Phys Conf Ser 1441:012138. https://doi.org/10.1088/1742-6596/1441/ 1/012138 4. Shinmura S (2017) New theory of discriminant analysis after R. Fisher. Springer, New York 5. Deisenroth MP, Faisal AA, Ong CS (2020) Mathematics for machine learning. Cambridge University Press, Cambridge 6. Lysenok EI (2010) An approach to the selection of hyperplane for recognition algorithms. Comput Math Math Phys 50(4):1867–1868 7. Zhuravlev YuI, Dyusembaev AE (2019) Construction of a neural network based on a model of algorithms with piecewise linear surfaces and parameters for recognition problems with standard information. Dokl Akad Nauk SSSR 488(1):11–15 8. Theodoridis S, Koutroumbas K (2009) Pattern recognition. Academic Press, p 961 9. Webb AR, Copsey KD (2011) Statistical pattern recognition. John Wiley 10. Fazilov ShKh, Lutfullaev RA et al (2019) Statistical approach to building a model of recognition operators under conditions of high dimensionality of a feature space. J Phys Conf Ser 1333:032017. https://doi.org/10.1088/1742-6596/1333/3/032017 11. Ruxanda G (2009) Supervised pattern recognition with potential functions method. Econom Comput Econom Cybernet Stud Res 2:43–60
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12. Oliveri P (2017) Potential function methods: efficient probabilistic approaches to model complex data distributions. NIR News 28(4):14–15. https://doi.org/10.1177/096033601770 3253 13. Pavlov Y (2019) Potential function method and stochastic approximation, preferences and value evaluation. https://doi.org/10.13140/RG.2.2.21234.76489 14. Sulewski P (2021) Recognizing distributions using method of potential functions. Commun Stat Simul Comput. https://doi.org/10.1080/03610918.2021.1908561 15. Fazilov Sh, Radjabov S, Mirzaev O, Mirzaeva S (2019) Construction of the model of recognition operators in the large dimensional feature space. J Phys Conf Ser 1210:012044. https://doi.org/ 10.1088/1742-6596/1210/1/012044 16. Povkhan I (2020) Logical recognition tree construction on the basis of a step-to-step elementary attribute selection. Radio Electron Comput Sci Control 2:95–105. https://doi.org/10.15588/ 1607-3274-2020-2-10 17. Ryazanov VV (2007) Logical regularities in pattern recognition (parametric approach). Comput Math Math Phys 47(10):1720–1735 18. Kudryavtsev VB, Andreev AE (2010) Test recognition. J Math Sci 169(4):457–480 19. Ignatiev OA (2015) Construction of the correct combination of algorithms for calculating estimates, adjusted by the method of sliding control. Comput Math Math Phys 55(12):2123– 2129 20. D’yakonov AG (2010) Theory of equivalence systems for describing the algebraic closures of a generalized estimation model. Comput Math Math Phys 50(2):369–381 21. Mirzaev NM (2010) About one model of image recognition, In: Proceedings of 1rd RussianPacific conference on computer technology and applications. Institute of Automation and Control Processes Far Eastern Branch of RAS, Vladivostok, pp 394–398 22. Kamilov M, Fazilov S, Mirzaev N, Radjabov S (2012) Estimates calculations algorithms in condition of huge dimensions of features’ space. In: Proceedings 4th international conference «problems of cybernetics and informatics» (PCI 2012, Baku, 2012), I., pp 184–187. https:// doi.org/10.1109/ICPCI.2012.6486314 23. Fazilov SK, Mirzaev NM et al (2019) Model of recognition operators based on the formation of representative objects. Int J Innov Technol Exploring Eng 9(1):4503–4507. https://doi.org/ 10.35940/ijitee.A4592.119119 24. Fazilov S, Mirzaev O, Saliev E, et al (2019) Model of recognition algorithms for objects specified as images. In: Proceedings of the 9th international conference advanced computer information technologies, pp 479–482. https://doi.org/10.1109/ACITT.2019.8779943 25. Fazilov Sh, Mirzaev N, Mirzaeva G, Tashmetov S (2019) Construction of recognition algorithms based on the two-dimensional functions. Commun Comput Inform Sci 1035:474–483. https://doi.org/10.1007/978-981-13-9181-1_42 26. Fazilov Sh, Mirzaev N, Mirzaeva G (2019) Modified recognition algorithms based on the construction of models of elementary transformations. Procedia Comput Sci 150:671–678. https://doi.org/10.1016/j.procs.2019.02.037 27. Lantz B (2019) Machine learning with R: expert techniques for predictive modeling. Packt Publishing Ltd 28. Kamilov M, Fazilov Sh, Mirzaeva G et al (2020) Building a model of recognizing operators based on the definition of basic reference objects. J Phys Conf Ser 1441:012142. https://doi. org/10.1088/1742-6596/1441/1/012142 29. Mirzaev NM, Khaydarova MYu, Mirzaeva GR, Ibragimova SN (2019) Models of recognition operators defined in the space of large dimension attributes. J Phys Conf Ser 1260:102009. https://doi.org/10.1088/1742-6596/1260/10/102009 30. Mirzaev ON, Radjabov SS et al (2022) Recognition algorithms based on the selection of 2D representative pseudo-objects. Commun Comput Inform Sci 1526:186–196. https://doi.org/10. 1007/978-3-030-94141-3_15 31. Fazilov ShKh, Mirzaev NM, Radjabov SS, Mirzaev ON (2018) Determining of parameters in the construction of recognition operators in conditions of features correlations. In: Belim S, Kononov A, Kovalenko Y (eds) Proceedings of the school-seminar on optimization problems and their applications (OPTA-SCL 2018) Omsk, Russia, July 8–14, 2018, pp 118–133
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Contour Extraction When Recognizing Numbers Presented as Images Ergash Saliev , Olimjon Mirzaev , Makhamadaziz Rasulmukhamedov , and Sayyora Ibragimova
Abstract The extraction of the contours of objects in images is an integral function of systems for processing and recognition of numbers presented in the form of images. The paper considers a class of algorithms focused on the formation of a set of pixels separating objects of interest from the background, and which is resistant to certain types of noise. The main idea of the proposed algorithms is the construction and analysis of fuzzy increments in the extraction of contours. The rules for calculating fuzzy increments for the considered pixel in an arbitrary direction are described. The algorithm has been tested and shown to be effective in solving the problems of recognizing car numbers. The practical significance of the obtained results lies in the fact that the proposed algorithms can be used to create a software module for preliminary image processing in image processing and recognition systems. Keywords Contour extraction · Fuzzy increment · Large increment · Small increment · Membership function
1 Introduction Modern information processing systems are characterized by a high level of use of various algorithms and technologies for the intellectualization of data processing
E. Saliev · O. Mirzaev · M. Rasulmukhamedov · S. Ibragimova (B) Research Institute for the Development of Digital Technologies and Artificial Intelligence, 17A, Buz-2, Mirzo Ulugbek, Tashkent 100125, Republic of Uzbekistan e-mail: [email protected] O. Mirzaev Tashkent University of Information Technologies Named After M. Al-Khwarizmi, 108, Amir Temur Street, Tashkent 100200, Republic of Uzbekistan M. Rasulmukhamedov Tashkent State Transport University, 1, Zheleznodorozhnikov Street, 1 Passage, Tashkent 100167, Republic of Uzbekistan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_123
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processes. One of the important directions in the field of intellectualization of information technologies is the processing of information presented in the form of photo and video data, in particular, images of symbols. It is a known fact [1–3] that the tasks associated with the selection of the contours of some object in the images are diverse, and they all have their own characteristics. Therefore, there is no possibility of successfully using a single effective algorithm focused on the selection of contour lines of objects based on digital image processing. At the present time, a number of algorithms have been developed for the extraction of the contour of objects in images [1–5]. The use of some algorithm for the contour extraction is carried out taking into account the peculiarities of the original image, the speed of its processing, and from the point of view of achieving the quality of the required level. It should be noted that most of the objects represented in real images are natural, and for various reasons (for example, due to poor lighting) they do not have precise boundaries separating them from each other. In this regard, the issues of improving the existing ones, the development and research of new algorithms for extracting the contours of objects in images are relevant. The main goal of this work is to develop algorithms for extracting the contours of objects based on the apparatus of the theory of fuzzy sets.
2 Literature Review Edge extraction is an important part of many image recognition systems. The methods used in such recognition systems assume the existence of a set of features extracted from the analysis and processing of the images in question. The extraction of features and the formation of an object image description based on digital image processing is one of the most important stages in solving applied problems using the image recognition and analysis system [6]. Undoubtedly, the most useful information in many problems of extracting features of objects in a digital image is information about the contours of the image (i.e. about the lines passing at the boundaries of homogeneous areas). In addition, the data on the contour lines of images is very useful for recognition systems of objects presented in the form of images [2]. At present, the following three approaches are mainly used to solve the problem of extracting the contours of objects in images [1–5]: 1) An approach based on the calculation of discrete derivatives. All methods that are developed within this approach are based on the calculation of the first-order and second-order derivatives, and consist of two groups. The first group of methods relies on the gradient operators, and the second—on the Laplacian operators. The main idea of gradient methods for extracting contours is to find a set of pixels corresponding to significant (maximum) changes in the discrete differential of the first order. In this case, the definition of the contours of objects is based on the search for the maximum modulus of gradient vectors [4, 7]. The extraction of contours using the Laplacian
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operators is reduced to the definition of a discrete derivative of the second order. The main idea of the methods based on the Laplacian operators is to emphasize the discontinuities in the brightness levels in the image and suppress the area with a weak change in brightness. The main advantage of methods based on the Laplacian operators is that they are very fast. The disadvantages of these procedures are that they are sensitive to image noise. Therefore, contour extraction methods based on the Laplacian operators are almost not used in solving applied problems; 2) An approach based on statistical analysis of the brightness in the vicinity of each pixel of the images. Nowadays, there are a number of edge detection algorithms developed on the basis of statistical methods. The main idea of these algorithms is to determine the contour of objects based on the analysis of the standard deviation of the brightness of neighboring pixels of the considered image element. One of the varieties of this approach is image segmentation, in which homogeneous areas of images are defined. As a result, the original image under consideration is converted into an ideal one. Further, using one of the methods based on the calculation of discrete derivatives, it is possible to extract the contours of the segmented image. When using these methods, large computational resources are required. In this regard, this method is almost not used when extracting the contour of objects in images [7, 8]. 3) An approach based on the use of the apparatus of the theory of fuzzy sets. To date, several methods based on the theory of fuzzy sets are known, with the help of which they try to extract the contours in the image [9–12]. In [9, 11], a method of edge detection is described, based on FIRE (Fuzzy Inference Ruled by Else-action) paradigms, which are relatively immune to noise. It uses the gray level differences in the 3 × 3 neighborhood as a contribution to the fuzzy rules. It was shown in [13] that the use of statistical indicators, such as the range and variance of the intensity window, can be as effective as the use of traditional ones, such as the estimation of gradients. A fuzzy logic-based contour extraction method is proposed, where local features, such as gradient, symmetry, and straightness, are combined to introduce the concepts of “contour” and “angle”. Scharr operator was proposed, which is optimal among the contour extraction operators based on the gradient method. Despite the advances made in the field of digital image processing, there are a number of unsolved problems. These include the problem of adequate mapping of the subject area to a fuzzy system, the choice of models of fuzzy inference and their integration into a single intelligent system. Therefore, the development and improvement of digital image processing methods based on the theory of fuzzy sets are highly relevant.
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3 Formulation of the Problem for the Extraction of Contours It is known that the most informative from the point of view of object recognition in images are not the values of the brightness of objects, but the characteristics of their boundaries—the contours [4, 5, 7]. Because the main information is not in the brightness (or color) of individual areas, but in their contours. The task of extracting the contours is to build an image, namely, the boundaries of objects and outlines of homogeneous areas. The tasks of the extraction of contours require the use of operations performed on the neighboring pixels of the considered image element. Let’s consider a set of valid images 𝕀 given in an RGB color space defined by three basic colors: red (R), green (G), and blue (B). Moreover, each admissible image 𝕀 is represented as a three-dimensional matrix X of size m × n × c (where c is the number of color channels; m and n are the number of rows and the number of columns, respectively): X = xi jk m×n×k , where xi jk —luminance level of element xi j by the base color. The task of extraction the contours of objects in the image is to find a curve on xi j m×n , , which bounds simply connected areas of a certain color (for example, for a grayscale image). m Let’s consider the set of 𝓂 images of car numbers J˜ , given in the form of a two-dimensional matrix 𝕏 of size H × W (where H, W are the numbers of rows and columns, respectively) [4, 6]: 𝕏 = 𝕩i j H ×W ,
(1)
where 𝕩i j —intensity of a given digital image (𝕩i j ∈ [0, 1, 2, . . . , 255]). The task is to construct such a matrix X of size H × W, whose elements are an indicator of contour lines: X = xi j H ×W , where xi j —characterizes the image element located on the i-th row and j-th column: xi j =
1, i f pi xel 𝕩ij is an element o f contour lines; 0, other wise.
In this case, it is required that the elements of the matrix X sufficiently characterize the shapes of objects presented in the form of digital images (1).
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4 Solution Method The main idea of the proposed approach is to form a contour image based on the analysis of fuzzy increments for each pixel. Let’s represent the considered image as a set of points, consisting of W × H elements. The proposed algorithm consists of the following stages: 1. Setting the neighborhood of the central element. For each central element at this stage, a sliding window of size LW xLh is determined (usually LW = 2k W + 1, L H = 2k H +1, k W , k H are natural numbers). The size of this window is set by the parameters k W and k H , , which are determined based on the peculiarities of the problem under consideration for identifying the contours of an object in the image. After determining these parameters of the sliding window, a simple increment is calculated for the considered central element (u, v): (u, v) = J(u + δu , v + δv ) − J(u, v),
(2)
where δu ∈ {−k W , . . . , 0, . . . , k W }, δv ∈ {−k H , . . . , 0, . . . , k H }, |δu | + |δv | = 0, δu , δv —whole numbers. In order to simplify the further presentation, it is assumed that the values of δu and δv satisfy condition: max|δu | = max|δv | = 1. 2. Filtering images in the vicinity of the central element. At this stage, in order to eliminate noise in the image and prepare it for further processing, local methods of image filtering are used, for example, averaging filtering of images is carried out [5, 6]. The main idea of the averaging filter is that the brightness of each central pixel is replaced by the average brightness in its vicinity, i.e. ⎛ I (u, v) = ⎝
kW
kH
⎞ J(u + δu , v + δv )⎠/(2k W + 1)(2k H + 1),
δu =−k W δv =−k H
where k W , k H —sliding window parameters; J(u, v), I (u, v)—original and filtered image. 3. Determining an increment in a specific direction. At this stage, for each central element I (u, v), eight simple increments can be calculated by formula (2) [4]. To determine which is indistinctly large (or indistinctly small) among the calculated increments, it is necessary to construct a set of fuzzy increments. It is known [4, 8] that the set of fuzzy increments is determined using the membership function of its elements. 4. Construction of a membership function for a set of fuzzy increments. At this stage, the membership function of fuzzy increments is provided by: 1) adaptation to noise components when performing fuzzy smoothing; 2) the difference between noise and structural objects of the image. These parameters must have a quality that characterizes human thinking (i.e. the ability to classify) and a quantitative value (i.e.
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the ability to express it in real numbers) for computer processing. Consequently, the reduction of the influence of noise in the image can be carried out on the basis of the theory of fuzzy sets introduced by L. Zadeh. It is known [14] that the construction of a membership function in the form of some simple mathematical function is the most convenient, which simplifies and reduces computing resources. When constructing membership functions, the method of parametric representation is used, which ensures the simplicity of constructing, for example, a triangular membership function [15]. In order to clarify the concept of a fuzzy increment, we introduce the qualitative concept “small” in the framework of the theory of fuzzy sets. This concept corresponds to fuzzy sets of small numbers, i.e. a = −λa , b = 0, c = λa . μ𝓁 (x, λa ) =
d, at x[−λa , . . . , λa ]; 0, at x ∈ / [−λa , . . . , λa ]
(3)
Here d = (1 − |x|)/λa , where λa (λa > 0)—an adaptation parameter that characterizes a specific set of small numbers. The membership function of the qualitative concept of a large increment can be determined based on formula (3): μ𝒷 (x) = 1 − μ𝓁 (x, λa ). After building the membership function of a fuzzy increment, it becomes possible to calculate the values of fuzzy increments in all directions. 5. Calculation of values of fuzzy increments. At this stage, a set of fuzzy rules is set. It is known [4, 8, 10] that fuzzy rules are constructed from membership functions of input and output images. These rules define the relationship between the premise and the conclusion expressed in the form “if… then…”. Phased inputs and outputs make it much easier to isolate rules and generalize them. Building good rules depends on the amount and quality of the imaging expert’s knowledge. However, the description of expert knowledge using fuzzy set theory is not formalized. Therefore, the choice, for example, of the form and parameter of the membership function is carried out arbitrarily. When calculating the fuzzy increment value for an arbitrary central element, corresponding fuzzy rules are used in each direction. After calculating the values of the fuzzy increments, it is possible to select a set of pixels corresponding to the contour lines. 6. Making a decision based on the analysis of the values of fuzzy increments. At this stage, a decision is made on the existence of an element (pixel) within the analyzed sliding window belonging to the contour line. In this case, the decision is made on the basis of a comparison of the estimates characterizing the fuzzy increment calculated in all directions.
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Thus, we have considered the main stages of specifying algorithms for extracting the contours of objects in images, built on the basis of the theory of fuzzy sets. These algorithms are designed to extract contour lines in images, and each of these algorithms is specified by a set of parameters π˜ (π˜ = (k W , k H , λa , {i }, r1 , r2 )). Based on the change (determination) of the values of these parameters, it is possible to distinguish the contour lines of the images in conditions of various noise and interference. In order to study the performance of the developed algorithms for identifying the contours of objects in images, an experimental study was carried out using the example of solving the problem of recognizing car license plates presented in the form of images.
5 Experiments In recent years, in order to improve the operational management of transportation, intelligent transport systems (ITS) have been created [16], which make it possible to ensure the stability, rhythm and sustainability of the transportation process by rail. When creating an ITS, an important place is occupied by issues related to the recognition of car numbers from their video images [17–19]. In addition, the use of ITS in solving various applied problems is constantly expanding. To assess the performance of the considered model, experimental studies were carried out when solving the problem of recognizing car license plates. A set of 300 images of car license plates is given as the initial data. These images were divided into 2 parts: training (200 images) and control sample (200 images). In the training sample for each class (figure), there were approximately 20 images. The issues of preliminary processing of images are considered in works [20, 21]. The feature extraction of digits presented in the form of contour images is carried out similarly to that considered in [22, 23]. Recognition of numbers in an image is carried out using a model of recognition algorithms based on radial functions [24].
6 Experimental Research Results Note that the proposed algorithms differ from others in that they have the ability to adapt taking into account a priori information about different images. As noted above, the main task of the experimental study is to extract the contours of objects in images when recognizing numbers presented in the form of images. When solving this problem, the contour lines of the images are first selected, and then the features are formed, after which the recognition algorithm is applied. It should be noted that the contour lines were extracted by the proposed algorithm and an algorithm based on the Canny method [25]. Based on the analysis of the contour lines, a set of features was determined for each digit. An experimental study to assess the performance of
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Table 1 Comparison of the results of character recognition in the test sample. The extraction of the contours of objects in the images was carried out using the Canny method and the proposed algorithm Main characteristics of the experimental study
Volume
Number of images
100
Mes. unit units
Number of characters in images
800
characters
Number of incorrectly identified characters in images processed by the Canny method,
126
characters
Number of incorrectly recognized characters in images processed by the proposed method
57
characters
Number of errors fixed
69
characters
the proposed contour extraction algorithm was tested as follows. First, the tasks are solved according to the first scheme: 1) preliminary image processing; 2) the selection of contours using the proposed algorithm; 3) extracting the signs of numbers on contour images; 4) recognition of numbers in images. Further, the same tasks are solved according to the second scheme: 1, 3 and 4 stages of image processing do not differ; 2) selection of contours using the Canny method. The recognition results for the numbers described by these features are shown in Table 1. The obtained results show (see Table 1) that the recognition accuracy of car numbers according to the first scheme is 92.88%, and according to the first scheme, it is 84.25%. Analysis of these results shows that the results of their recognition after extracting the contour lines by the proposed algorithm are higher (8% higher) than the results of their recognition after extracting the contour lines by the Canny method.
7 Discussion of the Results of Experimental Studies It is a known fact [5] that one of the most common and very effective methods for extracting the contours of objects presented in the form of images is the Canny method. Therefore, for a comparative assessment of the proposed algorithm when solving the problem of extracting contour lines, the Canny method was used. The results from the experimental study show the following: 1) the proposed algorithms for extracting the contours of objects in images are not an alternative to the existing algorithms, but only supplement them; 2) when the image under consideration is close to the ideal image, traditional algorithms should be used; 3) the proposed algorithms should be used only in the presence of significant noise in the image under consideration. The main result of the research carried out within the framework of this paper is the proposed approach based on the theory of fuzzy sets, on the basis of which algorithms for extracting contour lines in the image were developed. In these algorithms, it is possible to adapt to various noise in the images by entering a number of parameters.
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8 Conclusion The existing methods and algorithms for contour lines are mainly aimed at separating the contour lines of an ideal image. However, the use of these methods and algorithms when processing real images may not give the desired result. The paper proposes a specific approach that takes into account the features of the contour lines, which extract the outlines of numbers in this image. Based on this approach, algorithms have been developed for extracting the contour lines of numbers. These algorithms are based on the concept of fuzzy set theory, the main difference from other contour extraction algorithms is that they can adapt to various noise in the image using a number of parameters. To determine the performance of the proposed algorithm, an experimental study was carried out to extract the contour lines of the images of numbers. The results of experimental studies have shown that the proposed algorithm for extracting contour lines makes it possible to improve the accuracy when recognizing contour images of numbers. The proposed algorithm can be used to create software systems for preliminary image processing when recognizing objects presented in the form of images.
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13. Belim SV, Kutlunin PE (2015) Boundary extraction in images using a clustering algorithm. Comput Opt 39(1):119–124. https://doi.org/10.18287/0134-2452-2015-39-1-119-124 14. Perez-Hernandez AK et al (2013) Edge detection algorithm based on fuzzy logic theory for a local vision system of Robocup Humanoid League. TecnoLógicas 30:33–50 15. Kar R, Sur SN (2016) Object detection for collision avoidance in ITS. Eur J Adv Eng Technol 3(5):29–35 16. Yalov AL (2014) Recognition of car numbers using a neural network. Control processes and stability 1(1):424–427 17. Vygolov OV et al (2013) Algorithms for automatic detection and reading of numbers of railway cars and tanks. Herald Comput Inf Techol 10(112):13–19 18. Lisanti G, Karaman S, Pezzatini D, Del Bimbo A (2017) A multi-camera image processing and visualization system for train safety assessment. Multimedia Tools Appl 13(2):1583–1604. https://doi.org/10.1007/s11042-017-4351-4 19. Tukhtasinov MT, Mirzaev N, Narzulloev OM (2017) Face recognition on the base of local directional patterns. In: Proceedings of the conference dynamics of systems, mechanisms and machines (Dynamics 2016), 7819101. https://doi.org/10.1109/Dynamics.2016.7819101 20. Khamdamov RKh, Saliev EA, Mirzaev NM, Ibragimova SN (2019) Segmentation of colour image using fuzzy sets concept. J Phys Conf Ser 1333(3):032035. https://doi.org/10.1088/ 1742-6596/1333/3/032035 21. Mirzaev N, Saliev E (2018) Feature extraction model in systems of diagnostics of plant diseases by the leaf images. In: Instrumental engineering, electronics and telecommunications—2017. Proceedings of the International forum. Publishing House of Kalashnikov ISTU, Izhevsk, pp 20–27 22. Mirzaev NM (2010) About one model of image recognition. In: Proceedings of the 1st RussianPacific Conference on Computer Technology and Applications. Institute of Automation and Control Processes Far Eastern Branch of RAS, Vladivostok, pp 394–398 23. Fazilov S, Mirzaev O, Saliev E et al (2019) Model of recognition algorithms for objects specified as images. In: Proceedings of the 9th international conference advanced computer information technologies (ACIT 2019, Ceske Budejovice, Czech Republic, June 5–7, 2019). https://doi. org/10.1109/ACITT.2019.8779943 24. Mirzaev N, Saliev E (2018) Recognition algorithms based on radial functions. In: Proceedings of the 3nd Russian-Pacific conference on computer technology and applications, 8482213. https://doi.org/10.1109/RPC.2018.8482213 25. Rahman MA, Amin MFI, Hamada M (2020) Edge detection technique by histogram processing with canny edge detector. In: Proceedings of the 3rd IEEE international conference on knowledge innovation and invention (Kaohsiung, Taiwan), pp 128–131 https://doi.org/10.1109/ICK II50300.2020.9318922
The Method of the Real-Time Control of the Erect Inverted Pendulum Djavanshir Gadjiev , Aligadzhi Rustanov , and Ivan Kochetkov
Abstract The fuzzy logic controller and the fuzzification process was presented in this article by investigation to further develop the methods of the real-time control erect pendulum. The movement of the inverted pendulum has been described by the differential equations of the motion of the mass of the pendulum based on Newton’s Law. The cart motion strategy of the swinged-up pendulum was shown as the dependent on the work of the pendulum with the certain acceleration. The basic strategy of the motion of the pendulum is consisted of the energy consistently applied to the pendulum. The rules of the motion of the pendulum are utilized to generate the fuzzy controller. Two inputs of the fuzzy controller such as pendulum angle and pendulum angular velocity generated the output membership functions, which consists of the several fuzzy sets. The fuzzy rule base of the motion of the pendulum was developed to describe the relationship between the input variables and the output membership function. Keywords Inverted pendulum · Fuzzy logic controller · Deffuzification · Mamdani method
1 Fuzzy Control of the Erect Pendulum Method of fuzzy control is utilized in the example of the erect pendulum. The method of real-time control of the erect pendulum is developed by using fuzzy logic controller. The basic structure of the fuzzy controller consists of the following process: fuzzification, inference, defuzzification, process. The concept of the fuzzy controller is based on the cognitive task, which is performed by a human “control expert”. D. Gadjiev Florida South Western College, Lee Campus, Fort Myers, FL 33919, USA A. Rustanov (B) · I. Kochetkov Moscow State University of Civil Engineering, 26 Yaroslavskoye Shosse, 109377 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_124
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Fig. 1 Inverted pendulum movement
The Fig. 1 illustrates the basic structure the of the inverted pendulum system. The inverted pendulum comprised of the bar length of the inverted pendulum l, mass of the vehicle m v , mass of the inverted pendulum m p , gravity acceleration g, the angle β of the vertical position passing through the point P on the horizontal axis. The distance from the reference point on the horizontal axis is represented by angle β and x—coordinate. The inverted pendulum non-linear model is developed by using the Newton’s laws. The system of the equations [1–15] of the inverted pendulum is given at the center of gravity by x g = x + lsinβ,
(1)
yg = lcosβ.
(2)
Using Newton’s second law by moving in horizontal direction generated the differential equations: mv
d2x d2 y + m p 2 = F, 2 dt dt
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If we consider, the following derivatives such as: d sinβ = (cosβ)β , dt d2 sinβ = −(sinβ)β + (cosβ)β , dt 2 d cosβ = −(sinβ)β , dt d2 cosβ = −(cosβ)β − (sinβ)β , dt 2 Then, m v + m p x − m p l(sinβ)β + m p l(cosβ)β = F.
(3)
When the pendulum is moving, then differential equation is obtained to describe the movement of the mass of the pendulum around the point P: mp
d2 y d2x lcosβ − m + 2 (lsinβ) = m p glsinβ. p dt 2 dt
The Fuzzy logic controller block diagram is presented in Fig. 2. Based on Fig. 2 we can describe the general structure of the controller block as fuzzification, fuzzy inference, flushing and knowledge base [5, 16, 17].
Fig. 2 General structure of the controller block
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The fuzzification unit of the controller is converting the received input information from a system to the symbolic data of the linguistic qualifiers. The fuzzy inference unit is processing fuzzy values to produce the fuzzy outputs based on the base of the rules. The frequently used fuzzy inference methods are the Mamdani methods [3]. The defuzzification unit is based on the obtained fuzzy knowledge from the decision-making unit turbidity. The defuzzification unit is obtaining the realistic actual value of the solution to be used in real life practice. The defuzzification process is the process of converting fuzzy data into certain realistic results. The knowledge base is represented by the table of the data, which are collected from the system. The rule-based connections between inputs and outputs are generated from the expert knowledge. During defuzzification process the rule-based connections are modified into symbolic parameters. The designed controllers are used in the following linguistic variables such NB (negative big), NM (negative medium), NS (Negative small), Z (zero), PS (positive small), PM (Positive medium), PB (positive big) [3]. There is presented below the Tables of rules to describe the location of the vehicle and angle control of the inverted pendulum (Table 1). These rules are used all linguistic variables in the form as it is, e.g. such as: If the input E (error) is NB and DE (error change) is NB, then output membership function (OF) is NB. The numerical magnitude at the exit signal of the defuzzification process is used as the converted fuzzy information to produce certain results [3]. The geometric representation of the membership function to describe the relation between each input and output is either in triangular, sigmoid or Gaussian types or bell functions. Table 1. Tables of rules to describe the location of the vehicle and angle control of the inverted pendulum DE OF
NB
NM
NS
Z
PS
PM
PB
NB
NB
NB
NB
NB
NB
NM
Z
NM
NB
NB
NB
NM
NM
NS
PS
NS
NB
NB
NM
NS
Z
PS
PB
Z
NB
NM
NS
Z
PS
PM
PB
PS
NB
NS
Z
PS
PS
PB
PB
PM
NM
Z
PS
PM
PB
PB
PB
PL
Z
PS
PM
PB
PB
PB
PB
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2 Swing-Up Routine of the Inverted Pendulum with the Given Acceleration The pendulum’s swing up routine is described by the cart motion with the given acceleration. The cart motion strategy is based on the energy of the motion of the cart, which is pumped in into the pendulum. The problem appeared here is to find a strategy to add on to the optimal energy, which pendulum received. This strategy is supported by the Newtonian rule, which is illustrated in Fig. 1. The swing-up routine analysis is used the following notations such as vector notation(s) and regular scalar. The vector notation is used to describe the vector parameters in Newton Law, while regular notation represents the scalar parameters. − → According to the Newton Law the forces, which acted on the pendulum are F p — − → the force pumped in the pendulum, F g —gravitational force acted on the pendulum: − → − → − → F p = F p (sinβ i + cosβ j ); − → − → F g = −mg j . By using Newton Law, the force acted on the pendulum can be described as it is: F p = m p (sinβx + lβ + gcosβ). The total work W can be found as it is: − → W = F p ∂ x = F p sinβ∂ x = m p (sin 2 βx sinβlβ + gsinβcosβ)∂ x. The work effect is given by the term sin 2 βx . This term describes the acceleration employed on the pendulum at any angle β. The graphical representation of this sine function is given at Fig. 3. The Fig. 3 for the angle of the swing of the pendulum around ±90°. To maximize the work done on the pendulum, then the cart must be accelerated, when angle varies between −90° < β < +90°. The deceleration occurs when angle is near 0°. The swing-up strategy and acceleration/deceleration is shown in Fig. 4. The Fig. 4 of the acceleration and deceleration of the swing up strategy. According to Fig. 4, the cart is accelerated, when the pendulum is positioned in region I. The region II is the deceleration region. The region III shows the position of the pendulum when it reaches the maximum point. The process is repeated until the pendulum is on its inverted position. The region II is the hanging downward position of the pendulum, which is the rest condition of the pendulum. The swing-up strategy is based on the swing-up controller, which comprises of the series of the fast cart movements to produce the pendulum swinging. To bring the pendulum to its inverted
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Fig. 3 Work effect of sin 2 β
Fig. 4 Swing strategy of the acceleration and deceleration
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position with low angular velocity, the amplitude of the cart needs to get reduced gradually during higher swings of the pendulum. This process of the pendulum swing-up is applicable to generate a fuzzy controller. To generate a fuzzy controller, there are two input variables used such as pendulum angle β and pendulum angle velocity β . The trajectory length is extended enough to apply fuzzy controller strategy. There are considered the following fuzzy subsets such as: NL (negative large), NB (negative big), SSN (start swing negative), Z (zero), SSP (start swing positive), PB (positive big), PL (positive large). These subsets are utilized to describe the error of the pendulum angle. There are three subsets, which can be utilized for the error of pendulum velocity. The Fig. 5 represents the illustration of the inputs of the membership function, which is defined by the rule base. The Fig. 5 illustrates membership function for the pendulum angle and angle velocity. The rule base is represented in Table 2. The output of the membership function can be described by the following fuzzy subsets such as NEB (negative extremely big), NVB (negative very big), NB (negative big), N (negative), Z (zero), P (positive), PVB (positive very big), PEB (positive extremely big). The pendulum’s swing-up from downward to inverted position is in about 10 s and the number of fluctuations and swing-up time can be changed (reduced or increased) by changing the number of the amplitude of the membership function.
Fig. 5 Membership function of angle β and velocity angle β
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Table 2. Fuzzy rule base of the swing up of the pendulum eβ eβ
NL
NB
SSN
Z
NG ZS PS
SSP
PB
PL
P
Z
PB
P NB
Z
N
As we mentioned for the set of the inputs, we may use three linguistic terms such as “negative”, “approximately zero”, and “positive”. There are existed two types of the partitioning of the input sets: Crude partitioning is occurred between the input intervals of the negative and positive values of the linguistic terms. Refined partitioning: The refined partitioning of the input intervals is occurred between negative large values and positive large values of the interval of X. There are existing the range of the values of the inputs of the fuzzy control of an erect pendulum based on Mamdani control concept [3–8]. The concept is based on the model of the cognitive task, which is generated by a human “control expert”. The control expert is generating a knowledge based in the form of the linguistic rules, which include the following rule(s): (1) questioning of the expert, (2) observation of the expert responses and behavior. The linguistic rules comprise of (a) premises to specify the values for the quantities to be measured, (b) a conclusion, which is based on an appropriate control value. The measuring quantities of values of x1 , . . . , xm correspond to the control quantities of y1 , . . . , ym , which are the corresponding linguistic terms such as zero, positive small and etc. For the set of measuring quantities of x1 , . . . , xm ∈ X there are three linguistic terms such as negative, approximately zero and positive are assigned there for the purpose of the mathematical modeling, when the fuzzy set is related to every one of these linguistic terms. The range of values of the measuring quantities: Variation of the values of the angles: −90◦ ≤ x1 ≤ 90◦ , x1 = [−90◦ , 90◦ ]. Variation of the values of the angular velocity: −
45◦ ≤ β ≤ 45◦ , x2 = −45◦ , 45◦ . sec
Variation of the values of the force: −10N ≤ F ≤ 10N , ym = [−10, 10]. The following basic rules are consisting of the consequent premises such as: NL—negative large, NM—negative moderate, NS—negative small, AZ— approximately zero, PS—positive small, PM—positive moderate, PL—positive large.
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Table 3 The basic rules NL
NM
PS
PM
PL
AZ
PS
PM
PL
PS
NS
PS
PM
NM
Pl
NL
NL
NS
AZ
PS
PL
NS
PS
NS
NM
PM
NS
NM
AZ
NL
NM
PM
NS
The basic rules are represented by the given below Table 3, which contains 19 rules: There are the possible starting values may be chosen, e.g. such: Angle β = 42◦ . ◦ . Angular velocity β = − 1.35 sec There are basic rules applied and consecutive selected rules are chosen there, e.g. such as: Rule 1: If angle is small, and angular velocity is approximately zero, then the values of a force is positive small; or, Rule 2: If angle is positive moderate and angular velocity is approximately zero, then a value of force is positive moderate. If we used the rule 1, then the premise is satisfied at minimum measuring quan tities: = min φ 1 F (β), φ 1 F β = {0.3, 0.7} = 0.3, and the consequence is derived for the output values of the membership function:
out put R φ42,−1.351 (y)
=
⎧ ⎨
f or 0 ≤ y ≤ 1, f or 1 ≤ y ≤ 3, ⎩ 2 − 15 y f or 3 ≤ y ≤ 5, or 0, other wise. 1 y 5 1 5
For the rule 2 there is min{0, 5, 0.8} = 0.5 and the premise is satisfied at: η = min{φ 2 F (β), φ 2 F β . The consequence of the rule 2 is the following:
φ
out put R2
42,−1.35 (y) =
⎧ ⎨
− 1 f or 2 ≤ y ≤ 4, f or 4 ≤ y ≤ 7, ⎩ 1 2.5 − 5 y f or 7 ≤ y ≤ 8, or 0, other wise. 1 y 5
2 5
For the rest of the remaining 17 rules the degree of truth is zero and the truth zero premise is reached out, which is yielding fuzzy sets equivalent to zero.
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There is the following approach exists for using the evaluation of both rule decision logic there: The evaluation of the generated fuzzy sets is composed by the criterion of the forming maximum union by using MAX–MIN composite operators. Hence, the decision logic yields to:
out put φx1 ,...,xm : Y → [0, 1]; y → max q∈[1,...,n] min φ (1) j1,q (x1 ), . . . , φ (m) j1,q (xm ), φ jq (y) .
When the maximum is formed, then the fuzzy set is described by: ⎧1 1 f or 0 ≤ y ≤ 3.0, ⎨ 5 y f or 0 ≤ y ≤ 1, 5 out put 1 1 φ = (y) y − 1 f or 3 ≤ y ≤ 4, f or 4 ≤ y ≤ 6.5, 42,−1.35 5 ⎩5 1 2.5 − 5 y f or 6.5 ≤ y ≤ 7.5, 0, other wise. All the rest of the rules do not to contribute greatly to yield the fuzzy sets since the fuzzy sets are zero. It is worthwhile to note that the decision logic yielded a fuzzy set. The decision logic generates the transformation that assigns a fuzzy set with output membership function φ out put x1 ,...,xm to any m-tuple (x1 , . . . , xm ) ∈ X 1 ⊗ · · · ⊗ X m of the measured values. If we apply defuzzification, then the defuzzification meant that the control value is measured. The center of gravity yields to: F = 3.55. The maximum criterion method yields to: F = 4.95. Here exists general approach for the trajectory, which runs, when the endpoint lies in the center. There are existed the following rules for the defuzzification output: 1. The defuzzification output generates the iteration process that yields to the control quantity equal to zero; 2. Stability check is performed; 3. The fuzzy control is based on a) knowledge based definition of the set of characteristics, b) designed parameters, c) choice of fuzzy sets, d) partitions, e) conclusion, f) defuzzification, g) the structure of the set is approximated with required accuracy for every non-linearity of the characteristics.
3 Conclusions There was shown the inverted pendulum movement in the article here, which is a dynamic system, described by the non-linear mathematical model. The feeble balance between the pendulum angle and the vehicle position is controlled by the input applied to the vehicle, which is dynamically unstable and described by the differential equations based on Newton Laws. The complication of the unstable
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dynamic non-linear system is increased when we perform the control application. The fuzzy logic controller used here in the article. The fuzzy logic controller block is comprised of the knowledge base. The knowledge base is consisting of the data base, which followed by the rule base. The initial data is transformed by fuzzification process next. The fuzzification process is fuzzifying the initial data, which is considered as the input of the system. The fuzzification is followed by an inference, and then a defuzzification process, which is considered as an output of a system. The fuzzification unit performs the conversion of the received input data to the symbolic values of the linguistic qualifiers. There was presented a fuzzy inference unit in the article here, which is a fuzzification unit to produce fuzzy results by implementing a rule base. The frequently used fuzzy inference method is the Mamdani methods, which was utilized in the article here. The defuzzification unit is providing the fuzzy knowledge from the decisionmaking unit turbidity to obtain the actual values to be used in practice. The defuzzification is the process to convert the fuzzy data to certain practical results. There was presented the knowledge base consisting of the data in the form of the table presentation. The data describing a system is collected to be further inspected. The relations between the input and output is given by the rule base. There were generated the fuzzy control rules in the article here, which are usually derived from the expert knowledge. The input and output values are transformed into symbolic parameters in the fuzzy logic control in the defuzzification process. The choice of the membership function is led to describe the rule base between input and output. The membership function is utilized here in the article varies by the type from the triangular membership function form to trapezoidal, sinusoidal, sigmoid and Cauchy type.
References 1. Gadjiev D, Kochetkov I, Rustanov A (2019) The convex fuzzy sets and their properties with application to the modeling with fuzzy convex membership functions. In: Murgul V, Pukhkal V (eds.) International scientific conference energy management of municipal facilities and sustainable energy technologies EMMFT 2019. EMMFT 2019. Advances in intelligent systems and computing, vol 1259. Springer, Cham. https://doi.org/10.1007/978-3-030-57453-6_24 2. Gadjiev D, Kochetkov I, Rustanov A (2019) Aggregation of the fuzzy logic sets in terms of the functions of the triangular norm and triangular co-norm. In: IOP Conference series: earth and environmental science, vol 403, XII International scientific conference on agricultural machinery industry, Don State Technical University, Russian Federation, 10–13 September 2019 3. Gani A, Bas Z, Acikgoz H, Kececigoglu OF (2014) Control of nonlinear dynamic inverted pendulum system using fuzzy logic-based control methods. Int J Eng Res Technol 3(9):1400– 1404 4. Ogata K (1990) Modern control engineering. Prentice Hall 5. Kizir S, Bingul Z, Oysu C (2010) Fuzzy control of a real-time inverted pendulum system. J Intell Fuzzy Syst 21:121–133
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6. Bugeja M (2003) Non-linear swing up and stabilizing control of an inverted pendulum system. In: EUROCON Ljubljana, Slovenia 7. Muskinja N, Tovornik B (2006) Swinging up and stabilization of a real inverted pendulum. IEEE Trans Ind Electron 53(2):631–639 8. Stimac AK (1999) Standup and stabilization of the inverted pendulum. Massachusetts Institute of Technology 9. Zhong W, Rock H (2001) Energy and passivity based control of the double inverted pendulum on a cart. In: IEEE conference on control applications 10. Krishen J, Becerra VM (2006) Efficient fuzzy control of a rotary inverted pendulum based on LQR mapping. In: IEEE international symposium on intelligent control, pp 2701–2706. Germany 11. Craig K, Awtar S (2001) Inverted pendulum systems: rotary and arm driven a mechatronic system design case study. Mechatron J 12:357–370 12. Mirza A (2000) Inverted pendulum. AMSE J 55(3,4) France 13. Zadeh LA (1965) Fuzzy sets. Inform Control J 8:338–353 14. Passino KM, Yurkovich S (1998) Fuzzy control. Prentice Hall 15. Yasunobu S, Mori M (1997) Swing up fuzzy controller for an inverted pendulum based on a human control strategy. In: Proceedings of the sixth IEEE international conference on Intelligent Processing Systems, ICIPS 1997, pp 185–189 16. Magana ME, Holzapfel F (1998) Fuzzy-logic control of an inverted pendulum with vision feedback. IEEE Trans Educ 41(2):165–170 17. Bingul Z, Cook GE, Strauss AM (2000) Application of fuzzy logic to spatial thermal control in fusion welding. IEEE Trans Ind Appl 36(6):1523–1530
The Method of Mutual Use of the Labour Intensity of Finishing Works of Different Countries Rustam Fatullaev
and Tembot Bidov
Abstract In the era of globalization, information about the latest technologies developed at one end of the world instantly scatters across the globe, but the speed of decision-making on integration and practical application is faced with the problem of the lack of mechanisms for adapting technologies to the conditions of the place in which it is planned to use. Exploring the potential for cross-country use of regulations requires many factors to be taken into account. To calculate the final result, a sequential study of the individual groups of elements is required. The task of this research is to analyse time planning of finishing works as a part of construction system in accordance with the fundamental management tools based on Russian and Spanish standard databases, in order to research the possibility of borrowing some technological processes. Keywords Organizational and technological modeling · Standardization in construction · TSN-2001 · BEDEC · Borrowing of building codes · Regulatory labor intensity · Finishing works
1 Introduction The technology implementation into the regulatory documentation, on the basis of which the estimated labor intensity and cost of production of construction products is assessed, can take a significant part of the time from the moment it appears on the real trade. The lack of normative indicators for a particular technological process often leads to the abandonment of technology due to the impossibility of objectively assessing the time and financial resources required for its implementation [1]. Otherwise, the application of benchmarks, taking into account the experience of other countries, without adjusting for many factors taking into account local conditions, leads to significant errors between the calculated and actual indicators. The possibility of using data from foreign regulatory documents can be feasible in the R. Fatullaev (B) · T. Bidov Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, 129337 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_125
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case of establishing stable correlations between the regulatory data of technological processes, as well as data groups [2].
2 Research Methodology This article places emphasis on one general factor of project management: work force which is related throughout any project. The sequence of research is: • Analysis of Russian and Spanish standards in order to find the way to exchange each other. As there is a vast difference in prices, particularly in regards to geographical location within the country, especially in Russia, it has been decided to research standards for Moscow and Barcelona; • Activities definition and work force performance in agreement with the norms of two different countries; • Concluding task is to compare the achieved results and submit conclusions.
3 Main Part Based on the results obtained during research to identify the correlation between organizational and technological models in Group 1 (Fig. 1) developed on the basis of Russian and foreign regulatory documents, it was decided to conduct additional research aimed at increasing the objectivity of the results obtained. As in previous studies, the TSN-2001 regulatory framework used to determine the cost of construction in Moscow and the BEDEC database [3] developed by ITeC—the Institute of Construction Technologies of Catalonia, were used as the normative bases of two countries: Russia and Spain. used in Barcelona [4]. Within the framework of this study, a group of “single elements of buildings” [5] was used, which makes it possible to achieve an increase in the accuracy of calculations. In the course of the study, a number of technological processes were selected. The main criteria for choosing technological solutions remained unchanged, in addition to the fact that they should not repeat the previously studied groups of technological processes: the technological process must be widely applicable in practice; the
Fig. 1 The groups of works
The Method of Mutual Use of the Labour Intensity of Finishing … Table 1 Installation of floors from large-sized ceramic tiles such as porcelain stoneware on glue from dry mixes with a layer thickness of 4 mm with grouting (100 m2 ). Russia
Table 2 Improved painting with polyvinyl acetate water-based compositions of walls on prefabricated structures prepared for painting (100 m2 ). Russia
Table 3 Improved plastering of walls to concrete inside buildings (100 m2 ). Russia
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Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
82.08
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
23.1
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
74
technological process must be present simultaneously in the standards of Russia and Spain, the scope of work on technological processes must be identical, etc. Works that meet the selected search parameters are shown below: • • • • •
Installation of ceramic tile floors: Improved painting of walls with polyvinyl acetate water-based compositions; Improved plastering of walls to concrete inside buildings; Surface treatment of ceilings with a deep penetration primer inside the room; Arrangement of suspended ceilings from Armstrong-type panels.
Data from Russian and Spain standards for selected works are presented in Tables 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11: Then all data was bring to a single unit of measurement: Table 4 Surface treatment of ceilings with a deep penetration primer indoors (100 m2 ). Russia
Table 5 Installation of suspended ceilings from Armstrong-type panels (100 m2 ). Russia
Human and technical resources
Unit
Value
Labour costs of workers
Tech-hour
5.68
Human and technical resources
Unit
Value
Labour costs of workers
Tech-hour
176
1234 Table 6 Installation of ceramic tile floors (m2 ). Spain
Table 7 Improved painting with polyvinyl acetate water-based compositions of walls (m2 ). Spain
Table 8 Improved plastering of walls to concrete inside buildings (m2 ). Spain
Table 9 Surface treatment of ceilings with a deep penetration primer inside the room (m2 ). Spain
Table 10 Arrangement of suspended ceilings from Armstrong-type panels (m2 ). Spain
R. Fatullaev and T. Bidov Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
0.45 + 0.2 * 2 = 0.85
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
0.11 * 2 = 0.22
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
0.56 + 0.28 * 2 = 1.12
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
0.15
Human and technical resources
Unit
Value
Labour costs of workers
Man-hour
0.2*2 = 0.4
Table 11 Summary table of labours for all types of work for two countries Name of work
Unit (m2 )
Labour (Russia)
Labour (Spain)
Ceramic tile flooring
1
0.84
0.85
Improved painting with polyvinyl acetate water-based compositions of walls
1
0.23
0.22
Improved plastering of walls to concrete inside buildings
1
0.74
1.12
Surface treatment of ceilings with a deep penetration primer indoors
1
0.056
0.15
Arrangement of suspended ceilings from Armstrong-type panels
1
1.76
0.4
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3.1 The Equation of the Pair Regression 3.1.1
Using the Graphical Method
The next step was to determine the relationship between the results obtained. The pair regression equation with using the graphical method was used for this purpose. This method is used to visualize the form of communication between the studied indicators. So, in a rectangular coordinate system build the graph, the ordinate of the lay individual values of resultant variable Y, and the abscissa shows the individual values of factor X. The set of points of effective and factor features is called the correlation field (Fig. 2). Taking into account the data of the correlation field, we can assume that the relationship between all values of X and Y is linear. The linear regression equation looks like this: y = b · x + a [6]. The estimated regression equation will look like this y = b · x + a + ε, where ε are the observed values of errors ε, a and b, respectively, estimates of the parameters α and β of the regression model to be found. Here ε is a random error (deviation, perturbation) [7]. Reasons for the possibility of a random error: • • • • •
non-Inclusion of significant variables in the regression model; aggregation of variables; incorrect description of the model structure; incorrect functional specification; the error of measurement.
Since the deviations of ε for each particular observation are I-random and their values in the sample are unknown, then: 1) only estimates of the parameters α and β can be obtained from observations xi and yi 1.5
1
0.5
0 0
Fig. 2 Correlation field
0.5
1
1.5
2
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Table 12 Regression parameters x
y
x2
y2
x*y
0.84
0.85
0.7056
0.7225
0.714
0.23
0.22
0.0529
0.0484
0.0506
0.74
1.12
0.5476
1.2544
0.8288
0.056
0.15
0.00314
0.0225
0.0084
1.76
0.4
3.0976
0.16
0.704
3.626
2.74
4.4068
2.2078
2.3058
2) Estimates of the parameters α and β of the regression model are, respectively, values a and b, which are random in nature, since they correspond to a random sample; To estimate the parameters α and β—use least squares method (LSM). The least squares method gives the best (consistent, efficient, and unbiased) estimates of the parameters of the regression equation. But only if certain assumptions about the random term (ε) and the independent variable (x) are met. Formally, the LSM criterion can be written as follows: S=
(yi − y · i)2 → min
(1)
System of normal equations. a·n+b· a·
x +b·
x=
x2 =
y
y·x
(2) (3)
To calculate the regression parameters, we will build a calculation table (Table 12). For our data, the system of equations has the form: 5a + 3.626 · b = 2.74
(4)
3.626 · a + 4.407 · b = 2.306
(5)
Multiply the Eq. (1) of the system by (−0.725), we get a system that we solve by algebraic addition [8]. We get empirical regression coefficients: b = 0.1794, a = 0.4179 The regression equation (an empirical equation of regression): y = 0.1794x + 0.4179
(6)
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The empirical regression coefficients a and b are only estimates of the theoretical coefficients βi , and the equation itself reflects only the General trend in the behavior of the variables under consideration [9].
3.2 Parameters of the Regression Equation The sample average.
xi 3.626 = = 0.725 n 5 2.74 yi = = 0.548 y= n 5 2.31 xi yi = = 0.461 xy = n 5 x=
(7) (8) (9)
Sample variances:
x 2i − x 2 = 0.36 n 2 y i 2 − y 2 = 0.14 S (y) = n S 2 (x) =
(10)
(11)
Standard deviation S(x) = S(y) =
S 2 (x) = S 2 (y) =
√
0.36 = 0, 596
(12)
√ 0.14 = 0, 376
(13)
The correlation coefficient b can be found by the formula without solving the system directly: 0, 461 − 0, 725 · 0, 548 xy − x · y = = 0, 1794 S 2 (x) 0, 36
(14)
a = y − b · x = 0, 548 − 0, 1794 · 0, 725 = 0, 4179
(15)
b=
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R. Fatullaev and T. Bidov
The Coefficient of Correlation cov(x, y) = x · y − x · y = 0, 461 − 0, 725 · 0, 548 = 0, 0638
(16)
We calculate the indicator of tightness of communication. This indicator is a sample linear correlation coefficient, which is calculated using the formula: rx y =
xy − x · y 0, 461 − 0, 725 · 0, 548 = = 0, 285 S(x) · S(y) 0, 596 · 0, 376
(17)
The linear correlation coefficient gets values from −1 to +1. Connections between signs can be different: weak and strong [10]. Their criteria are estimated on a scale of Chedoke: • • • • •
< r x y < 0.3: weak; < r x y < 0.5: moderate; 0.5 < r x y < 0.7: noticeable; 0.7 < r x y < 0.9: high; 0.9 < r x y < 1: very high; In our example, the relationship between feature Y and factor X is weak.
4 Conclusions The research results show that there is a weak correlation between the studied parameters. This suggests that in the segment of finishing works, the linear relationship between the data of Spanish and Russian regulatory documents is rather weak. According to the results of two studies, there is a moderate and weak correlation between the parameters, which at this stage is not a basis for refusal or confirmation of a scientific and technical hypothesis. More research is needed.
References 1. Lapidus A et al (2020) Construction project organizational and technological parameters analysis. IOP Conf Ser Mat Sci Eng 23:072047. https://doi.org/10.1088/1757-899X/869/7/ 072047 2. Aidarov S, Nogales A, Reynvart I, Toši´c N, de la Fuente A (2022) Effects of low temperatures on flexural strength of macro-synthetic fiber reinforced concrete: experimental and numerical investigation. Materials 15(3):1153. https://doi.org/10.3390/ma15031153 3. Fatullaev R et al (2021) Assessment of the possibility of improving the efficiency of the organizational and technological model of the building under construction through the use of foreign single estimated standards for construction works. E3S Web Conf 09022. https://doi.org/10. 1051/e3sconf/202125809022
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4. Toši´c N, Aidarov S, De La Fuente A (2020) Systematic review on the creep of fiber-reinforced concrete. Materials 13:5098. https://doi.org/10.3390/ma13225098 5. Oleinik P, Kuzmina T, Zueva D, Balmashnova M (2020) Optimization of the duration of the pioneer construction period. IOP Conf Ser Mat Sci Eng. 23:062006. https://doi.org/10.1088/ 1757-899X/869/6/062006 6. Fatullaev RS (2019) Influence degree of constrained conditions on overhaul of apartment buildings. E3S Web Conf 135:03029. https://doi.org/10.1051/e3sconf/201913503029 7. Tokarsky A, Topchiy D (2021) The concept of quality control of the organization of construction processes during construction supervision through the use of information technology. E3S Web Conf 258:09028. https://doi.org/10.1051/e3sconf/202125809028 8. Goncharov A, Yefimov V (2021) Increasing the laying depth of the foundations fordeepened underground buildingsparts. E3S Web Conf 258:09017. https://doi.org/10.1051/e3sconf/202 125809017 9. Doroshin I, Perunov A (2021) Frequency of using additional coefficients during the engineering-and-technical investigation of buildings. E3S Web Conf 259:09006. https://doi. org/10.1051/e3sconf/202125809006 10. Aidarov S, Nadaždi A, Pugach E, Toši´c N, de la Fuente A (2022) Cost-oriented analysis of fibre reinforced concrete column-supported flat slabs construction. J Build Eng 51:104205. https:// doi.org/10.1016/j.jobe.2022.104205
Choosing Material and Method for Increasing the Wear Resistance of Elements of Transport and Handling Equipment Alexander Scherbakov , Andrey Misailov , Denis Shavelkin , and Natalya Verbova Abstract The paper examines the problem of choosing a material and a method for increasing the wear resistance of elements of transport and handling equipment. The reliability of the parts in use has a special influence on the performance of transport and handling equipment. The choice of materials for their manufacture allows further calculation of the likelihood of how such elements will affect its ability to work and productivity. In the process of determining the material and method for increasing the wear resistance of transport and handling equipment, structural steels with different chemical compositions were selected: low-carbon 08ps (as a model material), 10, 20, 30, St3 and low-alloy steels 09G2S and 10HSND, as well as high-carbon steel 65G and boron steel 30MnB5. Such methods as hightemperature annealing, normalization, hardening and high-temperature tempering, thermal cycling, cold plastic deformation, thermal cycling of steels after cold plastic deformation were applied. In the course of the experiment, it was found that both for low-carbon steels 08ps, 10, 20, 30, St3, and for low-alloy structural steels 09G2S and 10HSND, as well as for high-carbon steel 65G and boron-containing steel 30MnB5, an increase in the number of TCT cycles (thermal cycling treatment) leads to an increase in the strength properties of the metal. With an increase in the number of cycles over 3–6, the increase in strength properties slows down significantly.
A. Scherbakov (B) Saint Petersburg State University of Architecture and Civil Engineering, 4, Vtoraya Krasnoarmeiskaya Street, Saint Petersburg 190005, Russia e-mail: [email protected] A. Misailov Moscow State University of Civil Engineering, 26, Yaroslavskoe Shosse, Moscow 129337, Russia D. Shavelkin Moscow Aviation Institute (National Research University), 4, Volokolamskoe Shosse, Moscow 125993, Russia N. Verbova Peter the Great St.Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg 195251, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_126
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Keywords Transport and handling equipment · Increase in wear resistance of elements · Durability · Operation · Thermal cycling
1 Introduction It is known that the reliability of the parts in use has a special effect on the performance of transport-technological machines. The choice of materials for their manufacture allows in the future to calculate the probability of how such elements will affect its working capacity and productivity, allowing us to foresee possible difficulties that affect the operation of the machine, its repair, maintenance and replacement of materials. The choice of materials for the manufacture of transport and handling equipment occurs already at the design stage, since wear resistance depends both on the initial stages of creating transport and handling equipment and on subsequent ones: operation and maintenance [1–5]. One of the key properties of transport and handling equipment is reliability. Reliability is a property of transport and handling equipment that allows them to perform a number of necessary tasks without loss of technical capacity and a drop in productivity. Reliability is responsible for a number of indicators necessary for the stable operation of transport and handling equipment, which include operational, technical, economic and technological ones. Choosing the right materials and finding the right method to improve the wear resistance of the machine can prevent the possible risks of excessive financial costs associated with the restoration of the machine after its breakdown [6]. Reliability involves such properties as failure-free performance and durability. Failure-free performance is a property that implies stable operation of the machine for a long period of time, i.e., continuous operation until failure or scheduled maintenance [7, 8]. Durability is also an important property of machines. Durability implies the full use of transport and handling equipment with the preservation of their maximum level of performance until the onset of the limiting state. Durability differs from failure-free performance in that it implies the calculation of the level of the machine state by the duration of its operation, i.e., by its total operating time. This time period starts from the moment the machine is put into operation and lasts until repair work is carried out in the event of a breakdown or until the machine is completely utilized due to bringing it to the limit state [9]. The failure of the machine occurs under the influence of a number of factors: • • • •
lack of the required security level; non-compliance of the level of machine parameters with the initially set values; decrease in the efficiency of operation of transport and handling equipment; constant need for repair or maintenance work to maintain the correct functioning of the machine.
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There are a number of criteria applied to a transport and handling equipment in order to determine the level of its limit state. These include only those that categorically violate the operational properties of the equipment in question. This is a replacement of the central elements that affect the performance of the machine; carrying out a complete analysis of the machine due to critical damage, etc. Wear is a systematic transformation of the geometrical parameters of equipment parts (direct working elements, moving parts, combined segments) during contact with surfaces, leading to knocking out particles of material from the contact faces and to its subsequent distortion. In the equipment of the 21st century, breakdowns of elements of transport and handling equipment due to wear account for 80–90% of the total amount of breakdowns. Breakdowns in friction units occur due to the following factors: • abrasion of contacting edges due to excessive use; • instantaneous increase in the coefficient of friction to the degree of adhesion; • impermissible decrease in the friction coefficient in the elements responsible for the braking function and in the operation of kinematic pairs. Among these factors, the most significant is the wear of the contact faces. In most cases, wear depends on the amount of linear wear (in other words, on a decrease or increase in the dimensions of the working elements at the joint located in a perpendicular plane to the contact face). In some situations, to measure the amount of wear, such indicators as the amount of volumetric or mass wear are used [10]. There is such a form of the state of the transport and handling equipment as a failure. In the event of a failure, the machine loses (in whole or in part) operability and ceases to perform its key functions and tasks. In this case, there is a complete or partial deviation from the norms established by the technical documentation, regulated by standards or certain technical setups [11]. In most cases, failure occurs due to partial or complete destruction of elements or parts of transport and handling equipment. Each mechanism or machine has its own endurance limit. This limit depends on the level of stress that the product, material or complete machine structure can withstand in connection with a long or rapid, but deviant form of operation. Calculations play a huge role in setting the required stress level for a particular design. They allow knowing in advance the permissible stress level in order to assess the efficiency of the transport and technological machines at the initial design stage and calculate possible operational risks caused by wear of elements, parts or the machine structure itself [12–15]. The wear of the elements of transport and handling equipment primarily means the property of the material that makes up the part or element to succumb to the aging process, i.e., to wear. There are a number of factors affecting the wear resistance of elements of transport and handling equipment: • quality of the material of which the element is composed; • element surface quality; • degree of loads exerted on the surface of the element;
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• speed of surface friction; • adherence to strict rules for maintaining the correct functioning of the element, etc.
2 Materials and Methods The choice of materials from which its elements will be created has a great influence on the wear resistance of transport and handling equipment. The properties of the material make it possible to determine in advance the degree of wear resistance of the transport and handling equipment. Such properties as hardness, strength and viscosity are widely known. It should be noted that such properties make it possible to choose the material that will be optimal in the conditions of operation of transport and handling equipment. An example is the machines used in the drilling industry. When creating such machines, high-strength chromium steels with significant viscosity are used. The wear resistance of metals is greatly influenced by the chemical composition and structure. The most wear-resistant types of steel include fine-grained one. This type includes a high content of silicon, manganese, elements of nickel, chromium, molybdenum, tungsten, which make it possible to achieve the required level of wear resistance of materials used to create transport and handling equipment. In addition, the wear resistance is influenced by the materials from which the machine elements subject to wear are made, as well as their processing methods and their composition. Let’s consider the main types of steels used for the manufacture of elements of transport and handling equipment. Technical indicators of steel St3 make it possible to use it in the construction of loaded parts of buildings with welded joints and elements in machines and mechanisms that operate at high temperatures. Rolled stock of certain categories (specifically, category 5) is used for the construction of metal structures operating in a wide temperature range (from −40 to 425 °C). Upon completion of the assembly of a metal structure of complex configuration, it is necessary to subject it to heat treatment at a high temperature. Such actions are mandatory, as they help to remove excess stress arising from welding. The main advantages of this steel grade include: • good anti-corrosion properties; • high mechanical qualities; • good weldability. Steel 08ps belongs to the group of structural carbon steels. The composition at the chemical level is established by the Russian State Standard GOST 1050-88. It regulates the ratio of substances that are included in the structure of the 08ps alloy, namely: • • • •
C: 0.05 to 0.11%; Si: from 0.05 to 0.17%; Mn: 0.35 to 0.65%; Cr: not more than 0.10%.
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This steel has a high level of strength and hardness. The advantages of this material include the fact that it is not susceptible to loads that do not reach certain limits. If these limits are not exceeded, then the product made from this steel grade retains its original shape. However, it should be noted that the product will experience a slight deformation, after which it will return to its previous shape, and at the time of restoration, it will be in a state of stress. This steel grade exhibits positive qualities during welding, however, it must be remembered that products from this material that have undergone heat treatment are no longer suitable for use in welding work. Steel 09G2S was developed for the construction of metal structures intended for subsequent use in construction. This feature is explained by significant strength, reliability, as well as the admissibility of reducing the amount of raw materials consumed for the production of elements. So, when using a conventional alloy, the thickness of the element would be 5 mm, and when using the 09G2S, it would be 2.5–3 mm. The characteristics of steel of this grade make it possible to use it at temperatures from −70 to +450 °C. Because of this, it is used in the manufacture of various parts and connections. High weldability makes it possible to manufacture complex units for the machine building, shipbuilding, and railway industries. Steel 09G2S, which has undergone heat treatment, is used in the manufacture of pipelines. In the northern regions, it is used in the transportation of hydrocarbons. The excellent properties of steel make it possible to create profiled bars—I-beams, angles, etc. The scope of the area in which 09G2S steel is used is quite extensive and affects the machine tool industry, the transport industry and construction. In addition to low-carbon steels, low-alloy steels are also used in the production of individual elements of machines and mechanisms. In these steels, the content of alloying components in total is less than 2.5% (except for carbon). With a content of alloying elements in the amount of 2.5 to 10%, the steel is called medium-alloyed, with a content of more than 10% of alloying elements—high-alloyed. In the process of determining the material and method for increasing the wear resistance of transport and handling equipment, structural steels with different chemical compositions were selected: low-carbon steels 08ps (as a model material), 10, 20, St3, 30, low-alloy steels 09G2S and 10HSND, as well as high-carbon steel 65G and boron steel 30MnB5. The chemical composition of steels is given in Table 1. The reason for choosing these steels was that they: • are widely used in the manufacture of welded MS (metal structures) of transport and handling equipment, in mechanical engineering and other industries; • have high plasticity characteristics at ordinary and low temperatures; • have different chemical composition; • have different categories of strength and different susceptibility to cyclic hardening and softening; • have good weldability; • have increased and ordinary anti-corrosion properties;
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Table 1 Chemical composition of steels Steel grade Chemical composition. % C
Si
Mn
S
P
Cr
08ps
0.09
0.013
0.33
0.015
0.006
0.03
0.02
10
0.08
0.09
0.45
0.02
0.014
0.03
0.02
0.04
20
0.21
0.18
0.38
0.032
0.025
0.012
0.03
0.05
30
0.27–0.35 0.17–0.37 0.5–0.8
St3
0.19
0.21
0.53
0.034
0.032
0.06
0.03
0.07
09G2S
0.11
0.68
1.33
0.008
0.015
0.03
0.02
0.03
10HSND
0.10
0.64
0.56
65G
0.62–0.7
0.17–0.37 0.9–1.2
30MnB5
0.27–0.33 ≤0.40
≤0.040 ≤0.035 ≤0.25
Ni
Cu 0.03
≤0.30 ≤0.30
0.06
0.013
0.65
0.53
0.44
0.035
0.035
0.25
0.25
0.25
–
–
1.15–1.45 ≤0.035 ≤0.025
≤0.40
• make it possible to extend the obtained regularities to all steels close to the selected grades both in composition and in properties; • can be used to study the physics of a magnetomechanical phenomenon due to the low carbon content. To conduct research, plates of 30 mm wide and 150 mm long were cut from steel sheets across the rolling, which were subjected to various types of heat treatment. In the process of research, the study of the properties of these steels was carried out after various types of processing, such as: • high temperature annealing; • normalization (annealing and normalization temperature for steels 08ps, 20, St3, 09G2S and 10HSND was 900 °C, for steel 10–920 °C, holding time was 30 min); • hardening and high-temperature tempering (carried out for steels 20, 30 and 30MnB5 at temperatures of 880 and 600 °C, respectively, and for steel 65G—at temperatures of 880 and 360 °C, respectively); • thermal cycling treatment for the steels under study, carried out at a temperature of 770 °C and followed by cooling in air; • cold plastic deformation (fractional rolling) of steel to a degree of deformation of 20 and 50%; • thermal cycling treatment of steels after cold plastic deformation. To study the process of formation of the microstructure of structural steels in the process of heat, thermal cycling and deformation effects, microstructural analysis and the passive fluxgate method were used.
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3 Results and Discussion Types of heat treatment of the studied steels are presented in Table 2. In the process of carrying out experimental studies, it was found that high temperature annealing makes it possible to obtain the most coarse-grained and equiaxed structure in low-carbon and low-alloy steels. The analysis showed that a high effect during grinding in structural steels is obtained by the use of thermal cycling based on repeated cyclic heating of steels (austenization) and subsequent cooling after each cycle. The secondary effect here will be obtaining a uniform distribution of chemical elements, which is caused by the intensification of diffusion processes due to the enhancement of thermophysical factors. In the process of carrying out metallographic studies, it was found that, without taking into account the chemical composition and the initial structure of the studied steels, after TCT, a fine-grained structure with a different degree of dispersion is formed in all cases. Typical structures of steels after thermal treatment are shown in Figs. 1–3. The greatest changes in the structure of steels occur during the first 3–6 thermal cycles. A further increase in the number of cycles no longer has such a strong effect on the degree of structure refinement, however, it reduces the inequigranularity of steels. The same situation takes place in the case of other steels with different initial structural states; accordingly, to optimize the grain structure in structural steels, 3 to 6 cycles are required. It should be taken into account that the final grain size after TCT is also determined by the initial steel structure before this process. The structure of steels (delivery plus annealing at 900 °C), which is coarser-grained compared to the structure in the delivered state, also corresponds to a coarser-grained structure after thermal cycling (Figs. 1, 2). If structural steels are deformed prior to TCT, then a finer grain structure can be obtained in the output than in the case of other types of pretreatment (Fig. 3). It is advisable to initially apply the method of cold plastic deformation. The reason for this is that in the course of plastic deformation, redistribution and an increase in the density of dislocations, vacancies, and stacking faults occur, and the formation and development of small- and large-angle boundary is intensified. This subsequently optimizes the structure of steels in TCT. The mechanical properties of the well-welded and most widely used structural steels St3 and 10HSND after high-temperature annealing at 1050 °C and subsequent 1–10-fold TCT at 770 °C are shown in Table 3. For comparison, the properties of model steel 08, which has a low content carbon, are presented. These tables allow us to conclude that for both low-carbon steels 08ps and St3, and low-alloy steel 10HSND, a significant increase in strength properties is observed after TCT, especially after the first three cycles. But when the number of cycles exceeds 3, the increment in the strength properties of the metal slows down somewhat. Thus, in order to improve the basic strength characteristics of metals, it is advisable to use TCT during the first 3–6 cycles.
800
800
30MnB5
880
30
65G
900
20
900
920
10
900
900
08ps
10HSND
900
St3
09G2S
Annealing, °C
Steel grade
800
800
900
900
880
900
920
900
900
Normalization, °C
Table 2 Types of heat treatment of the studied steels
780 780 780
– 800 + 360, oil 880 + 600, oil
780
780
880 + 600, water
–
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
780
3 cycles
780
780
780
780
780
780
780
780
780
6 cycles
–
–
–
–
6 cycles
–
–
–
–
–
–
–
–
Normalization + 780 °C, cooling down to 630 °C in the air + water
–
–
–
–
3 cycles
780
6 cycles
3 cycles 780
Processing for granular perlite (normalization + TCT), °C
Annealing + TCT, °C Normalization + TCT, °C
880 + 600, water
–
–
Hardening + tempering, °C
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Fig. 1 Change in the structure of steel 09G2S during thermal cycling, ×650: a—as-delivered state; b, c—after the 3rd and 6th cycles, respectively
Fig. 2 Change in the structure of steel 08ps during thermal cycling, ×650: a—condition (asdelivered + annealing at 900 °C; b, c—after the 3rd and 6th cycles, respectively
Fig. 3 Change in the structure of steel 10 HSND during thermal cycling, ×650: a—condition (as-delivered + rolling on E = 50%); b, c—after the 3rd and 6th cycles, respectively Table 3 Mechanical properties of steels after thermal cycling Steel grade
Mechanical properties, MPa
Number of TCT cycles 0
1
2
3
4
5
7
10
08ps
σ0.2
166.0
172.0
181.5
188.0
190.5
193.0
193.5
195.0
σb
281.5
295.5
301.0
309.5
315.0
317.5
320.5
323.5
St3
σ0.2
233.0
242.5
250.0
255.5
259.0
262.5
263.0
263.5
σb
418.0
441.5
451.0
468.5
471.5
476.0
477.5
484.5
σ0.2
385.0
400.5
416.0
423.5
428.5
435.0
434.0
435.0
σb
503.0
538.0
538.0
563.5
568.5
573.5
578.5
583.5
10HSND
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A. Scherbakov et al.
Table 4 Mechanical properties of steels depending on different types of heat treatment Steel grade
Mechanical properties, MPa
Type of heat treatment
σ0.2
151.0
217.0
274.0
276.0
σb
280.0
331.0
352.0
353.0
σ0.2
149.0
223.0
250.0
252.0
σb
265.0
304.0
328.0
331.0
20
σ0.2
252.0
314.0
330.0
332.0
σb
388.0
421.0
448.0
449.0
St3
σ0.2
242.0
305.0
368.0
369.0
σb
392.0
439.0
460.0
462.0
σ0.2
279.0
338.0
404.0
406.0
σb
438.0
494.0
528.0
530.0
10HSND
σ0.2
425.0
492.0
615.0
617.0
σb
618.0
684.0
727.0
729.0
30
σ0.2
152.0
266.0
280.0
295.0
σb
235.0
295.0
354.0
356.0
σ0.2
468.0
614.0
620.0
622.0
σb
769.0
830.0
871.0
872.0
σ0.2
620.0
827.0
1197.0
1200.0
σb
815.0
1150.0
1695.0
1700.0
08ps 10
09G2S
65G 30MnB5
Annealing
Normalization
TCT, three cycles
TCT, six cycles
Changes in the mechanical properties of structural steels 08, 10, 20, 30, St3, 09G2S, 10HSND, 65G and 30MnB5, depending on various types of heat treatment, are shown in Table 4. In this case, steels in the state of factory delivery were subjected to annealing and normalization at 900 °C and thermal processing. Based on the data in Table 4, it can be concluded that the conduction of TCT, which makes it possible to obtain a fine-grained structure in structural steels, makes it possible to significantly change their mechanical characteristics. Thus, the yield strength and tensile strength of the steels under study after three- and six-fold TCT increase much more than during annealing and normalization. Carrying out TCT, in contrast to heat treatment, makes it possible to better identify the positive effect of alloying on strength and plastic properties. At the same time, by significantly increasing the strength and ductility, it is possible to obtain previously unattainable values of the work of destruction of alloyed steels in the process of various types of loading. Accordingly, the preliminary treatment of steel for the production of individual elements of machines and mechanisms will increase their strength and wear resistance.
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4 Conclusion To increase the productivity of machines and mechanisms, it is very important that the machine retains its efficiency and does not lose its performance. Reliability includes the ability of transport and handling equipment not to lose their production characteristics. Despite these circumstances, over time, the transport and handling equipment changes under the influence of a number of factors. It can be influenced by such factors as changing climatic conditions, changing temperatures, environmental influences, which leads to wear and tear of the machine and can completely put it out of operation. The main attention should be paid to the material from which the elements of transport and handling equipment and mechanisms are made. Under the influence of various factors, steel can have different degrees of wear resistance. For this reason, it is necessary to improve this property of steel, which will increase the service life of both individual elements of the machine and the entire mechanism as a whole. During the experiment, it was found that both for low-carbon 08ps, 10, 20, St3, and for low-alloy structural steels 09G2S, 10HSND, as well as for high-carbon steel 65G and for boron-containing steel 30MnB5, an increase in the number of TCT cycles leads to an increase in the strength properties of the metal. With an increase in the number of cycles over 3–6, the increase in strength properties slows down significantly.
References 1. Bajaj P, Hariharan A, Kini A et al (2020) Steels in additive manufacturing: a review of their microstructure and properties. Mater Sci Eng A 772:138633. https://doi.org/10.1016/j.msea. 2019.138633 2. Brika SE et al (2020) Influence of particle morphology and size distribution on the powder flowability and laser powder bed fusion manufacturability of Ti-6Al-4V alloy. Addit Manuf 31:100929. https://doi.org/10.1016/j.addma.2019.100929 3. Cui C, Uhlenwinkel V, Schulz A, Zoch HW (2020) Austenitic stainless steel powders with increased Nitrogen content for laser additive manufacturing. Metals 10:61. https://doi.org/10. 3390/met10010061 4. Kumar SS, Marandi L, Balla VK et al (2019) Microstructure—property correlations for additively manufactured NiTi based shape memory alloys. Materialia 8:100456. https://doi.org/10. 1016/j.mtla.2019.100456 5. Lou X, Andresen PL, Rebak RB (2018) Oxide inclusions in laser additive manufactured stainless steel and their effects on impact toughness and stress corrosion cracking behavior. J Nucl Mater 499:182–190. https://doi.org/10.1016/J.JNUCMAT.2017.11.036 6. Mantrala KM, Das M, Balla VK et al (2015) Additive manufacturing of Co-Cr-Mo alloy: influence of heat treatment on microstructure, tribological and electrochemical properties. Front Mech Eng 1:2. https://doi.org/10.3389/fmech.2015.00002 7. Mukherjee M (2019) Effect of build geometry and orientation on microstructure and properties of additively manufactured 316L stainless steel by laser metal deposition. Materialia 7:100359. https://doi.org/10.1016/j.mtla.2019.100359
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8. Saeidi K, Gao X, Zhong Y, Shen ZJJ (2014) Hardened austenite steel with columnar sub-grain structure formed by laser melting. Mater Sci Eng A 625:221–229. https://doi.org/10.1016/j. msea.2014.12.018 9. Sames WJ, List FA, Pannala S, Dehoff RR, Babu SS (2016) The metallurgy and processing science of metal additive manufacturing. Int Mater Rev 61:315–360. https://doi.org/10.1080/ 09506608.2015.1116649 10. Scherbakov A, Babanina A, Graboviy K (2021) Acting stresses in structural steels during elastoplastic deformation. Adv Int Syst Comp 1259:298–311. https://doi.org/10.1007/978-3030-57453-6_26 11. Scherbakov A, Babanina A, Kochetkov I, Khoroshilov P (2020) Technical condition of welded load-bearing metal structures of operated agricultural hoisting cranes. E3S Web Conf 175:11005. https://doi.org/10.1051/e3sconf/202017511005 12. Scherbakov A, Babanina A, Matusevich A (2021) Passive probe-coil magnetic field test of stress-strain state for welded joints. Adv Intell Syst Comput 1259:312–323. https://doi.org/10. 1007/978-3-030-57453-6_27 13. Scherbakov A, Monastyreva D, Smirnov V (2019) Passive fluxgate control of structural transformations in structural steels during thermal cycling. E3S Web Conf 135:03022. https://doi. org/10.1051/e3sconf/201913503022 14. Tan C, Zhou K et al (2017) Microstructural evolution, nanoprecipitation behavior and mechanical properties of selective laser melted high-performance grade 300 maraging steel. Mater Des 134:23–34. https://doi.org/10.1016/j.matdes.2017.08.026 15. Wołosz P, Baran A, Pola´nski M (2020) The influence of laser engineered net shaping (LENS™) technological parameters on the laser deposition efficiency and properties of H13 (AISI) steel. J Alloys Compd 823:153840. https://doi.org/10.1016/j.jallcom.2020.153840
Method for Obtaining Structures with a Given Degree of Dispersion in Low-Carbon and Low-Alloy Steels of Transport and Handling Equipment Alexander Scherbakov , Maxim Aleksandrovskiy , Denis Shavelkin , and Natalya Verbova Abstract Steel for transport and handling equipment should provide the required reliability at a lower level of costs in manufacturing and operation. To determine the relationship between mechanical, structural, and magnetic parameters, the change in the stray magnetic field under the application of external loads was measured, and then the magnetic field diagram was superimposed on the tension diagram. The passive fluxgate method was used to measure the stray magnetic field; steels 08ps and 09G2S were used as the object of study. In the course of the study, measurements of the magnetic stray field were carried out under stepped loading of metal structures. As a result, the dependence of the stray magnetic field on the magnitude of the metal structure stretching was established. Thermal hardening of these steels gives an increase in the yield strength by 25…30% and tensile strength by 15…20%, as well as a shift in the cold brittleness threshold by 15…20 °C towards negative temperatures. Keywords Transport and handling equipment · Passive fluxgate method · Metal structures
A. Scherbakov (B) Saint Petersburg State University of Architecture and Civil Engineering, 4, Vtoraya Krasnoarmeiskaya Street, Saint Petersburg 190005, Russia e-mail: [email protected] M. Aleksandrovskiy Moscow State University of Civil Engineering, 26, Yaroslavskoe Shosse, Moscow 129337, Russia D. Shavelkin Moscow Aviation Institute (National Research University), 4, Volokolamskoe Shosse, Moscow 125993, Russia N. Verbova Peter the Great St.Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg 195251, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_127
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1 Introduction Welded load-bearing metal structures of transport and handling equipment can be operated under the influence of various types of loads and loading modes, therefore steel for them must be selected in such a way as to ensure the necessary reliability of the structure at the lowest cost of manufacture and operation. All steels must have good weldability, i.e., they must have the ability to form a high-quality welded joint with the selected welding technology without additional methods, such as heating and subsequent heat treatment [1–5]. The steels used must necessarily have high ductility. This is caused by the fact that as a result of the influence of various concentrators and residual welding stresses in individual zones of the structure, local plastic deformations occur during loading, and the steel must have a sufficient margin of plasticity to withstand them without destruction. The greater the stress concentration, the thickness of the used rolled products, the level of residual stresses, the higher the requirements for metal ductility. In this case, the effect of low temperatures on the behavior of low-carbon and lowalloy steels during operation should be taken into account [6]. Thus, rimming low-carbon steels are the most sensitive to temperature decrease, killed ones are less sensitive, and low-alloy steels retain the greatest ductility at low temperatures. If the structure operates at temperatures below −45 °C, then the use of low-alloy steels becomes mandatory, since only they can provide the structure with resistance to brittle fracture. In this case, steels 09G2S up to 32 mm thick and 10HSND up to 40 mm thick are used. It should be noted that many metal structures of transport and handling equipment operate in aggressive environments, while the corrosion rate of low-carbon steels in an atmosphere of varying degrees of pollution is from 0.01 to 0.50 mm/year, and in sea water—up to 3 mm/year. Corrosion of welds occurs even faster, so in this case, it is necessary to select steels with increased anti-corrosion properties, i.e., containing chromium, nickel and copper [7–10]. Low-carbon and low-alloy steels, in which the carbon content does not exceed 0.22% and which have good plastic properties, are most widely used as a material for metal structures of transport and handling equipment. At present, low-alloy steels are widely used in mechanical engineering and other industries. Compared to carbon, they have higher mechanical properties, which is achieved by hardening ferrite with alloying elements (Si, Mn, Cr, Ni, Cu, and others) in an amount of less than 2.5%. Low-alloy steels are used in hot-rolled or heat-strengthened form in mechanical engineering, in the manufacture of welded MS, main oil and gas pipelines, storage tanks, etc. Low-alloy steels include steels with good weldability: 09G2, 09G2S, 09G2D, 14G2, 17GS, 10G2S1, 10HSND, 10HSNDP, 15HSND, 14G2AF, 16G2AF, 12G2SMF, 12GN2MFAYU, etc. [11, 12]. The use of low-alloy steels can significantly reduce the metal consumption of structures, save a large amount of metal, improve the performance of structures, etc. Steels 09G2S and 10HSND, which are used as delivered or heat-strengthened, are most widely used in the manufacture of metal structures for transport and handling
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equipment. Hardening is carried out by rapid cooling of steel in water, preheated to a temperature of Ac3+ (30 … 50 °C) [13–15]. In view of the foregoing, low-carbon steel 08ps (as a model material) and low-alloy steel 09G2S were chosen for experimental studies.
2 Materials and Methods One of the promising methods for identifying stress concentration zones and determining the effective stresses is the passive fluxgate control method. To implement the passive fluxgate control method, the IKNM-2FP device with a two-channel fluxgate converter was chosen. To measure the stray magnetic field strength of the object surface, continuous and point scanning was carried out using a fluxgate transducer, which was located perpendicular to the sample surface. During scanning, special attention was paid to those zones in which the values of the stray magnetic field strength differed from the average both upwards and downwards. The identified zones with extreme values correspond to the expected zones of stress concentration. To assess the degree of their danger, stepwise loading (unloading) of structural elements was carried out.
3 Results and Discussion To identify the relationship between the mechanical, structural and magnetic parameters of the studied steels with different structures, in the first place, a study of the change in the stray magnetic field strength Hp under the application of an external load was made, which required joint magnetomechanical tests in order to superimpose the change in the magnetic parameter Hp on the diagram tension in the load–strain coordinates. The change in the values of the stray magnetic field strength was carried out at stepwise stops: in the area of elastic deformation—through certain increments of the external load, during plastic deformation—through certain increments l. Typical curves obtained as a result of experiments are shown in Figs. 1 and 2. It can be seen that in the area of elastic tensile deformation, for steel 08ps in the states (as-delivered, as-delivered + annealing at 900 °C), with an increase in the external load (that is, with an increase in the acting stresses σ), the values of the controlled magnetic parameter Hp decrease. Further, in the area of the yield point, the stabilization of the minimum values of Hp (the minimum values of the magnetic parameter) and a subsequent increase in the region of plastic deformation are observed.
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The calculation of the confidence interval for the obtained dependences was carried out according to the Russian State Standard GOST 8.207-76 “Direct measurements with multiple observations. Methods for processing the results of observations”. Based on the calculation results, the confidence interval does not exceed 1.95 A/m (with a confidence probability P = 0.98 and Student’s coefficient tp = 3.10). Similar results were also obtained when testing specimens of low-alloy steel 09G2S in various initial structural states, which indicates the presence of the relationship Hp(σ) for structural steels with different chemical composition and initial structure.
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Therefore, the presence of the observed dependences between the magnetic parameter Hp, the initial structure, and the acting stresses in the metal gives grounds for further research in order to expand and refine the relationship Hp(σ) during elastic–plastic deformation of low-carbon and low-alloy steels. Considering that real welded supporting metal structures of transport and handling equipment during manufacture, transportation, installation and operation can be subjected to both magnetic and mechanical influences, the results of magnetic measurements of Hp can be affected by the magnetic and mechanical history of the metal. Therefore, it was necessary to establish such conditions for conducting passive fluxgate control that would make it possible to exclude this influence. For this purpose, on samples from low-carbon steel 08ps and low-alloy steel 09G2S in the state of factory delivery, artificial creation of zones of local magnetization of varying intensity was carried out using a permanent magnet and local plastic deformations with varying degrees of work hardening. Before magnetomechanical treatment, the samples under study were preliminarily subjected to one loading– unloading cycle in the elastic region of deformation. The test results are shown in Fig. 3. After the treatment of the samples with a permanent magnet, not only the sign changed, but also the absolute value of the magnetic parameter Hp, for example, from +195 A/m to −395 A/m (Fig. 3, A). However, during the subsequent loading– unloading cycle, a large open magnetic hysteresis loop is formed, which arises due to a sharp change in Hp. After complete unloading, the final values of Hp almost completely return to the values of the magnetic field strength before the samples were treated with a permanent magnet. At the 2nd cycle, the final and initial values Нр, A/m
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of Hp are equal to each other. It should be noted that the same patterns of the Hp(σ) dependence remained in force after magnetic treatment as before its application. When applying local deformations, the positive values of the stray magnetic field strength Hp also changed to negative ones. For example, it can be seen from Fig. 3B that during the first loading–unloading cycle, a wide open magnetic hysteresis loop is observed due to a sharp change in the Hp values, which stabilize during the subsequent cycle. Hp(σ) curves under the 3rd and 2nd loadings practically coincide with each other. The results of the research showed that both when processing samples with a constant magnetic field and when applying mechanical damage, the first loading– unloading cycle makes it possible to almost completely eliminate the influence of the magnetic and mechanical prehistory of the samples, which makes it possible to significantly increase the reliability of subsequent measurements on the elements of the metal structures of the transport and handling equipment. Passive protection of elements of metal structures of transport and handling equipment involves the use of anti-corrosion coatings that reduce the likelihood of occurrence and development of corrosion processes. When assessing the technical condition of metal structures, classical control methods require preliminary surface preparation, which involves the removal of a protective coating. According to the type of materials, protective coatings of metal structures can be classified as paint and varnish, metal, oxide, insulating. Combinations of different types of coatings are also possible. Lacquer coatings, depending on the type of pigment, provide barrier, combined or tread (electrochemical) protection of steel. Currently, of all types of coatings, the most common, affordable and quite effective are paintwork. To protect metal structures from corrosion, more than 70 different brands of paints and varnishes are recommended. The choice of coating composition is a technical and economic task, the solution of which takes into account the cost of the protective coating, its durability, the complexity of application, and other factors. The durability of a protective coating in a production environment is usually established from the experience of operating coatings in similar environments or experimentally. Coatings can be factory-made polymeric (3…5 mm thick), bituminous (3…5 mm thick), polymeric tapes (1…3 mm thick, depending on the number of tape layers). On above-ground technological pipelines for piping compressor stations, vibration- and noise-insulating coatings are used, including canvas, polymer-bitumen mastic, aluminum sheet, etc. (with a total thickness of 8…30 mm). Removal of coatings for research requires its restoration after completion of work, which is associated with the involvement of material and labor costs. Therefore, there is a need to assess the possibility of using a passive fluxgate control method without removing the non-magnetic coating from structural elements. Therefore, the possibility of using the passive fluxgate method for testing the metal of welded structures without removing the non-magnetic protective coating was assessed, and the dependence of the stray magnetic field strength Hp on the thickness of the non-magnetic protective coating for low-carbon steel 08ps and low-alloy steel 09G2S in various structural states was established.
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The size of the gap between the sensor and the control surface (the thickness of the non-magnetic protective coating) was changed using fragments of non-magnetic material introduced between the unloaded sample and the fluxgate transducer. The gap was changed from 0 to 15 mm, i.e., by the maximum possible thickness of real coatings. Given that the magnetic parameter Hp in the control zone can have both negative and positive signs and different numerical values, this point was taken into account in the studies. On samples of steels 08ps and 09G2S in different initial states, there were zones of stress concentration with different initial magnetization Hp (from −400 to +400 A/m). First of all, the influence of the chemical composition and the initial microstructure of the studied steels on the change in the magnetic parameter Hp with the gap size was studied. It can be seen (Fig. 4) that the chemical composition of steels and their structural states slightly affect the shape of the curves and the magnitude of the change in Hp with an increase in the thickness of the nonmagnetic protective coating. Figures 5, 6, 7, 8, 9 show the dependences of the stray magnetic field strength Hp on the gap size at different initial values of Hp on specimens of low-alloy steel 09G2S. It is characteristic of all dependences that, regardless of the initial values of Hp, with an increase in the gap size, a significant decrease in the value of the magnetic parameter Hp is observed. Further, starting from the non-magnetic coating thickness of 6…10 mm, it slows down somewhat. In this case, the absolute change in the values of the magnetic parameter is more pronounced for samples with high initial values of Hp. Figures 8 and 9 show the data of experimental studies of the influence of the thickness of the non-magnetic protective coating for steel 09G2S on the results of changing the strength of the stray magnetic field Hp. Similar dependences were also obtained for low-carbon steel 08ps. Нр,A/m -55
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Fig. 5 Dependence of the strength of the stray magnetic field Hp on the thickness of the nonmagnetic protective coating for steel 09G2S in the as-delivered state at various initial positive values of Hp: 14; 22; 41; 60 A/m (curves 1–4, respectively) Нр,A/m 440 400 360 320 280 240 200
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It has been established that with a thickness of a non-magnetic protective coating from 0 to 3 mm, the relative change in the values of the magnetic parameter Hp is in the range of 18.5…30%, which makes it possible to recommend passive fluxgate testing of the surface of welded metal structures when assessing their technical condition without removing the non-magnetic protective coating.
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Taking into account the above results of experimental studies, as well as the positive distinctive features of the passive fluxgate control method, its use in assessing the technical condition of welded load-bearing metal structures of operated transport and handling equipment is advisable when solving the following problems: • detection of stress concentration zones in the elements of metal structures; • determination of the sign of acting stresses (tension or compression);
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• assessment of the area (elastic, plastic) in which the identified SC zones are located; • assessing the degree of danger of the identified SC zones and identifying the most dangerous among them; • indirect assessment of the values of acting stresses in the identified SC zones of the MS elements; • determining the possibility of local plastic deformation in stress concentration zones by the nature of the magnetic hysteresis loop; • detection of zones of local and general corrosion damage; • detection of stress concentration zones in welded joints without surface preparation and removal of non-magnetic protective coating up to 3 mm thick.
4 Conclusion The requirements for structural steels of transport and handling equipment are considered, taking into account the type and modes of loading, the aggressiveness of corrosive media and operating conditions at various temperatures, and a reasonable choice of research material is made. A relationship has been established between the initial structure, the acting stresses and the strength of the stray magnetic field in low-carbon steel 08ps and low-alloy
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steel 09G2S in the process of obtaining a tension diagram in the load-strain coordinates, which gives grounds for using the passive fluxgate method in assessing the stress–strain state of metal structures of transport and handling equipment. The influence of the magnetic and mechanical prehistory of the metal and the thickness of the non-magnetic protective coating on the results of passive fluxgate testing of structural steels is studied. A technique for measuring the magnetic parameter minimizing the measurement error is proposed. It has been established that the appearance of extreme values in artificially created zones of hardening (work hardening) and local magnetization on the samples is eliminated during the first loading–unloading cycle of the metal during elastic deformation. At the same time, the dependence of the stray magnetic field strength on the acting stresses during subsequent test cycles does not qualitatively and quantitatively differ from the dependences obtained on samples without damage. This character of changes with an unknown magnetic and mechanical history of the metal has a positive value, since it increases the degree of reliability of the results of subsequent measurements. A method has been developed for obtaining structures with a given degree of dispersion in low-carbon and low-alloy steels due to recrystallization annealing and thermal cycling treatment of steels, as well as methods for passive fluxgate control of structural changes in the metal.
References 1. Bajaj P, Hariharan A et al (2020) Steels in additive manufacturing: a review of their microstructure and properties. Mater Sci Eng A 772:138633. https://doi.org/10.1016/j.msea. 2019.138633 2. Brika SE, Letenneur M, Dion CA, Brailovski V (2020) Influence of particle morphology and size distribution on the powder flowability and laser powder bed fusion manufacturability of Ti-6Al-4V alloy. Addit Manuf 31:100929. https://doi.org/10.1016/j.addma.2019.100929 3. Cui C, Uhlenwinkel V, Schulz A, Zoch HW (2020) Austenitic stainless steel powders with increased Nitrogen content for laser additive manufacturing. Metals 10:61. https://doi.org/10. 3390/met10010061 4. Kumar SS, Marandi L, Balla VK et al (2019) Microstructure—property correlations for additively manufactured NiTi based shape memory alloys. Materialia 8:100456. https://doi.org/10. 1016/j.mtla.2019.100456 5. Lou X, Andresen PL, Rebak RB (2018) Oxide inclusions in laser additive manufactured stainless steel and their effects on impact toughness and stress corrosion cracking behavior. J Nucl Mater 499:182–190. https://doi.org/10.1016/J.JNUCMAT.2017.11.036 6. Mantrala KM, Das M et al (2015) Additive manufacturing of Co-Cr-Mo alloy: influence of heat treatment on microstructure, tribological and electrochemical properties. Front Mech Eng 1:2. https://doi.org/10.3389/fmech.2015.00002 7. Mukherjee M (2019) Effect of build geometry and orientation on microstructure and properties of additively manufactured 316L stainless steel by laser metal deposition. Materialia 7:100359. https://doi.org/10.1016/j.mtla.2019.100359 8. Saeidi K, Gao X, Zhong Y, Shen ZJJ (2014) Hardened austenite steel with columnar sub-grain structure formed by laser melting. Mater Sci Eng A 625:221–229. https://doi.org/10.1016/j. msea.2014.12.018
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9. Sames WJ et al (2016) The metallurgy and processing science of metal additive manufacturing. Int Mater Rev 61:315–360. https://doi.org/10.1080/09506608.2015.1116649 10. Scherbakov A, Monastyreva D, Smirnov V (2019) Passive fluxgate control of structural transformations in structural steels during thermal cycling. E3S Web Conf 135:03022. https://doi. org/10.1051/e3sconf/201913503022 11. Scherbakov A, Babanina A, Graboviy K (2021) Acting stresses in structural steels during elastoplastic deformation. Adv Intel Syst Comp 1259:298–311. https://doi.org/10.1007/9783-030-57453-6_26 12. Scherbakov A, Babanina A, Kochetkov I, Khoroshilov P (2020) Technical condition of welded load-bearing metal structures of operated agricultural hoisting cranes. E3S Web Conf 175:11005. https://doi.org/10.1051/e3sconf/202017511005 13. Scherbakov A, Babanina A, Matusevich A (2021) Passive probe-coil magnetic field test of stress-strain state for welded joints. Adv Intel Syst Comp 1259:312–323. https://doi.org/10. 1007/978-3-030-57453-6_27 14. Tan C, Zhou K et al (2017) Microstructural evolution, nanoprecipitation behavior and mechanical properties of selective laser melted high-performance grade 300 maraging steel. Mater Des 134:23–34. https://doi.org/10.1016/j.matdes.2017.08.026 15. Wołosz P, Baran A, Pola´nski M (2020) The influence of laser engineered net shaping (LENS™) technological parameters on the laser deposition efficiency and properties of H13 (AISI) steel. J Alloys Compd 823:153840. https://doi.org/10.1016/j.jallcom.2020.153840
Modeling and Optimization of the Hitch System of the Harvesting Units of Cotton Harvesting Machine MX-1.8 Under Vertical Vibrations Bakhtiyor Azimov , Anvar Rizaev , Dilfuza Yakubjanova , and Saidazim Kubaev
Abstract The equations of motion of the cotton harvesting machine (CHM) MX1.8 and the hitch system of the harvesting unit under vertical vibrations are derived in the article. On the basis of the equations of motion obtained, models and algorithms for optimal control of the cotton harvesting machine MX-1.8 are developed. The necessary conditions for optimal control of the motion of the CHM MX-1.8 are investigated using the Pontryagin maximum principle. The values of vertical vibrations of the CHM MX-1.8 and vertical and torsional vibrations of the hitch system of harvesting units were determined in the process of moving along the roughness on the headland of the cotton field. The design flaws of the CHM MX-1.8 hitch system, i.e. non-uniform distribution of force in the rocker shaft of the hitch mechanism were detected. Keywords Cotton harvester · Hitch mechanism · Modeling · Optimal control
1 Introduction The development and improvement of information systems and technology processes predetermine the principles and approaches for the formation and formalization of all new classes of analysis models, productivity forecast and testing of cotton harvesters.
B. Azimov Research Institute for the Development of Digital Technologies and Artificial Intelligence, 100125 Buz-2 Street, 17A, Tashkent, Uzbekistan A. Rizaev Institute of Mechanics and Seismic Stability of Structures of the Academy of Sciences of the Republic of Uzbekistan, 100125 Durman yuli Street, 33, Tashkent, Uzbekistan D. Yakubjanova (B) · S. Kubaev Samarkand Branch of Tashkent University of Information Technology, Ibn Sino Street, 2, Samarkand, Uzbekistan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_128
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In the process of research and analysis of scientific publications in the field of development of object-oriented mathematical models to assess their application in machine-tractor units and cotton harvester’s operation under various driving conditions, the appropriate features were established. The study in [1] examines the technological process of a horizontal-spindle apparatus, and presents the experimental results obtained at test stations. In [2] presents the results of field tests of a semi-hitch horizontal-spindle cotton harvester. The possibility of its use in a zone with selected cotton varieties of high quality of the harvested cotton was established. In [3], the equations of motion of the machine unit of the cotton harvester and the cotton plant pullers were derived, their analytical solutions were obtained. Known and new models of cotton harvester’s productivity and the results of calculations of various tractors for their productivity are presented in [4]. The construction of object-oriented mathematical models of complex technical control systems is a complex scientific and technical problem, the assessment of which is mainly performed by the decision-maker. The whole difficulty of constructing this model lies in the fact that in order to obtain a solution, the model must be simple enough and, at the same time, it must reflect the essence of the problem, so that the results, obtained with it, have real physical meaning. When developing a mathematical model of vertical vibrations of the hitch system of a cotton harvester under various driving conditions, it should be taken into account that the hydraulic system of machine is functionally interconnected with its working system. A cotton harvester with a hitch system is an oscillating system consisting of several masses—a hopper, wheels, an engine, a cabin, and other units, interconnected by elastic constraints and dampers. These masses are divided primarily into sprung and unsprung masses. The sprung part of the CHM includes all of its elements, the weight of which is transferred to the elastic suspension device. The elements, the gravity of which is not transmitted through the elastic suspension device, are the unsprung CHM elements. The body and frame with mechanisms fixed on it are the sprung elements of the CHM, and the wheels with axles (bridges) are the unsprung elements. To study the vertical vibrations of the CHM, the Lagrange equation of the second kind is used; the second order differential equations describing the behavior of the dynamic model are derived with it. The equations of motion are obtained under the following assumptions: • vibrations of the machine and the wheels are low; • the characteristics of all elements are linear; • the axles of the CHM mass coincide with the main axles of the ellipsoid of inertia. In reality, a cotton harvester during its operation is exposed to external influences of a dynamic nature. The stochastic pattern of external influences substantially affects the performance of its units. There are various ways to reduce the influence of fluctuations in traction load on the output indices of the cotton harvester performance, one of which is the use of
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a hydrostatic transmission. Experimental testing of the efficiency of a CHM with a hydrostatic transmission of a power unit is difficult, expensive, and requires a lot of time [5]. Therefore, to assess the influence of fluctuations in the traction load, virtual studies are performed in order to identify the indices of the effect of hydrostatic transmission on the energy and other indices of the CHM under unsteady load modes, typical in real operating conditions. The CHM under consideration has a hydraulic system with three independent systems: the main system, the steering hydraulic system, and the rear axle hydraulic lock [6–8]. The task of the main hydraulic system is to provide the lifting and lowering of the hopper and devices. The random fluctuations of the traction load arising during the CHM operation, the amplitude of which reaches 30–40% of its average value, are a consequence of the effect of the field roughness on its aggregates, the non-uniform interaction of its working bodies with the soil, etc. Such a nature of the dynamic effect causes a change in the CHM engine operation, oscillations of the frame, increased slippage, which leads to a turn down operation.
2 Main Part Taking into account the above and in accordance with the design scheme presented in Fig. 1, a generalized mathematical model of vertical oscillations of the CHM MX-1.8 was compiled in the process of its moving along the roughness on the headland of a cotton field in the form of Lagrange equations of the second kind [9–12]: m m y¨m = Fy − b1 y˙m − y˙w1 − c1 ym − yw1 − b2 y˙m − y˙w2 − c2 ym − yw2 , 2 2 2π V 2π V m 1 y¨w1 = b1 y˙m − y˙w1 + c1 ym − yw1 − m 1 l 2 w1 h t 1 − cos l5 w1 t , 5 2π 2 Vw2 (m 2 − m 3 ) y¨w2 = b2 y˙m − y˙w2 + c2 ym − yw2 − (m 2 − m 3 ) l 2 2 h p 1 − cos jhc ϕ¨hc = Fhc · l6 − b3 (ϕ˙hc − ϕ˙rs ) − c3 (ϕhc − ϕrs ) − l7 · m a y¨m , jrs ϕ¨rs = b3 (ϕ˙hc − ϕ˙rs ) + c3 (ϕhc − ϕrs ) − l7 · m a y¨m , ϕ¨hc m hc y¨hc = ljhc , 7 −l6 jrs ϕ¨rs m rs y¨hc = l7 .
5
⎫ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ 2π Vw2 ⎬ t ,⎪ l 5
⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎭
(1)
J (q0 , u(t), q(t)) =
T
f 0 (q(t), u(t), t)dt + g 0 (q0 , g(T )) → min
t0
qi (0) = q0 (0), q˙i (0) = q˙0 (0), Vi (0) = V0 (0) qi (t) = q0 (t), q˙i (t) = q˙0 (t), Vi (t) = V0 (t) (i = 1, n), 0 ≤ t ≤ T,
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Fig. 1 Design scheme (CHM) of the dynamic model MX-1.8: a is dynamic model MX-1.8; b is top view of the hitching mechanism of harvesting machine; 1 is hydraulic cylinder; 2 is lever for connecting hydraulic cylinder; 3 is swinging shaft; 4 is levers for hitching the harvesting machines; 5 is harvesting machines
where y˙m and y¨m —are the linear speed and acceleration of the machine; y˙w1 and y¨w1 are the linear speed and acceleration of the front wheels; y˙w2 and y¨w2 are the linear speed and acceleration of the rear wheels; ϕ˙ hc and ϕ¨hc —are the angular velocity and acceleration of torsional vibratios of the hydraulic cylinder lever; ϕ˙r s and ϕ¨r s — are the angular velocity and acceleration of torsional vibrations of the rocker shaft lever; b3 is the coefficient of viscous resistance of the rocking shaft of the harvester hitch mechanism; c3 is the coefficient of rigidity of the rocking shaft of the hitch mechanism of harvesting devices; ma is the distributed mass along the harvesting device; mhc is the distributed mass along the hydraulic cylinder; mrs is the distributed mass along the rocking shaft; F hc is the force in the hydraulic cylinder of the harvester hitch mechanism; l1 , l 2 , l 3 , l 4 , and l 5 are the distances between the supports and
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Table 1 Parameter values of the CHM MX-1.8 operation under vertical vibrations at ht = 0.03 m Time, s
y˙m , m/s
y¨m , m/s2
1
2
3
4
5
6
7
8
9
10
0
0
1.647
12,706.7
0
0
0
0
0
0
0.1
0.098
0.647
4996.8
0.0768
1.2
6204.5
0.09
1.125
1505.33
0.2
0.18
0.7
5439.2
0.175
1.14
5849.9
0.179
1.06
1417.5
0.3
0.269
0.73
5639.9
0.268
1.09
5615.14
0.268
1.08
1457.6
0.4
0.357
0.7
5507.7
0.356
1.1
5698.6
0.356
1.12
1500.3
0.5
0.44
0.64
4940.06
0.439
1.2
6139.3
0.44
1.21
1627.2
0.6
0.5
0.5
3872.4
0.5
1.36
6979.05
0.5
1.38
1855.16
0.7
0.579
34
2653.2
0.573
1.55
7952.1
0.576
1.57
2101.3
0.8
0.63
0.25
1949.7
0.626
1.67
8535.6
0.629
1.66
2221.38
0.9
0.68
0.3
2336.9
0.68
1.6
8256.6
0.68
1.58
2113.15
1
0.742
0.53
4113.1
0.748
1.34
6848.4
0.745
1.3
1745.1
Fm, N
y˙w1 , m/s
y¨w1 , m/s
Fw1 , N
y˙w2 , m/s
y¨w2 , m/s2
Fw2 , N
roughness; l 6 is the length of the hydraulic cylinder lever; l7 is the length of the lever of the harvester hitch mechanism; jhc and ja are the moments of inertia of the levers for connecting the hydraulic cylinder and the harvester hitch mechanism. To solve the problem, an optimal control problem was formed. While testing the machines under the given operating conditions, the performance criterion was evaluated. The structure of optimal control of the guide wheels movement of a cotton harvester was obtained based on the Pontryagin maximum principle. To determine the auxiliary functions by a numerical method, a conjugate system with a variation of design parameters bi , ci , mi , ji —was studied [1, 9–12]. The computational experiment was conducted for the following parameter values: at tire deflection ht = 0.03 m; c1 = 16,722,278 N/m; b1 = 140,845.65 Nf/m; c2 = 850,200 N/m; b2 = 71,607.1 Nf/m; mm = 7714 kg; m1 = 5114 kg; m2 = 2600 kg; m3 = 1262 kg; ma = 675 kg; jhc = 552.96 Nms2 ; jrs = 276.48Nms2 ; r 1 = 0.785 m; r 2 = 0.43 m; hp = 0.07 m; ht = 0.03 m; Vm = 1.21 m/s; Fy = Fm sinα = 12, 970sin45 deg = 12, 706.7 H ; Fhc = 2215 H (Tables 1 and 2, Figs. 2, 3 and 4). The computational experiment was conducted for the following parameter values: at tire deflection ht = 0.04 m; c1 = 1,254,208.5 N/m; b1 = 105,634. Nf/m; c2 = 637,650 N/m; b2 = 53,705.3 Nf/m; mm = 7714 kg; m1 = 5114 kg; m2 = 2600 kg; m3 = 1262 kg; ma = 675 kg; jhc = 552.96 Nms2 ; jrs = 276.48 Nms2 ; r1 = 0.785 m; r2 = 0.43 m; hp = 0.07 m; ht = 0.03 m; Vm = 1.21 m/s; Fy = Fm sinα = 18, 050sin45 deg = 12, 763.277 H ; Fhc = 2225 N (Tables 3 and 4; Figs. 5, 6 and 7).
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Table 2 Operation parameters of the CHM MX-1.8 hitch system under torsional and vertical vibrations at h = 0.03 m Time, s
ϕ˙ hc , rad/s
ϕ¨hc , rad/s2
Mhc, Nm
y˙hc , m/s
y¨hc , m/s2
Fhc, N
1
2
3
4
5
6
7
0
0
– 1.16
– 642.25
0
– 4.0
– 2214.68
0.1
– 0.016
3.7
207.48
– 0.05
1.29
715.44
0.2
– 0004
3.56
197.09
– 0.014
1.23
679.63
0.3
0.003
2.9
160.37
0.011
1.0
553.02
0.4
0.0075
2.947
162.96
0.026
1.06
561.94
0.5
0.016
0.4
222.44
0.0567
1.387
767.05
0.6
0.0388
0.6
339.98
0.134
2.12
1172.36
0.7
0.08
0.86
477.3
0.28
2.97
1645.8
0.8
0.14
1.016
562.03
0.487
3.5
1938.03
0.9
0.2
0.958
530.03
0.71
3.3
1827.7
1
0.25
0.62
342.43
0.87
2.135
1180.8
Fig. 2 Change pattern in the parameters of CHM MX-1.8 movement under vertical vibrations at ht = 0.03 m
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Fig. 3 Change pattern in torsional vibrations of the hitch system of the MX-1.8 cotton harvester at ht = 0.03 m
Fig. 4 Change pattern in vertical vibrations of the hitch system of the CHM MX-1.8 at ht = 0.03 m Table 3 Operation parameters of the CHM MX-1.8 under vertical vibrations at h = 0.04 m Time, s
y˙m , m/s
y¨m , m/s2
Fm, N
y˙w1 , m/s
y¨w1 , m/s
Fw1 , N
y˙w2 , m/s
y¨w2 , m/s2
Fw2 , N
0
0
1.65
12,763.27
0
0
0
0
0
0
0.1
0.1
0.63
4884.14
0.07
1.22
6265.5
0.9
1.2
1613.58
0.2
0.18
0.68
5267.3
0.17
1.19
6095.5
0.18
1.04
1400.42 (continued)
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Table 3 (continued) Time, s
y˙m , m/s
y¨m , m/s2
y˙w1 , m/s
y¨w1 , m/s
Fw1 , N
y˙w2 , m/s
y¨w2 , m/s2
0.3
0.27
0.728
0.4
0.358
0.7
5620.28
0.269
1.1
5698.6
0.269
1.08
1444.36
5545.06
0.358
1.11
5708.5
0.357
1.128
1509.7
0.5
0.444
0.6
0.52
0.64
4988.87
0.44
1.2
6136.8
0.44
1.22
1637.58
0.5
3915.4
0.513
1.36
6890.6
0.516
1.39
0.7
0.583
1867.28
0.346
2668.09
0.57
1.56
7977.09
0.578
1.58
2118.09
0.8 0.9
0.63
0.25
1927.9
0.628
1.68
8596.8
0.63
1.67
2238.47
0.683
0.29
2288.39
0.683
1.63
8354.18
0.684
1.58
2120.7
1
0.74
0.53
4099.35
0.75
1.35
6923.6
0.749
1.3
1740.31
Fm, N
Fw2 , N
Table 4 Operation parameters of the CHM MX-1.8 hitch system under torsional and vertical vibrations at h = 0.04 m Time, ϕ˙ hc , s rad/s
ϕ¨hc , rad/s2
Mhc , Nm
y˙hc , m/s
y¨hc , m/s2
Fhc , N
0
0
– 1.166
– 645.068
0
– 4.02
– 2244.37
0.1
– 0.00227
0.37
205.43
– 0.078
1.28
708.377
0.2
– 0.0083
0.398
220.55
– 0.0287
1.375
760.53
0.3
0.0023
0.32
179.05
0.008
1.1
617.43
0.4
0.008
0.3
166.74
0.0285
1.04
574.96
0.5
0.0169
0.39
218.04
0.058
1.36
751.9
0.6
0.038
0.6
335.5
0.13
2.09
1156.9
0.7
0.08
0.86
476.8
0.277
2.97
1644.2
0.8
0.14
1.026
567.54
0.485
3.54
1957.04
0.9
0.2
0.97
540
0.71
3.36
1862.08
1
0.25
0.637
352.53
0.88
2.2
1215.6
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Fig. 5 Change pattern in the CHM MX-1.8 motion parameters under vertical vibrations at ht = 0.04 m
Fig. 6 Change pattern in torsional vibrations of the hitch system of the MX-1.8 cotton harvester at ht = 0.04 m
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Fig. 7 Change pattern in vertical vibrations of the hitch system of cotton harvester MX-1.8 at ht = 0.04 m
3 Conclusions Thus, the uniform movement of the machine depends on the mass and parameters of the controlled axles, the values of which are determined by the numerical solution of system (1) and the conjugate system with a variation of the motion parameters Fi , Mi and design parameters b, c, mi , ji for given road roughness. The physical meaning of the results obtained can be formulated as follows. If, at the initial point of time, the necessary conditions are met, then the optimal performance is reached with the following controls. On the time interval [t0 , t] the transportation force up (t) = + 1 has a maximum value. This means that on the interval [t0 , t] a “full speed ahead” mode occurs—and the speed increases to V m = 0.554 … 0.711 m/s, and at this point of time, the wheels of the harvester rise to the upper edge of the roughness. On the interval [t, T] the machine descends, and at this moment the transportation force turns to up (t) = –1, i.e., there is to a “full back” mode, ensuring the uniform movement of the guide wheels of the cotton harvester. The results obtained by solving the mathematical models of vertical vibrations of the CHM MX-1.8 and hitch systems in the process of moving over the roughness on the headland of the cotton field are in satisfactory agreement with the experimental data. The results of computational experiments show that the values of machine vibration and of the left and right harvesting devices decrease at ht = 40 mm. Left and right harvesting devices vibrate uniformly under vertical oscillation of the machine when the hydraulic cylinder for raising and lowering the harvesting devices is installed in the middle of the rocker shaft. The main reason for the non-uniform oscillation of the left and right harvesting devices is the arrangement of the lever that connects the hydraulic cylinder not in the middle of the rocker shaft, but on the left edge.
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References 1. Azimov BM, Usmanov II, Ruzikulov AR, Mirkhaitov UT, Yakubjanova DK (2016) Modeling, optimal motion control and calculation of the components of lateral forces of the guide wheels of the MX-1.8 cotton harvester. Uzbek J Prob Inf Energy 2:50–60 2. Spevakov R, Ravshanov S, Nishanaliev S (2015) Test results of a semi-hitch horizontal-spindle cotton harvesting machine. Tract Agri Mach 4:42–44 3. Tiloev S (2008) Equations of motion of the machine unit of a cotton harvester and a cotton plant puller. Bull Saratov State Agr Univ 2:80–82 4. Yuldashev SU, Rizaev AA, Yuldashev AT, Kuldashev DA (2010) Modeling and calculation of the productivity of cotton harvesting machines. Tract Agri Mach 2:35–38 5. Lebedev OV, Mukhitdinov AA (2004) The theory of motion of a wheeled vehicle. Tashkent, Publishing House of TADI, p 100 6. Vasiliev FP (1988) Numerical methods for solving extreme problems. Nauka, Moscow, pp 421–485 7. Guskov VV, et al (1988) Tractors: theory. Mechanical Engineering, p 33−35 8. Smirnov GA (1990) The theory of motion of wheeled vehicles. Mechanical Engineering, p 145−230 9. Afanasyev VN, Kolmanovskiy VB, Nosov VR (1989) Mathematical theory of design of control systems. Higher school, p 162−163 10. Azimov BM, Yakubjanova DK (2018) Imitation modeling and calculation of the parameters of Lateral forces components of guide wheels of Cotton-picker MH-1.8. Int J Adv Res Sci Eng Technol 5(1):5024–5032 11. Azimov BM, Yakubjanova DK (2018) Simulation and optimal motion control of cottonharvesting machines MX-2.4 and the hitch system of harvesting units under vertical oscillations. J Adv Res Dyn Control Syst 10(9-Special Issue):2513–2528 12. Azimov BM, Yakubjanova DK (2019) Modeling and optimal control of motion of cotton harvesting machines MX-1.8 and hitch systems of picking apparatus under vertical oscillations. IOP Conf Ser: J Phys 1210:012004. https://doi.org/10.1088/1742-6596/1210/1/012004
Energy Efficiency of an Orthogonal Balanced Wind Turbine Blade Valery Prokopiev
and Andrey Proskurin
Abstract Recently the problem of the structural stability of buildings gained great importance all over the world. In the context of Earth’s natural energy resources crisis one of the possible solutions would be using the wind power, which is already being widely applied due to wind generators. In this article, a numerical three-dimensional finite element model of the aerodynamic flow around an orthogonal balanced blade is used to evaluate the energy efficiency of a wind generator. Keywords Numerical simulation · Aerodynamic processes · Ansys CFD · Energy efficiency · Alternative energy sources in construction · Wind turbine · Wind turbine blade · Navier-Stokes equations
1 Introduction The task of creating energy-independent buildings in the modern world is very important for the whole world. The resources of the earth are inexorably running out and mankind needs to place great emphasis on the development of new alternative energy sources. Modern architectural solutions in the construction of metropolitan areas seek to use high-tech photovoltaic facades and flexible solar membranes to obtain the solar energy needed for the construction of capital construction projects. Through the combined use of wind and solar energy, we have the opportunity to design a building that integrates different methods of generating clean energy, which, in turn, will bring the building to its intended full self-sufficiency in electricity.
V. Prokopiev (B) · A. Proskurin Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, Moscow 129337, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_129
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Table 1 Characteristics of the calculated grid Hydraulic diameter
Reynolds number
Calculated Y+
Calculated distance Mesh thickening in from the wall the longitudinal direction
0.38
5.0e + 4
80
1.0e–2
1.0e–2
2 Materials and Methods Parameters of a single-bladed orthogonal high-efficiency turbine. (US Patent Victorlyatkher, US 8007235 B1, August 30, 2011, Russian Patent 2426911 C1) are used to evaluate energy efficiency. Since the profile of the investigated blade corresponds in cross-section to the aviation profile NACA-0021, the geometric characteristics are selected in accordance with the reference materials [1]. The aim of the work is to test the technique of numerical modeling of a rotating blade under the influence of an aerodynamic load during non-stationary flow around a turbulent flow in a three-dimensional formulation. The calculation study consists in determining the aerodynamic characteristics and an average assessment of the energy efficiency of the installation. As a research method, we used computer modeling of wind turbine blade flow with air flow in the ANSYS software package [2]. The characteristics of the computational grid of the computer model are shown in Table 1.
3 Boundary and Initial Conditions Parameters of the calculations [3–10]. Since the geometry at the beginning of the flow action is represented as a semicircle, the flow at the “inlet” was set taking into account the angle of curvature and the normal speed of 2 m/s with a percentage of turbulence equal to 7%. At the outlet, the flow is given “soft” opening boundary conditions with a relative pressure of zero and the same turbulence parameters as at the inlet. Conditions for “sliding walls” (U = V = W = 0 m/s) were established at the lower and upper boundaries. We set the condition for the rigidity of the body with the possibility of rotation around the Z axis and also set the angular speed of rotation. The cylindrical region was created as a subdomain with the adjustment of the recalculation of the finite element grid due to the rotation of the blade. The subdomain, domain interfaces, and blade should share the same air characteristics. This is necessary because the inner cylinder and the solid should move and rotate at the same speed for the proper isolation of movement. All relative movements between the inner cylinder and the blade will be eliminated, which will cause the zero grid to deform inside the inner cylinder (Fig. 1). The subdomain is not strictly necessary for decoupling rotational movements. However, the subdomain increases the reliability of the simulation by ensuring that
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Fig. 1 Boundary conditions
the entire mesh inside the inner cylinder has the same physical properties as the rigid body, and not just at the blade boundary and the inner interface of the cylinder [8]. The interface of a single domain has been modified to limit the rotational movement of the grid surrounding the subdomain. The grid located on the internal cylindrical interface of the domain will have the same physical properties as in solid form. To set the blade as a solid body, the weight of the entire blade was used, which was 250 kg. Since rotation cannot start without third-party assistance, the initial angular velocity was initialized without other third-party accelerations. The interface of the second domain was configured in a way that the air flow passed from one computational domain to another without any loss of properties. Both areas of the larger radius and the smaller one are stationary and do not require special settings for the finite-volume grid [11, 12].
4 Results of the Study Below there are main results of the calculated studies performed during the rotation of the wind turbine blade at different points in time, and the analysis of aerodynamic characteristics is made (Figs. 2, 3, 4, 5 and 6). The graphs of the studied forces show the non-stationarity of the simulated process, each wave corresponds to 1 rotation of the blade.
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Fig. 2 Velocity and pressure fields at the zero position of the blade (after the full flow of air)
Fig. 3 Velocity and pressure fields with partial rotation of the blade (after the full flow of air, at time t = 0.75 s)
5 Calculation of Energy Efficiency Unfortunately, the initial data are not sufficient for a complete analysis of energy efficiency data, but knowing the dimensions allow us to determine the amount of energy produced according to the area of sweeping. Depending on the size of the sweeping area, we can conclude that at different speeds, the level of energy produced will be the following (Table 2).
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Fig. 4 Fields of velocities and pressures at the zero position of the blade (after a complete run-up of the air flow, at the time t = 1 s)
Fig. 5 Velocity and pressure fields at the zero position of the blade (after the full flow of air, at time t = 1.25 s)
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Fig. 6 Graphics represent aerodynamic characteristics during the rotation of the blade a Lift force in time b Drag force in time
Table 2 Summary table of generated energy Flow rate, m/s
Air density, kg/m 3
2
1.185
5
1.185
10
1.185
11.8
15
1.185
39.8
20
1.185
94.4
25
1.185
184.3
Amount of generated energy, kW 0.09 1.475
6 Conclusions The frequency analysis, see Fig. 6, shows the coincidence with the blade rotation frequency, while the rotation speed remains constant, the time of 1 rotation of the blade is 1.7 s. This may indicate that the wind generator rotates in normal mode. The study shows the efficiency of the method for calculating the blade, taking into account the run-up of the blade from the influence of air flow. As can be seen in Table 2, at a flow rate of 25 m/s, the blade can provide a complete supply of energy to a small house. This allows us to conclude that a large number of such generators will be able to replace the current “harmful” power plants with more environmentally friendly ones.
References 1. Garbaruk AV, Strelets MKh, Shur ML (2012) Turbulence modelling in combined flow calculations. Tutorial, St. Petersburg
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2. Lutsky AE, Severin AV (2013) The simplest implementation of the method of wall functions. Preprints of the Keldysh Institute M.V. Keldysh, p 38 3. Handbook of aviation profiles 4. Schlichting G (1974) Boundary layer theory. Nauka, Moscow 5. Gorlin SM (1970) Experimental aerodynamics. Vysshaya Shkola, Moscow 6. ANSYS, Inc. (2014) ANSYS 15 Help 7. Tominaga Y, Mochida A et al (2008) AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. J Wind Eng Ind Aerodyn 96:1749–1761 8. Garbaruk AV, Strelets MK, Shur ML (2012) Turbulence modelling in complex flow calculations. Tutorial, SPb 9. Lutsky AE, Severin AV (2013) The minimal realization of the wall functions method. Keldysh Inst Pre 38:22 10. Berg OI (2015) Principles of construction and elements of control systems for autonomous power supply complexes based on renewable energy sources, p 88 11. Prokopiev VI, Lantsova IY, Proskurin AY (2018) Numerical simulation of aerodynamics of a high-efficiency orthogonal balanced blade of a wind generator. MATEC Web Conf 251:04063 12. Tominaga Y, Mochida A et al (2008) AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. J Wind Eng Ind Aerodyn 96(10–11):1749–1761
Study of the Influence of Design and Technological Parameters of a Horizontal Mixer on Its Performance Indicators Petr Savinykh , Nikolay Turubanov , and Fedor Kipriyanov
Abstract To obtain high-quality livestock products, it is necessary to use feed that is balanced in terms of nutritional value. Horizontal mixers allow getting feed with a high uniformity of distribution of components, so they should be preferred when preparing feed directly on farms. The paper presents the results of experimental studies of the influence of changing the parameters of a horizontal mixer with a combined working body on its performance indicators, which make it possible to obtain approximate mathematical models of the working process. The coefficients in the equations make it possible to assess the influence of the studied factors on the considered optimization criteria. The resulting mathematical models make it possible to construct two-dimensional sections of the response surfaces, which visually represent the dependence of the mixer performance on the magnitude of the change in factors. The results of experimental studies were obtained by employees of the laboratory of animal husbandry mechanization at the production base of the FSBSI FASC of the North-East region. The conducted studies allow increasing the homogeneity of compound feed obtained in horizontal mixers with belt augers, reducing the energy consumption of mixture preparation and increasing their throughput. Thus, according to the results of experimental studies, the uniformity coefficient of the finished product reaches the highest value of 94.2% when the mixing chamber is loaded with 50%, the rotational speed of the combined screw shaft is 12.9 min−1 , the mixing time is 18 min, while the specific energy costs are 4.54 kW*h/t and throughput is 1.45 t/h. The conducted studies allow concluding that in order to obtain a mixture of the best quality, the speed of the shaft of the combined auger should be within 13…15 min−1 , the mixing time of the feed components should be 18 min, the loading of the mixing chamber of a horizontal mixer with a belt auger should be 50…60% of the maximum.
P. Savinykh · N. Turubanov Federal Agrarian Science Center of the North-East Region, Lenin’s Street, 166-a, Kirov 610007, Russia F. Kipriyanov (B) Vologda SDFA, Shmidta, 2, Vologda-Molochnoe 160555, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_130
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Keywords Mixer · Mixing · Compound feed · Experimental studies · Response surfaces · Mathematical models
1 Introduction To obtain high-quality livestock products, it is necessary to use feed that is balanced in terms of nutritional value. Compound feed can be prepared directly on farms or purchased at feed mills. The advantage of on-farm feed preparation is that the local feed base is taken into account, the time and costs for transportation and storage of both components and finished products are reduced. For households with a small consumption of mixed fodder, the independent preparation of feed will be the most relevant [1, 2]. The homogeneity of the prepared feed directly depends on the quality of mixing components, and, accordingly, on the correct choice of the mixer [3, 4]. Horizontal mixers with belt augers make it possible to obtain feed with a high uniformity in the distribution of components [5, 6]. In such mixers, there is an intensive interaction of the components and their mixing, there is no hanging of the material, the finished feed mixture is unloaded completely [7]. Mathematical models obtained from the results of experimental studies describe the operation of the mixer and make it possible to determine its optimal technological and design parameters. Based on the obtained models, it is possible to build response surfaces that clearly show the dependence of the value of the considered optimization criteria on the values of the studied factors [8–10]. Thus, the study of the mixing process in horizontal ribbon mixers remains relevant today.
2 Materials and Methods The object of research is: the technological process of mixing feed components. The purpose of the study is: to determine the effect of changing the parameters of the mixer on the performance of its work. Employees of the laboratory of mechanization of animal husbandry on the basis of the Federal State Budgetary Scientific Institution Federal Agrarian Science Center of the North-East region made a horizontal mixer with a belt auger and carried out its experimental studies. The novelty of the design is confirmed by RF patent No. 2638978. The mixer consists of a body 1, a mixing chamber 2, a belt auger 3, a loading pipe 4, an unloading pipe 5, an engine 6, a gearbox 7 (Fig. 1b). The design of the screw allows moving the material in layers inside the mixing chamber. This movement of the material allows improving the quality of the finished product, reduce mixing time. The belt auger ensures that the mixture is completely discharged from the mixing chamber. When conducting experimental studies, crushed rye was chosen as the main component of the mixture. The average particle size was 0.8 mm. Peas were taken
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4
1 2 3 7
5
6
Fig. 1 Mixer: a general view of the mixing chamber; b design and technological scheme: 1—body; 2—mixing chamber; 3—belt auger; 4—loading pipe; 5—unloading pipe, 6—engine; 7—reducer
as a control component. The amount of the control component in the mixture during research is 12.5% [11]. The mixer shaft speed was changed using an Altivar ATV-312 frequency converter. The main technological indicators of the mixing process were determined by the following formulas. The power on the mixer screw shaft was determined by the following expression: Ns = Nel · η p · ηr ed · ηch ,
(1)
where Nel —power measured by a wattmeter, kW; ηb —belt drive efficiency; ηr ed — reducer efficiency; ηch —chain drive efficiency. Specific energy consumption was determined by the formula qel =
Nel , Q
(2)
where Nel —electric motor power, kW; qel —specific energy consumption, kW/h·t; Q—mixer throughput, t/h. The quality of mixing the feed components is determined by statistical characteristics. The main characteristic is the coefficient of heterogeneity in the distribution of the control component in the finished product Vc =
(xi −x)2 n−1
x
· 100%,
(3)
wherexi —the current value of the observable; x arithmetic mean of the observable x = nxi ; n– number of samples. The degree of homogeneity of the finished mixture was calculated by the formula ν = 100 − Vc .
(4)
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II
I
III
A B C a
b
Fig. 2 Sampling scheme in the mixer: a in the horizontal plane; b in a vertical plane 2
1
4
3
Fig. 3 Sampler: 1—housing; 2—inner pipe; 3—window for sampling; 4—marks for determining the depth of immersion of the sampler
When conducting experimental studies, after the completion of the mixing process, samples were taken to assess the homogeneity of the resulting mixture. Samples were taken from the mixing chamber according to the scheme shown in Fig. 2. The device shown in Fig. 3 was used as a sampler. Sampling was carried out according to the Russian State Standard GOST R ISO 6497–2011. The selected samples were placed in hermetically sealed bags (Fig. 4a) indicating the sampling area according to Fig. 2. Next, the sample was divided into a base and a control component using a set of sieves, and their weight was determined on a balance (Fig. 4b).
3 Results and Discussion To determine the effect of changing the parameters of the mixer on the performance of its work, the authors used the method of planning a multifactorial experiment. Based on the results of the single-factor experiments, the most significant factors and their variation intervals were determined [11]. As factors, the influence of which was studied, the following were chosen: x1—mixer shaft rotation frequency, min–1 ; x2—loading value of the mixing chamber, %; x3—mixing time, min. The following were chosen as indicators of the mixer operation: y1—coefficient of homogeneity
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b)
Fig. 4 General view: a samples in bags; b the control component on the scales
Table 1 Intervals and levels of factor variation Variation levels
Mixer shaft speed, min −1 x1
x2
x3
Upper (+1)
21.5
75
18
Medium (0)
17.2
62.5
15
Lower (−1)
12.9
50
12
Mixing chamber load, %
Mixing time, min
of the mixture ν, %; y2—specific energy consumption, kW*h/t; y3—throughput capacity, Q, t/h. When conducting experimental studies, the Box–Behnken design matrix was used. Intervals and levels of factor variation are given in Table 1. The computer-processed results of experimental studies made it possible to obtain the following equations of mathematical models that describe the change in the performance of the mixer depending on the level of factor variation: y1 = 90.92 − 0.95 · x2 − 0.36 · x3 + 0.58 · x1 · x2 − 0.39 · x1 · x3 − 0.62 · x2 · x3 + 1.11 · x32 ;
(5)
y2 = 3.37 − 0.47 · x2 + 0.53 · x3 + 0.10 · x22 − 0.08 · x2 · x3 ;
(6)
y3 = 2.09 + 0.42 · x2 − 0.34 · x3 − 0.07 · x2 · x3 + 0.06 · x32 .
(7)
The Fisher criterion allows checking the significance of the obtained mathematical models (5), (6) and (7). The criterion value obtained as a result of calculations was compared with the table value. If the calculated value is higher than the table one, the explained variance is greater than the unexplained one, and in this case the mathematical model is significant [12, 13]. For Eq. (5) Fcalc = 129.81 > Ftabl =
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4.07, for Eq. (6) Fcalc = 2360.86 > Ftabl = 4.26, for Eq. (7) Fcalc = 74,068.07.05 > Ftabl = 4,26, thus, all obtained mathematical models are significant. The estimation of the significance of the coefficients in the equations of mathematical models 5, 6 and 7 was carried out according to the Student’s t-test. The calculated value of the Student’s criterion was compared with the table. If the calculated value of the criterion is greater than the table value, then the coefficient in the equation of the mathematical model is significant [12, 13]. The R-Squared value shows how exactly the equation of the mathematical model corresponds to the change in the optimization criterion. Thus, according to the statistical data, the resulting mathematical model 5 describes the change in y1 by 97.48% depending on the value of the factors included in the equation. The mathematical model 6 describes the change in y2 by 99.82%, the model 7 describes the change in y3 by 99.99%. Thus, we can conclude that all the obtained regression equations reliably describe the change in the homogeneity coefficient of the mixture, specific energy consumption and throughput depending on the variation of factors [11–13]. The numerical values in the obtained equations of mathematical models made it possible to determine the influence of the studied factors on the performance of the mixer. Based on the value of the coefficients included in the equations of mathematical models 5, 6 and 7, we can conclude that the greatest influence on the quality of mixing ν (y1) has the degree of filling of the bunker (x2), while the rotational speed belt screw shaft (x1) does not directly affect the quality of the finished product, but only in combination with other factors. The change in the frequency of the belt screw shaft (x1) does not affect the specific energy consumption q (y2) and throughput Q (y3) (the factor (x1) is not included in the equations), while the mixer load (x2) and mixing time (x3) have the same effect on both optimization criteria. An analysis of the equations of models 5, 6 and 7 and two-dimensional sections of the response surfaces shown in the figure allow us to draw the following conclusions. Figure 5a shows that with a decrease in the amount of material in the mixing chamber (x2) from 75 to 50%, and a decrease in the rotational speed of the mixer screw shaft x1 from 21.5 to 12.9 min–1 , when the components are mixed for 18 min, there is an increase in mixture homogeneity coefficient ν from 90.28% to 94.2% and specific energy consumption q from 3.44 to 4.54 kW*h/t. The maximum value of the homogeneity coefficient of the finished product ν = 94.2% is achieved at the speed of the belt screw shaft x1 = 12.9 min–1 , the mixer load x2 = 50% and the mixing time x3 = 18 min, while the value of specific energy consumption is q = 4.54 kW*h/t and throughput is Q = 1.45 t/h. The minimum value of specific energy consumption q = 2.54 kW*h/t is achieved with the mixer load x2 = 75%, mixing time x3 = 12 min, while the screw speed (x1) does not affect the value of specific energy consumption q and the value of the coefficient homogeneity of the finished product is ν = 92.06%. Analysis of Fig. 5b shows that with an increase in the amount of material in the mixing chamber (x2) from 50 to 75% and a decrease in mixing time (x3) from 18 to 12 min at a speed of the belt screw shaft x1 = 21.5 min–1 , there are an increase in throughput Q from 1.45 t/h to 2.98 t/h and an increase in the homogeneity coefficient
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x3=1,0
1
90,5
x2
3,6
x3 90,5
0
4,0
1,88
92,5 4,2
93,0
-1
94,0
-1
0 a)
2,20 91,5
91,0 2,52
92,0
4,4
93,5
91,5
3,8
91,5
92,0
92,0
1,56
91,0
0
x1=1,0
1
90,0
1291
x1
1
-1
2,84 93,0
92,5
-1
0 b)
x2
1
Fig. 5 Two-dimensional sections of the response surface, characterizing the influence of the speed of the mixer belt screw shaft (x 1 ), the amount of loading of the mixing chamber (x 2 ) and the mixing time (x 3 ) on: a the uniformity coefficient of the finished product ν ( -y1 ) and specific energy consumption q ( -y3 ); b coefficient of homogeneity of the finished product νn ( -y1 ) and throughput of the mixer Q ( -y3 ).
of the finished mixture ν from 92.28% to 93.02%. At the maximum value of the homogeneity coefficient of the mixture ν = 94.2%, the throughput will be Q = 1.45 t/h. Throughput Q reaches a maximum value of 2.98 t/h with a mixer load x1 = 75%, mixing time x3 = 12 min, while the screw speed (x2) does not affect the throughput, and the uniformity coefficient of the finished product ν is 93.02%. Thus, based on the results of experimental studies, mathematical models of the working process of a horizontal ribbon mixer were obtained, which made it possible to determine the optimal design and technological parameters at which the value of the homogeneity coefficient of the finished product reaches the highest value ν = 94.2% with the mixer load x2 = 50%, frequency rotation of the belt screw shaft x1 = 12.9 min–1 , mixing time x3 = 18 min, while the value of specific energy consumption is q = 4.54 kW*h/t, and the throughput is Q = 1.45 t/h.
4 Conclusions Based on the results of experimental studies, mathematical models of the working process of a horizontal mixer with a belt screw were obtained, which made it possible to determine the optimal design and technological parameters of its operation, at which the value of the homogeneity coefficient of the finished product reaches the highest value ν = 94.2% at a mixer load of 50%, rotational speed of the belt screw shaft 12.9 min−1 , mixing time 18 min, while the value of specific energy consumption is q = 4.54 kW*h/t, and the throughput is Q = 1.45 t/h.
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According to the results of experimental studies, it can be said that for optimal operation of the mixer and obtaining the maximum value of the compound feed uniformity coefficient, the speed of the belt auger shaft should be within 13 … 15 min−1 , the mixing time of the components should be 18 min, the horizontal mixer should be loaded within 50 … 60% of the maximum.
References 1. Marczuk A, Sysuev V, Aleshkin A et al (2021) Theoretical studies of the interaction between screw surface and material in the mixer. Mater Link Disabled 14(4):1–29. https://doi.org/10. 3390/ma14040962 2. Boerman JP, Hornback WC, Beever DE et al (2021) Effects of physical preparation of diets and inclusion rate of modified wet distillers grains with solubles on production and rumen measurements of lactating dairy cows. J Dairy Sci 104(2):1680–1695. https://doi.org/10.3168/ jds.2020-18777 3. Adusei-Bonsu M, Amanor IN, Obeng GY, Mensah E (2021) Performance evaluation of mechanical feed mixers using machine parameters, operational parameters and feed characteristics in Ashanti and Brong-Ahafo regions, Ghana. Alex Eng J 60(5):4905–4918. https://doi.org/10. 1016/j.aej.2021.03.061 4. Addo A, Bart-Plange A (2008) Performance evaluation of two on-farm feed mixers. Agri Mech Asia Africa Latin Am 39(3):57–60. www.scopus.com 5. Wang D, Jiang Y (2006) Experimental study on the twin-shaft horizontal total mixed ration mixer. Nongye Gongcheng Xuebao/Trans Chin Soc Agri Eng 22(4):85–88. www.scopus.com 6. Wang D (2006) Analysis of mixing principle on twin-shaft horizontal total mixed ration mixer. Nongye Jixie Xuebao/Trans Chin Soc Agri Mach 37(8):178–182. www.scopus.com 7. Kushnir V, Gavrilov N, Kim S (2016) Justification of the design of the two-shaft mixer of forages. Proc Eng 150:1168–1175. https://doi.org/10.1016/j.proeng.2016.07.231. www.sco pus.com 8. Savinyh P, Aleshkin A, Turbanov N, Ivanovs S (2020) Investigation of impact of technological and structural parameters upon energy indicators of work of mixer. 19th Int Sci Conf Eng Rural Dev Proc – Jelgava 19:1338–1348 9. Marczuk A, Misztal W, Savinykh P, et al (2019) Improving efficiency of horizontal ribbon mixer by optimizing its constructional and operational parameters. Eksploatacja I Niezawodnosc – Maintenance Re-liability 21(2):220–225. https://doi.org/10.17531/ein.2019.2.5 10. Ma P, Li L, Wen B, Xue Y, Kan Z, Li J (2020) Design and parameter optimization of spiraldragon type straw chopping test rig. Int J Agri Biol Eng 13(1):47–56. https://doi.org/10.25165/ j.ijabe.20201301.4927 11. Marczuk A, Caban J, Savinykh P, Turubanov N, Zyryanov D (2017) Maintenance research of a horizontal ribbon mixer. Eksploatacja I Niezawodnosc – Maintenance and Reliability 19(1):121–125https://doi.org/10.17531/ein.2017.1.17 12. Garneoui S, Keppler I, Korzenszky P (2020) Mixing enhancement of wheat granules in a hopper bottom lab-scale mixer using discrete element simulations. FME Trans 48(4):868–873. https:// doi.org/10.5937/fme2004868G 13. Lyashuk OL, Sokil MB, Klendiy VM et al (2018) Mathematical model of bending vibrations of a horizontal feeder-mixer along the flow of grain mixture. INMATEH – Agri Eng 55(2):35–44. www.scopus.com
The Effect of Environmental Factors and Institutional Pressures on Construction Firms’ Performance: A Proposed Model Hassan Fehan
and Osaro Aigbogun
Abstract Purpose—As the construction industry evolves, a higher requirement is set on construction firms to improve their accountability to customers’ specifications by executing their projects based on specified criteria (time, cost, quality). However, several factors prevent effective and efficient performance management in construction firms. Efforts aimed towards understanding the impacts of these factors, such as environmental factors and institutional pressures on the performance outcomes of the construction firm, have led to empirical and theoretical controversy in mainstream construction management research. Design/methodology/approach— The study’s objectives were to examine the reliability and the validity of the adapted instrument’s construct measures in the ongoing study and develop a conceptual model comprising antecedent factors affecting Syrian construction firms’ performance. Primary data were collected from 197 respondents using a structured questionnaire, and data analysis was done using Smart-PLS 3.0 to assess the PLS-SEM measurement model. Findings—The findings show that the instrument is reliable and indicates strong rational validity proof. Originality/value—The research is of great significance because it explored the impact that vital environmental factors together with institutional pressures have on the performance outcomes of construction firms, and this is critical to improving effective performance management systems in construction firms. Moreover, the validation of the instrument will aid subsequent explorations of the subject matter. Keywords Transportation safety systems · Construction firms · Environmental factors · Performance measures · Institutional pressures · Reliability · Validity · Smart PLS
H. Fehan (B) Binary University of Management and Entrepreneurship, No 1, IOI Business Park, Bandar Puchong Jaya, 47100 Puchong, Selangor, Malaysia e-mail: [email protected] O. Aigbogun Curtin University Malaysia, CDT 250, 98009 Miri, Sarawak, Malaysia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_131
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1 Introduction and Background Due to its importance in economic growth and its critical position in a countries development plan, over the past few years, both scholars and professionals have emphasized the constraints faced by the construction industry [1]. The construction industry is regarded as a fractured and complicated field that faces relentless obstacles and tremendous demands. Therefore, to improve their competitive advantage and outperform their rivals, construction firms need to be more customer-oriented, flexible, and effective [2]. In order to stay relevant in the business environment that is both hyper-competitive, as well as, ever-changing, it is crucial that firms in the construction industry constantly enhance their performance [3]. For construction firms to identify best practices, an essential initial step is to carry out periodic performance evaluations and compare previous performance to recognize performance gaps and benchmark their standings relative to competitors. Despite the fact that there are significant evidences of awareness of performance management practices within the construction industry, there are significant problems relating to the rationale and model, implementation as well as application of these practices, and the transmission of non-adaptive effects compared to those expected in various countries [4]. Presently, construction organizations need viable information across a wide range of activities beyond that which the conventional measures of performance have the capabilities to provide; concurrently, decision-makers are supposed to select the policy which increases their expected utility over all possible outcomes [5]. Critiques such as [6] suggest that the role of performance management is not yet well known, at least in the rapidly evolving construction industry, and maybe subtly influenced by factors that are presently not fully described. Though the outcomes of performance, especially immediately after measurement, provide several benefits to those who utilize it for such purposes as evaluation, control, and the advancement of business operations; the factors which influence performance are, as yet, still being studied and examined inadequately at the organizational level. These factors can be implemented in order to improve the firm’s performance and place it on a higher level [7]. Drawing on institutional arguments, research scholars have debated the different factors that influence firm performance and have increased attention in their inquiries to explain heterogeneous performance outcomes [8]. On the one hand, several scholars have concluded that pressures such as environmental factors, either internal (under control the firms) or external (beyond control the firm), have a powerful impact on firm performance [9]. [10], drawing from his study on the Nigerian construction industry, stated that the political environment is the most crucial factor affecting local (medium and large) contractors’ performance, and the influence of social and political environmental variables impact on a construction project is primarily high. The empirical investigation of [11] further affirms that the economic environment is an external factor that positively influences construction firm performance outcomes. [12] observed that the technology
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environment, as an external factor, significantly and positively influences construction firms’ performance outcomes. Besides, [13] indicated that construction organizations’ performance is positively affected by their socio-cultural environment. In their study on leadership orientation in South African construction firms, [14] concluded that there are gaps in the perceived functions of leaders in implementing the fourth industrial revolution in South African construction firms, which affects their performance improvement efforts. [15] highlighted the existence of a positive relationship between human capital and construction firms’ performance outcomes. [16] empirical investigation assured that communication culture positively influences construction firms’ performance outcomes. On the other hand, the institutional pressures under which these firms have to work and adjust their organizational structure and actions are vital to their continued existence and legitimacy to achieve high performance [17]. Therefore, this study argues that construction firms react to institutional pressures and environmental factors differently depending on how they understand it as external pressures influence the performance outcomes. Their response to these pressures reflects their impact on firms’ performance. The construction industry in Syria is not an exception, as previous research has offered considerable attention to construction projects’ performance [18]. Though, to some extent, many of these reports are founded upon evidences which are sketchy, as enough attention has not been devoted to the exploration of the manner in which environmental factors or institutional pressures influence the outcomes of performance of construction firms so as to drive home most of these perceptions. Therefore, the impact of these environmental factors, whether internal or external, and institutional pressures on the performance of construction firms presents a potentially missing piece of the puzzle; hence it must be examined to depict performance outcomes better and highlight the importance of institutional pressures. To fulfill this argument, the model of this study model incorporates factors that are responsible for the heterogeneity of performance (environmental factors—institutional pressures), referred to as explanatory or predictive variables, and performance (the outcome variable). This model suggests that the organization’s superior performance is contingent upon external environmental factors and institutional pressures.
2 Conceptual Model The amount of research and studies that have been carried out within the construction industry context that explores empirically, the possible effect of environmental factors as well as institutional pressures on the performance of firms, are insufficient. Hence, this study conceptualized a model that incorporates factors that are responsible for the heterogeneity of performance, including internal environmental factors (leadership, human capital, communication culture), as well as external environmental factors (political environment, economic environment, technology environment, socio-cultural environment), as the independent (predictor) variables. In
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Political Environment
Economic Environment Technology Environment Environment ors Socio-cultural Environment
Construction Firm Performance
Communication Cultural
Human Capital
Leadership
Fig. 1 Conceptual framework
contrast, the dependent variable is the performance of the construction firm. Moreover, institutional pressures were adopted to examine their effect as a mediator on the relation between internal and external environmental factors and the performance of the construction firm. The proposed model for this study is shown in Fig. 1.
3 Methodology A cross-sectional, quantitative method using a deductive approach was conducted through a field survey, and the data were gathered with the use of a structured questionnaire that was anchored on a five-point Likert scale. All of the responses were arranged and aggregated in order to present a single response of the firm that synchronizes with the unit of analysis (construction firm). Simultaneously, the respondents, which are the unit of observation, were recruited from the strategic and operational levels of various construction firms. A total of 197 valid survey responses were received using a snowball sampling technique. Thus, the response rate was approximately 78.8%, which shows the effectiveness of the survey. Data were subjected to inferential statistical analysis using structural equation modeling partial least square (SEM-PLS) by Smart PLS 3.0.
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3.1 Instrument Design To assure the variables’ measurements, the study items were adapted from several sources so as to produce a peculiar pool of item and content validity, as shown in Table 1:
4 Data Analysis and Results PLS-SEM (using Smart PLS 3.0) was utilized in the data analysis in the preliminary study [19–25]. According to [26], PLS-SEM is a popular data analytic technique, mainly utilized because of its ability to adequately analyze sample sizes which are relatively small when compared to other co-variance-based Structural Equation Modeling techniques such as LISTREL or AMOS. Thus, because of the small sample size of the study, PLS-SEM is deemed appropriate; Fig. 2 illustrates the research model. Table 1 Source of the questionnaire measures S/N
Constructs
Dimensions
Source
1
Firm performance measures
Financial performance (FP)
Luu et al. [19], Jin and Deng [20], Ali et al. [4]
Customer satisfaction (CS) Internal business processes (IBP) Environmental performance (EP)
2
External environmental factors
Political environment (PE) Economic environment (EE) Technology environment (TE)
Sun and Meng [21], Akanni et al. [11], Funmilayo [22], Masadeh et al. [23], Mugo and Moronge [16]
Socio-cultural environment (SE) Internal environmental factors
Leadership (LS)
Institutional pressures
Coercive pressures Normative pressures Mimetic pressures
Human capital (HC) Communication culture (CC)
3
Dubey et al. [24] Iliya Nyahas et al. [25]
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Fig. 2 Research model
4.1 Reliability and Validity Assessment The measurement model accuracy assessment attempts to quantify the manifest variables’ reliability and validity and their objects to justify their use in the path model’s suitability. Validity defines the precision with which a construct represents the item it is to measure, while reliability refers to the level of consistency of the instrument’s accuracy over time, as well as across different scale objects [27]. Based on this and due to our reflective model, the evaluation was carried out by two main steps as follows: 1. Assessing the reliability by evaluating internal consistency (composite reliability). 2. Assessing convergent validity by examining average variance extracted (AVE); discriminant validity by examining the heterotrait-monotrait ratio of correlations (HTMT). Construct reliability is carried out by examining the outer model seen from the numerical values of composite reliability. Values that are equal or greater than 0.6, show the reliability of the scale [28]. The results of composite reliability (Table 2), are above 0.6. These results indicate adequate internal consistency. Moreover, Average Variance Extracted (AVE) was utilized in examining the convergent validity. According to [29], AVE has a threshold value of 0.5, showing that
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Table 2 Results of measurement model-convergent validity Constructs
AVE
CR
Financial performance
0.629
0.91
Customer satisfaction
0.681
0.895
Internal business processes
0.701
0.954
Environmental performance
0.66
0.933
Political environment
0.8
0.941
Economic environment
0.848
0.957
Technology environment
0.859
0.948
Socio-cultural environment
0.652
0.849
Leadership
0.85
0.919
Human capital
0.675
0.912
Communication culture
0.791
0.883
Institutional pressures
0.562
0.92
the construct explaining the variance is higher than the measurement error. Accordingly, all AVE values depicted in Table 2 are above 0.5, with 0.562 being the lowest value, demonstrating adequate convergent validity. Additionally, the discriminant validity acts such that measures are unable to be associated with each other; in literal fact, they are genuinely distinct from other constructs. Henseler et al. [30] illustrate via a simulation analysis and based on the multitrait-multimethod matrix, an alternative approach to evaluate the discriminant validity, which is the technique of using the heterotrait-monotrait ratio of correlations (HTMT). This method depicts superior performance utilizing a Monte Carlo simulation study. They suggested that if the value of HTMT is smaller than 0.9, there will be discriminant validity among two reflective constructs. As shown in Table 3, all the values of HTMT of the latent constructs were less than 0.9. Hence, it assures that the measurements of the latent construct were discriminating towards one another.
5 Discussion Based on the result of the analysis of the measurement of the proposed model, it can be concisely stated that all the integrated constructs of the internal and external environmental factors, institutional pressures, and outcomes of performance of the construction firms are all valid and reliable based on their factor estimations. The results indicate the PLS model utilized in this research was reasonably well defined in terms of its reliability as the composite reliability values were higher than 0.6. AVE values showed the mean commonality for each latent in the reflective model with coefficients values that were greater than 0.5. Moreover, all the HTMT values of the latent constructs were below 0.9, and this validated that in each construct,
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Table 3 Results of HTMT discriminant criteria CS
CC
EE
EP
FP
IBP
IP
LS
SE
PE
HC
TE
CS CC
0.533
EE
0.243 0.133
EP
0.728 0.769 0.206
FP
0.423 0.679 0.327 0.44
IBP 0.768 0.821 0.272 0.967 0.56 IP
0.41
0.771 0.362 0.764 0.907 0.694
LS
0.327 0.514 0.593 0.408 0.567 0.396 0.824
SE
0.634 0.56
PE
0.292 0.212 0.951 0.35
HC
0.281 0.554 0.501 0.682 0.616 0.556 0.901 0.797 0.945 0.593
TE
0.246 0.563 0.472 0.798 0.397 0.736 0.69
0.576 0.929 0.716 0.791 0.892 0.628 0.456 0.394 0.551 0.488 0.726 0.543 0.812 0.574 0.735
the manifest variables represented the allocated latent variable whilst confirming the discriminant validity of the model. Consequently, the measurement model established adequate reliability and validity standard that can be appropriate for data analysis in the related research area. Lastly, this paper reports notable findings and results with respect to the management of construction companies. Primarily, it broadly alludes to the institutional theory. Prior studies on the management of construction companies, based on institutional theory, have majorly approached outcomes of performance as isomorphic processes, especially at the project level. This paper, however, took the manner of approach of an inter-organizational matter towards performance outcomes, thus allowing the researchers to pay close attention to the institutional mechanisms which are at play within a complex organization at the organizational level.
6 Conclusion This study examined a conceptual model derived from a literature review to fulfill the acceptable requirements of the analyses for both reliability and validity with the use of Smart-PLS. The results indicated that all items correctly measure their respective constructs and assure the ability of the collected data to produce results that are both consistent and reproducible. However, this study was limited to the construction industry’s performance management practices’ environmental stewardship aspect. Therefore, future researchers are advised to empirically validate the structural model in order to determine the capability of the model to predict one or more target constructs by adding another environmental perspective. As a result, this will provide an in-depth understanding for academicians and practitioners on the effect of environmental factors and institutional pressures on the performance of construction
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firms and enable policymakers to enhance the performance of construction firms and manage their projects effectively.
References 1. Bowen P, Pearl R, Akintoye A (2007) Professional ethics in the South African construction industry. Build Res Inf 35(2):189–205 2. Oyewobi LO, Windapo AO, Rotimi JOB (2013) The effects of business environments on corporate strategies and performance of construction organisations. In: Proceedings 29th Annual Association of Researchers in Construction Management Conference, ARCOM 2013, p 691–701 3. Phua FTT (2006) Predicting construction firm performance: an empirical assessment of the differential impact between industry- and firm-specific factors. Constr Manag Econ 24(3):309– 320 4. Ali H, Al-Sulaihi IA, Al-Gahtani KS (2013) Indicators for measuring performance of building construction companies in Kingdom of Saudi Arabia. J King Saud Univ Eng Sci 25(2):125–134 5. Gunasekara K, Perera S, Hardie M, Jin X (2021) A contractor-centric construction performance model using non-price measure. Buildings 11(8):375 6. Manville G, Greatbanks R (2020) Performance management in hybrid organisations: a study in social housing. Eur Manag J 38(3):533–545 7. Dorsey D, Mueller-Hanson R (2017) Performance management that makes a difference: an evidence-based approach 8. Fehan H, Aigbogun O (2021) Influence of internal organizational factors and institutional pressures on construction firms’ performance. Constr Econ Build 21(2):81–99 9. Maruf B, Ratnaningsih A (2020) Analysis of business entities affecting the competitiveness of the construction industry in Indonesia with the multivariate approach. AIP Conf Proc 2278 10. Masrom A, Hamza G, Manap N, Shahifah Syahrom N (2019) Significant ways to improve the performance of medium and large local contractors in the Jigawa state, Nigeria. MATEC Web Conf 266:03018 11. Akanni PO, Oke AE, Akpomiemie OA (2015) Impact of environmental factors on building project performance in Delta State, Nigeria. HBRC J 11(1):91–97 12. Sait SS, Muharam FM, Chin TA, et al (2018) Impacts of technology assessments on firm performance. AIP Conf Proc 2044 13. Oyewobi LO, Windapo A, Rotimi JOB, Jimoh R (2020) Analysis of the South African construction industry business environment. J Facil Manag 18(4):393–416 14. Alade K, Windapo A, Wachira-Towey IN (2021) Rethinking leadership in the fourth industrial revolution: lessons for construction business organizations. J Leadersh Stud 15(1):74–80 15. Aliu J, Aigbavboa C (2019) Examining the roles of human capital theory. What next for construction industry? J Phys: Conf Ser 1378(2):1–9 16. Mugo KM, Moronge M (2018) Influence of organizational communication on implementation of building projects in influence of organizational communication on implementation of building projects. Strat J Bus Chang Manag 5(2):1144–1182 17. Wang G, He Q, Xia B, Meng X, Wu P (2018) Impact of institutional pressures on organizational citizenship behaviors for the environment: Evidence from megaprojects. J Manag Eng 34(5) 18. Fehan H, Aigbogun O (2020) Analysis of the factors affecting Syrian construction companies’ performance. Int J Innov Creat Chang 11(3):243–258 19. Van Luu T, Kim SY, Cao HL, Park YM (2008) Performance measurement of construction firms in developing countries. Constr Manag Econ 26(4):373–386 20. Jin Z, Deng F (2012) A proposed framework for evaluating the international construction performance of AEC enterprises. Eng Proj Organ Conf 2012:1–25
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21. Sun M, Meng X (2009) Taxonomy for change causes and effects in construction projects. Int J Proj Manag 27(6):560–572 22. Funmilayo OT (2017) Project environment factors contributing to time overruns of projects delivery in Lagos and Abuja, Nigeria. Int J Sci Eng Environ Technol 2(12):84–93 23. Masa’deh R, Obeidat BY, Tarhini A (2016) A Jordanian empirical study of the associations among transformational leadership, transactional leadership, knowledge sharing, job performance, and firm performance: a structural equation modelling approach. J Manag Dev 35(5):681–705 24. Dubey R et al (2017) Examining the effect of external pressures and organizational culture on shaping performance measurement systems (PMS) for sustainability benchmarking: some empirical findings. Int J Prod Econ 193:63–76 25. Iliya Nyahas S, Munene JC, Orobia L, Kigongo Kaawaase T (2017) Isomorphic influences and voluntary disclosure: the mediating role of organizational culture. Cogent Bus Manag 4(1):1–18 26. Wong KK-K (2013) Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Mark Bull 24(1):1–32 27. Drost EA (2011) Validity and reliability in social science research. Educ Res Perspect 38(1):105–123 28. Chin WW (1998) The partial least squares approach for structural equation modeling. Mod Methods Bus Res 1998:295–336 29. Fornell C, Larcker DF (1981) Structural equation models with unobservable variables and measurement error: algebra and statistics. J Mark Res 18(1):1–24 30. Henseler J, Ringle CM, Sarstedt M (2015) A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci 43(1):115–135
Application of Ventilation Systems with Increased Efficiency Olga Malikova
Abstract The general purpose of the work was a feasibility study of the use of energy-saving measures based on optimal design solutions of engineering systems in the development of ventilation systems with the use of energy-saving measures in the building of the Educational and Laboratory Building in St. Petersburg. The use of “passive” and “active” (“zero static pressure chamber” together with “fanclosers”) ways to increase the efficiency of ventilation systems have led to different indicators in the consumption of electrical energy. Therefore, it was necessary to estimate the cost of electricity and the total discounted costs. A one-time investment for an active impact solution is 3.5% more expensive than a standard design practice solution. The combined use of the “zero static pressure chamber” and “fan-closers” is cost-effective, and the system is quickly recouped compared to the estimated equipment life of 20 years, and the non-discount payback period was 2.7 years. When designing branched air ducts, you should leave the branches with approximately the same aerodynamic losses. On the floor branches, it is advisable to use “fan-closers”. The use of “active” methods to increase the efficiency of ventilation systems as energy-saving equipment is appropriate. Keywords Transport infrastructure · Ventilation · Aerodynamic efficiency · Throttle Valve · Zero static pressure chamber · Fan-closers · Feasibility study · Total-discounted costs
1 Introduction Improving the energy efficiency of buildings is a multi-component task, the solution of which requires the implementation of a number of technical measures [1–3]. An important part of such energy saving solutions is to improve the efficiency of general O. Malikova (B) Moscow State University of Civil Engineering (MGSU), 26, Yaroslavskoe Shosse, Moscow 129337, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_132
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ventilation systems, since they consume about 40% of the total electrical power supplied to buildings [4, 5]. According to the current norms and rules for the design of ventilation systems, the required performance of the ventilation unit, the costs of processing outdoor air to the state of supply air are determined. However, the system itself can be built with different options for laying air ducts, and hence with different pressure losses [6–10]. The team of authors (Gagarin VG, Zheldakov DY, Kozlov VV) proposed a method for calculating the energy efficiency of ventilation systems in residential and public buildings, which we applied to ventilation systems with increased “aerodynamic” efficiency. When designing ventilation systems, it is mandatory to determine the required performance of the ventilation unit, as well as the necessary costs for air treatment. These parameters are considered unchanged for the designed ventilation system, however, it itself can be built in various ways (for example, due to different laying of air duct routes). For different options of the designed ventilation system, the criterion for assessing the “aerodynamic” efficiency is the power consumed by the ventilation unit. The classical design approach often offers “passive” ways to influence the aerodynamic losses in the system, for example, changing the size of the duct section, etc. In this paper, it is proposed to apply methods to increase the efficiency of ventilation systems, which are called “active” methods of influencing the system, namely, dividing into several independent systems and using “zero static pressure chambers” in conjunction with “fan-closers” [11–13]. In this case, the “zero static pressure chamber” cuts off the section of the air duct network, served by a common fan as part of the supply unit, from the remaining sections, consisting of floor-by-floor branches and served by separate floor-by-floor “fan-closers”. With “passive” methods of influencing ventilation systems with different aerodynamic losses in the branches, it is necessary, with the help of additional resistances, to bring small aerodynamic losses closer to the largest value among the duct network. And this is the biggest disadvantage of passive regulation. The paper, using a real object, shows how to calculate the efficiency of the supply ventilation system with “passive” (option 1) and “active” (option 2) methods and at the same time give an economic assessment of these options.
2 Materials and Methods The object of study chosen as an example of a feasibility study of the measures applied in the system of its supply mechanical ventilation is the Educational and Laboratory Building, which is a four-story building in St. Petersburg. This building was chosen because the air duct routing in it is typical for most public buildings being designed, taking into account the location of the vertical supply shaft in such a way that the length of the branches on each floor is approximately equal and the minimum possible. In addition, this typicality allows us to disseminate the results obtained in the form of recommended ratios between capital and operating costs
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and to generalize the conclusions. When developing the supply system, two options were considered: using the main fan as part of the supply unit and “fan-closers” on floor-by-floor branches. The first aerodynamic calculation was performed according to the “standard” design practice, where the design direction is taken to be a line connected from successive sections from the air intake grid to the most remote branch. In this case, the pressure loss of the system is determined by the pressure loss of all successive sections (main) and the pressure loss in the air handling unit. As a result, it is quite difficult to link all branches of the system, where balancing is performed by varying the angle of rotation of the throttle valves. This is a passive effect on the ventilation system in order to equalize the costs through the air distribution devices [14]. In this case, the losses in each of the branches must be equal to the losses in the backbone. Additional aerodynamic resistance is specially added to the devices, which increases the power consumption of the fan. Passive effects also include: installing diaphragms, covering ventilation grids, changing the size of air duct sections. A schematic representation of the ventilation system according to the first option is shown in Fig. 1. The length of the duct is proportional to the pressure loss, and the thickness is proportional to the air flow. Determine the power loss during throttling by the formula (1): NT V =
L T V · PT V , ηf
(1)
where PT V —pressure drop across the throttle valve, Pa; L T V —air flow through the throttle valve, m3 /s; η f —fan drive efficiency. As a result of the calculation, the losses on the throttle valves amounted to 0.811 kW. In the second version of the system “with increased aerodynamic efficiency”, most of the throttle valves in the system are excluded, and pressure losses are determined at each floor branch, which greatly simplifies system balancing and reduces pressure losses as a whole. The paper uses the option of joint use of the “zero static pressure chamber” (ZSPC) with “fan-closers”. Under ZSPC, in our case and for other similar
Fig. 1 Supply ventilation system with “throttle valves” (option 1)
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Fig. 2 Supply ventilation system with “zero static pressure chamber” and “fan-closers” on each branch (option 2)
buildings, we mean a vertical collapsible shaft, the dimensions of which are selected in such a way that the pressure drop in the section is close to zero. The chamber has sufficient volume, so we believe that there are no aerodynamic losses “per impact”. The advantage of the chamber is the fact that at low speeds and large cross-sections, it can be compared with the use of a silencer, since with a uniform distribution of air, the sound pressure decreases. The disadvantage of this camera is the requirement for more space for its placement, which must also be taken into account in the feasibility study. For convenience of perception, the second system is presented in the form of a diagram in Fig. 2. In this case, the main fan in the supply unit overcomes the aerodynamic losses in the ventilation unit and the losses in the sections from the air intake grid to the zero static pressure chamber. In turn, the fan-closers that decompose the air work for their branch. Technical characteristics of the fan in the supply unit according to option 1: air flow 12,800 m3 /h; network pressure 500 Pa, total pressure 1030 Pa; power consumption 5.9 kW; rotation speed 1513 rpm; driven fan efficiency 67%. Technical characteristics of the fan in the supply unit according to option 2: air flow 12,800 m3 /h; network pressure 167 Pa, total pressure 593 Pa; power consumption 3.2 kW; rotation speed 1541 rpm; driven fan efficiency 72%, the total power consumption of the fan-closers and the main fan according to the second option is 5.0 kW. Energy efficiency is a characteristic that reflects the ratio of the beneficial effect from the use of energy resources to the costs of energy resources made in order to obtain such an effect. Already at the stage of project development, it can be judged by the indicator obtained on the expediency of applying energy-saving measures [15]. Finally, the efficiency of the supply system can be expressed by the formula (2):
ηf =
L
n Psup +
Nf
m j=1
L ρV2
2
(2)
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L
where ρ—air density, accepted 1.2 kg/m3 ; L = Lj —relative air flow through the j-th n —standard air outlet device; V—air velocity from the air outlet device, m/s; Psup losses in the installation elements, Pa; Nf—fan power consumption, kW. According to formula (2), the aerodynamic efficiency of the supply ventilation system is determined according to options 1 and 2: η1 = 0.358, η2 = 0.423. The main goal of the feasibility study at the stage of design work is to select the most appropriate and profitable design solution. The main criterion should be thorough, critical to the studied parameters and correctly reflecting the randomness of the initial conditions [16–19]. Economic indicators are expressed as capital, operating and total discounted costs (TDC). All costs can be presented in monetary terms (rubles). However, the optimal cost decision is a function of time, due to changes in market prices. TDC is a clear measure of economic viability, which boils down to the excess of the annual savings in energy costs over the annual interest on the loan or, if the investment is made from own funds, over the lost profits that could be obtained if instead of spending on energy savings, the corresponding amount was put in the bank. The use of “passive” and “active” ways to increase the efficiency of ventilation systems leads to different indicators in the consumption of electrical energy. Therefore, it is worth assessing several indicators that reflect first of all the costs of electricity [20], and then in financial terms using TDC. The components of capital costs (denote C) in ventilation systems include the market value of equipment, the cost of spare parts, transportation costs, packaging costs, procurement and storage costs, installation [17]. Capital costs for equipment and components for the compared options are given in Table 1. The cost of choke valves made of galvanized steel with their installation on all branches to balance the system according to the first option exceeds the costs in the second option by an average of 35%. The estimated cost of equipment also includes additional components (summarized in Table 2). Another important component of capital cost is the connection to the engineering and technical networks of the capital construction facility and the costs associated with it. The main indicator that determines the cost of connecting an object to the Table 1 Market value of installations, in rubles, collected
Capital costs, rub
Option 1
Option 2
Supply unit with automatic equipment set
595,638.00
414,405.00
Fan-closer 1
–
56,992.00
Fan-closer 2
–
64,104.00
Fan-closer 3
–
56,992.00
Fan-closer 4
–
45,660.00
Total Throttle valves Total capital costs
595,638.00
638,153.00
34,560.00
22,320.00
630,198.00
660,473.00
Market price of the unit
595,638.0
638,153.0
Option
1
2
3190.8
2978.2
Packaging
Table 2 Capital costs, in rubles, collected
6381.5
5956.4
Picking
38,289.2
35,738.3
Logistics
12,763.1
11,912.8
Replacement parts 19,144.6
17,869.1
Warehouse operations 95,722.9
89,345.7
Installation management
22,320.0
34,560.0
Throttle valves
17,280.0
22,800.0
Balancing the system
853,245.1
822,798.5
Total
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Table 3 Cost of connection to electric networks, in rubles Option
Rated load capacity P, kW
Issue of technical specifications
Checking the technical specification
Inspection
Connection and maintenance of work
1
5.25
2336.25
1580.25
215.51
738.94
2
3.50
1557.50
1053.50
143.68
492.63
The cost of connecting to the power grid according to option 1
4870.95
The cost of connecting to the power grid according to option 2
3247.30
Table 4 Operating costs, rubles/year Option
Power consumption of electric motors Ncons, kW
Duration of Annual operation electricity My , h/year consumption Ny , (kW·h)/year
The cost of Amortization electricity charges Ea , Ee , rub/year rub/year
Operating costs E, rub/year
1
5.9
2945
17,375.5
83,749.9
62,075.2
145,825.1
2
5
2945
14,725.0
70,974.5
64,236.9
135,211.4
E, rub/year
10,613.69
engineering and technical support network is the calculated power of the connected load [17]: N1 = 5.25 kW; N2 = 3.5 kW. This type of installation requires a supply voltage of 3f/50Gz/380 V. Table 3 presents the calculated cost of connection to the electrical networks of the engineering and technical support of Lenenergo PJSC. Operating financial costs (denote E) are determined by the energy costs for the treatment of supply air [20]. Two components will be involved in determining the difference in operating costs: the power consumption of fans and depreciation. The annual electricity consumption for air movement of ventilation systems is determined as the sum of the products of the power consumption of electric motors N, kW, installed in the system, and the duration of their operation Myear , h/g. The educational and laboratory building has a six-day work schedule (from Monday to Saturday), works in two shifts from 08:00 to 20:00. The electricity tariff of Lenenergo PJSC for the 2nd half of 2021 is a single-rate tariff of 4.82 rubles/(kWh). The results are summarized in Table 4.
3 Research Results Using the “active” method of impact, it was possible to increase the efficiency of the ventilation system to 0.423, while a similar system with a “passive” impact has an efficiency of 0.358. It can be concluded that the use of a “zero static pressure chamber” and “fan-closers” on floor branches, from a technical point of view, is
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Table 5 Total discounted costs at p = 10%, in rubles
Years
Total discounted costs for the option 1, rub
Total discounted costs for the option 2, rub
0
827,669.4
856,492.4
1
1,056,261.4
1,077,353.0
2
1,307,712.7
1,320,299.7
3
1,584,309.1
1,587,541.1
4
1,888,565.1
1,881,506.6
5
2,223,246.7
2,204,868.7
an effective and energy-saving measure in ventilation systems due to an increase in efficiency by more than 18% on average. One-time investments in the option with the use of “active” impact, as a way to increase the efficiency of ventilation systems, are 3.5% more expensive than the solution according to standard design practice. At the same time, operating costs are reduced by 7.3%. The total discounted costs (TDC) for T years are determined by the formula (3) [GOST R 56295-2014. Energy efficiency of buildings. Methodology of economic assessment of energy systems in buildings]: p T 100 p T + E 1+ −1 T DC = C 1 + 100 100 p
(3)
where p—discount rate,%; C—capital costs for the corresponding option, rubles.; T—estimated period, years; E—operating costs for the corresponding option, rubles/year. Based on the values of capital and operating costs defined above, TDCs are calculated. At the same time, a discount rate equal to 10% of annual costs was accepted. The calculation results are given in Table 5. The discounted payback period is 3.3 years, which is less than the maximum discounted period, which is usually set by the customer and is assumed to be 5 years. From Table 5 it can be seen that from the standpoint of TDC during a long operational period, the option with the use of energy-saving measures is less costly. The combined use of a “zero static pressure chamber” and “fan-closers” is cost-effective, and the system quickly pays for itself compared to the estimated equipment life of 20 years.
4 Conclusions The typicality of the duct system routing and the general engineering approach to its construction allows us to extend the results of the percentage of costs to any ventilation system in a public building, since the change in absolute values will
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occur proportionally. Analysis of the considered methods for calculating ventilation systems allows us to draw the following conclusions: • the use of a “zero static pressure chamber” and “fan-closers” led to an improvement in the efficiency of the ventilation system as a whole by more than 18% than with standard design practice. At the same time, capital costs slightly increase (no more than 5%), while operating costs decrease. The advantage of such an “active” method of influencing ventilation systems is the independence of the branches that are separated from each other. • the greater the pressure loss in the line and the lower the overall performance of the system, the greater the effect of the “active” impact on the system; • when designing branched air ducts, branches with approximately the same aerodynamic losses should be left in order to avoid excessive throttling when linking the system. This approach is typical for any type of system, since in fact, it is impossible to completely get rid of the branching of air ducts on the floor. It is necessary to reduce the branching of the system by installing such small individual fans up to a certain limit, the determination of which is a separate interesting task (from the point of view of technical and economic calculation). The results of the considered feasibility studies emphasize the need to develop and actively introduce into the design practice the proposed “active” ways to increase the efficiency of ventilation systems in order to save energy, taking into account their quick payback.
References 1. Yartsev DS, Tsynaeva AA (2019) Issledovanie raboty system ventilytsii i konditsionirovaniya torgovogo tsentra (Study of the ventilation and air conditioning systems of the shopping mall). Gradostroitel’stvo i Arkhitektura (Urban Constr Arch) 9:63–73. https://doi.org/10.17673/Ves tnik.2019.03.9 2. Iturriaga E, Aldasoro U, Terés-Zubiaga J, Campos-Celador A (2018) Optimal renovation of buildings towards the nearly zero energy building standard. Energy 160:1101–1114. https:// doi.org/10.1016/j.energy.2018.07.023 3. Santos T, Wines C, Hopper N, Kolokotroni M (2018) Analysis of operational performance of a mechanical ventilation cooling system with latent thermal energy storage. Ener Build 159:529–541. https://doi.org/10.1016/j.enbuild.2017.11.067 4. Fu X, Wu D (2015) Comparison of the efficiency of building hybrid ventilation systems with different thermal comfort models. Ener Proc 78:2820–2825. https://doi.org/10.1016/j.egypro. 2015.11.640 5. Fiorentini M, Serale G, Kokogiannakis G et al (2019) Development and evaluation of a comfortoriented control strategy for thermal management of mixed-mode ventilated buildings. Ener Build 202:109347. https://doi.org/10.1016/j.enbuild.2019.109347 6. Zhao W, Kilpeläinen S, Kosonen R, Jokisalo J, Lestinen S, Mustakallio P (2021) Thermal environment and ventilation efficiency in a simulated office room with personalized microenvironment and fully mixed ventilation systems. Build Environ 188:107445. https://doi.org/ 10.1016/j.buildenv.2020.107445
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7. Aridi R, Faraj J, Ali S, Gad El-Rab M, Khaled M (2021) Energy recovery in air conditioning systems: comprehensive review, classifications, critical analysis, and potential recommendations. Energies 14(18):5869. https://doi.org/10.3390/en14185869 8. Sharapov A, Myakotina E, Shatskikh Y, Peshkova A (2019) Increase of energy efficiency of the mechanical ventilation system. IOP Conf Ser: Earth Environ Sci 272:022218. https://doi. org/10.1088/1755-1315/272/2/022218 9. Sekhar C, Bivolarova M, Akimoto M, Wargocki P (2021) Detailed characterization of bedroom ventilation during heating season in a naturally ventilated semi-detached house and a mechanically ventilated apartment. Sci Technol Built Environ 27:158–180. https://doi.org/10.1080/237 44731.2020.1845019 10. Park D, Battaglia F (2015) Effect of heat loads and ambient conditions on thermal comfort for single-sided ventilation. Build Simul 8:167–178. https://doi.org/10.1007/s12273-014-0200-9 11. Kassai M (2016) A developed method for energy saving prediction of heat-and energy recovery units. Ener Proc 85:311–319. https://doi.org/10.1016/j.egypro.2015.12.257 12. Puring SM, Vatuzov DN, Tyurin NP (2016) Parameter choice optimization of ventilating air cleaning equipment while designing and constructing industrial buildings. Proc Eng 153:563– 568. https://doi.org/10.1016/j.proeng.2016.08.192. 13. Wang W, Kato N, Kimoto S, Matsui Y, Yoneda M (2020) Simulation and evaluation of sheltering efficiency of houses equipped with ventilation systems. Build Environ 168:106491. https://doi. org/10.1016/j.buildenv.2019.106491 14. Rosato A, Guarino F, Filomena V, Sibilio S, Maffei L (2020) Experimental calibration and validation of a simulation model for fault detection of HVAC systems and application to a case study. Energies 13(15):3948. https://doi.org/10.3390/en13153948 15. Hunt D, Suibhne N, Dimache L, McHugh D, Lohan J (2020) Advances in multifunctional balanced ventilation technology for dwellings and arising challenge to quantify energy efficiency and renewable generation contributions using international test standards. Renew Sustain Energy Rev 134:110327. https://doi.org/10.1016/j.rser.2020.110327 16. Oldewurtel F, Jones C, Parisio A, Morari M (2014) Stochastic model predictive control for building climate control. IEEE Trans Control Syst Technol 22:1198–1205. https://doi.org/10. 1109/TCST.2013.2272178 17. Malyavina E, Malikova O (2018) Analysis of annual energy consumption of air conditioning systems, calculated on the basis of probabilistic-statistical climate model. IOP Conf Ser: Mater Sci Eng 451:012104. https://doi.org/10.1088/1757-899X/451/1/012104 18. Kim SM, Lee JH, Moon HJ, Kim S (2012) Improvement of indoor living environment by occupants’ preferences for heat recovery ventilators in high-rise residential buildings. Indoor Built Environ 21(4):486–502. https://doi.org/10.1177/1420326X11429714 19. Malyavina E, Malikova O, Pham L (2020) Probabilistic-statistical model of climate in estimation of energy consumption by air conditioning systems. Adv Intell Syst Comput 982:69–77. https://doi.org/10.1007/978-3-030-19756-8_7 20. Karpuk M (2019) Minimization of fan energy consumption in ventilation and (or) airconditioning systems as an optimization calculus of variations. E3S Web Conf 116:00033. https://doi.org/10.1051/e3sconf/201911600033
Socio-Psychological and Criminological Characteristics of Persons Prone to Reckless Driving Ivan Tretyakov
Abstract In this Article the Author deals with the problems of deviant (or in some cases outright criminal) behavior of vehicle drivers, who grossly and cynically violate traffic safety rules. The analysis of the socio-psychological and criminological characteristics of drivers accused of committing transport crimes constitutes the purpose of this scientific work. The Author puts forward the working hypothesis that the drivers of road vehicles responsible for traffic accidents have distinctive ideological, subcultural, motivational and characterological (pathocharacterological) shortcomings/problems, as well clear signs of maladaptation and desocialization. The following tools and methods were used in this study—statistical, documentary, experimental psychological methods, sociological methods of questioning and personality analysis. The materials of specific criminal cases on transport crimes, acts of judicial psychiatric, narcological, psychological and technical examinations, as well as the results of surveys and interviews of the drivers themselves (the accused) were used as the empirical basis of this Article. It was concluded that the core pattern of deviant (aggressive, scatterbrained, provocative or criminally motivated) behavior of drivers is a heterogeneous group of personality disorders manifested as a destructive sociopathic complex. The most striking manifestations of such complex include the following—complete disregard for moral norms, low level of culture, emotionalvolitional imbalance, hyper aggressiveness, impulsiveness, a tendency to addictive lifestyle, low empathy, and narcissism. Keywords Driver · Sociopath · Transport · Aggressive driving · Aggression · Crime
I. Tretyakov (B) Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya, 195251 Saint-Petersburg, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_133
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1 Introduction For over a hundred years dangerous behavior of drivers (leading to accidents on the roads and human tragedies) remains the most important social problem that governments, as well as public and international organizations are trying to solve. According to UN experts, numerous violations of traffic rules, such as speeding, overtaking, driving under the influence (DUI), provocations against other drivers, etc. are the causes of most fatal traffic accidents (the number of which is steadily growing in the world) [1, 2]. Usually it is law-abiding citizens, children, as well as police officers performing their duties (trying to detain violators) who increasingly become the victims (die or get injured) of aggressive or irresponsible drivers [3–5]. The search for the most efficient ways to prevent traffic accidents (and crimes) is inextricably linked with the analysis of the human factor, since the real causes and conditions of deviant activity and behavior lie in the person himself, his/her worldview, motives, etc. Thus, the deep interdisciplinary study of the socio-psychological and criminological characteristics of drivers prone to reckless driving seems quite relevant and extremely promising.
2 Materials and Methods The phenomenon of aggression of road transport drivers is the most important point in modern interdisciplinary studies devoted to a wide variety of their deviant activities [6–9]. Normally, the aggressive actions of drivers are contemplated within the framework of hypertrophied and socially dangerous behavior, characterized by the predominance of affective, motivational or instrumental components. According to established tradition, special place is given to anger [10, 11], drug addiction and alcohol drinking of the those responsible for accidents [12–14], to professional level of drivers, psychological support, monitoring of their condition [15–17], as well as characterological features in the form of overestimated self-assessment [18], psychopathization, weakening (or lack) of control over one’s actions, or additive attitudes [19–21]. The works, in which the authors used the cognitive approach to explain the nature of the so-called road rage proposing cognitive-behavioral training in special groups to strengthen the adaptive potential of drivers and prevent aggression [22] are of undoubted interest. Our Spanish colleagues discussed in detail the issues related to traffic accidents where pedestrians were injured, in which they specified how guilty they were, the behavior of drivers, the nature of objective circumstances and the state of technical means [23]. At the same time, we have to state that in the available scientific literature nothing is said about the structure of violations of the arbitrary self-regulation of aggressive drivers at the time they committed a crime. Moreover, we could find no discussions concerning more remote (deeper) aggression predictors such as disharmonious
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upbringing, marginalized/lumpenized environment, or early formation of addictive responding attitudes. Neither we could see any publications related to the mechanisms of stress coping behavior of drivers, to pseudo-adaptive coping strategies of those prone to reckless driving. The study was carried out from January 2017 to January 2022 on the basis of state expert institutions of Moscow and St. Petersburg. 500 drivers of vehicles, against whom criminal cases were initiated (for violation of traffic rules, which, through negligence, caused serious harm to the health of a victim or death of a person) participated in the study. With due account of demographic factors, it was established that—1) 390 persons (78%) were males, 110 persons (22%) were females; 2) the age of the persons in question was from 19 to 42 years, with average age being 24.2 ± 4.6 years; 3) 248 persons (50%) at the time of the crime had no permanent job, 201 persons (40%) worked in the field of commercial services, mainly in trade, 51 persons (10%) were people from law enforcement agencies, or civil authorities. The most common methods to study drivers prone to reckless driving and accused of committing a crime were as follows—observation, interrogation (including drivers’ self-reports), personal questionnaire aimed at making clinical profiles of the accused (the clinical profile of each participant of the experiment reflected the diagnostic orientation of destructive and positive personal traits, symptoms revealing violation of adaptation, evidences of borderline states, or of more serious symptoms). The use of the following well-known techniques was deemed to be most promising: 1. Buss-Durkee Hostility Inventory, (BDHI)—the questionnaire with personality scales to determine the degree of aggressiveness and hostility of the participant in the experiment (the authors identified two types of hostility and five types of aggression). 2. Minnesota Multiphasic Personality Inventory (MMPI)—distinguished for its reliability and validity; it allowed to establish the individual qualities of the accused (both in normal and pathological conditions). This questionnaire enabled identification of both conscious and latent (insufficiently conscious) impulses, needs, interests, etc. 3. Charles Spielberger Scale (State-Trait Anxiety Inventory—STAI)—designed to assess anxiety (including personal and situational), emotional lability.
3 Results 21 (4%) males, aged 18 to 20, had driving experience of up to one year; 196 persons (39%) had driving experience from one to five years; 204 persons (41%)—from five to ten years; while 79 persons (16%) reported of their driving experience of over 10 years (Fig. 1). Driving experience data show that traffic crimes are committed mostly by persons with driving experience from one to ten years. It has to be noted that women who
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Fig. 1 Percentage distribution of drivers of private cars depending on driving experience
took part in the study had driving experience of five to ten years, with average age being 25.2 ± 5.5. The nature of the deviant activity of drivers reveals that 447 (90%) of the respondents were repeatedly subjected to administrative penalties (mainly fines), 125 persons (25%) were previously prosecuted for committing acquisitive, violent crimes and various acts in the field of drug trafficking. 184 persons (37%) committed a crime in the state of drug intoxication, 146 persons (29%)—being in the state of alcoholic intoxication. 170 persons (34%) reported that they never used psychoactive substances, however they faced problems related to other addictions, i.e., various forms of addictive behavior (Fig. 2). Every tenth person guilty of a traffic accident tried to escape from accident site. Moreover, during the interview it turned out that 80 people (16%) have the remotest idea of the Traffic Laws (which raised questions about how legally they got their driver’s license). Family disharmony (family troubles) is an important social factor of general maladaptation. It is significant that female respondents were either unmarried or
Fig. 2 Percentage of accused who committed a motor vehicle collision who were found to be intoxicated
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divorced. By the time of criminal case initiation, only 66 males (13%) were married, and lived with their families. About 40% claimed to be supporters of a hedonistic lifestyle and a marginal subculture that echoed criminal (prison) culture and the attitudes of drug addicts and alcoholics. The accused defended their exclusivity and special aesthetics (philosophy), e.g., 10% of young people under the age of 27 years belonged to various organized criminal groups (both general criminal and extremist). About 33% of respondents considered themselves the Street Racers bloggers. The intellectual level of the respondents was extremely low, the needs were quite primitive (on spite of the fact that every fourth had a higher or incomplete higher education). Over 70% have not read any book over the past ten years, neither have they attended any cultural event. Persons of this category spent their free time on reckless driving and viewing stories (videos) full of cruelty and violence on social networks. 11% of males had a low level of empathy and were especially cruel (observation made by forensic psychiatrists). Their violent tendencies became more intensive under the influence of alcohol. The study revealed that in everyday life, the category of persons in question occupied such social (or rather asocial) niche in terms of interpersonal relations and extensive communications, that made them deeply marginalized in the eyes of our experts. Above all, this was the evidence of their unwillingness to comply with the standards of law and generally accepted morality. Most of these people showed all signs of desocialization, maladjustment and dissociative pathology. But still they happened to be very well adapted to functioning in their usual habitat (among poorly cultured/educated individuals, those prone to violence, and criminal strata of population). Living like this, such lumpen and outcasts have developed their deviant behavioral stereotypes, specific algorithms to respond to favorable or unfavorable factors, which help them avoid stress and problems, as well as minimize contacts with government officials. However, such coping of the accused had nothing to do with the constructive, deeply meaningful coping strategies of law-abiding citizens who are able to adequately respond to external challenges and psychological problems. Socio-psychological analysis of stress overcoming skills of the drivers prone to (brutal) aggression and provocations on the roads, reveals that 1) the accused with driving experience of up to one year had an extremely low level of coping behavior; in fact, the experts were able to establish both the absence of rational, positive attitudes and the lack of pseudo-adaptive strategies formation; 2) persons with driving experience of one to five years showed low and medium levels of coping behavior; 3) the accused with driving experience of 5 to 10 years were more confident in stressful situations, which they often provoked themselves; they were characterized by medium and relatively high levels of personal coping strategies; at the same time selective mobility of cognitive functions was evident; 4) the group with driving experience over 10 years turned out to be quite heterogeneous (i.e., it consisted of people with low, extremely low and medium levels of coping response, with only six persons having a high level of such response); at the same time, this category of persons was characterized by overestimated self-assessment, disinhibited behavior, inability to think critically, inability to assess objectively their actions or predict their consequences, together with intellectual insufficiency.
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The results of the psychodynamic examination indicated that newbie drivers (with insufficient life experience) were extremely anxious and insecure while driving. At the same time, such newbies sought to assert themselves, draw attention to themselves, and get an adrenaline rush. Those from the second group were fully aware of their insufficient experience and lack of competence, of their vulnerability on the road, but they chose exceptionally aggressive driving style, defiantly violating traffic rules. People from the third group considered themselves experienced drivers. They completely ignored any critical remarks and showed a cynical indifference to the life and health of those around them. Such respondents were proud of being regularly reported on social networks about their so-called exploits (e.g., they shared their skills in creating emergency situations, posted stories about their hooliganism on the roads, about their fights with drivers and pedestrians). The representatives of the fourth group demonstrated clearly how such a lifestyle with all their unresolved psychological problems brought them down to a broad-scale degradation and self-destruction. The vast majority of those accused with driving experience over 10 years have been repeatedly prosecuted. Furthermore, the respondents revealed some signs of organic brain damage (which was the result of numerous injuries, drug or alcohol addiction), they were unable to control their emotions, showing a tendency to frequent outbursts of impulsive, unmotivated violence. Thus, by deliberately violating the law, the accused individuals sought to assert themselves and overcome their personal ill-being, as well as to enjoy the thrill (through reckless driving), while each of them had his/her special pseudo-adaptive coping strategies that did not help them make pragmatic and/or pro-social solutions. Indicators of hostility, aggression and the degree of readiness to commit asocial acts were obtained using the Buss-Durkee Hostility Inventory (BDHI), Minnesota Multiphasic Personality Inventory (MMPI), Charles Spielberger Scale (State-Trait Anxiety Inventory—STAI), our own clinical questionnaire specially designed for this study. The results of the study are shown in Table 1. We established that in all cases there were high values on the scales of physical aggression, irritation, verbal aggression, impulsivity, psychopathy, hypomania, and social introversion. The anxiety level (combined with uncertainty, and emotional liability) reached its maximum only for newbie drivers with driver’s license of less than one year validity. Further, with an increase in driving experience, there was a decrease in absolute values of anxiety. As a rule, young, inexperienced individuals committed a driving crime were guided by group or game motives. Quite often they followed the pattern of a mythological street racer (an extremely attractive, invulnerable and brutal superman). It is junk information on social networks, lowquality action films, and unhealthy environment, that form such pattern of behavior. Newbie drivers stood out from the accused for not having such qualities as negativism, excessive suspicion, and rigidity; they also show no signs of indirect aggression. At the same time, the accused with a driving experience of up to one year showed a tendency to hysterical reactions/verbal aggression, moreover, they were characterized by higher impulsiveness, often with pronounced rancor. The behavior of drivers from the second and third groups (the persons guilty of the most driving crimes) fully corresponded to modern interactionist views and
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Table 1 The results of the psychological analysis of the accused with different driving experience № Scales of psycho-diagnostic techniques
Drivers with < 1 year driving experience
Drivers with up to 5 years driving experience
Drivers with 5–10 years driving experience
Drivers with Reliability over 10 years driving experience
1
Physical aggression
6.67 ± 0.57
6.49 ± 0.43
6.72 ± 0.39
6.80 ± 0.41 p ≤ 0.05
2
Indirect aggression
3.73 ± 0.22
4.66 ± 0.28
4.48 ± 0.31
5.20 ± 0.17 p ≤ 0.05
3
Rancor
5.15 ± 0.14
4.74 ± 0.17
5.34 ± 0.11
6.42 ± 0.19 p ≤ 0.05
4
Negativism
3.03 ± 0.11
4.18 ± 0.13
5.01 ± 0.18
6.02 ± 0.13 p ≤ 0.05
5
Verbal aggression
7.01 ± 0.09
6.02 ± 0.11
6.55 ± 0.02
7.11 ± 0.04 p ≤ 0.05
6
Resentment
3.04 ± 0.18
3.21 ± 0.16
5.24 ± 0.17
5.33 ± 0.63 p ≤ 0.01
7
Suspicion
2.91 ± 0.13
3.71 ± 0.21
2.77 ± 0.09
4.53 ± 0.14 p ≤ 0.01
8
Anxiety
5.01 ± 0.7
3.08 ± 0.14
1.96 ± 0.54
1.67 ± 0.22 p ≤ 0.01
9
Rigidity
2.71 ± 0.69
4.97 ± 0.74
5.02 ± 0.8
5.83 ± 0.27 p ≤ 0.01
6.33 ± 0.21
4.71 ± 0.66
5.89 ± 0.34
4.62 ± 0.73 p ≤ 0.01
10 Impulsiveness 11 Deception
24.9 ± 1.75
20.0 ± 2.4
19.15 ± 1.11 20.7 ± 2.13
12 Correction
70.71 ± 2.61 69.33 ± 2.16 68.62 ± 2.73 68.91 ± 2.44 p ≤ 0.05
–
13 Hypochondria
40.09 ± 2.47 30.11 ± 1.91 35.14 ± 2.11 36.17 ± 0.12 –
14 Depression
28.13 ± 3.14 25.43 ± 1.17 24.57 ± 0.99 27.48 ± 1.84 –
15 Hysteria
63.91 ± 1.71 50.31 ± 2.29 49.14 ± 4.12 48.01 ± 2.23 p ≤ 0.05
16 Psychopathy
48.14 ± 2.24 48.17 ± 1.16 60.11 ± 1.01 61.22 ± 1.77 p ≤ 0.05
17 Masculinity/femininity 45.07 ± 1.01 44.81 ± 2.03 44.92 ± 1.99 44.77 ± 1.53 p ≤ 0.01 18 Paranoia
30.71 ± 2.63 31.11 ± 0.94 34.07 ± 1.85 62.12 ± 2.93 p ≤ 0.01
19 Psychasthenia
40.24 ± 1.91 40.37 ± 1.57 41.19 ± 1.15 68.9 ± 1.38
20 Schizophrenia
20.46 ± 1.11 19.32 ± 1.01 19.97 ± 1.34 19.91 ± 2.02 p ≤ 0.01
21 Hypomania
48.16 ± 1.91 50.19 ± 2.42 58.72 ± 1.71 39.98 ± 3.01 p ≤ 0.05
22 Social introversion
50.92 ± 1.77 50.88 ± 1.91 51.36 ± 2.02 41.74 ± 1.54 p ≤ 0.05
p ≤ 0.01
dysfunctional-cognitive approaches in explaining the mechanisms of aggressive reactions. Our data show high rates on most scales, with the exception of the scale of anxiety, hysteria, hypochondria, depression, and psychasthenia. Among those from the fourth group, deviant forms of response were manifested both on a purely personal and a psychophysiological level. Motivations were focused on addictive incentives and the satisfaction of various addictions. The highest values were recorded on the following scales—direct and verbal aggression, negativism, rigidity, suspicion, resentment, envy, hatred, rancor, hypochondria, psychopathy, paranoia, psychasthenia, schizophrenia, hypomania. Moral aspect also deserves attention. Only 7 persons reported that they felt guilty, remorse and were ready to apologize to the relatives of the victims.
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4 Discussion It is sometimes difficult to discuss the empirical material, which formed the basis of this study, because it is quite specific in nature. The fact is that today’s scientists practically do not consider the reckless drivers, who are passing comprehensive forensic examination (after initiation of a criminal case, as a result of grave consequences of what they did, of because of their inappropriate behavior on the road) to be an object of their research. A lot of works (related to the topic in question) are devoted to specific factors that contribute to reckless driving. For example, A. K. Yadav and N. R Velaga (2021) analyzed how alcohol intoxication (with different levels of alcohol in the blood) affects the cognitive functions of a person, his/her psychophysiological reactions, emotionality and behavior in general [24]. K. P. Kuypers et all (2020) also studies this problem and came to the conclusion that depending on the individual characteristics of a person, alcohol and synthetic drugs (stimulants) lead to either a euphoria or a pronounced aggression [25]. As we could see, 66% of drivers (participants in the experiment) were abusing psychoactive substances all their lives and committed crime while intoxicated. Evidently, the correlation between alcohol, drugs and violence [26], observed by of A. A. Duke et all (2018), as well as addiction of violent criminals to drugs and alcohol [27], mentioned by L. Erikson at all (2020), can well be confirmed. According to many authors, family problems and troubles is the most important marker of criminal aggression (real, potential, or hidden). Such factors point to the earlier problems of bad upbringing/education. humiliation, frequent conflicts with parents, and later with a spouse. According to our data, only 13% of respondents were married at the time of the traffic accident (while 10% were ready to divorce shortly). The role of family disorders in the formation of maladaptive and aggressive behavior was pointed out by D. Gadd et all (2019), M. J. Brem et all (2018) [28, 29]. J. Bjureberg and J. J. Gross (2021) created an original socio-psychological concept to explain the phenomenon of road aggression. Unfortunately, the said authors ignored such factors of drivers’ rancor as low level of culture, education, quality of life, mental disorders and asocial attitudes [30]. V. Ross et all (2021) focus their attention on two types of aggression of young drivers (i.e., reactive and proactive). Their study is of an undoubted practical significance since they suggest a deep and purposeful approach to the problem of neutralizing rancor of the drivers. In this case, however, we talk about law-abiding and adequate people who are quite able to control their emotions [31]. While our study is mainly devoted to problematic drivers, whose psycho clearly needs correction (sometimes with the help of a psychiatrist). A lot of observations we made, as well as some of our theoretical statements are consistent with the data obtained by our Chinese colleagues. In particular, this refers to the work of H. Cong et all (2021). Like our Chinese colleagues, we also drew attention to various intergroup correlations and considered correlations with age, gender, education, driving experience and psychological health [32].
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With all the above in mind, we can come to a number of very significant theses. Social (social-psychological) space of the individual is one of the most controversial issues the specialists deal with. Aggressive drivers jeopardize the life and health of completely random people. Reckless driving has a multifactorial origin being a complex juxtaposition and interaction of situational, legal, social, cultural, psychological, biological and medical aspects. The share of each factor in aggressive tendencies, violence, and hostility depends to a large extent on the individual characteristics of the driver’s personality. In the course of our study, we emphasized the high deviant nature (pathology) of the accused, and the self-destructive nature of their behavior, which was determined by microsocial ill-being, unformed or deformed motivational and semantic lines, moral consciousness.
5 Conclusion Reckless driving offenders show varying degrees of aggression, which is most pronounces in groups with five to ten years and over ten years of driving experience. In terms of numbers, most driving crimes are committed by persons with one to ten years of driving experience. Aggressive drivers with over five years of driving experience are characterized by violent behavior in various situations; threatening the victim being the source of positive emotions for them. The urge to suppress others, demonstrating their superiority, is normally provoked by addiction to psychoactive substances and disorders of higher nervous activity. Each participant of the experiment had special pseudo-adaptive coping strategies that prevent him/her from making pragmatic and pro-social decisions. There is no doubt that social (microsocial, subcultural, domestic, etc.), situational factors, along with pathopersonological features play a significant role in the formation of various models of aggressive behavior of drivers (who committed a crime). The core pattern of deviant (aggressive, scatterbrained, provocative or criminally motivated) behavior of drivers is a heterogeneous group of personality disorders in the form of combined destructive sociopathic factors. Out of such factors the most striking are—complete disregard for moral norms, low level of culture, imbalance of emotional and volitional activity, high aggressiveness, impulsiveness, a tendency to an addictive lifestyle, low empathy, and narcissism. By investigating and revealing the features that characterize destructive personality of a driver prone to reckless driving we obtain important social and psychological information about his/her life attitudes, his/her health, as well as his/her possible inadequate behavior (which the doctors and psychologist must consider when issuing the driver’s license).
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Evaluation of Forestry Industry Agglomeration and Regional Different Analysis in China’s Southern Collective Forest Region Fang Liu
and Hongxun Li
Abstract Studying the development trend of forestry industry agglomeration in China’s southern collective forest region will provide data reference for the development of future development plans in the region, which will be beneficial to the healthy and sustainable development of forestry. Based on the data of forestry output value and GDP in the southern collective forest region from 2000 to 2019, the trend of forestry output value and contribution rate to GDP was analyzed, and the location quotient model was used to calculate the agglomeration status of the forest industry in the region. Based on the competitive state model, the competition status of forest industry clusters in the region was explored. From 2000 to 2019, the forestry output value of the southern collective forest areas showed an obvious increasing trend, and the contribution rate of forestry output value to the gross national product showed a decreasing trend. The level of forestry development in the southern collective forest areas is uneven. Among them, Guangdong, Guangxi, Fujian, Hunan, Jiangxi and Zhejiang have relatively high forestry output values, while Hainan, Guizhou, and Yunnan have relatively low forestry output values. Among them, the productive areas of the southern collective forest region are mainly concentrated in Guangdong, Guangxi and Fujian in the southeast; Yunnan is rich in forestry resources and has a large space for development; Guangxi, Jiangxi and Guizhou’s forestry output value contributes significantly to regional GDP, and its forestry status It is more significant in the province, and Jiangsu forestry has the lowest contribution rate. The distribution of forest industry agglomeration and competition in the southern collective forest region is extremely unbalanced. Advantageous areas include Hunan, Zhejiang, Guizhou, and Guangxi. Guangdong Province is in a potential area. Inferior areas include Jiangsu, Hubei and Sichuan. The strength areas include five provinces including Anhui, Jiangxi, Fujian, Hainan and Yunnan. The development level of forestry industry in the collective forest region in the south has been significantly improved, but the development between regions is extremely unbalanced. In the future, the productivity of forest industry must be rationally arranged, differentiated and customized, and regional development planning should be done well. F. Liu · H. Li (B) School of Economics and Management, Beijing Forestry University, Beijing 10008, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_134
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F. Liu and H. Li
Keywords China’s Southern collective forest region · Location quotient model · Competition state model · Difference analysis · Sustainable development · Energy efficiency in transportation · Transport infrastructure
1 Introduction China’s forestry, one of the important components of national economy, plays a crucial role in maintaining its economic development and ecological balance [1, 2]. Over the past few decades, Chinese government has attached great importance to the development of national forestry and forest industry. China’s forestry has undergone a growth from 2007 to 2019, forestland increased from 1.7 billion hm2 to 2.2 billion hm2 and forestry output value has surged from 188.99 billion CNY to 8075.1 billion CNY. However, due to its vast territory, China has a forest coverage rate less than the world average that is 22.96%. Moreover, quality of China’s forest resource is poor; utilization rate of national forestland is 52% lower than that of developed countries that is 95%; growing stock per square hectometer is 72.89m3 that is approximately 69% of the world average; also, China’s forestry has not build a solid foundation and its industrial agglomeration is low [3, 4]. Since the 18th CPC National Congress, the CPC Central Committee and the State Council has highlighted forestry in future development, and President Xi Jinping has made a series of important instructions on ecological civilization construction and forestry reformation. In addition, the five concepts for development of innovation, coordination, green, open and sharing was declared during the fifth Plenary Session of the 18th CPC Central Committee, which emphasized an important role of forestry in accelerating China’s development and transformation. At current stage, the challenges facing China are to seize opportunities, to reform conventional industries and to promote development of forest industry in key areas. Since the 1990s, a number of researches on the relationship between industrial agglomeration and economic growth has emerged [5], one of the most widely believed conclusions would be there is an endogenous relationship between industrial agglomeration and economic growth [6–8]. As China’s forestry economy gradually developed, the forest industry has appeared agglomeration. Jiang and Xu [9] explored several problems after analyzing concentration rate of forest industry in Heilongjiang on the basis of data from 1999 to 2013 and made corresponding solutions. Liu, et al. [10] applied location quotient model to calculate agglomeration of forest industry in Yunnan from 1997 to 2014 and resulted in a relationship between the agglomeration and provincial economic growth. Feng and Qin [11] conducted an econometric analysis on the trend of agglomeration of forest industry in Guangxi from 1999 to 2007 consequently found that primary forest industry has no industrial agglomeration, while secondary and tertiary forest industries does. Most studies focus on analyzing the trend of agglomeration of a single provincial forest industry. The focus of this study was forestry and forest industries in southern collective forest region employing data of forestry output value from 2000 to 2019 in each province. Based
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on agglomeration and growth rate of provincial forest industry, this study used the competitive state model to analyze competitiveness of each province’s forest industry in the southern collective forest region and the gaps between them. The objective of this study is to offering thoughts on optimal allocation of forest production factors and restructure of forest industry in this region.
2 Overview of the Research Region and Data Resources 2.1 Overview of the Research Region China’s southern collective forest region includes 13 provinces, Hunan, Hubei, Jiangxi, Anhui, Zhejiang, Fujian, Guangdong, Guangxi, Guizhou, Hainan, Sichuan, Yunnan and Jiangsu, with a total land area of 2.5453 million km2 , dominates one of the China’s key forest resources regions. According to 2019 annual statistic report, the wooded lands in this region reached 143,312,700 hm2 , covering 43.97% of total wooded lands in entire nation; forests was 120,653,600 hm2 , accounting for a national volume of 54.73%; the total growing stock of living wood reached 9.457 billion m3, which was 49.77% of the national total stock; the average forest coverage rate of collective forest area in southern China was 45.66%. Moreover, the total output value of forest industry of this region was 6100.337 billion CNY, made up 75.55% of China’s forest industry, presenting that the southern collective forest region has a great contribution to the national forest industry. As shown in Table 1, the gaps between development statuses of each province in the research region are wide; in Yunnan, wooded lands, forests and growing stock of living wood are respectively higher than those of other provinces. Of this region, wooded lands in Yunnan amounts for 18.14% with area of 25.9944 million hm2 , and forests in Yunnan covers 17.46% of its land with 21.0616 million hm2 and its living wood growing stock amounts for 22.54% with an amount of 2.132 billion m3. However, Yunnan’s output value of forest industry is low, 248.417 billion CNY, accounting for 4.07% of total output value of the whole region. Conversely, Guangdong has the maximum output value of forest industry, followed by Guangxi and Fujian. Guangxi’s forest industry makes the greatest contribution to its GDP, which is 33.16%, followed by Jiangxi and Guizhou, respectively accounts for 20.72% and 20.06%; Jiangsu is the lowest, which is 4.96%. Therefore, Yunnan has the most abundant forest resource, whereas the Guangdong, Guangxi and Fujian concentrate the productivity of the southern collective forest region.
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Table 1 Development index of collective forest area in Southern China in 2019 Province
Wooded lands (104 hm2 )
Forests (104 hm2 )
Living wood growing stock (108 m3 )
Forestry output Contribution value (Billion to provincial CNY) GDP (%)
Hunan
1257.59
1052.58
4.61
502.977
12.61
Hubei
876.09
736.27
9.95
409.576
9.02
Jiangxi
1079.90
1021.02
5.76
511.205
20.72
Anhui
449.33
395.85
2.61
434.523
11.79
Zhejiang
659.77
604.99
3.14
516.722
8.27
Fujian
924.40
811.58
7.97
645.054
15.24
Guangdong
1080.29
945.98
5.01
841.595
7.79
Guangxi
1629.50
1429.65
7.44
704.264
33.16
Guizhou
927.96
771.03
4.45
336.458
20.06
Hainan
217.50
194.49
1.63
65.413
12.27
Sichuan
2454.52
1839.77
19.72
394.788
8.52
Yunnan
2599.44
2106.16
21.32
248.417
10.70
Jiangsu
174.98
155.99
0.96
489.345
4.96
2.2 Data Resources The data used in this study are from the Statistical Yearbook of China (Year 2001– 2020), the Statistical Yearbooks of each province in the southern collective forest region, and official data published by the Ministry of Land and Resources. Data are derived from Statistical Yearbook of China (Year 2019) and Statistical Yearbooks (Year 2019) of each province above.
3 Methodology 3.1 Location Quotient Model Location quotient model was first used to measure the degree of concentration of economic development in regional economy. It was first introduced by P. Higgett into location analysis and was widely employed to measure the agglomeration of a certain industry in a studied area, in order to explain the degree of specialization of this industry [12, 13]. Location quotient model is applied in this study to evaluate the degree of concentration in forest industry in the southern collective forest region, and the formula is: L Qi j =
Qi j/gdpi j Li j/G D Pi j
(1)
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in which, LQij stands for the location quotient of the J th province in year i, Qij stands for forestry output value of the J th province in year i, GDPij stands for the gross product value of the J th province in year i, L ij stands for forestry output value of the southern collective forest region in year i, and GDPij stands for the gross product value of the southern collective forest region in year i. If LQ > 1, then forest industry in certain province has a high agglomeration and strong competitiveness; if LQ < 1, then the concentration degree of forestry industry in this province is lower than the average of all provinces in this region and its competitiveness is weak; if LQ = 1, then there is no advantages for that forest industry.
3.2 Growth Rate of Agglomeration Growth rate of agglomeration is used to explain the changes and trends of industrial agglomeration in the study period [14]. This study took LQ value of year 2000 to 2019 and used the following formula to calculate differences of each province’s agglomeration in the southern collective forest region:
LQj − LQj × 100% P= LQj
(2)
in which, P stands for the growth rate of forest industrial agglomeration, LQ’j stands for the location quotient of forest industry in J th province in 2019, and LQj stands for the location quotient of forest industry in the J th province in 2000.
3.3 Competitive State Model As in Fig. 1, the competitive state model is set with the location quotient of 2019 as the horizontal axis, the growth rate of agglomeration as the vertical axis, and (1, 0) as the origin.
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F. Liu and H. Li II Area with potential
I Predominate area
potential
III Disadvantaged area
IV Powerful area
Fig. 1 Competitive state model forest industry
4 Results and Analysis 4.1 Contribution of Forest Industry in the Southern Collective Forest Region to GDP Contribution Rate of the Southern Collective Forest Region. Figure 2 presents the results after analyzing output value of each province in the southern collective forest region and its contribution to local GDP (contribution rate of forest industry to GDP = output value of forest industry/GDP × 100%) and there is a significant increase of output value from 2000 to 2020. Total output value of forest industry in this region rose from 651.23 billion CNY in 2000 to 4257.412 billion CNY in 2019, which is 6.55 times more, with an average annual growth rate of 9.9 percent, indicating that the development of this region has been significantly improved and its forest industry is in a relatively stable development stage. Although total output value has increased, the contribution rate of forest industry to GDP revealed a decreasing trend as economic aggregate of collective forest area in southern China has grown more. From 2000 to 2011, contribution rate drop from 12.40 to 7.86%, with an average annual decrease of 0.042%, since then, the reduction decelerated, from 7.86 to 7.21%, with an average annual decrease of 0.0045%. Thus, the development of the southern collective forest region has been growing steadily, while the growth rate lags behind its gross economic output. Output Value and Contribution Rate of Provinces in the Southern Collective Forest Region. Among the region, there are considerable gaps between the developments of each province’s forest industry. The output value of Guangdong, Guangxi, Fujian, Zhejiang and Hunan forestry are comparatively higher than that of other provinces, while that of Yunnan and Hainan are the lowest. From 2000 to 2019, excepting slight fluctuations in individual years, the output value of the majority maintained a tendency of increase, including Hunan, Hubei, Jiangxi, Anhui, Zhejiang, Fujian, Guangdong, Guangxi, Guizhou, Sichuan and Jiangsu. In Fig. 3, every province had a flat increase rate of output value before 2009 and has turned to
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Output Value of provincial forest industry
4500
14.00%
4000
12.00%
3500 10.00%
3000 2500
8.00%
2000
6.00%
1500
4.00%
1000 2.00%
500 0 2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2002
2003
2000
0.00% 2001
Output value of provincial forest industry (billion CNY)
Contrubition rate of forestry to provincial GDP
Fig. 2 Trends and changes of contribution of forest industry to provincial GDP in the southern collective region from 2000 to 2019
accelerate since 2010, for instance, Jiangxi, Anhui, Yunnan, Sichuan, Guangdong, Guangxi and Fujian. Of the increase rate of output value, Guizhou’s was the most outstanding, boosted from 18.04 billion CNY in 2000 to 275.62 billion CNY in 2019, which is 16.28 times more, followed by Guangxi province, Hunan Province and Yunnan Province, which respectively increased by 11.28 times, 8.39 times and 7.94 times in the past two decades. Zhejiang has the minimized increase rate of output value, it increased by 2.79 times, from 67.79 billion CNY in 2000 to 121.77 billion CNY in 2019. The output value of forest industry in Sichuan fluctuated greatly; it increased from 49.1 billion CNY in 2000 to 179.44 billion CNY in 2015, since then, it has ramped up and reached 379.7 billion CNY in 2019. In Table 2, from 2000 to 2020, the contribution rate of forest industry to provincial GDP in Hunan, Jiangxi, Anhui, Zhejiang, Fujian and Jiangsu had a direction of decrease, reflecting that the growth rate of provincial GDP was higher than the increase rate of output value of its forest industry in each province from 2000 to 2020. Other than the above provinces, contribution rate of the rest provinces fluctuated widely, among them, Guangxi and Jiangxi have greater contribution rate, which is about 20% or higher, while Jiangsu had lowest contribution rate, about 5%. Data are derived from Statistical Yearbooks (Year 2000–2019) of each province below.
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F. Liu and H. Li Hunan Zhejiang Guizhou Jiangsu
Hubei Fujian Hainan
Jiangxi Guangdong Sichuan
Anhui Guangxi Yunnan
Output value of provincial forest indutry (billion CNY)
500 450 400 350 300 250 200 150 100 50 0
Fig. 3 Output Value of provincial forest industry in the southern collective forest region (year 2000–2019)
4.2 Analysis on the Trends of the Forest Industry Agglomeration in the Southern Collective Forest Region Based on location quotient method, the forest industry agglomerations in southern collective forest region from 2000 to 2019 are calculated, as shown in Table 3. Taking LQ in 2019 as the horizontal axis and P as the vertical axis leads to a quadrant diagram of competition of forest industry clusters in the region as in Fig. 4. It can be observed that the distribution of competition state of forest industry agglomerations is unbalanced. (1) Predominant area Quadrant I consists of the areas with competitive advantages, including Hunan, Guizhou, Guangxi and Zhejiang provinces that are concentrated in the west and east collective forest region. Between 2000 and 2019, the forest industry agglomeration degrees of Hunan, Guangxi and Guizhou were higher than 1.00, even though Guangxi and Guizhou started with week foundation, their momentum of development was strong and their growth index of cluster degree reached 68.31% and 61.77% respectively. The agglomeration degree of Zhejiang’s forest industry fluctuates greatly and is less than 1 in most years.
Hunan
16.4
15.5
15.2
19.5
18.2
17.3
16.6
18.3
16.5
16.3
15.9
14.2
13.7
13.7
13.3
13.0
12.2
11.6
11.8
12.6
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
9.0
8.9
8.9
8.2
8.1
7.7
6.9
6.9
6.9
6.1
6.4
6.4
5.5
6.3
6.7
6.6
8.7
7.3
8
11.3
Hubei
20.7
19.1
18.9
19.2
18.7
19.5
19.7
20.1
20.4
19.8
21.1
21.6
21.8
21.7
21.5
22.9
25.1
24.1
24.8
25.5
Jiangxi
11.8
11.4
11.8
11.9
13.2
13.6
12.1
12.2
11.9
10.9
12.4
12.9
13.7
14.5
14.7
15.1
18.7
19.7
20.4
22.1
Anhui
8.3
8.2
8.3
8.3
8.5
8.7
8.3
9.1
9.1
9.4
10.5
10.0
10.1
10.2
11.6
11.7
11.8
12.9
10.7
11.0
Zhejiang
15.2
14.9
14.2
14.1
13.8
13.4
13.4
13
13.5
14.3
13.3
13.8
13.1
13.9
14.8
15.0
15.9
18.8
20.2
21.9
Fujian
7.8
7.5
7.4
7.9
7.1
7.1
7.0
6.9
6.8
6.8
7.2
7.2
7.2
7.5
7.9
8.3
8.5
9.2
9.7
10.2
Guangdong
33.2
33.5
34.7
33.7
34.7
35.3
35.9
34.8
34.5
34.1
32.6
33.7
33.1
32.8
31.5
32.9
35.1
31.8
33.3
34.6
Guangxi
20.2
21.3
21.9
21.6
18.1
15.8
13.6
12.9
13.2
13.9
14.4
15.0
14.6
16.1
16.9
18.9
23.1
19.6
18.3
22.5
Guizhou
Table 2 Contribution rate of forest industry to provincial GDP in collective forest areas (year 2000–2019)
12.3
11.8
11.9
11.8
12.4
12.3
14.4
16.1
11.2
12.4
11.9
11.8
14.3
16.2
14.2
12.9
14.7
16.4
14.8
14
Hainan
8.5
9.1
9.4
6.7
6.8
6.9
6.8
6.3
6.2
6.6
8.0
6.9
8.3
8.8
9.5
9.8
11.1
11.6
11.8
12.5
Sichuan
10.7
12.7
13.3
12.3
13.3
13.7
14.8
11.9
17.6
15.5
21.8
22.3
22.7
25.8
20.5
18
18.6
13.1
12.1
14.7
Yunnan
5.0
4.7
4.6
4.7
4.8
4.8
4.8
4.8
4.9
4.9
5.1
5.1
5.3
5.5
5.4
5.7
5.5
6.4
6.3
6.5
Jiangsu
Evaluation of Forestry Industry Agglomeration … 1333
1.21
1.67
1.68
1.70
1.65
1.80
1.63
1.65
1.62
1.49
1.49
1.46
1.39
1.38
1.34
1.26
1.22
1.20
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
11.93
1.19
2001
P(%)
1.12
2000
LQ
– 11.19
0.74
0.77
0.79
0.82
0.77
0.71
0.61
0.57
0.54
0.51
0.55
0.53
0.53
0.60
0.63
0.59
0.69
0.62
0.61
0.89
Hunan Hubei
Province
– 2.60
2.01
1.95
1.94
2.30
2.21
2.16
2.18
2.25
2.16
2.47
2.61
2.62
2.57
2.44
2.39
2.37
2.38
2.22
2.18
1.99
– 10.22
1.54
1.60
1.55
1.56
1.66
1.68
1.51
1.55
1.46
1.37
1.53
1.57
1.61
1.63
1.62
1.57
1.78
1.81
1.79
1.72
Jiangxi Anhui
– 50.07
0.43
0.44
0.43
0.44
0.45
0.45
0.47
0.52
0.51
0.54
0.63
0.60
0.60
0.62
0.69
0.70
0.64
0.86
0.94
0.86
– 21.88
1.33
1.32
1.33
1.44
1.52
1.66
1.67
1.66
1.66
1.61
1.64
1.68
1.54
1.57
1.64
1.55
1.51
1.73
1.77
1.71
Zhejiang Fujian
19.91
0.52
0.53
0.52
0.51
0.51
0.51
0.50
0.50
0.48
0.48
0.28
0.26
0.27
0.29
0.33
0.34
0.33
0.39
0.41
0.43
Guangdong
68.31
2.36
2.44
2.45
2.32
2.35
2.39
2.48
2.39
2.28
2.27
2.05
2.15
2.02
1.89
1.72
1.75
1.81
1.45
1.52
1.46
61.77
2.24
2.19
2.21
2.17
1.65
1.33
1.08
1.01
1.00
1.11
1.16
1.21
1.14
1.24
1.32
1.44
1.72
1.34
1.17
1.37
– 55.65
3.66
3.21
3.16
3.24
3.37
3.65
4.75
6.14
7.85
7.50
5.94
7.40
7.57
7.44
7.11
7.57
7.09
7.02
6.56
7.13
Guangxi Guizhou Hainan
Table 3 Agglomeration degrees of forest industry in southern collective forest region (Year 2000–2019)
25.74
1.09
1.22
1.23
0.87
0.86
0.85
0.85
0.81
0.76
0.82
0.98
0.84
0.97
0.99
1.05
1.02
1.06
1.06
1.04
0.98
57.94
3.04
3.10
3.05
2.93
2.93
2.93
3.09
2.79
3.39
3.19
3.92
3.91
3.86
4.02
3.38
2.91
2.72
2.13
1.94
1.93
– 24.30
0.23
0.22
0.21
0.22
0.23
0.22
0.22
0.23
0.23
0.24
0.25
0.25
0.27
0.28
0.27
0.28
0.24
0.31
0.29
0.28
Sichuan Yunnan Jiangsu
1334 F. Liu and H. Li
Evaluation of Forestry Industry Agglomeration …
1335
Growth rates of agglomera on degrees %
80
Guangxi Guizhou
60 Zhejiang
40 Guangdong
20 Hunan
0
0.5 Jiangsu
Hubei 0 -20
1
1.5 Anhui
Jiangxi 2
2.5
3
3.5
Fujian
Sichuan -40 -60
Hainan Yunnan
-80
Fig. 4 Quadrant diagrams of competition statuses of forest industry agglomeration in southern collective forest region
(2) Area with potential Quadrant II is made up with potential areas, Guangdong is one of the representatives. From 2000 to 2019, the agglomeration degree of Guangdong’s forest industry was lower than 1.00, however, it has tend toward increase since 2008, illustrating a long-term competitiveness. During the 10th Five-Year Plan period, Guangdong province formed a new pattern of industrialization of its forest industry, with plantation and afforestation, woods production, forest production and diversified management, meanwhile, reform of forestry science and technology had been kept deepen. In the 11th Five-Year Plan period, Guangdong’s ministry of finance set up a specific fund for forestry science and technology for the first time, which is used for strengthen the forestry scientific research and development and support the establish of public platforms for research and development, in order to integrate the advantages of science and technology resources and improve capacity of innovation in science and technology. Furthermore, in the 12th Five-Year Plan period, Guangdong focus on exploiting forest industry to transform primary industry focusing on forest resources to pluralistic mechanism of development. In response to the implementation of national laws and regulations on land circulation, Guangdong issued the “Measures on the Management of wood-filled Lands and Woods Circulation”, resulting in standardized forest circulation management of a tract of 1,186,000 hm2 . The government also provides training to new types of forestry business
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F. Liu and H. Li
and there had been a number of 1510 various cooperatives were initiated by 2015, containing 456,000 farmers. (3) Disadvantaged area In Quadrant III is disadvantaged area including Jiangsu, Hubei and Sichuan. From 2000 to 2019, their agglomeration degrees of forest industry were lower than 1.00 and growth rate respectively was –24.30%, –11.19% and –50.07%, pointing that the competitiveness of each province raised less than their cluster degrees declined. (4) Powerful area In Quadrant IV, there are Anhui, Jiangxi, Fujian, Hainan and Yunnan defined as powerful areas with agglomeration degrees all exceed 1.00, which is higher than the average of the southern collective forests, fully embodies the competitiveness of each province. It is worth noting that the cluster degree of forest industry in Hainan was once exceeded 3.00. Hainan province lies in the tropics and is the China’s reserves of tropical rain forest and tropical monsoon rain forest. In July 1999, its government lunched "Guidelines for Construction of Hainan as Ecological Province", stating a 30-year (Year 2000–2030) ecological development plan, aiming to build Hainan to a province offering developed forest industry system, high-qualified ecologic environment, harmonious coexistence between man and nature, and national first rated living environment. Hainan government has formulated a series of state regulations and policies to improve management system of forest industry and ensure the implementation of its ecologic construction. In 2013, President Xi paid a visit to Hainan and claiming that forests is the pillar of our ecosystem and the relationship between fast development and proper protection should be maintained under a rational vision. Additionally, Hainan should make efforts on "increase green" and "protect blue" and lead a successful way to national ecological civilization construction, thus benefits future generations with a sustainable "green bank". Hainan has continuously deepened its forest industry reformation and gradually improved the quality and ecological functions of forests; it also stimulates its forest industry with an annual input of 1.3 billion CNY. In Hainan, the forests are 2.175 million hm2 covering 63.3% of its total land area in 2019 while the ratio was 51% in 2000; also, its total stock of living wood was 163 million m3 in 2019. In recent years, forest therapy industry in Hainan has been acted a turning point of Hainan’s forest industrial supply-side reform. There are 8 national forest parks, 17 provincial forest parks and 32 state-owned forest farms, committed to the development of Hainan’s forest industry by creating forest ecological tourism products such as tropical rain forest tour, and tropical flower garden tour. In 2019, under the competition with other provinces, Anhui, Jiangxi, Fujian and Hainan should upgrade their forest constructions and enhance their comparative advantages in forest industry. Furthermore, Yunnan province has a high agglomeration degree of its forest industry, which was 3.04 in 2019 and has been remarkably above 2.5 since 2003. Its agglomeration degree rocketed by 57.94 from 2000 to 2019, illuminating that forest
Evaluation of Forestry Industry Agglomeration …
1337
industry in Yunnan Province has been developed rapidly in the past twenty years. Although output value of Yunnan’s forest industry is relatively backward, it shows a great potential in future development. Wooded lands and forests respectively cover 63.42% and 59.7% of Yunnan’s total lands; total growing stock of living woods was 2.132 billion m3 in 2019. Forests make major contribution to poverty eradication in western China, reflected in a 1.68 trillion CNY of annual service value of forest ecosystem and Yunnan’s ecological protection index was 75.79 points that is in the front rank in China. Data are derived from Statistical Yearbooks (Year 2000–2019) of each province above.
5 Conclusions and Outlook 5.1 Conclusions Based on the analysis of output value of provincial forest industry in China’s southern collective forest region, contribution of forestry output value to GDP and competition statuses of forest industry from 2000 to 2019, the following can be concluded: (1) From 2000 to 2019, output value of forest industry in the southern collective forest region had been showing an increasing trend and development of forest industry had been significantly improved. However, contribution rate of forest industry to GDP had been decreased due to larger increase of provincial economic aggregate. (2) There are gaps between the developments of forest industry in the southern collective forest region; among them, Guangdong, Guangxi, Fujian, Hunan, Jiangxi and Zhejiang has higher output value, while Hainan, Guizhou and Yunnan has lower output value. In southern collective forest region, productive areas are concentrated in Guangdong, Guangxi and Fujian; Yunnan is rich in forest resources with development potential; Forest industry in Guangxi, Jiangxi and Guizhou have greater contribution of output value to provincial GDP and forests is valued high in these provinces, whereas Jiangsu has the lowest contribution rate of forest industry to its GDP. (3) There are disparities between competition statuses of forest industry agglomeration in southern collective forest areas: Hunan and Zhejiang, Guizhou and Guangxi lie in predominant areas of quadrant diagram; Guangdong province lies in potential areas; Jiangsu, Hubei and Sichuan sit in disadvantaged areas and Anhui, Jiangxi, Fujian, Hainan and Yunnan sit in powerful areas.
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5.2 Outlook In recent years, the development of forest industry in China’s southern collective forest region has been significantly improved, but the gaps between developments of provinces are wide. Basically, the conclusions are consistent with studies of Liao Wenmei [15] and Wang Zhen [16] et al. Liao also pointed that forest industry of each province in the southern collective forest region develops faster than most that of other provinces in China, proving that the forest industry plays an important role of national economy. As a rural revitalization strategy was issued, developing forest industry became one of the main strategies of China’s targeted poverty alleviation program, which drives the development of rural communities in southern collective forest areas. Energetically develop forest industry in the light of local conditions and promote competitiveness are the keys to implement poverty alleviation strategies. To solve the problem of unbalanced status among developments of provincial forest industry, provincial government should rationally allocate forest industry productivity and customized the development plan. Additionally, the government should foster a favorable environment for the development of forest industry clusters. On one hand, the government of competitive areas should improve the innovation ability and upgrade the transformation of forest industry, thus stimulate the modernization of southern collective forest areas; on the other hand, the government of disadvantaged areas should give financial and policy support. In terms of the southern collective forest areas as a whole, provinces should strengthen cooperation and facilitate the development of disadvantaged areas through the superiority of forest industry clusters. This paper analyzed the competition status of southern collective forest areas applying location quotient method and competitive state model, providing a valuable reference for the development plan of forest industry in southern collective forest areas. However, this paper is lack of analysis on the advantages of forest industry comparing with primary, secondary and tertiary industries while applying the output value of forest industry on the statistical data of forestry output value, thus suggesting a direction to further studies.
References 1. Zhao C (2017) The development of forestry economy in China from the perspective of ecological civilization. China For Econ 4:70–71 2. Wen Y (2000) The function of sustainable forest products in China’s social economy. J Beijing For Univ s1:59–62 3. Liu M, Sun Y, Zhang S (2017) Thoughts on the sustainable development of forestry in China. For By-Product Spec China 4:97–98 4. Zhang Z (2005) Researches on the strategy system of Chinese forestry industry’s modernization. Prob For Econ 25(1):7–10 5. Huang L, Zhai Y, Liang J (2008) Forestry industrial structure changes and economic growth: contributions and space difference. China For Econ 5:5–8
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6. Baldwin RE, Forslid R (2000) The core-periphery model and endogenous growth: stabilizing and destabilizing integration. Economic 67(267):307–324 7. Martin P, Ottaviano GIP (2001) Growth and agglomeration. Int Econ Rev 42(4):947–968 8. Zhang Y, Liu X (2008) Agglomeration economy and economic growth: empirical evidence from China. J World Econ 31(3):60–70 9. Jiang Y, Xu X (2021) Analysis on forestry industry cluster level and efficiency in Heilongjaing province. For Econ 38(6):55–58, 69 10. Liu X, Ma G, Mai Q (2017) Forestry industry agglomeration and regional economy growth of Yunnan province. J Southwest For Univ 37(1):216–220 11. Feng Q, Tan F (2011) Econometric analysis on forestry industrial agglomerations in Guangxi. J Anhui Agri Sci 39(30):18656–18659 12. Lin Z, He P, Li X (2017) The pattern and mechanism of agricultural geographical agglomeration in Sichuan province. Chin J Agri Res Reg Plan 38(1):207–215 13. Cheng P, Li J, Zhang H, Zhang Z (2018) Forest industry agglomeration, forest economic growth and its space spillover effect – based on the spatial analysis of the marginal penal data from 2004 to 2015. J Anhui Agri Univ 45(06):1063–1070 14. Zhang H, Wang L, Tian X (2010) A study on the agglomerative performance of regional tourism industry cluster and the comparison of its competitive situation-based on the empirical analysis of 21 cities in Guangdong province. Econ Geogr 30(12):2116–2121 15. Liao W (2014) Analysis on the industrial structure evolutions and its differences of the forest economic growth from 1995 to 2011 of 13 provinces (autonomous regions) in the Southern collective forest region of China. Scientia Silvae Sincae 50(8):131–140 16. Wang Z, Liu W, Weng N (2015) The comprehensive measurement and analysis on the level of forestry industry development in Southern collective forest. Iss For Econ 35(1):68–74
Statistical Measurement of SMEs’ Credit Risk from the Perspective of Financial Crisis Chenyao Zhang
and Jinsong Zhang
Abstract Since the US sub loan crisis, countries have paid more attention to the prevention of credit risks. SMEs are more difficult to measure their credit risk than large enterprises due to their own limitations, and therefore the issue of their risk measurement deserves discussions. This paper analyzes the current situation of SMEs’ credit financing, properly selects the financial data of listed companies on the New OTC Market, and establishes a Logistic regression analysis model based on factor analysis of cross section data, so as to measure the credit risk level of SMEs. Keywords Financial crisis · SMEs · Credit risk · Logistic regression analysis
1 Introduction The impact of the sub-prime mortgage crisis in the United States began to emerge starting from the spring of 2006. And by August 2007, the sub-prime mortgage crisis had swept across the world [1–3]. The negative impact of the US sub-prime crisis was multi-faceted and multi-layered. Since the US sub-prime crisis, commercial banks and other non-bank financial institutions worldwide have paid more attention to the measurement of credit risk. As an important part of the market economy, the healthy development of SMEs is of great importance to the overall national economy [4]. However, SMEs’ credit risk is often difficult to assess accurately due to the external and internal constraints, that is, imperfect credit systems and inadequate financial systems. Therefore, it is very important to study the credit risk measurement factors of SMEs in order to accurately identify their credit risks [5, 6].
C. Zhang (B) Business School, Yangzhou University, Yangzhou 225000, China e-mail: [email protected] J. Zhang Medical School, Soochow University, Suzhou 215000, China © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_135
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C. Zhang and J. Zhang
2 Literature Review According to the literature, the questions of how to assess the credit risks of SMEs and prevent them effectively, so as to promote the healthy and stable development of the credit market, has become an issue which has been widely studied and discussed by experts and scholars after the US sub-prime crisis in 2008. The first one is to explore the methods of how to optimize and upgrade the measurement indicators of credit risk from the perspective of SMEs. Su Hui (2019) proposes optimizing the entry rule indicators among the qualitative indicators, so as to ensure the authenticity and completeness of the loan application information submitted by SMEs in the entry process. After that, it is also necessary to screen out the invalid indicators of the credit risk scorecard for SMEs through stability testing, so as to ensure the objectivity and accuracy of the scorecard evaluation results. Liu Qi you (2010) argues that it is more scientific and reasonable to use a modified VaR (Value at Risk) method, i.e. CVaR based on the GARCH model, to measure risk. The advantage of this method is that it can reflect the size of the average potential loss that may be suffered if the loss exceeds the VaR, making up for the shortcoming that the VaR cannot defect of information reflecting loss tail, thus effectively reducing the possibility of catastrophic risk for banks. The second is to study the management mechanism of commercial banks’ credit risk from their perspective. From the perspective of supply chain finance, Li Guangrong (2020) proposes a six-factor systemic analysis framework based on system theory and suggests that commercial banks should deepen their supply chain relationship management to reduce the probability of credit risk events and losses. At the same time, they are supposed to innovate the application of information technology to solve the problems of information asymmetry and business collaboration. Bei Weizhi (2009) proposes to accelerate the construction of internal database to improve the quantification of credit risk, by analyzing the current situation of credit risk management in commercial banks and the risk management mechanism. This paper examines the probability of financial distress of a company listed on the New OTC Market based on key financial indicators. Based on the faceted that the existing literature tends to take only a few key variables when measuring credit risk, there may be a problem of omitting indispensable variables. This paper selects 12 variables to explain the financial information, which has a broader coverage. In addition, the article adopts the method of factor analysis to pre-process the explanatory variables in order to optimize the explanatory effect of the subsequent regression model.
Statistical Measurement of SMEs’ Credit Risk … Table 1 Sample classification
Type of enterprise
1343 Training sample
Test samples
Total
Risk enterprise
40
10
50
Health enterprise
120
30
150
Total
160
40
200
3 Selection and Description of Credit Risk Indicators for SMEs 3.1 Selection of the Research Sample Considering that the financial data of non-listed SMEs are not publicly available and the difficulty to obtain, this paper selects the New OTC Market listed enterprises as the research object and uses the CSMAR database. This paper collates the New OTC Market companies with fewer missing entries and conducts random screening, and finally selects 200 of them as the research sample. In terms of the difficulty of collecting exposure indicators for SME credit risk, we use ST as a criterion to measure the risk. It is not difficult to reason that a company that is ST will have a higher credit risk. In this paper, whether companies denoted as ST is show as “risky companies” and “healthy companies” respectively, and are represented by dummy variables 1 and 0. In terms of sample classification, this paper divides the samples into two categories, training samples and testing samples. The specific sample classification is shown in Table 1.
3.2 Selection of Indicators China has not yet established a specific and clear indicator system for SME credit risk assessment at present. The indicators given in the relevant literature are also divergent and scattered. From the author’s point of view, the indicators for measuring credit risk should have these following four characteristics: Comprehensiveness. The indicators selected should reflect the financial position and solvency of an enterprise in a comprehensive manner, without missing key factors. There should be multiple dimensions of indicators to cover a wider coverage of explanatory variables. Consistency. This is a basic requirement for explanatory variables in econometrics, i.e. the explanatory variables selected should be consistent in their direct economic relationship with the explanatory variables.
1344 Table 2 Key financial indicators of SMEs
C. Zhang and J. Zhang Solvency
X1 current ratio X2 cash ratio X3 asset liability ratio
Development capacity
X4 growth rate of total assets X5 net profit growth rate X6 growth rate of operating income
Profitability
X7 return on assets X8 return on net assets X9 return on investment
Operating capacity
X10 accounts receivable turnover X11 inventory turnover X12 total assets turnover
Operability. The indicators selected should be publicly available, easily accessible and relatively complete, with few missing data entries. This will reduce the operational difficulty of building and applying the model to some extent, thus making it more specific and feasible. Simplicity. The measures chosen should also be common and easy to understand and estimate. This not only makes the model more user-friendly, but also reduces the probability of making mistakes in data processing and model construction. Combining the above ideas, this paper refers to the ideas of the CAMEL model and selects 12 financial indicators based on the characteristics of SMEs’ finances and their risk measurement needs in four aspects: solvency, growth, profitability and operating capacity, as shown in Table 2.
4 Factor Analysis and Model Construction of Credit Risk Indicators 4.1 Factor Analysis of Explanatory Variables This paper selects 12 explanatory variables to explain the level of credit risk of SMEs. However, a larger number of explanatory variables may cause the problem of multicollinearity in model prediction. With reference to the relevant literature, this paper adopts the method of factor analysis to do the dimension reduction treatment for the indicators. The aim is to rearrange the original variables and consolidate them into a few key credit risk influencing factors, so as to build a logistic regression model instead of using the original explanatory variables, with a view to achieving better explanatory effects.
Statistical Measurement of SMEs’ Credit Risk … Table 3 KMO and Bartlett tests
1345
KMO sampling suitability quantity
0.507
Bartlett ball test
Approximate chi-square
786.842
Freedom
66
Significance
0.000
In terms of correlation tests, the KMO and Bartlett’s sphericity tests, as shown in Table 3. We can draw these following two main results. The first one is that the KMO value is 0.507 > 0.5, indicating that the degree of information overlap between the variables is passable and there is a greater possibility of deriving a more satisfactory factor analysis mode. The another one is that the significance level is extremely low, which can reject the original hypothesis that the variables are independent of each other, i.e. there is a strong correlation between the variables. Combining these two analyses, it can be concluded that the selected explanatory variables can be subjected to factor analysis. In terms of principal component analysis, consideration was given to making the common factors extracted by the factor analysis method having practical implications and to make the coefficients in the factor loading matrix more significant. This paper uses rotation based on Calculation of initial factor load matrix in order to reassign the relationship between the factors and the original variables so that the relationship between them can be better explained. The calculated explanations of each factor for the total variance are shown in Table 4. As can be seen from the table, the cumulative contribution of the five principal components to the variance reached 65.081%, which has a relatively strong explanatory power. And after rotation, the difference in the percentage of the total variance accounted for by each factor narrowed, indicating that the amount of information was more optimally allocated. Further, this paper also calculated the component score coefficient matrix for each factor. By summing the columns of the component score coefficient matrix and weighting the original explanatory variables according to the score coefficients, the expressions of the common factors can be obtained. After that, this paper will use the factors to construct the logistic regression model instead of the original explanatory variables.
4.2 Construction of the Logistic Regression Model The dummy variables 0 and 1 are introduced as the explanatory variables of this regression model are whether or not the SME is in ST, i.e. whether or not there is financial distress. In view of this, this paper adopts a binary logistic regression model, which features a binary categorical variable as the dependent variable and a continuous variable as the independent variable. The logistic model was chosen for the regression analysis based on the intuitive nature of the actual meaning reflected in the model.
1.371
1.265
1.031
3
4
5
8.596
10.546
11.426
16.460
65.081
56.486
45.940
34.514
Extraction method: principal component analysis
1.975
2
18.055
Cumulative%
1.031
1.265
1.371
1.975
2.167
8.596
10.546
11.426
16.460
18.055
Variance%
Total
18.055
Variance%
Total
2.167
Initial characteristic value
Initial characteristic value
1
Component
Table 4 Explanation of total variance by factors
65.081
56.486
45.940
34.514
18.055
Cumulative%
1.040
1.364
1.454
1.906
2.047
Total
8.663
11.365
12.117
15.880
17.056
Variance%
Initial characteristic value
65.081
56.418
45.054
32.936
17.056
Cumulative%
1346 C. Zhang and J. Zhang
Statistical Measurement of SMEs’ Credit Risk … Table 5 Results of the Hosmer-Lemeshow test
1347
Chi square
Freedom
Significance
3.118
8
0.927
Table 6 Results of regression analysis Variable
B
SE
Wald
DF
Sig
Exp(B)
F1
– 1..504
1.353
1.235
1
0.266
0.222
F2
– 7.988
1.842
18.799
1
0
0
F3
– 0.502
0.235
4.562
1
0.033
0.606
F4
– 0.276
0.378
0.531
1
0.466
0.759
F5
– 0.223
0.194
1.323
1
0.25
0.8
C
– 4.35
0.932
21.792
1
0
0.013
The original sample for the regression analysis was derived from the training set of 160 samples mentioned in the previous section. Among them, 40 were risky firms and 120 were healthy firms. The dependent variable for the regression was a dummy variable, i.e. financial health indicators (risky firms are denoted by 1 and healthy firms are denoted by 0). The independent variables for the regression were, the five common factors obtained by factor analysis method after dimensionality reduction in the previous section, denoted as F1, F2, F3, F4 and F5. The regression analysis was conducted using SPSS 23.0 software, and the results of the Hosmer-Lemeshow test and the regression analysis obtained results, are shown in Tables 5 and 6 respectively. As seen from Table 6, F2 and F3 have good significance and therefore the following credit risk assessment model can be derived. p = −4.35 − 7.988F2 − 0.502F3 (1) Logit(P) = ln 1− p The probability of default can be deduced that from this: P=
exp(−4.35 − 7.988F2 − 0.502F3) 1 + exp(−4.35 − 7.988F2 − 0.502F3)
(2)
4.3 Analysis of the Predictive Power of the Model Equation (2) above allows for the estimation of the probability of default of a firm and thus measures the credit risk of that firm. In this paper, the test sample set up in the previous section is selected and brought into the formula to calculate the probability of risk. According to the calculation results, as shown in Table 7. The model predicts risky and healthy enterprises correctly at 70% and 96.7% respectively under the threshold of 0.5, and the overall correctness of the model is 90%. This shows that the model is accurate for the assessment of credit risk of SMEs.
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Table 7 Model test results Type
Train Observe
Test Assess
Accuracy (%)
Observe
Assess
Accuracy (%)
Risk
40
32
80
10
7
70
Health
120
117
97.5
30
29
96.7
Total
160
149
93.1
40
36
90
5 Conclusions and Recommendations 5.1 Conclusions In the measurement and statistics of the relevant data, the author found that: the score coefficients of each factor component in the factor analysis were relatively scattered, and the significance of the beta coefficient of the regression model was not very good. Therefore it is believed that there may be two reasons as follows. Firstly, there is a natural disadvantage of the data as the SME stocks are less liquid and not traded as frequently as the main board stocks. Secondly, the data are not very stable because the size of the companies corresponding to the SME stocks is small and they are more significantly affected by policy factors.
5.2 Recommendations In this paper, the principal component extraction and logistic regression found that the common factor F2, which focuses on solvency, can serve as a better assessment. It can be seen that the solvency type of financial information represented by the gearing ratio and cash ratio of SMEs can better reflect the overall financial health of the enterprises and thus map out the credit risk level of the enterprises. In view of this, commercial banks’ credit departments can focus on SMEs’ solvency financial indicators as an important reference for assessing their credit risks; SMEs should rationalize their assets and liabilities to meet the need for liquidity and ensure better solvency. In addition, profitability, represented by return on investment, and accounts receivable turnover, represented by operating capacity, both play a role in the other significant metric, F3. This shows that SMEs should organize their investment activities scientifically and rationally, and make sound investments under the premise of effective risk control. At the same time, business operations and managers should formulate the right business strategies to effectively improve the efficiency of their operations. For regulators, the takeaway is that the measurement of SMEs’ profitability and operating capacity should not be overlooked. Moreover, the impact of platform development capability on credit risk is not very significant. This also reflects the fact that the main concern of commercial banks about the credit risk of
Statistical Measurement of SMEs’ Credit Risk …
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SMEs is how well the enterprises are able to grow. It is easy to think that SMEs are currently in a historical period of transition from traditional industries to hightech industries, and a large number of innovative products are facing the problem of downstream market acceptance. Therefore, the industrial chain will be an issue that needs to be carefully considered, both for commercial banks and SMEs. Acknowledgements The authors contributed equally to this work. Entrepreneurship training plan for college students of innovation and entrepreneurship College of Yangzhou University “C202011117012Y”.
References 1. Tian T (2021) Study on credit risk strategies of commercial banks for small and medium-sized enterprises. Bus Manag 04:154–158 2. Guangrong L, Yinxue G, Ying H (2020) Credit risk characteristics, analysis framework and management countermeasures of supply chain finance. Bus Econ Res 13:167–169 3. Hui S, Wei G (2020) Optimization of credit risk evaluation indicators for small and micro enterprises in banks. Finan Accoun Mon 01:27–32 4. Jingui Z, Hou Y (2014) Empirical analysis of credit risk of small and medium-sized enterprises based on logit model. Friends Accoun 30:40–45 5. Qiyuan L, Nengfu Z, Tiesheng L (2010) Research on the CVaR credit risk measure based on GARCH model. Stat Dec Making 10:26–29 6. Weizhi B (2009) Research on credit risk management mechanism of commercial banks from the perspective of financial crisis. Reg Finan Res 09:36–39
Assessment of the Quality of Customs Services Alexander Shtrikov , Natalia Persteneva , and Darya Shtrikova
Abstract In the context of ever-increasing volumes of international economic activity, the issue of the quality of customs services has great importance. In connection with the annual increase in demand for customs services, there is a question of solving the following tasks: the quality and availability of customs services provided and the development of a quality monitoring system, indicators of methodological support of customs services provided. The issues of criteria and principles for assessing the work of customs authorities and quality of customs services, taking into account the specifics of the provision of customs services, are considered. To assess the quality of customs services, a consumers’ satisfaction model, based on individual or group assessment, was chosen. A questionnaire was developed to assess the quality criteria of customs services. The survey involved 40 enterprises of the Samara region participating in the foreign economic activity. The obtained data were subjected to correlational and hierarchical cluster analysis. The Data Envelopment Analysis method was used to evaluate the efficiency of the responding enterprises. As a result of collecting data on the questionnaire, three clusters were identified. The comparative efficiency of economic activity of the respondents is analyzed. The most problematic indicators of assessing the quality of the work of customs authorities have been identified. Measures to improve problematic issues have been proposed and their effectiveness has been assessed. Keywords Foreign economic activity · Customs authorities · Customs services · Satisfaction · Evaluation criteria · Efficiency · Costs
A. Shtrikov (B) · N. Persteneva Samara State University of Economics, 141, Sovetskoy Armii Street, Samara 443086, Russian Federation e-mail: [email protected] D. Shtrikova Samara State Technical University, 244, Molodogvardeyskaya Street, Samara 443100, Russian Federation © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_136
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1 Introduction The idea of assessing the quality of customs services is quite common today. According to the Decree of the Government of the Russian Federation dated May 23, 2020 No. 1388-r “On Approval of the Strategy for the Development of the Customs Service of the Russian Federation until 2030”, various interrogative methods for monitoring the quality of public services are used to inform and consult through a questionnaire of citizens and legal entities. The criteria for evaluating the work of customs authorities are: 1) 2) 3) 4)
the speed of customs operations of import and export; reduction of costs of interested parties in the course of customs operations; timeliness and completeness of receipt of customs payments; the effectiveness of counteracting crimes and administrative offenses.
Other indicators of the quality of customs services are efficiency, confidentiality, objectivity and independence of execution, completeness and integrity of the performance of services, law enforcement guarantee and competence. Despite the rather large amount of literature on the issues of customs services, the problem of assessing the quality of customs services remains poorly understood. The article by E. Fuchs, V. Novikov and S. Novikov indicates the complexity of the customs control after the release of the goods, depending on the type of transport in which the goods are transported. Attention is drawn to the importance of defining the main directions for improving customs control after the release of goods, as well as developing scientific and practical recommendations to improve this type of control. An innovative methodology is proposed, whose feature is both the determination of the possible consequences of violations for the state and society, as well as the probability of an violations, followed by the modeling of the level of risk using the MATLAB program [1]. The article by Yu. Somov, V. Burdin, T. Mikhailenko and S. Novikov analyzes the digital information and communication technologies used in the Russian customs authorities to improve the quality of customs services and identifies opportunities for their improvement and improvement of customs practice. The experts assessed the degree of existing and possible “intellectualization” of the examined customs information technologies [2]. Using firm-level Egyptian customs data and World Bank Doing Business data for the period 2005–2016, the article by R. Hendy and Ch. Zaki examines the impact of administrative barriers to trade, including the quality of customs services, on firms’ exports. The results confirm that the quality of customs services can be perceived as a fixed and variable cost that affects both extensive and intensive services. Perishable and seasonal products are more sensitive than other products, and large companies are more sensitive than small and medium exporters [3]. The article by M. Pourakbar and R. A. Zuidwijk develops models that allow quality of customs services to be optimized to identify high-risk containers without impeding the flow of safe containers through additional port delays. The model characterizes the optimal speed of information and physical examination based on risk factors [4].
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The paper by D. Elliott and C. Bonsignori assesses the role of instant clearance customs procedures in facilitating trade flows and analyzes the international express air freight acts as a channel to this effect. Use a ’Gravity’ model, including drugs based on personal data from the Global Express Association, which may be significant for trade flows: the introduction to the media for trade flows in a 5% [5]. Customs services are an important effective factor in the development of the export of goods and services. The study carried by H. A. Shirsavara and M. Shirinpour examines the impact of electronic customs on the export of goods and services. The results indicate that the identification of new opportunities to reduce transaction costs in exporting is effective, it aims to create a competitive advantage and it will develop in the case of increase in export [6]. The implementation of electronic customs platforms to ensure compliance and facilitate trade is a key strategic issue for governments and customs agencies around the world. This ensures a higher quality of customs services. The objective of the study done by L. Urciuoli, J. Hintsa and J. Ahokas is to understand what factors encourage or hinder the usage of electronic customs platforms. The results show that factors such as cost reduction and simplicity of use are significant in the use of electronic customs platforms, while the profitability and utility of electronic customs platforms do not have a significant impact [7]. The purpose of the article by J. Biljan and A. Trajkov is to analyze the importance of a risk management approach to improve the quality of customs performance, with a special focus on the experience of Macedonian customs. The main feature of the customs risk management approach is to specify which persons, goods and vehicles must be controlled. The Customs Administration of the Republic of Macedonia carries out modern improvements and developments in the field of standardization and harmonization of customs procedures and administrative systems [8]. The study carried by N. A. Panayiotou and V. P. Stavrou provides a systematic review of the literature on electronic services provided by the government to businesses, including customs services and e-customs. Case studies and surveys are the most popular research methods [9]. The project carried by P. Morales-Fusco, S. Saurí, A. M. Lekka and I. Karousos developed a common system to assess the performance of 61 Mediterranean ports in the form of a set of key performance indicators (KPIs) together with a list of best practices related to operational and customs procedures. The ports have been assigned key performance indicators related to traffic, financial, operational and human resources, sustainability and customs procedures. These values have been compared with the current practice in relation to customs formalities. A low correlation was found between the achievement of KPIs and implementation of the best practices in customs procedures [10]. The main objective of the article by K. Trubitsyn, E. Mitrofanova, V. Khryashchev and A. Mitrofanova is to study the improvement of the quality of state customs services from the development of the workforce of customs officials. The authors developed two types of questionnaires: for the distribution of state customs services according to the Kano model and for the assessment of the quality of each service. The methodology proposes relevant priority areas for the development and impact
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on the level of consumer (participants in foreign economic activity) satisfaction and on the quality of the services provided by customs officials with higher job potential [11]. The article by S. Aljaber, N. M. Almutairi and A. Alkandari presents the design of an application that provides internal and external customs services for both the customs officer and the citizens. The internal services area is used by the employee and the external services area is used by the citizens. As a result of this application, it saves time and effort for citizens and customs and reduces the number of customs inspectors [12]. The article by E. P. Levina presents a unique approach to the development of tools for customs and customs regulation of imports, formulates an original definition of customs service, identifies a contradiction between the current model for implementing the principle of expansion established by the World Trade Organization and justifies the need for import duty rates to differentiate this group of goods. The most effective instruments to regulate the importation of goods are the uniform customs tariff and the nomenclature of foreign trade goods [13]. The article by K. Trubitsyn. E. Mitrofanova and V. Khryashchev deals with the problems of the concept, structure and assessment of the job potential of customs officers. The structure of the labor potential of customs personnel was determined. Based on the analysis, an author methodology for assessing job potential was developed, which is an integral part of a comprehensive system for assessing job potential, and an algorithm was modeled to determine a comprehensive assessment [14]. The article by S. Zubenko notes that in connection with the increasing volume of foreign economic activity of the Russian Federation, the tightening of the rules and conditions of international trade, there is a growing need to develop modern customs technologies and improve the quality of customs services to ensure economic development and foreign economic activity [15]. The approach of Yu. Gupanova and Yu. Chechulin for a comprehensive assessment of the quality of customs services is proposed, including assessment principles, assessment areas, a methodology for calculating the overall assessment of quality, and specific indicators for assessing of each indicator [16]. The article by D. V. Lapina provides an analysis of the existing system of indicators to evaluate the activities of customs authorities. The conceptual provisions for the creation of an integrated system of indicators of the efficiency and effectiveness of the activities of customs authorities are presented. A methodology is proposed for the expert analysis of the balance and harmonization of the system of indicators of efficiency and effectiveness of customs activities and ways of its practical implementation [17].
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2 Methods and Materials To assess the quality of customs services, a participant satisfaction model was chosen. This model based on individual or group assessment. The purpose and objectives of monitoring and measuring customer satisfaction should be clearly defined, which may include, for example: • • • •
assessment of consumer response to services; obtaining information on specific aspects; investigating the causes of consumer complaints; monitoring of consumer satisfaction.
In the course of the work, a questionnaire, based on Yu. Gupanova’s questionnaire (Yu. E. Gupanova “Methodology of quality management of customs services: monograph”, RIO of the Russian Customs Academy, Moscow, p. 152, 2017), was developed in which the following criteria for the quality of customs services were evaluated on a 7-point scale: 1. 2. 3.
The level of culture of specialists working with clients in call center; Completeness of the services provided; The level of information support about the receipt of services on the FCS (Federal Customs Service) website; 4. Time spent on the implementation of the full package of services; 5. Level of interactions between customs structures; 6. Level of corruption; 7. The level of convenience of the site; 8. Feedback from FCS officials; 9. Professionalism of customs officials; 10. Organization of waiting areas for customers on the territory of warehouses. The survey involved 40 enterprises participating in foreign economic activity of the Samara region. The data obtained were subjected to a hierarchical cluster analysis, ordering objects into relatively homogeneous groups by combining respondents into clusters (groups) according to the degree of similarity of their answers and highlighting the indicators that are most important for each cluster. The following operations were sequentially carried out: preparing a table with data, correlation analysis in the Statistica 10 program, hierarchical clustering, grouping the questionnaires of respondents in accordance with the cluster, compiling a table of values for each cluster and checking which quality indicators are decisive for each cluster. As a clustering method, the Ward method was used, which involves the use of the squared Euclidean distance as a measure of proximity between objects. To analyze the significance of indicators for each indicator, the mean value, mode and median were calculated. The Data Envelopment Analysis—DEA method was used to evaluate the efficiency of the responding enterprises. The model of the DEA method for determining the enterprise that most effectively conducts its foreign economic activity will include
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independent variables X1 (the share of employees involved in foreign economic activity), X2 (the share of the cost of wages of employees of the foreign economic activity department from the total expenses of the enterprise) and the function Y1 (efficiency of employees of the foreign economic activity department in filling out customs declarations). The EMS program calculates the CCR model, which determines the maximum efficiency rating and leaders in the analyzed group according to the selected criteria, and the Super-efficiency model allows to determine the most efficient company from all companies with a 100% result according to the CCR model.
3 Results As a result of data processing, three clusters were identified. The answers of the first cluster which includes enterprises 3, 5, 7, 10, 18, 19, 20, 27, 28, 36, 37, 38 (see Table 1) combine the following features: they highly appreciate the level of culture of specialists of call center, the completeness of services provided, the level of information about receiving services on the FCS website, the level of corruption, professionalism of employees and organization of waiting areas for customers on the territory of warehouses. Rather, they are satisfied with the amount of time spent on the implementation of the full package of services, the level of interaction between customs structures, the quality of feedback from FCS. The enterprises included in this cluster are united by the fact that they are all active participants in foreign economic activity, their specialists already have work experience and have interaction with customs authorities. Table 1 Cluster No. 1 survey results Criteria
Mean
Mode
Median
The level of culture of specialists of call center
2.75
3
3
Completeness of the services provided
2.75
3
3
The level of information support about the receipt of services on the FCS website
2.5
3
3
Time spent on the implementation of the full package of services
1.92
2
2
Level of interactions between customs structures
1.75
2
2
Level of corruption
3
3
3
The level of convenience of the site
1.42
1
1
Feedback from FCS officials
2.25
2
2
Professionalism of customs officials
3
3
3
Organization of waiting areas for customers on the territory of warehouses
2.59
3
3
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Table 2 Cluster No. 2 survey results Criteria
Mean
Mode
Median
The level of culture of specialists of call center
1.36
1
1
Completeness of the services provided
2.91
3
3
The level of information support about the receipt of services on the FCS website
2.18
2
2
Time spent on the implementation of the full package of services
2.09
2
2
Level of interactions between customs structures
1.73
2
2
Level of corruption
2.09
2
2
The level of convenience of the site
2
3
2
Feedback from FCS officials
1.82
22
2
Professionalism of customs officials
2.91
3
3
Organization of waiting areas for customers on the territory of warehouses
1.09
2
2
The second cluster which includes enterprises 2, 6, 13, 15, 16, 17, 26, 29, 33, 34, 35 (see Table 2) is characterized by the maximum appreciation of the completeness of the services provided and the professionalism of customs officials. Consumers are more satisfied with the level of information about the receipt of services on the FCS website, the level of corruption, the time spent on the implementation of a full package of services, the level of interaction between customs structures, the level of convenience of the site, feedback from FCS officials and the organization of places waiting for customers in warehouses. Cluster No. 2 includes enterprises that have extensive experience in foreign trade activities and communication with representatives of customs authorities, so all indicators are averaged. The third cluster which includes enterprises 1, 4, 8, 9, 11, 12, 14, 21, 22, 23, 24, 25, 26, 31, 32, 39, 40 (see Table 3) is characterized by a high appreciation of professionalism of customs officers. Respondents are more satisfied with the level of culture of specialists of call center, the completeness of services provided, the level of information about receiving services on the FCS website, the time spent on the implementation of a full package of services, the level of interaction between customs structures, the level of corruption, the level of convenience of the site and feedback from officials of the Federal Customs Service. Enterprises included in cluster No. 3 do not participate in foreign economic activity frequently. The data required for the calculation are summarized in Table 4. Among the participants, enterprises 1,4 and 18 showed the highest efficiency. In this example, 3 subgroups of participants can be distinguished that have comparable effectiveness: 1. the most effective participants, score from 75 to 100% inclusive. 2. participants with average efficiency, score from 25 to 74% inclusive. 3. participants with low performance, score from 0 to 24% inclusive.
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Table 3 Cluster No. 3 survey results Criteria
Mean
Mode
Median
The level of culture of specialists of call center
2.35
2
2
Completeness of the services provided
2.35
2
2
The level of information support about the receipt of services on the FCS website
2.35
2
2
Time spent on the implementation of the full package of services
1.94
2
2
Level of interactions between customs structures
1.53
2
2
Level of corruption
2.35
2
2
The level of convenience of the site
1.65
1
2
Feedback from FCS officials
2.18
2
2
Professionalism of customs officials
2.82
3
3
Organization of waiting areas for customers on the territory of warehouses
0
0
0
If we compare the results of the analysis of effectiveness according to the CCR model of the DEA method and the correlation and cluster analysis of the survey results, then it is worth paying attention to the fact that two out of three leaders entered cluster No. 2 in the cluster analysis.
4 Discussion From the point of view of the respondents the most problematic indicators of assessing the quality of the work of customs authorities are the level of culture of specialists of call center, the convenience of the site, and the organization of waiting areas for clients in warehouses. To solve these problems, the following measures are proposed: 1. Organization of an intensive 4-day training to improve the skills of 15 specialists in interaction with citizens by invited specialists for a duration of 16 h (4 h a day); 2. Involvement of an IT specialist to evaluate and improve the site interface to improve the convenience of the site; 3. Organization of a comfortable waiting area with the possibility of rest and warming up food on the territory of warehouses to increase the level of confidence in the customs authorities. To carry out the above activities, you need to make the following costs: Organization of training to improve the skills of specialists—52,200 roubles a year, including payment for work of the training manager (32,000), job printout (1000) and catering for 15 participants and 1 training manager (19,200 or 300 rubles per person a day);
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Table 4 Data for determining and analyzing the comparative efficiency of the economic activity of the respondents №
X1{I}
1
0.0625
345
0.009137
100
101.23
2
0.017985612
24.6
0.000249
11
11
3
0.026315789
62
0.000027
0.79
0.79
4
0.029761905
4.33333333
0.003568
100
916.94
5
0.016207455
34.8
0.000004
0.17
0.17
6
0.014245014
13.5
0.000095
5.38
5.38
7
0.035897436
4.85714286
0.000270
6.74
6.74
8
0.049382716
12
0.000430
7.23
7.23
9
0.05
48
0.001191
19.22
19.22
10
0.018181818
98
0.000106
4.02
4.02
11
0.03125
234
0.000663
13.73
13.73
12
0.045454545
165
0.000094
1.5
1.5
13
0.142857143
24
0.001270
7.41
7.41
14
0.023771791
43.8666667
0.000135
4.43
4.43
15
0.022988506
216.5
0.000395
10.54
10.54
16
0.02293578
31.6
0.000251
8.7
8.7
17
0.033936652
4.06666667
0.000189
5.64
5.64
18
0.029411765
365
0.005172
100
120.29
19
0.058823529
123
0.000037
0.49
0.49
20
0.142857143
12
0.000203
2.06
2.06
21
0.015337423
9.66666667
0.000089
4.77
4.77
22
0.090909091
48
0.000884
7.99
7.99
23
0.019230769
12
0.000464
19.75
19.75
24
0.055555556
87.5
0.001702
24.15
24.15
25
0.083333333
54
0.000349
3.42
3.42
26
0.166666667
9
0.000256
3.46
3.46
27
0.008797654
3.66666667
0.000033
3.13
3.13
28
0.047619048
93.5
0.000095
1.56
1.56
29
0.027777778
32
0.000075
2.16
2.16
30
0.066666667
76
0.000017
0.2
0.2
31
0.018181818
87
0.000048
1.86
1.86
32
0.025641026
19
0.001360
43.18
43.18
33
0.0125
8.5
0.000017
1.1
1.1
34
0.142857143
432
0.012201
63.75
63.75
Y1{O}
X2{I}
Evaluation of CCR model, %
Evaluation of super-efficiency model, %
(continued)
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Table 4 (continued) №
X1{I}
35
0.125
34
0.002010
13.35
13.35
36
0.012468828
17.6
0.000003
0.17
0.17
37
0.01369863
12
0.001005
59.4
59.4
38
0.018518519
48
0.000556
22.78
22.78
39
1
3
0.001310
53.03
53.03
40
1
48
0.003400
8.6
8.6
Y1{O}
X2{I}
Evaluation of CCR model, %
Evaluation of super-efficiency model, %
Involving an IT specialist to evaluate and improve the site interface—35,000 roubles, including one-time payment for work of an IT specialist; Organization of a comfortable waiting area—24,500 roubles, including one-time purchase of sofa (14,000), microwave (4,000) and water cooler (2,500). Thus, the cost of events in the first year will be 107,700 rubles, of which 59,500 rubles will be one-time costs and 52,200 rubles—annual periodic costs.
5 Conclusion The participant satisfaction model, as a method for assessing the effectiveness of activities and the quality of services provided by the customs authorities, was chosen as the basis for research. A survey of 40 participants in foreign economic activity was conducted. Further, the obtained results were subjected to correlation and cluster analysis. The efficiency of the respondent enterprises was calculated using the DEA method. After the study was completed, proposals were put forward to improve the most vulnerable points and their socio-economic efficiency was calculated. The developed measures will allow not only to optimize the work of customs authorities, but also to increase the satisfaction of participants in foreign economic activity, which will definitely lead to an improvement of mutual understanding and interaction between customs authorities and enterprises.
References 1. Fuchs E, Novikov V, Novikov S (2022) Improvements in post-release customs control of goods moved by different modes of transport. Transp Res Proc 61:200–205. https://doi.org/10.1016/ j.trpro.2022.01.033
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Energy-Efficient Technologies and Their Role in the Development of the Innovation Economy Daria Kichikova , Nikolai Zakirov , and Yuri Katanov
Abstract On the example of the circumpolar zone of the Arctic region of YNAO the article considers the innovation policy in oil and gas production, which is an integral part of the socio-economic policy of the Russian Federation. It shows the main general priorities of development of the innovation economy and oil and gas production companies, including the introduction of new energy-efficient technological solutions, increased investment in science and production. Keywords Energy efficiency in transportation · Technology · Oil and gas sector · Economic and mathematical analysis · Hard-to-recover oil reserves
1 Introduction The Yamal-Nenets Autonomous Okrug (YNAO) is an integral part of the Russian Arctic. It is an area where natural resources of strategic importance to the national economy are concentrated. Today, the region has already created a multifaceted industrial and social infrastructure. With the adoption of the Russian Arctic Zone Development Strategy, many of Yamal’s tasks have acquired the status of national priorities. In the circumpolar zone of the YNAO, a significant number of different innovative projects have been implemented and still exist. Central Arctic oil and gas projects are an engine of growth in the development of innovative technologies and their implementation will load the domestic industry—metallurgy, chemical production, production of machinery and equipment, transport and construction—and this will create additional jobs throughout Russia [1–12].
D. Kichikova (B) Tyumen State University, 6, Volodarskogo Street, Tyumen 625003, Russia e-mail: [email protected] N. Zakirov · Y. Katanov Tyumen Industrial University, 70, Melnikaite Street, Tyumen 625007, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_137
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There are currently 16 oil and gas provinces in Russia, producing in 2020 more than 512 million tonnes of oil and 692.3 bcm of gas, of which the West Siberian Oil and Gas Province (ZSNGP) accounts for over 51.1% of oil and 81.1% of gas. At the same time, 37 million tonnes of oil (7.2%) and 526.9 bcm of gas (76.1%) were extracted from the subsoil of the Arctic region of the Yamalo-Nenets Autonomous Okrug in 2020. It should be noted that proven gas reserves in the YNAO reach 45 trillion m3 and Yamal will essentially be an energy guarantor of the state’s security for many years to come [13, 14]. NOVATEK’s most important federal project is the construction of a liquefied natural gas (LNG) plant by NOVATEK with a capacity of 7.5 million tonnes each. The implementation of the project for the construction and commissioning of the LNG plant—2 will allow Russia to take a leading position in the development of Arctic field development technologies, to enter new markets in the Asia–Pacific region and to give impetus to the development of the Arctic corridor—the Northern Sea Route and to increase investment. For example, the Bovanenkovo field, with its reserves of almost 5 trillion m3 will give the country more than 100 bcm of gas a year, will become a reference point for the development of the Kara Sea water area, i.e., Yamal is the future of the country’s gas industry, the northern outpost of the Russian state [15, 16].
2 Theoretical Analysis Currently, the modernization and technical development of the regional economy and the country plays a major role in the creation and implementation of innovative technologies, and the expenditure of Yamal enterprises on innovation in recent years has amounted to several billion rubles. Figure 1 shows the current methods and criteria for cost-effectiveness of project innovations. Authors of work [16] offered a rational variant of development of oil and oil–gascondensate fields, improving technical and economic indices of development, thus it is necessary to determine it by maximum discounted cash flow (NPVmax), and income of subsoil user should be defined by the ratio: NPVned =
Tϑ ∂nt + ∂ct + ∂ pt ∗3ϑt ∗(1 + E np )1−t , 100 t=1
where ϑ = 1, 2, 3, . . . N ; ∂nt —bank interest (~10%); ∂ct —insurance coefficient (~10%); ∂ pt —development coefficient (~10%); 3ϑt —the cost of producing oil.
(1)
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Static Year, econ. ef. Break-even point
Dynamic Net income (NI) Net discounted income (NDI)
Relative
Static Return on investment
Dynamic Index of return (IR) Intrinsic Rate of Return (IRR)
Temporary Dynamic Payback period of the investment
Static Simple rate of return on investment
Fig. 1 Current methods and criteria for cost-effectiveness (by N. Tolstykh, 2011)
The income state Dr is defined by the ratio: ϑ ϑ − N P Vned Drϑ = N P Vmax
(2)
This will, firstly, increase the completeness and efficiency of oil extraction from the subsoil and bring unprofitable hydrocarbon deposits under the current system of taxation into commercial development, and secondly, stimulate investment in production, since the subsoil user’s income depends directly on its volume and is not linked to the geological and physical conditions of the fields. For example, Rosneft, Russia’s largest company operating in the YNAO, is actively pursuing strategic development and accelerating the company’s growth until 2033. This is linked to the start of commercial offshore production. Arctic projects will allow Rosneft to become the world’s largest operator of this type of reserves, and the company’s proven oil reserves are the largest in the world. The company plans to invest $400 billion in the development of Russia’s Arctic shelf between 2014 and 2034. The circumpolar zone of the YNAO is attractive to organisations and individuals engaged in the development and implementation of innovative ideas and projects, facilitating the effective functioning of firms and enterprises focused on innovative development. This zone also attracts the attention of domestic and foreign investors. Innovation, embodied in new scientific knowledge, technologies and services, is one of the main factors of competitiveness in all developed countries. Consequently, the innovation activity of the Yamal region should be considered as the ability of
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the region to create competitive advantages through the development of innovation, providing the improvement of conditions for sustainable economic growth and quality of life of the region’s population [15–20]. The innovative development strategy of any region should define a system of goals and objectives for improving the investment climate and increasing investment activity in priority areas. Innovation policy should be pursued in all spheres of oil and gas companies’ activities, and at all oil prices. Innovative activities in the fuel and energy sector in Western Siberia, including the Yamalo-Nenets Autonomous District, are currently carried out by research institutes, universities and their technology centres, and small innovative enterprises. The former and the latter (research institutes, universities) generate ideas, conduct research and create prototypes, while small innovative enterprises must use these prototypes to create working products, introduce them into production and bring them to the market.
3 Discussion Results The development of innovation policy in general, and the innovation economy in particular, in the circumpolar zone of the Arctic region of YNAO will require: • stimulating innovation in companies through financing with the federal budget and the Foundation for Assistance to Small Innovative Enterprises in Science and Technology, • stimulating the process of testing a prototype of innovative products by getting manufacturers interested in grants for testing samples of new technology. The innovation policy of companies in the circumpolar zone of the Arctic region of YNAO should include the creation of production sites, and not just any sites, but ready-made shops and buildings where new production facilities can be located, or old ones can be modernised. Innovation is the gene pool of the modern economy, a model of development that uses natural capital sustainably as a source of resources and environmental services on which our well-being is based. It is fundamentally important that the YNAO will provide about 80% of Russia’s gas for years to come and remains a strategically important region. To practically implement this postulate Gazpromdobycha Yamburg is developing fundamentally new technologies and equipment to improve the accuracy and quality of control for the development of gas and gas condensate fields, which simultaneously allow for a radical reduction of gas emissions to the atmosphere inevitable during field development. For example, the technology developed for conducting group surveys of cluster gas wells makes it possible to almost completely eliminate methane emissions into the atmosphere. In the short term, the future of the gas industry will be linked to the development of offshore deposits. For companies operating in the YNAO, these are the wells of the
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Ob and Taz Bays. Applying traditional technologies and field development control methods here will not be enough. To ensure environmental and industrial safety in the development of onshore and offshore hydrocarbon fields, the use of onshore gravimetric methods will make it possible. Gravimetric observations and the results obtained at the Zapolyarnoye field have not only proved the effectiveness of the technology but have also created standards for gravimetric surveys and their interpretation. This technology can and should be used at other fields, providing substantial cost savings and an environmentally friendly process. In other words, the innovative technologies that have been created and implemented by all gas producers make it possible to significantly minimise the environmental impact of their operations. Mobile compressor units (MCU) based on the distributed compression method, which effectively solve the problems of low-pressure gas production, preparation and use at the late stage of field development, have been introduced at the fields of Gazpromdobycha Noyabrsk. This technology is used at long-operating fields, where low-yielding wells are being squeezed, reservoir fluid accumulates in wells and gas gathering networks, and reservoir pressure and gas production are reduced. If the cost-effectiveness criterion is met, the introduction of these innovative technical solutions will improve production efficiency and extend the life of the fields. A synergistic project, accumulating experience, knowledge and engineering thought, for the implementation of MCU, is being successfully implemented in cooperation with other companies. In April 2019, YNAO Governor D. Artyukhov and Rector of the Moscow Institute of Physics and Technology (MIPT) N. Kondratyev signed a cooperation agreement, and MIPT in Yamal began implementing a pilot project that will contribute to the innovative development of the Arctic and the application of new developments in Russian science. In the YNAO, based at the Arctic Research Station of the Institute of Plant and Animal Ecology of the Ural Branch of the Russian Academy of Sciences, the Arctic Ecosystem Dynamics laboratory has been established as part of the national Science Project, with the main aim of studying three factors influencing ecosystems-climate change, reindeer breeding and industrial development of Arctic territories. The new laboratory is synchronised with cutting-edge research projects in other countries of the Arctic region, involving scientific collaborators—colleagues from Norway, France, Canada, Germany, Finland, Holland, Poland, New Zealand, the USA and other countries. Using the opportunities of Yamal, Russia can become the absolute and practically has no alternative supply centre for energy carriers and products of their processing for the economies of the states of the entire continent. The autonomous district yields over 80 per cent of all gas produced in Russia and provides environmental-friendly fuel for Western Europe by 40 per cent. Over 46 years of its development, Yamal-Nenets autonomous district has yielded about 15 per cent of the proven reserves.
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In addition to hydrocarbons, the list of priority areas for innovation in the YNAO also includes technologies for prospecting, exploration and development of deposits of ore and non-metallic minerals, their extraction and transportation. The Yamal-Nenets Autonomous Okrug has a council for state scientific, technological and innovation policy. There are 14 registered enterprises in Yamal involved in research and development, with the regional budget funding projects to develop a model for the innovative development of small and medium-sized businesses. The authors of this paper, together with other experts from the Institute of Geology and Oil and Gas Production at TIU, developed and economically justified the application of about 16 innovative technologies protected by Russian patents for invention and utility model (Nos. 2588582, 2604100, 2613067, 2620684, 2631512, 2661171, 189893 etc.) in 2016–2019, which include: • developing new technological compositions for repair and insulation work in oil and gas wells, • ways of carrying out technological operations, such as: isolating bottom water; reducing sand seepage; isolating gas coming from the gas cap; preventing the formation of bottom water in horizontal wells; cutting off the cone of bottom water; developing deposits with high-viscosity oil, etc., • technical packers, circulation valves and plugging equipment, as well as injection well equipment for simultaneous extraction of thermal water and its injection into formations with hard-to-recover oil, technologies for well development and research, etc.
4 Conclusions The abundant raw material resources of the circumpolar zone of YNAO provide ample opportunities for investment in all sectors of the economy, allowing for the creation of a basis for economic growth, so it is necessary to develop the oil and gas sector with the involvement of modern energy-efficient and innovative technologies. In other words, modernisation and the creation of an innovative economy are inextricably linked to the oil and gas sector. The processes of sustainable innovative development have already created favourable conditions for the Yamal region to become a strategic outpost of the Russian Federation in the Arctic. The solution to the problem of increasing the efficiency of innovation use should lie in the implementation of general management principles and the application of a systematic approach to enterprise and regional management, using the principle of science-based management. Further improvements are needed in innovation and investment legislation, in terms of introducing new forms of state support and incentives for investors, proper use of investment resources by businesses, etc. There is a need to use resources more efficiently and increase investment in the economies of regions in need of structural reorganisation, increase productivity, improve the investment climate and improve governance.
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Improving the innovation and investment climate in the competitiveness of the regional and the Russian economy as a whole in the current environment is a major challenge for both government and business. In other words, a new economy with a competitive infrastructure, powered by modern technology, is needed. The transition to an innovative stage of economic development and the creation of an appropriate infrastructure should be pursued more intensively, and effective mechanisms to improve the competitiveness of both regions and the country should be proposed. It is known from foreign experience that effective state administration in the energy sector creates in a short period of time certain innovative industries that are powerful catalysts for innovative economic development and provide additional opportunities for job creation and economic diversification both for energy companies and the country as a whole. Thus, according to the WEF methodology, the highest stage of a country’s development is that of an innovation economy, whose competitive advantages are considered to be innovation and technology. Therefore, not only individual regions, but the country as a whole, need to transition as quickly as possible from an economy focused not only on increasing labour productivity to an innovative economy, where the engine of economic development is the generation of innovation, and the key role in this process in the YNAO, and in the Russian Federation as a whole, is assigned to the oil and gas complex. Having stated the above, we must conclude that the development and implementation of energy-efficient technologies in the oil and gas complex of the Russian Federation should be the biggest innovative breakthrough in the development of the Russian economy, which will give impetus to the rise in other sectors of the economy and will significantly strengthen Russia’s position both in exports of high-tech oil and gas products and in the competitiveness of our country.
References 1. Vilensky PL, Livshits VN, Smolyak SA (2002) Evaluating the effectiveness of investment projects: theory and practice. Delo, Moscow, p 888 2. Smolyak SA (2002) Assessing the effectiveness of investment projects under conditions of risk and uncertainty (theory of expected effect). Nauka, Moscow, p p182 3. Makov VM (2008) Analysis of innovation processes in the Russian economy and oil and gas complex. Industry of Russia. Stat.sb. Rosstat, p 381 4. Kichikova DV, Kleshchenko II (2011) Vertically integrated oil companies and their role in Russia’s oil and gas complex. “Economics and the fuel and energy complex.” MIPTEC 4:52–53 5. Belkina EY, Khasanov IS, Polovin EA (2011) Methodological approaches of Russian oil companies to assess efficiency of innovation projects. Nedra: “Terriya Neftegaz” Moscow 4:70–73 6. Kichikova DV (2011) Current trends in the development of global and Russian oil markets. Vector Book, Tyumen, p 118 7. Kabanov SS (2012) Scientific and technological development as a determinant of international competitiveness of the national economy. Young Scient 3:166–170
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8. Innovation Policy Review of the Russian Federation. http://gtmarket.ru/news/state/2011/05/ 30/2956 9. Global Innovation Index 2012. http://gtmarket.ru/news/state/2011/07/06/4531 10. Kleshchenko II, Kichikova DV (2012) Topical trends of general and innovative activities of Russian oil and gas companies. NTJ “Science and Fuel and Energy Complex”, vol 8. TyumSOGU, Tyumen 11. Kleshchenko II, Kichikova DV (2012) Actual trends in the development of innovative technologies in the fuel and energy sector and economy of Western Siberia. NTJ “Science and Fuel and Energy Complex”, vol 9. TyumSOGU, Tyumen 12. Novak A (2012) Materials of the meeting on the innovative development of Russia’s economy. NTJ Oil Gas Siberia 3(8):4–6 13. Kichikova DV (2013) Innovative activities in the Russian oil and gas complex as a factor to increase the international competitiveness of the country. TyumSOGU, Tyumen, p 90 14. World Economic Forum: Global Competitiveness Report 2012–2013. http://gtmarket.ru/news/ 2012/09/05/4949 15. Kichikova DV (2013) Innovations in the Russian fuel and energy complex and international competitiveness. Vector Book, Tyumen, p 131 16. Baturin YE, Plyonkina VV, Selezneva LA (2009) On selection of rational system of oil field development and taxation in oil production. In: Problems of fuel and energy complex of Western Siberia. Tyumen Branch of Rans, Tyumen, p 420 17. Pogodaeva TV, Kichikova DV (2013) Energy-efficient technologies as a priority of innovative development of oil and gas complex. Kazan 3:89–94 18. Global Competitiveness Ranking. http://www.weforum.org/ 19. Kichikova DV, Zakirov NN, Mansurova MM (2020) Effective technological solutions in the development of innovation economy. TIU, Tyumen 20. Shlein GG, Kleshchenko II, Zakirov NN, Popova JS, Kichikova DV (2020) Development and investigation of wells penetrating complex oil reservoirs by jet engines. Constr Oil Gas Wells Land Sea 2:32–38
Research on Topology Generation and Fault Prediction Technology of Low Voltage Distribution Network Based on State Perception Ying Yao , Dalong Ji, and Wenjin Fu
Abstract Fault diagnosis and prediction technology of distribution network is the basis of active repair of distribution network. Currently, in low-voltage systems, due to frequent changes in power load and topology, it is difficult to identify the real topology of distribution network. Moreover, there are little research involves failure prediction of low-voltage distribution network equipment, and the failure prediction technology for low-voltage distribution network is still in its infancy. Based on this, this paper first proposes a low-voltage distribution network topology selfadaptive generation method to realize the verification with the low-voltage distribution network topology. Then, a method for predicting the failure of distribution network equipment is proposed based on historical data and monitoring data. Based on the generated topology and the established low-voltage distribution network equipment failure rate model, an active repair strategy for low-voltage distribution network can be formulated. The research results are of great significance to the active repair of low voltage distribution network. Keywords Low voltage distribution network · State perception · Topology identification · Fault diagnosis · Fault prediction
1 Introduction With the continuous advancement of society and the continuous advancement of the level of industrialization, users have put forward higher requirements for the quality and level of power supply. Power outages may have a greater impact on social order and the normal operation of the economy. In order to build the "last mile" of the distribution network, the topology of the low-voltage distribution network Y. Yao (B) · D. Ji Electric Power Research Institute, State Grid Tianjin Electric Power Company, Tianjin 300171, China e-mail: [email protected] W. Fu NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_140
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is becoming increasingly complex, and the troubleshooting and troubleshooting of the grid is more complicated, which will directly affect the level of power supply service. Changeable operation modes and load levels may cause differences between the distribution network topology in the background system and the actual topology. At the same time, the role of the distribution automation system in fault research and judgment and fault handling is becoming more and more obvious. However, the current distribution automation transformation is mainly concentrated on the 10 kV distribution network level, and the low-voltage fault monitoring and perception capabilities are relatively weak. Therefore, it is necessary to carry out research on low-voltage distribution network topology generation and fault prediction technology to lay an important foundation for active repair of low-voltage distribution network. For the emergency repair of the power distribution network, the coordination and optimization of the emergency repair and restoration of the fault through alternate emergency repair and grid reconstruction is studied in [1]. A distribution network risk assessment model from an economic point of view is established in [2]. A binary particle swarm algorithm to solve the method of emergency repair and recovery strategy of distribution network and updates the network topology in [3]. Literature [4] considers the time-varying characteristics of DG and load, and proposes a multifault troubleshooting strategy. A multi-objective-based fault recovery model for the distribution network considering the impact of new energy sources are established in [5]. Literature [6] proposed a network reconstruction method that considers the restoration sequence and restoration path of power generation nodes. Literature [7] proposed an optimization strategy model for emergency repair based on game theory for the multi-point sudden failure of the distribution network. Literature [8] studied the emergency resource dispatching plan in the case of power system failure. Literature [9] studied the low-voltage distribution network fault research and judgment method based on the typical characteristics of low-voltage electrical quantities of distribution transformers. Literature [10] studied the fault location method of lowvoltage distribution network considering new energy access under multi-point fault conditions. Literature [11] studied a new method of fault line selection and location in distribution network based on median resistance switching. Literature [12] studied the single-phase ground fault location of distribution network based on zero sequence current. Literature [13] considered the impact of neutral grounding and proposed a single-phase fault protection method for distribution network. Literature [14] studied the power grid fault research and judgment model based on gray experience fusion. Literature [15] studied the fault diagnosis and fault handling methods of non-sound information in the distribution network. Literature [16–20] mainly studied the fault prediction of 10 kV distribution network transformers and feeders. In summary, the existing research mainly focuses on the emergency repair strategy of the high and medium voltage distribution network, as well as the research, judgment and disposal of the distribution network fault. In low-voltage systems, due to frequent changes in load and grid topology, it is difficult to identify the topology, and there is currently a lack of effective identification methods. In addition, in terms of equipment health prediction technology, existing research also rarely involves low-voltage distribution network equipment.
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Based on this, this paper studies the relationship between the user’s electricity meter, the cable branch box and the transformer branch box, and realizes the verification of the low-voltage distribution network topology. On this basis, based on the generated topology, integrated historical data and current data, a comprehensive prediction model for low-voltage distribution network equipment failures was researched and established to provide a reference for the formulation of active repair plans for low-voltage distribution networks.
2 Topology Generation and Verification Scheme Due to the complex structure of the low-voltage distribution network frame and frequent load changes, the topology change or load change process may cause the distribution network topology to be inconsistent with the actual target. It is necessary to accurately identify the actual low-voltage distribution network frame on site. Provide support for the low-voltage distribution network emergency repair program. Based on this, this paper proposes a topology recognition and verification technology based on low-voltage sensing units. The main implementation schemes are as follows: (1) Obtain user-side LTU equipment data and branch box data by obtaining the terminal meter data of the user-side LTU equipment, the FLTU data at the outlet switch of the low-voltage overhead line branch or the low-voltage cable branch box, and the TLTU data at the low-voltage outlet of the station box transformer Outgoing FLTU data. Then, Classify and sort the obtained FLTU data, TLTU data, and LTU data to obtain the data set S. Among them, the power of the LTU equipment is,P1 , P2 , …, PN , and the outgoing FLTU power of the branch box is P1 , P2 , …, PM . The power data of each device is read every 0.2 s, 20 sampling points are used as a set of data, and 20 data are arranged, and the average of the middle 10 numbers is taken as the calculated value of the time window. The power of each device has 21,600 data a day. S1 = [S1,1 , S1,2 , …, S1,21600 ] means One day’s data for the first LTU device. S1 =[S1,1 , S1,2 , …, S1,21600 ] is one day’s data for FLTU at the outlet of the first branch box. (2) According to the sudden power changes of the user-side LTU device and the outgoing FLTU device, the clustering method is used to find the association relationship between the user-side LTU device and the outgoing FLTU device. The specific method is as follows: according to the generated data set Si, j , Si, j , to calculate the power mutation value P of the user-side LTU device and the power mutation value P of the FLTU at the outgoing line. On this basis, search for user-side LTU devices (P) larger than 100 W, and find the FLTU device at that moment according to the time corresponding to the found user-
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side LTU device is P . At the same time, calculate the error array and error ratio array of the sudden power of the device at the LTU μx y and the sudden power of the FLTU νx y at each moment:
νx y = Px y /Px y μx y = Px y − Px y
(1)
where x = 1, 2, …, n, n is the total number within a day after filtering the data. y = 1, 2, …, m, m is the total number of FLTU devices. v = [v11, v12, …, v1m, …, vnm] T, μ=[μ 11, μ 12, …, μ 1 m, …, μ nm] T. Thus, the set of error to error ratio can be obtained: J = [v,μ] (3) Based on this, look for the class with the largest amount of data in the set J, by randomly determining a point in the set J as the center point C, calculate all the points that are less than or equal to R from C as the M group. With C as the center, calculate the vector from point C to the remaining points in the M group, and calculate the sum of all vectors as SC. Suppose C = C + SC, and let C advance in the direction of SC, then the moving distance is the absolute value of SC. Through repeated iterative calculations, until the error meets the threshold value k, record the current value of C. ε≤k
(2)
where k is 10−3 . If the error meets the threshold value, the distance between the C value of the currently obtained group M and the C value (e.g., C2) of other existing groups (e.g., M2) is less than the threshold. Then merge C and C2. Otherwise, the newly generated M is classified as a new group, and one class is added. Repeat the calculation until all points in the set J are traversed and classified. Based on this, the corresponding relationship between the FLTU equipment and the user-side LTU equipment is used to make a corresponding low-voltage distribution network topology diagram. The connection relationship between FLTU and LTU is recorded through the adjacency association matrix. When there is a connection relationship between nodes, the corresponding element of the matrix is “1”, otherwise it is “0”. Among them, the topology generation relationship of the LTU device downstream of the FLTU device is as follows: if the FLTU device number is 1, the other FLTU device numbers are 2,…,i. On this basis, calculate the number of LTU devices connected to FLTU devices, and leave enough space. In the same way, the topological structure of the station area between the FLTU at the outgoing line and the station area transformer TLTU can also be obtained by the above method. (4) Use the corresponding relationship between the low-voltage transformer TLTU and the cable FTU, as well as the outgoing line FLTU and the user-side LTU, and do topology inspection through power consumption.
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Obtain low-voltage transformer TLTU, cable FLTU and user LTU power
Preprocess the acquired power data
Extract LTU power mutation amount and cable FLTU power mutation amount, transformer TLTU power mutation amount
Establish the relationship between LTU and FLTU by means of clustering technology
According to the known topology, solve the error between the cable FLTU and the corresponding LTU
≤ 2%
Generate a new topological structure, and establish the relationship between transformer TLTU and cable FLTU by means of clustering technology According to the known topological structure, solve the error between the TLTU and the cable FLTU
≤ 2%
Generate a new topology structure and compare and check with the actual demand topology
Fig. 1 Topology verification scheme of low voltage distribution network based on perception unit
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According to the corresponding relationship between the generated FLTU and the user-side LTU, the sum of the power of all LTU devices downstream of the FLTU is compared with the FLTU power. If the error is met, the topological relationship between the cable FLTU and the user LTU can be considered to be correct. At the same time, calculate the sum of the power of the transformer TLTU in the station area and the power of all FLTUs downstream to verify the topological relationship between the transformer in the station area and the cable feeder. Finally, based on the generated low-voltage distribution network network, compare and check the actual required low-voltage distribution network target topology. If there is an inconsistency, the transfer system, switchgear or circuit needs to be overhauled. The low-voltage distribution network topology and verification scheme based on the state-aware unit is shown in Fig. 1.
3 Fault Prediction Technology of Distribution Network Equipment 3.1 Mathematical Method of Equipment State Description Based on Historical Data For equipment, its full life cycle can generally be described by a bathtub curve. In this article, the Weibull distribution is used to describe the change trend of the life of the distribution network equipment, and its expression is as follows: λ(t) =
n t n−1 m m
(3)
Among them, m and n is the shape parameter and scale parameter of the Weibull distribution of the equipment, and t is the failure time. If n = 1, The failure rate is constant, λ(t) indicates that the low-voltage distribution network equipment is in normal operation. If n > 1, the failure rate is on the rise, indicating that the lowvoltage distribution network equipment is in a lossy operation period. In practical applications, the parameters m and n can be solved by the improved Gauss–Newton method [19], and the final parameter estimates m and n can be obtained through multiple iterations.
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3.2 Device Fault Catastrophe Model Based on State-Aware Data The operating status of the equipment in the distribution network is not only related to historical data such as operating years and maintenance, but also related to the recent impact of the equipment in different environments. This paper uses distribution automation terminals, TTU terminals, and user smart meters to perceive the operating status of the equipment in real time, and uses monitoring information as the factors affecting the status of the equipment in the distribution network. Based on this, this paper takes F as the operating state score of the distribution network equipment, and FM as the judgment value of the normal state and abnormal state of the distribution network equipment. The FM value can be obtained based on on-site statistical data. (1) Running status value F > FM If F > FM , it shows that the equipment of the distribution network is in a normal state. The data at this stage is mainly affected by the historical data of the equipment. The equivalent running time td of the equipment of the distribution network can be solved by formula (4). Td = (100 − F)T /(100 − FM + Tdk )
(4)
them, the distribution network equipment is 100 points after overhaul, F = Among F (n) /n means the average point value of the equipment operation. Tdk indicates the equivalent operating life of the equipment in the distribution network after the kth overhaul. After the power distribution network equipment was put into operation for the first time, Tdk =0. Status value F < FM . If F < FM , it means that the device has entered an abnormal or faulty operation state from the normal operation state. The abnormal state of the equipment does not mean that a failure occurs immediately, and the equipment can still operate for a period of time. Therefore, this paper uses Gamma distribution to describe the changing trend of equipment during abnormal operating conditions, and the equipment probability density function is as follows: f a(t - s),β (f) =
f a(t−s)−1 −x/β 1 e , f≥0 (a(t − s)) β a(t−s)
(5)
where a and β are the shape parameter and scale parameter of the probability density ∞ function of the device,(a(t −s)) = 0 e−u ·u a(t−s)−1 du.a and β can be obtained by this method. After the distribution network equipment status score is lower than FM, n groups of distribution network equipment status data can be obtained at different times between FM and FN, (FM,t1), (F2, t2), …, (Fn-1, tn-1), (FN, tn). Taking the n sets of data as a small sample of Gamma distribution, the shape and scale parameters of the Gamma distribution are solved by the expectation maximization algorithm
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[20]. The distribution parameters can be corrected in real time according to the latest distribution network equipment scores.
3.3 Fault Prediction Model for Equipment in Distribution Network Combining the calculation models of 3.1 and 3.2, the fault prediction model of distribution network equipment can be obtained by formula (6): r(t, Ft ) = r1 (t) · 1{Ft ≤FM } + r2 (t) · 1{Ft >FM }
(6)
where Ft indicates the operating state score of low-voltage distribution network equipment at time t. r1 (t) indicates the failure rate of low-voltage distribution network equipment in the state Ft > FM . r2 (t) indicates the failure rate of low-voltage distribution network equipment in the state Ft ≤ FM . Equation (6) indicates that the equipment has entered an abnormal operating state at time t.
4 Verification and Analysis 4.1 Topology Generation Technology of Low-Voltage Distribution Network Based on State-Aware Unit In order to verify the effectiveness of the proposed low-voltage distribution network topology generation technology, the distribution network topology shown in Fig. 2 is taken as an example to illustrate the low-voltage distribution network topology generation method. According to the topology automatic generation technology mentioned in the article, the adjacency matrix based on the topology can be obtained as shown in Table 1. According to the adjacency matrix in Table 1, the outgoing FLTU power and its corresponding user LTU power are checked, and the transformer TLTU power and cable FLTU power are checked at the same time to ensure the correctness of the established topology matrix. On this basis, proofread based on the checked low-voltage distribution network topology and the actual demand topology, if it is consistent with the actual demand, then based on the topology, the fault prediction of the distribution network equipment in the area is carried out; if After the check, the low-voltage distribution network topology is inconsistent with the actual one, then analyze the different topologies in the area, analyze the possibility of switch, circuit and secondary equipment failures in the area, and determine the troubleshooting point.
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B1
L1
C1
C2
L2
C3
C4
L3
C5
C6
C7
C8
C9
Fig. 2 Topology diagram of typical low voltage distribution network
Table 1 Adjacency matrix corresponding to topological connection Node
1
2
3
4
5
6
7
8
9
10
11
12
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4.2 Implementation Method of Failure Prediction for Low-Voltage Distribution Network Equipment According to the low-voltage distribution network topology obtained above, combined with the failure prediction rate of various equipment in the low-voltage distribution network, the abnormal operation of the low-voltage distribution network equipment is actively repaired. Therefore, the prediction model that effectively characterizes the failure trend of low-voltage distribution network equipment is to develop low-voltage distribution network equipment. The basis for the active repair of the network. Take the transformer in a certain area of the low-voltage distribution network as an example to illustrate the failure prediction method of the low-voltage distribution network equipment. According to the failure rate of transformers in the station
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area of a low-voltage distribution network in different operating years, the results are shown in Table 2. By analyzing the data in Table 2, it can be seen that the transformer failure rate of the low-voltage distribution network station area should conform to the Weibull distribution. According to the fitting method of the equipment’s failure rate curve based on historical data proposed in this paper, segment fitting is performed. When the cut-off point is located at 15 years, S(l) is the smallest. According to the Weibull Table 2 Average annual failure rate of low voltage distribution transformer Operating life/year
Failure rate (Times/set·year)
Operating life/year
Failure rate (Times/set·year)
0.5
0.0011
12.5
0.0384
0.6
0.0007
13
0.0395
0.8
0.0012
13.5
0.0202
0.9
0.0031
14
0.0033
1.2
0.0094
15
0.0218
1.6
0.0193
16
0.0158
2
0.0091
16.3
0.0316
2.5
0.0143
16.5
0.0396
3
0.0087
16.8
0.0285
3.4
0.0188
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0.028
3.9
0.0261
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0.0464
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0.015
18.5
0.03231
4.6
0.0143
18.9
0.0238
4.6
0.0126
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0.0226
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0.0574
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0.0138
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0.0558
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0.0761
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26
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0.1143
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0.25
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0.15
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15 Operating life/year
20
25
30
Fig. 3 Failure rate fitting curve
distribution parameter, the 15th year can be set as the cut-off point between the accidental failure period and the wear-out period, that is T2 = 15. Then, the failure rate is K = 0.0169 and the corresponding Weibull parameter are n = 4.551, m = 28.1719. After the Weibull parameters and the demarcation points are determined, the fitting curve of the failure rate of the low-voltage distribution transformer can be obtained, as shown in Fig. 3. Compared with the actual failure rate, the results show that the adopted failure rate fitting algorithm has high fitting accuracy, which can meet the requirements of engineering application. On this basis, considering the influence of short-term monitoring information and other factors, according to on-site operating experience, each device in the lowvoltage distribution network uses 80 points as the threshold value for distinguishing the normal state of the equipment from the abnormal operating state. Therefore, the status evaluation scores of the low-voltage distribution network equipment in case1 and case2 in the table are higher than the threshold value, indicating that the lowvoltage distribution network equipment in these two cases is in a normal operating state and does not need to describe the gamma distribution. Based on this, according to the obtained equipment failure rate based on historical data and the failure rate obtained based on monitoring information, the failure rate of the distribution network equipment under normal operation and abnormal operation can be obtained. Based on the generated topology and the failure rate model of each distribution equipment, the power outage loss evaluation under the failure of the distribution network can be realized [2]. On this basis, according to the obtained low-voltage distribution network topology and the failure prediction model of low-voltage distribution network equipment, the low-voltage distribution network failure risk assessment can be carried out, and the low-voltage distribution network failure repair strategy can be obtained, which will effectively improve the low-voltage distribution network. Operation and maintenance level of distribution network equipment (Table 3).
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Table 3 State parameters of low voltage distribution network equipment under different state scores Parameter
Status score
Shape parameter, α
Scale parameter, β
Case1
90
–
–
Case2
80
–
–
Case3
75
2
2
Case4
65
2
3
Case5
55
2
4
In summary, the method proposed in this article can not only make the low-voltage distribution network active repair plan take into account the impact of incorrect distribution network topology, and the changing trend of low-voltage distribution network equipment, so that the equipment operating status is more in line with the actual project, and it is effective for the low-voltage distribution network. The active repair of equipment has reference value.
5 Conclusion In view of the current low-voltage distribution network load and topology changes frequently, the actual topological structure is difficult to accurately identify, and the low-voltage distribution network equipment lacks an effective comprehensive fault prediction method. This article first proposes a layered automatic generation technology of station topology based on low-voltage sensing unit, which realizes the topology recognition and verification of transformer and cable branch, and cable branch and subscriber unit. On the one hand, it can directly act on incorrect equipment. The behavior provides the basis for maintenance. On the other hand, it provides an accurate primary system structure for formulating regional low-voltage distribution network maintenance strategies. On this basis, by integrating historical data and monitoring data of low-voltage distribution network equipment, a comprehensive analysis model for predicting the failure rate of low-voltage distribution network equipment has been established, which can effectively evaluate the actual health operation status of low-voltage distribution network equipment and take the initiative in low-voltage distribution network equipment. The formulation of emergency repair plans has important reference value. Acknowledgements The research is support by State Grid Tianjin Electric Power Company Science and Technology Innovation Fund Project (KJ20-1-26).
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References 1. Lijun Y, Xuejiao LV, Dan L (2016) Coordinated optimization strategy for multi fault repair and recovery of distribution network with distributed generation. Autom Electr Power Syst 40(20):13–19. https://doi.org/10.7500/AEPS20160116002 2. Zhigang L, Zhaozheng L, Jing Z (2015) Post disaster phased repair strategy for distribution network with distributed generation. Adv Technol Electr Eng Energ 34(1):69–74 3. Zhaoli G, Mingkai X, Suying D et al (2019) Optimization scheduling of multi-fault rush repair for distribution networks based on modified artificial bee colony algorithm. Power Syst Protect Control 47(13):107–114. https://doi.org/10.19783/j.cnki.pspc.180924 4. Ming AL (2016) Research on multi fault repair strategy of active distribution network considering DG and time-varying load. Yanshan University 5. Jorge MB, Héctor VO, Miguel LG, et al (2014) Multi-fault service restoration in distribution networks considering the operating mode of distributed generation. Electr Power Syst Res 116:67–76. https://doi.org/10.1016/j.epsr.2014.05.013. 6. Zhang C, Zhenzhi L, Fushuan W (2014) Multi objective bi level optimization strategy for power system network reconfiguration. Autom Elect Power Syst 38(7):29–38. https://doi.org/ 10.7500/AEPS20130623007 7. Guo K, Jin P, Qi L, et al (2015) A multi-fault rush repair strategy for distribution systems based on game theory of multi-agent. Chinese Automation Congress (CAC), 27–29 Nov 2015, Wuhan, China 8. Xiaoming G, Junyong L (2011) Research on power grid emergency resource scheduling scheme. Power Syst Protect Control 39(20):11–16. https://doi.org/10.1016/j.rser.2014.03.034 9. Bojiang L, Shujiang Z, Huiyu Z (2020) Fault diagnosis integrated platform based on typical characteristics of electrical signal on the low voltage side of distribution network. J Electr Power Sci Technol 35(6):90–98 10. Zhiyou C, Mingjin T, Xiaojing L et al (2018) Distribution line fault location method based on double-terminal electrical quantities. Electr Measur Instrum 55(8):46–50, 57. http://www.emi journal.net/dcyyb/ch/reader/view_abstract.aspx?file_no=20170514003&flag=1. 11. Zhenxing L, Jialing W, Xin W et al (2021) A novel method of fault line selection and section location based on the input and cutoff of medium resistance. Power Syst Protect Control 49(7):57–65. https://doi.org/10.19783/j.cnki.pspc.200670 12. Yanqing C, Tao L et al (2020) Single-phase-to-earth fault location in distribution networks considering the distributed relations of the zero-sequence currents. Power Syst Protect Control 48(22):118–126. https://doi.org/10.19783/j.cnki.pspc.200045 13. Xiao Y, Ouyang J, Xiong Y et al (2020) Fault protection method of single-phase break for distribution network considering the influence of neutral grounding modes. Protect Control Modern Power Syst 2:1–13. https://doi.org/10.1186/s41601-020-00156-w 14. Xiaohong L, Min Z, Wenzhong C (2018) Research and judgment model of power grid fault based on Grey experience fusion. Electr Power 51(4):27–33 15. Daning Y, Hanbing Q, Jian H et al (2018) Research on fault analysis and identification strategy for distribution network. Power Syst Protect Control 46(13):84–91. https://doi.org/10.7667/ PSPC170862 16. Yaling L (2019) Research on 10 kV feeder fault prediction method based on deep learning. Chongqing University 17. Junting S (2018) Fault analysis of 10 kV rural distribution network based on Grey prediction. Shenyang Agricultural University 18. Hua Z (2016) Research on reliability prediction model and algorithm of distribution system. Chongqing University
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19. Zhichun Y, Xiaoping J, Jian L (2019) Real time evaluation method of distribution equipment status based on MI-PSO-BP algorithm. Electr Power Autom Equip 39(12):108–113. https:// doi.org/10.16081/j.epae.201911008 20. Peng S, Shaohui C, Caiqing Z (2020) Life cycle failure rate assessment of substation equipment based on Marquardt method parameter estimation. Power Syst Protect Control 40(1):85–90. https://doi.org/10.3969/j.issn.1674-3415.2012.01.015
Research on Target Customer Sales Strategy of Electric Vehicles Based on Machine Learning Zhiyuan Wang , Uchani Omar , and Menglin Lv
Abstract In order to improve the development of the new energy automobile industry and improve the technology of all aspects of electric vehicles in a targeted manner, this article will establish a preference model based on the time-length survey data. First of all, this paper uses two different embedding methods based on penalty terms and tree model are used for feature selection. The former uses three models of LR, LASSO, SVM, LF and LightGBM models for machine learning. Find the relevant characteristics that affect the sales of different brands, and use the voting method on the selected characteristics. The results found that the battery technical performance, comfort, target customers’ annual mortgages, and car loans accounted for the three brands’ annual household income. The sales have a greater impact. In addition, economy, safety, and customer work conditions also have varying degrees of impact on the sales of different brands. Keywords Embedding method · LR · LASSO · SVM · LightGBM · Machine learning
1 Introduction The automobile industry is an important pillar industry of the national economy, and the new energy automobile industry is a strategic emerging industry. Vigorously developing new energy vehicles represented by electric vehicles is an effective way to solve energy and environmental problems, and the market prospects are broad. However, electric cars are a new thing after all. Compared with traditional cars, consumers still have some doubts in some areas, such as battery problems, and their market sales require scientific decision-making. There are many influencing factors that determine whether a target customer will buy an electric car, including the factors of the electric car itself, and also the personal characteristics of the target customer. This paper analyzes the existing Z. Wang (B) · U. Omar · M. Lv Chongqing University of Posts and Telecommunications, Chongqing 400065, China e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_141
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market research data, plans out the factors that affect the sales of different brands of electric vehicles, establishes customer mining models for different brands of electric vehicles, and evaluates the excellence of the models.
2 Implementation Steps 2.1 Overview The filtering method and the wrapping method in the feature selection method are carried out independently in the feature selection process and the model training process, while the embedding method is to comprehensively consider these two processes and perform feature selection while learning. Therefore, in order to make the results more meaningful Representativeness, which is conducive to model training, this article uses the following two embedding methods. One is the feature selection method based on penalty items. This paper uses the penalty item feature selection method based on SVM model, LASSO model, and logical regression model to select features [1–4]. Use the regular L1 norm as the penalty term. The L1 norm can not only reduce the risk of overfitting, but also make the obtained w have more components as zero. So when you want to reduce the dimension of the feature for use in other classifiers, you can choose the feature corresponding to the coefficient that is not 0. The other one is the feature selection method of the tree model. This method can be used to calculate the importance of features, so it can be used to remove irrelevant features. This paper uses the tree model feature selection method of random forest model and LightGBM [5] model to select features. According to the importance of the features, a threshold is set to obtain the top features of each algorithm.
2.2 The Establishment of LR Model Logistic regression is a powerful statistical method, which can use one or more explanatory variables to represent a binomial result [6]. It estimates the probability by using a logistic function to measure the relationship between the category dependent variable and one or more independent variables, the latter obeys the cumulative logistic distribution. Its definition is as follows: h(z) =
1 1 + exp(−z)
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The domain of this function is the entire real number domain, the value domain is (0, 1), and it is a monotonic increasing function. According to the requirements of the distribution function, this function can be used as the distribution function of the random variable x, namely: p(x ≤ z) = h(z)
2.3 The Establishment of LASSO Model The full name of LASSO is Least absolute shrinkage and selection operator, which is a kind of compression estimation. It obtains a more refined model by constructing a penalty function, which makes it compress some regression coefficients, that is, the sum of the absolute values of the forced coefficients is less than a certain fixed value. At the same time set some regression coefficients to zero [7]. Therefore, the advantage of subset shrinkage is retained, and it is a biased estimate for processing data with multicollinearity. LASSO adds an lp norm as a penalty constraint in the calculation of RSS minimization. The advantage of the lp norm is that when λ is sufficiently large, some coefficients to be estimated can be accurately contracted to zero. Through the cross-validation method: cross-validate the given value of λ, select the λ value with the smallest cross-validation error, and then refit the model with all the data according to the obtained λ value. ∧
β Lasso = argmin(||Y − Xβ||2 + λ
d j=1
|β j |)
(1)
Among them, t corresponds to λ one by one, which is the adjustment coefficient.
2.4 The Establishment of SVM Model The SVM support vector machine is mainly for the two-class linear classifier. The method is to determine a hyperplane to maximize the distance between the data points and the hyperplane. This is a quadratic programming problem [3]. Since it is difficult to find a suitable mapping for any data set, it is usually selected from the commonly used kernel functions. Commonly used kernel functions include polynomial kernel functions, Gaussian functions, linear functions and so on. The constraints of the classification hyperplane are: yi (w T xi + b) ≥ 1
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If the slack variable ξi and the penalty factor C are added to punish the samples that violate the inequality, the following optimization problem can be obtained: min 21 w T w + c li=1 ξi yi (w T xi + b) ≥ 1 − ξi ξi ≥ 0, i = 1, 2, ..., l
2.5 The Establishment of LightGBM Model LightGBM is a distributed gradient boosting framework based on decision tree algorithm. Its advantage lies in reducing the use of data to memory, ensuring that a single and as much data as possible without sacrificing speed, while reducing the cost of communication, improving the efficiency of multi-level parallelism, and achieving linearity in calculations accelerate [8–10].
2.6 The Establishment of Random Forest Model Random forest refers to an algorithm that uses multiple decision trees to train and predict samples [11]. The specific formula is as follows: Giniindex (D, a) =
v v=1
|D v | Gini(D v ) D
The Gini gain is: Giniindex (D, a) = Gini(D) − Gini_index(D, a)
2.7 Feature Selection Results Based on Tree Model Feature Method This paper adopts the tree model feature selection method of random forest model and LightGBM model to select features, and the calculation results are shown in Tables 1 and 2.
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Table 1 Features selected by embedding method based on penalty term Feature selection method
Brand 1
Brand 2
Brand 3
LR
a1 a2 a3 b4 b5 B15 B16 B17
a1 a2 a3 b4 b5 B11 B15 B16 B17
a1 a2 a3 b4 b5 B15 B16
SVM
a1 a2 a3 b3 b6 B10 B16 B17
a1 a2 a3 b3 b6 B10 B11 B16 B17
a1 a2 a3 b3 b6 B10 B16
LASSO
a1 a2 a3 a6 b6 B12 B16 B17
a1 a2 a3 a6 b6 B10 B12 B16 B17
a1 a2 a3 a6 b6 B12 B15
Table 2 Features selected by embedding method based on tree model Feature selection method
Brand 1
Brand 2
Brand 3
LightGBM
a1 a2 a3 a6 b6 B12 B16 B17
a1 a2 a3 b3 b6 B10 B11 B16 B17
a1 a2 a3 b4 b5 B15 B16
SF
a1 a2 a3 b3 b6 B10 B16 B17
a1 a2 a3 b3 b6 B10 B11 B16 B17
a1 a2 a3 b3 b6 B10 B16
Figure 1 is a graph of feature appearance times obtained by voting on each feature using five models. This paper selects features with appearance times greater than or equal to 2 as important features, and believes that it will have an impact on the three brands of electric vehicles.
2.8 Summary It can be seen from Fig. 1 that for the three brands, the battery technical performance, comfort, target customer’s annual housing loan, and car loan accounted for twice or more of the annual household income. The customer’s purchase situation has a greater impact. In addition to the above four indicators, the factors affecting the purchase of brand 1 include economy, safety, driving control, and target customer positions; economy, safety, power, appearance and interior decoration, and target customer’s working conditions (Including working years and the nature of the unit), annual family income and disposable annual income will be the main considerations for target customers to purchase brand 2; the main influencing indicators of brand 3 sales are motivation, the target customer’s marriage and family situation, and Working years.
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5 4 3 2 1 0 a1 b16 b17 a2
a3
a4
b6 b12 a6
b2 b15 b7
a5
5 4 3 2 1 0
a1 a3 b16b17 a5 a7 b11b15b13 a2 a4 b10 b8 b9 b14 b1
5 4 3 2 1 0
a2
a16
Fig. 1 Feature appearance
a1
a5
b6
b10
b17
b15
a3
a6
a8
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3 Conclusion By comparing and verifying five models, the team found that Random Forest is suitable for joint venture brands and new power brands, independent brands are suitable for LightGBM model, and the F1 value and AUC value of the two models are both greater than 97%, which is close to the perfect model. Therefore, precision marketing can be carried out on the basis of these models. In order to find an optimal solution for improving customer satisfaction and reducing service difficulty, a conclusion is drawn on the basis of the established model: joint ventures, independent and new power brands, under other conditions unchanged, respectively improve customer’s economic efficiency and battery performance Satisfaction with comfort and comfort helps to increase the customer’s car purchase rate. In summary, the above sales strategy meets: the need to increase customer satisfaction and purchase rate under the condition that the number of services and the difficulty of the service are as small as possible; for target customers with certain characteristics, such as home address in the city, married, Freelance or mediumincome families carry out precision marketing to help the sales department maximize benefits.
References 1. Zijian Z, Xiangling L, Xinzhe L et al (2021) Prediction of soil Cu pollution risk based on binary logistic regression model. Soil Bull 52(06):1418–1426. https://doi.org/10.19336/j.cnki. trtb.2021020701 2. Qianying Y, Juan L, Hongde D, Fulu X (2022) Prediction of similar remaining life of aeroengine based on Lasso variable selection. J Aerodyn 1–8. 10.13224/ j.cnki.jasp.20210516 3. Dongmei L, Haoran W, Chun L, Zhiqiang L (2021) Research on fault diagnosis of spectrometer amplifier based on GSA-SVM. Sens Microsyst 40(12):62–65. https://doi.org/10.13873/J.10009787(2021)12-0062-04 4. Xiang A (2021) Research on the control model of LF furnace alloy optimization system based on data. Shenyang Ligong Univ. https://doi.org/10.27323/d.cnki.gsgyc.2021.000247 5. Qian X, Yunfei M, Zhipeng J, Jinhao M, Hongjie J (2022) Research on online prediction of remaining service life of electric vehicle battery based on improved LightGBM. J Electrotech Eng 1–13. https://doi.org/10.19595/j.cnki.1000-6753.tces.211075 6. Wenjing H, Dan D, Jielin D, Mingyue W (2021) A high-dimensional logistic regression model based on the graph structure of predictors. J Chongqing Technol Bus Univ (Nat Sci Ed) 38(05):107–113. https://doi.org/10.16055/j.issn.1672-058X.2021.0005.018 7. Tong F, Zhi S (2021) A LASSO-based multi-variable mixing GARCH model design and optimization algorithm research. Quant Econ Tech Econ Res 38(12):146–163. https://doi.org/10. 13653/j.cnki.jqte.2021.12.007 8. Jianli D, Yue S (2021) Multi-class prediction of flight delay based on LightGBM. J Nanjing Univ Aeron Astron 53(06):847–854. https://doi.org/10.16356/j.1005-2615.2021.06.003 9. Lanye H, Wenbo J, Yanting L (2021) Wind turbine fault diagnosis based on LightGBM. Acta Solar Energy 42(11):255–259. https://doi.org/10.19912/j.0254-0096.tynxb.2019-1183
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10. Zhihui W, Jing W, Pengbo F, Fan X, Qimeng L (2021) Abnormal flow detection method for electric power industrial control system based on LightGBM. Electr Power Inf Commun Technol 19(11):69–77. https://doi.org/10.16543/j.2095-641x.electric.power.ict.2021.11.010 11. Yanping X, Yian C (2021) Urban air quality prediction model based on random forest regression and meteorological parameters: taking Chongqing as an example. J Chongqing Technol Bus Univ (Nat Sci Ed) 38(06):118–124. https://doi.org/10.16055/j.issn.1672-058X.2021.0006.016
Automatic Recognition of Draft Marks on a Ship’s Board Using Deep Learning System Yaroslav Kirilenko
and Ignat Epifantsev
Abstract One of the basic concepts affecting the technical-operational characteristics of the vessel is its draft, which in the conventional sense means vertical distance from water level to the lowest point of the bottom of the vessel. The displacement of the vessel can be calculated from the observed draft. Currently there are a number of ways to determine the draft, among which visual observation of marks of the vessel board of the officer responsible for this is the basic of world practice. However, all existing methods have different restrictions on the installation and use of systems necessary for their implementations or give a significant error when measuring the draft. As the main instrument to fix this problem in this paper the use of artificial neural networks of deep learning is proposed. An algorithm for frame-by-frame video processing using a system of technical vision for detection of marks on the vessel board and detection of operating waterline is given. Solving these two challenges will give a conclusion about the ship’s draft based on the extracted visual information. On the basis of experimental data, the possibility of introducing a technical vision system in solving the considered problem is assessed. Keywords Deep learning · Measurement · Draft marks · Computer vision
1 Introduction The carriage of different goods by sea transport is backbone of the today international economy and trade. According to United Nations Conference on trade and development it is estimated that 80% of the volume of all cargoes are being transported by ships [1]. One of the stages of loading the goods on the vessel is monitoring the load lines since the abidance of required load line is essential for vessel security while on the high seas. Example of such marks could be seen at Fig. 1. Y. Kirilenko · I. Epifantsev (B) St. Petersburg State Marine Technical University, 3, Locmanskaya Street, 190121 St. Petersburg, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_143
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Fig. 1 Example of load lines and draft marks
Moreover, error on this stage of loading and overloading the vessel could lead to a fine and delay of the vessel, whereas shortage of cargo even by centimeters can result in a loss of 8,000 $ to $100,000 in income depending on the type of cargo and the type of vessel. The most common way to control the correct placement of marks on vessel board is by human observation, where surveyors observe at each set of marks and the average is calculated to find out the mean draft. Example of such marks can be seen at Fig. 1. While this solution is quite cheap and effective, it can produce many errors that any man made observation is producing, because of effects such as: lack of surveyor experience, bad visibility or simply error in calculations. Moreover, observation while in the bad weather or high waves can be potentially dangerous to the lives of surveyors. To fix this problems, many alternative methods and instruments were proposed and developed such as: hydrostatic pressure, GLONASS/GPS equipment, ultrasonic sensors and computer vision. However, most of the presented methods have some kind of limitations, that are preventing them from being implemented in practice in most seaports. Determination of vessel draft using hydrostatic pressure consists in measuring the distance from the lower edge of the keel of the ship to the surface of calm water using hydrostatic pressure sensor of at least three points located in the bow, middle and stern parts of the vessel. All measuring points are located at the bottom of the vessel, while calculations of the average draft are carried out automatically using the controller. The problem with this method is the long and difficult method of installation, that leads to high price and therefore inefficiency to recreate this method on every ship if we would like to automate draft detection. The essence of the GLONASS/GPS method lies in the fact that the determination of the ship’s draft is carried out using the geodetic equipment GLONASS/GPS by measuring the heights of the receiving antennas of the ship’s rover and rover installed on a floating base, and using a mobile computer to calculate the desired parameter in
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the ship’s coordinate system. While this method is effective and easy to implement than hydrostatic pressure, it doesn’t work well in troubled waters. Ultrasonic sensors are installed on the vessel hull, where it emits a sound signal on the surface of the water, and when it receives it back, calculates height to waterline. Problem of this method is that when high waves are close to each other, it is almost impossible to get correct data using this method. Computer vision method needs excellent adjustment of algorithms, and it is sensitive to noises in the image. However, if these problems would to be overcame, computer vision method could be automated even in undeveloped seaports. This paper will discuss needed algorithm for detection of marks on the vessel board as well as instruments which are needed to properly execute it.
2 Computer Vision Algorithm The algorithm for computer vision in general can be described as follows. First, a frame is taken from the incoming video stream at a certain time interval, for example one frame per second. In this frame first step algorithm needs to be done is to evaluate place where hull of the vessel is located, where’s the surface of the water. Second one is to detect locations of numbers Third one is to deduce center of detected numbers. Fourth step is to make a coordinate scale. Fifth step is to draft by intersection point of waterline and coordinate scale. Visualization of this algorithm could be seen at Fig. 2. To complete this steps, algorithm needs to preform semantic segmentation of the image and preform object detection. Instrument that could be used to preform step number one and two is a deep convolutional neural networks (CNNs). CNN is a deep learning algorithm that can take image as input, and assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other. It consists of different layers, purpose and number of which differs in different realizations. However, there are layers that are used in any type of CNN, those layers are: Convolutional layer and Pooling layers. Convolutional layer is the first layer that is used to extract the various features from the input images. It uses a filter (kernel) that represents a weight matrix. This kernel slides through 2d image across 3 channels (RGB) performing the multiplication operation element by element with the part of the input data over which it is currently
Fig. 2 Process of semantic segmentation
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located, and then sums all the obtained values into one output pixel. This operation preforms on each location making input matrix to smaller variant, but still a 2d matrix of features. Before using Pooling layer, ReLU (Rectified Linear Unit) that is representing f(x) = max(0,x) is usually used on output of previous layer. It used, because to train deep neutral networks with backpropagation of errors, CNN needs a nonlinear function, that acts like a linear function. After the use of ReLU, there is still some problem with a result of convolutional layer, that a feature map output is a record of a precise positon of features in the input. This makes small movements in the position of a feature of the input image results in a different feature map. To bypass them, Pooling Layer is used. Pooling operation uses same principal of kernel manipulation, but with different function. The size of kernel is smaller than the size of the feature map; specifically, it is almost always 2 × 2 pixels applied with a stride of 2 pixels, which results in a pooling layer being reduced by factor of 2. Kernel operation is specified; in most cases it is a function called “Max Polling” that selects the maximum element from the region where filter is looking at. Therefore, the output after filter goes every patch is a feature map that contains the most valuable features of input feature map. After using stack of those layers in a row, other layers that are used in CNN become more different with each realization. For example, to complete semantic segmentation, there are many different CNN that could it with different approach, like R-CNN, U-NET, or FCN. In the future, when we will create a working program, we have decided to use CNN U-NET, because this particular architecture was made for semantic segmentation. Example of theoretical result of such segmentation could be seen at Fig. 3. Semantic segmentation is the first step of the algorithm. Second step of the Algorithm is to determine the draft marks on the board of the vessel, and it can also be done with CNN. Draft marks are always drawn in the same way, “M 8 6 4 2” where right of M is located integer number of height, and 8 6 4 2 are decimal numbers. Because we know how are they looking, where they are placed on board of the ship, and their relative size to each other, we can collect dataset from
Fig. 3 Result of algorithm
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different vessels to train and train a deep learning neutral network, so that it would be able to detect needed numbers on the frame. When we will create program we will use YOLO with realization on CNN, reasons for why we decided to use it will be described in the next chapter. It should be noted that there could be potential noise on images that we get from camera feed. For example, rain can potentially make it impossible to properly understand what numbers are on a given frame. Without a working model, we cannot say for sure how far these potential problems can lead to, but if they will, methods to prevent them will need to be developed. Such methods could be preforming deraining algorithm to remove the effect of rain and restore the image from a given frame, or analyzing video feed at a higher FPS to average the value from multiple images analyses. If we will be able to successfully make this analyses, we will be able to perform steps 3 and 4 to found center of numbers and create coordinate scale. After that we will be able to perform step 5, to detect draft by intersection point.
3 Training a Model for Mark Detection First, we need to choose what instruments we will use to collect dataset and train needed model. We decided to use resources provided by Roboflow [2] and Google Collabs [3]. Roboflow will give us instruments to organize, annotate, and create a dataset, whereas Google Collabs will provide us with cloud based GPU needed to train a model. First step needed to train a model that we need to detect draft marks, is to collect a dataset of different images of ship boards in the water. This data will be collected from “Youtube” from channel named “Max Ma” [4]. From this source, we will collect different draft measurement videos with total duration of 7 min. From this videos we will sample total of 420 images, that we will randomly divide in format 70% train 20% validation 10% test. Because detection of numbers is quite simple, every popular architecture can be used to detect theme with high precision. This is why we have decided that the most important characteristics for trained model should be: speed with which algorithm will detect numbers, and therefore the best work in real-time scenario. We have decided that the best model that meets these criteria is architecture named YOLO (You Look Only Once), because it is one of the fastest models and is the best choice for analyzing live video feed [5]. YOLO a state-of-the-art, real time object detection system. The idea of YOLO could be described as follows: Yolo divides a frame into a S × S grid, where each grid cell is responsible for predicting the object centered in that grid cell. For each grid cell YOLO predicts B bounding boxes, that are confidence for those boxes, that are made up of 5 numbers: x position, y position, width, height, and the confidence. Also YOLO predicts C conditional class probabilities. This class prediction is represented by a one-hot vector length C, the number of classes in the dataset. It should be noted
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Fig. 4 YOLO model
that there is only one C per grid cell, and that means that if there are two or more different classes in one grid cell, YOLO will fail to correctly find both correctly. Because board numbers are 20 cm apart each other, frame that will be analyzed should show relative close image of numbers, because if number will be to close on the analyzed frame YOLO will fail to classify them. Overall prediction of model is a S * S * (B*5 + C) tensor. Visual example on how it works can be seen at Fig. 4. We decided to use Scaled YOLO-V4 version of this architecture, because it’s one of the fastest and one of the most developed version of YOLO. Also, for training a model there is two most notable realizations of YOLOv4. First one is YOLOv4-CSP made using PyTorch framework, for training somewhat standard YOLO V 4 Model. Second one is YOLOv4-tiny made using Darknet framework, that is worse than first one in detection accuracy because it has less layers. However, thanks to that model preforms much faster and can be used on mobile platforms [6].
4 Synthesis of Linear Filter After determining the draft according to the algorithm presented in Sect. 2, it is necessary to filter the values to exclude abrupt changes, draft due to various noises associated with the ship’s pitching, frame noise at the time of detection of marks, etc. To do this, we synthesize the simplest linear filter. The algorithm consists of two repeating phases: prediction and correction. At the first, the prediction of the state at the next moment in time is calculated (considering the inaccuracy of their measurement). On the second, the new information corrects the predicted value (including considering the inaccuracy and noisiness of this information).
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Fig. 5 Visualization of filtering an array of measurements with the linear filter
The current value of the draft at time ti is found from the expression X (ti ) = Y ∗ (ti ) − ξ (ti ) where Y ∗ (ti )—draft measure, ξ (ti )—total deviation X (ti + 1) = X (ti ) + P(ti ) Y ∗ (ti ) − X (ti )
with X (ti ), X (ti + 1)—current and next draft estimate, Y ∗ (ti ) − X (ti ) = τ — residual, P(ti )—residual weight. −1 P(ti + 1) = K (ti ) K (ti ) + τ 2 =
K (ti ) K (ti ) + τ 2
K (ti + 1) = K (ti ) − P(ti + 1)K (ti ) =
K (ti )τ 2 K (ti ) + τ 2
where K (ti )—variance error matrix. The filtered values of the ship’s draft are shown in the Fig. 5.
5 Implementation of Algorithm A successfully made algorithm is needed to be implemented in some kind of a hardware, that can give a video frame from board of the ship to analyze it. From our point of view, this equipment should be able to give a good stable image being perpendicular to the draft marks that program is analyzing. The best overall equipment for this criteria is unmanned aerial vehicle (UAV).
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This how we see it may be implemented: Operator in a ship port controls the drone to bring it to the required vessel to needed angle, and turns the hovering function on the drone. Now, drone is giving out the draft level for a person responsible for ship loading, while operator can do something else, for example moving another drone for another ship. When loading is complete, operator gives command for drone to automatically return to base the same way that it was operated before. While developing a working program that operator will use, there are some potential features implementation of which should be considered. First, because different ships need different load, that differentiates in different time of a year, operator should be able to type in what exact vessel draft he needs. Secondly, it makes sense to average the resulted output from algorithm, by showing as output average calculations of, for example, results of last three probabilities of reaching goal vessel draft so that a person who is using this data would not see possible errors because of the noise, such as lapping waves. Third, algorithm should detect when vessel load is near inputted numbers, to inform those who are responsible for ship load that they should end loading soon. Depending on a difficulty of developed algorithm, and characteristics of a drone that will be used to automate the process of ship draft measurement, there could be 2 potential ways to make calculations. First, drone could make analyzes and calculations on its own, as well as giving needed information for operators, or if equipment will be to slow the only drone will do is give out camera feed for computer located in ship port, where it will complete actions similar to self-working drone. If we would like to make a self-working drone we will need to install GPU somewhere in its corpus, because we need it to make calculations. However, if we want to install an additional electronic part in a drone we need it to meet some characteristic. First on is that the weight of installed GPU should be as low as possible, because drone will simply not able to fly if it’s too heavy. Second thing that should be considered is energy consumption of a GPU installed compared to how much power drone buttery provides, because if drone battery is too weak or GPU consumption is too big, then drone will not able to fly for a period of time needed to evaluate the draft. Raspberry Pi 4 and Jetson Nano are the most popular and affordable microcomputers that we can use to meet these criteria. Because the most required thing we need from a microcomputer is its GPU, we have decided that Jetson Nano will be more optimal choice, since 128-core Maxwell is much more efficient GPU than Broadcom Video Core VI that raspberry provides. According to tests [7] of YOLO on Jetson Nano, we will be able to get somewhere around 4 to 6 FPS using YOLOv4 versions that provide the most accurate results. Considering that we don’t need high FPS for our goals, because there are not much objects going in and out a frame when observing draft marks, we think that Jetson Nano have potential to provide optimal results needed for precise draft reading.
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6 Possible Problems of Implementaiom and Methotds to Fix Them Geographic location of sea ports in which drone will operate should be consider, as well as weather conditions could be very important because there are some potential problems that can occur. For example, Russia is a very big country and there are many sea ports that are located in northern part of the country. If a drone was not designed to be used under -10 to -15 °C than it can potentially malfunction, for example in Murmansk port. Also, protection from weather condition such as rain, snow and strong wind should be considered in drone design, if we want be able to use it in when weather condition is potentially dangerous for ship draft observers. Loading of a vessel can perform for days and drone can’t observe numbers for all of this time. Potentially, there are two ways to fix this problem. First one is to use UAV when it’s become obvious that a ship should be soon stop loading. Second one, is to use a drone with some intervals in time, and after some limit drone is used more frequently, waiting for when the main algorithm should be used.
7 Conclusion Different ways of drafting ship is considered and deduced what type of method we should use. Algorithm that could be implemented for successful computer vision is developed. We found out what instrument we should use to have correct camera feed and have analyzed what possible problems could be encountered in implementation phase and how can they be avoided.
References 1. Review of Maritime Transport 2018 (UNCTAD) 2. Popov AP, Sayarkin KS, Zhilenkov AA (2018) Analysis of perspective models of artificial neural networks for control of robotic objects. In: Paper presented at the 2018 IEEE conference of Russian young researchers in electrical and electronic engineering (EIConRus), pp 958–961. https://doi.org/10.1109/EIConRus.2018.8317248. 3. https://colab.research.google.com/notebooks/intro.ipynb 4. https://www.youtube.com/user/ponysgs/videos 5. Karpov AD, Zhilenkov AA (2017) Designing the platform for monitoring and visualization orientation in Euler angles. In: Paper presented at the 2017 IEEE conference of Russian young researchers in electrical and electronic engineering (EIConRus), pp 301–305. https://doi.org/10. 1109/EIConRus.2017.7910551 6. Choi J, Ahn M, Kim J (2015) Implementation of hardware model for spiking neural network. In: Paper presented at the international conference on artificial intelligence 7. Zhilenkov AA, Gilyazov DD, Matveev II, Krishtal YV (2017) Power line communication technologies in automated control systems. In: Paper presented at the 2017 IEEE conference of Russian young researchers in electrical and electronic engineering (EIConRus), pp 246–249. https://doi.org/10.1109/EIConRus.2017.7910539
Creation and Verification of a Simulation Model of the Flotation Process of Copper-Nickel Ore Enrichment on the Example of Inter-cycle Flotation Roman Nikitin , Sergey Lukichev , Valery Biryukov , Yulia Kameneva , and Irina Vishnyakova Abstract The paper considers the dependence of the results of inter-cycle flotation of copper-nickel ores on the fineness of grinding, in particular, on the content of the flotation of the fineness class −0.071 mm in the feed. The forecast of the distribution of crushed ore into fineness classes was carried out by modeling the process of reducing the fineness based on the Gauss—Laplace distribution, taking into account the specifics of the ore material and grinding conditions. For the analytical presentation of the experimental results, an integrated approach was used based on the representation of the dependence of the froth product yield on the fineness of the flotation feed grinding in the form of an offset exponential distribution and a normalized offset Weibull distribution. The solution of the problem of analytical representation of the distribution of the useful component in the fineness classes of flotation products was performed on the basis of the B (beta) distribution according to the technological indicator of the extraction of the useful component. As a result, the developed model allowed to obtain an absolute error in the predictive ability of technological indicators at the flotation feed fineness interval used in experiments, no more than 1.28% for the yield of products and no more than 0.16% for the content of a useful component in products. Keywords Inter-cycle flotation · Transport infrastructure · Copper-nickel ores · Simulation model · Multivariate experiment · Weibull · Gauss-Laplace distributions · B (beta) distribution
R. Nikitin (B) · S. Lukichev · V. Biryukov · Y. Kameneva · I. Vishnyakova Mining Institute of the KSC RAS, 24, Fersman Street, Apatity, Murmansk Region 184209, Russia e-mail: [email protected] V. Biryukov Branch of Murmansk Arctic State University, 29, Lesnaia Street, Apatity, Murmansk Region 184209, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_144
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1 Introduction Copper-nickel sulfide deposits form the basis of the mineral resource base of the leading nickel-producing countries [1, 2]. The difficult-to-enrich thinly interspersed copper-nickel ores of the Pechengsky deposit are characterized by the predominance of thin inclusions of sulfides. The indicators of their enrichment are determined not only by the content of sulfides, but also by the ratio of ore and silicate minerals and other mineral and technological parameters [3]. The most important factor affecting the enrichment of interspersed copper-nickel ores is textural and structural. Therefore, the choice of the optimal grinding mode is an important factor for ensuring the necessary efficiency of mineral separation [4, 5]. One of the main reasons determining the unsatisfactory indicators of the flotation process is the insufficient disclosure of sulfide minerals during the grinding process [6]. Traditionally, when processing interspersed copper-nickel ores, twostage flotation schemes are used, including inter-cycle flotation after the first stage of grinding. Important components of research aimed at improving the efficiency of ore processing are the identification of factors affecting the enrichment processes, and the development of simulation models for these purposes as tools for predicting enrichment indicators [7–12]. Studies were carried out on the basis of the results of laboratory experiments, statistical processing methods, analysis of the experience of simulation modeling of enrichment processes [13, 14].
2 Study of Factors Affecting the Process of Inter-cycle Flotation of Coper-Nicel Ore The research was carried out on thinly interspersed ore. The ore belongs to the hardto-enrich and is characterized by a thin hard-to-open inclusiveness (0.4–0.6 mm). According to the analysis, the nickel content in the ore sample was 0.504%. The distribution of nickel in crushed ore indicates that it is controlled by the yield of fineness classes. A increase in the nickel content is observed in the class of −0.071 + 0.045 mm, and in the class of −0.045 mm it increases by 1.8 times (Fig. 1). Ore crushing was carried out in laboratory crushers to a size of −2.0 mm, with the finished product being eliminated. For grinding, a ball mill was used. The mass of the crushed sample was 1.2 kg, the ratio of liquid to solid was 1:0.6. Flotation experiments were carried out in an open cycle in a mechanical flotation machine. The flotation time was 10 min with a solid-to-liquid ratio of 1:2.5. Potassium butyl potassium xanthogenate (Kx) and sodium butyl aeroflot (Af) were used as collectors, copper sulfate was used to activate sulfide minerals, soda ash was used to create a pH medium. The flotation scheme is shown in Fig. 2. The research was carried out in two stages. Initially, a two-factor (n = 2) experiment was used to study the effect on the flotation of the content in the feed of the
Mass fracon
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Yield of size classes Distribuon of nickel in size classes
-0,045 +0,000
-0,071 +0,045
-0,100 +0,071
-0,160 +0,100
-0,200 +0,160
-0,315 +0,200
-0,400 +0,315
-0,630 +0,400
-1,000 +0,630
-1,600 +1,000
-2,000 +1,600
Size classes, mm
Fig. 1 Crushed ore: granulometric composition, content and distribution of nickel in fineness classes
Initial ore
Na2СO3;
Grinding
CuSO4;
Inter-cycle flotation Froth product
Chamber product
Fig. 2 The scheme used in conducting experiments on inter-cycle flotation
fineness class -0.071 mm (S) and the consumption of the xanthogenate (G). The following three levels of factor values (m = 3) were used: S = 40, 50 and 60%, G = 50, 60 and 70 g/t. Other factors of conducting experiments were maintained unchanged. The experiments at each point of the factor space were repeated twice (k = 2). The purpose of the first stage was to obtain a regression equation of the form ε = f (S, G) and establish the significance of the factors under consideration. For a two-factor experiment ε = f (S, G) takes the form of a polynomial: ε = b0 + b1 X 1 + b2 X 2 + b12 X 1 X 2 ,
(1)
where b—regression coefficients, X —encoded values of factors. For established factors: X1 =
S − 50 G − 60 ; X2 = . 10 10
(2)
The regression coefficients were calculated by solving a system of equations of the form (1). Note that such a system can be compiled and solved for each of the sets of values of εk and subsequently this will require averaging the obtained values of the regression coefficients. The solution of the system of equations for the average values of ε is equivalent. For the found (four) values of the regression coefficients: b0 = 31.64; b1 = 8.18; b2 = 1.27; b12 = 0.44
(3)
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the predicted values of nickel extraction into the froth product were calculated. The growth of the determination coefficient showed that a decrease in the fineness of the flotation feed leads to an increase in the extraction of nickel into the froth product, and a change in the xanthogenate consumption and the effect of interaction of the factors under consideration do not statistically affect the result. The reverse transition from the encoded values of the factors gives the dependence: ε = 0.818S − 9.278.
(4)
Further increase of up to 70% in the content of the fineness class −0.071 mm in the feed with a constant xanthogenate consumption of 60 g/t showed that with an increase in the extraction of nickel into the froth product to 43.6%, its content decreases to 2.8%.
3 Study of the Dependence of the Distribution of Nickel in the Fineness Classes of Flotation Products on the Content of the Fineness Class −0.071 mm in the Feed At the second stage the dependence of the distribution of nickel in the fineness classes of flotation products on the content of the fineness class −0.071 mm in the feed was studied. The purpose was the formation of an algorithm for the simulation model of the flotation process of copper-nickel ore enrichment. The range of content in the feed of the fineness class −0.071 mm was expanded: S = 30, 40, 50, 60 and 70%. The results of experiments are shown in Table 1. γ fei - is the output of the i-th class of fineness and β ef i —is the nickel content in the i-th class of fineness in the froth product, γcie —is the output of the i—th class of fineness and βcie —is the nickel content in the i—th class of fineness in the chamber product. γ , β, S—here and below are given in fractions. The considered simulation model of the flotation is based on the dependence of the flotation indicators on the degree of grinding of the feed and on the ability to perform the forecast of reducing the fineness of mineral particles. The algorithm for simulating a discrete density function of the distribution of the yields of the fineness classes of mineral particles can be represented as follows. Let’s N fineness classes of granularity of crushed ore are allocated. To denote the number of each class, we will use the index i, 1 ≤ i ≤ N . The smallest, so-called thin particles have sizes in the range 0 < d1s ≤ d1 ; then: d1 < d2s ≤ d2 ; and so on to: d N −1 < d Ns ≤ d N . Here di —are the values of the boundaries of the fineness classes, dis —are the final sizes of particles in the fineness classes. The density function of the distribution of the yields of the fineness classes of particles in crushed ore is determined by the results of analysis and by entering the designation of the yield of the fineness class γi , it can be illustrated in the form given in Table 2.
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Table 1 The results of experiments on flotation with different degrees of grinding of feed Fineness classes. mm
Total
−0.045 −0.071 −0.100 −0.160 −0.200 −0.315 −0.400 −0.630 −1.000 +0.000 +0.045 +0.071 +0.100 +0.160 +0.200 +0.315 +0.400 +0.630 The grinding time is 10 min. S = 0.3163 γ ef i 0.0304
0.0036
0.0047
0.0057
0.0027
0.0022
0.0002
β ef i γcie βcie
0.0247
0.0313
0.0215
0.0190
0.0179
0.0178
0.0135
0.2272
0.0551
0.0646
0.0893
0.0627
0.1796
0.0941
0.1264
0.0513
0.9505
0.0049
0.0032
0.0032
0.0034
0.0036
0.0040
0.0040
0.0043
0.0042
0.0041
0.0495 0.0235
The grinding time is 16 min. S = 0.4268 γ ef i 0.0331
0.0048
0.0043
0.0054
0.0024
0.0015
0.0515
β ef i 0.0317
0.0338
0.0255
0.0228
0.0212
0.0168
0.0295
γcie βcie
0.3130
0.0759
0.1034
0.1603
0.0949
0.1660
0.0256
0.0095
0.9485
0.0043
0.0031
0.0033
0.0033
0.0035
0.0037
0.0036
0.0036
0.0037
The grinding time is 22 min. S = 0.4975 γ ef i 0.0354
0.0059
0.0050
0.0061
0.0018
0.0011
0.0553
β ef i γcie βcie
0.0322
0.0349
0.0271
0.0223
0.0181
0.0136
0.0301
0.3580
0.0982
0.1256
0.1748
0.0888
0.0926
0.0066
0.9447
0.0041
0.0032
0.0032
0.0031
0.0033
0.0034
0.0032
0.0036
The grinding time is 29 min. S = 0.6021 γ ef i 0.0428
0.0063
0.0059
0.0048
0.0010
0.0004
0.0613
β ef i 0.0368
0.0359
0.0282
0.0225
0.0175
0.0131
0.0343
γcie βcie
0.4327
0.1202
0.1502
0.1615
0.0507
0.0235
0.9387
0.0032
0.0030
0.0030
0.0031
0.0033
0.0033
0.0031
The grinding time is 37 min. S = 0.7144 γ ef i 0.0608
0.0061
0.0051
0.0026
0.0004
0.0750
β ef i γcie βcie
0.0330
0.0337
0.0235
0.0190
0.0146
0.0318
0.4995
0.1480
0.1517
0.1036
0.0176
0.0046
0.9250
0.0029
0.0026
0.0028
0.0029
0.0030
0.0036
0.0029
Table 2 The form of the density function of the distribution of the yields of the fineness classes in crushed ore Fineness classes
Total
Class number
1
i
N
Class boundaries
−d1 + 0
−di + di−1
−d N + d N −1
Fineness class yield in the feed
γ1
γi
γN
N
i=1 γi
=1
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In the process of reducing the fineness of the particles formed during the destruction of larger particles replenish the number of smaller particles. This will lead to the formation of a lower triangular i ∗ i matrix, the elements of which will represent the normalized values of the weights of the discrete density function of the distribution of the yield of particle fineness classes obtained as a result of the particle fineness reduction. Let’s consider the procedure for calculating one element of such a matrix in a distribution, for example, of the i-th class of fineness: Step 1. Calculation of the variance of the distribution of this fineness class: σi =
dis
E/K exp − − exp(−E/K ) , 2
(5)
where E—is the energy per unit volume of the mineral grain being destroyed, K—is the Bond work index. These values are related by an empirical dependence dE = K
dd , dm
(6)
the integration of which at different values of m leads to expressions of the wellknown laws of reduction of the fineness of Kirpichev-Kik, Rittinger and Bond, which, in turn, define a functional relationship between the final size of particles obtained after reducing the fineness of mineral grains diend and their initial size dis : diend = ω dis , E/K .
(7)
Step 2. Calculation of the matrix element. In the process of forming a matrix of values of weights of the density function of the distribution of the yields of the fineness classes of mineral particles, the particles of the i-th class are distributed into the j-th classes, 1 ≤ j ≤ i: ⎛ ⎛ 2 ⎞ 2 ⎞⎤ s end s end d d − d + d j i j i 1 ⎢ ⎜ ⎟ ⎜ ⎟⎥ √ ⎣exp⎝− ⎠ + exp⎝− ⎠⎦. 2σi2 2σi2 σi 2π ⎡
f i j d sj =
(8)
Step 3. Calculation of the sum of the weights of the density function of the distribution of the yields of the mineral particle fineness classes for each i-th class of fineness in the form: i j=1
f i j d sj
Step 4. Normalization of the obtained values of the sums of the weights of the density function of the distribution of the yields of the fineness classes of mineral particles and, in fact, the formation of the desired matrix (Table 3).
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Table 3 The form of the matrix of the normalized values of the weights of the density function of the distribution of the yields of the fineness classes of particles obtained as a result of the reduction of fineness Fineness classe
1
j
N
1
1
-------------
-------------
1
i
f i1n =
f inj =
-------------
i
f i1 (d1s )
d sj
n j=1 f i j
=1
f i j d sj
s j=1 f i j d j
i
j=1 f i j
N
i
f Nn 1 =
f Nn j =
f Nn N =
f N 1 (d1s )
N s j=1 f N j d j
f N j d sj
N s j=1 f N j d j
s f N N (d N
) N f d sj N j j=1
N j=1
f Nn j = 1
Table 4 The form of presentation of the result of simulation modeling of the discrete density function of the distribution of the outputs of particle fineness classes after reducing the fineness Fineness classes
Total
Class number
1
Class boundaries
−d1 + 0
Fineness class yield in the feed
γ1sim =
i N i=1
N
−di + di−1 γi f i1n
γ jsim =
N i= j
−d N + d N −1 γi f inj
γ Nsim = γ N f Nn N
N j=1
γ jsim = 1
Finally, the fineness reduction model for the density distribution function of the yields of the mineral particle fineness classes γisim , based on (8), is formed by summing the products of its normalized weight values by the values of the yields of the fineness classes in the feed of the fineness reduction on the columns of the matrix shown in Table 3. The result of this can be presented in the form shown in Table 4. Using the above algorithm for simulating the reduction of the fineness of mineral particles, modifications of the density function of the distribution of fineness classes were obtained, in particular, for the results of flotation experiments conducted at the second stage of research at various degrees of grinding of the feed γie . The quantitative assessment of the simulation was carried out by calculating the coefficient of determination, the Cheddock scale was used for the qualitative assessment (Table 5). S sim —the content in the feed of the fineness class −0.071 mm, obtained during modeling; “High” and “Very high” are qualitative estimates of modeling on the Cheddock scale, respectively, at 0.7 < R 2 ≤ 0.9 and 0.9 < R 2 ≤ 0.99.
+0.045
+0.000
+0.071
−0.100 +0.100
−0.160 +0.160
−0.200
0.2189
γisim
0.0988
0.0587
0.0952
0.0693 0.0956
0.0950 0.0974
0.0654
0.3197
γisim
0.1529
0.0807
0.1319
0.1077 0.1104
0.1657 0.0950
0.0973
0.3773
γisim
0.1702
0.1041
0.1393
0.1307 0.1075
0.1809 0.0865
0.0906
0.4736
γisim
0.1886
0.1265
0.1396
0.1561 0.0942
0.1663 0.0634
0.0517
0.5603
0.6458
γie
γisim
0.1907
0.1541
0.1107
0.1568 0.0400
0.1062 0.0118
0.0180
The grinding time is 37 min. S = 0.7144. S sim = 0.8366. Very high
0.4756
γie
The grinding time is 29 min. S = 0.6021. S sim = 0.6622. Very high
0.3934
γie
The grinding time is 22 min. S = 0.4975. S sim = 0.5475. Very high
0.3461
γie
The grinding time is 16 min. S = 0.4268. S sim = 0.4726. High
0.2576
γie
The grinding time is 10 min. S = 0.3163. S sim = 0.3177. High
−0.071
−0.045
Fineness classes. mm
0.0009
0.0046
0.0293
0.0238
0.0612
0.0936
0.0758
0.1675
0.0965
0.1818
+0.200
−0.315
0.0103
0.0395
0.0066
0.0602
0.0256
0.0980
0.0943
+0.315
−0.400
0.0010
0.0164
0.0387
0.0095
0.1015
0.1264
+0.400
−0.630
0.0021
0.0140
0.0759
0.0513
+0.630
−1.000
0.0014
0.0205
+1.000
−1.600
0.0001
0.0017
+1.600
−2.000
0.9463
0.9534
0.9116
0.8206
0.7616
R2
Table 5 Results of modification of the density function of the distribution of mineral particle fineness classes, obtained as a result of simulation modeling of the reduction of fineness
1410 R. Nikitin et al.
Creation and Verification of a Simulation Model … 0.075
1411
γf
0.070 0.065 0.060 0.055 0.050 γ-0.71
0.045 0.30
0.40
0.50
0.60
0.70
Fig. 3 Graphs of the experimental dependence of the yield of the froth product γ f on the content of flotation of the fineness class −0.071 mm γ−0.071 in the feed (solid line) and its interpretation by means of an biased exponential distribution (dotted line)
Next, the dependence of the froth product yield on the content of the fineness class −0.071 mm in the feed was considered. It was found that this dependence had the form of a biased exponential distribution γ f = λexp(γ−0.071 + c1 )α1 .
(9)
The distribution parameters (9) λ, c1 , α1 were identified from the results of experiments with different degrees of feed grinding (see Table 1). Graphs of the experimental dependence and its interpretation by means (9) are shown in Fig. 3. To represent the distribution of the froth product by fineness classes, a normalized biased Weibull distribution of the form was used: γ f i = γ f (1 − exp(− p(di + c2 )α2 )).
(10)
The distribution parameters (12) p, c2 , α2 were also identified by processing the results of experiments. Figure 4 shows the results of modeling the distribution of the froth product by fineness classes for two of the five values of the S-factor. The solution of the problem of representation of the distribution of nickel in the size classes of flotation products was performed on the basis of the use of B (beta) distribution. As an argument, it was proposed to use the values of the normalized left 0.07 0.06
γfi
Experiment. S=0,4268 Model. S=0,4726. R2=0,9672
0.05 0.04
Experiment. S=0,7144
0.03
Model. S=0,8366. R2=0,9405
0.02 0.01 0.00
di, mm -0,045 +0,000 -0,071 +0,045 -0,100 +0,071 -0,160 +0,100 -0,200 +0,160 -0,315 +0,200 -0,400 +0,315
Fig. 4 Results of modeling the distribution of the froth product by fineness classes for the content of the fineness class −0.071 mm in the feed in comparison with the results of the experiment
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boundaries of the fineness classes, defined as follows: x1 =
−0 + d N −1 −di−1 + d N −1 −d N −1 + d N −1 = 1; xi = ; xN = = 0. d N −1 d N −1 d N −1
(11)
Further, for each fineness class, the extraction of a useful component into a froth or chamber was determined by finding integrals of the form: xi+1
Ii (x) =
x a−1 (1 − x)b−1 d x, B(a, b)
(12)
xi
where the distribution parameter b = const in the cases of determining the extraction values in both froth b f and chamber (bc ) products was determined empirically, the distribution parameter a was determined by identifying the functional dependencies a f = f f (S) and ac = f c (S). Let εef i be the extraction of nickel into the i-th class of fineness of the froth product obtained in the experiment; εsim f i —is the extraction of nickel into the i—th class of fineness of the froth product obtained by modeling. Let the subscript c mean the same for the chamber product. Then taking into account (12). e sim e εsim f i = (Ii (x) − I(i+1) (x)) · ϕ f (ε f ) and εci = (Ii (x) − I(i+1) (x)) · ϕc (εc ), (13)
where ϕ f and ϕc , respectively, are the normalizing functions for extraction into froth and chamber products. Table 6 shows the results of modeling. εef i —is the extraction of nickel obtained in the experiment, εsim f i —is the extraction of nickel obtained during modeling into the fineness classes of the froth product, εcie — is the extraction of nickel obtained in the experiment, εcisim —is the extraction of nickel obtained during modeling into the fineness classes of the chamber product. Finally, Table 7 shows the integral values of technological indicators of inter-cycle flotation obtained experimentally and during simulation modeling. “Exp.”—the results of the experiment. “Mod.”—results of modeling of technological indicators. “ ” is the absolute difference between the experimental results and the modeling results. γ f , β f , ε f —output, nickel content and nickel extractionfroth product of inter-cycle flotation, γc , βc , εc —output, nickel content and nickel extraction—chamber product of inter-cycle flotation. The considered algorithm can be used to predict the results of inter-cycle flotation of copper-nickel ores, as well as for its implementation in the form of a software application.
+0.045
+0.000
+0.071
−0.100
0.0347
0.0658
0.2203
0.2278
0.0591
0.0404
0.0156
0.0201
S sim
0.0940
0.0611
0.0197
0.0215
= 0.3177
+0.100
−0.160
0.0471
0.0728
0.2667
0.2755
0.0616
0.0668
0.0193
0.0216
0.0890
0.1052
0.0207
0.0245
0.0626
0.0719
0.2940
0.2840
0.0591
0.0808
0.0201
0.0271
0.0815
0.1067
0.0199
0.0271
εef i
0.3130
0.0450
0.0333
0.0216
The grinding time is 29 min. S = 0.6021. S sim = 0.6622
0.0315
0.2887
εsim fi e εci sim εci
0.0406
0.2262
εef i
The grinding time is 22 min. S = 0.4975. S sim = 0.5475
0.0286
0.2413
εsim fi e εci sim εci
0.0321
0.2082
εef i
The grinding time is 16 min. S = 0.4268. S sim = 0.4726
0.0208
0.1466
εsim fi e εci sim εci
0.0224
0.1488
εef i
The grinding time is 10 min. S = 0.3163.
−0.071
−0.045
Fineness classes. mm
0.0010
0.0571
0.0355 0.0034
0.0628
0.0058
0.0586
0.0059
0.0028
0.0719
0.0410 0.0065
0.1216
0.0077
0.0050
0.1020
0.1431
0.0122
0.0077
+0.200
−0.315
0.0661
0.0068
0.0102
0.0488
0.0453
0.0080
0.0095
+0.160
−0.200
0.0000
0.0192
0.0042
0.0009
0.0000
0.0275
0.0183
0.0015
0.0000
0.0509
0.0740
0.0039
0.0007
+0.315
−0.400
0.0000
0.0165
0.0000
0.0003
0.0000
0.0283
0.0068
0.0007
0.0000
0.0780
0.1074
0.0032
0.0000
+0.400
−0.630
0.0000
0.0022
0.0000
0.0000
0.0000
0.0057
0.0000
0.0000
0.0000
0.0384
0.0430
0.0004
0.0000
+0.630
−1.000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0001
0.0000
0.0000
0.0000
0.0048
0.0000
0.0000
0.0000
+1.000
−1.600
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
+1.600
−2.000
(continued)
0.9679
0.9684
0.9076
0.9264
0.9692
0.8689
0.9961
R2
Table 6 Results of modeling the values of nickel extraction in the fineness classes of froth and chamber products in comparison with the results of experiments of the second stage of research
Creation and Verification of a Simulation Model … 1413
0.0719
0.0674
0.2727
0.2842
0.0346
+0.045
0.3626
+0.000
0.0529
0.0901
0.0205
+0.071
−0.100
0.0680
0.0998
0.0179
+0.100
−0.160
0.0372
0.0763
0.0562
0.4769
0.2918
0.2623
εsim fi e εci sim εci
0.0406
0.3984
εef i
0.0413
0.0846
0.0195
0.0238
0.0477
0.0597
0.0143
0.0099
The grinding time is 37 min. S = 0.7144. S sim = 0.8366
e εci sim εci
εsim fi
−0.071
−0.045
Fineness classes. mm
Table 6 (continued)
0.0166
0.0104
0.0028
0.0011
0.0271
0.0330
0.0045
+0.160
−0.200
0.0196
0.0033
0.0017
0.0000
0.0385
0.0154
0.0036
+0.200
−0.315
0.0040
0.0000
0.0000
0.0000
0.0106
0.0000
0.0004
+0.315
−0.400
0.0000
0.0000
0.0000
0.0000
0.0070
0.0000
0.0001
+0.400
−0.630
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
+0.630
−1.000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
+1.000
−1.600
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
+1.600
−2.000
0.9528
0.9557
0.9518
R2
1414 R. Nikitin et al.
0.050
0.023
0.231
0.951
0.004
0.769
γf
βf
εf
γc
βc
εc
Exp.
0.770
0.004
0.952
0.230
0.024
0.048
Mod.
S= 0.3163 S sim = 0.3177
0.000
0.000
0.001
0.000
0.001
0.001
0.699
0.004
0.949
0.301
0.030
0.052
Exp.
0.673
0.004
0.945
0.327
0.030
0.055
Mod.
S= 0.4268 S sim = 0.4726
0.025
0.000
0.003
0.025
0.000
0.003
0.670
0.004
0.945
0.330
0.030
0.055
Exp.
0.627
0.003
0.941
0.373
0.032
0.059
Mod.
S= 0.4975 S sim = 0.5475
0.043
0.000
0.004
0.043
0.002
0.004
0.583
0.003
0.939
0.417
0.034
0.061
Exp.
0.556
0.003
0.932
0.444
0.033
0.068
Mod.
S= 0.6021 S sim = 0.6622
0.027
0.000
0.007
0.027
0.001
0.007
0.526
0.003
0.925
0.474
0.032
0.075
Exp.
0.448
0.002
0.912
0.552
0.032
0.088
Mod.
S= 0.7144 S sim = 0.8366
Table 7 Integral values of technological indicators of inter-cycle flotation obtained experimentally and during simulation modeling
0.079
0.000
0.013
0.079
0.000
0.013
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References 1. Chanturia VA, Kozlov AP (2017) Modern problems of complex processing of refractory ores and technogenic raw materials. In: Proceedings of the scientific conference “Modern problems of complex processing of refractory ores and technogenic raw materials.“ Plaksin Readings 2017, Krasnoyarsk, pp 3–6 2. Gavin M (2010) Mudd Global trends and environmental issues in nickel mining: sulfides versus laterites. Ore Geol Rev 38(1–2):9–26 3. Chernousenko EV, Neradovsky YN, Kameneva YS, Vishnyakova IN, Mitrofanova GV (2018) Ways to increase the efficiency of flotation enrichment of difficult-to-enrich sulfide coppernickel ores. Phys Tech Prob Miner Dev 6:173–179 4. Kirjavainen V, Heiskanen K (2007) Some factors that affect beneficiation of sulphide nickelcopper ores. Miner Eng 20(7):629–633 5. Bruckard WJ, Sparrow GJ, Woodcock JT (2011) A review of the effects of the grinding environment on the flotation of copper sulphides. Int J Miner Proc 100(1–2):1–13 6. Bulatovic SM (2007) 12-flotation of copper sulfide ores. In: Handbook of flotation reagents. chemistry, theory and practice flotation of sulfide ores, pp 235–293 7. Alouani A, Arbaoui A,et al (2017) Optimization of flotation reagents’ specific consumption by modeling during mineral enrichment. Glob J Res Eng XVII(V):10–21 8. Niedoba T, Surowiak A, Pi˛eta P (2017) A multidimensional analysis and modelling of flotation process for selected polish lithological copper ore types. In: Mineral engineering conference 2018. 9. Oluwabunmi K, Adeleke A et al (2014) 2k factorial experiments on factors that influence the recovery of gold during the upgrade of ilesha-itagunmodi gold ore through froth flotation. J Miner Mater Charact Eng 2:32–39 10. Subasinghe GKNS, Schaap W, Kelly EG (1990) Modelling screening as a conjugate rate process. Int J Miner Process 28(3–4):289–300 11. Aleksandrova TN, Nikolaeva NV, Lvov VV, Romashev AO (2019) Ore processing efficiency improvements for precious metals based on process simulations. Obogashchenie Rud 2:8–13 12. Ksenofontov BS, Titov KV (2015) Simulation modeling and operator method of analysis of flotation water purification processes. In: Ecology of industrial production, vol 4. STC OK “Compass”, Moscow, pp 35–39 13. Opalev A, Birukov V, Nikitin R (2020) Mathematical modeling of ferromagnetic particle aggregation in iron ore processing technologies. SGEM 1(1):813–820 14. Lukichev SV, Nikitin RM, Birukov VV, Oleinik AG (2020) Simulation modeling concept of disintegration of minerals based on gauss - laplace and B (beta) distributions. SGEM 1(1):847– 854
Technological Control of the Granulometric Composition of Active Materials of Chemical Current Sources Dmitry Fugarov
Abstract Within the framework of this paper, a methodology for non-destructive acoustic spectral-timbre computer technological control of composite materials is proposed, which provides tracking and registration of the diagnosed quality parameters and detection of defects according to standard parameters. The completeness of the diagnosis, high accuracy and self-testing of the measuring system is achieved by using mathematical software with the preservation of all hardware modules. Keywords Mathematical model · Transport infrastructure · Non-destructive testing · Registration · Defect detection · Diagnostics
1 Introduction Modern technological production of goodss made of powders, charges, other dispersed and composite materials requires the creation of a complex of automatic continuous control. Positive electrodes of chemical current sources are composite products that are thin tapes, plates or disks, the main carrier of which is a current collector in the form of a grid, a perforated tape or plate, a porous powder or fiber matrix. The active mass is pressed, rolled or otherwise applied to the current collector from one or two sides [1]. The active mass is usually a three-component mixture of the powder of the active material, a conductive additive and a binder. The latter plays the role of a hardener of the porous mass, gives it elasticity, increases the strength of adhesion to the current collector. High requirements for the electrical and mechanical characteristics of the electrodes lead to the need to control the homogeneous active mass, its density, identify various defects, cracks, peeling from the current collector, etc.
D. Fugarov (B) Don State Technical University, Ploshchad Gagarina, 1, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_145
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D. Fugarov
2 Problem Statement Ensuring the specified quality characteristics of the electrodes requires monitoring the granulometric composition of the active mass. The existing methods of controlling the granulometric composition of powders and granules of active masses are characterized by high time costs and labor intensity. They do not allow creating a system of rapid and continuous measurement and tracking in real time. The separation of powders into fractions is usually carried out by sifting them through a sieve system. The obtained result often does not correspond to the actual dispersed composition of active mass powders. The acoustic spectral-timbre method allows to largely solve the problem of fine-tuning the active mass to the required dispersion with continuous monitoring [2]. The essence of the control of the dispersion of the active mass is as follows. The active mass in the form of powder or granules is introduced into the closed circuit of the measuring and technological system. With the help of a fan, the air-dispersed mass moves along the measuring circuit and in the process of turbulent movement through the pipeline is intensively mixed and crushed due to the collision of particles with each other, the walls of the pipeline, while acoustic emission is generated, the parameters of which are recorded by piezo ceramic converters (sensors) with corresponding resonant frequencies and amplitude-frequency characteristics (AFC) [3]. The current information is collected in the form of a sequence of short exponential pulses of acoustic emission, which are received at the inputs of the spectrum analyzing equipment. The input signals are filtered and normalized by frequencies, amplitudes and phases. The result of measuring the mass dispersion is influenced by many physical parameters of the powder: 1. the nominal level characterizing the amplitudes of the main and timbre harmonics; 2. the frequencies of these harmonics; 3. the dispersion; 4. the mass of the powder introduced into the proposed model of a closed measuring technological system. The acoustic spectral-timbre method allows to solve to a large extent the problems of automation of control, its extension to most operations of the technological process, analysis of the physical and chemical properties of composite materials [4].
3 Theoretical Part The generalized model of composite systems can be represented as a region of Euclidean space, enclosed by some solid medium of the hardener, into which material particles t1, t2, … tN, are immersed and distributed according to some statistical law, forming an elastic–plastic system with k—degrees of freedom.
Technological Control of the Granulometric Composition of Active …
1419
A combination of external probing impulses, which has a certain time sequence, acts on the material particles ti, imparting to them some part of the energy. This energy, in turn, causes forced vibrations in the elastic—plastic material system, as a result of which a force response of the system arises [5]. This complex motion breaks down due to group interaction into elementary harmonic oscillations arising in the measuring chain from the interaction of particles, generating fields of acoustic emission (AE) signals. The registered information signals are contained in the frequency range from 0 to 60 kHz. The analysis and decryption of the AE signal is performed by a discrete fast Laplace–Fourier transform: U ( p) =
∞
e− pt u(t)dt;
(1)
0
u(t) =
1 2n j
σ1 + j∞ σ1 − j∞
U ( p)e pt dt;
(2)
where, p = σ + jωt = Re( p) + j lm ( p);
(3)
Re (p)—the real part of a complex variable p (t), σ = Re ( p);
(4)
lm (p)—the imaginary part of a complex variable p (t), ωt = lm ( p).
(5)
Each fraction of the composite material generates a signal consisting of pulse sub-spectrals nested in each other [6]. To apply the principle of superposition to the processing of sub-spectrals, their analog frequency characteristics (AFC) must be linearized using weighting coefficients: Cn , Fi = k Bik
(6)
where Cn—the parameters of the mono-fraction of material particles specified in the training experiment; Bik—amplitudes of the sub-spectrum. The weight coefficients are determined independently from each other based on the results of the experiment. Thus, when determining the granulometric composition of the powder of the active material, the parameter Ci—th of dispersed fractions is found by the formula:
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D. Fugarov
k (Bik · Fik ) · β0 Ci = i k (Bik · Fik )
(7)
where β0—is the scale factor. Then the percentage of fractions is defined as ϕi = (Ci/C) · 100%,
(8)
where C = C1 + C2 + . . . + Cn =
N
Ci
(9)
(i=1)
Each sub-spectrum isolated in the full Fourier spectrum corresponds to the content of the kinetic energy introduced by individual mono-fractions of the hardener, and allows to confidently isolate the energy contribution of each dispersion interval from the acoustic power of the analyzed AE signal. The signal generated by acoustic emission is regulated by the sensor in the form of a time sequence of pulses, decomposed by the spectrum analyzer into a spectrum of fundamental and higher harmonics, which are multiples of the fundamental frequency and are significantly distinguished from the noise field [7]. The higher harmonics of the acoustic signal provide a greater resolution of the measuring path. If the first fundamental frequency harmonic of the composite system differs only by from the main harmonic, then the frequency of the sound of the solid phase is f n = fr + .
(10)
The higher harmonics are multiples of the main one and differ by k : , so (fr + ) · k = fr · k + · k,
(11)
where k—is the multiplicity coefficient of the higher harmonics; fr—is the frequency for a plastic or viscous medium. Thus, the higher harmonics of the spectrum carry more complete information about the amplitude-frequency parameters of composite systems and allow to distinguish AE signals by classes of dispersed composition [8]. The interaction of the elements of composite systems under the influence of thirdparty probing impulses is also pulsed, and the mathematical representation of the oscillations is reduced to the problem of approximating the function [9]. Depending on the applied model of the system of complicating functions f1 (t), f2 (t) … fk(t). The registered oscillation u(t) of the AE is approximated more and more accurately as the index k increases. The convergence of the sequence of functions fk(t) and u(t) allows to establish a class of dispersed composition with certain (corresponding) parameters [10].
Technological Control of the Granulometric Composition of Active …
1421
The convergence criterion is more convenient for practical problems:
t2
lim
n→∞
[u(t) − f k (t)] · t = 0,
(12)
t1
since it allows to get more accurate solutions. The accuracy of representing a given oscillation u(t) and finding an approximating function fk(t) is an interpolation problem and the solution can be obtained as a combination of given linearly independent orthogonal functions f (t) = α0 · ϕ0 (t) + α1 · ϕ1 (t) + . . . + αn · ϕn (t).
(13)
Next, the coefficients α0, α1, … αn are determined for which in the limit f (tk) = u(tk).
(14)
In the variant of the trigonometric functions will receive C0 (t), C1 (t), C2 (t) . . . Cn (t), αi ϕi(t) = Ci (t).
(15)
In this case, the studied signal will be decomposed into systems of basic functions u(t) = s(t) =
N i=1
ai · Ci (t).
(16)
The acoustic signal spectra of objects from the composite system can be represented as a series [11]. The construction of a series approximating the Fourier spectrum transformation represents various operations that can be represented only in a finite frequency range [12].
4 Conclusion Technological computer monitoring allows for un optimized control of the parameters of products made of composite materials according to the parameters of testing signals characteristic of a particular product [13]. In continuous technologies, these parameters are tracked in quantitative and qualitative terms, and if they deviate from the normalized ones, a correction is introduced into the technological process. A mathematical model of the interaction of system elements, i.e. between particles and hardeners, formed the basis of the developed algorithm and software for product quality control. An acoustic analog signal using analog-to-digital conversion is formed into a time series file in the form of a real sequence of samples in a 16-bit binary code of a set of number pairs (amplitude-frequency). The results of the generated time series are converted into the source data format for the direct
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f, kHz 2,6 2,5 2,4 2,3 2,2 2,1 micron 37,0
44,0
58,0
73,0
Fig. 1 The dependence of the frequency of the main harmonics of the subspectra on the particle diameter
Fourier transform [14]. The image recognition program for dividing the feature space into classes, depending on the specific industrial technology, provides for the necessary number of classes. For example, to assess the degree of compaction (adhesion) between composite particles and hardeners, two or three classes are sufficient. These are the degrees of permissible and unacceptable compaction (adhesion) [15]. Figure 1 shows the dependence of the frequency of the main harmonics of the subspectra on the particle diameter. Computer technological control of composite materials is non-destructive, provides tracking and registration of the diagnosed quality parameters and detection of defects according to regulatory parameters [16]. The completeness of the diagnosis, high accuracy and self-testing of the measuring system is achieved by using mathematical software with the preservation of all hardware modules [17].
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References 1. Sukhinov AI et al (2020) Accounting method of filling cells for the solution of hydrodynamics problems with a complex geometry of the computational domain. Math Models Comput Simul 12(2):232–245 2. Ganzhur M, et al (2020) Modeling of storage processes using Petri nets. In: E3S web of conferences, vol 175, p 05038 3. Purchina OA, et al (2021) The algorithm development based on the immune search for solving unclear problems to detect the optical flow with minimal cost. In: E3S web of conferences, vol 258, p 06052 4. Agibalov O (2020) On the issue of using intuitionistic fuzzy sets for describing the expediency of solving optimization problems by genetic algorithms with given parameters. In: E3S web of conferences, vol 224, p 01008 5. Chernyshev YO (2015) Swarm-intelligence-based algorithm of connections permutation between pins. J Theor Appl Inf Technol 80(1):466–473 6. Gazizov A, et al (2020) Theoretical aspects of the protection of personal data of employees of the enterprise by the method of pseudonymization. In: E3S web of conferences, vol 210, p 11001 7. Gerasimenko Y et al (2021) Mathematical modeling and synthesis of an electrical equivalent circuit of an electrochemical device. Adv Intell Syst Comput 1259:471–480 8. Fugarov DD, Gerasimenko YY (2018) Methods for revealing hidden failures of automation system for technological processes in oil and gas sector. J Phys Conf Ser 1118:012055 9. Poluyan AY (2018) Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex. J Phys Conf Ser 1015:022013 10. Chernyshev YO (2015) Swarm-intelligence-based algorithm of connections permutation between pins. J Theor Appl Inf Technol 80(1):13–20 11. Onyshko DA, et al (2020) Synchronization system in wireless sensor networks of oil and gas complex. In: E3S web of conferences, vol 164, p 03030 12. Poluyan AY et al (2019) Application of bionic and immune algorithms for the solution of ambiguous problems of transportation routing. J Phys Conf Ser 1333:032057 13. Poluyan AY et al (2019) Solution of task on the minimum cost data flow based on bionic algorithm. J Phys Conf Ser 1333:032056 14. Ventsov NN, et al (2017) In: International conference on industrial engineering, applications and manufacturing, ICIEAM, p 8076476 15. Solomentsev KY et al (2018) Interference elimination in digital controllers of automation systems of oil and gas complex. J Phys Conf Ser 1015:032179 16. Fugarov D (2022) Development and mathematical modeling of the AC sensor for refinery automation systems. Smart Innov Syst Technol 247:271–281 17. Fugarov DD, Gerasimenko EY, Gerasimenko AN (2021) Modeling of electric mass transfer process in controlled electrochemical resistance. J Phys Conf Ser 2131(4):042050
Economic Security: A Critical Approach to Assessing the Effectiveness of the Resource Potential of Business Guzaliya Klychova , Gamlet Ostaev , Alsou Zakirova , Albert Iskhakov , Elena Konina , and Ekaterina Gainutdinova
Abstract Economic security of any economic entity is the key to the successful functioning and development of business. Calculation of indicators reflecting the effectiveness of organizations engaged in big business in terms of economic security is significant for assessing the resource potential, which they need to apply rationally (effectively) in the process of economic activity, including the absolute leading monetary opportunities. The purpose of the article is to form a conceptual approach to the assessment of efficiency and intensification of corporate finance in terms of economic security. In the process of the research, the developed methods for calculating the indicators reflecting the effectiveness of organizations engaged in big business in terms of economic security were tested and the aggregate direct and aggregate indirect indicators of efficiency and intensification of corporate finances were calculated according to them. Using the offered methods in practical activity, the service of economic security of corporation will receive the exact information about efficiency and intensification of finances and, hence, will develop the actions focused on maximization of financial benefit due to concrete resource-saving directions as the primary source of money saving on each kind of activity depending on the current economic conjuncture, which will provide them with stable competitive advantages in the occupied market segments. Keywords Economic security · Evaluation · Corporate efficiency · Profit · Cash flows
G. Klychova (B) · A. Zakirova · A. Iskhakov Kazan State Agrarian University, 65, Karl Marx Street, Kazan 420015, Russia e-mail: [email protected] G. Ostaev · E. Konina · E. Gainutdinova Izhevsk State Agricultural Academy, 11, Studencheskaya Street, Izhevsk 426069, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_146
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1 Introduction Economic security in the assessment of resource potential relies on the diversification of corporate activities, which is a set of operational, investment, financial commercial transactions with the corresponding cash receipts (result) and payments (costs), when comparing them with each other, efficiency indicators are formed, affecting their subsequent change (intensification) [1, 2]. Economic security includes a toolkit—methods for determining performance indicators and intensifying corporate finance of a direct (direct) and indirect (indirect) nature, which do not contradict the interpretations of both categories established in economic science and fully reveal the mechanism for the formation of interacting results (net profit) and costs (payments), performance (direct profitability or direct profitability) and cost (indirect profitability or indirect profitability) of cash flows [3–6]. Economic security is composed of basic social security, defined by access to basic needs infrastructure pertaining to health, education, dwelling, information, and social protection, as well as work-related security [7]. Economic security of big business is multifaceted, since it manifests itself in the synthesis of entrepreneurship and social responsibility of the subjects engaged in it, among which in conditions of the current economic mechanism corporations are absolute leaders in resource potential, including the monetary funds available to them, due to the hypertrophic concentration of their financial investments in various commercial projects that bring them multiplier benefits, while being significant for the population in meeting their needs for vital welfare. These facts testify to the indisputability of the key role of the economic security of corporations in the balanced development of the national economy. And to what extent they will be most useful for the state and its society in many respects depends on efficiency (effectiveness and cost) and intensification (maximization of result and minimization of expenses in dynamics mainly due to qualitative (relative) parameters, reflecting efficiency of activity) of finances. That is why we need a toolkit uniting method of calculation of indicators expressing both categories described above and their objective assessment, which is what the author’s scientific approach is devoted to. Its conceptuality in terms of economic security is based on the traditional interpretation of efficiency and intensification and the specifics of corporations’ activity (diversification of business processes, aimed by them, first of all, at making profit) [8–10]. The conceptual approach is intended to help employees of service of economic security in carrying out an objective estimation of efficiency and expenses of the cash flows directed on financing of activity and revealing of reserves for maximization of financial benefit due to influence of relative (intensive) indicators on change of result and expenses (net profit and cash flows in a part of payments, primary factors of economic efficiency). For its embodiment in a reality it is necessary to define indicators of efficiency and intensification of corporate finances, to analyze them in dynamics on an example of one of domestic corporations and to reveal its weaknesses by means of the offered toolkit [11–13].
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2 Materials and Methods At formation of the conceptual approach to an estimation of efficiency and intensification of corporate finances in a part of economic safety the calculationconstructive method supplemented with elements of the mathematical analysis and logarithmization is applied. Combining them with each other, it is possible to obtain with a high degree of accuracy the necessary parameters and conduct a complete and comprehensive analysis of the interaction between the resulting and factor indicators in the field of financial efficiency and financial intensification at the corporate level. Formation of economic security tools to assess efficiency and ratemaking we will begin with a consideration of the structure of corporate activities. Due to the fact that they operate in the sphere of big business, their activity is inherent in diversification, they carry out operational and other (investment, financial) commercial projects, affecting the aggregate result and aggregate costs. Therefore, when constructing methods for calculating efficiency and intensification indicators, we will include cash flows in terms of payments for operating, investment and financial activities in the composition of costs [14–16]. In turn, the commercial essence of corporations predetermines the result desired by them according to the founding documents—net profit (the main source of financing of activity and re-production of economic processes) [17, 18]. Comparing them, we get direct and indirect dependence of efficiency of corporate finances on the ratio between net profit and cash flows in terms of payments as a whole. According to the above, the general methods of calculation of indicators of aggregate direct efficiency of corporate finances look as follows (formulas (1), (2)): E F c f (cd) =
Pnpi C F psi − C F pli = , C F pli C F pli
(1)
where E F c f (cd) –is the aggregate direct efficiency (aggregate direct profitability index) of corporate finance; Pnpi —aggregate net profit of corporations, rubles; CFpsi —aggregate cash flows of corporations in terms of receipts, rubles; CFpli —aggregate cash flows of corporations in the part of payments, rubles.
E F c f (ck) =
CFpli C F pli = , Pnpi C F psi − C F pli
(2)
where EFcf(sk) is the total indirect efficiency (index of total indirect profitability) of corporate finance; CFpli —aggregate cash flows of corporations in the part of payments, rubles; Pnpi —aggregate net profit of corporations, rubles; CFpsi —aggregate cash flows of corporations in terms of receipts, rubles.
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The dynamics of direct and indirect efficiency indicators (intensity indicators) affect the change in the result and costs, which are indicators of direct and indirect intensification. Hence, the methods of aggregate intensification indicators of corporate finance (in our case, the change in aggregate net profit due to the change in aggregate direct and the change in aggregate cash flows in terms of payments due to the change in aggregate indirect efficiency of corporate finance) take the appropriate structure (formulas (3), (4)): CDIcf = Pnpi =
| | d Ef kf(n)i ∗ F CFpli + C F pli , (3)
| |
ln P Ri[d( Pnpi )] ln P Ai[d( Pnpi )]
where CDIcf —cumulative direct intensification (effect of cumulative direct intensification) of corporate finances, rubles; Pnpi —the intensive change in the aggregate net profit of corporations, rubles; ( Efkf(n)i )—the differentiated share of the reported aggregate direct efficiency of corporate finance; ln | P Ri[d( Pnpi )]| is the log-adjusted change in aggregate net corporate profit due to ln | P Ai[d( Pnpi )]| theimpact of the aggregate direct intensive factor; F( CFpli )—basic aggregate cash flows of corporations in terms of payments, rubles; CFpli —the incremental share of the reporting aggregate cash flows of corporations in terms of payments, rubles.
AIIcf = C P pli(i) =
| |
| | d Ef k f (k)i ∗ F Pnpi + P npi (4)
ln C P Ai [d(C F pli )]
ln C P R i [d(C F pli )]
where AIIcf is the aggregate indirect intensification (effect of aggregate indirect intensification) of corporate finances, rubles; CPpli(i) —the intensive change in the aggregate cash flows of corporations in terms of payments, rubles; ( Efkf(k)i )—the differentiated share of the reported aggregate indirect efficiency of corporate finance; ln |C P Ai [d(C F pli )]| —the logarithmically adjusted change in the aggregate cash ln |C P R i [d(C F pli )]| flows of corporations in terms of payments due to the impact of the aggregate indirect intensive factor; F( Pnpi ) —basic aggregate net profit of corporations, rubles; Pnpi —the incremental share of the reported cumulative net profit of corporations, rubles. The significance of the impact of intensive factor indicators on the total net profit and total cash flows in terms of payments (total direct and total indirect intensification of corporate finance) should be determined by comparing them with identical
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resulting indicators (total change in net profit and total change in cash flows in terms of payments) obtained under the influence of extensive factor indicators (total direct and total indirect extensification of corporate finance), taking into account a similar time interval. Having compared in pairs the effect of total direct and total indirect intensification and extensification for the purposes of economic security, we will get an objective answer about intensive or extensive development of corporate finances in general and on their separate elements (operational, investment, financial types of activity) due to the complexity and consistency of all these methods, comprehensively reflecting the essence and content of the categories «efficiency» and «intensification» and, moreover, formed on the principle of universality of application (without sectoral, organizational, legal and other discrimination), based on the functional cost principle of its construction.
3 Results Let’s test the developed methods of calculation of the indicators reflecting efficiency of the organizations involved in big business in terms of economic security and let’s calculate the aggregate direct and aggregate indirect indicators of efficiency and intensification of corporate finances on the example of Limited Liability Company (LLC) «Agro-Belogorye Group of Companies» (Table 1). Table 1 shows the generalized indicators of the aggregate efficiency of the corporation’s finances for the period under study. According to the dynamics of effectiveness and costs of its activity it is clearly seen that both indicators sharply worsened, and the reason for this situation is obvious—a sharp increase in the index of total indirect profitability (total indirect profitability), which caused a rapid decrease in the index of total direct profitability (total direct profitability) of cash flows. Detailing the identified cause of the deterioration of indicators of aggregate efficiency of corporate finances by type of activity (Table 2), we focus the attention of the corporation’s management on the key negative factor manifested in the negative dynamics of direct profitability of its operating activities, which affected the reduction of net profit, along with the downward dynamics of similar indicators for investment and financial commercial transactions (Table 3). Having compared in pairs the effect of total direct and total indirect intensification and extensification for the purposes of economic security, we will get an objective answer about intensive or extensive development of corporate finances in general and on their separate elements (operational, investment, financial types of activity) due to the complexity and consistency of all these methods, comprehensively reflecting the essence and content of the categories «efficiency» and «intensification» and, moreover, formed on the principle of universality of application (without sectoral, organizational, legal and other discrimination), based on the functional cost principle of its construction.
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Table 1 Generalized performance indicators of corporate finances of LLC «Agro-Belogorye Group of Companies» Indicators
Baseline year (2015) Reporting year (2019)
Revenue from sales, thousand rubles
387,588
351,347
Aggregate fixed costs of sales, thousand rubles
64,972
100,353
Aggregate variable costs of sales, thousand rubles
256,877
323,734
Aggregate total costs of sales, thousand rubles
321,849
424,087
Total profit (total loss) from sales, thousand rubles
65,739
−72,740
Aggregate other income (together with interest receivable), thousand rubles
8,583,595
5,651,072
Aggregate other expenses (together with interest 229,118 receivable), thousand rubles
5,493,544
Total profit before taxation, thousand rubles
8,420,216
84,788
Incometax, thousand rubles
167,926
64,414
Deferred income tax, thousand rubles
–
133
Change in deferred tax assets, thousand rubles
425
–
Other income, other than other income, thousand 34 rubles
–
Total net profit, thousand rubles
8,252,749
20,507
Aggregate cash flows in terms of payments, thousand rubles
9,182,517
7,525,586
Aggregate direct efficiency of corporate finances 0,9
0,03
Aggregate indirect efficiency of corporate finances
33,33
1,11
Table 2 Detailed efficiency indicators of corporate finances of LLC «Agro-Belogorye Group of Companies» Indicators
Baseline year (2015)
Reporting year (2019)
Changes Absolute, +, –
Relative %
Aggregate net profit, thousand rubles
8,252,749
20,507
−8,232,242
−97,52
Cash flows in terms of payments from operating activities, thousand rubles
1,946,268
5,040,404
3,094,136
158,98
(continued)
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Table 2 (continued) Indicators
Reporting year (2019)
Changes Absolute, +, –
Relative %
16,366
−223,090
−93,17
Cash flows in part of 6,996,793 payments on financial activities, thousand rubles
2,468,816
−4,527,977
−64,72
Aggregate cash flows 9,182,517 in terms of payments, thousand rubles
7,525,586
−1,656,931
−18,03
Direct efficiency of 4,17 cash flows in terms of payments from operating activities
0,01
−4,16
−99,76
Direct efficiency of 33,33 cash flows in terms of payments for investment activities
12,5
−20,83
−62,5
Direct efficiency of 1,18 cash flows in terms of payments from financial activities
0,01
−1,17
−99,15
Aggregate direct efficiency of cash flows in terms of payments
0,01
−8,32
−99,88
Indirect efficiency of 0,24 cash flows in terms of payments from operating activities
245,79
245,55
102,312,5
Indirect efficiency of cash flows due to payments in investment activities
0,03
0,8
0,77
2566,67
Indirect efficiency of cash flows as part of payments for financial activities
0,85
120,39
119,54
14,063,53
Aggregate indirect efficiency of cash flows relating to payments
1,12
366,9
365,78
32,658,93
Cash flows in terms of payments on investment activities, thousand rubles
Baseline year (2015) 239,456
8,33
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Table 3 Detailed indicators of direct intensification and direct extensification of corporate finances of LLC «Agro-Belogorye Group of Companies» Indicators
Changes Baseline, + , – Relative, %
Intensive change in the corporation’s net profit due to the logarithmic parameter-adjusted change in the direct efficiency of corporate finance in operating activities, thousand rubles
−7,199,067
−87,23
Intensive change in the corporation’s net profit due to the log-adjusted parameter of the change in the direct efficiency of corporate finance in investment activities, thousand rubles
−54,218
−0,66
Intensive change in the corporation’s net profit due to the log-adjusted parameter of the change in the direct efficiency of corporate finance in financial activities, thousand rubles
−936,661
−11,35
Intensive change in the corporation’s total net profit due to the change in the total direct efficiency of corporate finance adjusted for the logarithmic parameter, thousand rubles
−8,189,946
−99,24
Extensive change in the corporation’s net profit due to the log-adjusted change in cash flows in terms of payments for operating activities, thousand rubles
4,469,188
54,15
Extensive change in the corporation’s net profit due to the change −2,575,225 in cash flows in terms of payments for investment activities adjusted for the logarithmic parameter, thousand rubles
−30,59
Extensive change in the corporation’s net profit due to the change −1,851,667 in cash flows adjusted for the logarithmic parameter in terms of payments for financial activities, thousand rubles
−21,84
Extensive change in the corporation’s aggregate net profit due to the change in aggregate cash flows in terms of payments adjusted for the logarithmic parameter, thousand rubles
1,72
42,296
Change in the aggregate net profit of the corporation due to the −8,232,242 logarithmic-adjusted change in the aggregate direct efficiency of corporate finances (impact of the aggregate direct intensive factor) and due to the logarithmic-adjusted change in the aggregate cash flows in terms of payments (impact of the aggregate extensive cost factor), thousand rubles
−97,52
4 Discussion Under the conditions of the economic crisis caused by the coronavirus pandemic, falling real incomes, rising unemployment, the issues of food security, as an important component of ensuring the country’s economic security, are becoming increasingly important [19–21]. Even before the outbreak of COVID-19, food security was considered a serious problem that worried the entire world community. One of the most important challenges that remain relevant today is the sustainable and stable solution of food problems and a significant increase in the availability of food in the long term. The world food system must meet the following basic requirements:
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1. All actors of the food system, including peasant farmers, women and youth, must be provided with financial, insurance, transportation, education and other services; 2. It is necessary to reduce the negative impact on the environment, conserve natural resources, especially non-renewable resources, and increase resilience to changes in the natural and socio-economic environment; 3. Produce enough food. At the same time, household waste and post-harvest losses should be reduced; 4. Ensure the consumption of nutritious, healthy and safe food [22–24]. 5. Food security is based on four key components (Fig. 1). Important factors contributing to the continuous provision of food security include strong capacity and self-development of national economies. Optimization of interaction between international organizations, and identification of effective mechanisms and ways of using available food resources, can be referred to the priority areas of food security activity. Food security is designed to: – provide reliable protection from internal and external threats to the basic interests of society, the state and the individual; – to provide full and maximum possible independence of the state from external sources of foodstuffs; – to maintain the state food reserve at a standard level; – ensure that the quality of foodstuffs is maintained at a level that meets safety and quality standards; – to provide the necessary living wage, a decent level and high quality of healthy life; – contributes to the creation of an effective system of management of the national economy of the country;
domestic needs, demand and trade turnover for certain types of food
total income, unemployment, economic growth, and poverty rates
realities
accessibility
consumption
stability
health, level of education
Fig. 1 Components of food security
the physical and economic accessibility of appropriate food
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expands the production of competitive export-oriented food products; develops the material and technical base of the agro-industrial complex; uses the achievements of scientific and technological progress in agriculture; exercises state control over the food market (controls production activities, external and internal supplies and stocks of food).
To solve the problems of food security it is necessary to develop measures aimed at state regulation of the agro-industrial complex. First of all, the system of economic interaction in the production, procurement, processing, storage and sale of agricultural products should be improved. Particular attention should be paid to market and state regulation of prices for agricultural products, their optimal combination in order to increase the solvency of the population and strengthen the competitiveness of domestic food products in domestic and foreign markets. In addition, the measures aimed at the state regulation of food security should include issues related to the taxation of agricultural producers, with the import and export of food products, with the introduction of advanced technologies, increasing the investment attractiveness of the agroindustrial complex [25]. By introducing certain tax incentives, agricultural enterprises will be given the opportunity to re-equip their material and technical base, form a logistical system and, consequently, increase their investment attractiveness.
5 Conclusions The formed critical approach to assessing the effectiveness of the resource potential of business in terms of economic security is appropriate because of the complete correlation of their resultant and factor indicators. It will provide corporations with opportunities related to the regulation of performance and cost, and, thereby, the result and costs, which indicates the complementarity of the methods built in accordance with it, using which corporations will be able not only to determine intensive cost indicators, but to compare the degree of influence their increment (positive or negative change) with the degree of influence of the increment of extensive indicators on the movement of results and costs for the time interval chosen for analysis and to know your strengths and weaknesses in the field of finance. The critical approach of an estimation of efficiency of resource potential of the business, based on toolkit on calculation of indicators of efficiency and intensification of the finances at corporate level, differs universality and is applicable in all economic subjects (the organizations with corporate status) complying to it on the standard criteria. Adhering to it, the service of economic security of corporation will receive the exact information on efficiency and intensification of finances and, hence, will develop the actions focused on maximization of financial benefit at the expense of concrete resource-saving directions as the primary source of money saving on each kind of activity depending on current economic conjuncture that will provide them stable competitive advantages in the occupied market segments.
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19. Rahman MT, Akter S, Rana MR et al (2022) How COVID-19 pandemic is affecting achieved food security in Bangladesh: a perspective with required policy interventions. J Agric Food Res 7:100258. https://doi.org/10.1016/j.jafr.2021.100258 20. Ouoba Y, Sawadogo N (2022) Food security, poverty and household resilience to COVID-19 in Burkina Faso: evidence from urban small traders’ households. World Dev Perspect 25:100387. https://doi.org/10.1016/j.wdp.2021.100387 21. Béné C, Bakker D, Chavarro MJ et al (2021) Global assessment of the impacts of COVID-19 on food security. Glob Food Secur 31:100575. https://doi.org/10.1016/j.gfs.2021.100575 22. Rohr V, Blakley J, Loring P (2021) A framework to assess food security in regional strategic environmental as-sessment. Environ Impact Assess Rev 91:106674. https://doi.org/10.1016/j. eiar.2021.106674 23. De Raymond AB, Alpha A, Ben-Ari T et al (2021) Systemic risk and food security: emerging trends and future avenues for research. Glob Food Secur 29:100547. https://doi.org/10.1016/j. gfs.2021.100547 24. Brouwer ID, McDermott J, Ruben R (2020) Food systems everywhere: improving relevance in practice. Glob Food Secur 26:100398. https://doi.org/10.1016/j.gfs.2020.100398 25. Coomes OT, Barham BL, MacDonald GK et al (2019) Leveraging total factor productivity growth for sustainable and resilient farming. Nat Sustain 2:22–28. https://doi.org/10.1038/s41 893-018-0200-3
Spectral Response Characteristic of Local Earthquakes According to Instrumentation Readings of the Engineering-Seismometrical Service Vladimir Lapin , Nurakhmet Makish , Kamadiyar Kassenov , Zhassulan Omarov , and Dauren Kassenov Abstract In 2019, the Engineering and Seismometric Service Stations of Kazakh Scientific Research and Design Institute of Civil Engineering and Architecture JSC registered 3 Local Earthquakes with foci in Almaty city and adjacent areas of Almaty region. In September 2019, there were two earthquakes with foci near Almaty city. Earthquake accelerogram recorded in the substructure and upstairs of an 11-storey building with a steel frame, as well as on the 10th and 16th floors in a 17-storey building with a stiffening core were obtained on September 02, 2019, September 07, 2019. The buildings are located near tectonic faults. Spectral curves describing the frequency content of the seismic impact are constructed. It is established that the frequency behavior of the footing, composed of soils of the 2nd category in terms of seismic properties, are high-frequency with prevailing periods of 0.06–0.13 s. Resonance phenomena for flexible buildings were not observed in the local earthquakes indicated. Instrumental records are included in the database of accelerograms of Kazakh Scientific Research and Design Institute of Civil Engineering and Architecture JSC. The results of the work can be used in the calculation and design of buildings and structures in Almaty city. Keywords Accelerograms · Transport infrastructure · Seismic station · Earthquakes · Seismic impact · Buildings
1 Introduction The entire territory of Almaty region is exposed to strong earthquakes, which can pose a danger to buildings and structures on the territory of Almaty city. V. Lapin (B) · N. Makish · Z. Omarov · D. Kassenov Kazakh Research and Design Institute of Construction and Architecture JSC (JSC KazRDICA), 21 Solodovnikova, 050043 Almaty City, Kazakhstan e-mail: [email protected] K. Kassenov Satpayev University, 22a Satbayev Street, 050013 Almaty City, Kazakhstan © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_147
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The seismic hazard of Almaty city is usually associated with the seismogenic zones of the Jungar-North Tien-Shan region. The areas of the Zailiy and KungeyAlatau ridges, as well as the eastern part of the Kirgiz Ridge, are particularly highly seismic. Strong earthquakes with foci in these zones and magnitudes from 7.5 to 8.5, respectively, are possible, and the earthquake intensity in the city can reach from 8 to 10° [1–9]. Almaty city was twice destroyed by the strongest earthquakes—Vernen in 1887 with a magnitude of 7.2 and Keminskiy in 1911 with a magnitude of 8.2. The city has repeatedly experienced less strong earthquakes. The Zhalanash-Tyup earthquake of 1978 with a magnitude of 6.9 and the Suusamyr earthquake of 1992 with a magnitude of 7.3 can be marked. They were felt with an intensity of 5–6° [1] in different parts of the city. In the last 15 years, the occurrence of earthquake foci has been marked on the territory of the city, the seismic effect of which has so far been marked in the range of 2–4°. Since the beginning of 2018, about 15 earthquakes have occurred both with foci in the city and around [9]. However, in 2019, sensible local earthquakes occurred much less frequently. In 2020, there were no sensible earthquakes in the city. In Almaty city, there are 10 Engineering and Seismometric Stations on buildings, which also recorded earthquakes with foci in the city. The stations are equipped with digital and analog systems. The stations are supposed to be re-equipped with new digital measuring systems [10–14]. The network of the Engineering and Seismometrical Service Stations accomplishes two important tasks. Firstly, instrumental monitoring of the buildings state is performed. Secondly, earthquake-prone areas monitoring is carried out. One of the challenging tasks is to evaluate the parameters of the soil vibration of the footing of buildings and structures or foundation and basement structures. On the territory of Almaty city, there are numerous tectonic faults, the influence of which on the parameters of soil vibrations of the footing or foundation structures is poorly studied. The task of determining the spectral response characteristics of the vibration of the buildings footing using instrumentation records of even weak earthquakes recorded on the territory of the city, as well as assessing the influence of tectonic faults on the reaction of the building, is accomplished.
2 Method and Subject of Research According to the operational data of the Geophysical Research Institute Data Center on September 02, 2019, at 15:06 a.m. Nur-Sultan city time (at 09:06 a.m. GMT), an earthquake occurred 4 km northeast of Almaty city. Epicenter coordinates: 43.28° north latitude, 76.94° east longitude. Magnitude mpv = 3.4. Energy class K = 8.5. Depth h = 7 km. The earthquake was felt in Almaty city with an intensity of 2–3°.
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Another earthquake was registered on September 07, 2019 at 06:30 Astana time (00:30 GMT), an earthquake occurred 28 km south of Almaty city on the territory of Kazakhstan. Epicenter coordinates: 42.97° north latitude, 76.91° east longitude. Magnitude mb = 3.8. Energy class K = 8.0. The earthquake was felt in Almaty city with an intensity of 3°. Prospekt Abaya Station № 11 is located on an 11-storey administrative building, made in a metal frame. It should be noted that this station is one of the very first in Almaty city—it commissioned in 1970. In 2010, the first station upgrade took place—a digital instrument and measurement system was installed. The second upgrade was carried out in 2016—the ADXL accelerometers were replaced with the AT 1105. Soils - boulder-gravels. The building has a plan size of 15 × 36 m, height of 43.6 m. From a structural point of view, the building is frame-panel. Exterior wall panels made of aluminum with glass and stemalite infilling. The frame consists of longitudinal and transverse closed frames with a transverse and longitudinal column pitch of 6 m. The height of the basement is—3.4 m, the first floor is—4.2 m and all subsequent 3.6 m. Concrete strip foundations. The basement walls are made of cast concrete. The columns of the frame are anchored to the basement walls with metal shoes. The floors above the first and basement floors are made of monolithic reinforced concrete; the floors above the other floors are made of precast reinforced concrete ribbed plates measuring 3 × 6 m. Partitions are made of precast haydite concrete panels, as well as from precast gypsum-concrete and slag concrete plates. At the top of the building there is an engineering storey (12th floor), where measurement and control equipment part is located - the upper registration point (at the elevation of 40.2 m). The lower registration point is located in the basement. The devices are located at the elevation of −4.4 m (the basement itself—is at − 3.4 m). Previously, instrumentation records (accelerograms) were obtained on this building in the earthquake of August 9, 2017 in China (Xinjiang Uygur Autonomous Region).
3 Results Tables 1 and 2 show the results of processing instrumentation records during the earthquakes of September 02, 2019 and September 09, 2019. Table 3 with data on the processing of instrumentation records for Novaya Plochshad Station №17 of the earthquake September 02, 2019, installed on a 16-storey building with a stiffening core [7, 8].
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Table 1 Maximum values of acceleration level and parameters of accelerograms during an earthquake dated September 02, 2019, station № 11 Component
Acceleration, cm/c2
Effective duration, s
Spectral ratio
Maximum period of the spectrum, s
02.09.19–11-frag-u1, OX roof coating
2.351
0.179
3.132
0.09
02.09.19–11-frag –u2, OY roof coating
0.916
3.354
5.074
0.08
02.09.19–11-frag –u3, OZ roof coating
7.011
0.499
3.376
0.16(0.09)
02.09.19-frag-u6, OX basement
2.562
0.128
3.528
0.07
02.09.19–11-frag -u7, OY basement
1.233
2.842
5.737
0.08
02.09.19–11-frag -u8, OZ basement
4.277
0.122
3.570
0.08
Table 2 Maximum values of acceleration level and parameters of accelerograms during an earthquake dated September 07, 2019, Station № 11 Component
Acceleration, cm/c2
Effective duration, s Spectral ratio
Maximum period of the spectrum, s
07.09.19–11-u1, OX roof coating
0.834
6.413
4.935
0.13
07.09.19–11-u2, OY roof coating
0.580
2.854
4.494
0.15
07.09.19–11-u3, OZ roof coating
2.209
1.133
4.43
0.15
07.09.19-u6, OX basement
1.222
0.205
3.364
0.13
07.09.19–11-u7, OY basement
0.998
0.826
3.486
0.13
07.09.19–11-u8, OZ basement
0.457
38.554
3.294
0.06
The spectral curves of the instrumentation records were calculated using the packages of computer mathematics systems Mathcad and MATLAB. Figure 1, 2, 3 and 4 shows the spectral curves of the earthquake in the upper and lower levels of registration. The nature of the spectral curves shows that there are no resonant vibrations for an 11-storey building with a steel frame. Seismic impacts are impulsive. The impact spectra are quite narrow. Here, the acceleration at the basement level in the horizontal plane is 0.457– 2.562 cm/c2 .
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Table 3 Maximum values of acceleration level and parameters of accelerograms during an earthquake dated September 02, 2019, station № 17 Component
Acceleration, cm/c2
Effective duration, s Spectral ratio
Maximum period of the spectrum, s
02.09.19–6-5-u1, 16th OX floor
3.646
0.512
5.344
0.10
02.09.19–6-5-u2, 16th OY floor
7.59
0.80
7.036
0.10
02.09.19–6-5-u3, 16th OZ floor
16.044
0.73
5.400
0.10
02.09.19–6-5-u7, 10th OX floor
2.624
27.94
3.508
0.13
02.09.19–6-5-u8, 10th OY floor
2.765
3.596
0.08
2.899
Seismic event 02.09.2019
Fig. 1 Spectral curves in the roof coating level during the earthquake dated September 02, 2019 (Station 11)
6 curve along the OX axis
5.5
curve along the O Y axis curve along the O Z axis
5
beta coefficient
4.5 4 3.5 3 2.5 2 1.5 1 0.5 0
0.1
0.2
0.3
0.4
0.5 0.6 period, s
0.7
0.8
0.9
1
Seismic event 02.09.2019
Fig. 2 Spectral curves in the basement level during the earthquake dated September 02, 2019 (Station 11)
6 curve along the OX axi s curve along the O Y axis
5.5
curve along the O Z axis
5
beta coefficient
4.5 4 3.5 3 2.5 2 1.5 1 0.5 0
0.1
0.2
0.3
0.4
0.5
0.6
period, s
0.7
0.8
0.9
1
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Fig. 3 Spectral curves in the roof coating level during the earthquake dated September 07, 2019 (Station 11)
5
curve along the OX axis curve along the O Y axis curve along the O Z axis
4.5
beta coefficient
4 3.5 3 2.5 2 1.5 1 0.5 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
period, s
Fig. 4 Spectral curves in the basement level during the earthquake dated September 07, 2019 (Station 11)
Therefore, the earthquake intensity on September 02, 2019, September 07, 2019 is not higher than 3° in the area of the Prospekt Abaya Seismostation № 11 and Novaya Plochshad Seismostation № 17. The effective accelerogram durations vary widely here. Maximum periods of the spectrum at the basement level in the horizontal plane are 0.06–0.13 s.
4 The Discussion of the Results In Figs. 5, 6 and 7, the spectral curves at the basement level for a pair of earthquakes are grouped along the axes. We emphasize that the soil conditions are the same boulder-gravel. It should be noted that all the reaction spectra, as a rule, have one peak. The exception is the accelerograms recorded along the vertical axis.
Spectral Response Characteristic of Local Earthquakes … Fig. 5 Spectral curves at the basement level along the OX axis (Station 11)
Fig. 6 Spectral curves at the basement level along the OY axis (Station 11)
Fig. 7 Spectral curves in the basement level along the OZ axis (Station 11)
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Due to the unavailability of instrumentation records in the basement level at station № 17, it is not possible to analyze the spectral characteristics of the impact at the basement level. However, the values of the maximum spectrum are quite close to the similar values obtained at station № 11 (Tables 1 and 2). The obtained prevailing periods of soil vibration can be used in the calculation and design of buildings and structures on soils of the 2nd category for seismic properties (boulder-gravels). The building with the Station № 11 is removed from the tectonic faults on both sides, approximately 500–800 m. The building with the Station № 17 is located at a distance of 100 m from the tectonic fault. Attention is drawn to the high acceleration value of 16.04 cm/c2 on the 16th floor of the building in the vertical direction (Table 3), which is noticeably higher than the acceleration values in the horizontal plane on the same floor. This phenomenon may be associated with the active operation of a nearby tectonic fault. Instrumental observations on these buildings should be continued. It should be noted that resonance phenomena for flexible buildings under the impact of local earthquakes are not observed. Such phenomena were observed under the impact of remote earthquakes with foci in the Xinjiang Uygur Autonomous Region of the Republic of China [6].
5 Conclusion 1. The maximum period of the spectrum at the basement level characterizes the spectral content of the seismic impact. For a flexible building, the prevailing periods of vibration of the footing in the horizontal axes, composed of soils of the II category (boulder-gravel) according to seismic properties, during local earthquakes are quite close and are in the range of 0.06–0.13 s. 2. The main conclusions of the work [9] on the spectral content of local earthquakes are generally confirmed. The number of local earthquakes with foci within Almaty region in 2019-2020 is much less than in 2018. 3. It should be noted that resonance phenomena for flexible buildings under the impact of local earthquakes of such intensity are not observed. Such phenomena occur under the impact of remote earthquakes with foci in the Xinjiang Uygur Autonomous Region of the Republic of China. 4. The influence of a nearby tectonic fault is expressed in a significant increase in the acceleration value in the vertical direction at the level of the 16th floor (seismic station No. 17). 5. The accelerograms given in the article will replenish the database of accelerograms of Kazakh Scientific Research and Design Institute of Civil Engineering and Architecture JSC. 6. It is necessary to continue installing Engineering-Seismometrical Stations on high-rise buildings, buildings with special seismic-insulating foundations [15– 19] and buildings built on sites with difficult soil conditions [20, 21].
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Acknowledgements The research was carried out using the funds of the grant AP 05130702 of the Ministry of Education and Science of the Republic of Kazakhstan.
References 1. Mikhaylova NN, Sokolova IN et al (2015) Earthquakes in the city of Almaty. Bull Natl Nucl Center 3:87–93 2. Mikhailova NN, Uzbekov AN (2018) Tectonic and technogenic earthquakes in central Kazakhstan. News Natl Acad Sci Republic Kazakhstan News Natl Acad Sci Republic Kazakhstan Ser Geol Tech Sci 429:146–155 3. Galperin RM, Nersesov IL, Galperin EI (1985) Seismic regime of Almaty for 1972–1982 years. Science, Moscow 4. Kurskeev KA, Timush AV, et al (2000) Seismic zoning of the Republic of Kazakhstan. Evero, Almaty, p 220 5. Sadykova AB, Silacheva NV, Stepanenko NP (2021) Seismic mikro zoning of the territory of Almaty on a new metodolodgical basis. News Natl Acad Sci Republic Kazakhstan Ser Geol Tech Sci 445:127–134 6. Lapin V, Makish N, Kassenov K, Omarov Zh, Kassenov D (2021) Instrumental records received in 11 storey steel frame building during a remote earthquake. In: E3S web of conference, vol 258 7. Lapin V, Yerzhanov S, Kassenov K, et al (2020) Response of the building with a stiffening core during an earthquake of February 02, 2018 in the territory of a metropolis. In: E3S web of conference, vol 217 8. Lapin VA, Yerzhanov S, Essenberlina D (2020) Dynamics of a 16-storey building with a core of rigidity in a local earthquake. In: IOP conference series: materials science and engineering, vol 953 9. Lapin VA, Yerzhanov SY, Daugavet VP (2018) Features of fluctuations in the foundations of buildings during local earthquakes. Earthq-Resist Constr Saf Struct 6:25–32 10. Deng M et al (2019) A wireless monitoring system for a high-power borehole-ground electromagnetic transmitter. Geosci Instrum Meth Data Syst 8:13–19 11. Zhang X, Zhang Q, Wang M et al (2017) Development of a full-wave form voltage and current recording device for multichannel and current recording device for multichannel transient electromagnetic transmitters. Geosci Instrum Meth Data Syst 6:495–503 12. Yang L, Stehly L, Paul A (2018) Working Group High-resolutional surface wave tomography of the European crust and uppermost mantle from ambient seismic noise. Geophys J Int 214(2):1136–1150 13. Qiao S, Duan H, Zhang Q et al (2018) Development of high-precision distributed wireless microseismic acquisition stations. Geosci Instrum Meth Data Syst 7:253–263 14. Groukamp L, Rossow JJ, Fourie CJS, Cormbrinck L (2011) Foundation requirements for a lunar laser ranger facility at matjiesfontein. Afr J Geol 114(3/4):573–576 15. Bulat AF, Dyrda VI, Lysytsya MI, Grebenyuk SM (2018) Numerical simulation of the stressstrain state of thin-layer rubber-metal vibration absorber elements under nonlinear deformation. Strength Mater 50(3):387–395 16. Ahmad S, Ghani F, Md Raghib A (2009) Seismic friction base isolation performance using demolished waste in masonry housing. Constr Build Mater 23:146–152 17. Dyrda VI, Kobets A, Bulat AF, et al (2020) Present problems of vibration isolation in heavy mining machines at long-term cyclic loads. In: E3S Web of conference, vol 168 18. Lapin V (2020) Comparative analysis of the effect of seismic isolation by means of stations of engineering seismometric service on buildings. In: 16th world conference on seismic isolation, energy dissipation on active vibration conference of structures, pp 325–332
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19. Bulat AF, Dyrda VI, Grebenyuk SN, Klimenko MI (2019) Determination of effective characteristics of the fibrous viscoelastic composite with transversal and isotropic components. Strength Mater 51(2):183–192 20. Yerzhanov S (2020) On some issues of taking account of the interaction of seismically isolating pile foundations with foundation soil under seismic effects. In: 16th world conference on seismic isolation, energy dissipation on active vibration conference of structures, vol 955–963 21. Zhussupbekov AZh, Frankovská J, Stacho J, Al-Mhaidib AI, Doubrovsky M, Uranhayev N, Yerzhanov S, Morev I (2015) Geotechnical and construction considerations of pile foundations in problematical soils. In: 15th Asian regional conference on soil mechanics and geotechnical Engineering, ARC 2015: new innovations and sustainability, pp 2704–2709
Consolidation of Powder Materials During the Production of Products by Hot Isostatic Pressing Vladimir Makarov , Yuri Molev , and Alexey Markov
Abstract The development of powder metallurgy is largely determined by the improvement of the quality of materials. The problems of creating new materials with the specified properties can be successfully solved by the methods of powder metallurgy. Metal powders have unique properties: high hardness, refractoriness, a given porosity. The technique of isostatic pressing for obtaining parts from metal powders has become widely used abroad. The use of isostatic pressing allows you to create blanks with a denser and more uniform structure than when compacting in another way. To obtain a product of specified shapes and sizes with the appropriate structure and properties, the consolidation of powders is used. This can be done using various technological processes: pressing, sintering, rolling, extrusion. This article discusses the main methods of consolidating powder materials in the production of products by hot isostatic pressing. Keywords Transport infrastructure · Powder metallurgy · Hot isostatic pressing · Additive technology · Consolidation
1 Introduction Modern technologies for producing products from powder materials have great prospects in modern industry. Thanks to such technologies, it is possible to obtain products with a complex geometric shape, as well as materials with a unique set of properties. A powder is understood as a set of individual solids (or their aggregates) in contact with small sizes-from a few nanometers to a thousand microns [1]. In relation to the manufacture of nanomaterials, ultrafine powders are used as the starting material, i.e. particles of a size not exceeding 100 nm, as well as larger powders obtained under conditions of intensive grinding and consisting of small crystallites of a size similar to those indicated above. V. Makarov (B) · Y. Molev · A. Markov Nizhny Novgorod State Technical University, NSTU, 24 Minina Street, 603155 Nizhny Novgorod, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_148
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Subsequent operations of powder technology: pressing, sintering, are designed to ensure the receipt of a sample (product) of specified shapes and sizes with the appropriate structure and properties. The totality of these operations is often called consolidation. Consolidation is a process or a set of processes for obtaining whole and connected solids, and products by combining the structural elements that make up them. The latter can be fibers, granules, powders. The concept of consolidation includes not only the processes of powder metallurgy (molding, pressing, sintering), but also others, that is, consolidation is a process in which the main bulk part of the structural elements remains in a solid state [2].
2 The Main Part Consolidation should ensure, on the one hand, almost complete compaction (absence of macro-and micropores in the structure), and on the other hand, preserve the nanostructure associated with the initial dimensions of the ultrafine powder (i.e., the grain size in sintered materials should be as small as possible and in any case less than 100 nm) [3]. Figure 1 lists the main methods of consolidation of metal powders. The main methods of forming products from metal powders are: 1) Pressing in molds; 2) Isostatic pressing; 3) Rolling of powders;
Fig. 1 Methods of consolidation of metal powders
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4) Mouthpiece pressing; 5) Slip molding; 6) Dynamic pressing. More than any other operation, forming limits the technological possibilities of powder metallurgy. The complexity of the phenomena occurring in this case makes it necessary to carry out special operations to prepare the powder for subsequent compaction [4]. The molding operation involves a large amount of energy, which is spent on compacting the preform by moving and deforming the particles, to overcome the frictional forces between the particles and the walls of the cavity. To facilitate molding, a plasticizer is introduced—a plastic substance that helps to seal and harden the moldings. The larger the contact surface of the powder particles, the stronger the engagement and adhesion between them. And the contact area, naturally, increases with increasing pressure on the surface (approximately proportionally). By increasing the contact between the particles during molding, the strength of the molded body increases, the porosity decreases, the accumulations of particles are crushed, and sometimes the particles themselves, and some hardening (hardening) of the particles occurs. Porosity is the ratio of the volume of voids in a material to its total volume. In the molding process, powder blanks are given the shape, dimensions, density and mechanical strength necessary for the subsequent manufacture of articles. Figure 2 shows a diagram of the change in volume when molding powders. Powder metals can deform both as a result of the deformation of individual particles and as a result of their displacement and filling of pores with them. Thus, the deformation of a free-flowing body, in contrast to a compact one, changes not only its shape, but also its volume. Usually, when molding, the height of the workpiece in relation to the height of the poured powder decreases 3–4 times or more [5]. During molding, elastic, brittle and plastic deformation of the particles can occur simultaneously. Figure 3 shows possible schemes for the movement of powder metal particles. When particles approach each other, an increase in the area of contact areas can occur both without deformation of the particles (a) and with their deformation (b); removal of particles (c) causes a decrease in the contact areas and can even lead to a break in the contact; sliding of particles (d) is accompanied by a displacement of the contact areas; along with the movement, the particles can be destroyed due to brittle deformation (e). As a result of brittle deformation, both the accumulations of particles and the particles themselves can be destroyed. This is observed when forming powders with brittle and hard components, for example, fine cast iron shavings, as well as hard but brittle metal compounds. The degree of particle deformation increases with an increase in the plasticity of the formed material and the applied pressure [6]. The results of molding are influenced by various factors: the bulk density of the powder, the pretreatment of powders, the magnitude and direction of pressure during molding, etc. Loose bodies occupy a volume at which the mechanical strength of the body, due to the mutual engagement of particles, is sufficient to resist the pressure
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Fig. 2 Scheme of the change in volume during the molding of powders
Fig. 3 Schemes of movement of powder particles during molding
caused by mass of powder. If the mechanical strength is high, then a sufficient degree of engagement is obtained even with loose laying and the powder has a low bulk density. If the strength of the bulk body is low, then in order to obtain the necessary engagement, a denser packing is needed, which increases the bulk density of the powder [7].
3 Pressing When pressing the powder, the target product is formed and compacted when pressure is applied to it. For pressing nanopowders at room temperature, static uniaxial pressing, dynamic magnetic pulse pressing, complex pressing (isostatic), ultrasonic
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sealing, and intensive plastic deformation are used. The variety of compaction methods provides wide technological possibilities for the production of high-density and porous materials. The dispersion of dispersed powders is significantly influenced by such parameters as the average particle size, the content of impurities, the surface condition, the shape of the particles, the method of pressing and the presence of strong particle agglomerates. Despite the use of rather high pressing pressures (up to 2–5 GPa), even under vacuum conditions and at a small sample height (up to 1 mm), it is possible to obtain samples with a porosity of at least 10–15%. Ultrafine powders are characterized by low compaction during pressing due to the significant influence of the friction characteristics between the particles. In the technology of pressing powders at room temperatures, the use of ultrasonic vibrations is effective, which reduce the elastic aftereffect after removing the load during pressing and slightly increase the relative density of compressed products, expanding the possibilities of their manufacture in the form of bushings and other forms [4, 5]. Uniaxial pressing is more widely used for the consolidation of nanopowders: static pressing (in molds, stamping), dynamic pressing (magnetic pulse, explosive), vibrational pressing (ultrasonic). Complex (isostatic) compression is used to obtain materials of high density and uniformity: hydrostatic, gas-static, quasi-hydrostatic (in special forms of high pressure). Currently, the method of intensive plastic torsion deformation under high pressure is successfully applied. In some cases, rolling is used to make tapes. As the particle size decreases, the pressing density decreases significantly. If the particle size is less than the critical one, they are dislocation-free, so the nanopowder cannot be plastically deformed to large strain values, and its compaction does not occur during compaction. Thus, the use of high-energy methods of consolidation, involving the use of high static and dynamic pressures and moderate temperatures, allows to a certain extent to delay the growth of grains [6].
4 Sintering To eliminate the residual porosity, heat treatment of compressed samples is necessary—sintering. However, the usual modes of sintering of powder objects do not allow preserving the original structure. The processes of grain growth (recrystallization) and compaction during sintering (shrinkage), being diffusion-controlled, go in parallel, overlapping each other, and it is not easy to combine a high compaction rate with the prevention of recrystallization. Conventional modes of pressing and sintering of ultrafine powders can be used to obtain nanostructured porous semi-finished products, which are then subjected to pressure treatment operations for complete consolidation. It is possible to delay the growth of grains during normal sintering by using special non-isothermal heating modes. In this case, due to the competition of the mechanisms of shrinkage and
1452 Table 1 Sintering mechanisms
V. Makarov et al. №
Mechanism
Source of the material
1
Surface diffusion
Surface
2
Volume diffusion
Surface
3
Steam
Surface
4
Grain boundary diffusion
Grain boundary
5
Volume diffusion
Grain boundary
6
Volume diffusion
Dislocations
7
Viscous flow
Particle volume
grain growth, it is possible to optimize the compaction processes, largely eliminating recrystallization phenomena [7]. Electric discharge sintering, carried out by passing current through the sintered sample, and hot pressure treatment of powder objects (for example, forging or extrusion) can also contribute to the inhibition of recrystallization and be used to produce nanomaterials. Sintering of ceramic nanomaterials under microwave heating conditions, which leads to a uniform temperature distribution over the sample crosssection, also contributes to the preservation of the nanostructure. However, the size of the crystallites in the listed consolidation variants is usually at the level of the upper limit of the grain size of the nanostructure, i.e. usually not lower than 50–100 nm [8]. Sintering mechanisms Table 1.
5 Extrusion Extrusion is used for forming long products of various profiles. The main methods of implementation—mouthpiece and screw pressing-are characterized by ease of automation and high productivity. Depending on the temperature of the molded material, hot and cold extrusion are distinguished. Hot extrusion is carried out at temperatures corresponding to the maximum plasticity of the material. This method is used to press plastic metals, both in the cast and in the crushed state [9, 10]. The versatility of cold extrusion lies in the possibility of forming any powder materials. The technological properties of the plasticized powder are mainly determined by the composition and quantity of the plasticizer and do not depend much on the powder itself. As a result, products as diverse in composition as ferrite cores, carbide tools, bronze and titanium filters, aluminum heat exchangers and many others can be obtained using similar technologies. Cold extrusion expands the possibilities of powder metallurgy. It allows you to obtain products that are difficult or impossible to manufacture by other methods: pipes of a complex profile (for example, with screw surfaces), thin-walled filters, powder cords for gas-thermal coating, long products of variable profile.
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6 Conclusion It is necessary to note the importance of consolidation of metal powders. The use of consolidation methods should ensure almost complete compaction, that is, the absence of macro-and micropores, as well as preserve the structure associated with the initial powder sizes, that is, the grain size in sintered materials should be as small as possible. Acknowledgements The work was carried out with the financial support of the Ministry of Education and Science of the Russian Federation within the framework of the project "Creation of high-tech production of materials, products and equipment using additive technologies and gas-conditioning technologies on the basis of PJSC RUSPOLIMET "under Agreement No. 075-11-2019-084 of 18.12.2019 (Decree of the Government of the Russian Federation No. 218 of April 09, 2010).
References 1. Alymov MI, Gulyaev PY, Semichev SV (2019) Consolidation of powder nanomaterials: review of development trends and applications. Bull Ugra State Univ 15(4):7–16 2. Kubanova AN, Sergeev AN, Dobrovolsky NM, Gvozdev AE, Medvedev PN, Maliy DV (2019) Features of materials and technologies of additive manufacturing of products. Chebyshevsky Collect 20(3):453–477 3. Borovinskaya IP et al (2007) Technology of self-propagating high-temperature synthesis of nanosized powders of refractory compounds. Nanotechnol Russia 3:114–119 4. Manyanin SE, Vaxidov YS, Maslov KA (2021) Theoretical aspects of production of products by hot isostatic pressing. In: IOP conference series: materials science and engineering, p 052011 5. Tschopp MA et al (2014) Bulk Nanocrystalline metals: review of the current state. JOM 66(6):1000–1019 6. Manyanin SE, Vaxidov YS, Maslov KA (2021) Operations for the preparation of metal powders for hot isostatic pressing. J Phys Conf Ser Intell Inf Technol Math Model 2021:052029 7. Makarov VS, Molev YI, Markov AI (2021) Additive technologies in the production of products by hot isostatic pressing. In: IOP conference series: materials science and engineering, p 052010 8. Alymov MI, Shustov VS, Ustyukhin AS, Evstratov EV (2012) The ratio between the quality of nanopowders and the performance of their production methods. Compos Nanostruct 3:5–9 9. Alymov MI, Bakunova NV, Barinov SM, Belunik IA, Fomin AS, Ievlev VM, Soldatenko SA (2011) Features of compaction during pressing of hydroxyapatite nanopowders. Russian Nano-technol 5–6:50–52 10. Brokhin IS, Federmeer DL, Shapiro SS (1959) Molding of powders of carbide mixtures by extrusion. In: Hard alloys. VNIITS, pp 100–101
Research of Early Structure Formation Process of Concrete Where Concrete Waste is Used as Crushed Stone Ivan Pulyaev
and Sergey Pulyaev
Abstract Currently, Russia is undergoing a period of mass housing construction, the main goal of which is to provide the country’s citizens with high-quality comfortable housing. In particular, the city of Moscow has adopted a program for the renovation of the housing stock, within the framework of which more than 5,000 low-rise dilapidated houses built during the Soviet period will be dismantled in the coming years. It is obvious that as a result of the dismantling of structures, a large amount of concrete scrap is formed, which needs subsequent processing. One of the ways to utilize this waste is to crush it and then use it as a coarse aggregate in a concrete mixture. This process will allow, on the one hand, to ensure the secondary processing of previously used raw materials, and on the other, to reduce the cost of the construction process of the facility. The article is devoted to the study of the processes of early structure formation occurring in hardening concrete, in which the specified waste in the form of concrete scrap is used as a large aggregate. The article will be useful for engineering and technical personnel, researchers, specialists employed in the real construction sector, as well as everyone who is interested in the topic of the secondary use of industrial waste. Keywords Transport infrastructure · Cement · Hardening · Strength · Heat dissipation · Concrete
1 Introduction The development of the construction industry in the world keeps pace with the times and in the conditions of the economic and political realities of a particular country. At the same time, new knowledge and experience are already being applied everywhere, I. Pulyaev (B) Central Laboratory of Engineering Thermophysics, Eniseyskaya Ulitsa, 7, Moscow 129344, Russia e-mail: [email protected] S. Pulyaev Moscow State University of Civil Engineering, Yaroslavskoe Shosse, 26, Moscow 129337, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_149
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modern complexes for the processing of secondary raw materials are being put into operation, innovative technologies are being introduced. In Russia, after the collapse of the USSR, the issue of updating the housing and public fund, bringing it in line with modern standards, arose quite acutely. One of the most important reserves of saving material and energy resources in the construction industry is currently the use of waste from precast enterprises and construction projects in the form of the resulting concrete scrap [1, 2]. Currently, in connection with the massive construction of housing in Russia, the adoption in Moscow of the program for the renovation of the housing stock, complexes for the destruction of substandard reinforced concrete products by mechanical means and the production of crushed stone from crushed concrete have become widely demanded. And based on the volume of raw materials obtained, the issue of its rational use in the technology of reinforced concrete products and structures arises [3, 4]. In the course of construction work, a large amount of old concrete mortar accumulates, remaining on the walls of concrete mixers, as well as various unnecessary concrete and reinforced concrete structures. Such garbage is taken to landfills, but there is too much of it, and therefore significant areas are required for organizing garbage collectors, special transport and lifting equipment. A completely unacceptable way to destroy construction waste is to bury it without removal. Concrete waste does not rot in the ground and can persist for a very long time even with active moisture. Recycled raw materials help to reduce the profitability of new concrete mortar, due to its use as a filler. However, the existing difficulties in the disposal of crushed stone from crushed concrete, caused, first of all, by the peculiarity of the properties and heterogeneity of the source material in strength, grain composition, pollution, the content of weak components and other factors, restrain the widespread use of crushed stone from crushed concrete in the technology of reinforced concrete structures and in construction [5–7]. Studies by Russian and foreign experts have shown that the rational use of building materials waste as aggregates gives the ability to obtain reinforced concrete products characterized by sufficiently high strength indicators and lower cost.
2 Methods The use of secondary materials (concrete battle) in the construction industry is gaining momentum in our country. The high efficiency of using broken concrete is proved by the increased growth in demand for secondary crushed stone. The cost of crushed concrete after the demolition of buildings and other building structures, even with subsequent processing, remains quite low. The process of processing concrete scrap into crushed stone is based on crushing and subsequent sorting of the resulting material using special installations. Crushed
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concrete or, as it is called, broken concrete after processing is used for the construction of various objects, where high-quality and inexpensive filler is needed. Broken concrete differs from other types of crushed stone in a lesser degree of frost resistance. However, this lack of crushed stone is insignificant in most cases. It is very important to note that broken concrete is not a battle in the usual sense, but crushed stone sorted into fractions. In view of what, broken concrete is of a fairly high quality. But we all understand that granite and gravel crushed stone in their performance is somewhat superior to concrete breakage. However, in many cases, the qualities that crushed concrete has are quite enough. The use of crushed concrete is possible for various purposes: – – – – – – – –
in the manufacture of cement-concrete mortars; to correct the landscape during work on the arrangement of sites; as a backfill for ponds, canals and wetlands; in the form of dumping during the construction of roads and the construction of embankments; for the production of certain grades of concrete and new concrete products; for the manufacture of paving slabs and asphalt; as a backfill at the bottom of trenches (pits) when laying utility lines on loose and swampy soils; as an interlayer in the construction of wells, as well as artificial reservoirs.
The solution to the problem of rational use of crushed stone from concrete in the technology of reinforced concrete products and structures is possible, first of all, when developing technical conditions and regulations for the production of work, as well as creating a regulatory framework for obtaining a conditioned aggregate [8, 9]. The resulting concrete scrap can be used in concretes for various purposes of various classes. And this, in turn, requires a large complex of studies aimed at obtaining information about the effect of crushed stone from crushed concrete on microprocesses and macroprocesses occurring in hardening concrete, among which the study of the process of early structure formation of concrete on crushed stone from concrete scrap is one of the priorities and promising ones. The process of forming the structure of concrete can be divided into three periods: initial, during which the concrete mixture turns into concrete; subsequent, during which the structure of the concrete is gradually strengthened; and third, when the structure stabilizes and hardly changes over time (Fig. 1). The boundary between the first and second periods is point A, which determines the moment when the initial structure of concrete has already emerged and further strengthens it. The first period is characterized by the fact that the products of cement hydration have a gel-like appearance. These are especially small particles of fibrous, fibrous and lamellar forms that fill the spaces between the cement grains. They form a coagulation structure in the form of a loose framework, a kind of porous matrix, which is gradually filled with hydration products [10–12]. The second period of the early structure formation process is characterized by a sharp increase in strength. This is due to the growth of neoplasms and the crystallization process within the formed initial framework. By the end of the period of
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Fig. 1 Estimated periods of structure formation: I—the period of formation of the initial structure; II—period of strengthening of the structure; III—period of stabilization of the structure
formation of the structure (point A), there is a sharp transition from a plastic-viscous cement system to a brittle solid—cement stone [13, 14]. The structure of the cement system, formed by the end of the first period, has a significant impact on the structure and properties of the cement stone. The structure formation process is mainly determined by the presence of three phases in these systems: liquid, solid and gaseous. The quantitative ratio between these phases has a significant effect on the distribution and forms of water bonds and, thus, on the properties of the mixture, as well as on the physicochemical processes occurring during the hydration of cement.
3 Results The study of the process of early structure formation of concrete on crushed stone from concrete scrap was carried out by changing the limiting shear stress, the speed of ultrasound transmission, contraction and heat release by standard methods. Were investigated concrete mixtures prepared on the Belgorod cement grade M500, crushed stone from concrete with a fraction of 5–20 mm and quartz sand of medium size. For comparison, concrete mixtures were also prepared on granite crushed stone of the Pitkaranta deposit with a fraction of 5–20 mm. Superplasticizer C-3 was used as a surfactant. Were investigated two series of concrete samples on granite crushed stone and crushed stone from concrete: with the same water-cement ratio equal to 0.49, with the following material consumption in kg per 1 m3: • cement—395, water—195, sand—588 and granite crushed stone—1208; • cement—395, water—195, sand—347, crushed concrete—1149; • the same as in composition 2, but with the addition of C-3 in the amount of 0.6% by weight of cement;
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with the same mobility equal to 5 cm of the draft of a standard cone with the following material consumption in kg per 1 m3: • cement—395, water—195, sand—588 and crushed granite 1208; • cement—395, water—214, sand—321 and crushed stone from concrete—1311 at W/C = 0.54. The dependences presented in the graphs (Figs. 2, 3, 4 and 5) show that a more intensive growth of plastic strength, an increase in the speed of passage of ultrasonic vibrations, contraction and heat release is observed in concrete on crushed stone from concrete scrap. This phenomenon can be explained by the fact that the structure of the concrete mixture changes significantly as a result of the redistribution of water in the system, since crushed stone from concrete has increased porosity and, as a result, higher water absorption. As a result, part of the mixing water is immobilized in the concrete mixture due to the suction of water by the filler. According to a number of researchers, it has been proven that the period of formation of the structure of a cement stone in concrete under isothermal conditions strictly depends on its water-cement ratio. Therefore, the period of formation of the structure of concrete on crushed stone from concrete turned out to be somewhat shorter than that of control concrete on granite crushed stone with the same water-cement ratio. Subsequently, during hardening, the water absorbed by the aggregate from the concrete mixture, as a result of the increased capillary potential and contraction of the cement stone after the period of structure formation, begins to be sucked out by the cement stone and actively participate in the hydration of the cement. All this contributes to the formation of a denser cement stone with reduced porosity and finer 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0
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Fig. 2 Dependence of the contraction value V, % on time, h, where: 1—concrete on crushed granite; 2—concrete on crushed concrete; 3—concrete on crushed stone from concrete with the addition of superplasticizer
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Fig. 4 Dependence of the ultimate shear stress T, MPa on time, h, where: 1—concrete on crushed granite; 2—concrete on crushed concrete; 3—concrete on crushed stone from concrete with the addition of a superplasticizer
pore character, as well as the formation of a strong and dense contact zone between the cement stone and the aggregate. The introduction of a superplasticizer into the concrete mixture at the same watercement ratio (composition 3) leads to a lengthening of the structure formation period caused by an increase in the latent period of cement hydration, which is consistent with the data obtained by G.I. Gorchakov [15].
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Fig. 5 Dependence of the speed of ultrasound transmission, V, m/s on time, h, where: 1—concrete on granite crushed stone; 2—concrete on crushed concrete; 3—concrete on crushed stone from concrete with the addition of superplasticizer
Thus, the studies carried out have shown that the use of crushed stone from a concrete house has a positive effect on the formation of the structure of hardening concrete, increasing its strength and performance characteristics, as well as improving environmental and economic indicators. The studies carried out also allowed us to conclude that the properties of large secondary aggregate obtained from concrete scrap correspond to the requirements of regulatory documents for the aggregate, and also showed the positive effect of the aggregate on the properties of heavy concrete. And the expansion of the use of recycled aggregate from concrete scrap makes it possible to reduce the extraction of natural aggregates and reduce the damage caused to the natural landscape during the development of deposits of nonmetallic materials.
References 1. Magsumov AN, Sharipyanov NN, Krasinikova NM (2018) The use of concrete scrap as a large aggregate for the production of concrete mixtures. Int Sci J «Symb Sci» 6:29–32 2. Efimenko AZ (2014) Improving the efficiency of production of volumetric cabins using expert assessments. Sci J «Mater Conc Technol» 2:17–21. 3. Romanenko II, Romanenko MI (2015) New materials in road construction. Sci J «Sci Sci» 1:1–12 4. Kurochka PN, Merzaliev RR (2012) Concretes with aggregate from crushing products. Sci Tech J «Vestnik RGUPS» 3:140–147 5. Gusev BV, Zagursky VA (1988) Secondary use of concrete, p 97 6. Gusev BV, Kudryavtseva VD (2013) Crushing of reinforced concrete products and recycling of concrete. Sci J «Tech Technol Silicates» 20:25–28 7. Golovin NG, Alimov LA, Voronin VV (2005) Use of concrete scrap crushing screenings. Sci J «Constr Mater Equip Technol XXI Century» 9:26–27
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8. Flora F, Mariano AZ, Katya B, Carlo P (2015) Valorization of co-combustion fly ash in concrete production. Sci J «Mater Des» 85:687–694 9. Jin R, Chen Q, Soboyejo A (2015) Current state, comprehensive analysis and proposals on the practice of construction and demolition waste reuse and recycling in Portugal. Sci Tech J «Res Conserv Recycl» 105:148–159 10. Bazhenov YuM, Gorchakov GI, Alimov LA, Voronin VV (1984) Improving the durability of concrete and reinforced concrete structures in harsh climatic conditions. In: Improving the durability of concrete and reinforced concrete structures in harsh climatic conditions, p 274 11. Bazhenov YuM, Gorchakov GI, Alimov LA, Voronin VV (1972) Structural characteristics of concrete. Sci Tech J «Conc Reinforced Conc» 9:13–18 12. Bazhenov YuM, Gorchakov GI, Alimov LA, Voronin VV (1978) Structure formation in cement stone. In: Concrete with specified properties, p 53 13. Voronin VV, Alimov LA, Balakshin AS (2010) Low-stone concrete on crushed concrete from concrete scrap. Sci Tech J «Conc Technol» 3:28–29 14. Balakshin AS (2011) Properties of low-crushed concrete with an organomineral additive based on concrete scrap crushing screenings. Sci Tech J «Vestnik MGSU» 1:253–258 15. Gorchakov GI, Alimov LA, Voronin VV, Sobolev GM (1979) The principle of optimization of concrete compositions for energy construction considering structural characteristics. Collect Sci Pap «Power Constr» 8:107–121
Design of Energy-Saving Heat Pump Heat Supply Systems in Residential and Non-residential Premises Sergey Fedosov , Vadim Fedoseev , and Svetlana Loginova
Abstract Cost of energy, especially for commercial, industrial and other organizations, is a limiting factor. Heating and cooling costs are an increasing share of operating costs, so the use of renewable energy sources is aimed at reducing existing energy costs. Heating systems based on air heat pumps are promising. The article discusses the specifics of the operational features of heat pump heat supply systems using low-grade heat of atmospheric air, which significantly affects the efficiency of further operation of the systems under consideration. When designing heat supply systems using design and spatial solutions, it is necessary to take into account the process of modeling and controlling the spread of heat in the room. Since the use of new capital-intensive heat supply technologies, including the use of heat pumps, is proposed at the stage of a feasibility study it is necessary to consider in more detail such energy-efficient measures as the use of energy-saving enclosing structures; the use of energy-saving supply and exhaust ventilation, recuperation; creation of a rational system of heat supply for the premises with the use of control and metering units for heat energy; installation of economical hot water draw-off devices. Keywords Energy efficiency in transportation · Heat pump · Energy saving · Energy efficiency · Energy · Microclimate
S. Fedosov National Research Moscow State University of Civil Engineering, Yaroslavskoe Sh., 26, 308012 Moscow, Russia V. Fedoseev Ivanovsk State Polytechnic University, Sheremetevsky Pr., 21, 153000 Ivanovo, Russia S. Loginova (B) Yaroslavl State Technical University, Moskovsky Pr., 88, 150023 Yaroslav, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_150
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1 Introduction The climatic feature of the regions of Russia requires various kinds of maintenance of a comfortable microclimate, both in non-residential and residential premises. Today, in modern conditions, there are high requirements for the reliability, efficiency and energy efficiency of heat supply systems. Despite the fact that the air environment of the premises is protected from the direct influence of the atmosphere on it by the enclosing structures of the building, its parameters, under certain conditions, can have an adverse effect on human well-being, as well as on the nature of the implementation of technological processes [1]. At present, heat pumps have not received proper application in Russia due to the high cost of equipment and installation, poor awareness of Russian consumers about the possibilities and advantages of heating by heat pumps, etc. When designing buildings and structures taking into account energy-saving technologies, including the use of heat pumps that use the heat of secondary energy resources and non-traditional energy sources, it is necessary to consider the object as a whole. At the early stages of design, it is important to achieve consistency of technical solutions, considering the object as a whole from an architectural and constructive point of view, in order to select the optimal schemes for the introduction of energy-saving technologies that ensure the minimum payback period for capital and operating costs. At the design stage, it is necessary to take into account the geographical location of the object [2]. It is advisable to make a decision on the use of the proposed energy-saving heat pump systems at the stage of development and approval of the design assignment. As prerequisites for the use of such systems, it is possible to designate: remoteness from centralized heating systems; limitation in the use of the installed capacity of electricity in accordance with the existing market norms; availability of secondary energy resources (ventilation emissions, waste heat); relatively low temperature potential of the heat load: (fan coil units); technical conditions for connection to external power supply sources [3]. The listed design stages must go through the stage of a feasibility study (FS). At this stage, various engineering systems with each other and with the heat pump heat supply system (TST) should be worked out quite clearly in terms of the use of secondary renewable energy resources (atmospheric air, etc.) [4, 5]. As a rule, heat pumps are selected in terms of power for the value of the main loads according to the existing schedule of their change. All this ensures their maximum use and a more stable mode of their operation. As additional energy sources designed to cover peak loads, it is advisable to use small shadows (heaters) operating in a coordinated mode. The surrounding air, having internal energy, consists of kinetic heat and pressure energy. When the influence on its characteristics (temperature, absolute humidity, pressure) changes, the corresponding part of the internal energy will be released. Additional energy can be extracted from the released energy. The amount of this energy will depend on the efficiency of the selected energy extraction process. The recovered energy, utilizing heat and electrodynamic technology, is converted into
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a form of energy suitable for the consumer (thermal or mechanical), in this case for heat supply of the premises with an air heat pump [6–9]. To extract low-grade thermal energy and pressure energy, it is necessary that the energy converter has a receiving device that creates a potential thermal hole at the inlet; a device that converts the characteristics of the extracted energy from a low potential to a potential higher than that of the consumer; a device that transfers energy to a consumer [10, 11]. Therefore, proceeding from the fact that heat pumps today make it possible to extract heat from the environment, while continuing to develop the extraction of the surrounding air for the purpose of obtaining full autonomy of the HTN operation mode, scientists work using this technology to obtain a certain amount of electricity, relying on thermodynamics and electrodynamics in the process of heat and mass transfer of this technology [8, 10]. The specificity of the operational features of heat pump heat supply systems using low-grade heat of atmospheric air significantly affects the energy efficiency of the further operation of the systems under consideration. This greatly complicates the task of predicting the thermal behavior of the heat collection system throughout the year. This explains the use of design-spatial solutions in the design of heat collection systems, taking into account the statistical data on the climatology of a particular region.
2 Materials and Methods As a result of experiments carried out in real conditions on the territory of the Central Federal District, as well as studies to assess the permissible operational impacts on the system of heat transfer of energy from the air at the HTP, it was found that the operation of the HTN in such conditions is characterized by two main periods: winter - 210 days, summer - 150 days. The experiment was carried out on the basis of a modernized Chinese device Meeting MD20D - a monoblock heat pump with a power of 7 kW, 220 V [9, 12]. The first period: from the beginning of the heating season to the outside air temperature +150 °C. The second period is characterized by an external temperature from +100 to −300 °C. The configuration of all parameters of the Meeting control system, as well as ensuring its operational diagnostics, is carried out by mounting the control panel in the hydraulic module. Using temperature sensors, the control panel regulates the temperature inside the house, the return temperature and the temperature from the solar collector. Also, the Meeting heat pump has a built-in emergency power kit that allows you to maintain minimum heating parameters in the event of a system failure. The authors of [10] proposed a combined heat pump heat supply system, including a mixing chamber, an air exchange circuit with a recuperation element and an additional heating element controlled by an electronic pulse controller (Fig. 1). With such a specificity of the air exchange mode of the HTN with a recuperation element, the
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Fig. 1 Air exchange system of air heat pump
functionality of the heat exchange system operating through the boiler room and the air ducts of the room is determined. In the heat exchange system, the warm air of the room partially heats the counter cold flow and goes out as exhaust through the guides of the air duct into the mixing chamber to the evaporator and then through the HTN to the street, and partially already heated recuperative air enters the room. In such conditions, proceeding from the main goal of creating energy-efficient heating, we obtain an economically profitable air exchange system for the VTN heat generator. According to the current regulatory documents, the use of new modern heat supply technologies requires a preliminary feasibility study, namely, the definition of the main architectural and planning solutions; design thermal and electrical loads of the facility, taking into account all internal household and technological heat release; development of possible measures to reduce energy loads using traditional methods; determining the structure of energy consumption (heat and electricity); daily and annual schedules of heat and electricity consumption; elaboration of traditional heat supply schemes and determination of costs for its creation; calculation of annual
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operating costs for the traditional heat supply option and the heat pump option; calculation of the payback period of the TST [9, 12]. If the payback period is acceptable and the TST option is accepted for implementation, the following design stages are performed in accordance with the existing standards with a mandatory calculation justification for the choice of the structure and technical characteristics of the equipment used.
3 Main Part The main advantages of using heat pumps are [13–15]: 1. Profitability. The heat pump uses the energy expended more efficiently than any heat generator that burns fuel. Its efficiency factor is much greater than one. 2. A source of dissipated heat from the ambient air can be found anywhere. 3. Environmental friendliness. The unit (HP) does not burn fuel, therefore, harmful oxides CO, CO2 are not formed. Freons currently used in heat pumps do not contain chlorocarbons and do not deplete the ozone layer. 4. Versatility. Heat pumps can be switched from heating in winter to air conditioning in summer. Instead of radiators, fan coils are connected to an external collector, creating the required microclimate. 5. Security. Heat pumps are practically explosion and fire safe. No part is heated to temperatures that could ignite flammable materials. Stops of heat pumps do not lead to damage or freezing of liquids. The disadvantages of air heat pumps include the high cost of installed equipment, as well as a decrease in the heat conversion coefficient associated with a lower ambient temperature (Fig. 2) and, as a consequence, with a lower boiling point in the “air” evaporator. However, during the modernization of the HTN Meeting MD20D [8, 9, 12], we obtained results that convincingly prove the effective performance of the HTN under the conditions of the Central Federal District for a year. Comparative calculation [1, 6, 8, 9] of energy costs in a heating system using air heat pumps in relation to diesel, electric and gas shows that the cost of heating a house using modern heat pump units is lower than the cost of heat supply using the listed types. Table 1 shows the calculation of prices for heating a residential building in the Moscow region with an area of 200 m2 . An important factor in assessing economic efficiency is the possibility of heating/cooling the house during the warm season. It should be noted that the combined systems of heat and cooling supply of heat pumps with solar collectors, wind generators and low-capacity additional energy carriers are economically efficient [16].
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Table 1 Heating costs per year
Costs, rub
Diesel
Propane-butane
Electric boiler
Wood pellets
Firewood
HTN
Natural gas
139 788
113 775
110 944
81 593
57 799
25 285
24 301
4 Conclusions • The economic effect of the new Meeting system is such that after two years of operation of this heat pump, it demonstrates results higher than gas and diesel boilers, and after 4 years of operation it surpasses electric boilers. This system also reduces monthly DHW costs. • Versatility, flexibility, circuit combinations of the use of air heat pumps for heating systems of buildings and structures help in all cases to solve a number of issues that are cost-effective and related to energy saving and energy efficiency, reducing the use of non-renewable fossils and improving the environment.
References 1. Grosheva EK, Chuprin AD (2020) Alternative energy sources, their application in Russia. In: Business education in the knowledge economy, pp 19–23 2. Khare V, Nema S, Baredar P (2016) Solar – wind hybrid renewable energy system. Renew Sustain Energy Rev 58:23–33
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3. Chicherin SV (2017) Reliability and efficiency of medium-temperature heat supply. In: Materialovedenie. Energy, pp 75–79 4. Volodin VI, Sedlyar KV (2016) The choice of operating parameters and refrigerant for steam compressor air heat pumps. In: Proceedings of BSTU. Chemistry and technology of inorganic substances, vol 3, pp 147–153 5. Shcherba AD (2019) The use of heat pumps in Russia. Educ Sci Russia Abroad 1(49):45–47 6. Rukavishnikov AM (2019) New Russian patents on refrigeration technology and heat pumps. Refrig Technol 4:57–59 7. Khalilullina AR (2019) Renewable energy sources in the form of a geothermal heat pump. Innov Sci 2:42–44 8. Fedosov SV, Fedoseev VN, Zaitseva IA, Emelin VA (2020) High-tech system of air heat pump for low-rise and cottage buildings. J Pribory 2(236):49–53 9. Rumyantsev EV, Fedosov SV, Fedoseev VN, Petrukhin AB, Chistyakova YuA (2018) Innovative solutions for safe and environmentally friendly heat supply systems for industrial buildings as a factor in reducing the energy intensity of the Russian economy. Bull Voronezh Inst State Fire Serv EMERCOM Russia (Mod Prob Civil Protect) 4:45–50 10. Fedosov SV, Fedoseev VN, Zaitseva IA (2020) Recirculating air heat pump with recuperation: application experience. AVOK Ventil Heat Air Condit Heat Supply Build Thermal Phys 8:54–57 11. Kim DH, Park HS, Kim MS (2014) The effect of the refrigerant charge amount on single and cascade heat pump systems. Int J Refrig 40:254–268 12. Fedoseev VN, Emelin VA, Voronov VA, Ostryakova YuE, Sviridov IA (2017) Patent No. 174083, Russian Federation, Heat pump; app. from 01/09/2017; publ. 09/29/2017. Bul. No. 28 13. Herbert J, Krishnan U (2016) Quantifying environmental performance of biomass energy. Renew Sustain Energy Rev 59:292–308 14. Makhova AV, Nelipa AV (2018) Analysis and prospects for the use of alternative energy sources in Russia in 2014–2024. Eurasian Union Sci 3–4(48):41–44 15. Jung HW, Kang H, Chung H, Ahn JH, Kim Y (2014) Performance optimization of a cascade multifunctional heat pump in various operation modes. Int J Refrig 42:57–68 16. Seregina EA, Beimanov T (2019) Use of heat pumps for heating rooms in Russia. Urban Plan Infrastruct Commun 2(15):16–21
Influence of Temperature on the Energy Consumption for Pressure Pipelines Vladimir Orlov
and Dmitry Peterburgsky
Abstract The problem of evaluating the influence of the temperature factor on the electricity consumption for the transportation of water in pressure pipes made of suitable materials is an integrated approach that includes, as a prerequisite, conducting bench hydraulic experiments to determine the hydraulic friction coefficient, as well as calculation and analytical operations, followed by widely used software automated programs. The pipes made of non-plasticized polyvinyl chloride are subject to a detailed study. To provide the best objectivity when comparing the experimental and design values of the desired issues, the algorithms of automated programs have a number of restrictive bands on a number of indicators such as the Reynolds number, the ratio of dynamic viscosities, respectively, related to the temperatures of the pipe walls and transported water, as well as the water kinematic viscosity. Modeling based on the results of the automated calculations and their subsequent analysis enables determination of the electricity consumption amount under the appropriate temperature conditions of the pipeline operation along with identification of the optimal parameters for controlling the water transportation process, which allows the utility managers to provide an effective management of the water transportation process, helping to ensure minimal energy consumption. Keywords Energy efficiency in transportation · Temperature · Pipelines · Modeling · Electricity consumption
1 Introduction General Research Topic and Relevance of the Work Provision of the electrical energy consumption savings in buildings and structures, in particular, saving the electricity for mechanical transportation of water through aging pressure pipelines by reducing the hydraulic resistance of their internal walls V. Orlov (B) · D. Peterburgsky Moscow State University of Civil Engineering (National Research University) (MGSU), Prospekt Mira, 26, Moscow 129337, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_151
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is a relevant problem [1, 2]. This fact makes the designers and builders to solve a number of tasks and relevant studies for effective and rapid reconstruction works of the pipeline transporting utilities, including the use of trenchless technologies [3]. The similar tasks are also assigned to scientists and researchers in the form of conducting hydraulic tests of new alternative pipe materials and repairing protective coatings available at the construction markets in order to obtain the data on their real “hydraulic efficiency” [4]. These issues are very important for managers of public utilities, who should provide the further efficient operation of pipeline engineering mains [5]. The problems of updating dilapidated pipeline transportation utilities in some areas of pipeline systems, for example, in central heating houses should be solved in parallel with a complex problem of reducing the electrical energy consumption of the buildings and structures, when laying pipes under the ground, above the ground and the like [6]. The purpose of this study is to identify the nature of changes in the amount of hydraulic friction from the temperature conditions of the transported water and the environment in certain ranges, with the subsequent possibility to control the transportation process and reach the minimum energy consumption. The task is to be achieved by conducting experimental hydraulic studies on large-sized benches, as well as using a computational and analytical approach (using automated complexes) to determine the dynamics of changes in the pipeline hydraulic parameters [7]. The most well-known and significant publications on this topic are the following [8, 9]. In the field of pipeline system hydraulics, a significant number of methods for determining the hydraulic friction coefficient are used [10–12]. In cases where the influence of the temperature of the liquid transported through the pipeline on the value of the hydraulic rhenium coefficient is concerned, the methodological approaches require some additional interpretation [13, 14]. At the same time, it is possible to simulate thermal modes with the search for new dependencies to determine the values of the hydraulic friction coefficient, provided that the limiting ranges for a number of parameters are respected [15]. In practice, a symbiosis of experimental and analytical approaches is possible to determine the dynamics and ranges of changes in individual hydraulic flow characteristics and, in particular, the value of the hydraulic friction coefficient under different temperature conditions for laying and operating pipelines [16–18]. Analytical methods are accompanied by modeling, which enables a quick comparison of the experimental and design values of the hydraulic friction coefficients with the analysis of the amount of their possible discrepancies within the strict limits of the established optimal ranges of values of the Reynolds numbers and dynamic viscosities [19].
2 Materials and Methods of Research The study included the hydraulic experiments and analytical operations and studies, where the pipes of unplasticized polyvinyl chloride (UPVC) made the subject of the investigation, namely:
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– the hydraulic experimental studies, carried out in the Laboratory of the Department of “Water and wastewater” of NRU MGSU (1); – the automated processing of the obtained data to identify the dynamics of changes in the hydraulic friction coefficient L at different temperatures of the pipe wall and the transported water (2); – the automated search for optimal parameters that enable the control of the water transportation process based on the identification of the minimum values of electricity consumption E under the appropriate temperature conditions (3). The automated programs were used to process the results of the hydraulic experiments, to perform computational and analytical operations and a subsequent analysis [20, 21]. The first stage of the research was carried out on a large-sized bench. The experimental studies were carried out at a temperature of water and the surrounding space of 16 °C. The results of the experiments were used to determine the values of the hydraulic friction coefficients L0 for the UPVC pipe with an internal diameter of 0.1046 m in a wide range of water flow rates. The second stage of the research was to simulate the operation of the pipeline in order to identify the dynamics of changes in the hydraulic friction coefficient L depending on temperature conditions, in particular, the temperature of the pipeline wall at a stable temperature of the transported water. Based on the results of the automated calculation, intermediate values, such as the Reynolds number (Re), the ratio of dynamic viscosities, as well as the ratio of the calculated and experimental values of the hydraulic friction coefficients were monitored and analyzed. The third stage of the research comprised an automated search for optimal parameters for controlling the process of water transportation based on the identification of minimum values of E electricity consumption. The electricity consumption E (kW·h) for overcoming pressure losses during water transportation through pressure pipelines is calculated using the following basic formula (1): E = ρg Q H/1000η p 24 · 365 κg · m 2 · h/s 3 = κ W · h
(1)
where ρ is the liquid density, kg/m3 ; g—acceleration of free fall, m/s2 ; Q—the flow rate of water supplied by the pipeline, m3 /s; ηp—the efficiency of the pumping unit; 24—number of hours of the pump operation per day, h; 365—number of days per year; 1000—conversion factor from W to kW; H—the head loss in a pipeline of a certain length, m of water column. Expressing the pressure loss H in terms of the specific resistance of the pipeline made of the specified material A (s2/m6), the length l (m) and the flow rate Q (m3/s), we get the formula (2): H = A · l · Q2
(2)
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When transporting the water, i.e. at ρ = 1000 kg/m3 , g = 9.81 m/s2 , as well as performing mathematical conversion operations, the basic formula (1) will be written as (3): E = 9.81Q 3 (A · l)/η p 24 · 365
(3)
If the pipeline specific resistance A is unknown, it is possible to use the value of the hydraulic friction coefficient L for the pipeline of the corresponding material and the diameter d (m). From the Darcy-Weisbach formula (4) it follows: H = L(l/d) · 8Q 2 /π2 d 4 g = 8LQ2 l/π2 d 5 g
(4)
When transporting the water, i.e., at ρ = 1000 kg/m3 , g = 9.81 m/s2, as well as based on the results of mathematical operations of converting H, the basic calculation formula for determining the electricity consumption is written in the form (5): E = 0.81 · Q 3 · l · L · 24 · 365/ d 5 · η p
(5)
3 Results and Discussions The results of the first stage of the research were the determination of an array of experimental values of the hydraulic friction coefficient Lo for the corresponding values of the transported water flow rate. For example, at a water flow rate of Q = 0.0043 m3 /s, the Lo was 0.02305 (see Table 1). The results of the second stage of the research consisted in getting and analyzing the ratio of the experimental Lo and the design coefficients of hydraulic friction L depending on the temperature conditions, in particular, on the temperature of the pipeline wall at a stable temperature of the transported water. The Table 1 shows in a simplified form the input and output information based on the results of an automated calculation for an arbitrarily selected water flow rate (Q = 0.0043 m3 /s) and the same water and pipe wall temperatures (16 °C). The analysis of the data in the Table 1 shows the following: at the same temperatures of the liquid and the pipe outer wall (16 °C), as well as within the optimal ranges of the Reynolds numbers Re and the established ratio of the dynamic viscosities Z, the calculated coefficients of the hydraulic friction L differ from the experimental value Lo by X = 6.86%. Also, the tasks of the second stage of research included the analysis of the dynamics of changes in the values of the hydraulic friction coefficient L depending on the pipe wall temperature t. The calculations were carried out at three flow rates: 0.00322 (1), 0.00694 (2) and 0.01303 (3) m3 /s. For each of the modes, the water temperature in the pipeline was assumed to be constant (16 °C). Only the pipe wall
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Table 1 Initial values and the results of the parameters after the automated calculation at the same water and wall temperatures in the pipeline Initial values
Calculation results
Water flow temperature t w , °C
16.0
Temperature of the pipe wall t t , °C
16.0
Coefficient of hydraulic friction for the accepted flow rate (from experiments)
0.02305
Dynamic viscosity coefficient related to the fluid flow ηw , Pa·s
1.13151·10–3
Dynamic viscosity coefficient related to the temperature of the pipe wall ηt , Pa·s
1.13151·10–3
The ratio of dynamic viscosities Z (ηw /ηt )
1.0
Coefficient of kinematic viscosity of the liquid ν,
m2 /s
1.096·10–6
Reynolds number Re
0.4477381·105
Design coefficient of hydraulic friction for the accepted flow rate L
0.021469
The ratio of the design and experimental values of the hydraulic friction coefficients X, %
6.86
Hydraulic friction coefficient (calculated) L
temperature from 9.5 to 61.5 °C was subject to a step-by-step change, which corresponded to the strict limits for maintaining the recommended parameters for Z, i.e. in the range of 0.839–2.498 and the Reynolds numbers (Re) in the established interval of 2.8·104 –4.5·105 . Based on the results of the automated calculation, the dynamics of the change in the value of L was tracked, which is illustrated by the graphical dependencies in the Fig. 1.
0.02 0.018 0.016 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0
L=-0,0019Ln(t) + 0,0227 L=-0,0018Ln(t) + 0,0214 L=-0,0016Ln(t) + 0,0199
0
20
40
60
80
Pipe wall temperature t, degrees Celsius Fig. 1 Dependence of the hydraulic friction coefficient on the dynamic viscosity related to the pipe wall temperature: upper, middle and lower curves, respectively, for flow rates (1), (2) and (3)
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The curves shown in the Fig. 1 indicate the identical nature of the change in the hydraulic friction coefficient from the temperature for the corresponding water flow rates. With an increase in the temperature of the pipeline wall, the coefficient of hydraulic friction decreases at all water flow modes by about 20.6–23.5%, which can be described as a positive effect: when the pipeline is heated, the hydraulic resistance to the movement of the liquid decreases. The results of the third stage of the research were the search for the temperature areas of the pipeline wall and the transported water, at which the minimum electricity consumption is provided. To implement this task, on the basis of the obtained mathematical dependencies presented in the graph of the Fig. 1, a search calculation of the dynamics of the change in the coefficient L has been performed for the three above-mentioned values of water flow rates with a sample array of pipe wall temperatures: 9.5; 15; 30; 45; 61.5 °C. Based on the data obtained from the results of the automated complex, the Figs. 2, 3 and 4 show sample curves of electricity consumption described by linear dependencies. Summarizing the data presented in the graphs of Figs. 2, 3 and 4, we can draw a number of basic conclusions regarding the water rates and the electricity consumption with a constant pipe diameter:
Electricity consumption E, kWh
– the higher the flow rate of the transported water and the lower the temperature of the pipeline wall, the greater the energy consumption for the water transportation; for example, for the Fig. 2, the E value at the pipe wall temperature of 9.5 °C is 1.45 kW·h, and for the Fig. 4, about 22.45 kW·h;
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
E=-0,0005t + 1,4561 E=-0,00012t + 1,2889 E=0,0003t + 1,1227
0
20
40
60
80
Water temperature t, degrees Celsius
100
Fig. 2 Graphs of electricity consumption with an illustration of the temperature range of water and the pipeline wall at a flow rate of transported water Q = 0.00322 m3 /s and a water temperature of 8–77 °C (the blue curve for the pipe wall temperature of 9.5, the red curve of 30 and the green curve of 61.5 °C)
Electricity consumption E, kWh
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5 4 3 E=-0,0027t + 3,9718
2
E=-0,0003t + 3,5425
1
E=0,0007t + 3,1182
0
-10
10
30
50
70
90
Water temperature t, degrees Celsius
Electricity consumption E, kWh
Fig. 3 Graphs of electricity consumption with an illustration of the temperature range of water and the pipeline wall at a flow rate of transported water Q = 0.00694 m3 /s and a water temperature of 2–77 °C (the blue curve for the pipe wall temperature of 9.5, the red curve of 30 and the green curve of 61.5 °C)
-10
25 20 15
E=-0,0122t + 22,946
10
E=-0,0017t + 20,618
5
E=0,0037t + 18,285
0 10
30
50
70
90
Water temperature t, degrees Celsius Fig. 4 Graphs of electricity consumption with an illustration of the temperature range of water and the pipeline wall at a flow rate of transported water Q = 0.01303 m3 /s and the water temperature of 2–77 °C (the blue curve for the pipe wall temperature of 9.5, the red curve of 30 and the green curve of 61.5 °C)
– the higher the temperature of the transported water, the less electricity is consumed and there is a greater calculated range of potential effective control of the pipeline system, which can be estimated by different length of the power consumption curves. Summing up the results of the graphic material analysis, it can be noted that in the future, the piping utility managers, having automated calculation data or optimal areas of operation of the pipeline system obtained on their basis, can provide optimal values of electricity consumption for the corresponding option of the pipeline system operation, including at different values of the efficiency of pumping units.
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The calculated data enable identification of certain trends for two cases: at a stable water temperature of 16 °C (the first case) and a stable pipeline wall temperature of 16 °C (the second case). The essence of the results obtained for the first case can be interpreted as follows: • when a relatively large amount of the transported water Q = 0.01303 m3 /s and a stable temperature t w = 16 °C, as well as the temperature growth of the pipe wall within the range of 12–25 °C, there is a decrease in electricity consumption in the range respectively from 22.442 to 20.993 kW·h, i.e. of 6.5%; at the temperature growth of the pipe wall the trend continues until 61.5 °C; at this temperature the electrical power consumption is reduced to 18.368 kW·h, i.e. the total reduction is 18.15%; • with an average water rate Q = 0.00694 m3 /s and the same temperature conditions, a decrease in electricity consumption is in the range, respectively, from 3.878 to 3.617 kW·h, i.e. 6.7%; the absolute values of the electricity consumption steadily decrease with the growth of the pipe wall temperature within the specified range of 21.957/3.789 = 5.8 times; when the temperature of the pipe wall goes up to 61.5 °C, under the other equal conditions, there is a continuing trend of lower values of the electricity consumption to 3.132 kW·h, i.e. by 19.24% of the initial value within the considered range (12–61.5 °C); The essence of the results obtained for the second case can be interpreted as follows: • with a relatively large water flow rate Q = 0.01303 m3 /s, a stable pipe wall temperature t t = 16 °C and the temperature range of transported water within 12–25 °C, a relatively constant electricity consumption is observed in the range from 21.974 to 21.964 kW·h, respectively, i.e. the difference is about 0.05%; an increase in the temperature of the transported water over 25 °C does not allow for an estimate of electricity consumption by calculation and analysis, since the design values of the hydraulic indicators go beyond the established values; • with a medium water flow rate of Q = 0.00694 m3 /s, a stable pipe wall temperature of t t = 16 °C for the temperature range of the transported water within 12–25 °C, there is an almost constant energy consumption at the level of 3.78–3.79 kW·h; any increase in the temperature of the transported water does not allow for correct calculations, since the hydraulic indicators go beyond the established values; Analyzing the possibility of the energy saving process control at a stable temperature of the pipe wall of 16 °C in the range of the above mentioned rates (0.01303–0.00322 m3 /s), it is possible to make the following conclusions (recommendations): – the pipeline system operation control process as to determination of the expected amount of the electricity consumption becomes very limited and is possible only in the temperature range of the transported water from 12–25 °C; – when the water temperature increases, the calculated parameters of the hydraulic characteristics go beyond the established values.
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4 Conclusions 1. Provision has been made of a comprehensive analysis of operation of a UPVC pipeline of a given diameter aimed at determining its hydraulic characteristics and the electricity consumption in wide temperature ranges of the pipe wall, the transported water and its flow rate. 2. It has been established that the analytical monitoring of the electricity consumption modes by the pipeline systems is possible within certain temperature ranges of the pipe wall and the transported water. 3. An attempt was made to assess the possibility of the process control of ensuring energy savings during the water transportation under various temperature conditions by using automated complexes, as well as the recommendations developed based on the calculation results. 4. The temperature limits were determined, that allow public utility pipeline managers to provide an effective control of the water transportation procedure with the minimal energy consumption.
References 1. Khramenkov SV (2012) Time to manage water. M.: Publishing House Moscow textbooks and cartolithographyb, p 279 2. Rameil M (2007) Handbook of pipe bursting practice. Vulkan verlag, p 351 3. Kuliczkowski A (2012) Renovation or reconstruction on the example of water and sewage pipes. INSTAL 1:46–49 4. Orlov VA, Averkeev IA, Koblova EV (2013) Hydraulic component of alternative materials of pipes and protective coatings during trenchless renovation of pressure pipelines. Water Supply Sanit Tech 6:22–26 5. Pimentel Gomes H, de Farias PASS et al (2020) Efficiency indicator for assessment of water distribution networks carrying capacity. Env Eng Manag J 19(5):747–753 6. Todera¸sc M, Iordache V, Petcu C, Petran H (2019) Real time monitoring of indoor environment quality and energy consumption in a residential building. Env Eng Manag J 18(7):1391–1620 7. Orlov VA (2020) Pipeline networks. S-Pb.: Publishing House LAN, p 159 8. Leznov BS (2006) Energy saving and adjustable drive in pumping and blower installations. M.: Publishing House Energoatomizdat, p 359 9. Orlov VA (2021) Trenchless technologies and energy saving. M.: Publishing House ASV, p 159 10. Grossmann S, Lohse D (2017) Curvature effects on the velocity profile in turbulent pipe flow. Eur Phys J E 40:16–19 11. Ilyasov DZh, Aginey RV (2020) Experimental assessment of the influence of fluid flow vortices on the hydraulic resistance of the pipeline. E3S Web Conf 1(81):40–47 12. Samarin OD (2016) Building a universal dependence for pressure losses in pipelines. J Plumb Heat Air Condition 1(169):24–25 13. Altshul AD (1982) Hydraulic resistances. M.: Publishing House Nedra, p 224 14. Sukharev MG, Karasevich AM, Samoilov RV, Tverskoy IV (2005) Investigation of hydraulic resistance of polyethylene pipelines. Eng Phys J 78(2):136–144 15. Chesnokov YuG (2017) New formulas for calculating the flow characteristics of a liquid or gas in a circular cross-section pipe. Eng Phys J 90(4):1005–1011
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16. McKeon BJ, Zagarola MV, Smits AJ (2005) A new friction factor relationship for fully developed pipe flow. J Fluid Mech 538:429–443 17. Avci A, Karagoz I (2009) A novel explicit equation for friction factor in smooth and rough pipes. ASME J Fluid Eng 131(6):061203 18. Ghanbari A, Farshad FF, Reice HH (2011) Newly developed friction factor correlation for pipe flow and flow assurance. J Chem Eng Mat Sci 2:83–86 19. Fang X, Xu Y, Zhou Z (2011) New correlations of single-phase friction factor for turbulent pipe flow and evaluation of existing single-phase friction factor correlations. Nucl Eng Des 241:897–902 20. Zotkin SP, Orlov VA (2013) Program of analysis of hydraulic characteristics of pressure pipelines. Certificate of State registration of computer programs No. 2013610520 dated 09.01.2013 21. Orlov VA, Zotkin SP, Inshakova MA, Peterburgsky DA (2020) Calculation of hydraulic parameters of pressure pipes when changing temperature regimes. Certificate of state registration of the computer program No. 2020661754 dated of 30.09.2020
Discrete-Continuous Approach to the Moisture Transfer in Building Enclosures Kirill Zubarev
Abstract In the field of the moisture regime of the enclosing structure, there are methods for assessing the stationary moisture state that have a rather low calculation accuracy, as well as methods for assessing the unsteady-state moisture regime which cannot be implemented without using numerical methods and a computer. Based on the introduced scale of the moisture potential F, a new mathematical model of heatmoisture transfer has been developed. The equation of moisture transfer has been derived on the basis of the theory of potential importance. The boundary conditions of moisture exchange of the third kind have been described. A method for calculating enclosing structure moisture regime using a discrete-continuous approach is proposed, and the final formula that allows one to determine the distribution of the moisture potential has been derived. The distribution of moisture over the thickness of the enclosing structure is calculated for a single-layer wall structure made of aerated concrete and a multilayer wall with a clay brick base and silicate brick cladding. Mathematical modeling of the walls moisture state was made according to three separate methods based on the theory of moisture potential. It is shown that the current engineering method for assessing moisture regime gives an error of 21.13% compared to the numerical method that has an error of only 2.39%. Thus, it was concluded that the proposed method using the discrete-continuous approach could be implemented into the construction industry. Keywords Transport infrastructure · Moisture · Heat and moisture transfer · Moisture determination · Moisture potential · Mathematical modeling · Construction materials · Thermal insulation K. Zubarev (B) Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, Moscow 129337, Russia e-mail: [email protected] Research Institute of Building Physics of Russian Academy of Architecture and Construction Science, 21, Lokomotivny proezd, Moscow 127238, Russia Peoples’ Friendship University of Russia (RUDN University), 6, Miklukho-Maklaya Street, Moscow 117198, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_152
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1 Introduction 1.1 Moisture Regime of Enclosing Structures in the Construction Industry The humidity regime of the building envelopes is one of the most intricate questions in the construction industry. Despite the overall development of science in the sphere of humidity conditions, the equation of moisture transfer that takes into account all the properties of moisture transfer is still not found [1]. The complexity of moisture transfer is connected with the fact that moisture transfer depends on the type of moisture-material bond: moisture can be present as a frozen or non-frozen substance, as well as liquid or vapor [2]. The water vapor transfer can be performed by means of the specific mechanisms of moisture transfer, for example, under the action of a water vapor gradient, a liquid moisture gradient, a temperature gradient, an air filtration gradient, or depending on their combination [3]. The humidity field is closely connected with the temperature field, which also affects moisture transfer. As a result, modern scientists are forced to work with mathematical models that describe only part of the processes that affect moisture transfer [4]. The applied value of the humidity regime is large. The humidity regime affects the heat-protective envelope of the building [5], heat losses [6] and the enclosing structure durability [7]. All that is complicated by the development of new architectural and design solutions in modern construction sphere, which leads to creation of new types of heat carrier connections [8, 9]. New materials are being implemented into current solutions for enclosing structures [10]. In science laboratories, building materials are undergoing certification and investigation tests to determine the moisture movement rate in various states. The experimental equipment itself is also being improved and developed [11, 12].
1.2 Theoretical Studies in the Field of Humidity Regime of the Enclosing Structure There are two types of mathematical models of the heat-humidity regime: models that take into account the movement of moisture under the influence of partial transfer potentials and models based on the theory of moisture potential. In the latter, moisture transfer occurs under the single transfer potential that is called the moisture potential. It is also possible to single out mathematical models of moisture transfer, where part of the transfer potentials is replaced by the moisture potential, whereas other potentials be described by the partial moisture transfer potentials [13]. Mathematical model of K.F. Fokin that takes into account the transfer of vaporous and liquid moisture can be set as an example of moisture transfer mathematical model based on separate registration of transfer potentials [14, 15].
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The basis of the temperature field of the mathematical model is the differential equation of thermal conductivity in a stationary setting [14, 15]: ∂ ∂ (λ · ) = 0 ∂x ∂x
(1)
where t—temperature, °C; x—coordinate, m; λ—thermal conductivity coefficient, W/(m·°C). At the edges of the enclosing structure, the boundary conditions of heat transfer of the third kind are set [14, 15]: ∂t −λ = αext (text − t1 ) (2) ∂ x i=1 ∂t λ = αin (tin − t N ) (3) ∂ x i=N where text —outside air temperature, °C; tin —inside air temperature, °C; t1 —temperature of enclosing structure section which contacts with outside air, °C; t N —material temperature near enclosing structure surface which contacts with inner air, °C; αin —heat exchange coefficient between inside air and enclosing structure surface, W/(m2 ·°C); αext —heat exchange coefficient between outside air and enclosing structure surface, W/(m2 ·°C). The moisture field is described by the following differential equation of moisture transfer [14, 15]: γ0
∂ ∂w ∂ ∂e ∂w = (β(w) )+ (μ ) ∂τ ∂x ∂x ∂x ∂x
(4)
where β—moisture conductivity coefficient, kg/(m·s·kg/kg); e—water vapor partial pressure, Pa; μ—vapor permeability coefficient, kg/(m·s·Pa); γ0 —dry material density, kg/m3 ; w—material moisture, % by weight; τ—time, s. On the right-hand side of the Eq. (4), there are two transfer potentials at once: the gradient of the partial pressure of water vapor and the gradient of liquid moisture. The disadvantage of the Eq. (4) is the inability to solve it analytically. Also, to work with the differential equation of moisture transfer (4), it is necessary to set the boundary conditions for moisture exchange of the third kind [14, 15]: ∂e −μ1 = βext (eext − e1 ). ∂ x i=1 ∂e μ2 = βin (ein − e N ). ∂ x i=N
(5) (6)
where eext —partial pressure of inside air water vapor, Pa; ein —inside air partial pressure, Pa; e1 —partial pressure of water vapor which contacts with outside air of the
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enclosing structure section, Pa; e N —partial pressure of material water vapor which contacts with inside air of enclosing structure surface, Pa; μ1 —vapor permeability coefficient of enclosing structure layer which is the nearest to the building outside surface, kg/(m·s·Pa), μ2 —vapor permeability coefficient of enclosing structure layer which is the nearest to the enclosing structure inner surface, kg/(m·s·Pa); βext —moisture exchange coefficient of outside air and enclosing structure surface, kg/(m2 ·s·Pa); βin —moisture exchange coefficient of inside air and enclosing structure surface, kg/(m2 ·s·Pa). H.M. Künzel model is an illustration of the mathematical model based on the theory of moisture potential [16, 17]. Within the present model, apart from using the moisture potential, the influence of the moisture field on the temperature field is taken into account by introducing an additional term into the differential equation of thermal conductivity [16, 17]: d H ∂T · = ∇(λ∇T ) + r · ∇(μ · ∇(ϕ E t )). dT ∂τ
(7)
where H—enthalpy, J/m3 ; ϕ—relative air humidity; T—absolute temperature, K; E t —saturated water vapor pressure, Pa; r—specific heat of the liquid–vapor phase transition, J/kg. H.M. Künzel moisture transfer equation can be represented as [16, 17]: dW ∂ϕ · = ∇(Dϕ ∇ϕ + μ · ∇(ϕ E t )) dϕ ∂τ
(8)
where W —material moisture content, volume percentage; Dϕ —liquid moisture transfer coefficient, kg/(m·s).
1.3 The Problem Create a mathematical model of moisture transfer based on the theory of moisture potential and obtain an analytical expression for the distribution of moisture potential using a discrete-continuous approach.
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2 Methods 2.1 Derivating the Moisture Transfer Equation and Formulating the Mathematical Model of Heat-Moisture Transfer Using the Moisture Potential Theory Moisture transfer equations are usually derived using Fick’s second law. In the present work, as a basis for the differential equation of moisture transfer it is proposed to use the moisture potential F of V.G. Gagarin and V.V. Kozlov that takes into account the liquid moisture transfer in the excess sorption zone of humidification and moisture transfer presented as water vapor in the sorption zone of humidification. An example of the moisture potential scale for a silicate brick is illustrated (Fig. 1) [15]. In Fig. 1, the X-axis is showing the potential moisture F, Pa, while the Y-axis is showing the moisture content of the building material in % by weight. Lines 1, 2, 3, 4, 5, 6, 7 are isotherms. Thus, the moisture potential F is a function of the two variables, namely moisture and temperature. A separate moisture potential scale can be defined for each building material. The moisture gradient has been known to be proportional to the transfer potential. In this case, the transfer potential is the moisture potential F. Therefore, the following equation can be written as: γ0
∂ ∂ F(w, t) ∂w = − (−μ ). ∂τ ∂x ∂x
(9)
where F—moisture potential, Pa.
Fig. 1 The moisture potential scale of lime brick using the Gagarin’s and Kozlov’s moisture potential F (1 - −10 °C; 2 - −5 °C; 3 - 0 °C; 4 - 5 °C; 5 - 10 °C; 6 - 15 °C; 7 - 20 °C) [15]
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Since the moisture potential is a complex function, the derivative of moisture with respect to time will be revealed according to the following expression. ∂w ∂w ∂ F(w, t) ∂w ∂t = · + · ∂τ ∂ F(w, t) ∂τ ∂t ∂τ
(10)
The Eq. (10) is substituted into the Eq. (9): γ0 ·
∂w ∂w ∂t ∂ F(w, t) ∂ ∂ F(w, t) · + γ0 · · = − (−μ ) ∂ F(w, t) ∂τ ∂t ∂τ ∂x ∂x
(11)
To simplify the Eq. (11), the influence of the derivative of humidity with respect to temperature is neglected, i.e.: ∂w = 0. ∂t
(12)
Thus, owing to substituting (12) into (11), the differential equation is significantly simplified: γ0 ·
∂ F(w, t) ∂ ∂ F(w, t) ∂w · = − (−μ ) ∂ F(w, t) ∂τ ∂x ∂x
(13)
For the sake of simplicity, let us consider a single-layer enclosing structure. The right term of the Eq. (13) is simplified, since the vapor permeability of the building material does not change within the layer, i.e. the Eq. (13) can be rewritten as: γ0 ·
∂ F(w, t) ∂ 2 F(w, t) ∂w · =μ ∂ F(w, t) ∂τ ∂x
(14)
To simplify the differential equation of moisture transfer, the function of the moisture potential is substituted into the left side of Eq. (14). After transforming the resulting equation, the following expression can be obtained: ∂ F(w, t) ∂ 2 F(w, t) = κ F (w, t) · E t (t) · ∂τ ∂x
(15)
where κ F —heat-humidity characteristic coefficient, m2 /(s·Pa). The resulting Eq. (15) is the differential moisture transfer equation used in this mathematical model. For the Eq. (15), boundary conditions of the third kind based on the theory of moisture potential are applied: 1 ∂ F = (Fext − F1 ) μ ∂ x x=0 Rm.ext
(16)
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∂ F 1 = (Fin − FN ) ∂ x x=l Rm.in
(17)
where κ F —heat-humidity characteristic coefficient, m2 /(s·Pa). Rm.in —resistance to moisture exchange between inner air and enclosing structure surface, (m2 ·s·Pa)/kg; where Rm.ext —resistance to moisture exchange between outer air and enclosing structure surface, (m2 ·s·Pa)/kg; Fext —outer air moisture potential, Pa; Fin —inner air moisture potential, Pa; F1 —material moisture potential in enclosing structure section in contact with outer air, Pa; FN —material moisture potential in enclosing structure section in contact with inner air, Pa. The relationship between the temperature and humidity fields occurs via the dependence: E t = 1.84 · 1011 · e− 273+t . 5330
(18)
2.2 Solving the Non-stationary Moisture Transfer Equation Using the Discrete-Continuous Approach The moisture transfer Eq. (15) can be solved using a numerical method. Nevertheless, it is infeasible to find its analytical solution due to the dependence of the coefficient of heat and moisture properties of the material κ F (w, t) on such characteristics as mass moisture and temperature. Thereby, the moisture transfer Eq. (15) can be rewritten as: ∂ 2 F(w, t) ∂ F(w, t) = κ F0 · E t (t) · . ∂τ ∂x
(19)
where κ F0 —average heat-humidity characteristic coefficient, m2 /(s·Pa). This transformation enables us to apply a discrete-continuous [18–20] to the Eq. (19) and determine its numerical-analytical solution in matrix form: F = p · ((E t · A)−2 · e Et ·A·τ − τ · (E t · A)−1 − (E t · A)−2 ) · L + (E t · A)−1 (e Et ·A·τ − E) · B + e Et ·A·τ · F 0 .
(20)
3 Results Mathematical modeling of a multi-layer building envelope made of clay brick masonry with silicate brick cladding was made (Fig. 2).
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Fig. 2 Mathematical modeling of the moisture state of a multilayer enclosing structure (1—mathematical modeling of a non-stationary moisture regime using the numerical method; 2—mathematical modeling of a non-stationary moisture regime using a discrete-continuous approach according to formula (20); 3—mathematical modeling of a stationary moisture regime; 4 is the boundary between the layers)
4 Discussion As can be seen from the graphs, moisture distribution according to the proposed method based on the discrete-continuous approach coincides both quantitatively and qualitatively with the moisture state of the enclosure that was obtained by the numerical method in mathematical modeling. This coincidence is observed both across the thickness of a single-layer enclosing structure of a building wall made of aerated concrete and across the thickness of a multi-layer enclosure with a clay brick base and silicate brick cladding. Moreover, both quantitative and qualitative coincidence is registered throughout a year. Moisture state of the enclosing structure made of aerated concrete was compared using three different methods of the theory of moisture potential F for January as the coldest and the most interesting month for research, since the greatest heat losses occur in January. The results of above mentioned comparison of the moisture state of the enclosing structure made of aerated concrete obtained using three different methods of the theory of moisture potential F (Table 1) are presented. Thus, the effectiveness of the proposed method for assessing the unsteady humidity regime using the discrete-continuous approach is proved. Consequently, it can be noted that the numerical method by the Eq. (15) shows the highest calculation accuracy. The discrepancy between the results of mathematical modeling by the numerical method and by the stationary method for calculating the moisture regime of the enclosing structure for January is 21.13%. Thereby, current engineering method for determining the moisture state leads to a raw error. A discrepancy between the proposed estimation method using the discrete-continuous approach according to the analytical expression (20) and the stationary method is only 2.39%, which confirms its potency.
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Table 1 The comparison results of the moisture state of the enclosing structure made of aerated concrete obtained by three different methods of the theory of the moisture potential F Method for assessing the moisture Month selected for state of the building envelope comparison
Average moisture value w, % by weight
Mathematical modeling of a non-stationary moisture regime using a numerical method
January
4.18
Mathematical modeling of a non-stationary moisture regime using a discrete-continuous approach
January
4.08
Mathematical modeling of stationary humidity regime
January
5.30
5 Conclusions The described mathematical model is based on fundamental physics and mathematics and uses the moisture potential F as its basis, which uniformly takes into account the movement of liquid and vaporous moisture. The mathematical model is based on the differential equation of moisture transfer, the equation of stationary thermal conductivity, the equation connecting the saturated water vapor pressure and temperature, boundary conditions of heat transfer and moisture exchange of the third kind at the edges of the structure. A new effective method for assessing the unsteady humidity regime by analytical expression (20) using the discrete-continuous approach has been developed. The method given can operate without applying numerical methods and can be used by design engineers. Moreover, as it has a significantly smaller error in assessing the unsteady humidity regime in comparison with the existing stationary methods, it can be implemented into engineering practice.
References 1. Kaczorek D (2019) Moisture buffering of multilayer internal wall assemblies at the micro scale: experimental study and numerical modelling. Appl Sci-Basel 9:3438 2. Ferrari S, Riva A (2019) Insulating a solid brick wall from inside: heat and moisture transfer analysis of different options. J Archit Eng 25:04018032 3. Nizovtsev MI, Letushko VN, Borodulin VYu, Sterlyagov AN (2020) Experimental studies of the thermo and humidity state of a new building facade insulation system based on panels with ventilated channels. Energy Build 206:109607 4. Borodulin VYu, Letushko VN, Nizovtsev MI, Sterlyagov AN (2019) The experimental study of evaporation of water–alcohol solution droplets. Colloid J J Phys Conf Ser 1359:012044 5. Vieira GB, Petrichenko MR, Musorina TA, Zaborova DD (2018) Behavior of a hollowed-wood ventilated façade during temperature changes. Mag Civil Eng 3(79):103–111 6. Zaborova D, Vieira G, Musorina T, Butyrin A (2017) The building extension with energy efficiency light-weight building walls. Adv Intell Syst Comput 692:482–489
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7. Shen X, Li L, Cui W, Feng Y (2018) Coupled heat and moisture transfer in building material with freezing and thawing process. J Build Eng 20:609–615 8. Bespalov V, Kotlyarova E, Adamyan R (2020) Scientific and methodological principles of forming an assessment of the level of environmental safety of construction projects in urban areas. E3S Web Conf 193:02007 9. Bespalov V, Kotlyarova E (2020) Methodological bases for assessing the level of environmental safety of dynamically developing urbanized territories. IOP Conf Ser Mat Sci Eng 1001:012101 10. Qu K, Chen X et al (2021) Comprehensive energy, economic and thermal comfort assessments for the passive energy retrofit of historical buildings - a case study of a late nineteenth-century Victorian house renovation in the UK. Energy 220:119646 11. Petrov A, Ivantsov A (2020) Design and calculation of the internal roof drain system structure in terms of thermal protection and moisture condensation. IOP Conf Ser Mat Sci Eng 890:022141 12. Petrov AS, Kupriyanov VN (2016) Variable value of the vapor permeability of materials under operating conditions and its influence on the prediction of the moisture state of building envelopes. Int J Pharm Tech 8(1):11248–11256 13. Arfvidsson J, Claesson J (2000) Isothermal moisture flow in building materials: modelling, measurements and calculations based on Kirchhoff’s potential. Build Env 35(6):519–536 14. Zubarev KP (2021) Using discrete-continuous approach for the solution of unsteady-state moisture transfer equation for multilayer building walls. Int J Comput Civil Struc Eng 17(2):50– 57 15. Gagarin VG, Zubarev KP, Akhmetov VK (2018) Unsteady-state moisture behavior calculation for multilayer enclosing structure made of capillary-porous materials. IOP Conf Ser Earth Environ Sci 177:012021 16. Guimaraes AS, Ribeiro IM, Freitas TS (2018) Numerical models performance to predict drying liquid water in porous building materials: comparison of experimental and simulated drying water content profiles. Cogent Eng 5(1):1–14 17. Kaczmarek A, Wesolowska M (2017) Factors affecting humidity conditions of a face wall layer of a heated building. Procedia Eng 193:205–210
Research on Purification of Natural Water to Drinking Quality by Electrocoagulation Yuriy Bebikhov
and Alexander Semenov
Abstract This article discusses the results of experimental studies of electrocoagulation treatment of natural water on the example of the Northern Territories located in the Republic of Sakha (Yakutia). Various technologies have been compared allowing to treat the source water and achieve drinking quality. A non-convention electrochemical conditioning method was selected for drinking water treatment of surface waters of a certain river, which allows obtaining high-quality drinking water corresponding to the requirements of relevant standards without the need to apply chemical reagents. The effectiveness of electrochemical treatment of water systems of the Northern Territories with low mineral content has been confirmed experimentally. The optimal conditions for electrochemical conditioning of the studied water have been selected and substantiated. Installation components and their parameters were developed to implement the electrocoagulation method in the conditions of the Northern Territories, as well as separating the installation into separate modules with different characteristics. Keywords Electrocoagulation · Northern Territories · Water treatment · Conditioning · Clarification · Disinfection · Energy efficiency in transportation
1 Introduction The major part of the Northern Territories of the Republic of Sakha (Yakutia) is located in permafrost region. This aspect has a fundamental effect on the quality of the natural water in rivers and lakes, as well as artificial reservoirs [1]. Filtering through the soil, flood water and thawing permafrost are saturated with humic substances and Y. Bebikhov Thermal Water Supply Company of PJSC ALROSA, 6 Lenin Street, Mirny 678170, Russian Federation Y. Bebikhov · A. Semenov (B) Ammosov North-Eastern Federal University, 58 Belinskiy Street, Yakutsk 677000, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_153
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get yellow–brown color. The water color index reaches the values of 100–200°, and in certain regions—400–500°. In winter, when there’s practically no runoff, the color index of water under the ice is reduced to 70–80°. The water of the northern territories is natural water with low mineral content, low content of suspended solids and high color index, low temperatures [2], which results in specific requirements and complexity of water treatment to bring its composition and properties to the requirements of sanitary regulations and standards. The main disadvantage of known treatment methods applied to natural waters is the use of significant quantities of various chemical reagents [3], which increases the water treatment costs due to the increased production and transportation costs, as well as the need for drinking water disinfection by chlorination to kill pathogenic microorganisms [4]. It is known that during water chlorination, up to 50 organochlorine compounds may form including chloroform, carbon tetrachloride, trichloroethane, which have carcinogenic and mutagenic effects [5]. The existing reagent-based water treatment techniques are aimed mainly at clarification and disinfecting the natural waters, which color index is affected by humic substances. Humic substances bind and lead to the accumulation of various metals from the earth resulting in the migration of metal ions into the soil in the form of stable compounds, which are almost impossible to be removed [6]. A wide range of molecular masses and specific properties of humic acids complicates the process of clarification and removal of toxins from natural waters using chemical coagulants. Based on the foregoing, this article presents experimental studies of the intensification of natural water clarification, suspended solids removal and disinfection processes using electrocoagulation method. During the experiments, the optimal operating conditions were determined for the process equipment units and different equipment performance levels, a control testing of the developed method has been conducted in the hydrologic system of the Matta River near the Berdigestyakh village located in the Republic of Sakha (Yakutia). Currently, the technologies of the drinking water preparation and clarification proposed by a number of foreign and domestic companies can be divided into the following main categories—reagent-based coagulative [7, 8], membrane [9–11], catalytic [12, 13], sorption [14, 15], ultrasound, electrochemical [16], combined. Furthermore, despite the various physical and chemical processes being the based for all these technologies, they can be roughly divided into two groups—reagentbased technologies [17] and technologies without reagent application [18]. In [19, 20], the designs of drinking water treatment installations are discussed in detail.
2 Materials and Methods The experiment was conducted using an electrolysis cell (electrolyzer) representing a plexiglass assembly containing electrodes made of St3 steel. The electrodes are installed with alternating polarity at a certain distance and are connected to a 50 V 30 A DC power source. The custom-made power source consists of a variable transformer and a rectifier unit (rectifying bridge). The power source has output voltage
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and current controls. The power source allows smoothly changing the output voltage and current over a wide range, which is a prerequisite for this experiment. To determine the optimal clarification conditions, the current density α (A/m2 ) and treatment time t (sec) were changed, and the experiment is considered positive when the color index β (degrees) and suspended solids γ (mg/l) are reduced to 20 and 0.6, respectively, or below in the number of experiments n. This condition can be represented mathematically in the following form: ⎧ ⎫ ⎨ α = (30; 50; 80; 100; 130; 150) ⎬ β = min(0...204), γ = min(0...1.24) t = (30; 60; 90; 120; 180) . ⎩ ⎭ n = 30
(1)
The current density α is calculated by the formula: α=
I , S
(2)
where I is the current (A); S = 0.065 m2 is the active area of the electrodes. The distance between the electrodes was changed stepwise from 4 to 12 mm through the experiment, which allowed to expand the studied conditions and obtain a denser range of values for detailed analysis. The experiment was conducted as follows: 250 ml of the source water was measured using a measuring cup, the measured water was poured into the electrolyzer and the current was fed to the electrolyzer electrodes with the required current value set using the adjustment knob. After that, the electrochemical treatment process was measured by the timer before turning off the current supply. The clarification effect is determined after 30 min of settling. To determine the clarification effect, the settling time is recorded per the volume change dynamics, specifically by the visible boundary of the medium separation. The results of water sampling with the subsequent express analysis of two indicators (color index, suspended solids) are presented in Figs. 1(a–c). Analysis of curve change patterns in these graphs shows that color index and suspended solids decrease with the increase in current and source sample treatment time. The “standart” line marks the limits of the permissible color index in accordance with the requirements of SanPiN 2.1.4.1074-01 “Drinking water. Hygienic requirements for water quality of centralized drinking water supply systems. Quality control”. The effect of distances between the electrodes on the electrochemical treatment of source water was also investigated (Fig. 1(d)). During experiments, the distance between the electrodes was periodically changed and the indications of power source monitoring devices were recorded. Figure 1(d) shows that the dependence of the voltage on electrodes on the current density is linear. With an increase in the distance between the electrodes, the trend line inclination angle to the abscissa increases, while the power of the electrolysis process can be calculated by formula (3), which states that the consumed power grows with the voltage increase at constant current:
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(a)
(b)
(c)
(d)
(e)
(f)
Fig. 1 Dependence of water color index on treatment time t at different current density α (a); dependence of water color index on current density α at different treatment time t (b); dependence of suspended solids on treatment time t at different current density α (c); dependence of the voltage of the electrolysis process on the current density at the electrodes and the distances between them (d); electrictrolyzer power consumption by experiment group at the same current density (e); area of “performance—power” solutions allowing to obtain a specific final color index (f)
N = U · I,
(3)
where U is the voltage of the electrolysis process. In Fig. 1(d), the “24 V” and “48 V” bar lines are maximum permissible voltages for water treatment equipment used in household and production conditions, respectively. An area of safe operation conditions is located under these lines. At a 12 mm distance between the electrodes, the maximum possible current density does not exceed 54 A/m2 and 108 A/m2 for household and production conditions, respectively. At an 8 mm distance between the electrodes, the maximum possible current density increases to 85 A/m2 at a maximum voltage of 24 V. The graph of the water color index on current density shown in Fig. 1(d) shows that the minimum
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possible current density α = 33 A/m2 is sufficient to obtain a positive result. Given the high cost of current converters and the related safety requirements, it is preferable to choose a lower voltage for the electrolysis process. At the same time, the distance between the electrodes shall be set to 4 mm minimum, as small distances result in the electrolyzer performance decrease and a faster electrode wearing. In addition, the electrodes are subject to deformation by the electromagnetic interaction forces, which value is inversely proportional to the square of the distance between the electrodes, while there is also a chance of a short circuit along the lower side of the power supply. The obtained results allow concluding that condition (1) is true in most experiments. Analysis of experiments that have positive results at different parameters showed that energy consumption is not equal at the same current density and at different treatment times. Indeed, if the power consumed by the electrolyzer is equal to (3), then the power consumed during the process can be calculated as follows: P=
N ·t , 3600
(4)
where 3600 is coefficient used to convert seconds into hours. As noted above, electrochemical coagulation is a water treatment method that does not use reagents, which is one of its advantages. But at the same time, electrochemical treatment consumes a certain amount of power. Therefore, power consumption can be regarded as the consumption of a certain resource, which leads to a conclusion that the performance of electrochemical coagulation process depends on the consumption of this resource. To compare power consumption during the electrolysis, it is necessary to consider all processes at one voltage. Let us consider the dependence of the voltage on the current density at a distance between the electrodes R = 8 mm as calculated, and graphically find all values of U for each α. Figure 1(e) shows that the color index of the final product is different at an approximately identical energy consumption of the electrolysis process. This is due to the difference in the source water treatment parameters. Conditions with a positive result are located under the “standart” line. The obtained data on the difference in power consumption at different conditions requires adjusting the condition (1). Furthermore, the effect of various conditions on the performance of the electrolysis process shall be studied as well. Condition (1) will take the form: ⎫ ⎧ ⎪ α = (30; 50; 80; 100; 130; 150) ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎬ ⎨ t = (30; 60; 90; 120; 180) . (5) β ≤ 20, γ ≤ 0.6 n = 17 ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ P = min(...) ⎪ ⎪ ⎪ ⎪ ⎭ ⎩ Q = min(...) y
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To build and evaluate the “performance—energy consumption” dependence, let us introduce a conditional performance value inversely proportional to the treatment time t: Qy =
1 · χ, t
(6)
where χ is the consumption coefficient taken equal to 10,000 units in our case. The area of efficient conditions is shown in Fig. 1(f). This figure includes an area with the significantly different performance at a small difference in power consumption. The conditions with the highest possible performance and minimum power costs are of particular interest. All points in Fig. 1(f) satisfy the condition β < 20; γ < 0.6.
3 Results and Discussion For complete physical and chemical treatment an experimental test bench was constructed, shown in Fig. 2(a), where the following elements are designated by reference: 1—sampling cylinder; 2—electrolyzer; 3—DC power supply; 4—cylinder for water settling after electrochemical treatment; 5—coarse-grain filter; 6—sorbent filter; 7—sterilizing lamp; 8—cylinder for collecting water after a complete treatment cycle. Analysis of the results showed that: 1. For the aqueous medium with the mentioned color index, the electrochemical treatment method (at a current density α ≥ 33 A/m2 ) reduces the color index
(a)
(b)
Fig. 2 Process diagram for the electrochemical treatment testing installation (a); stages of source sample treatment. Right to left: a) water after treatment in the electrocoagulation unit; b) coagulation starts, flake formation; c) clarification process; d) finished product (b)
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down to 5–10° (at a normal value of 20). A further increase in current density I practically does not have a significant effect on color index. 2. The optimal time for electrochemical treatment of aquatic media is 2–3 min, as this ensures the maximum reduction of color index at minimum power consumption (current density α = 36–32 A/m2 ). 3. Electrocoagulation occurs within permissible limits when the current density α changes from 32 to 150 A/m2 . 4. The electrocoagulation method provides partial disinfection without the need for dedicated sterilization treatment. The following has been determined: – With an increase in the distance between the electrodes, the energy costs of aquatic medium treatment increase significantly. – Regardless of the installation design, the current–voltage curve is almost linear, while the required voltage of rectifying devices for the studied water at a current of 5–6 A and the distance between the electrodes below 8 mm does not exceed 24 V. Increasing the distance between the electrodes up to 12 mm at the abovementioned current value increases the required voltage on rectifier devices up to 37 V, or by 154%, which requires power sources with greater capacity to sustain the electrochemical water treatment in industrial conditions. – Changing current strength and parameters of electrochemical treatment equipment allows choosing the minimum voltage for the stable flow of the coagulation process. – With approximately equal consumed power, different color index values of the finished product can be obtained at different volumes depending on the process parameters. – With approximately equal consumed power, different volumes of the finished product can be obtained with different color index values depending on the process parameters. The experimental studies were especially focused on water clarification kinetics. The following has been determined: • Large flakes formed in the process of electrochemical coagulation settle after 15–25 min, and the color index of the treated water decreases below 20°. • During 2.5–12 h of settling, the volume of the non-clarified layer is reduced from 250 to 35 ml, depending on the process parameters. • With the consumed power increase, the clarification time decreases nonlinearly. Nonlinearity is associated with the voltage increases at increasing current density. The flaking process and subsequent clarification of the fluid column after treatment in the electrocoagulation unit are shown in Fig. 2(b). Flaking starts in 3 min after the treatment process is finished. Large flakes begin to settle in 7 min after the treatment process is finished. Water is clarified in 30 min after the treatment process is finished. In this case, the cylinder contains a fine suspension and the medium
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separation boundary is clearly visible. A finished product—drinking water is obtained in electrocoagulation unit in seven hours after the treatment process is finished. The study results show that the final color index of water treated using the abovementioned technique is 2–5° (at a regular value of 20 and the initial value of 120–300°) without the need to add any chemical reagents. The cost of natural drinking water treatment using the proposed technology is 2–3 times lower compared to the cost of reagent-based water treatment.
4 Conclusion An experimental device has been made with the electrode area S = 0.065 m2 operating in a steady-state (accumulative) mode allowing to change the following process parameters—the treatment time of the aqueous medium t, distances between the electrodes R, current density α at electrodes. The obtained experimental data were analyzed according to the mentioned method. Such properties of water systems as the color index and suspended solids were determined. The processing results were analyzed, the dependencies of properties were built for aqueous media after treatment by electrochemical method, and were summarized. Thus, to implement the technique of natural drinking water treatment in the Northern Territories on the example of the Republic of Sakha (Yakutia) using the electrochemical method for coagulation, we recommend to include the following main process steps—mechanical filtration, electrocoagulation and disinfection using soluble anodes, subsequent separation of deposit from treated water, control fine filtering and additional disinfection.
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7. Alekseev E, Shambina S (2021) Coagulation of waste water from the point of view of physicchemical interactions. E3S Web Conf 263:04011 8. Kodura A (2016) An analysis of the impact of valve closure time on the course of water hammer. Arch Hydro-Eng Environ Mech 63(1):35–45 9. Jain H, Garg MC (2021) Fabrication of polymeric nanocomposite forward osmosis membranes for water desalination—a review. Environ Technol Innov 23:101561 10. Xue W, Jian M, Lin T et al (2020) A novel strategy to alleviate ultrafiltration membrane fouling by rotating membrane module. Chemosphere 260:127535 11. Nasir AM, Goh PS, Ismail AF (2019) Highly adsorptive polysulfone/hydrous iron-nickelmanganese (PSF/HINM) nanocomposite hollow fiber membrane for synergistic arsenic removal. Sep Purif Technol 213:162–175 12. Thomas N, Dionysiou DD, Pillai SC (2021) Heterogeneous Fenton catalysts: a review of recent advances. J Hazard Mater 404:124082 13. Pletneva IV, Gavrilov YA (2017) Highly active catalysts for oxidation of thiols. ChemChemTech 60(8):70–73 14. Dang TH, Rudakov OB, Khorokhordina EA et al (2020) Application of crushed shells Cristaria plicatato separation cadmium and chromium from polluted water by static sorption. Sorbtsionnye i Khromatograficheskie Protsessy 20(5):556–564 15. Aubakirova R, Daumova G, Seraya N, Afanasenkova I (2020) Sorption extraction of heavy metal ions from wastewater by natural and synthetic sorbents. Chem Eng Trans 81:343–348 16. Bebikhov YV, Semenov AS, Podkamenny YA (2021) Experimental studies of the electrochemical method of water purification in the subarctic territories. Ecol Ind Russia 25(11):24–29 17. Cai QQ, Lee BCY, Ong SL, Hu JY (2021) Fluidized-bed Fenton technologies for recalcitrant industrial wastewater treatment–recent advances, challenges and perspective. Water Res 190:116692 18. Kruse P (2018) Review on water quality sensors. J Phys D Appl Phys 51(20):203002 19. Haldar A, Gupta A (2020) Application of electrocoagulation: issues with community-level defluoridation. Int J Environ Sci Technol 17(2):789–798 20. Kim G, Kim T, Jang J, Akter J, Lee H (2019) Performance characteristics of phosphorus removal in sewage treatment using electrocoagulation and fiber filtration process. Desalin Water Treat 154:141–146
Object Trajectory Tracking in Industrial Building: Coupling of Building Information Modeling and Microwave Radar Technologies Vladimir Badenko , Vladimir Kuptsov , Sergey Ivanov , Alexander Fedotov , Yulia Volkova , and Galina Badenko Abstract Currently, within the framework of the concept of Industry 4.0 and the development of technologies for factories of the future, the development of methods for tracing the trajectories of objects in industrial buildings is an urgent task. The method for trajectory tracking of moving object inside industrial building is proposed. The method is based on coupling of building information modeling and microwave radar technologies. The proposed method has wide application in applications of advanced manufacturing technologies for factories of the future. Keywords Transport infrastructure · Tracking · Microwave radar · BIM technologies · Positioning system · Factories of the future
1 Introduction The development of industry 4.0 technologies has led to the emergence of the concepts of digital, smart and virtual factories of the future with extensive use of cyber-physical systems technologies [1–3]. The development of factories of the future is based on digital twin and smart manufacturing technologies integrated with BIM technologies for industrial buildings that provide industrial infrastructure for modern production [4–6]. It should be noted that modern smart manufacturing extensive use of unmanned technologies, in particular, unmanned vehicles and robots in industrial buildings [7–9]. Therefore, for modern smart manufacturing, the actual problem is the positioning and tracking of unmanned vehicle and robots inside industrial buildings [10, 11]. The main difficulties are related to the fact that while the global positioning systems can be used outdoors the signal from the global positioning system may be lost indoors and other positioning technologies are needed indoors [12, 13]. For indoor positioning can be used different techniques and one of the most popular methods is based on measurements by receiving an electromagnetic signal V. Badenko (B) · V. Kuptsov · S. Ivanov · A. Fedotov · Y. Volkova · G. Badenko Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Street, Saint Petersburg 195251, Russian Federation e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_154
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transmitted by several spatially distributed base stations, taking into account environmental situations inside industrial building [14, 15]. Complete and accurate information about the geometry of an industrial building (3D database) is currently supported by the Building Information Modeling (BIM)-technologies environment [16]. Therefore, an urgent task is to develop a technology based on the integration of methods for positioning objects inside and as-is BIM [17] for existing industrial buildings. It should be noted the important role of laser scanning technologies in creating an accurate three-dimensional model of buildings for BIM technologies [18]. One of the most popular methods for solving of positioning tasks (determination of the object/target coordinates) is TDoA (Time Difference of Arrival) method [19, 20]. TDoA is based on the measurement of the difference in the time of arrival of an electromagnetic signal emitted by an object and received by several base stations (Fig. 1) [15]. The TDoA method is highly accurate, but TDoA requires time synchronization at base stations, and indoors it adds the problem of false targets and reflections from obstacles [21, 22]. Surfaces on which the difference in time of arrival of the microwave signal in the TDoA method to two base stations (BSs) is constant are hyperboloids in 3D space with BSs in their focuses [23]. Therefore, the coordinates of the target can be identified as the intersection of these surfaces. Finding such an intersection is a rather laborious task and therefore approximate methods are often used [24]. In [25] an analytical method which can eliminate the ambiguity in determining of 3D coordinates of a target and improves the accuracy of target position determination using the analysis of TDoA of microwave radar signals [26] from the target to BSs receivers is proposed. Therefore, it is important to accurately determine the position of the base stations. In the case of an industrial building considered here, the base stations must be located on the building structures, and the exact information about the geometric characteristics (coordinates) of the structures is stored in the BIM database. The objective of this work is to develop key points of a method for tracking objects/targets adopted for implementation inside industrial buildings based on microwave radar and BIM technologies. Fig. 1 The principle of localization by TDoA: the green dot indicates the location a target the black dot represents the base stations, di—is the distance between the target and base stations, therefore the target location is estimated by the intersection point of hyperbolas
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2 Method In the method presented below, it is proposed to use the results obtained in our previous work. The exact solution has several advantages over the approximate methods, although noise in the received signal will still be taken into account. To effectively solve problems with the occurrence of false targets and “extra” points, it is proposed to use the BIM database. Let us consider the values of the difference between the arrival times of the TDoA signal from the object between BSi and BS1 , which are the basis for determining the position of the object/target. Then, in the absence of TDoA measurement errors, we have (1): τi1 =
ri − r1 ri1 = , i = 2, . . . M cl cl
(1)
M—amount of BSs, cl —speed of light, r i —distance between object and BSi , r 1 — distance between object and BS1 . The variant of constructing a positioning system in space with 4 BS is economically viable, but at the same time we obtain an ambiguous solution in the form of the intersection of two hyperboloids along two lines in space. Information from the BIM database can help determine the true position of an object, but this is not always possible. To eliminate these shortcomings, it is proposed in [25] to include the fifth BS in the positioning system. If we consider the positioning system, which includes five base stations BSC , BSL , BSR , BSU , BSD (which are receivers of a microwave signal from the object/target), then the coordinates of the object’s position are solutions of a system of hyperbolic Eq. (2): ⎧ ⎪ (x − x L )2 + (y − y L )2 + (z − z L )2 ⎪ ⎪ ⎪ 2 2 2 ⎪ − (x − ⎪ ⎪ xC ) + (y − yC ) + (z − z C ) = c · τ LC ⎪ 2 2 ⎪ ⎪ (x − x R ) + (y − y R ) + (z − z R )2 ⎪ ⎪ ⎨ − (x − xC )2 + (y − yC )2 + (z − z C )2 = c · τ RC ⎪ (x − xU )2 + (y − yU )2 + (z − zU )2 ⎪ ⎪ ⎪ ⎪ ⎪ − (x − xC )2 + (y − yC )2 + (z − z C )2 = c · τU C ⎪ ⎪ ⎪ ⎪ (x − x D )2 + (y − y D )2 + (z − z D )2 ⎪ ⎪ ⎩ − (x − xC )2 + (y − yC )2 + (z − z C )2 = c · τ DC
(2)
The indices in (2) at the coordinates correspond to the base stations BSC , BSL , BSR , BSU , BSD , the coordinates without indices refer to the unknown coordinates of the target, τLC , τRC , τUC , τDC —the difference in the arrival times of the microwave signal between the BSL , BSR , BSU , BSD and the reference base station BSC . In [25] the exact solution is presented. However, in the general case, the system of Eq. (2) has 8 solutions, but in the absence of TDoA measurement errors, the coordinates of four points will be the same. Such a solution will be true and for its search in [25] a special algorithm is proposed, which has shown there efficiency.
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2. Choose of test BSs location
3. Testing of BSs location for error steadiness
4. BSs location guidelines
Fig. 2 The general block diagram of the method proposed
Also, structure (2) shows that the accuracy of the coordinates determination strongly depends on the position of the BSs. This is due to the fact that the solution to system (2) depends on the determinants (3): −2X L −2Y L −2Z L i = −2X R −2Y R −2Z R −2X −2Y −2Z U U U = −8 · (X L Y R Z U + X U Y L Z R + X R YU Z L − X L YU Z R − X R Y L Z U − X U Y R Z L ) (3) where X L = x L − x C , Y L = yL − yC , Z L = zL − zC . Hereinafter the indices correspond to base stations BSC , BSL , BSR , BSU , BSD . Therefore, it is necessary that the determinant (3) is different from zero. This can be ensured by a sufficient difference in coordinates. If we are talking about an industrial building, then in the horizontal plane it is quite easy to provide. For the Z coordinate, you can suggest placing base stations at different heights. The position of the base stations should be included in the BIM design for an industrial building. It is possible that the vertical position is not important in a given manufacturing process. Then the task is greatly simplified [19] and it is recommended to provide in the BIM database, for example, the location of the base stations in the corridor under the ceiling at the same height. The general block diagram of the method proposed is shown in Fig. 2.
3 Results According to the block diagram in Fig. 2, you must first, according to block 1, select the test positions of the base stations (block 2) and test them in block 3 according to the method from [25]. Block 3 also consults the BIM database to improve results. In block 2, testing for robustness against possible errors/noise is also performed. It is necessary to ensure that the test positions of the BS allow for acceptable errors. It is proposed using a computer experiment to investigate the dependence of the root mean square deviation (RMS) of the object coordinates estimate if the same Gaussian white noise is added to the TDoA value at the input of each receiver of the positioning
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Fig. 3 Comparison of RMS for different BSs location
system for all BSs. The standard deviation of the estimate of the coordinates of the object should be determined in accordance with the expression (4): RMS =
1 n [(x k − x)2 + (y k − y)2 + (z k − z)2 ] k=1 n
(4)
In (4) index k is the number of the experiment, [x k , y k , z k ] is the estimation of the coordinates of the object in the k-th experiment, [x; y; z]—values of object coordinates. For example, for RMS, we obtained the following results for experiments implemented in the LabVIEW simulation system. Figure 3(a) shows the results for 100 experiments for a configuration of five BSs located at different heights, BS C [x C ; yC ; zC ] = [29.4; −40.45; 20], BS L [x L ; yL ; zL ] = [−29.4; −40.45; 25], BS R [x R ; yR ; zR ] = [−47.55; 15.45; 30], BS U [x U ; yU ; zU ] = [0; 50; 0], BS D [x D ; yD ; zD ] = [47.55; 15.45; 10] meters, Target height is z = 5 m. For comparison, Fig. 3(b) shows the simulation result, where the target height z = 2 m, and the position of the stations simulates their location in the corridor of an industrial building, 5 m high and 5 m width: BS C [x C ; yC ; zC ] = [0; 0.25; 2], BS L [x L ; yL ; zL ] = [10; 5.5; 4], BS R [x R ; yR ; zR ] = [20; 5.25; 3], BS U [x U ; yU ; zU ] = [30; 0; 5], BS D [x D ; yD ; zD ] = [40; 5; 1]. As you can see in Fig. 3, that our recommendations for the location of the base stations are consistent.
4 Conclusion The key points of the method for tracking objects/targets adopted for implementation inside industrial buildings based on microwave radar and BIM technologies have been
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described. The proposed method is based on earlier developments of the authors. It is now suggested to use the BIM database for industrial buildings to find the best location to locate base stations. The presented results show the efficiency of the method. The proposed method has wide application in applications of advanced manufacturing technologies for factories of the future. Acknowledgements The reported study was funded by RFBR, project number 19-29-06034
References 1. Ghobakhloo M (2018) The future of manufacturing industry: a strategic roadmap toward Industry 4.0. J Manuf Technol Manag 29(6):910–936 2. Lu Y, Liu C, Kevin I, Wang K, Huang H, Xu X (2020) Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues. Robot Comput-Integr Manuf 61:101837 3. Frontoni E, Loncarski J, Pierdicca R, Bernardini M, Sasso M (2018) Cyber physical systems for industry 4.0: towards real time virtual reality in smart manufacturing. In: Lecture notes in computer science 10850:422–434 4. Tao F, Zhang H, Liu A, Nee AY (2018) Digital twin in industry: state-of-the-art. IEEE Trans Industr Inf 15(4):2405–2415 5. Badenko VL, Bolshakov NS, Tishchenko EB et al (2021) Integration of digital twin and BIM technologies within factories of the future. Mag Civil Eng 101(1):10114–10114 6. Oztemel E, Gursev S (2020) Literature review of Industry 4.0 and related technologies. J Intell Manuf 31(1):127–182 7. Andronie M, L˘az˘aroiu G, S, tef˘anescu R, Ut, a˘ C, Dijm˘arescu I (2021) Sustainable, smart, and sensing technologies for cyber-physical manufacturing systems: a systematic literature review. Sustainability 13(10):5495 8. Orgeira-Crespo P, Ulloa C, Rey-Gonzalez G, Pérez García JA (2020) Methodology for indoor positioning and landing of an unmanned aerial vehicle in a smart manufacturing plant for light part delivery. Electronics 9(10):1680 9. Morgan J, Halton M, Qiao Y, Breslin JG (2021) Industry 4.0 smart reconfigurable manufacturing machines. J Manuf Syst 59:481–506 10. Lu S, Xu C, Zhong RY, Wang L (2017) A RFID-enabled positioning system in automated guided vehicle for smart factories. J Manuf Syst 44:179–190 11. Qu J, Hou L, Zhang R et al (2019) An improved measurement variable estimation model for positioning mobile robot. Interact Stud 20(1):78–101 12. Pang Z, Xie B, Zhu H, Luvisotto M (2019) Location aided commissioning of building automation devices enabled by high accuracy indoor positioning. J Ind Inf Integr 15:258–263 13. Batalla JM, Mavromoustakis CX et al (2020) Adaptive positioning systems based on multiple wireless interfaces for industrial IoT in harsh manufacturing environments. IEEE J Sel Areas Commun 38(5):899–914 14. Zafari F, Gkelias A, Leung KK (2019) A survey of indoor localization systems and technologies. IEEE Commun Surv Tutor 21(3):2568–2599 15. Gu F, Hu X, Ramezani M et al (2019) Indoor localization improved by spatial context—a survey. ACM Comput Surv 52(3):1–35 16. Volk R, Stengel J, Schultmann F (2014) Building Information Modeling (BIM) for existing buildings—Literature review and future needs. Autom Constr 38:109–127 17. Anil EB, Tang P, Akinci B, Huber D (2013) Deviation analysis method for the assessment of the quality of the as-is Building Information Models generated from point cloud data. Autom Constr 35:507–516
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18. Badenko V, Fedotov A, Zotov D, Lytkin S, Volgin D, Garg RD, Min L (2019) Scan-to-BIM methodology adapted for different application. Int Arch Photogram Rem Sens Spat Inf Sci ISPRS Arch 42(5/W2):1–7 19. Kuptsov VD, Ivanov SI, Fedotov AA, Badenko VL (2020) High-precision analytical TDoA positioning algorithm for eliminating the ambiguity of coordinates determination. IOP Conf Ser Mat Sci Eng 904(1):012013 20. Wang X, Zhang Z, et al (2021) Indoor localization and trajectory tracking system based on millimeter-wave radar sensor. In: IEEE 10th data driven control and learning systems conference (DDCLS), pp 1141–1147 21. Wang D, Yin J, Tang T, Chen X, Wu Z (2018) Quadratic constrained weighted least-squares method for TDOA source localization in the presence of clock synchronization bias: analysis and solution. Digit Signal Process 82:237–257 22. Kuptsov VD, Ivanov SI, Fedotov AA, Badenko VL (2020) Multi-target method for small unmanned vehicles parameters remote determination by microwave radars. J Phys Conf Ser 1515(3):032045 23. Tahat A, Kaddoum G et al (2016) A look at the recent wireless positioning techniques with a focus on algorithms for moving receivers. IEEE Access 4:6652–6680 24. Díez-González J, Álvarez R, Sánchez-González L et al (2019) 3D Tdoa problem solution with four receiving nodes. Sensors 19(13):2892 25. Kuptsov V, Badenko V, Ivanov S, Fedotov A (2020) Method for remote determination of object coordinates in space based on exact analytical solution of hyperbolic equations. Sensors 20(19):5472 26. Kuptsov VD, Ivanov SI, Fedotov AA, Badenko VL (2019) Features of multi-target detection algorithm for automotive FMCW radar. In: Lecture notes in computer sci, vol 11660, pp 355–364
Evaluation of the Location for the Construction of Windfarm Nail Timerbaev , Fouad Alhajj Hassan , Leysan Gainullina , Farida Filippova , and Safin Rushan
Abstract The electrical energy use continues extending and more applications will be founded on electrical power in the next decades, further developing atmosphere changes. For that reason, renewable energy must be used in an efficient way. Wind power plants are widely spread, including in Russia. The location of the wind farm plays a big role in determining the efficiency of the power output. For the select a site for construction, it is necessary to investigate factors such as annual wind speeds, terrain relief, the presence of nearby forests, water and other physical and geographical features characteristic of the study area. This article analyzes the site for the Sorochi Gory wind farm. An analysis of the terrain relief was carried out using maps and satellite images. The wind speed and direction were determined according to the installed anemometers and weather vane. Based on the results of the study, the layout of the turbines was proposed. Keywords Energy efficiency in transportation · Wind energy · Wind farm location · Turbine configuration · Gross energy
1 Introduction Wind farm location is an important factor to be studied, before building turbines, to get the highest power efficiency. In this project, selecting the construction site requires studying such factors as annual wind speeds, terrain, the presence of nearby forests, water, physiographic features, and the characteristics of the studied territory [1]. The terrain location, makes changes in the wind regime of the area [2, 3]. For example, breezy forest strips divide the flow by changing the wind speed. In and out of the forest strips, the wind speed becomes almost zero. The complete recovery of N. Timerbaev · F. A. Hassan · L. Gainullina (B) · F. Filippova Kazan State Power Engineering University, Krasnoselskaya Street, 51, 420066 Kazan, Russia e-mail: [email protected] S. Rushan Wood Processing Department, Kazan National Research Technological University, Karl Marx Street, 68, Kazan, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_155
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wind speed depends on the density of the green strip and occurs at a distance equal to 15–50 tree heights [4]. The wind speed is also significantly affected by the slightest difference in the mountains height. When the wind moves through the strip, its speed increases. A significant gradient in the wind speed creates its turbulence. This project considers the Sorochy Gory district, a mast is placed on the site to measure the wind speed from July 2018 to July 2019 in order to estimate the energy output. The project is intended to produce 150 MW using 60 wind turbines. The turbines are of three types, Siemens Gamesa SG 3.4-132 3.465 MW, Vestas V126-3.45 MW HTq and Lagerwey L100-2.5 MW.
2 Materials and Methods Sorochi Gory project is located approximately 65 km southeast of the city of Kazan in the republic of Tatarstan. Publicly available maps and satellite images were used to study the terrain and the physiographic features of the area. To monitor and process wind parameters, several anemometers are installed on the meteorological mast, calibrated in accordance with the requirements of MEASNET and installed in accordance with IEC 6. The sensors are set at different heights in order to measure the wind speed and wind direction at several tips. To study the possibility of including a wind power plant in the electric grid, the previous parameters were obtained.
3 Results and Discussion This article shows panoramic views of all perspectives, analyzes the terrain and provides information about it. The selection of the area is justified by the average wind speeds on the map of the Republic of Tatarstan. The average annual wind speeds for the Sorochy Gory region. The analysis of the annual values of wind speeds on the studied mast, resulted in a long-term wind speed of 7.25–8.0 m/s. such values are optimal to locate a wind farm [5]. In Table 1 shows the terrain contours, bumps and forest maps for the site. Places where there are obstacles to the flow (for example, trees in the surrounding of a weather mast or turbine), it is extremely important to take into account the impact of these obstacles on the wind flow model [6]. Directly to the northwest of the site there is a dense forest area. Data of the scale of forestry were obtained as a result of aerial photography, and on-site observations. The height of trees in the forest area is approximately from 9 to 12 m. It is assumed that the forestry conditions observed during the site visit are representative of the measurement period, and should be representative of the period of operation of the wind farm.
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Table 1 Plot characteristics Site characteristic
The resulting input to the analysis
Source
Terrain
Digital map of the area with a radius of 11 km with contours with an interval of 2.5 m
A publicly available SRTM contour map
Terrain
Terrain map with the following categories:
Publicly available satellite images based on the Davenport classification
Woodlands
Forestry
0.5 m
Localities
0.3 m
Light forestry
0.2 m
Bushes
0.15 m
Swamps
0.07 m
Plot and surrounding areas
0.03 m
Water
0.0002 m
Forestry map of the territory of the site, Publicly available satellite showing woodlands with a height of 9 to images 12 m
The following methodology was used to log the impact of the forest area: 1. The zones of forestry and plant cover were studied, in order to take into account both the area and the height of the trees. 2. For each pole and the location of the turbine, a possible decrease in the rating or the height of the hub was estimated in order to represent the influence of trees as an obstacle to wind flow. The determination of these parameters depends on the height of the trees’ displacement, the proximity of the pole or turbine to the trees, and the frequency of the event of the corresponding wind directions. 3. A characteristic profile of the energy loss coefficient was determined to reflect any changes in forestry (due to the expected expansion of the forest area or felling of trees) during the first ten years of the wind farm’s operation. 4. For wind farm locations located inside or near forestry or tree zones, it is necessary to take into account the impact of how the trees may change over time, and the impact this will have on the wind flow over the site, and therefore the energy production of the wind farm. The consequences of future tree falling, if known, may also need to be studied. A panoramic perspective from the location of the mast. The mast is installed at the point (431079, 6137641). The biome around the mast is relatively smooth. When designing a wind power plant, it is necessary to consider the possibility of its inclusion in the electrical network of the Republic of Tatarstan. In this case, such a possibility exists. There is an electric substation connected to the power grid of Tatarstan on Sorochy Gory [7]. Extreme environmental conditions can affect access to more remote sites, which can affect accessibility. An example of this would be an area that is subject to severe
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Table 2 Parameters of the proposed turbine models Turbine
Rated power [MW]
Hub height [m]
Peak power coefficient [Cp ]
PC air density [Kg/m3 ]
Operational temperature range
Siemens Gamesa SG 3.4–132 3.465 MW
3.465
97
0.46
1.24
−20 to + 40 °C
Vestas V126-3.45 MW HTq
3.45
87
0.45
1.25
−20 to + 45 °C
Lagerwey L100-2.5 MW
2.52
99
0.48
1.225
−30 to + 30 °C
snow drifts during the winter season. The impact on energy will depend on the operation and maintenance plans [8]. In the Sorochy Gory, the following turbines were proposed for wind power plants: Siemens Gamesa SG 3.4-132 3.465 MW, Vestas V126-3.45 MW HTq, Lagerwey L100-2.5 MW, the characteristics of which are presented in Table 2 [9]. Turbine Layouts The wind farm format was structured in order to maximize energy production; for the Siemens Gamesa SG 3,4-132 turbine with a capacity of 3,465 MW, a single wind farm project was developed, since the largest rotor diameter in the turbine model, two other turbine models used the same layout for analysis [10]. Thus, the computational optimization of the wind farm format was carried out using the DNV GL WindFarmer software. For this optimization, the accompanying limitations for the Siemens Games ASG 3,4-132 turbine with a capacity of 3,465 MW were used [11]: • The distance between the turbines with a rotor diameter of 6.0 mm in the prevailing wind directions; • The distance between the turbines with a rotor diameter of 4.0 in non-prevailing wind directions; • An elliptic constraint is used based on the above criteria; • The slope of the terrain is below 10°; • The boundary of the plot; • An offset of 300 m from the site boundary; and further reduction of distances: – – – –
50 m from unpaved internal roads and 200 m from highways; 100 m from reservoirs; 200 m from high voltage lines; 300 m from the forest areas.
A map of the site indicating the excluded zones and allowed zones for the placement of wind turbines [12, 13].
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Table 3 Turbine layout configurations Configuration Id
Turbine type
Hub height [m]
Number of turbines
Rated power [MW]
1
Siemens Gamesa SG 3.4-132 3.465 MW
97
60
207.9
2
Vestas V126-3.45 MW HTq
87
60
207
3
Lagerwey L100-2.5 MW
99
60
150
The following layout was developed taking into account the location of 60 turbines (Table 3). Based on the previous findings, a map of the site was obtained, showing the designed layout of the turbine and the place of wind measurement (the location of the meteorological mast) [14]. The configurations were examined on windfarm analysis program to estimate the output power of each turbine configuration the results are shown below [15]. Computer virtual experiment leads to the results for the three configurations, where each wind turbine is processed individually. The results are shown in the following tables. • Results of configuration 1, Siemens Gamesa SG3.4-132, 3.465 MW: In this situation, the hubs of the turbines are installed at the elevation of 97 m. The total energy output of configuration 1 is 614.5 GWh/annum (Fig. 1). • Results of configuration 2, Vestas V126-3.45 HTq: In this wind farm, the hubs of the turbines are installed at the elevation of 87 m. The total energy output of the configuration 2 is 551.9 GWh/annum (Fig. 2). • Results of configuration 3, Lagerwey L100-2.5 MW: In this wind farm, the hubs of the turbines are supported at the elevation of 99 m. The total energy output of the configuration 2 is 411.1 GWh/annum (Fig. 3). It should be noted that the wind speed is at the ideal case, while the output energy includes the wake effects of the turbines, at it can be concluded that Siemens is the most suitable while the Lagerwey wind turbine configuration lacks the optimal output energy due to the wake effects. The following recommendations are available for this layout: • Higher inter-turbine distances should be used. In any case, it was necessary to reduce the inter-turbine separation in order to ensure the maximum capacity of the wind farm on the site, while adjusting the requirements for reducing trace losses, and consequently, reducing potential fatigue loads. • It should be noted that for the proposed turbines, a preliminary study of the structure proportional to the intensity of turbulence was carried out. Consequently, it was chosen to obtain the optimization effects without any additional changes or
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Wind Speed [m/s]
12 10 8 6 4 2 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 Average
0
Turbine ID
Wind Speed [m/s]
Energy output [GWh]
Fig. 1 Energy results for configuration 1, Siemens Gamesa SG3.4-132, 3.465 MW
Wind Speed [m/s]
12 10 8 6 4 2
Wind Speed [m/s]
Energy output [GWh]
Fig. 2 Energy results for configuration 2, Vestas V126-3.45 HTq
58
52
Average
Turbine ID
55
49
46
40
43
37
31
34
25
28
19
22
16
13
10
7
4
1
0
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58
Average
Turbine ID
55
52
49
43
46
40
37
34
28
31
25
22
19
16
10
13
7
4
9 8 7 6 5 4 3 2 1 0 1
Wind Speed [m/s]
Evaluation of the Location for the Construction of Windfarm
Energy output [GWh]
Fig. 3 Energy results for configuration 3, Lagerwey L100-2.5 MW
reduction in the number of turbines. Some of the turbine platforms in the format are provided in the surrounding of trees up to about 12 m high. The height of these trees is significantly less than the proposed height of the hub, and the potential for increased turbulence is small. According to the data presented, the mast is located at a height of about 175 m, while the height of the turbines varies from about 85 to 175 m. Thus, the position of the pole of the site is considered not quite representative for turbines located at lower altitudes, for example, a group of turbines located along the northern edge of the site. It is recommended to carry out additional measurements at the site, especially in the northern part, which will reduce these uncertainties. The uncertainty associated with horizontal flow modelling can also be further reduced by using CFD (Computational Fluid Dynamics) [16].
4 Conclusion In this article, the project location was presented, the wind speed and the network substation were considered suitable for the project. For accurate measurements, a mast was built at the point (431079, 6137641); a panoramic perspective of the site, including the mast, was presented. Some factors affecting the installation were considered, such as the terrain, forestry, and the proximity of electrical networks. The limitations of the turbines were discussed and studied to calculate the distance between them and estimate the location of each of the wind turbines.
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It should be noted that for the proposed turbines, a preliminary study of the structure proportional to the intensity of turbulence was carried out. Consequently, it was chosen to obtain the optimization effects without any additional changes or reduction in the number of turbines.
References 1. Ivanova IYu, Nogovitsin DD, Tuguzova TF et al (2013) Wind energy resources of the city of Verkhoyansk of the Sakha Republic (Yakutia) and the possibility of their use for energy supply. Fund Res. 4(part 1):30–38. https://doi.org/10.17513/use.37168 2. Hou P, Zhu J, Ma K et al (2019) A review of offshore wind farm layout optimization and electrical system design methods. J Modern Power Syst Clean Energy 7(5):975–986. https:// doi.org/10.1007/s40565-019-0550-5 3. Sliz-Szkliniarz B, Vogt J (2007) GIS-based approach for the evaluation of wind energy potential: a case study for the Kujawsko-Pomorskie Voivodeship. Karlsruhe. Renew Sust Energy Rev Germany 15:1696–1707. https://doi.org/10.1016/j.rser.2010.11.045 4. Claudia H, Andreas L (2019) The impact of a feed-in tariff on wind power development in Germany. Res En Econ 57:18–35. https://doi.org/10.1016/j.reseneeco.2018.12.001 5. Official website Globalsolaratlas.info 6. Ya D et al (2018) Effects of building height and porosity on pedestrian level wind comfort in a high-density urban built environment. Springer 11(6):1215–1228. https://doi.org/10.1007/s12 273-018-0451-y 7. Official website https://www.entsoe.eu/data/map/ 8. Hong J, Abraham A (2020) Snow-powered research on utility-scale wind turbine flows. Acta Mech Sin 36:339–355. https://doi.org/10.1007/s10409-020-00934-7 9. Mestnikov N, Hassan FA, Alzakkar A (2021) Study of operation of combined power supply system based on renewable energy in territory of far east of Russia. In: International conference on industrial engineering, applications and manufacturing (ICIEAM), pp 114–118. https://doi. org/10.1109/ICIEAM51226.2021.9446439 10. Ali N, Hamilton N, DeLucia D, Cal RB (2018) Assessing spacing impact on coherent features in a wind turbine array boundary layer. In: EAWE, pp 43–56. https://doi.org/10.5194/wes-3-43 11. Hassan FA, Sidorov A (2019) Study of power system stability: Matlab program processing data from Zahrani power plant (Beirut, Lebanon). E3S Web Conf 124. https://doi.org/10.1051/ e3sconf/201912405011 12. Allhibi H, Chowdhury H, Zaid M (2018) Prospect of wind energy utilization in Saudi Arabia: a review. In: 2nd international conference on energy and power, Australia, pp 746–751. https:// doi.org/10.1016/j.egypro.2019.02.184 13. Alzakkar A, Hassan FA, Mestnikov N, Valeev I (2021) Study of impact of the main parameters of synchronous generators on the dynamic stability in the Syrian power system. In: International conference on industrial engineering, applications and manufacturing (ICIEAM), pp 197–203. https://doi.org/10.1109/ICIEAM51226.2021.9446185 14. Charhouni N, Sallaou M, Mansouri K (2019) Realistic wind farm design layout optimization with different wind turbines types. Int J Energy Environ Eng 10:307–318. https://doi.org/10. 1007/s40095-019-0303-2 15. Almohammed O, Philippova F et al (2021) Practical study on heat pump enhancement by the solar energy. E3S Web Conf 181–187. https://doi.org/10.1051/e3sconf/202128801069 16. Sanders B, van der Pijl SP, Koren B (2011) Review of computational fluid dynamics for wind turbine wake aerodynamics. Wind Energy 14(7):799–819. https://doi.org/10.1002/we.458
Comparative Assessment of Acoustic Baffles Vadim Bespalov
and Natalya Samarskaya
Abstract The article presents a comparative analysis of three variants of acoustic baffles for highways, differing in material of manufacture and operating conditions, but having comparatively the same acoustic efficiency. The aim of the study was to select the most optimal version of the acoustic baffle in terms of the degree of economic efficiency and the most favorable operating conditions. The analysis of the modern market for sound-absorbing and sound-reflecting materials made it possible to select the following options for comparison: an acoustic baffle made of acrylic panels, an acoustic baffle made of metal perforated sheets and mineral wool, and an acoustic baffle made of used car tires. Moreover, the latter option is considered as an alternative and is not common in the practice of providing acoustic comfort in urban areas. Consideration of the possibility of using waste tires as an acoustic baffle is due to the fact that the use of traditional acoustic baffles to solve the problem of reducing the level of acoustic impact is not always economically justified. The cost of acoustic panels, support profiles, racks, installation of the structure is considered to be very high. In turn, the use of used car tires as an acoustic shield will significantly reduce capital and operating costs. Along with solving the problem of acoustic discomfort, a solution to the problem of recycling used car tires will also be provided. Keywords Acoustic discomfort · Acoustic baffles · Car tires · Urban areas recycling
1 Introduction Currently, the problem of acoustic discomfort in residential areas has become particularly urgent [1]. First of all, this problem manifests itself in those territories where residential buildings are located near high-speed roads. Increased acoustic exposure around the clock negatively affects the health of the population, promotes sleep V. Bespalov · N. Samarskaya (B) Don State Technical University, 1, Gagarina Square, 344022 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_156
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disturbance, leads to an increase in stressful situations, and also causes diseases of the cardiovascular and nervous systems [2]. The analysis of this problem on a global scale has shown that the most effective solution is the use of road acoustic baffles or the so-called noise barriers [3]. The modern market provides a huge selection of sound-absorbing and sound-insulating materials, as well as acoustic baffle designs that meet the requirements of national building standards. However, in general, when choosing a material and design, special attention is still paid to the criterion of economic efficiency. This is due to the fact that the cost of modern acoustic panels, support profiles, racks, installation of the structure is considered to be very high [4]. In addition to the high cost, significant problems in the use of acoustic screens on highways are considered to be a decrease in noiseprotective properties and the appearance of a structure during operation [5]. Our field observations, as well as the results of analytical studies, showed that design errors, incorrect installation of the structure, poor quality materials, vandalism, corrosion of metal elements, pollution and turbidity of transparent panels are among the causes of this problem.
2 Materials and Methods Taking into account the importance of the problem of acoustic discomfort for residential areas, as well as the significant problems of using traditional acoustic screens, we have studied three options for noise protection baffles, characterized by almost the same degree of acoustic efficiency (10–11 dBA). The selected options for acoustic baffles differ in materials of manufacture and features of their operation. These differences, in our opinion, will have a significant impact on the criterion of economic efficiency of using one or another type of acoustic baffle. For a comparative assessment, we have chosen the following options: option 1: acoustic baffle made of acrylic panels; option 2: acoustic baffle made of metal sheets and mineral wool; option 3: acoustic baffle made of used car tires. Option 1 and option 2 were selected based on the results of the analysis of the market of services provided in the construction of acoustic baffles for highways and are the most in demand, since they have a number of advantages. Option 3 is not common in the practice of providing acoustic comfort and is proposed as an alternative option in terms of design, material of manufacture and operating conditions.
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3 Results Comparative evaluation of the selected options for acoustic baffles revealed the following features of each of them. Option 1 of the acoustic screen is related to the type of sound reflective ones and is a translucent structure (Fig. 1). The considered design of panels made of acrylic provides good visibility to all road users and does not disrupt the appearance of the urban environment. According to analytical data, acrylic material has many names and is acrylic resin, synthetic vinyl polymer of methyl methacrylate, thermoplastic transparent plastic that can be dyed or tinted. This material has high impact strength, which is important in modern operating conditions. Due to their optical properties, acrylic acoustic baffles are very popular and visually fit favorably into the architecture of any urban area. In addition to aesthetic appeal, the manufacturers point out that the advantage of the option under consideration is the minimum number of support profiles. As a support profile for such a variant of acoustic baffles, metal stands are traditionally used. However, a number of manufacturers use a special technology that allows acrylic panels to be installed through springs, excluding micro-movements of structural elements. The decrease in the number of racks determines the ease of installation, thereby increasing the economic efficiency of using Option 1. The practice of using acrylic acoustic baffles has shown their maintainability due to the possibility of replacing the panel without dismantling the entire structure. In addition, a very important advantage of Option 1 is the ability to provide a large height of the acoustic baffle. The acrylic baffle can be mounted up to 7–8 m high. At the same time, the strength and rigidity of the structure do not decrease with increasing height. In general, the expediency of using acoustic baffles in Option 1 has been proven by the experience of numerous countries. But, despite this, a significant drawback can be noted. So, unlike sound-absorbing baffles, this option reflects most of the sound wave, returning it to the source of the noise. In this regard, the noise source, together with the side opposite to the protected object, receives an increased sound load. Based on this, we can conclude that the scope of this type of acoustic baffle is limited. Fig. 1 Structural diagram of an acoustic baffle made of acrylic panels
1
2
1 – transparent acrylic panel 2- metal stand
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Fig. 2 Structural diagram of an acoustic baffle made of metal perforated sheets and mineral wool
1 – perforated metal sheet 2 - metal rack The constructive basis of the acoustic baffles in Option 2 is a metal cassette, one side of which is solid and rigid, and the other side is perforated (Fig. 2). Between the solid and perforated metal sheets there is a sound-absorbing material—mineral wool wrapped in a protective film or one layer of fiberglass. Mineral wool is widely used in the field of sound-absorbing materials. Depending on the feedstock, it can have a different fiber structure, is characterized by resistance to high temperatures and the effects of chemicals. This version of the acoustic baffle functions as a sound absorption. When installed, the acoustic baffles are positioned so that their perforated (sound-absorbing) side faces the noise source. The multi-layer construction of the acoustic baffle allows the kinetic energy of sound to be damped between the layers of the material. That is, a sound wave, falling on the material, is not reflected from it, but penetrates inside and scatters, losing the force of its pressure. Due to this, Option 2 has an advantage in terms of the number of protected objects—safety is ensured both for residential areas located along the highway and for road users. The considered Option 2 has also become widespread in the practice of ensuring the acoustic comfort of urban areas, but it has a significant drawback. The multi-layered structure determines its high cost. Considering that the recommended height of the acoustic screen is not less than 4 m and with a margin of 5 m on both sides, this disadvantage is significant. Option 3 is considered as an alternative in terms of material of manufacture, design and operating conditions. The proposed Option 3 takes into account, first of all, the criterion of economic efficiency and is, in our opinion, beneficial, since waste is used as the main material of the acoustic baffle—used car tires. This type of waste is practically not subject to natural decomposition [5]. In Russia, as well as in the EU countries, a ban has been established on the disposal of tire waste in order to stimulate the recycling of waste. According to [4], the volume of waste tires accumulated in the world is more than 80 million tons. The results of a comparative analysis of the handling of used car tires in several highly developed countries show that the volume of production in each of them reaches several hundred thousand tons (Table 1). Most of the tire waste goes to crumb rubber and energy.
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Table 1 Waste management (used car tires) in some countries Country
Tire production, thousand tons
Disposed of in landfill, %
Energy recieved %
Crumb rubber production %
Retreading %
Export %
USA
4039
12.1
47.6
32.1
0
Japan
1000
7.8
64.3
10.5
5.6
11.5
7.6
Germany
582
0
36.4
34.5
12.9
14.4
1.7
Great Britain
527
4.5
35.5
39.5
7.4
5.5
7.6
Italy
421
0
55.6
28.5
6.7
4.0
5.2
France
457
0
49.7
27.4
7.7
10.9
4.4
2.5
Other %
0
Based on the data in Table 1, as well as statistical data for other countries, it can be concluded that the disposal of used car tires is another problem of urban areas, which can be partially solved by using them as a building material for an acoustic baffle without any preliminary processing. In order to assess the possibility of using used car tires as an element of an acoustic baffle, we analyzed the possible types of their wear. The used car tire is characterized by the types of wear, which can be classified as follows (Fig. 3). After analyzing Fig. 3, we can conclude that car tires subject to any type of wear are suitable as a building material for an acoustic baffle. However, the type of wear will in part determine the degree of acoustic performance. Types of automobile tyres wear
Tread wear in the middle of the tire
Cracks and bulges on the sidewall of the tire
Reason: incorrect tire pressure
Reason: tire hitting a curb or pit
Flat wear spots Reason: sudden braking, acceleration or skidding
Tire edge wear
One-sided wear
Reason: insufficient tire pressure
Reason: wrong wheel alignment
Fig. 3 Types of car tire wear
1522 Table 2 Properties of isoprene and divinyl synthetic rubbers
V. Bespalov and N. Samarskaya Parameters of properties
Rubber type Isoprene
Divinyl
Electrical resistance
2
2
Fire resistance
4
4
Gas tightness
3
3
Heat resistance
3
3
Frost resistance
2
2
Strength, MPa/cm2
>21
>14
Hardness, Shore A
30
40
Compression set
1
1
Elasticity cold
1
1
Elasticity hot
1
1
Wear resistance
1
1
Chemical resistance to light
3
3
Chemical resistance to water
2
1
Chemical resistance to diluted acids
2
2
The rubber that is part of the tire is made, as a rule, from synthetic rubber, as a simpler and more cost-effective material. We have analyzed the properties of isoprene and divinyl synthetic rubbers used for the production of automobile tires (Table 2). Isoprene synthetic rubbers have high mechanical strength and elasticity. They are used as substitutes for natural rubber both in the production of tires and in the manufacture of conveyor belts, footwear, sports and medical products. Divinyl (butadiene) synthetic rubbers are general purpose rubbers. In addition to the production of tires, they are used in the manufacture of footwear, cable insulation, conveyor belts, linoleum, and household products. It is also a durable and elastic material. Despite the good performance properties that allow car tires to be considered as an acoustic baffle, there is a significant drawback—the relatively high flammability of synthetic rubbers. This problem can be solved by additional treatment of the tire surface with flame retardants. One of the important characteristics of synthetic rubbers is their sound absorption coefficient. The average sound absorption coefficient of isoprene and divinyl synthetic rubbers is 0.4–0.9 and depends on the presence of pores on the tire surface. The more embossed the surface of a used tire with cracks and pores, the more efficiently the sound absorption process takes place. The choice of the design of the acoustic baffle from used car tires depends on the conditions for ensuring the stability of durability, strength and simplicity and is the topic of separate studies. Obviously, the two-row arrangement of car tires will provide a greater degree of acoustic efficiency. One of the options for the placement of structural elements is shown in Fig. 4.
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Fig. 4 Layout of used car tires in the structure of the acoustic baffle
The advantages of the construction of an acoustic baffle made of used car tires, in our opinion, are the ease of assembly, minimal costs for materials and the strength of the structure. Two-row placement of car tires allows to create a denser and stronger barrier, and the gaps formed when the tires are staggered allow for a sufficiently high sound absorption effect.
4 Discussion To improve the aesthetic perception of Option 3 of the acoustic baffle, as well as to increase the efficiency of sound absorption on the side surfaces of the structure, vertical gardening techniques can be applied. This activity involves filling the inner surface of the tires with fertile soil and sowing perennial grasses or climbing plants on this soil. Depending on the climatic zone and the characteristics of the region, lemongrass, ivy, hops, Amur grapes can be used as unpretentious species. Thus, it is possible to create a green volume, completely hiding car tires from visual perception. Thus, the most significant drawback of Option 3 will be only the limitation of the view due to the opacity of the structure.
5 Conclusions Taking into account the peculiarities of Option 3 of the acoustic baffle, it can be concluded that the main function—reducing the sound pressure level to acceptable values—will be performed. Moreover, this design will have a number of advantages: – durability. Synthetic rubbers have the property of resisting any atmospheric and mechanical influences, temperature extremes. The service life of such a fence is not even limited to a century; – ease of operation. The acoustic baffle requires little maintenance. It can be dyed and washed as needed. In case of additional landscaping, maintenance work will include plant maintenance;
1524 Table 3 Comparative cost of acoustic baffle options
V. Bespalov and N. Samarskaya Comparative parameter
Option 1
Option 2
Option 3
Materials cost
145–150
200–250
22–24
Foundation cost
13–15
15–16
4–5
Installation cost
40–50
50–55
20–30
– ease of installation. Installation work does not require special knowledge and skills, as well as machinery and equipment; – The use of used car tires will make a significant contribution to solving the problem of recycling this type of waste. Based on the analysis of the features of materials and structures of acoustic screens, we carried out a comparative assessment of the economic efficiency of using the selected options based on the average prices of various manufacturers in euros according to the following parameters: – cost of materials; – cost of the foundation; – installation cost. The cost indicated in Table 3 is given for acoustic baffles with a height of 4 m per one running meter, taking into account the cost of fastening elements. Table 3 shows that the cost of material for Option 3 is 22–24 euros, which is significantly lower than the cost of materials for [Option 1 and Option 2 and represents the cost of only fastening elements. At the same time, the main material—used car tires is supposed to be used free of charge. Considering that the material is a waste, the degree of economic efficiency of the application of Option 3 obviously increases due to the solution of the problem of recycling used car tires.
References 1. Mapar M et al (2017) Sustainability indicators for municipalities of megacities: integrating health, safety and environmental performance. Ecol Ind 83:191–271. https://doi.org/10.1016/j. ecolind.2017.08.012 2. He SY, Thøgersen J (2017) The impact of attitudes and perceptions on travel mode choice and car ownership in a Chinese megacity: the case of Guangzhou. Res Transp Econ 62:57–67. https:// doi.org/10.1016/j.retrec.2017.03.004 3. Zhong Q, Ma J, Zhao B, Wang X, Xiao X (2019) Assessing spatial-temporal dynamics of urban expansion, vegetation greenness and photosynthesis in megacity Shanghai, China during 2000–2016. Remote Sens Environ 233. https://doi.org/10.1016/j.rse.2019.111374 4. Sohrabi S, Khreis H (2020) Burden of disease from transportation noise and motor vehicle crashes: analysis of data from Houston, Texas. Environ Int 136. https://doi.org/10.1016/j.envint. 2020.105520 5. Thacher JD, Poulsen AH, Raaschou-Nielsen O, et al (2020) High-resolution assessment of road traffic noise exposure in Denmark. Environ Res 182. https://doi.org/10.1016/j.envres.2019. 109051
Technological System Reliability as the Basis for Quality Indicators Stability Produced Machine Parts Galina Prokopets , Anatoly Prokopets , and Svetlana Vozhakova
Abstract The paper is focused on one of the advanced types of finishing—vibratory machining. We are considering the structure of a technological system; besides, we are analyzing the influence of the system elements reliability on the reliability of the technological system in general, as well as the degree of that influence. We particularly present the technical system which is the main part of the technological system for vibratory machining. We experimentally proved that during vibratoryabrasive machining, the least reliable element is the tool environment for processing (working medium—WM), that is the total of abrasive particles of a definite shape and size, which are moving along certain trajectories with the parts under processing placed inside the medium. The WM wear causes decrease in treatment efficiency due to deterioration of its cutting ability. In addition, we have revealed those treatment process factors that mostly influence the wear-and-tear of the WM; we have suggested theoretical and experimental function to define the amount of mass wear of the WM in vibratory-abrasive machining. The fulfilled analysis and theoreticaland-experimental research allows the opportunity for vibratory machining process optimization, as well as for its control in order to decrease the parts manufacturing charges. Keywords Finishing methods · Machining process optimization · Quality of the parts · Vibratory machining process
1 Introduction Any technical system (TS) possesses a definite reliability margin. A technological process (TP) is a system, as well, and comprises all its main characteristics. Its implementation provides parts machining of definite quality and quantity with minimum technological self-cost. Along with this, practically any TP for parts machining is a certain dynamic system, including quite a large amount of elements, inter alia a G. Prokopets (B) · A. Prokopets · S. Vozhakova Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_157
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precisely definite quantity of technological and auxiliary operations interconnected with a system of networks (power, information, logistics, facilities and others) [1]. That being said, the reliability of the ‘Technological Process’ system is primarily determined by the reliability of each element of the system, that is—by the reliability of each separate technological operation (TO). Nevertheless, another factor of crucial importance is the reliability of interconnections among TO, whereby their composition, contents and structure are specified at the stage of TP design. Thus, the reliability characteristics are preset by a manufacturing engineer and depend on his/her qualification, being limited by the actual conditions of production where such a TP is going to be carried out. We find it reasonable to start our consideration of reliability indicators of the ‘Technological Process’ system with the analysis of reliability of its main elements (technological operations) [2–9]. A technological operation is an integral element of a technological process, as a system, aimed at controlled transformation of a workpiece into a part or its version which is to be a workpiece for the following operation. The type of transformation is determined by the position of a technological operation within a technological process. Methods of finishing treatment, including vibratory machining, are of special importance for the purpose of assurance of quality indicators for the parts under machining. Consequently, to ensure reliability of finishing technological operations is still a topical task.
2 Methods Vibratory Machining (VM) in most cases is used as finishing treatment and is attributed to the group of non-dimensional methods [4]. VM does not influence the part shape and size. VM is based on the impact of the working substance particles of a definite shape, size, and physical and mathematical parameters (WM), on the part surface layer. There are two standard types: vibro-abrasive and shock-vibrating machining. Shock-vibrating machining is primarily used for the part strengthening treatment due to plastic deformation of the part surface layer [5, 6]. Vibro-abrasive machining is mainly used for formation of micro-relief with specified characteristics, on the surface of the parts under processing, by removing microchips from it. Some vibratory methods of machining use the combination of various kinds of energy [3, 7]. The VM technological operation comprises all the basic features of TS including structuredness, controllability, adaptivity, functional dependence on a certain objective. In this system we have two major processes: part machining itself, providing the specified quality level (making useful effect), and process control. Process control parameters are defined by the reference document worked out by a process engineer (TP for mechanical treatment), where the complete working cycle of a technological system is definitively stated. The document contains all the information that is necessary for machining process control, including the information on TS, which is the principal part of the vibratory machining technological system.
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The reference document contains managerial information that makes it possible to provide (during the TS initial set up) the parts under processing with the quality level as specified in engineering documentation. Nevertheless, it does not make it possible to provide the stability of the mentioned quality level during a certain period of time which is defined by either the size of the part lot, or the output, or other production factors. In addition, it is only the above mentioned factors in total that provide VM TP reliability. Thus, we assume that VM TP reliability is the provision of the specified by technical documentation level of quality indicators, to the surface of parts under machining, during continuous TO execution (within a single operation), without interruption for auxiliary actions on re-adjustment of the process parameters assumed by technological documentation and providing the specified quality level. The input data for defining the conditions for the necessary reliability level are as follows: – – – – – – –
– – –
technological system structure and composition; equipment and WM wear rate; production volume or the lot volume of parts under processing; numerical values of parameters for workpiece quality (surface roughness, hardness of material, and others), which are significant for purposes of the operation; numerical values and quality parameter tolerance for the part surface under processing; labour intensity for a single operation or for machining of a part lot, and others. based on these data we can define the required values of TS reliability indicators. The TS reliability assessment can be fulfilled upon solution of a number of problems, including the following: to present the rationale for the possibility of TO usage to provide the specified quality level for the parts under machining; to estimate the stability of TS characteristics within a certain time period; to get information in order to provide the possibility of machining process parameters control (including the adaptive method), inter alia—with the purpose of stability provision, and others.
The given analysis illustrates that process stability provision is of great importance and is definitely topical.
3 Results and Discussion The TS plays the most important role in stability of quality indicators within the lot of parts under machining. The TS, in its turn, possesses all the features of the system and can be precisely structured. Therefore, at the initial stage of theoretical analysis it is necessary to define the system boundary, to identify its structural elements and their interconnections.
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Vibratory machining is fulfilled in a TS, and its composition can considerably vary. That being said, such a TS contains a basic case, which provides the principal possibility to carry out the machining (Fig. 1), and an additional part aimed at solution of the following major objectives: – to machine individual part surfaces or parts with certain constructive peculiarities (that is provided by usage of special technological equipment); – to increase the process performance (for instance, to use automatic control systems or special equipment in order to enable additional movement of parts under machining or to raise energy characteristics of WM particles); – to increase the TO reliability (for instance, to use automatic process control systems during the TO); – to combine operational objectives (for example, surface coating), etc. In other words, the additional elements of the technological system are mainly meant to adapt the process to the conditions and objectives (parameters of the parts under processing) of the machining, and to increase its reliability. The result of TS reliability increase is the process productiveness growth and improvement of the part machining quality. The base TS is a vibratory machine with base configuration comprising the following elements: – the body; – the actuator with a power source (engine);
Fig. 1 WM TO structure analysis. Influence of its constituents on reliability
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– the bumper suspension (a vibro-platform with bumper elements), – the control system, providing the system adjustment to the machining mode, as specified by the designed TP. Besides, base configuration must include base technological equipment—a working chamber as an element providing formation of the trajectory for loading environment circulation. The loading environment includes WM and the parts under machining, and, depending on the machining objectives and conditions, the process liquid, as well. The additional configuration elements and their combination can vary. Their composition depends on numerous factors like the following ones: – characteristics of the parts under machining (part shape and size, specified parameters of the surface layer and their tolerance, etc.); – the parameters of a work piece, coming for machining at TO (physical and mechanical characteristics of the part material, work piece roughness parameter, work piece mass, and others); – the volume of the lot of parts under machining i., a.,—the correlation of the volume of parts under machining and the WM, and others. Lots of factors influence the VO TP reliability. The process is complicated from the kinematics point of view. Besides, the connections among the WM elements inside the load mass, and with the units inside the working chamber, are rather weakly determined. Therefore, the complete theoretical description of the process itself, as well as the formation of its reliability indicators, at this stage of research appears impossible. Each element of the vibratory machining TS influences the TP reliability, though, to various extents, and, depending on the operation labour intensity. Thus, technical characteristics of the main and additional equipment define the level of quality for the parts under machining, but, as a rule, they remain stable during the operation, that is why they practically do not influence the process stability while the operation is going on. So, in the process stability analysis, the equipment elements wear, for example, or the wear of working chamber coating within a single operation, can be neglected. At the same time, the tool (working medium) and the condition of the process liquid can considerably change during the same period of time, and noticeably define the process stability, and, consequently, the range of scatter for the quality indicator of the parts under machining. A great number of experimental research held at the Don State Technical University, has shown that the basic cause of reliability damage in vibratory machining is the fault in the process stability [1, 2, 5, 8, 9]. The load mass for the working chamber has to move in accordance to a specified law in order to provide stability of the quality parameters for the parts under machining. The mass load circulation trajectory is defined by the shape of the working chamber surface and by the vibration quantity, specified by the settings of the vibratory machine. Figure 2 shows the results of experimental research of mass wear of the WM U, that is, its dependence on one of the elements of vibro-abrasive machining—the vibrational amplitude of the working chamber. From the present function we see
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the WM wear direct dependence on the vibrational amplitude. In addition, similar functions have been obtained to define the mass wear dependence on the vibrational amplitude of the working chamber and the time of machining. The fulfilled experimental research has shown that dependence of WM wear on the machining time, vibration amplitude and frequency, provided the working capacity is kept stable, can be divided into two parts: a period of wearing fast and normal wear period. In this respect, during the normal wear period such a dependency, to a high degree of approximation accuracy, can be described by an exponential function. Coefficients, used in such dependences, are functions of the type/durability of the WM (S, kg × m2 ), machining time (t, c), amplitude (A, mm) and frequency (f, c − 1) of the working chamber vibrations, considering the degree of their influence on the wear indicator U: U = s ks × t kt × A k A × s f k f
(1)
It is necessary to mention that the mass wear of the WM is the major destabilizing factor in vibratory abrasive machining.
Fig. 2 Dependence of WM wear rate (abrasive 16TB, medium granulation, 20 mm) on the vibrational amplitude of the working chamber (A): line 1—A = 1.5 mm, line 2—A = 2.5 mm. Experimental conditions: Horizontal Vibratory Machine, 4 × 10, working chamber capacity—10 l, working chamber vibration frequency f = 33 Hz
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4 Conclusion The completed research illustrates that the main way to ensure the quality indicators for parts surfaces is to stabilize the cutting ability of the WM. To provide this, it is necessary to ensure the specified WM wear parameter during the TO within certain limits. The WM wear during the TO should not exceed the limits of working capacity. The allowable WM wear is defined by the tolerance for the quality indicators for the parts under machining. At the same time, as shown by the experimental research, the wear does not only depend on the WM characteristics and machining time, but on the vibrations mode, as well: amplitude and frequency. Thus, when choosing the abrasive working medium, it is necessary to consider not only the quality indicators of the surfaces of parts under machining, and their material properties, specified by technical documentation, but the durability of the working medium and influence of machining modes on its wear. The obvious dependency of the WM wear on the time and mode of machining reveals the possibilities for the VO process optimization, as well as for its control in order to reduce the parts production cost.
References 1. Azarova A, Prokopets G, Prokopets A, Murugova E (2020) Standardization of the technological parameters of vibratory abrasion as a tool for process reliability enhancement. In: Materials conf. state and prospects for the development of the agro-industrial complex, Rostov-on-Don, DSTU 2. Prokopets G, Prokopets A, Yerina T (2019) The analysis of the technological operation of the abrasive-vibratory machining as integral dynamic system. Eugenii Gvizdon. Conf. prospective lines of development of finishing and strengthening treatment and vibro-wave technologies 3. Ivanov V, Smolentsev V, Lebedev V (2019) Chemical and mechanical bases of application of coatings in vibration technological systems. Electroplating and surface treatment 4. Tamarkin M, Tischenko E Current state and outlooks in development of methods of processing in granulated working environments. Don State Technical University 5. Lebedev V, Pastukhov F, Sokolov V, Boyko (2019) Efficiency of application of additional strengthening treatment by the surface plastic deformation method for increasing the fatigue durability of details 6. Lebedev V, Sokolov V, Kirichek A (2016) Energy state of a plastically deformed surface layer. In the collection Procedia Eng 7. Shtyn S, Lebedev V, Ivanov V, Kapustyanskiy A (2017) Aviation University Obtaining coatings in vibrowave technological systems based on the energy model of control of the mechanochemical synthesis of the process. Vestnik Akademicheskii P.A. Solovyov 8. Prokopets A, Smirnov S, Shlyakhov N, Vernidub S (2018) WM circulating motion modeling in vibro-abrasive machining based on experimental research. Don State Technical University, Rostov-on-Don, pp 148–150. Collected papers from the international scientific and technical conference “Perspective Lines for Development of finishing, strengthening and vibro-wave technologies”, Rostov-on-Don 9. Tamarkin M, Tishchenko E, Sosnitskaya T, Novokreshchenov S (2017) Reliability control of technological processes of parts processing by dynamic methods of surface plastic deformation. Don State Technical University, Rostov-on-Don
Bypass Bends Deformability of CuZn5 Brass, X10CrNiTi18-9 and C22 Steel at Forming by Euler-Mode Buckling Volodymyr Kukhar , Oleksandr Hrushko , Oleg Markov , Oleksandr Anishchenko , and Andrii Prysiazhnyi
Abstract A new method for bypass bends pipe fittings obtaining by buckling according to the Euler mode was proposed on the basis of an analysis of the tubes axis shaping. Deformation of tubular blanks made of CuZn5 brass and X10CrNiTi18-9 and C22 steel under direct compression with buckling was analyzed. The stress-strain state and the deformability index according to Del’-Ogorodnikov-Nakhaichuk were assessed in the most deformable zone, i.e. along the bisector of the bend, to ensure the required quality, eliminate the corrugation, folding or cracking defects. Calculations of the stress stiffness coefficient, Lode-Nadai stress parameter and the deformation history were carried out using phenomenological approaches, with accounting of the researching materials work-hardening regularities. It is shown that the strain paths in the “hard” and “soft” regions are straight lines, and the lowest plasticity is characteristic of CuZn5 brass blanks, for which the deformability is in the range of 0.34...0.734. Keywords Bypass bend pipe fitting · Transport infrastructure · Phenomenological approach · Stress-strain state · Deformability · Tubular blank · Defect · Buckling · Forming
1 Introduction Bypass bends and pipe bended fittings (bridge short fitting, long bypass bend, etc.) are widely used in liquid and gas supply pipe systems. Materials, shape, production V. Kukhar (B) · O. Anishchenko · A. Prysiazhnyi Technical University “Metinvest Polytechnic”, LLC, 71A, Sechenov Street, Mariupol 87524, Ukraine e-mail: [email protected] O. Hrushko Vinnytsia National Technical University, 95, Khmelnytsky Highway, Vinnytsya 21021, Ukraine O. Markov Donbass State Engineering Academy, 72, Akademichna Street, Kramatorsk 84313, Ukraine © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_158
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scale, requirements for geometry and performance properties of the product are considered when choosing a production process. Currently, there is an intensive research regarding a new free bending process, which includes pushing a pipe through a channel of a flexible bending die [1]. The disadvantage of this process includes the need for great force spent both for forming and overcoming friction in the die channel [2]. As for the rotary draw bending [3], the implemented system of forces can lead not only to ovalization and destruction of the cross-section in the bending zone, but also to tube longitudinal buckling. The centering difficulties must to be encountered in the production of pipes and hollow products using extrusion methods [4]. The work [5] showed production methods of hollow and tubular blanks using deep drawing, including a telescopic punch. The large-sized pipes and hollow products of various cross-sections are produced by open die forging [6]. At the same time, the described forging upsetting operation involves the use of only short blanks to exclude buckling during axial compression. The paper [7] show that the blanks with solid cross-section buckling phenomenon is turned into a positive solution for the case of dieless (impression-free) manufacturing of products with a bent axis. The determination of the application field for tube buckling in obtaining bypass bends shows promising scientific and practical interest. High pipes are deformed by Euler-mode buckling (column buckling) under longitudinal compression [8]. It is necessary to consider the structure and properties of the primary metal, and the resulting complex stress-strain state in order to predict the deformation and quality indicators of products in the development of new technological processes, including pipe buckling [9]. There are requirements for geometry, thermal conductivity, strength, temperature, and corrosion resistance when taking into account the variety of bypass bend applications. Thus, not only constructional steel (C22 type), but also stainless steels (X10CrNiTi18-9 type), and non-ferrous metals are used as a material for tube blanks [10, 11]. Traditionally, this includes Cu-based materials. It should be noted that the deformability of brass pipes is of greatest interest [12] (CuZn5 brass as a special case) in regards to the cracking. It is obvious that buckling without distortion of the flow cross-section is possible only for relatively thick-walled tubular blanks with upsetting in height limited degree. The existing technological limitations require a study of the tubes stress-strain state in order to predict deformation. The rejection criteria for a bypass bend obtained by buckling include: cracks, corrugations, unacceptable ovalization of the section, and significant separation of the blank end from the die face, blank end crushing, folds, and local wall reduction. Taking into account modern concepts of technological mechanics, the deformability index or limiting value of the plasticity margin for a material in the absence of rejection criteria may serve as a complex quality indicator [13]. According to G. A. Smirnov-Alyayev (as indicated in the works [14, 15]), this value is the ratio of the limit deformation e p of the metal to the accumulated deformation ei under the same forming conditions. According to the standard modern stress-strain state, the history of deformation, and the influence on the plasticity of the third invariant of the stress tensor, the limiting value of the plasticity margin (deformability index),
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calculated using the Del-Ogorodnikov-Nakhaichuk dependencies, should not exceed 0.5...0.7 for critical details in the cold deformation processes [14, 15]. Otherwise, the presence of macrocracks, a decrease in endurance, a decrease in the corrosion resistance of pipes, etc. is possible. Thus, the analysis of the deformability of bent connection pipes is carried out, determining the value of the plasticity margin, taking into account the properties of materials and the stress-strain state.
2 Materials and Methods The connection pipes made of materials with functionally different properties were selected as research materials: C22 common constructional steel, X10CrNiTi18-9 corrosion-resistant heat-resistant steel and CuZn5 brass. The preliminary experiments showed that the implementation of the process requires the following conditions: m 0 = L 0 / D0 = 3.3…6.2 and S0 / D0 ≥ 0.17, where L 0 , D0 , and S0 are the initial length (height), diameter, and thickness of the tubular blank, respectively. It is also necessary that engineering strain (εx ), calculated as a relative decrease in height, does not exceed the limit value at which rejection criteria appear. Respectively: εx = L 0 − H f /L 0 ,
(1)
where H f is the final height after upsetting with buckling. The dimensions of the pipe blanks were chosen the same for all cases with the initial diameter D0 = 14 mm. The (L 0 )/(S0 )/(H f ) ratio was preserved with the following sample sizes: No. 1—(L 0 = 70 mm)/(S0 = 3.5 mm)/(H f = 51.5 mm); No. 2—(L 0 = 73 mm)/(S0 = 2.5 mm)/(H f = 62 mm), No. 3—(L 0 = 90 mm)/(S0 = 2.2 mm)/(H f = 79.7 mm). Figure 1 shows examples of upset blanks. When analyzing the mechanics of deformation, it was assumed that the plane section hypothesis is applied at the main stage of deformation by buckling. The following assumptions were used as limits: (i) the tube material is isotropic, hardening; (ii) the process is monotonous; (iii) the shell that is bending blank is considered to be momentless; (iv) corrugation, ovalization, crushing, and other geometric deviations were not taken into account, since they occur beyond the limiting upsetting degrees with buckling. The diagrams of stress-strain curves of materials were formed as a result of tensile tests of materials after annealing, which were approximated by pattern: σi = Aein ,
(2)
where σi —equivalent stress; ei —equivalent strain; A and n—the approximation coefficients of the stress-strain curve for the tube material (Table 1).
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Fig. 1 Tubular blank samples upsetted to different engineering strain (X10CrNiTi18-9, C22, CuZn5)
Table 1 Approximation coefficients for materials stress-strain curves
Material
Function (2) coefficients A (MPa)
CuZn5 X10CrNiTi18-9 C22
Correlation coefficient
n
585
0.196
0.96
1305
0.288
0.95
730
0.205
0.94
The balance of the elements of the outer and inner zones of blank is considered (Fig. 2). Stresses σα and σθ of one sign: in the outer zone—tensile (Fig. 2a), in the inner zone—compressive (Fig. 2b). The elements have double curvature. The curvature is determined by the radius of the middle surface of the pipe r in the cross section, and by the radius of ρ curvature of the axis, that is R1 = (ρ +r ); R2 = (ρ −r ) in the meridional section. The indicated radii are the principal radii of the shell. All the forces are projected onto the normal drawn to the middle surface of the element (see Fig. 2b), and then calculate: σα r Sdθ sin d α + σθ R1 Sdα sin d θ = 0,
(3)
where S—the wall thickness of the deformed pipe, then: σα /R1 + σθ /r = 0.
(4)
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(b)
Fig. 2 The tube upsetting with buckling scheme: stress in the outer (a) and internal (b) elements with double curvature
The action of the longitudinal compressive force in the cross section of the blank causes the neutral layer to shift from the geometric axis of the shell by the amount of eccentricity e = ρδ/(1 + δ), where δ is—the compressive deformation of the blank axis, which is hypothetically assumed to be uniform along the length. In accordance with the plane section hypothesis, the longitudinal logarithmic deformations in a section with curvature (ρ + e) are calculated as follows eα = ln
ρ + r sin θ . ρ+e
(5)
The equations of circular arcs with a radius ρ or a function that is close in appearance to the Gaussian normal distribution curve can be selected for approximation of the blank axis that acquires a shape due to buckling: x − xc 2 y(x) = yc ex p − . Hf w
(6)
Equation (6) was used for the solution and the value w = 0.319 was obtained after processing the data of the preliminary experiments by the least squares method. The curvature radius ρ at each point of the tube bent axis can be defined as 2 1.5 d2 y dy 1 = / 1+ . ρ dx2 dx
(7)
The parameter yc is found under the condition that the change in the length L f of the blank axis during deformation follows the L f = L 0 (1 − δ), where the compressive deformation of the axis is determined by the proposed empirical equation: δ = kδ · (1.716 − 0.263 · m 0 ) · εx .
(8)
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While, kδ = 1...2, where values close to 1.0 should be applied for thick-walled blanks made of plastic materials by significant upsetting. Values close to 2.0 should be applied for thin-walled blanks made of less plastic materials at small εx . The following equation is used applying the known parameters of the axial line function (6):
Hf
L f = L 0 (1 − δ) =
1+
0
dy dx
2 d x.
(9)
Solving Eqs. (9) for yc , taking into account Eq. (2): eα =
3 ei 1 ei (σα − σ0 ) = (2σα − σθ ), 2 σi 2 σi
(10)
where σ0 is the average normal stress. Equivalent stress for the studied case: σi =
σα2 + σθ2 − σα σθ .
(11)
Taking into account the power approximation (2) and Eqs. (4), (5), (10), and (11), after transformations, the following is obtained: σα = Aeαn 2n
r 2+ ρ + r sin θ
−n 1+
r + ρ + r sin θ
r ρ + r sin θ
2 0,5n−0,5 . (12)
The second principal stress is obtained from Eq. (4): σθ = −σα
r . ρ + r sin θ
(13)
The most important characteristic of the material is the plasticity diagram (in coordinates η−e p ). The limit deformation before destruction was calculated as ep =
τp
ξi dτ,
(14)
0
where τ p is the deformation time until the first crack appears. Circumferential (tangential) deformation: 1
eθ = 0.5 · A− n · σi n 1
−1
· (2 · σθ − σα ).
(15)
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Table 2 Calculation results of the deformation paths of tube blanks No. S 0 , mm D0 , mm L 0 , mm H f sample
Hard region η
ei∗
Soft region a2
η
ei∗
a1
1
3.5
14
70
51.5 0.614 0.175 −2.202 −0.242 0.72
2
2.5
14
73
62
3
2.2
14
90
79.7 0.622 0.325 −1.163 −0.269 0.527 1.387
0.668 0.186 −1.779 −0.42
1.052
0.491 1.183
Equivalent strain:
2 ei = √ eα2 + eθ2 + eα eθ . 3
(16)
The stress-strain state of the pipe in the x = H f /2 region is characterized by the maximum of tensile stresses on the outer side and maximum compressive stresses on the inner side. The accumulated deformation at these points is maximum and extreme values of the plasticity margin (deformability index) can occur here. The outer zone is in the hard region (η > 0), and the inner zone is in the soft region (η < 0). The stiffness coefficient of the stress state diagram is defined as [14, 15]: η=
σα + σθ 1+k σθ r 3σ . = =√ ,k = =− 2 σi σi σ ρ + r sin θ 1−k+k α
(17)
The deformation paths in hazardous areas were formed for samples with dimensions given in Table 2 using dependencies (8), (11)–(13), (15), (16).
3 Results and Discussion Figure 3 shows the experimentally calculated points of the deformation history corresponding to different buckling engineering strain εx (from 0 to the final stage) for sample No. 2 (see Table 2). The diagrams originating from points η = −1 and η = 1 are close to straight lines. It should be noted that similar patterns are shown for other samples. The deformation paths were approximated by linear functions: – in the soft region (η < 0): ei = a1 η − 1;
(18)
ei = a1 η + 1,
(19)
– in the hard region (η > 0):
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Fig. 3 Diagrams of material plasticity and deformation paths in hazardous zones for samples No. 1 (1), No. 2 (2), and No. 3 (3), respectively (according to Table 2)
where a1 , a2 —approximation coefficients that depend only on the ratios of the geometric dimensions of the original blank and the deformed sample. The calculation results of deformation paths for characteristic points and coefficients a1 , a2 are summarized in Table 2. Since the deformation path in the soft region has a complex shape, the limiting value of the plasticity margin (Ψ ) will be affected by the index change rate η – (dη/dei ) [14, 15]. G.D. Del–V.A. Ogorodnikov– V.G. Nakhaichuk deformability criterion was used to calculate Ψ , which is based on the nonlinear theory of damage accumulation, taking into account the history of deformation, and in this case has the following form: Ψ = 0
ei∗
0.2· f
ei (1 + 0.2 · f ) · 1+0.2· f dei ≤ 1, e p (η)
(20)
dη where f = ar ctg de and e p (η)—the value of the plasticity diagram, which correi sponds to the value ei of the deformation path; ei∗ —value of the accumulated equivalent strain in the dangerous area. The plasticity diagram was approximated by the equation:
e p (η) = e p (η = 0) · ex p(−λ1,2 η), e (η=0)
e (η=−1)
(21)
where λ1 = ln e pp (η=1) and λ2 = ln epp (η=0) —the sensitivity of the material to changes in the hard (η > 0) and soft (η < 0) regions; e p (η = −1), e p (η = 0), e p (η = 1)— value of accumulated deformation at η = −1, η = 0, η = 1, respectively, which are given in Table 3 for CuZn5 brass, X10CrNiTi18-9 stainless steel and C22 steel. The equations were obtained using formulas (18) and (19) in criterion (20), which were integrated using MathCad software:
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Table 3 Limiting plasticity for materials Material
Compression, torsion and tensile plasticity e p (η = −1),
e p (η = 0)
e p (η = 1)
CuZn5
1.75
0.60
0.45
X10CrNiTi18-9
1.40
1.05
0.78
C22
1.57
1.10
0.65
Table 4 Calculation results of the utilized plastic margin for some blanks No. sample
Utilized plasticity margin (Ψ ) CuZn5
X10CrNiTi18-9
C22
Region Soft
Hard
Soft
Hard
Soft
Hard
1
0.612
0.466
0.530
0.304
0.455
0.375
2
0.340
0.483
0.325
0.313
0.274
0.389
3
0.411
0.734
0.359
0.465
0.307
0.58
ei∗
Ψ = 0
Ψ = 0
ei∗
[1 + 0.2 · ar ctg(a1 )] · e0.2·ar ctg(a1 )
1+0.2·ar ctg(a1 ) dei ; e p (η=−1) e p (η = 0) · ex p −ln η=0 · (a1 ei − 1)
(22)
[1 + 0.2 · ar ctg(a2 )] · e0.2·ar ctg(a2 )
1+0.2·ar ctg(a2 ) dei . e (η=0) e p (η = 0) · ex p −ln pη=1 · (a2 ei + 1)
(23)
The calculation results Ψ of the considered pipes are given in Table 4. It was found that the deformation paths in dangerous zones during buckling are linear functions of ei (η). The highest depletion of the plasticity margin is observed in brass samples No. 1 and No. 3, which is associated with the low plasticity of this material under severe stress states. The plasticity margin of the remaining samples is quite high, which indicates their satisfactory technological heredity and the required level of strength and performance characteristics.
4 Conclusions The manufacture of bypass bends and tube bended fittings by impression-free (dieless) forming based on the Euler-mode buckling was evaluated. The evaluation of the deformability and technological heredity for CuZn5 brass, X10CrNiTi18-9 and C22 steel made bypass bends obtained by buckling, has been carried out. It is shown that the highest plasticity margin utilizing (Ψ = 0.340–0.734) are observed in brass samples; the smallest values (Ψ = 0.304–0.53) are typical for X10CrNiTi18-9
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stainless steel, which is a material with high values of flow stress, that also has high plastic properties. It was found that during deformation of blanks with S0 to D0 ratio in the range of 0.157 – 0.25 to engineering strain εx = 0.11 – 0.26, the residual plasticity of all blanks is sufficient to ensure satisfactory technological heredity.
References 1. Guo X, Ma Y et al (2018) Simulation and experimental research of the free bending process of a spatial tube. J Math Proc Tech 255:137–149. https://doi.org/10.1016/j.jmatprotec.2017. 11.062 2. Chen H, Wang H et al (2021) Impact of bending dies with different friction forms on forming force and quality of tubes manufactured by free bending technology. Chinese J Aeronaut 34(4):253–264. https://doi.org/10.1016/j.cja.2020.08.029 3. Safdarian R (2020) Investigation of tube fracture in the rotary draw bending process using experimental and numerical methods. Int J Math Form 13(4):493–516. https://doi.org/10.1007/ s12289-019-01484-5 4. Hrudkina N, Aliieva L et al (2020) Predicting the shape formation of hollow parts with a flange in the process of combined radial-reverse extrusion. East-Eur J. Enterpr Tech 4(1-106):55–62. https://doi.org/10.15587/1729-4061.2020.203988 5. Arhat R, Puzyr R, Shchetynin V, Moroz M (2021) The manufacture of cylindrical parts by drawing using a telescopic punch. In: Lecture notes in mechanical engineering, pp 363–372. https://doi.org/10.1007/978-3-030-68014-5_36 6. Markov OE, Gerasimenko OV, Kukhar VV, Abdulov OR, Ragulina NV (2019) Computational and experimental modeling of new forging ingots with a directional solidification: the relative heights of 1.1. J Braz Soc Mech Sci Eng 41(8):310. https://doi.org/10.1007/s40430-019-1810-z 7. Kukhar V, Burko V, Prysiazhnyi A, Balalayeva E, Nahnibeda M (2016) Development of alternative technology of dual forming of profiled workpiece obtained by buckling. East-Eur J Enterpr Tech 3(7(81)):53–61. https://doi.org/10.15587/1729-4061.2016.72063 8. Murawski K (2021) Experimental comparison of the known hypotheses of the lateral buckling for semi-slender pinned columns. Int J Struct Glass Adv Math Res 5(1):82–114. https://doi. org/10.3844/sgamrsp.2021.82.114 9. Shatskyi I, Makoviichuk M, Perepichka V, Dalyak T (2017) Effect of cracks closure in plates and shells under combined tension and bending. Eng Mech 866–869 10. Shapoval A, Drahobetskyi V, Savchenko I, Gurenko A, Markov O (2020) Profitability of production of stainless steel + zirconium metals combination adapters. Key Eng Math 864:285– 291. https://doi.org/10.4028/www.scientific.net/KEM.864.285 11. Tkachov RO, Kukhar VV, Klimov ES, Prysiazhnyi AH (2019) Development and application of tube end forming process with combined swaging and local differential pre-heating. Math Sci Forum 946:755–760. https://doi.org/10.4028/www.scientific.net/MSF.946.755 12. Smith E, Wilding MJ (1983) The effect of non-uniform bending deformation on the stability of circumferential growth of through-wall cracks in brass tubes. J Mech Phys Solids 31(3):223– 229. https://doi.org/10.1016/0022-5096(83)90023-6 13. Gonchar AV, Mishakin VV, Klyushnikov VA (2018) Estimation of plasticity margin in stainless steel by the thermo-ultrasonic method. AIP Conf Proc 2053:030021. https://doi.org/10.1063/ 1.5084382 14. Del’ GD, Ogorodnikov VA, Nakhaichuk VG (1975) Criterion of the deformability of metals during mechanical working. Izv Vyssh Uchebn Zaved Mashinostr 4:135–140 15. Solona O, Derevenko I, Kupchuk I (2019) Determination of plasticity for pre-deformed billet. Solid State Phenomena 291:110–120. https://doi.org/10.4028/www.scientific.net/SSP.291.110
Computerized Hardware and Software System for Investigation of Welding Defects of High-Strength Steel Based on a Subminiature Eddy-Current Transducer Vladimir Malikov , Alexander Katasonov , Nikolay Tihonskiy , Viktorya Kozlova , Ekaterina Valulina , Anatoly Sagalakov , Sergey Dmitriev , and Alexey Ishkov Abstract The article presents the results of the creation of a computerized defect detection system targeted at defect finding in welded joints of high-strength steels. As the research object, welded joints of transformer tanks made of steel were selected. The choice of this type of metal is conditioned by the ultra-low carbon content, which opens up prospects for the application of nondestructive testing using eddycurrent methods. To perform direct measurements, a scanning system was designed and brought in an optimal state, which included a transducer based on the principles of eddy currents and having three circuits assembled on an 80NMZ ferrite core. The system operation was controlled by a specially developed software controlling the signal generation and reception units, and noise filtering using analog and digital signal filters. The system was tested using samples with modeled continuity defects (cracks and holes). Also, modeling of corrosion defects in welded joints was carried out as a part of the study. Keywords Defect detection system · Nondestructive testing · Ultra-low carbon steels · Welded joints
1 Introduction Ultra-low carbon high strength steels have attracted extensive attention, because of their excellent comprehensive performance and superior weldability. Specifically, the satisfactory combination of high strength, remarkable low-temperature impact property and superior weldability has made the ultra-low carbon high strength steels become an indispensable material for jumbo size steel plates used for bridge, ship V. Malikov · A. Katasonov · N. Tihonskiy · V. Kozlova · E. Valulina · A. Sagalakov · S. Dmitriev Altay State University, Lenina, 61, Barnaul, Russia A. Ishkov (B) Altay State Agricultural University, Krasnoarmeysky, 73, Barnaul, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_159
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hulls, pressure vessels, and offshore structures [1]. Assessing and predicting impact toughness of high strength steel has always been an active field of research [2, 3]. Specific or complex deep drawing operations with a high plastic strain ratio, good elongation, high hardening index and low yield to tensile strength ratio can be performed by this type of steel. These properties provide an advantage to the application of sheet stamping in industries. The development of new types of high-strength steels contributed to the development of research in the field of assessing the strength characteristics of their welded joints. It should be recognized that despite the significant development of technological processes, welded joints are still inferior to the base metal. Joining of low carbon steel for multi-component fabrication in an automobile industry is very important. Welding is most appropriate for joining. Presently, continuous research and development are being executed to improve the weld properties. Initially, welding was performed on aluminium and its alloys. Later, welding was applied on magnesium and its alloys due to both materials low melting point. Recently, welding has proven to be perfectly appropriate for welding high-melting temperature alloys, such as Fe- [4], Ni- [5], and Ti-based alloys [6]. Due to the specific features inherent in the technology of creating welded seams, this type of connection of structural elements is not able to approach the base metal in terms of mechanical properties. In addition, due to the same technological features, the welded joint, regardless of the metal, is distinguished by an increased inhomogeneity of the substance and an increased degree of internal stresses, which reduce reliability. In addition, in this regard, it becomes possible for the occurrence and propagation of cracks in it. Low strength match, equal strength match and high strength match are the three strength matching relations of welded joint and base metal. Relevant literature [7–9] thought that the welded joint fracture toughness of middle low carbon and middle low strength steel was good under high strength match but it lacked of quantitative analysis and demonstration. During repair using welding in butt welded joints, various defects may be formed, the admissibility standards of which are given in the current regulatory and technical documentation. The resulting defects in welded joints adversely affect the life, reducing their reliability and safety [10, 11]. To determine the defectiveness of a welded joint, a rich arsenal of non-destructive testing methods is currently being used, the use of which is laid down in methods for assessing the technical condition welding [12]. But the existing methods for predicting the life of technical systems do not take into account the fact that each welded joint has an individuality, which depends on the geometric dimensions of the welded joint, the presence of defectiveness, the type of defect, allow you to reject the weld only by the parameter of “admissibility” of defects and do not give a qualitative assessment of further term of safe operation of welded joints [13].
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The list of spheres of application of welded joints on high-strength steels includes the industrial production of tanks for TMG transformers. Structurally, these transformers are made in the form of metal tanks, inside of which are placed the necessary windings of copper or aluminum wire, or foil on the low voltage (LV) side. As a rule, three methods of non-destructive testing are used to check the condition of welded joints in the steel shell of a transformer, namely, ultrasonic, X-ray [14], and magnetic particle methods. However, it should be noted that electromagnetic methods, including those using the principles of eddy currents, are most accurate in relation to surface discontinuities. This approach to non-destructive testing makes it possible to promptly identify defects, determine their linear dimensions, as well as the depths. The convenience and complex nature of the information obtained allows drawing conclusions about the state of the welded joint. In addition, as experience shows, after applying protective or insulating coatings, as well as due to the natural roughness of surfaces, the use of methods other than eddy current becomes problematic. Eddy current inspection is based on the principles of electromagnetic induction and is used to identify or differentiate amongst a variety of physical, structural, and metallurgical conditions in electrically conductive ferromagnetic and nonferromagnetic metals and metal parts. Since defects are detected based on a local change of the electrical conductivity in the material, previous knowledge on the electrical conductivity field variation due to processing is required in order to distinguish background material from defects. The inspection is done by characterizing the variation of the Electrical Impedance (EI) of the probe coil, caused by any defects in the material. The EI is the opposition offered by an electrical component when an alternating sinusoidal current is flowing across it at a given frequency. The testing frequency has a direct influence on the induced currents density profile. Increasing the frequency leads to eddy currents more concentrated near the surface. Reducing the testing frequency will lead to deeper penetration of the eddy currents into the material or the part. Testing frequency is often chosen taking into account the standard depth of penetration (δ) and the expected defect depth. The standard depth of penetration is defined as the depth at which eddy currents density is reduced to e−1 ≈ 36.78% of the surface density. The applicability of the eddy current method for monitoring the state of metal in TMG transformers is due to two circumstances: the approach allows detecting corrosion damage inside steel; the method does not require direct contact of the detector with the surface of the controlled object [15]. At the same time, the installations on the market are characterized by insufficient sensitivity to weak distortions of the magnetic field. This is a problem since such low distortions are usually associated with local defects located under the surface of the scanned object. A number of publications [16–19] present the development of eddy current sensors with increased sensitivity. For example, a group of researchers led by Park [16] has created a scanning device capable of detecting shallow defects in pipes with a diameter of 8 inches. As part of their work, the researchers managed to achieve a 200% increase in scanning efficiency with a system of several sensors. A group led by R. Kumar succeeded in creating compact sensors capable of detecting
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structural disturbances in matter in 12 mm thick carbon steel plates. The researchers noted that the compact sensors outperform standard sensors in terms of sensitivity and measurement locality. Attempts to create scanning installations from several sensors are presented in the work of Gruger [17], who created an array of compact eddy current sensors. Development testing carried out on a 1.5 mm thick steel plate successfully identified holes with a diameter of 2 mm. In their writings, Sharatchandra et al. [18] have studied defects in the form of metal thinning hastily. The object of the study was a 64 mm crawler rope used in the mining industry. Scanning flaw detection installations currently on the market often consist of permanent magnets, which are designed to magnetize the test object, as well as Hall sensors or measuring coils for direct reading of magnetic field indicators [19]. A wide range of such devices is united by insufficient efficiency in detecting local and subsurface disturbances in the structure of matter. The solution to this problem requires the use of highly sensitive devices that are able to register weak magnetic fields associated with defects in the metal (for example, the walls of the transformer tank). In this regard, an important and urgent task is to develop recommendations for assessing the “individual” resource of welded joints using non-destructive testing methods, in order to timely identify welds with the smallest resource to ensure reliable operation of the equipment and the inadmissibility of premature failure in the weld zone. Taking into account the above, we have chosen as the purpose of this work to study the correlation between the eddy current transducer signal amplitude and structural disturbances in of steels of the K65 strength class. Also, within the framework of the work, data will be given on the applicability of the developed flaw detection installation, using the principles of eddy currents, to the problem of identifying defects in continuity and corrosion in this type of metal.
2 Experimental Technique At the preparatory stage, in order to improve the accuracy of the measurements at the test objects, samples was created knowingly having defects with known parameters, such as the depth of the defect, the size of the defect, and the type of defect. This step made it possible to test the developed software and hardware-scanning complex (SHSC) [20, 21] on model defects and to determine the control values of the obtained indicators, as well as to get an idea of the behavior of the system in each specific case. The oil tank of the TMG-400/10/0.4 transformer served as the basis for creating samples with model defects. The walls of this tank are made of welded steel sheets, 2 mm thick. During the creation of welded joints, defects were created in the thickness of the welded seam. Defects were made by drilling and sawing metal to different depths. Such defects were identified as model defects.
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Fig. 1 Photograph of a sample № 1: two cracks located at a depth of 0.6 mm (1) and 1.2 mm (2)
Figure 1 shows a photograph of a sample of a steel weld with structural disturbances in the substance in the form of two cracks located at a depth of 0.6 mm (1) and 1.2 mm (2) (Sample № 1). Figure 2 shows a photograph of a sample of a steel weld with structural damage in the form of a point corrosion damage (Sample № 2). Figure 3 shows a photograph of a sample of a steel seam with violations of the structure of the substance in the form of lack of penetration with different degrees of filling of the weld (from 30 to 90%) (Sample № 3). Figure 4 shows a photograph of a sample of a steel weld without model defects, for comparison (Sample № 4). The scanning installation includes an overhead eddy current transducer (ECT) consisting of three elements: a coaxial generating inductance coil, a measuring coil, and a special circuit that is necessary to compensate for the effect of the generating coil on the readings. The general scheme of the installation is as follows: the generator creates a current that is directed to the generating winding of the transformer and creates a magnetic field. The measuring and compensation circuits are included in the circuit in such a way that in the absence of a controlled object near the transformer, the signal from the ECT is zero. When a conductive object appears in the area of the measuring circuit, the magnetic field from this coil induces eddy currents in the controlled object. They, in turn, initiate the appearance of a useful signal about the structure of the substance in the measuring coil. The unit also includes an additional electronic unit. Its functional load consists in the quantitative indication of the signal recorded from the measuring coil. In this case, the received signal is a change in the electromotive force induced on the measuring circuit of the converter.
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Fig. 3 Photograph of a sample № 3: violations of the structure of the substance in the form of lack of penetration with different degrees of filling of the weld (from 30 to 90%)
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Fig. 4 Photograph of a sample № 4: without model defects
The ECT of the installation developed by us has the following parameters: the diameter of the generating winding is 0.5 mm; the measuring winding is 0.1 mm. The frequency of the current supplied to the generating circuit was selected in such a way as to maintain the sensitivity of the system at depths of up to 2 mm and was 2 kHz. The technological gap between the surface of the test object and the transducer was 0.2 mm. To maintain the gap, an aluminum plate 0.1 mm thick was used, which conducts an electric current. The sample itself was made from a sheet of thin steel St-20, which obviously had various violations of the structure of the substance. The ECT described in this paper is under the control of the developed hardware and software complex VDSS-8. In order to prepare the readout indicators for visualization, the signals received from the transducer were processed by the electronic unit of the transformer meter, combined with the spectrum analyzer of the recorded signal. As a result, it was possible to display a picture on the screen and visualize the received data in a form that is easy to understand. The hardware and software complex was designed in such a way as to provide the ability to fine-tune the scanning system for a specific test object, thereby increasing the efficiency and convenience of working with the system. The regulation of the installation implies entering the amplitude and phase parameters into the SHSC computing unit with further determination of the coefficient of the inverse transformation function. The data inside the system is adjusted in accordance with the thickness of the control object and the size of the technological gap between it and the transmitter. At the next step, the
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signal indicators are recorded in the absence of a control object and with a zero gap between it and the converter. These data play the role of extreme beacons, between which the true values of subsequent measurements will be located.
3 Research Results and Their Discussion After the completion of the tuning step, the transducer is positioned over the object surface in such a way as to be able to move the ECT at a constant speed and transmit the received data in the form of a graph attached to the points of the weld of the object. The coordinate of the ECT location was changed discretely with a step of 5 mm and was taken as the distance from the edge of the object to the point of the current location of the sensor at a given moment. During the measurement, the value of the voltage applied to the measurement circuit was chosen as the parameter carrying the useful information load. Based on these data, conclusions were drawn about the presence of defects in the scanned area. The change in the introduced voltage on the displacement of the ECT along the test object No. 1 is shown in Fig. 5. The graphs below illustrate the received signal at a current frequency on the excitation circuit of 500 and 3000 Hz. Correction of the change in the introduced voltage in the zone of action of the edge effect was carried out according to the voltage recorded in the center of sample № 4, which obviously had no defects. As the obtained data show, in the zone of defect № 1, which was located at a depth of 0.6 mm, the voltage on the measurement circuit is significantly reduced. In this case, the decrease in the applied voltage is exponential. A similar correlation is noted when analyzing the data obtained by measuring at frequencies of both 500 and 300 Hz. At the same time, in the case of defect № 2, the depth of which is 1.2 mm, we got a slightly different picture. In particular, when scanning at a frequency of 500 Hz, the voltage decrease is similarly exponential, while at a frequency of 3000 Hz, the decrease in the applied voltage is rather linear. The greater depth of occurrence, which does not allow providing the required measurement accuracy at high frequencies, can explain such a discrepancy. Fig. 5 Change in voltage amplitude when scanning sample № 1
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Fig. 6 Change in voltage amplitude when scanning sample № 2
The indicators obtained by moving the ECT along the sample № 2 having a model defect in the form of a point damage to the welded joint of a corrosion nature are shown in Fig. 6. We can observe a significant dip in the ECT signal. Compared to sample № 1, the dip is shorter and well discernible regardless of the frequency on the drive circuit of the converter. The change in the parameters of the voltage introduced to the measurement circuit during the examination of sample № 4 is shown in Fig. 7. In this case, the model defect was insufficient penetration of the weld with a filling degree of 30 to 90%. As can be observed, a defect with a filling degree of 30% is well recorded at any frequencies, and the voltage decrease is exponential at both 500 and 3000 Hz. With a filling degree of 60%, high frequencies show a significantly lower scanning efficiency. The greater depth of the defect and the distribution of the seam substance closer to the plane of the sensor movement can explain this. Defective welds with a filling degree of 90%, according to the data obtained, do not differ significantly from welded joints that do not have defects at all. The measurement results are shown in Fig. 8. Fig. 7 Change in voltage amplitude when scanning sample № 3
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Fig. 8 Change in voltage amplitude when scanning sample № 4
4 Summary The work carried out has convincingly shown the possibilities of using the eddy current method for detecting violations of the structure of matter in welded joints of steel alloys, which are used in the manufacture of cases of oil transformers. The installation showed a high sensitivity to corrosion defects, cracks in the thickness of the welded joint, as well as to insufficient weld penetration. As the measurements have shown, depending on the frequency, there are differences in the information content of the signal from defects located at different depths. It was found that to obtain a complete picture of the type and depth of the defect location, it is necessary to change the frequency during scanning, as well as a corresponding change in the signal amplitude. Acknowledgements This project was funded by the Russian Science Foundation, project No. 2179-00026 «Development of hardware and software complexes for the study of conductive materials based on subminiature eddy-current transducers».
References 1. Roth CC, Mohra D (2014) Effect of strain rate on ductile fracture initiation in advanced high strength steel sheets: experiments and modeling. Int J Plast 56:19–44 2. Lee J (2015) Properties controlling the bend-assisted fracture of AHSS. Int J Plast 75:100–120 3. Zhao Y, Xu S (2017) Enhancement of low temperature toughness of nanoprecipitates strengthened ferritic steel by delamination structure. Mat Sci Eng A 691:162–167 4. Ueji R, Fujii H et al (2006) Friction stir welding of ultrafine grained plain low-carbon steel formed by the martensite process. Mater Sci Eng A 423:324–330 5. Ye F, Fujii H, Tsumura T, Nakata K (2006) Friction stir welding of Inconel alloy 600. J Mater Sci 41:5376–5379 6. Su F, Song R, Wen Z (2020) Experimental research on oxidation of ultra-low carbon interstitialfree steel at high temperatures in rolling. Adv Eng Sci 52(2):200–206 7. Peng XN, Peng XK, Du ZJ (2018) Study on microstructure and fracture behavior of fusion zone of ultra high strength steel low matched welded joint. Hot Work Tech 47:44–47
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8. Wu GF, Luo Y (2010) Microstructure and properties of Gr91/12Cr1MoV dissimilar steel welded joint of high strength match. Weld Tech 39:8–11 9. Wang Y (2020) Research on microstructure and performance of welded joint of high strength match. IOP Conf Ser Earth Env Sci 585:012159 10. Kulakov PA, Kutlubulatov AA, Afanasenko VG (2018) Forecasting of the hydraulic fracturing efficiency as components of its design optimization. Socar Proc 2:41–48 11. Roxas C, Bernardo L (2019) An artificial neural network model for the corrosion current density of steel in mortar mixed with seawater. Int J Geom 16(56):79–84 12. Cozzani M (2019) 3-dimensional finite element analysis of the outcomes of Alexander, Gianelly, Roth and MBT bracket prescription. Int Orthod 17(1):45–52 13. Naumkin EA et al (2020) The assessment of the individual resource of the welded joint during repairs of the technological pipeline. IOP Conf Ser Mater Sci Eng 734:1–8 14. Sundaram BA, Kesavan KS (2018) Recent advances in health monitoring and assessment of in-service oil and gas buried pipelines. J Inst Eng Ser A 90:729–740 15. Rifai D, Abdalla A, Razali R (2017) An Eddy current testing platform system for pipe defect inspection based on an optimized eddy current technique probe design. Sensors (Basel) 17(3):579–603 16. Park GS (2002) Improvement of the sensor system in magnetic flux leakage-type nondestructive testing (NDT). IEEE Trans Magn 38(2):1277–1280 17. Gruger H (2007) Array of miniaturized fluxgate sensors for non-destructive testing applications. Sens Actuat 106:326–328 18. Sharatchandra WS (2011) GMR-based magnetic flux leakage technique for condition monitoring of steel track rope. Insight 53(7):377–381 19. Zhang J, Liu X (2019) A comparative study between magnetic field distortion and magnetic flux leakage techniques for surface defect shape reconstruction in steel plates. Sens Act A Phys 288:10–20 20. Dmitriev SF, Malikov VN (2021) Scanning the thickness of conductive and dielectric coatings using superminiature eddy current probe. In: Lecture notes in civil engineering 130:548–554 21. Dmitriev S, Malikov V, Sagalakov A (2020) Subminiature Eddy current transducers for thickness measurement problems. J Mach Manuf Rel 49(9):783–786
The Problem of High Humidity in the Ice Arena and Ways to Solve It Evgeniy Neverov , Igor Korotkiy , Dmitry Goleshov , Maxim Mokrushin , and Pavel Korotkih
Abstract This paper reviews the problem of high humidity in the ice arena in Sochi and ways of solving it. The authors consider ventilation system structure and identify the causes of the high humidity—moisture in the water vapor form and a cold surface of ice which cools the surrounding space and objects. The consequences of this air state are fogging over the ice surface; condensate formation which worsens the quality of ice rink; corrosion of steel and iron structures; mold attack. In addition, the facility microclimate is uncomfortable for people to stay there. In the course of the study, the authors identified several ways to achieve the necessary indoor air parameters. The first method is sorption dehumidification. This system is able to function at low temperatures and to cope with extreme dampness, but it has significant costs. The second method, more simple and more effective, is assimilation. This method is based upon the ability of warm air masses to hold a larger amount of water vapor in comparison with the cold ones. This way of improving the air parameters is more effective when required to modify an already-existing ventilation system. In this particular case, in the ice arena in Sochi, assimilation was the most effective method. Air coolers with a drift eliminator were installed in the already-existing ventilation system. The calculation of the selected heat exchangers was carried out using the ventilation equipment selection software (VESS). Keywords Transport infrastructure · Ventilation system structure · High humidity · Air parameters
1 Introduction According to the International Ice Hokey Federation, Russia has 419 indoor arenas. At the same time, the construction of new and reconstruction of an already-existing ice arenas of different purposes is rapidly progressing. E. Neverov (B) · I. Korotkiy · D. Goleshov · M. Mokrushin · P. Korotkih Kemerovo State University, 6 Krasnaya Street, Kemerovo 650000, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_160
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It is impossible to further develop this direction without taking to another level technical equipment, automation and security of this facilities. Comfortable and healthy living conditions for people depend on different factors. One of them is the microclimate. The working efficiency of a person significantly decreases in uncomfortable conditions, such as heat, cold, excessive humidity, stuffiness and others. Moreover, the microclimate influences surrounding objects, such as the ice surface, steel structures, and others. Modern sport facilities with artificial ice are complexes of engineering systems, including refrigeration supply systems, ventilation and air conditioning systems, lighting, security systems, sport equipment and so on [1, 2]. Ice sport facilities demand more capital investments during construction and subsequent operation. To date, these buildings are energy demanding and require flexible individual approach at the planning phase, especially in terms of engineering and technical equipment. The appliance of modern technology of excess heat disposal enables a possibility to make them comfortable for visitors and save significant financial resources. Technological equipment of the modern ice sport facilities is a combination of many systems. This includes systems of refrigeration supply, air conditioning, water supply, heat supply, sewerage, electricity supply, various types of security and so on. In ice arenas, humidity problems arise because of two reasons: moisture in the water vapor form and a cold surface of ice, which cools the surrounding space and objects. The main moisture source on the rink is the outside air, which enters through ventilation. High moisture concentration in the air leads to condensation and fogging indoor, that, in turn, leads to mold attacks and putrefying. Indoor fog is usually formed by mixing outdoor air and cold air over the ice surface. Condensation is usually formed on the ceiling and objects due to temperature decreasing below ambient dew point. Condensate formation worsens the quality of ice rink and makes it unsafe to use. Corrosion of steel and iron structures occurs at a humidity of more than 60%. Mold attacks occur at a humidity of more than 70%. Also, with high humidity, the indoor microclimate is uncomfortable and the air feels “damp” and “sticky” [3–6]. The optimal humidity level depends on the tasks, assigned to the dehumidification system. The air distribution systems adopted in the projects for facilities with ice surface (rinks of different purposes, ice arenas, etc.) largely determine the state of the microclimate in the area of the ice surface and viewing stands, as well as the ice state. This article overviews the requirements for indoor air parameters, the main decisions for air conditioning systems and air exchange and air distribution schemes. It is established that reliable predication of the indoor air parameters, analysis and optimization of air distribution schemes are impossible without appliance of methods of numerical modelling of temperature, velocity and humidity fields in the airspace. The authors checked design choices for the air distribution systems with modelling of temperature, velocity and humidity fields in the airspace for the warm period of the
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year. Entering of adjustments to the design air distribution scheme made it possible to get rid of stagnation in the area of the ice surface, to obtain air temperatures of 14.5–20.5 °C in the viewing stands zone, and to ensure the relative humidity in the area of the optimal value—55% in the stands zone [2, 7, 8]. It is necessary to maintain all year round optimal parameters of the indoor air in the design of air conditioning systems for facilities with ice surface (rinks of different purposes, ice arenas, etc.). The aim is to provide required parameters in the zone where people are training and in the viewing stands zone. In each of these zones it is necessary to maintain varying and different parameters of the indoor air. The ice state largely depends on the temperature and ice surface air humidity, as well as on the even distribution of these parameters across the rink. Well-known problems of such facilities are: 1) condensation on the surface of building envelopes (at a relative air humidity of more than 60%, corrosion of steel fastening and supporting structures occurs; condensation spoils the paint); 2) condensation on the ice surface (the ice thickness increases undesirably and uncontrollably, causing quality loss); 3) condensation on the glass between the rink and the viewing zone (it prevents the observation of the game); 4) fogging (the fog disturbs viewers and sportsmen). It is a technically complex and costly task to maintain the required parameters of the temperature, velocity and humidity of the air in the serviced zone with the ice, on the surface of which it is also necessary to provide certain temperature. The state of the microclimate and ice surface largely depend on efficiency of the air distribution systems and structure of the air exchange systems. In the technical literature on ventilation and air conditioning systems of ice rinks and ice arenas, the information about recommended schemes of air exchange and air distribution systems is scattered. At the same time, there are different approaches to the decisions of air conditioning systems for sport facilities for different competition types. This articles systematizes the information of the decisions of air conditioning systems for ice sport facilities with viewers. It is impossible to analyze and optimize the air distribution systems, as well as predict reliably the parameters of the indoor air, without appliance of methods of numerical modelling of temperature, velocity and humidity fields in the airspace [9–12].
2 Methods and Materials Consider the structure of the ventilation system of the ice arena (Fig. 1). It consists of: P1—external air inlet; P2—ductwork; P3—damper; P4—flexible connector; P5—fresh air valve; P6—heater; P7—cooler; P8—fresh air ventilator; P9—silencer; P10—air distribution components; SY—control system. On addition of the air recirculation to the system, it would be possible to mix the indoor air with the outdoor one. Closing the damper P3 completely on partially provides regulation of the incoming humidity and its collection in the heat exchanger of the cooler. That makes it possible to dry the air without a large additional cost.
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Fig. 1 Structure of the ventilation system
There are several ways to achieve the required air parameters: 1. Sorption dehumidification. The main element is the rotor, passing through which the air masses are drained and thus get rid of excess liquid. The system is able to function at low temperatures (up to −40 °C), to cope with extreme dampness and is compatible with the pre-cooling air devices, but it requires significant costs (adsorption process, air passes through a material that adsorbs moisture); 2. Assimilation. This method is based upon the ability of warm air masses to hold a larger amount of water vapor in comparison with the cold ones. This method is relatively simple and effective in cases when it is necessary to modify an already-existing system, as in this very case (condensation process, air cooling to the condensation temperature). The air parameters for the indoor arenas with viewers (with the calculated parameters of the outdoor air “B”): in the cold period of the year: temperature +18 °C; relative humidity 30–45%; in the warm period of the year: temperature maximum +26 °C; relative humidity maximum 60% (on rinks: temperature maximum +25 °C; relative humidity maximum 55%). The warm period of the year is the calculation period to measure refrigeration capacity of the refrigeration stations. The article also normalizes the parameters of the indoor air for the viewer stands zone, the zone where people are training and for the ice temperature according to the specifics of the ice sport type. For the rinks, the air temperature is normalized at the height of 1,5 m above the ice surface. The temperature depends on the ice sport type, for which the arena is built.
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3 Results and Discussion To prevent condensation formation on the ice rink surface and to preserve the speed properties of the ice, the relative humidity should be maintained above the dew point of the air layer over the ice surface. It is recommended to limit the speed of the air flow over the ice surface to 0.25 m/s. According to the article about the technological requirements for figure skating and short track competitions on the ice rink, at the height of 1 m above the ice surface and the air speed of maximum 0.2 m/s, it is necessary to maintain the temperature of +14 °C, relative humidity of 40% and moisture contents of 4 g/kg of dry matter. Under these conditions, the air dew point is about 0 °C. The ice surface of a large area has a significant impact on the microclimate in the airspace. In addition to convective heat transfer, radiant heat exchange between the ice surface and the surrounding surfaces makes a significant contribution to the thermal balance. The radiant heat exchange between the ice surface and the cover is the most pronounced. As a result, the cover and its beams are significantly cooled. If the cover temperature is below the ambient dew point, moisture from the air condenses on the cooled surfaces. Appeared dripping influences building structures and the quality of the ice surface. For example, the water vapor condensation was observed on the surfaces of the metal trusses and the cover. To avoid this, it is necessary to control the temperature and humidity conditions and dry the air in the cover area and farms [13–15]. In the design of the air conditioning systems for facilities with ice rinks, such as indoor ice rinks, indoor arenas, etc., it is necessary to solve the problem of condensation formation on the internal surfaces of the outer shell. To avoid condensation on the outer shell at the surface temperature of −3 °C, the dew point should be maintained at 4–5 °C. The air temperature of the indoor ice rinks usually varies from +10 °C without viewers to +8 °C with viewers. On the surface of building structures, the temperature should be 0.5–1 °C above the dew point of the air adjacent to the structures. There are several ways to avoid condensation on the outer shell:— painting the surfaces with the aluminum paint or covering with aluminum foil to decrease radiant heat exchange;—placing heat screen between cover and ice surface (suspended ceiling); air blowing of the upper area of the facility with heated air;—air dehumidification of the upper area of the facility. The scheme of the fresh air supply at border between the viewer stands and the ice rink is suitable for ice hockey competitions, but it cannot provide the required air parameters for figure skating. Therefore, it is logical to supply the fresh air to the ice arena directly. For this purpose, a ring air collector was provided above the arena. The fresh air supply for the lower layer of the viewer stands is provided at the floor through grilles, installed under each seat. However, it causes a significant non-isothermal flow (in height and in horizontal sections); interaction of the fresh air flows and viewers convection currents; impact of the radiant heat exchange on the surrounding surfaces and structures. When the fresh air is supplied to the area of the ice rink, the air jet spreads as “cold” in the surrounding air, and when it approaches the ice surface, it begins to behave as “warm”. Accordingly, it is difficult to determine the
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non-isothermality coefficients for the fresh air jets when using “traditional” methods for calculating air distribution. This article also considers one of the inexpensive ways to improve the air parameters: the selection of the channel water cooler. For the selection, certain parameters of the heat exchanger were given: – – – – – –
The inlet air temperature is 30 °C; The outlet air temperature is 16 °C; The propylene glycol; The inlet coolant temperature is 0 °C; The outlet coolant temperature is 5 °C; The air flow of the required unit is 2035 m3 /h.
Figure 2 shows an example of a ventilation equipment selection software (VESS). Figure 3 demonstrates some calculated characteristics of the selected equipment and its scheme. The selected input unit SlimLine 70–40/R [Cassette Filter G4] [WC.6] has overall dimensions 910 * 680 * 620, insulation thickness of 25 mm, galvanized steel apparatus casing, standard section connection and non-adjustable support frame. The unit weight is 123,75 kg. The filter is 700 mm wide, 400 mm high, 210 mm long. The filter weight is 23 kg. The filter type is the cassette G4. The water cooler is 910 mm wide, 620 mm high and 510 mm long. The weight is 52 kg. The liquid used is the propylene glycol. The capacity reaches 24,76 kW. The coolant flow is up to 4,53 m3 /h; the volume is 5,63 L. The cooler has 6 rows, 12 contours. The ribs distance if 2,1 mm.
Fig. 2 Screenshot of VESS
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Fig. 3 The selected input unit SlimLine 70–40/R [Cassette Filter G4] [WC.6]
4 Conclusion The result of the considered problem is the selection of water coolers, but there are other variants of improving the air parameters. This makes it possible to choose the method that is more suitable for exact conditions and parameters of ice arenas.
References 1. Wolkoff P (2018) Indoor air humidity, air quality, and health - an overview. Int J Hyg Environ Health 221:376–390 2. Wolkoff P (2018) The mystery of dry indoor air - an overview. Environ Int 121:1058–1065 3. Derby MM, Hamehkasi M, Eckels S, Hwang GM, Jones B, Maghirang R, Shulan D (2017) Update of the scientific evidence for specifying lower limit relative humidity levels for comfort, health, and indoor environmental quality in occupied spaces. Sci Technol Built Environ 23(1):30–45 4. Meyer B (1983) Indoor air quality. Addison-Wesley, Reading 5. Bornehag CG, Blomquist G, Gyntelberg F et al (2001) Dampness in buildings and health. Nordic interdisciplinary review of the scientific evidence on associations between exposure to “dampness” in buildings and health effects. Indoor Air 11(2):72–86 6. Bornehag CG, Sundell J, Bonini S et al (2004) Dampness in buildings as a risk factor for health effects, EUROEXPO: a multidisciplinary review of the literature (1998–2000) on dampness and mite exposure in buildings and health effects. Indoor Air 14(4):243–257 7. Wyon DP, Fang L, Lagercrantz L, Fanger PO (2006) Experimental determination of the limiting criteria for human exposure to low winter humidity indoors. HVAC R Res 12(2):201–213 8. Arundel AV, Sterling EM, Biggin JH, Sterling TD (1986) Indirect health effects of relative humidity in indoor environments. Environ Health Perspect 65:351–356 9. Jomehzadeh F, Nejat P, Calautit JK, Yusof MBM, Zaki SA, Hughes BR et al (2017) A review on windcatcher for passive cooling and natural ventilation in buildings, Part 1: indoor air quality and thermal comfort assessment. Renew Sustain Energy Rev 70:736–756 10. Tanabe S, Kimura K (1989) Importance of air movement for thermal comfort under hot and humid conditions. In: Proc. second ASHRAE far east conf. air cond. hot clim, Kuala Lumpur, Malaysia, pp 95–103 11. Wigo H, Sandberg M (2001) Velocity variations in ventilated rooms as a method for creating comfort. In: 22nd annu AIVC conf
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12. Van Berkel S, Pressnail KD, Touchie MF (2014) Residential ventilation: a review of established systems and a preliminary laboratory investigation of an innovative fine wire heat recovery ventilator. In: Proc. 14th CCBST, Toronto, Canada, pp 381–390 13. Kaup C (2012) Impulslüftung für bessere Luftqualite at. Instatione are RLT-Anlage zur intermittierenden Raumlüftung (Pulsed ventilation for better air quality. Unsteady air-conditioning system for intermittent room ventilation). Tech. Am Bau. TAB. Organ Des Bundesindustrieverbandes Heizungs-, Klima-, Sanit artechnik, Tech. Geb audesysteme e.V. Fachzeitschrift Für Tech. Geb audeausrüstung 43:54–59. Jg. 20 14. Bas E (2004) Indoor air quality: a guide for facility managers 15. Abusharha A, Pearce E (2013) The effect of low humidity on the human tear film. Cornea 32(4):429–434
The Use of Various Compositions of Borate Mixtures in the Development of Hardening Boride Coatings Vladimir Malikov , Nickolay Tihonskii , Victoria Kozlova , and Alexey Ishkov
Abstract The first of these reactions is the main for the formation of coatings in mixtures with amorphous boron. For a complete description of the boriding process using HFC heating, the reactions between boron and Fe oxides given above should also be added to it. The second thermodynamically resolved reaction can be implemented in addition to the main processes of boron reduction from its carbide with calcium at lower temperatures, and silicon at higher temperatures, also described above. compositions 1 and 3 proceed directly on the surface of a steel specimen upon its contact with the putty (backfill) and heating, constitute the first stage and accelerate the process, and composition 2 proceeds deep in the already borated specimen and can go both by the combination and disproportionation mechanism, it has a lower speed and occurs in the second stage of the process. Keywords Transport infrastructure · Boriding process · Powder metallurgy · Boron carbide
1 Introduction The powder metallurgy (P/M) method offers many advantages for many types of materials in the manufacture of finished parts over other manufacturing methods. Production with powder metallurgy eliminates the need for many machining processes required for castings and forged products, thus achieving the production of structural parts with higher precision structural. For these reasons, it is both more cost-effective and more environmentally friendly production method for materials [1, 2]. Important advantages of P/M include high dimensional accuracy, high surface quality, repeatability, low cost and material savings due to the absence of secondary V. Malikov · N. Tihonskii · V. Kozlova Altai State University, Lenina, 61, Barnaul, Russia A. Ishkov (B) Altai State Agricultural University, Krasnoarmeisky, 98, Barnaul, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_161
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processes [3–5]. This method does not require melting to form complex components unlike conventional manufacturing methods, and high alloy components can be used due to the rapid solidification of powder production [6]. P/M is one of the easiest methods of producing metallic parts closest to the final shape. This method is widely used in the production of structural materials and many automobile parts [7]. The P/M production method allows the formation of a good combination of mechanical properties, corrosion and wear resistance by changing the microstructure properties [8]. However, the mechanical properties of the steels produced by this method may be lower than those of other steels with the same composition due to the porosity found after production [9]. Boriding is a thermo-chemical surface treatment that allows the production of a boride layer near the substrate surface without creating an additional layer on the surface [10–12]. Boriding can be applied to a wide range of steel alloys as well as materials such as cobalt-based alloys, nickel-based alloys, titanium and molybdenum to achieve the very high hardness and wear resistance on their surfaces [13, 14]. Borided steel components have excellent performance in many industries due to their superior tribological properties [15, 16]. Parameters such as boron potential of the medium, process temperature and duration, chemical composition of the substrate control the phase structure of the formed boron layer. Depending on these parameters, tetragonal Fe2 B (8 wt% B) and orthorombic FeB (16 wt% B) phases can be formed according to the amount of boron diffused into iron alloys [17–19]. Generally, singlephase Fe2 B layer is preferred over double phase FeB + Fe2 B layer for parts operating at high loads [20, 21]. In a study, Yazici and Çavdar [22] compared 30MnB5, 28MnCrB5 steels with borided steel which was produced by powder metallurgy and boriding process. They carried out the sintering process at 1120 °C and boriding process at 950 °C. After boriding, they obtained 1400 HV hardness in the sintered steel sample which contained 0.3% C and 2% Cu. As a result of their abrasive wear tests, sintered and borided steel yielded favorable results among other steels. In another study, Çavdar et al. [1] sintered samples containing iron-based powders at 1120 °C for 30 min. The samples containing different amounts of copper and graphite were borided after the sintering process. As a result of hardness tests, they obtained hardness values between 950 and 1550 HV depending on the varying graphite and copper ratio. Serafini et al. [8] investigated the mechanical and microstructural properties of sintered 316 L steel by the addition of different boron amounts. After the sintering process was carried out at 1240 °C for 30 min, microstructure, hardness and micro abrasion properties of the samples were tested. Thanks to the liquid phase formed during sintering, the parts produced were found to have lower porosity and a higher density. They also found that the hardness increased due to the phases such as M2B (M = Metal) and M23 (B1.5C4.5) and wear coefficient decreased. Franco et al. [23] applied boro-niobizing heat treatments on P/M AISI M2, and compared the properties and wear behavior of obtained coatings. They obtained coatings composed of iron borides, niobium borides and niobium carbides with higher hardness (3000 HV). The authors also investigated the wear behavior of coatings obtained on P/M AISI M2 steel and reported that the highest wear resistance was obtained in iron boride coatings. In addition to these studies, boriding of iron-based materials produced by powder metallurgy [24, 25] or adding
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boron directly to the composition has been tried in many other studies. However, in literature examinations, no studies have been found in which boriding process is applied simultaneously with powder metallurgy production method [23]. Sintering is an alternative production technique made by bringing the powder particles together under or above the melting temperature. Boriding is a crucial surface treatment to improve the mechanical and oxidation properties of steels. In this study, as a new approach, simultaneous application of sintering and boriding process is aimed. By applying the boriding process during sintering, it can be ensured that the substrate material is free from problems such as grain growth and loss of mechanical properties during subsequent boriding treatment. Besides, it is possible to save costs due to the absence of additional boriding treatment which is conducted at temperatures of 800 °C or above. In case of boriding by HFC heating, the rate of coating formation increases tenfold due to an accelerated heating rate, and there is no need to create a protective atmosphere when using special fluxes, as the time of boriding does not exceed several minutes. In addition, HFC heating makes it possible to reduce the time of exposure of the base metal to high temperatures, as well as easily combine the boriding process with subsequent heat treatment. In the future, a short boriding time in case of HFC heating application may suggest the use of this method of boriding at production lines for mass serial production with large numbers of parts to be hardened per shift.
2 Materials and Method The preliminary experiments carried out by us have shown the possibility in principle of the formation of boride coatings on the surface of steel parts using HFC heating. In pilot experiments, it was clarified and confirmed that the rate of the reaction, and hence the formation of a coating, increases by ten folds compared to isothermal thermochemical processing in a furnace with an increase in the heating rate. It was also found that the use of borate fluxes, for example, original P-0.66 flux is required in order to obtain high-quality extended coatings. For studying of the processes of boriding using the HFC heating of surfaces of the main structural and alloyed steel grades used in agricultural machine building, and investigation of the effect of carbon and alloying elements content in steel on the physical, physico-mechanical properties and wear resistance of boride coatings, sample coatings were obtained on St3, 45, 40 KhN, 50 G, 50 KhGA, 65 G steels from compositions of a boriding mixture based on boron carbide and amorphous boron under HFC heating. The composition of putties for steel part surfaces saturation is shown in Table 1, either boron carbide or amorphous boron was used as a boriding agent, and calcium fluoride (CaF2 ), ammonium chloride (NH4 Cl) or red prussiate of potash (K3 [Fe(CN)6 ]) served as the boriding process activators.
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Table 1 Compositions of boriding mixtures used for high-speed HFC-boriding Composition #
Component
Weight %
Component
Weight %
Component
Weight %
Component
Weight %
1
B4 C
92
P-0.66
8
−
−
−
−
2
B4 C
84
P-0.66
16
−
−
−
−
3
B4 C
80
P-0.66
20
−
−
−
−
4
B4 C
84
P-0.66
11
K3 [Fe(CN)6 ]
5
−
−
5
B
92,5
CaF2
5
P-0.66
2,5
−
−
6
B
90
CaF2
5
P-0.66
5
−
−
7
B
89
P-0.66
5
NH4 Cl
6
−
−
8
B
84
P-0.66
10
NH4 Cl
6
−
−
9
B
85
CaF2
5
P-0.66
5
K3 [Fe(CN)6 ]
5
10
B
79
P-0.66
10
NH4 Cl
6
K3 [Fe(CN)6 ]
5
3 Results and Discussion The first of these compositions is the main for the formation of coatings in mixtures with amorphous boron. For a complete description of the boriding process using HFC heating, the composition s between boron and Fe oxides given above should also be added to it. The second thermodynamically resolved composition can be implemented in addition to the main processes of boron reduction from its carbide with calcium at lower temperatures, and silicon at higher temperatures, also described above. When boriding occurs under isothermal conditions, in backfills with 800–950 °C, composition 2 is responsible for the two-phase anisotropic boride layer formation and process deceleration. However, it also provides chemical boron diffusion in the material to maximum depths. Other processes may also occur. Exemplarily, active carbon released during composition 5 can partially carburize steel, form refractory dispersed carbides with active alloying elements, or react with oxygen when the process is carried out in air, and boron carbide, which is disproportionate even when heated to 850–900 °C, when boriding in furnaces with putties, gives B2 O3 and carbon monoxide (IV). Cementite formed by composition 6 can also be found in coatings obtained using HFC heating of steels due to the interaction of iron with active carbon. The structure and major characteristics of boride layers obtained by boriding using HFC heating of the tested steels with various compositions are shown in Figs. 1, 2, 3, 4, 5 and 6 and Table 2. To investigate the effect of composition of boriding mixture on the characteristics of resulting hardened layers, the temperature of boriding using HFC heating was about 1050 °C, the maximum temperature did not exceed 1070 °C, and the minimum was not below 950 °C. The increase of temperature of boriding process using HFCheating above 1070 °C can result in low-melting boride eutectics formation, which was confirmed by partial fusion of the specimen surface, the heating time was 76 s.
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Fig. 1 Boride coating microstructure when using composition # 1: a – with boriding agent particle size of 75 µm, b –particle size of 150 µm, c –particle size of 315 µm
Fig. 2 Boride coating microstructure when using composition # 2: a – with boriding agent particle size of 75 µm, b –particle size of 150 µm, c –particle size of 315 µm
Fig. 3 Boride coating microstructure when using composition #2 with particle size of 315 µm
Fig. 4 Boride coating microstructure when using: a – composition #5, b – composition #6 µm
Fig. 5 Boride coating microstructure when using: a – composition #7, b – composition #8
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Fig. 6 Boride coating microstructure when using: a – composition #4, b – composition #9, c – composition #10
Table 2 Major characteristics of boride coatings obtained on 65 G steel using high-speed HFC heating Composition
Boriding agent main faction particle diameter, µm
Coating thickness, µm
Microhardness HV100, MPa
Coating/base interface state
1
75
340
15,332
Diffuse
1
150
320
13,315
Expressed
1
315
290
12,057
Expressed
2
75
360
7817
Absent
2
150
600
9194
Absent
2
315
350
13,778
Presence of interlayer
3
315
195
10,970
Presence of interlayer
5
−
675
26,275
Expressed
6
−
80
11,678
Expressed
7
−
110
8464
Diffuse
8
−
800
20,117
Diffuse
4
75
20
4826
Absent
4
150
30
4204
Discontinuity
4
315
400
10,325
Discontinuity
As can be seen from Fig. 1.a, when using a composition consisting of boron carbide with fraction size of not exceeding 75 µm at a ratio of 92% by weight and P-0.66 flux at a ratio of 8% by weight, the formation of a boride coating with a finegrained ledeburite-like iron-boride eutectic structure is observed. At that, uniformly distributed closed carbide regions are observed in the eutectic matrix, by their composition and appearance similar to the structures obtained by the authors when surfacing with boriding mixtures. The increase in the boriding agent particle size up to 150 µm (Fig. 1.b) results in a reduction in area occupied by carbide regions and widening of iron-boride eutectic, the transition zone in such a coating is absent. Any further increase in the
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size of boriding agent particles results in a decrease of the carbide regions to an even greater extent, which is perfectly visible in the presented photo of the microstructure (Fig. 1.c), no expressed transition zone is observed, as in case of conventional diffusion boriding. An increase in the size of boriding agent particles in composition 1 results in a decrease of boride coating thickness and microhardness of the hardening phase in the form of an iron-boride eutectic, but at the same time, the total area occupied by carbide-containing regions in the microstructure of the resulting hardened layer decreases. An increase in fused P-0.66 flux content up to 16% with a boriding agent fraction of 75 µm makes it possible to obtain a boride coating with an average thickness of 360 µm and structure representing an iron-boride eutectic with inclusions of carbide-containing regions (Fig. 2.a). An increase of the particle size of boriding up to 150 µm allows to obtain a boride coating the average thickness reaching 600 µm (Fig. 2.b), accompanied with a decrease in the area of carbide inclusions as compared with the use of a composition with a finer fraction of boriding agent. An increase in the particle size of boriding agent up to 315 µm makes it possible to obtain a boride coating with an average thickness of 350 µm, with simultaneous decrease in the volume of carbide-containing regions (Fig. 2.c). A further increase in the content of P-0.66 flux up to 20% (composition # 3, Table 1) with a boriding agent particle size of 315 µm results in a decrease in the average thickness of the boride coating to 195 µm with a microhardness of the HV100 hardening phase of 10,970.4 MPa. The microstructure of the resulting boride coating represents the same ledeburite-like iron-boride eutectic with closed carbide regions (Fig. 3). This allows to make a conclusion that it is not advisable to further increase the content of fused flux in the boron carbide-based boriding mixture. When using boriding mixture #5 (Table 1) in which calcium fluoride with the addition of a small amount of fused flux P-0.66 is used as activator, a boride coating consisting of two zones with different structures is formed during 76 s of the boriding process. The first zone consists of manganese boride crystals with a microhardness HV100 of 26,275.5 MPa located in a softer matrix of ledeburite-like iron-boride eutectic with HV100 of about 10,000 MPa (Fig. 4.a), under which there is the second zone consisting of iron-boride eutectic similar to the above described ones. The average thickness of such layer is 675 µm. Similar structures were obtained by the authors [13] when depositing a layer from a mixture consisting of 50% of MnB + 50% of Fe. An increase of the content of P-0.66 fused flux up to 5% by weight due to a reduction of the amount of boriding agent (composition # 6, Table 1.) results in boride coating with a structure represented by a ledeburite-like iron-boride eutectic with closed carbide regions (Fig. 4.b). The average thickness of such a coating is 80 µm when the main hardening phase microhardness HV100 of 11,678 MPa. Introduction of ammonium chloride in an amount of 6% by weight to the boriding mixture as an activator (composition # 7, Table 1) allows to obtain a boride coating consisting of a ledeburite-like iron-boride eutectic with closed carbide regions (Fig. 5.a). The thickness of this coating formed during the time of the boriding
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process using HFC heating is 110 µm, and the microhardness HV100 of the main hardening phase is 8464 MPa. When increasing the content of P-0.66 fused flux in the boriding mixture up to 10% (composition #8, Table 1), a boride coating is formed with a thickness of 800 µm (Fig. 5.b) and structure consisting of an iron-boride eutectic with closed carbide regions, the microhardness HV100 of the eutectic is 20117 MPa. However, unlike other coatings in the form of an iron-boride eutectic with closed carbide regions, the grain size of these eutectics is much larger, and the microhardness of this coating is also much higher, which indicates the formation of a structure of a different type. Addition of potassium ferrocyanide to the composition of the boriding mixture when boriding with the use of HFC heating and boron carbide as a boriding agent (composition # 4, Table 1) with particle size of at least 75 µm makes it possible to obtain a boride coating in the form of “islands” whose thickness is not exceeds 50 µm. A similar phenomenon is observed when using a boriding agent with particle size 105 µm, however the thickness of the boride coating does not exceed 30 µm in this case. Only the use of boron carbide with particle size of 315 µm made it possible to obtain boride coatings over the entire surface of the specimen. Thus, during the boriding process of 76 s (Fig. 6.a) the average thickness of the boride coating made 400 µm, its structure consisted of an iron-boride eutectic with closed carbide regions. A similar behavior of the resulting boride coating is observed when adding potassium ferrocyanide also into the composition of the boriding mixture based on amorphous boron. Thus, when this component is added to the composition in which calcium fluoride is used as an activator (composition # 9, Table 1), the boride structure consists of manganese and iron carboboride crystals having microhardness HV100 of 23,941 MPa and located in a matrix of softer ledeburite-like iron-boride eutectic with microhardness of HV100 of about 10,020 MPa (Fig. 6.b). The average thickness of this coating is 405 µm. The addition of potassium ferrocyanide in the composition of amorphous boronbased boriding mixture with ammonium chlorides as an activator results in the formation of boride coatings with an average thickness of 390 µm and a microhardness HV100 pf 11,678 MPa. The microstructure of such coating is presented on the photo in Fig. 6.c.
4 Conclusions In the course of the study conducted, the influence of various compositions of boriding mixtures on the properties and structure of hardening boride coatings has been considered. During the study, 10 compositions of mixtures have been analyzed, where boron carbide or amorphous boron has been used as a boriding agent, and amorphous calcium fluoride (CaF2 ), ammonium chloride (NH4 Cl) or potassium ferricyanide salt (K3 [Fe(CN)6 ]) has been used as an activator. The expediency of fused flux content increase in the boron carbide-based boriding mixtrure composition approximately up to 16% (corresponding to composition #2,
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Table 1). With further increase of fused flux content, a decrease of the microhardness of the obtained coating is observed (compositions # 3 and # 4, Table 1). The investigation of coatings obtained using a composition in which calcium fluoride is used as an activator showed the formation of coatings with two zones of different structures and, as a consequence, different microhardnesses. At the same time, an increase in the content of fused flux up to 5–10% makes it possible to obtain a more uniform structure of the coating with a higher overall microhardness. The possibility of using calcium fluoride as an activator has been also analyzed: in the course of the experiments, it was established that crystals of manganese and iron carboborides with high microhardness located in a soft matrix of a ledeburite-like iron-boride eutectic have been formed. Acknowledgements The experimental study of boriding mixtures was carried out at the expense of a grant from the President of the Russian Federation for state support of young Russian scientists No. MK-3213.2022.4. The investigation of coatings obtained using a composition was carried out with the financial support of the Program for the Support of Scientific and Pedagogical Workers of the FSBE HE “Altai State University”, project «Creation and research of promising heat-resistant com-posite materials».
References 1. Çavdar U, Ünlü BS, Pinar AM, Atik E (2015) Mechanical properties of heat treated iron based compacts. Mater Des 65:312–317 2. Yener T, Yener SC, Zeytin S (2018) Nb addition effect on microstructural properties of Ti–TiAl3 in situ composites produced by resistive sintering. J Therm Anal Calorim 134:1359–1365 3. Ali M, Ahmad F, Sri P, Yahya N, Aslam M (2019) ScienceDirect investigation of boron effect on the densification of Fe-50% Ni soft magnetic alloys produced by powder metallurgy route. Mater Today Proc 16:2210–2218 4. Kulkarni H, Dabhade VV (2019) Green machining of powder-metallurgy-steels (PMS): an overview. J Manuf Process 44:1–18 5. Erdogan A, Yener T, Zeytin S (2018) Fast production of high entropy alloys (CoCrFeNiAlxTiy) by electric current activated sintering system. Vacuum 155:64–72 6. Azevedo JMC, CabreraSerrenho A, Allwood JM (2018) Energy and material efficiency of steel powder metallurgy. Powder Technol 328:329–336 7. Neystani R, Beidokhti B, Amelzadeh M (2019) Fabrication of dissimilar Fe-Cu-C powder metallurgy compact/steel joint using the optimized resistance spot welding. J Manuf Process 43:200–206 8. Serafini FL, Peruzzo M, Krindges I, Ordoñez MFC, Rodrigues D, Souza RM, Farias MCM (2019) Microstructure and mechanical behavior of 316L liquid phase sintered stainless steel with boron addition. Mater Charact 152:253–264 9. Wu MW, Cai WZ, Lin ZJ, Chang SH (2017) Liquid phase sintering mechanism and densification behavior of boron-alloyed Fe-Ni-Mo-C-B powder metallurgy steel. Mater Des 133:536–548 10. Balusamy T, Sankara Narayanan TSN, Ravichandran K, Song Park I, Lee MH (2013) Pack boronizing of AISI H11 tool steel: role of surface mechanical attrition treatment. Vacuum 97:36–43 11. Genel K (2006) Boriding kinetics of H13 steel. Vacuum 80:451–457 12. López-Perrusquia N, Martínez-Trinidad J, Escobar-Galindo R, OrtizDomínguez M, MenesesAmador A, Campos-Silva I (2009) Characterization of AISI 4140 borided steels. Appl Surf Sci 256:2372–2379
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Nanotechnologies in the Field of Concrete Production Anatoly Lastovka , Tamara Danchenko , Inna Petukhova , and Ilya Polyakov
Abstract This paper discusses the features of concrete production using nanotechnology. The authors propose a production method using matter with a given atomic structure and consciously manipulating atoms and molecules, which are included in small doses of a substance and consist of many (trillion) atoms. Shifting to work using atoms and microparticles will lead to precision and efficiency. The structural unit of nanotechnology is a nanoparticle. In this study, special attention is paid to it. Nanoparticles can change the color of artificial coatings, increase the wear resistance of materials, and improve the resistance of materials. Innovative technologies use reinforced steel, composite reinforcement, nano-coatings. This is one of the main conditions for creating products of improved quality. The authors provide detailed information on structural composites with a tile, iron, or polymer matrix. The paper analyzes all the advantages of nanoconcrete, including the development of highstrength concretes by scientists. Nanoconcrete unites a whole group of materials, where a general classification of innovative concretes is formed. In accordance with the needs of the object, this will allow setting the desired characteristics for products and structures. The proposed material can be used in the development of innovative technologies. Keywords Transport infrastructure · Concrete · Reinforced concrete · Composite · Molecules · Nanoparticle
1 Introduction The modern world is the world of developing nanotechnologies that are actively used in various branches of science and technology, including the production of concrete with certain characteristics. The meaning of the word “nanotechnology” is more often used as “all-encompassing” and should be understood as a set of techniques for the manufacture of materials with a certain atomic structure by controlling molecules A. Lastovka · T. Danchenko (B) · I. Petukhova · I. Polyakov Siberian Federal University, 79 Svobodny Avenue, 660041 Krasnoyarsk, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_162
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Fig. 1 Modern molding shop for the production of reinforced concrete products (photo by the author)
and atoms. Nanotechnology makes it possible to obtain particles of matter and create devices with a size of 1–100 nm on their basis. The production of concrete and reinforced concrete products, despite the use of the most modern concrete equipment, is a complex and lengthy process (Fig. 1). Excess energy and metal consumption of this process significantly affects the economic performance of production. In addition, the automation and mechanization of technological lines play their role. This greatly affects the quality of the manufactured product due to the so-called human factor. Concrete dominates in the construction industry for the simple reason that there are often no other alternatives to it. Therefore, any innovative ideas regarding this material do not go unnoticed by scientists and builders. Basically, innovative activity in relation to concrete concerns the development of its new types, reinforcement for it, additives. In addition, specialists are also working on the creation of new structures and technologies that will maximize the protection or restoration of concrete [1–3]. How are the construction complexes of the Krasnoyarsk Krai developing? What are the positive factors and what disadvantages are the enterprises of the construction industry facing? Positive factors include: – the list of production of the nomenclature of building materials has the prospect of development, since it uses its mineral resource base; – provision of the region with relatively low cost energy resources; – Siberian Federal University is a scientific center for the training of qualified personnel; – it is noted that the active “buyers’ market” is solvent and creates competition in the market of construction companies. This improves the quality of buildings and landscaping of the property in order to create attractiveness in the listing. The city is being built, and the residents of Krasnoyarsk have modern sports facilities, new roads, hospitals, shopping areas, and residential buildings. But along with this, there is another side, which also needs to be discussed. This is an increase in competitive pressure on the regions from large
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companies at the federal level. This is the deterioration of the production capacities of organizations and the use of production technologies that do not meet modern requirements for energy and economic efficiency. A large percentage of the total number of construction companies that belong to micro-enterprises cannot divert working capital for innovation. The disadvantages include price factors and the high level of housing prices in comparison with the level of wages of the population.
2 Nanotechnology in Construction Nanotechnology is a way of producing and using materials with a given atomic structure at the level of single atoms, i.e. consciously manipulating atoms and molecules. Modern production methods work with doses of a substance that is made up of trillions of atoms. This means that devices that seem to be super-accurate, give parameters with large errors in values at the atomic level. Shifting to work at the molecular level with microparticles is a breakthrough in science that will lead to incredible precision and efficiency. How does a molecule - nanoparticle behave? What makes it possible to change and create in the process? The discovery was that the color of artificial coatings changes, the ability to self-clean, to create special antibacterial coatings appeared. A chain of positives leads to the fact that UV protection increases the wear resistance of the materials. In addition, they help prevent the appearance of yellowness, which is very important for doors and windows made of metal-plastic. Due to their resistance properties, nanoparticles help to strengthen the resistance indicators of materials on the plane of plastic pipes. In this regard, we can say that nanomaterials with unique magnetic, thermal and optical characteristics can make a breakthrough in the production of building materials. Thanks to the results of many years of research on innovative technologies, manufacturers are using improved advances in production. Reinforced steel, concrete, composite reinforcement, various nano-coatings, these materials are being re-studied as materials with new unexplored characteristics and properties. Structural composites, which have a wide range of applications, deserve special attention. These are additives for a variety of structures with a tile, iron or polymer matrix. Composites that include carbon fiber and a polymer matrix are carbon fiber reinforced plastics. Materials consisting of many components and a plastic base - matrix, according to the studied characteristics, have increased strength and rigidity. Structural composites are classified into many types, but they are all based on a metal, ceramic, or polymer matrix. For example, carbon fiber reinforced plastic made from a polymer matrix and carbon fibers is used in the manufacture of space technology, aircraft construction, medical equipment, prostheses, as well as various sports equipment. The structural unit of nanotechnology is a nanoparticle. It can be represented in the form of a cluster. Its diameter is 1–100 nm. It contains from several tens to several thousand atoms (Fig. 2).
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Fig. 2 Particle size and specific surface area of concrete components [4, 5] (fig. by the author)
Existing metal alloys with a high viscosity index, which are used in the construction of hydraulic engineering and road facilities, have been studied using nanocoatings. The results of the studied strong steel changed their characteristics, markedly increased the resistance of the metal to protect against corrosion, has water - and dirt-repellent, heat-insulating properties. The study and discovery of important qualities of nano-coatings continues, including energy saving. Nano-coatings tend to accumulate solar energy and may become full-fledged batteries in the future. Using transparent nanogels, sound and heat insulation is made, therefore they are used in energy-saving and roofing systems. On the contrary, innovative films protect the room from overheating. They reflect 80% of infrared radiation thanks to their unusual component - diamond paints. Pipes made of nanocomposite materials are used in gas supply, water supply and heating systems. They are tens of times superior in technical and operational characteristics to similar pipes, but have a low cost. Nanotechnology is used in the production of fiberglass reinforcement. This product has a number of positive characteristics, since its weight is four times lighter than its metal counterpart, has a high degree of strength, and is not inferior in chemical properties. In addition, it is a dielectric, provides low thermal conductivity and does not lend itself to corrosion, which allows it to be used in all areas of construction. The implementation of complex innovative engineering solutions requires the use of nanomaterials. The prospects for the development of the future of the construction industry depend on them. At the same time, the foundations of buildings will be able to regulate and compensate for soil shrinkage themselves; supporting structures will independently control the state of stress deformation; fences and roofs will function as a solar energy accumulator; nano-coatings will be able to determine the physical and mental state of a person [6–8].
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3 Concrete Nanotechnology Concrete that will last 500 years - this is the lifespan that the developers of highstrength concrete expect. This is the highest quality concrete for today. Such characteristics were achieved thanks to ultrafine and nanosized particles, which are used for its manufacture. The largest manufacturers of Japan, Germany, Switzerland and Norway are working on this topical development [9, 10]. Structure formation and destruction mechanisms operate at every level. It is both nano-, micro- and macroscale. Nanochemistry allows designing in the direction from the smallest to the largest, allows creating a variety of new products that can be successfully used in concrete technologies. In particular, new additives for concrete are currently being actively developed. These are mainly polycarboxylate superplasticizers [7, 11, 12]. Higher indicators (in particular, a more durable cement stone up to 115 MPa with a control strength of 72–89 MPa) are achieved due to the fact that organomineral nanolayers (nanomesh) are formed on cement particles. In this case, the surface is amorphized [13–15]. Due to the fact that nanoparticles are used in common building materials, these materials acquire specific characteristics that are very important in the construction of special, large-span and high-rise structures [16, 17]. For example, SiO2 nanoparticles (nano-silica, Figs. 2 and 3) can be added to high-quality and self-compacting concrete, which will optimize its wear resistance and ease of placement [18, 19]. The smallest particles (micro- and subsequently nano-silica) used in the manufacture of concrete made it possible to achieve a major breakthrough in this area in literally 20–30 years. It should be noted that nano-fibers (for example, nano - Al2O3, see Fig. 3, right) are another promising element that is used in concrete production technology [20, 21]. The increase in performance was caused by the selection of the cement component and special additives. The latter were conventionally called construction fiber. They
Fig. 3 Particles of nano-silica (left) [1, 4] and nano-fibers Al2O3 provided by ANF Development (right). Photos are taken using transmission electron microscopy
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differ in the manufacturing method, composition, and technical qualities. A breakthrough in nanotechnology was made by fullerenes and similar materials. These are huge framework molecules made of carbon atoms (nanotubes). The classification includes the following types: A carbon nanotube has the form of a framework with molecules of different types. Steel (the most durable). Polymer (corrosion resistant and cheap). Basalt and alkali-resistant fibers. UHMPF—ultra-high modulus polyaramide fibers. Highly modulus carbon fibers. The use of new plasticizers has led to the minimization of water consumption in the mortar. This significantly lightened the material and increased the mobility of the composition, which eliminated the likelihood of cracking. Aerated concretes belong to different brands and classes. Various formulation variations open up unlimited application possibilities and continue to be studied. In a laboratory environment, nano-additives trigger a cascade of reactions that ultimately provide high strength without the need for reinforcement. This stage of the technological process has received its definition. Dispersed self-reinforcement is the acquisition of super strength due to the growth of crystals of a mineral substance, provoked by nano-additives. The development of technologies goes in several directions, including the strengthening of reinforced concrete with transformed reinforcement. Technologies are developing in several areas, which include: a) the addition of special ingredients; b) application of protective coatings with special properties on finished bases; c) strengthening of reinforced concrete with transformed reinforcement. The super-strong properties of the material make it possible to use it in the construction of high-rise buildings or airfield platforms. The innovative composition is classified by density into the following varieties: light; middle; strong; high strength. Depending on the goals and objectives for the erected structure, the appropriate nanomaterial is taken. For private buildings and interior floors, lightweight options are used. Roadways, airfield strips, oil and gas platforms, and access roads require a more solid form. Powerful reinforced concrete structures, bridges, skyscrapers require ultra-strong nano-concrete. It is successfully applied in construction in areas of high fire hazard and in seismically unstable zones. The table shows the main qualities of the improved stone and its advantages (Table 1).
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Table 1 The main qualities of the improved stone and its advantages Properties
Comments
Advantages
Strength
1.5 times higher than plain concrete
Durability
Destroys only intense and prolonged ultrasound Resistant to temperature changes
Impact interval - from −180 to Use in extreme conditions +800 ◦ C
Bactericidal
Gives off atomic oxygen
Supports a special microclimate
Strong adhesion of concrete and metal
Penetrates the area of corrosion, restoring strength
Restoration work
Light weight
Provided by a reduced volume Lightening the entire structure, of water in solution reducing the cost of construction due to a less powerful foundation
Uniform structure
Does not crack, delaminate, break
The ability to use the casting method
Water tightness
Does not require waterproofing
Does not allow moisture to enter the premises
Fire resistance
+800 ◦ C
Fire safety
Chemical resistance to acids and alkalis
As a result of the interconnection of nanoparticles
Use in aggressive environments
Low abrasion
High impact resistance due to homogeneity and density of the mass
Good for road and floor surfaces
4 Discussion With the advent of nanoparticles, many industries began to develop at an accelerated pace. New materials surpass analogues and broaden horizons. The word “nanotechnology” has become firmly established in many industries. This definition denotes the smallest particles with unique properties. The sphere of building materials has become the object of introducing useful small additives. The development of methods for characterizing the nanoscale structure of materials based on cement and computer materials science have enabled scientists to study the structure of concrete and set the necessary improved technical characteristics. One of the results of the development of scientists was nano-concrete: it is produced using a special technology and has a unique composition. The material is based on either special nano-additives that replace traditional plasticizers, or special grinding of components is used. During construction, the reliability of the future object and its durability depend on the correctly selected classes and grades of concrete. If the solution is selected or made with violations, neither reinforcement nor high-quality masonry materials will save. Nanoconcrete is not a specific brand, but a whole line of solutions with
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Fig. 4 Concrete goods in Krasnoyarsk
unique technical parameters and physical properties. Thanks to their use, not only the quality of construction increases, but also its capabilities expand. By combining nano-additives in various ratios, it is possible to obtain concrete with specified characteristics of strength and endurance. This makes it possible to customize the solution for specific tasks as efficiently as possible. The term “nanoconcrete” unites a whole group of materials that differ from analogues in composition and manufacturing process (Fig. 4), and, therefore, in properties. It is even possible to refuse reinforcement - the solution will keep its shape even without a binder. A general classification of innovative concretes has already been formed. They differ in density: light, medium, dense and super dense. Light are optimal for use inside buildings in private and low-rise construction. They used for partitions and walls. Classification of medium-sized concrete–they are suitable for the construction of pavements with increased wear on bridges, roads, runways. Dense and super dense concrete–they are used in high-rise construction, in the construction of load-bearing structures, elevator shafts, etc. That is, where the maximum endurance and reliability of the composition is required. The emergence of a galaxy of nanoconcrete freed the hands of architects and designers: now they do not have to be limited by the possibilities of mortar. On the contrary, it can be made according to the needs of the object by setting the desired properties. So soon we will witness original designs in buildings and structures.
5 Conclusions However, today the application of the considered technologies in the field of construction is rather limited, since advanced ideas are mainly aimed at achieving a surface effect, but not creating new structures of building materials. Nowadays, technological processes by which products and structures are manufactured meet all the requirements of the Russian State Standards SP, GOST. Nevertheless, the advances
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in global research in the field of nanotechnology are already being applied in construction. These are many production processes that are not complete without structural composite materials with unique strength indicators. Also, in the production process, innovative varieties of reinforcing steels are used. In addition to construction, the scope of application is rapidly expanding, as is the development of new forms of air binding matter. Composite coatings based on nanoconcrete are used for sewage facilities, where the action of an aggressive environment is obvious. As a result, the concrete does not collapse, and the metal does not rust. The multilayer composite is suitable for floors and walls of public buildings-shopping and administrative centers, parking lots, and schools.
References 1. Sanchez F, Sobolev K (2010) Nanotechnology in concrete–a review. Constr Build Mater 24(11):2060–2071 2. Sobolev K, Flores I, Hermosillo R, Torres-Martínez LM (2008) Application of nanomaterials in high-performance cement composites. In: Proceedings of the ACI Session on Nanotechnology of Concrete: Recent Developments and Future Perspectives, 2006. Denver, USA, ACI SP-254, pp 93–120 3. Thomas JJ, Jennings HM, Chen JJ (2009) Influence of nucleation seeding on the hydration mechanisms of tricalcium silicate and cement. J Phys Chem C 113:4327–4334 4. Qing Y, Zenan Z, Deyu K, Rongshen C (2007) Influence of nano-SiO2 addition on properties of hardened cement paste as compared with silica fume. Construct Build Mater 21(3):539–545 5. Flores I, Sobolev K, Torres LM, Valdez PL, et al (2010) Performance of cement systems with nano-SiO2 particles produced using sol-gel method. In: TRB First International Conference in North America on Nanotechnology in Cement and Concrete. Irvine, California, USA. 6. Makar JM, Margeson J, Luh J (2005) Carbon nanotube/cement composites–early results and potential applications. In: Proceedings of the 3rd International Conference on Construction Materials: Performance, Innovations and Structural Implications. Vancouver, B.C., pp 1–10 7. Sanchez F, Zhang L, Ince C (2009) Multi-scale performance and durability of carbon nanofiber/cement composites. Nanotechnology in construction. In: Bittnar Z, Bartos PJM, Nˇemeˇcek J, Šmilauer V, Zeman J (eds) Nanotechnology in Construction 3, pp 345–350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00980-8_46 8. Shah SP, Konsta-Gdoutos MS, Metaxa ZS, Mondal P (2009) Nanoscale modification of cementitious materials. Nanotechnology in construction. In: Bittnar Z, Bartos PJM, Nˇemeˇcek J, Šmilauer V, Zeman J (eds) Nanotechnology in Construction 3, pp 125–130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00980-8_16 9. Han B, Yu X, Kwon E (2009) A self-sensing carbon nanotube/cement composite for traffic monitoring. Nanotechnology 20:1–5 10. Cassar L, Pepe C, Tognon G, Guerrini GL, et al (2003) White cement for architectural concrete possessing photocatalytic properties. In: Proceedings of the 11th International Congress on the Chemistry of Cement (ICCC). Dur-ban, South Africa 11. Makar JM, Margeson J, Luh J (2005) Carbon nanotubes/cement composites-early results and potential applications. In: Proceedings of the 3rd International Conference on Construction Materials: Performance, Innovation and Structural Implications. Vancouver, BC, p. 1–10. 12. Shah SP, Konsta-Gdoutos MS, Metaxa ZS, Mondal P (2009) Nanoscale modification of cementing materials. In: Bittnar Z, Bartos PJM, Nˇemeˇcek J, Šmilauer V, Zeman J (eds) Nanotechnology in Construction 3, pp 125–130. Springer, Berlin, Heidelberg. https://doi.org/ 10.1007/978-3-642-00980-8_16
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13. Feynman R (1960) There’s plenty of room at the bottom (reprinted from a speech given at the annual meeting of the American physical society) [There’s plenty of room in that world]. Eng Sci 23:22–36 14. National Nanotechnology Initiative–Strategic Plan, December 2007. The Office of the President of the United States 15. Drexler E, Peterson C, Pergamite G (1991) The Unbounding Future: The Nanotechnology Revolution. William Morrow, New York 16. Bartos, P.J.M. (2009). Nanotechnology in construction: a roadmap for development. In: Bittnar Z, Bartos PJM, Nˇemeˇcek J, Šmilauer V, Zeman J (eds) Nanotechnology in Construction 3, pp 15–26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00980-8_2 17. Scrivener CL, Kirkpatrick RJ (2008) Innovation in the use and research of cementitious material. Cem Concr Res 38(2):128–136 18. Scrivener, K.L. (2009). Nanotechnology and cementitious materials. In: Bittnar Z, Bartos PJM, Nˇemeˇcek J, Šmilauer V, Zeman J (eds) Nanotechnology in Construction 3, pp 37–42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00980-8_4 19. Sobolev K, Ferrada-Gutrnrrez M (2005) How nanotechnology can change the concrete world: part 2. Am Ceram Soc Bull 84(11):16–19 20. Sobolev K, Shah SP (2008) SP-254 Concrete Nanotechnology: Recent Developments and Future Perspectives. American Concrete Institute, Detroit 21. de Miguel J, Porro A, Bartos PJM (2006) Nanotechnology in construction, p 416. RILEM Publications SARL
Assessment of Porosity and Fracturing of Rocks Using Digital Photographs of Core Thin Sections Galina Prozorova
and Elena Slinkina
Abstract Modern methods of lithological research allow obtaining results in digital form. This increases the objectivity, accuracy, reliability of data on rocks and makes possible their further computer processing and modeling. The article studies the issue of analyzing the composition and properties of rocks using digital photographs of the core sample. Existing techniques shall be considered. A scheme for the automated assessment of porosity and fracture parameters based on photographs of petrographic thin sections shall be proposed: 1) semi-automatic selection of voids by color; 2) automatic selection of cracks based on geometric features; 3) estimation of parameters of absolute porosity, total length and average width of cracks. To highlight voids, color filtering was applied with interactive input of the values of the classification attributes. Allocation of cracks from the general mass of voids was carried out according to the characteristics of the shape and area. The value of the absolute porosity was estimated as the ratio of the area of the selected voids to the total area of the photography. To determine the average width and total length of the cracks, the inscribed rectangle approximation was used. The scheme is implemented using algorithms of the OpenCV library, integrated into a custom software application. Convergence of the results of using the application with the results of a non-automated expert assessment for the parameter of porosity 80%, fracturing 70%. Estimation errors refer to cases of low color contrast of voids and mineral skeleton and segmentation of fracture lines in the original photographs. When using the application, a significant increase in speed and a decrease in the labor intensity of a specialist’s work was obtained. This allows us to recommend the developed application for express analysis of photographs of core thin sections. Keywords Transport infrastructure · Analysis of the images · Lithology · Core sample photography · Computer vision · OpenCV · Porosity · Fracturing
G. Prozorova (B) · E. Slinkina Industrial University of Tyumen, Volodarsky Street, 38, 625003 Tyumen, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_163
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1 Introduction Assessment of the composition and properties of rocks by visual analysis of core samples is a very labor intensive process in the work of a petrophysics, largely dependent on his subjective professional qualities. To improve performance, objectivity and accuracy of the assessment, real samples shall be replaced with computer graphic models obtained by digital tomography and photography. The article devoted to computer analysis of core samples photos. The task of automating the quantitative assessment of the parameters of porosity and fracturing of rocks from photographs of petrographic thin sections was solved. The available works and the possibility of reproducing their results were analyzed. A scheme for the assessment of porosity and fracture parameters based was proposed: 1) semi-automatic selection of voids by color; 2) automatic selection of cracks from the general array of voids on geometric features; 3) estimation of parameters of absolute porosity, total length and average width of cracks. The scheme implemented using a number of algorithms from the OpenCV library and tested on real data. The traditional way of studying the lithological composition and properties of rocks is visual analysis of core—samples obtained while drilling wells. Nonautomated core analysis performed according to classical methods is subjective; its accuracy and productivity currently do not meet the requirements of geological and mining companies. The methods of modern optical microscopy make it possible to obtain digital photographs of rock samples suitable for further computer analysis. The complexity of computer analysis of core photographs is due to the high heterogeneity and variability of the color characteristics of lithotypes and rock properties. There is no single color classifier, the classification signs are set by experts. There are semi-automatic and automatic classification methods. In semi-automatic classification, the expert interactively indicates color signs on the fragments of the photography. Then the color segmentation of the entire image shall be programmatically implemented using filtering or supervised learning methods. Semi-automatic classification shall be used to analyze individual photographs. Automatic classification shall be performed for large sets of photographs, in which training and test sets shall be separated and then machine learning methods shall be applied. A limitation of automatic classification is the requirement for uniformity of color features in both samples. It shall be reliably carried out only within one geological object (well, rock formation). To study the composition and properties of rocks, photographs of samples of different sizes shall be used (whole core, petrographic thin sections) obtained under daylight and ultraviolet light (Fig. 1). To increase the number of classification features, different color models (RGB, HSL, shades of gray), image augmentation methods, additional data (texture, structure of samples) shall be used.
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Fig. 1 Examples of fragments of photographs of core samples: a whole core in daylight; b whole core in ultraviolet light; c petrographic thin section in daylight [1]
2 Overview of Available Solutions A significant number of works devoted to the recognition of rock lithotypes from core samples photographs. In one of the first works, Prince and Chitale (2008) implemented semi-automatic recognition of two lithotypes (sand and shale) in the HSL color model (hue, saturation, lightness) [2]. Thomas et al. (2011) to identify lithotypes, the method of automatic classification with training was used. The training and test sets included photographs of the core sample from one well. In the training set in the RGB color model (red, green, blue), four lithotypes were identified (sand, shale, carbonate and core absence) The knearest neighbors method used for the classification. The technique works with high productivity and accuracy, but for each investigated well it shall be required to create its own training set [3]. Akinshin A.V. (2013) developed a method for determining the volume fraction of textural components of a thin-layered rock from photographs of a whole core. On the basis of color differences, the author carried out a statistical separation of textural components and determination of the areal fraction of clay interlayers in the samples [4]. I.I. Khasanov et al. (2013, 2015, 2016) developed a technique for recognizing lithotypes and petrophysical properties of rocks (oil saturation, porosity, permeability) [5, 6]. The authors use photographs taken in daylight and ultraviolet light and analyze them in RGB and HSV color models, thus obtaining six classification features. To analyze the photographs of thin sections, a semi-automatic classification was applied using the In Range Python color filter. The classification process includes the sequential recognition of individual classes of lithotypes and properties, their quantitative analysis, and further integration of all classes into a single image [5]. To classify photographs of a whole core, the same six color features were used, their boundary values were set interactively in the photograph. Further, for the analysis of all samples taken from one well, an automatic classification was implemented using a multilayer perceptron [7]. W.E. Ellington (2013) applied a similar approach: interactively determined the dependence of color and lithotype for a training set of whole core samples. Further, these dependencies were applied for automatic recognition of lithotypes throughout the well [8].
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Chatterjee et al. (2017) used texture and structure characteristics along with color to identify lithotypes from photographs of a whole core sample. The classification carried out according to eighteen criteria using the support vector machine rate (SVR) [8]. In the works of E.E. Baraboshkina et al. (2016, 2018, 2019), convolutional neural networks (CNN) were used to analyze photographs of a whole core. The training dataset included twenty thousand images from various fields, wells and stratigraphic formations. For training, 800 samples were used, on which five lithotypes were identified (massive and layered sandstones, limestones, shales, siltstones). Algorithms for image rotation, brightness and color model changes (RGB and shades of gray) were used for augmentation. A super-pixel approach was applied, which took into account groups of pixels with their semantic values (texture, intensity, etc.). To create a neural network and analyze images, the open libraries Python OpenCV, NumPy, Python Keras and TensorFlow were used. The recognition accuracy was 72% compared to expert judgment. Inaccurate recognition obtained with close values of color and structural features of the classes and also at the presence of several lithotypes on photography. To improve the quality of recognition, the authors plan to implement a more detailed typing of lithotypes and pixel-by-pixel analysis of photographs [3, 9–11]. Analyzing photographs, authors formally recognize voids by color as one of the lithotypes. Cracks considered the only type of voids. K.I. Bagrintseva (2007) analyzed fracturing from photographs of luminophore-saturated core samples. In ultraviolet light, cracks on the samples are high-contrast in photographs and appear as luminescence [12]. For cracks selection, the author used the Canny boundary determination algorithm. The total fracture area calculated pixel by pixel within the selected boundaries. Deviations from manual laboratory measurements are up to 10%. To test the applicability of the proposed K.I. Bagrintseva method, we tested the Canny algorithm on photographs of core thin sections taken in daylight. In the case of a high color contrast of cracks with a mineral framework, a high-quality separation of the boundaries was obtained. If the contrast is low, the borders are not reliably distinguished; before applying the Canny algorithm, additional transformations of the photo image shall be required. O.A. Yadryshnikova (2021) used the SUSAN (Smallest Univalue Segment Assimilating Nucleus) algorithm for identifying cracks. To calculate the values of the area, length and average width of cracks, proprietary mathematical models have been proposed [13]. The results of automated and manual measurements of fracture parameters differ by no more than 10%. We were unable to reproduce the method proposed by the author due to the lack of an implementation of the SUSAN algorithm in the OpenCV library. The authors consider cracks as the only type of voids and select them using color segmentation algorithms. However, in the samples, along with cracks, voids of other types (cavities, intergranular voids) with similar values of color features may be present. In this case, for the cracks selection from the general array of voids, we propose to use geometric features—the shape and size of the area.
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3 Materials and Methods We solved the problem of recognizing and quantifying the parameters of voids and cracks in photographs of petrographic thin sections. The algorithms of the Python OpenCV library were used to analyze images. The calculations were carried out in the Python 3.6 programming language. A scheme for the assessment of porosity and fracturing parameters based on photographs of core sections was proposed: 1) semi-automatic selection of voids by color; 2) automatic selection of cracks from the general array of voids on geometric features; 3) estimation of parameters of absolute porosity, total length and average width of cracks. We considered the voids as one of the lithotypes of the rock, similar to the works of other authors [1–3, 5–10]. The values of the color features of the voids set interactively for each photo. To highlight voids, the OpenCV InRange color filtering algorithm was used in the HSV model. The result of applying the algorithm is a binary raster with cell values 1 (void) and 0 (mineral skeleton). The Canny boundary detection algorithm was applied to the binary raster, as a result, a raster image of the void boundaries was obtained. To the image of the boundaries of voids, the algorithm for highlighting the contours FindContours was applied. As a result, a vector image of the contours of voids was obtained, which allows calculating the values of the area and perimeter separately for each contour. The selection of contours using the FindContours algorithm can be performed on a binary raster without pre-testing applying the Canny algorithm. But such selection is of a lower quality, since FindContours has poor resistance to interference. To distinguish cracks from the general mass of voids, signs of area and shape were used. The cracks in the photograph of a thin section have a larger area than voids of other types (Figs. 3, 4 and 5). The boundary value of the area was selected empirically in pixels. The areas of the contours of voids were estimated using the ContourArea function, then the contours with an area less than the boundary area were deleted programmatically. The shape of the cracks shall be characterized by a significant excess of length over width; the ratio of the contour area to the square of the perimeter serves as an indicator of the shape. We accepted the excess of the length over the width by 10 times, it corresponds to the value of the ratio 0.02. Values less than or equal to 0.02 correspond to the contours of cracks, more than 0.02—to the contours of other types of voids. The value of the perimeter was obtained using the ArcLength function, the calculation of the ratio of the area to the square of the perimeter was implemented in software. Selection of cracks gave equal results by both methods. The absolute porosity value calculated as the ratio of the total area of the pixels related to the voids to the total area of the sample. To estimate the parameters of the cracks, the contours were approximated by inscribed rectangles using the minAreaRect function (Fig. 2). Each rectangle has a specific width and length. The software calculated the average width of the rectangles, taken as the average value of the crack width (opening), and the sum of the lengths of
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the rectangles, taken as the total length of the cracks. Length and width calculations shall be done in pixels. The calculation results shall be converted into millimeters, taking into account the scale set during shooting and indicated in the photographs. A detailed scheme of porosity and fracturing assesment based on photographs of core thin sections: 1. Voids selection using the InRanges algorithm in the HSV color model. 2. Calculation of the value of the absolute porosity as the ratio of the area of voids to the total area of the photography. 3. Selection of the boundaries of voids using the Canny algorithm. 4. Vectorization of boundaries of voids in the form of contours using the FindContours algorithm.
Fig. 2 Approximation of cracks contours by rectangles (minAreaRect function)
Fig. 3 Application window: 1—original photo, voids displayed in blue; 2—overlaying a binary raster of voids on a photo, voids selected in red; 3—the image of the contours of the cracks
Fig. 4 An example of recognizing a wide crack
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Fig. 5 An example of recognizing a narrow crack
5. Calculate the area values of contours and the ratio of the area of the contour to the squared perimeter using the ContourArea and ArcLength functions. 6. Selection of cracks from the general array of contours based on area and shape. 7. Rectangle approximation of crack contours using the minAreaRect function. 8. Calculation of the average crack width as the average width of the rectangles, the total crack length as the total length of the rectangles.
4 Results To test the scheme, an application was developed in the C# language (Fig. 3). The application provides interactive input of the color range of voids in the original photo, display of images of voids and cracks, output of values of absolute porosity, average width and total length of cracks, saving the results in the form of pictures and a text file with estimated parameters. The application was tested on twenty photographs of core thin sections. The thin sections were coated with a blue contrast resin before photographing, so in the photographs the voids correspond to dark blue and blue pixels. The application allowed us to select exposed cracks in all photographs. Reliable and accurate recognition was obtained for wide and deep cracks completely covered with contrast resin (Figs. 3 and 4). Errors associated with inaccurate identification of narrow cracks and with the assignment of other types of voids to the class of cracks (Fig. 5). Narrow cracks in the original photograph represented as chains of blue segments with low values of brightness and saturation (Fig. 5). This is due to the fact that the contrast resin penetrates the narrow cracks unevenly and shallowly. The segmented view shall be preserved when recognizing voids and then when selecting cracks from the general array of voids. The resulting fracture pattern is imprecise, but reliable and suitable for visual analysis. A consequence of the segmentation of narrow cracks is the need to establish low values for the area and shape indicators during cracks separation from the general array of voids. This leads to false positive recognition of non-fractured voids and distortion of the fracture pattern.
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Segmentation of narrow cracks leads to a decrease in the value of the total length of cracks in the photography. This decrease is not critical, since it shall be compensated by the summation of the void lengths, erroneously attributed to cracks. Comparison of the results of using the application with the results of the experts’ assessment showed 80% coincidence in the value of the total porosity, 70% in the values of the average width and total length of the cracks. The discrepancies in the results relate to photographs with low color contrast of the mineral framework and voids and to segmentation of the fracture image.
5 Discussions and Conclusions The developed scheme makes it possible to asses the parameters of porosity and fracturing using photographs of core thin sections with an accuracy of at least 70%. We think such a result to be successful for the pilot variant. It confirms the adequacy of the proposed solutions: a method for cracks selection from a total mass of voids by the shape and area characteristics, methods for the shape and area characteristics estimation, methods for the average width and total length of cracks estimation. To implement the scheme, algorithms of the OpenCV library were used. This allowed us to create a usable, compact user application in a short time. To recognize voids in photographs, a semi-automatic approach with interactive indication of color signs was applied. In the absence of a unified color classifier of rocks, semi-automatic methods for analyzing core photographs are the most realistic for production conditions. The development of methods for automatic classification based on deep learning and the creation of representative training sets for large geological objects are currently relevant prospecting and research tasks. Readymade solutions for these tasks for widespread implementation in companies have not been presented yet. For individual laboratories and medium-sized enterprises, selfdevelopment of applications for automatic classification of core photographs is very problematic. The implementation of applications for semi-automatic classification is real and will significantly increase the productivity and accuracy of the work of a petrophysics. The authors plan to refine the algorithm and software application. To reduce the number of errors caused by low color contrast of voids and mineral framework, it shall be planned to select augmentation methods. To eliminate the errors associated with the segmentation of cracks in the photographs, it shall be supposed to combine the segments into lines before the stage of separating cracks from the void array.
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6 Conclusion The article presents a scheme for the automated assessment of the parameters of porosity and fracturing of rocks using photographs of core thin sections. The scheme intended to increase the objectivity and accuracy of the assessment, reduce labor intensity and increase the efficiency of the petrophysic. Automation of the assessment based on the representation of core photos as formalized raster images, for the analysis of which computer vision algorithms were applied. In the works on the analysis of core photographs, the main attention shall be paid to the recognition of the composition of rocks based on differences in color characteristics. Voids are identified as one of the lithotypes, cracks as the only type of voids in the photography. Algorithms based on high color contrast with the mineral skeleton of the rock shall be used to highlight cracks. In the scheme presented in the article, void recognition shall be performed by color, similar to the works of other authors. A different approach was applied to the recognition of cracks: cracks are not the only type of voids in the photography; geometric features of the shape and size of the area were used to distinguish cracks from the general array of voids. To recognize voids and cracks and quantify their parameters, a sequence of algorithms of the Python OpenCV library was selected. Based on the scheme, a software application has been developed for assessing the parameters of porosity and fracturing of rocks (absolute porosity, average width and total length of fractures) from a core photography. We compared the results of using the application with the results of a non-automated assessment in the same photographs. The difference in results at this stage of the study is satisfactory. In further work, the authors plan to improve the quality of detecting voids and cracks, the color characteristics of which are close to the background, and to improve the algorithm for recognizing cracks.
References 1. Poshibaev VV, Konovaltseva ES, Omelchenko OV, Kuznetsov AS (2012) Lithological studies of core using modern hardware and software systems. In: Baltic School-Seminar: Petrophysical Modeling of Sedimentary Rocks Petromodel-2013, pp 1–9 2. Prince CM, Chitale J (2008) Core image analysis: reliable pay estimation in thin-bedded reservoir units. In: Society of Core Analysts Annual Meeting, pp 1–6 3. Baraboshkin EE, Ismailova LS et al (2019) Deep convolutions for in-depth automated rock typing. Computer Geosci 135. https://doi.org/10.1016/j.cageo.2019.104330 4. Akinshin AV, Akmanaev AR, Efimov VA (2013) Determination of the proportion of clay layers and inclusions from photographs of the core sample. Oil Ind 10:88–90 5. Khasanov II (2013) Method of quantitative evaluation of chromaticity of core material and its practical application. In: Materials of the Baltic School Seminar Petrophysical Modeling of Sedimentary Rocks, Petromodel 2013 6. Postnikov AV, Khasanov II (2015) Computer modeling of structural and texture features of rocks. In: Proceedings of the Baltic School-Seminar etrophysical Modeling of Sedimentary Rocks. Petromodel 2015. St. Petersburg
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7. Khasanov II, Ponomarev IA, Postnikov AV, Osintseva NA (2016) Methods for the quantitative assessment of the reservoir parameters of rock reservoirs using digital processing of core photos. In: Conference: Geomodel 2016–18th Science and Applied Research Conference on Oil and Gas Geological Exploration and Development, September 2016. https://doi.org/10.3997/22144609.201602277 8. Ellington WEJ, Moore JC, Smith MA, Dubinsky GL (2013) Products and methods for identifying rock samples. Pat. US 2013/0156270 A1 9. Patel AK, Chatterjee S, Gorai AK (2017) Development of online machine vision system using support vector regression (SVR) algorithm for grade prediction of iron ores. In: 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA), pp 149–152. IEEE 10. Baraboshkin EE, Ismailova LS, Baraboshkin EYu, Ivchenko A (2018) Core photo lithological interpretation based on computer analyses. In: Proceedings of the 2018 IEEE Northwest Russia Conference on Mathematical Methods in Engineering and Technology (MMET NW 2018), pp. 426–428 11. Baraboshkin E, Ismailova L, Orlov D, Koroteev D (2019) Machine vision methods in the application for core image segmentation. In: European Association of Geoscientists & Engineers. Conference Proceedings, Progress 2019, pp 1–5. https://doi.org/10.3997/2214-4609.201 953061 12. Bagrintseva KI, Chilingar GV (2007) Examining few methods for estimation of cracking porosity. On the part cracks are playing in development of complex reservoirs and in fluid filtration in natural reservoirs. Oil Gas Geol 5:26–35. ISSN 0016-7894 13. Yadryshnikova OA (2021) A software complex for core data processing when assessing hydrocarbon reserves under uncertainty. In: European Research: Innovation in Science, Education and Technology. Collection of Scientific Articles. LXXI International Correspondence Scientific and Practical Conference (London, United Kingdom), pp 14–23
Bulk Cargo Pressure Acting on Vehicle Body Walls Andrew Nikitchenko , Viktor Artiukh , Sergey Kargin , Valentina Kashintseva, and Asiiat Mottaeva
Abstract Transportation of bulk cargo occupies one of the leading positions in the market of transport services. According to analysts’ forecasts, in the future, the volume of transportation of such bulk cargoes as grain, cement, mineral fertilizers, etc. will only increase. The creation of vehicles designed for the transportation of bulk cargo with improved technical and economic indicators is an important and urgent task that cannot be effectively solved without a study of the loading of the vehicle with bulk cargo. The analysis of the applied methods for calculating the active and passive pressure of bulk cargo, including taking into account the vertical and horizontal accelerations acting on the vehicle, is carried out. Nowadays, equations used to determine bulk cargo pressure acting on vehicle body walls are applicable only for nearly vertical walls. Their use in calculating pressure for sloping walls for which angle of inclination to horizon is less than 80º leads to incorrect results. Paper is devoted to determination of compact analytical equations that can be applied to calculate pressure of bulk cargo acting on vehicle body walls in range of wall inclination angle to horizon equal to from 0 to 90º. Keywords Bulk cargo pressure · Thrust load · Active pressure · Dynamic pressure · Soil mechanics A. Nikitchenko All-Union Research and Development Centre for Transportation Technology, Street Polytechnicheskaya 29, St. Petersburg 199106, Russia V. Artiukh (B) Peter the Great St. Petersburg Polytechnic University, Street Polytechnicheskaya 29, St. Petersburg 195251, Russia e-mail: [email protected] S. Kargin Pryazovskyi State Technical University, Street Universytetska 7, Mariupol 87500, Ukraine V. Kashintseva Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, Moscow 109377, Russia A. Mottaeva State Corporation of Rostechnology, Usacheva Street, 24, Moscow 119048, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_164
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1 Introduction At present, transportation of bulk cargo makes up a very significant share in volume of transportation by road and by rail. Creation of vehicles with improved technical and economic parameters with high strength and reliability is important and actual task facing manufacturers [1–4]. Load which largely determines parameters of vehicles transporting bulk cargo is thrust pressure of bulk cargo. Value of this load directly affects walls thickness, number and section of body reinforcing elements and other key parameters, for example, such as tare weight and carrying capacity [5–7]. Recently, numerical methods for modeling bulk substances have been used in addition to theoretical mechanics studies of bulk substances based on analytical relations. Among them two main approaches can be distinguished which differ significantly from each other: – modeling of bulk body using finite element method (FEM); – modeling of bulk body using set of solid particles (method of discrete elements) [8–12]. Perhaps, usage of these methods makes it possible to obtain distribution of loads acting on walls of vehicle body from interaction with bulk substances which is more approximate to results of field tests but requires complex resource-intensive numerical studies implementation of which within project it is not always possible [13–17]. In this regard purpose of this paper is to develop method for determining active pressure acting on walls of vehicle body which can be used during numerical studies.
2 Methods and Results Equation often used for conducting numerical studies can be considered Pa = 1 + kνdγ · g · y · sin2α + ϕsin2αsinα − δ1 + sinϕ + δ · sinϕ − βsinα − δ · sinα + β2 where k vd is vertical dynamics coefficient; γ is cargo density; g is gravitational acceleration; y is distance downward from surface of cargo; α is angle of body wall inclination to horizon; β is angle of cargo surface inclination to horizon; δ is angle of friction of cargo against body walls; ϕ is angle of repose. Equation (1) can be converted to form
(1)
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Pa = γ · g · y · K a
(2)
where K a is active pressure coefficient Ka =
sin 2 (α + ϕ) 2 sin 2 (α)sin(α − δ) 1 + sin(ϕ+δ)·sin(ϕ−β) sin(α−δ)·sin(α+β)
(3)
This is well-known Coulomb equation. It can be converted to Rankine equation when wall is vertical (α = 90°) in Eq. (3), cargo is without top (β = 0°) and friction of cargo against body walls is neglected Ka =
1 − sin(ϕ) 1 + sin(ϕ)
(4)
This equation is recommended for use by the Association of American Railroads (AAR); in this case angle of repose is recommended to be taken equal to 25° and active pressure coefficient is always equal to 0.41 regardless cargo being transported. In addition, Eq. (4) is recommended by national standards in many countries in slightly modified form when cargo is without top (β = 0°) and friction of cargo against body walls is neglected (δ = 0) K a = tg 2
π 4
−
ϕ 2
(5)
Approaches used in Russian regulatory documents do not have clear theoretical justification while the Mononobe-Okabe approach takes into account horizontal and vertical accelerations and it is recommended by European standard for determining loads acting on walls from bulk mass. In this approach active pressure coefficient is determined as follows Ka =
(1 ± kvd )sin 2 (α + ϕ − θ ) 2 ) cos(θ )sin 2 (α)sin(α − θ − δ) 1 + sin(ϕ+δ)·sin(ϕ−β−θ sin(α−θ−δ)·sin(α+β)
when β ≤ ϕ − θ Ka =
(6)
(1 ± kvd )sin 2 (α + ϕ − θ ) when β > ϕ − θ cos(θ )sin 2 (α)sin(α − θ − δ)
(7)
where θ is angle of seismic inertia θ=
khd 1 ∓ kvd
where khd is horizontal dynamics coefficient.
(8)
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Table 1 Active pressure coefficient of bulk cargos Cargo
ϕ
δ
Theoretical method for active pressure calculation Coulomb
Rankine
Mononobe-Okabe 0.41
Coal
0.62
0.45
0.24
0.27
Sand
0.70
0.35
0.20
0.22
0.32 0.27
Grain
0.44
0.30
0.36
0.40
0.48
Alumina
0.37
0.40
0.41
0.47
0.55
Given approach is widely used for assessment of seismic impacts acting on elements of buildings and structures, therefore, terms such as ‘seismic inertia’ are used but this term denotes horizontal and vertical accelerations acting on structure. Thus, this approach can be used in transport engineering. Signs ‘±’ and ‘∓’ in Eqs. (6)–(8) mean that vertical acceleration should be considered acting up and down and the highest value obtained should be taken. Angle of seismic inertia is equal to zero and Eq. (6) is become equivalent to Eq. (1) when there is absence of horizontal accelerations. Table 1 shows values of active pressure coefficients calculated according to above given methods for several of the most typical bulk cargos. Wall is taken to be vertical (α = 90°), surface of bulk cargo is horizontal (β = 0°). Coefficient of vertical dynamics is equal to k vd = 0.34. Horizontal dynamics coefficient is equal to k hd = 0. Above given theoretical methods for calculation of bulk cargo active pressure were developed long time ago but they are still mostly used on practice. Numerous theoretical studies on this topic which were carried out later [18–20] are mainly devoted to consideration of any particular cases and in field of vehicle body loading research is hardly applicable. Applicability of considered methods for bodies with almost vertical walls is based on many years of design experience and does not raise any doubts. But attempt to determine thrust load for sloping wall using equations that take into account angle of inclination of body wall to horizon, as a rule, leads to unexpected results. Figure 1 shows dependence of denominator of Eq. (3) to angle of body wall inclination to horizon. After analyzing Eqs. (3) and (6) it can be concluded that value of denominator of this equation makes sense only for α ≥ δ because for α < δ root value is negative (refer to Fig. 1). As a result, question arises about limits of its applicability. Thus, there is a need to develop a methodology that allows to adequately determine loads acting from bulk cargo on body walls (including sloping ones) under action of vertical and horizontal accelerations. In case of horizontal surface of cargo, walls are classified as steep for which condition applies αst ≥
π − 2
1 sin(δ) δ ar csin − 2 sin(ϕ) 2
(9)
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Fig. 1 Dependence of radical value from Eq. (3) to angle of body wall inclination to horizon
Method for determining bulk cargo active pressure acting on sloping walls was developed long time ago by V.V. Sokolovsky but it did not find application in regulatory documents. This method is based on assumption that bulk cargo in certain area behind retaining wall is entirely in limiting stress state. Application of Sokolovsky method in general case requires a lot of calculations and for steep walls it gives results close to Coulomb theory. Thus, to determine coefficient of active pressure acting on steep walls for angle of inclination greater than αst according to Eq. (9) it is advisable to use Coulomb equation. S.S. Golushkevich proposed graphical construction (refer to Fig. 2) to determine soil pressure acting on sloping wall supporting flat slope. Graphical view given on Fig. 2 can be shown as equation K a_sloping =
A
sin(θ ) cos(ϕ)
2 + B 2 + 2 ABsin(θ + ϕ)
sin(θ ) cos(ϕ)
(10)
Following intermediate variables are used in Eq. (10) θ = ar ctg
cos(β) + A=
cos(ϕ)sin(ϕ − β) sin 2 (ϕ) − sin 2 (β) − cos(ϕ)cos(ϕ − β)
(11)
sin 2 (α + β)cos(ϕ) sin(α)cos(θ − β)sin(ϕ − β + θ )
(12)
cos(α + θ )sin(α + β) sin(α)cos(θ − β)
(13)
B=
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Fig. 2 Graphical view of soil forces acting on sloping walls
Angle β is equal to zero when surface of cargo is horizontal and, thus, calculation equations can be significantly simplified. As a result, to calculate active pressure coefficient acting on inclined walls following steps should be performed sequentially: – determine boundary of body wall steepness αst by Eq. (9); – active pressure coefficient acting on steep walls (α ≥ αst ) is determined by equation K a_steep =
sin 2 (α + ϕ) 2 sin 2 (α) · sin(α − δ) 1 + sin(ϕ+δ)·sin(ϕ) sin(α−δ)·sin(α)
(14)
– active pressure coefficient acting on sloping walls (α < αst ) is determined by equation K a_sloping =
1
2cos
π 4
−
ϕ 2
4cos(2α)sin(ϕ) − cos(2ϕ) + 3 sin(ϕ) + 1
(15)
Graph of dependence of active pressure coefficient on inclination angle of wall to horizon is shown on Fig. 3.
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Fig. 3 Dependence of active pressure coefficient to angle of body wall inclination to horizon
Solid line indicates values obtained by Eqs. (14) and (15); dotted line indicates values obtained by Eq. (3) (refer to Fig. 3). It is obvious that currently used method is only suitable for walls that can be classified as steep. Proposed method makes it possible to determine value of active pressure acting on walls with any angle of inclination. When wall becomes horizontal active pressure coefficient becomes equal to one that corresponds to gravity of cargo.
3 Conclusion The most common theories of analytical determination of bulk cargo active pressure which are currently recommended for use by current regulatory documents are considered. Their limited suitability for non-vertical walls is concluded. On the basis of fundamental work in the field of bulk cargo a new approach is proposed for determining active pressure acting on walls of vehicle body (including sloping ones) which can be used in numerical studies. Acknowledgements The reported study was funded by RFBR according to the research project №19-08-01241. The authors declare that there is no conflict of interest regarding the publication of this paper.
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References 1. Yepes V, Alcala J, Perea C, Gonzalez-Vidosa F (2008) A parametric study of optimum earthretaining walls by simulated annealing. Eng Struct 30(3):821–830. https://doi.org/10.1016/j. engstruct.2007.05.023 2. Mitra T, Chattopadhyay KK, Ghosh A (2021) Analysis of pile under seismic motion using pseudo-static approach. In: Latha Gali M, Raghuveer Rao P (eds) Geohazards. LNCE, vol 86, pp 335–344. Springer, Singapore. https://doi.org/10.1007/978-981-15-6233-4_23 3. Sokolovsky AI, Putyata AV (2016) Pressure on the front wall of gondola cars, changing the volume and characteristics of bulk cargo. In: Transport Means-Proceedings of the International Conference 20th International Conference Transport Means 2016, Proceedings, pp 942–947 4. Nikitchenko A, Artiukh V, Shevchenko D, Prakash R (2016) Evaluation of interaction between flat car and container at dynamic coupling of flat cars. In: MATEC Web of Conferences, vol 73, p 04008. https://doi.org/10.1051/matecconf/20167304008 5. Nikitchenko A, Artiukh V, Shevchenko D, Misailov A, Makhov D (2019) The use of nonlinear dynamic analysis in the calculation of cargo fall onto the hatch of the gondola car. In: E3S Web of Conferences, vol 110, p 01050. https://doi.org/10.1051/e3sconf/201911001050 6. Maksarov VV, Keksin AI (2018) IOP Conference Series: Earth and Environmental Science, vol 194, no 6, p 062016. https://doi.org/10.1088/1755-1315/194/6/062016 7. Patra S, Shahu JT (2019) Pseudo-static analysis of reinforced soil wall based on Pasternak model. Indian Geotech J 252–260. Springer Science and Business Media in.https://doi.org/10. 1007/s40098-019-00400-7 8. Yang M, Deng B (2019) Simplified method for calculating the active earth pressure on retaining walls of narrow backfill width based on DEM analysis. Adv Civ Eng 2:1–12. https://doi.org/ 10.1155/2019/1507825 9. Craig RF (2004) Craig’s soil mechanics, Seventh edn, p 458. ISBN 0-203-49410-5 10. Nikitchenko A, Artiukh V, Shevchenko D, Larionov A, Zubareva I (2019) Application of nonlinear dynamic analysis for calculation of dynamics and strength of mechanical systems. In: Murgul V, Pasetti M (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. AISC, vol 983, pp 496–510. Springer, Cham. https://doi.org/10.1007/978-3-030-19868-8_49 11. Pantelidis L (2019) The generalized coefficients of earth pressure: a unified approach. Appl Sci 9:5291. https://doi.org/10.3390/app9245291 12. Su Y-J, Song E-X (2015) Active earth pressure analysis based on normal stress distribution function along failure surface in soil obeying nonlinear failure criterion. Acta Geotech 11(2). https://doi.org/10.1007/s11440-015-0390-z 13. Levandovskiy AN, Melnikov BE, Shamkin AA (2017) Modeling of porous material fracture. Mag Civ Eng 1:3–22. https://doi.org/10.18720/MCE.69.1 14. Osadchii VA, Gorbatyuk SM, Filippov DI, Kuprienko NS (2019) Metallurgist 63(5–6):658– 664. https://doi.org/10.1007/s11015-019-00872-1 15. Solomonov KN (2012) Application of CAD/CAM systems for computer simulation of metal forming processes. In: Materials Science Forum, vol 704–705, pp 434–439. https://doi.org/10. 4028/www.scientific.net/MSF.704-705.434 16. Loginova II, Artamonova DA, Stolyarov ON, Melnikov BE (2015) Effects of structure type on viscoelastic properties of geosynthetics. Mag Civ Eng 4. https://doi.org/10.5862/MCE.56.2 17. Alekseev NN, Kovalenko IA, Stolyarov ON, Melnikov BE (2017) Viscoelastic properties of geosynthetic materials. Constr Unique Build Struct 5(56). https://doi.org/10.18720/CUBS.56.2 18. Kitaeva DA, Rudaev YaI, Ordobaev BS, Abdykeeva SS (2015) Modeling concrete behavior under compression. In: Applied Mechanics and Materials, vol 725–726, pp 623–628. https:// doi.org/10.4028/www.scientific.net/AMM.725-726.623
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19. Malinov LS, Malysheva IE, Klimov ES, Kukhar VV, Balalayeva EY (2019) Effect of particular combinations of quenching, tempering and carburization on abrasive wear of low-carbon manganese steels with metastable austenite. In: Materials Science Forum, vol 945, pp 574–578. https://doi.org/10.4028/www.scientific.net/MSF.945.574 20. Efremov DB, Gerasimova AA, Gorbatyuk SM, Chichenev NA (2019) Study of kinematics of elastic-plastic deformation for hollow steel shapes used in energy absorption devices. CIS Iron Steel Rev 18:30–34. https://doi.org/10.17580/cisisr.2019.02.06
Solving the Problem of Using Laser Levels in Low-Light Conditions Yanis Olekhnovich , Maksim Kuznetsov , Anna Zanina , and Andrey Ivashchenko
Abstract The solution of this problem is relevant today, because modern laser levels are not designed to work in low light conditions, which creates major problems when working at night and slows down the construction process in many of its industries, this is especially noticeable in the field of road construction. The articles propose a solution to the problem using the developed design to eliminate the lack of illumination for electronic levels. Verification of this installation is carried out experimentally, the technique of which is described in this paper. The results of which is the minimum value of illumination in which the UPC is minimal and in the operation of the device there are no serious deviations. This study offers a possible solution to the problems in the operation of electronic levels at night, which will allow in the conditions of the Russian daylight to increase the speed and quality of the constructed objects. Keywords Engineering surveying · Transport infrastructure · Illumination · Laser level · Leica Sprinter 50 M · Leica Sprinter 250 M · Sokkia SDL250 · Leveling · Construction of roads
1 Introduction In the modern world more often approved and built larger engineering objects. For the construction of such projects it is necessary to carrying out geodetic work [1]. For carrying out these works using various geodetic instruments, including levels [2]. Levels are divided into optical and electronic (digital), each of which has a number of advantages and disadvantages. Y. Olekhnovich (B) · M. Kuznetsov · A. Zanina Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya Street, 29, 195251 St. Petersburg, Russian Federation e-mail: [email protected] A. Ivashchenko Moscow State University of Civil Engineering, 26 Yaroslavskoye Shosse, 129337 Moscow, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_165
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Nowadays, electronic levels are increasingly being used, this is due to the fact that electronic levels are more accurate and comfortable to use [3]. A sufficient number of system studies have been carried out: electronic levels – bar-code rail, both abroad, and in the Russian Federation [4–10]. Modern construction also requires an increase in the speed of construction of objects, keeping while speed, since a small mistake on the scale of construction can lead to serious economic costs. High speed of construction can be achieved in various ways, for example by adding night shifts. The correct operation of these electronic levels may be impaired due to the low light exposure bar-code levels rail [6], which means, at the moment it is impossible to carry out geodetic leveling in night shifts [7]. In this article proposes a solution to this problem of taking readings by electronic levels due to the lack of sufficient illumination, on the example of devices Leica Sprinter 50 M, Leica Sprinter 250 M, Sokkia SDL 250. The aim of the work is to develop recommendations on the method by the way exploitation laser levels in low light conditions. In this article, the possibilities of three laser levels are considered: Leica Sprinter 50 M with an increase in the visual trumpet 24x with bar-code rail GSS 112. Standard deviation for 1 km double stroke – 2.0 mm; Leica Sprinter 250 M with an increase in the visual trumpet 24x with bar-code rail GSS 112. Standard deviation for 1 km double – 0.7–2.5 mm; Sokkia SDL 250 with an increase in the visual trumpet 28x with bar-code BGS 40. Standard deviation for 1 km double– 1.5 mm. With their help was produced geodetic survey in the dark time, and also a technical solution to the problem was proposed and its operability was checked.
2 Methods For geodetic work in the dark, the following technical solution is proposed. A special rectangular plate is attached to the tripod, at the corners of which wooden ribs are fixed, height greater than the height of any levels used. The device is located on a plate, the thickness of which allows you to fix it with an attachment screw on a tripod. A cover is installing on these ribs, on which, using fixtures and hinges, a source of directional light is fixed, in this case a lamp, at the end of which a focusing lens is mounted. The design resembles the shape of a parallelepiped, on the sides of which there is open space, which allows the levels to have a 3600 view. A diagram of this design is shown in the Fig. 1. For comparison of the considering levels a technique was developed based on leveling forward [11]. The order of the experiment consists of several stages: On the terrain a straight line breaks up with small differential and lack of artificial lighting. The track was chosen in the park of Peter the Great St. Petersburg Polytechnic University. Plan-scheme location of the track is shown in the Fig. 2.
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Lighting element
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Focusing lens Barcode rail
Levels Collimating ray
Fig. 1 Measurement scheme
Hou se 1
pr. G idro tehn ikov
10 m 20 m
0m 5m
30 m 40 m
15 m
50m
25 m
60 m 80 m
55 m
90 m
65 m
100 m
75m 85 m
av. G
45 m
jats kay
35 m
70 m
Hous e2
95 m
Fig. 2 Plan-scheme location of the track
Straight with a total length of 100 m is divided every 5 m and fixed with pegs. Each device produced leveling forward to get the source data. When passing the route before each countdown of the rail, the value of illumination is measured using a luxmetr, as well as the time when the report was made. Used digital luxmetr GM1010. Measurements are carried out a second time already at night with illumination close to zero. Then the third phase of measurements is carried out using a special design to improve visibility. The results of the experiment are shown in Tables 1, 2 and 3.
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Table 1 The results of leveling in the daytime by the device Leica Sprinter 50 M Location of points, m
Countdown, mm
Illumination, lux
Number of attempts
Time, min
5
1501
476
1
15:18
10
1350
430
1
15:20
15
1308
416
1
15:21
20
1222
556
3
15:23
25
1218
450
3
15:26
30
1007
455
1
15:27
35
755
348
2
15:28
40
538
470
1
15:29
45
477
530
1
15:30
50
538
531
1
15:30
55
685
503
1
15:31
60
846
510
2
15:33
65
1098
483
1
15:33
70
1169
477
1
15:34
75
1113
473
1
15:35
80
1080
366
2
15:37
85
1057
396
2
15:38
90
955
319
2
15:39
95
881
312
3
15:40
100
972
266
3
15:41
Table 2 The results of leveling in the nighttime by the device Leica Sprinter 50 M Location of points, m
Countdown, mm
Illumination, lux
Number of attempts
Time, min
5
0
0
9
17:25
Table 3 The results of leveling in the nighttime with a flashlight by the device Leica Sprinter 50 M Location of points, m
Countdown, mm
Illumination, lux
Number of attempts
Time, min
5
1502
10
1349
512
3
20:16
76.1
2
15
20:18
1307
52.9
5
20:21
20
0
7.64
8
20:26
Solving the Problem of Using Laser Levels in Low-Light Conditions
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3 Results and Discussion According to Table 1, in the daytime, the device took a count from all 20 points, but according to Table 2 it can be seen that in the nighttime with an illumination of 0 lx, the device could not make a single count due to the lack of the required amount of light. After installing the light source over the level, he took the first three points. A small number of measurements are related to the factory characteristics of the device, as well as a sharp drop in luminous flux due to discharge lantern power elements. It should be noted that the countdown was obtained with a minimum error. According to Table 4 and 4.1, in the daytime, this level took a counting from the first 18 points. This is due to the fact that after four in the evening he lacks light. In the nighttime, without installing a lighting device, the level did not work. After installing the light source level Leica Sprinter 250 M took the first 11 points. In the nighttime the device took the first 14 points. A small number of countdowns taken due to the fact, that at half past four in the evening the sunlight is not enough for the device to work. For this reason, the device did not take counts during night measurements without a flashlight, and after installing the light source, he took the counts of the first 7 points. According to Tables 1, 2, 3, 4 and 5, a graph was constructed dependence of changes in rails illumination on distance to the light source when working with the proposed equipment. The graph is shown in Fig. 3. Based on the data shown in Fig. 3 and in Tables 1, 2, 3, 4 and 5, the minimum illumination values were determined at which the devices took the last count. According to these tables and graphs, an analysis of the operation of each device was carried out. Leica Sprinter 50 M took the count on average from the 4th attempt with a minimum value of illumination – 52.9 lx. Leica Sprinter 250 M took the count on average from the 2nd attempt with a minimum value of illumination – 25.2. Sokkia SDL 250 took the count on the second attempt, but with an illumination of 21 lx. In this way, Leica Sprinter 250 M and Sokkia SDL 250 showed the same average number of attempts to take a count, but device Sokkia SDL 250 took the last sample at a lower value of illumination, which shows its advantage when working in the nighttime. A similar experiment was conducted by other authors, the results of which are given in articles [7, 12–14]. In article [7] the author says that illumination plays an important role when working with an electronic level, and it is also impossible to pass a 100-m-long track without proper lighting. In this work, we got a similar result: none of the devices could overcome the mark of 60 m, which does not correspond to the declared characteristics of the devices. In his article, the author says that that under natural light, his devices operate at 6.6 lx. In this article, the minimum value of illumination at which similar devices operate is –21 lx. This is due to that under artificial lighting there is a scattering of a beam of light, resulting in, a greater value of illumination is necessary for the stable operation of devices.
1500
1351
1309
1222
1088
1006
756
540
478
5
10
15
20
25
30
35
40
45
275
244
233
178
210
260
228
195
240
1
1
1
1
1
1
1
1
3
15:59
15:58
15:57
15:57
15:56
15:55
15:54
15:52
15:51
Time, min 0
−
8
Number of attempts
20
15
10
5
Location of points, m
1224
1309
1351
1502
Countdown mm
39
65
152
330
Illumination. lux
1
1
1
1
Number of attempts
Leica Sprinter 250 M, nighttime measurements with a flashlight
5
Illumination, lux
Countdown mm
18:46
18:44
18:43
18:41
Time, min
17:29
Time, min
Location of points, m
Number of attempts
Countdown mm
Location of points, m
Illumination, lux
Leica Sprinter 250 M, nighttime measurements without a flashlight
Leica Sprinter 250 M, daytime measurements
Table 4 The results of leveling by the device Leica Sprinter 250 M
1608 Y. Olekhnovich et al.
138
117
683
847
1096
1170
1112
1080
1058
−
55
60
65
70
75
80
85
90
147
169
174
187
202
227
236
539
50
Illumination, lux
Countdown mm
Location of points, m
7
1
2
1
1
1
3
1
1
Number of attempts
Table 5 The results of leveling by the device Sprinter 250
16:09
16:08
16:07
16:05
16:04
16:03
16:02
16:01
16:00
Time, min
60
55
50
45
40
35
30
25
Location of points, m
25.2 5.2
−
28.4
45.7
48.5
61
15.7
22.3
Illumination, lux
686
539
476
539
757
1006
1086
Countdown mm
8
4
1
2
5
4
2
1
Number of attempts
19:32
19:28
19:24
19:21
19:18
19:15
18:52
18:48
Time, min
Solving the Problem of Using Laser Levels in Low-Light Conditions 1609
59
50
1308.6
1223.9
1086.8
1006.5
755.9
539.1
477.3
537.6
683.9
846.8
1097.3
−
20
25
30
35
40
45
50
55
60
65
70
67
70
74
81
75
56
68
77
68
59
73
7
1
1
1
1
2
1
2
1
1
1
1
1
16:30
16:27
16:27
16:26
16:25
16:25
16:24
16:24
16:23
16:23
16:22
16:20
16:19
5
40
35
30
25
20
15
10
5
Location of points, m
21 10.7
−
23.6
47
73
140
430
510
Illumination lux
755
1007
1088
1223
1308
1350
1500
Countdown mm
8
2
3
1
3
2
2
1
Number of attempts
Sokkia SDL 250, nighttime measurements with a flashlight
0
−
1351.6
5
15
16:19
10
85
1
1501.3
Number of attempts
5
Illumination lux
Countdown mm
Location of points, m
Time, min
Sokkia SDL 250, nighttime measurements without a flashlight Number of attempts
Countdown mm
Location of points m
Illumination, lux
Sokkia SDL 250, daytime measurements
Table 6 The results of leveling by the device Sokkia SDL 250
18:24
18:14
18:12
18:10
18:09
17:54
17:44
17:40
Time, min
17:33
Time, min
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Solving the Problem of Using Laser Levels in Low-Light Conditions lux 600
-Sokkia SDL250. -Leica Sprinter 250M. -Leica Sprinter 50M.
500 Illumination, lux
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- The last point where the report was taken by the device
400 300 200
100 25,2
52,9 21,0
0
5
m 10 15 20 25 30 35 40 45 50 55 60 Location of point, m
Fig. 3 Graph of changes in the illumination of the rail from the distance to the light source
In article [10] authors, authors experimentally find, that with a value of artificial lighting of 20 lx, electronic level is operating normally. In this article, was obtained a similar value of 21 lx. The discrepancy is minimal and caused by different conditions for measuring illumination: in article [10] all work was carried out indoors unlike the conditions of this experiment: with open spaces as close as possible to real ones. From which we can conclude that the results obtained are correct.
4 Conclusions Based on the work done, the following conclusions can be drawn. 1. Conducted experiment indicates that due to a special technical solution, it is possible to carry out geodetic leveling not only in the daytime, but also at nighttime. This will allow to take measurements on night shifts, which will speed up the process of building roads. 2. According to the results of the work, comparing the performance of electronic levels when working in the nighttime Sokkia SDL 250 takes a counting at the lowest value of illumination –21 lx. 3. In order to take counting at a distance of more than 100 m in the nighttime, it is necessary to improve the quality of technical equipment. 4. During the experiment, was identified the main disadvantage constructions, consisting in the difficulty of selecting a lighting device for suitable dimensions, installation his focusing, fast discharge of the battery and weak issued light power at a long distance.
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5. This technical solution upon elimination main disadvantages construction will give an opportunity conduct geodetic work 24 h a day. That is why this direction needs to be investigated in more detail.
References 1. Mikhailenko EB et al (2014) Engineering geodesy. Use of modern equipment for solving geodetic problems. Peter the Great St. Petersburg Polytechnic University 2. Braila NV, Lazarev YG, Romanovich MA, Simankina IL, Ulybin AV (2019) Improving the organizational and technological reliability of construction and operation of industrial-civil and road construction facilities. Peter the Great St. Petersburg Polytechnic University 3. Olekhnovich Y, Sulatskiy K, Kulakov K (2019) Maintenance of construction pit against hydrological influences. In: E3S Web of Conferences, vol 135, p 5. https://doi.org/10.1051/e3sconf/ 201913503073 4. Fomicheva V, Zanina A, Radaev A (2020) Determination of optimal values for the technical characteristics of construction machinery unit with application of fractional linear programming. In: 24th International Scientific Conference Construction the Formation of Living Environment, (FORM 2021). https://doi.org/10.1051/e3sconf/202126304034 5. Glushko D, Pavlenko A, Radaev A, Rajczyk J (2021) Determination of the characteristics for the construction machinery fleet with application of fractional linear optimization. In: Vatin N, Borodinecs A, Teltayev B (eds) Proceedings of EECE 2020. EECE 2020. LNCE, vol 150, pp 441–453. Springer, Cham. https://doi.org/10.1007/978-3-030-72404-7_43 6. Mikhalenko EB, Belyaev ND (2014) Quality control of construction. Geodesic support of construction and operation of water management and hydrotechnical structures. Peter the Great St. Petersburg Polytechnic University 7. Mikhalenko EB, Belyaev ND, Zagryadskaya NN (2014) Monitoring of technical condition and deformations during construction and operation of structures. Peter the Great St. Petersburg Polytechnic University 8. Tsareva O, Portnov F (2019) Improving the methodology for observing deformations of buildings and structures. In: E3S Web of Conferences, vol 110, p 8. https://doi.org/10.1007/978-3030-37919-3_38 9. Yaagoubi R, Miky Y (2018) Developing a combined light detecting and ranging (LiDAR) and building information modeling (BIM) approach for documentation and deformation assessment of historical buildings. In: MATEC Web of Conferences, vol 149, p 6. https://doi.org/10.1051/ matecconf/201814902011 10. Tsareva O, Olekhnovich Y, Razumnova E (2020) Method of evaluation of historical objects of transport infrastructure deformations. In: Popovic Z, Manakov A, Breskich V (eds) VIII International Scientific Siberian Transport Forum. TransSiberia 2019. AISC, vol 1116, pp 387–404. Springer, Cham. https://doi.org/10.1007/978-3-030-37919-3_38 11. Elhassan IM, Ali AS (2011) Comparative study of accuracy in distance measurement using: optical and digital levels. J King Saud Univ Eng Sci 23:4. https://doi.org/10.1016/j.jksues. 2010.10.001 12. Nasreldin MA (2018) Design and simulation of a compensator for automatic-optical leveling instrument. In: ICCCEEE 2018. https://doi.org/10.1109/ICCCEEE.2018.8515894 13. Sidki HM (2015) New test method for surveying optical level instruments using CMM as a distance comparator technique. MAPAN J Metrol Soc India 30:5. https://doi.org/10.1007/s12 647-015-0131-7
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14. Beshr AAA, Abo Elnaga IM (2011) Investigating the accuracy of digital levels and reflectorless total stations for purposes of geodetic engineering. Alex Eng J 50:6. https://doi.org/10.1016/j. aej.2011.12.004 15. Beshr AAA, Irughe RE (2020) Development and implementation of calibration mathematical models and procedures for precise digital level. Environ Earth Sci 1:6. https://doi.org/10.24018/ ejgeo.2020.1.4.50
Quality Control of Welded Joints During Construction and Technical Expertise Irina Serebryanaya
and Alexandra Nalimova
Abstract Metal structures in the construction market of Russia occupy a significant segment, which has clearly grown during the pandemic. The use of metal structures simplifies and speeds up the construction of small architectural forms, supporting frames, facades, roofing, and bridge construction. All this becomes possible due to the performance characteristics, long service life, strength of metal structures. The wide use of metal structures in the construction industry puts forward serious requirements for the properties and quality of the metal used, the quality of construction and installation work, timeliness of maintenance and correct operation. The correct and timely solution of this set of tasks is the key to the absence of damages and deformations of metal structures, their durability and trouble-free operation. By introducing a new document, it is proposed to increase the efficiency of construction and technical expertise of metal structures of construction facilities. The form of the new document is developed on the basis of the analysis of the results obtained by applying statistical methods of quality control of welded joints of metal structures elements. Keywords Construction and technical expertise · Transport infrastructure · Metal structures · Defects · Welded joints · Statistical methods
1 Introduction Currently, there is a clear trend of rapid growth of industrial and civil construction, increasing interest in the reconstruction of buildings and structures of historical and cultural heritage. In addition, the number of legal transactions with real estate still under construction and already existing ones is constantly increasing. All this poses complex and diverse professional tasks for designers, architects, builders and operators. One of the most important tasks is to assess the construction quality and the quality of construction and installation work. Such an assessment should be carried I. Serebryanaya (B) · A. Nalimova Don State Technical University, 1, Gagarin Square, 344003 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_166
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out by qualified construction experts who understand all the nuances of construction, and fully cover all aspects of construction: from the design of the structure to operation. An important part of such an assessment is the diagnosis of the quality of building materials and building structures. The purpose of such diagnostics is to determine the degree of compliance of real materials and structures with the established regulatory requirements. Such compliance is established not only for the construction materials and structures used, but also for the corresponding types of construction and installation works, as well as methods of operation. Due to the fact that such assessments are characterized by a significant volume of measurements, complexity and variety of studies performed, rather high requirements should be placed on the competence of an expert builder. An expert must possess a variety of measurement methods for various indicators of the quality of construction products; be competent in the life cycle of products; know the regulatory requirements for products; understand the nuances of defects appearance in building materials, products, structures and the causes of their occurrence; be guided by the rules of construction and installation works, design and operation of structures. In addition, the expert should be able to carry out organizational measures related to expert examination and documentation (photo fixation) of the results, to make a competent and motivated conclusion. In the work of the expert, an important place is occupied by the building structures quality assessment. To date, metal structures play a huge role in the building structures market. In relation to Russia, according to the Association for Steel Construction Development, the market of metal structures demonstrates enviable stability. Thus, in the first half of 2020 alone, the production and consumption of metal structures amounted to more than 950 thousand tons [1]. At the same time, the use of metal structures in commercial real estate, construction of roads and railways, in the construction of new buildings, in particular, in the construction of hospital buildings for COVID-19 patients, has significantly increased. The main advantages of using metal structures in construction are a significant reduction in construction time, its weak dependence on the time of year and weather conditions (all-season), reduced transport costs and high energy efficiency. The widespread use of metal structures in the construction industry places serious demands on the properties and quality of metal, the quality of construction and installation work, timely maintenance and proper operation. The correct and timely solution of this set of tasks is the key to the absence of damage and deformation of metal structures, their durability and trouble-free operation. From the range of issues, this paper considers the issue of quality control of constructed and already operated metal structures. Since in most cases metal structures are load-bearing, the very existence and normal functioning of the entire structure or facility largely depends on their performance. In this regard, the inspection of metal structures should be carried out regularly, with a certain frequency.
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The inspection procedure of metal structures should be carried out for compliance with the requirements established by the state [2]. The main purpose of such a procedure is to prevent the occurrence of any problems associated with metal structures. Such an inspection in many cases can be quite a complex technical measure and, therefore, very expensive. Therefore, the owners who operate such buildings and structures sometimes neglect to conduct a timely technical inspection. It is important to note that the examination of metal structures should be carried out not upon the fact of the first appearance of any defects, for example, deformations or any other damage. In cases where an emergency has already occurred, the goals and objectives of the construction expertise should be significantly changed. Now the purpose of the construction expertise, first of all, is to identify the main causes of damage to metal structures [3–6]. There can be quite a lot of such reasons. All of them are of a very diverse nature: mistakes made during design; mistakes made during installation; improper operation (overload, untimely prevention or repair); the influence of external factors on structures (climate, the presence of harmful impurities, high temperatures, high humidity, etc.), etc. Welded joints are one of the places where defects may appear when carrying out construction and installation works with metal structures. Any deviation from the technical standards that occurred during installation work threatens to disrupt the operability of the entire structure. As a result, the structure may not withstand the estimated design load and break down, which in turn can lead not only to a threat to human life and health, but also to tangible financial losses [7–11]. Quality control of welds is necessary to make sure that the weld is high-quality, well-welded, has no undercuts, overlaps, burns, excessive ripple and other flaws. Welds are checked not only after the construction is made, but also during its operation – as they are subject to corrosion and other adverse external influences. Regular inspections are also necessary when surfacing several layers on an already used and worn-out structure. At the same time, each new layer must be subject to mandatory control. Namely, it is necessary to measure the length of the weld and the thickness of the base metal. These data are compared with the established standard for this element of the metal structure, taking into account the load applied to this element. The first (primary) quality check of the weld is done by the welder himself. Further control is carried out by other employees: job superintendant, engineer, etc. After the inspection, an act of visual inspection of the welds is drawn up [12–14]. A significant disadvantage of the primary check is that there is currently no uniform standard for the template of the act and its design. This means that each employee can issue it in any form. It can be written by hand or typed on a computer. A letterhead with a corporate logo and details of a construction and installation company or the most ordinary piece of paper can be used. It seems necessary to standardize the quality control process of welded joints within the organization, it is mandatory to develop a template for this document and use it. It can also be recommended that the form of the act and its design be specified in the accounting policy of the enterprise. If the act is made in an electronic form, then it must be printed out
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in order to place the original signatures of the responsible persons in it. The act of visual inspection of welds must be done in a single copy, which is assigned a serial number [15, 16].
2 Methods In this paper, a methodology for improving the documented procedure for quality control of welds is proposed. Such control must necessarily be carried out: – at the stage of construction and installation works during the initial quality control of works; – during the repair and restoration of metal structures, which are already in use; – during the construction and technical expertise. Namely, it is proposed, in addition to the mandatory template of the act, to use the statistical method of quality control of welds used during the construction expertise [7, 14]. To do this, it is proposed to introduce a new document “Checklist” [7, 8]. It is advisable to draw up this document not only during the initial inspection of the quality of work, but also to use it during the construction and technical expertise. The checklist will allow the inspector (foremaster, construction expert) to facilitate the task of controlling welds and provide various kinds of facts for analysis, correction and improvement of the quality of the welding process (production of works). The proposed checklist is a data logging tool made in a standard form. The controlled parameters have been entered in this form in advance, according to which it is possible to mark the necessary data using marks or any symbols [9, 10, 13]. In order to fully fulfill the purpose of the checklist, the following research tasks were formulated: – to study the classification of welds; – to study the main defects of welds (external and internal) that occur at the stage of work and the causes of their occurrence; – to develop a checklist template; – to test the template of the checklist in real conditions during the construction and technical expertise of the object with the use of metal structures. The study of welds classification has shown that, in general, they can be classified according to a fairly large number of parameters: position in space; degree of convexity; relative location; extent; shape of the products being welded; direction of the acting force; direction of the vector of action of external forces; shape of the cross section, etc. [1, 12] Weld defects are divided into external, deteriorating mechanical properties of the joint, which in turn leads to destruction. Such defects include undercuts, overlaps, gas voids, cracks, and so on. Internal defects, unlike external ones, are the most dangerous, since they are difficult to detect during visual inspection. They are identified only by diagnostics using non-destructive testing devices.
Quality Control of Welded Joints During Construction …
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3 Results According to the results of the work, external defects of welds that occur at the stage of work (defects in the shape and size of the weld, defects in the preparation and assembly of products, external defects) and the causes of their occurrence are formulated. To present and analyze the information, the statistical the cause-andeffect diagram method was used [8, 12]. This method makes it possible to effectively identify the most significant cause-and-effect relationships between factors and consequences, and present the results graphically. Figure 1 provides the resulting cause-and-effect diagram. Table 1 presents the classification of internal defects of welds and the causes of their occurrence. When developing a Checklist template for registering the types of nonconformities, a list of major defects was formulated. The inspector (the expert during the construction and technical expertise) must put in the registration table in the appropriate column a conditional symbol (dots, dashes, crosses or others) corresponding to the number of the observed events. The data are summarized for each category and for the entire observation interval. Before using the form, it is necessary to instruct the employee who will be responsible for collecting information. One must understand how to fill out the checklist, what events need to be recorded in it and in what time interval. The data analysis is proposed to be entrusted to the inspector (an expert during the construction and technical expertise).
Fig. 1 Ishikawa diagram
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Table 1 Internal defects of welds and their causes Gas voids
Slag intrusions
Causes of Occurrence Coating humidity; Refractory and inIrregular adjust- creased viscosity of ment of the burn- electrode slags; Poor deoxidation of er flame; The presence of the weld metal; scale and rust; Poor cleaning of the Staining of drop- rollers from slag at let-like inclusions multilayer welding; of metal and slag; Slag has leaked into Insufficient pro- the gaps between the tection of the edges and undercuts; weld during CO2 Uneven fusion welding Exclusion Methods Forging Single inclusions are allowed
Poor penetration
Cracks
Insufficient current or low burner power; Fast movement of the electrode and the burner; Ingress of oxides into the weld; Poor edge cleaning
Harmful impurities of sulfur and fluorine; High cooling speed; Changes in the structure of the metal during welding; Voltage due to uneven heating
Removal of the defect by surface gouging with repeated welding
Unacceptable defect
If a defect is detected during the examination that is not specified in the checklist (type of defect or measurement range), it must be entered in the “Other” category. Based on the analysis of the results obtained on the classification of internal defects of welds and the causes of their occurrence, a checklist template was developed. The proposed template is presented by Table 2.
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Table 2 Checklist for weld quality assessment Inspector – …… Welder – ……… Date ………………
Control area ………
Number of defects
Defect type
Control data
Total
Wrong edge bevel angle
///// ///// //
12
Large (small) root face
///// ///
8
Non-constant clearance between the edges along the /// length of the joint
3
Mismatch of joints of elements, contamination, edge ///// ///// stratification
10
Uneven weld width
/
1
Uneven reinforcement along the weld length
///// ///// ///// 15
Undercut
/
1
Crater
//
2
Overlap Burnout Gas voids
///
3
Slag inclusions
//
2
Lack of penetration Cracks Other
4 Discussion A method for improving the documentation of the procedure for welds quality control assessment using a checklist is proposed. This method was developed based on the application of statistical methods of quality control of welded joints of elements of metal structures and was successfully tested during the construction expertise of construction sites in Rostov-on-Don. The results obtained indicate the relevance, expediency and high efficiency of this document. Thus, the proposed checklist for welds quality assessment developed by the authors is recommended to be used during construction and technical examinations of metal structures of construction objects. The task of further research is to develop a comprehensive computer model describing the occurrence of all possible deviations in the operation of the metal structure depending on types of defects [11]. Such a model can be created, for example, in the ANSYS 2021 R1 finite element analysis software package. This will allow expert analysis to simulate the emerging and observed defects in metal structures and determine the cause of their occurrence. In turn, this will contribute to finding ways to eliminate the defects that have occurred, and, therefore, will be the key to their absence during further metal structure operation.
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References 1. 23rd International Conference Russian Metal Market, Moscow, Russia, 9 November 2020. http://2020.rynokmetallov.ru/results 2. SP 13-102-2003. Requirements for inspection of load-bearing structural elements of buildings and structures. Moscow: Gosstroy of Russia, State Unitary Enterprise CPI, p 22 3. Vydrin VN, Zubko OV (2015) Diagnosis of the technical state of metal structures. Symb Sci Int Sci J 10–2:112–114 4. Saraeva A (2020) Features of the construction and technical examination of metal structures. In: The Future of Science-2020: A Collection of Scientific Articles of the 8th International Youth Scientific Conference, pp 403–406 5. Guseva KB (2019) Features of the survey of metal structures. Izv. Olympus 5(39):23–25 6. Serebryanaya IA, Egorochkina IO, Shlyakhova EA, Matrosov AA, Serebryanaya DS (2020) Integrated construction and technical structural analysis of the industrial buildings. In: IOP Conference Series: Materials Science and Engineering, vol 913, p 022071. https://doi.org/10. 1088/1757-899X/913/2/022071 7. Buntova OS, Buntova EV, Yusupova OV (2013) Methods of mathematical statistics used in the construction examination of materials. Int Res J 11–1(18):5–8 8. Terekhina YV, Kotlyar VD, Serebryanaya IA, Cherenkova IA (2013) Quality control sheet–a data collection and analysis tool for the production of ceramic bricks. Eng J Don 4(27):230 9. Uchaeva TV (2020) Application of statistical methods in the analysis of production efficiency of construction materials. Constr Mater Equip Technol 21st Century 3(4(254–255)):46–49 10. Egorov SB, Loktev DA, Kapitanov AV, Mitrofanov VG, Egorova TP (2015) Statistical process management as a way of reducing production costs and improving product quality. Eurasian Union Sci 5–3(14):51–55 11. Penyagin D, Mavlikhanov E, Zolatorev A, Novikov D, Novikov V, Ryabinin Y (2016) Typical defects detected during expert examination of steel structures of skips. Tech Superv 1(110):140– 141 12. Malashina LA, Suschev AK (2020) Analysis of welded steel structures defects. In: Technology and Technology: Ways of Innovative Development. Collection of Scientific Works of the 9th International Scientific and Practical Conference, pp 10–12 13. Knyazkina EV, Minina MV (2018) Statistical methods of monitoring main defects of welded steel structures by example of scattering diagram. In: Innovative Strategies for Management Development in Construction and Urban Economy, Samara, pp 221–227 14. Sabirov RA, Poteshkin PV, Avrenyuk AN, Yakimov VM, Filipovich SS (2019) Studies ensuring completeness and reliability of conclusions on technical condition of structures. Oil Ind 8:141– 145 15. Slivets EP (2018) Forensic construction, technical and cost expertise in forensic engineering expertise. Forum Young Sci 4(20):1359–1364 16. Zilberova IY, Petrov KS, Morozov VE, Kirillova AS (2019) Methods and means used by the construction expert in conducting judicial construction and technical examinations. Eng J Don 2(53):22
Reduction of Permeability of Fine-Grained Concrete Inna Egorochkina
and Elena Shlyakhova
Abstract The paper substantiates the possibility of reducing the permeability of fine-grained concrete due to the modification of cement by expanding additives and a micro-filler. Fly ash from Novocherkassk GRES power plant with a specific surface area of about 3000 cm2 /g was used as a micro-filler. The combined use of an expansion additive, a micro-filler and a superplasticizer provided a significant increase in the strength and water resistance of fine-grained concrete. The positive effect of a sulfoalluminate-type expansion additive on the activation of ash microparticle components is shown. An exothermic effect that occurs during the hydraulic activity of ash, contributing to the formation of a fine-pored, low-defect structure of concrete, has been established. A resource-saving technology has been developed for producing materials with a particularly low degree of permeability, resistant to damaging effects of aggressive industrial environments. The innovative technology allows expanding the raw material base for the production of special types of concrete, including for winter concreting, contributes to saving natural resources and improving the environmental situation in the areas of thermal power plants. Keywords Fine-grained concrete · Transport infrastructure · Fly ash · Expansion additive · Water resistance
1 Introduction The reliability of concrete and reinforced concrete structures operated under aggressive environmental conditions is determined not only by strength indicators, but also by the permeability of concrete. This is especially true for fine-grained concrete, including sand, which is characterized by increased cement consumption. This is due to the fact that in fine-grained concrete there is no coarse aggregate, which is the main component in ordinary heavy concrete by weight and volume. I. Egorochkina (B) · E. Shlyakhova Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_167
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As shown by Yu.M. Bazhenov, V.K. Vlasova, I.M. Krasny and many other researchers [1–3], cement consumption in fine-grained concrete can be significantly reduced by introducing finely dispersed mineral micro-fillers into the mixture. At the same time, in order to achieve an ecological and economic effect, it is preferable to use local man-made materials that are waste or by-products of industrial enterprises [4, 5]. At the same time, it should be borne in mind that the high total surface of the components of fine-grained concrete determines the high water consumption of the concrete mixture to ensure the required workability. As a result, fine-grained concrete has increased permeability due to evaporation of excess mixing water. Such concretes are characterized by the increased shrinkage deformations, which negatively affect the formation of the structure and strength and durability indicators. The most effective way to reduce water demand of a concrete mixture is the introduction of superplasticizer additives into its composition, the range of which is very wide [6, 7]. The techniques for compensating shrinkage deformations by introducing additives with an expanding effect are widely covered in the technical literature [8, 9]. The modification of fine-grained concrete mix with a complex additive based on an ash micro-filler, a specially prepared expanding additive and an effective plasticizer will optimize the structure and properties of fine-grained concrete mixes. The purpose of the research is to develop a resource-saving technology for the production of high-tech fine-grained concrete. The stage of the research work is to study the effect of a complex additive based on an ash micro-filler and a compensator for contractional and moisture shrinkage on the main parameters of the quality of the concrete structure – indicators of water permeability and frost resistance, which determine the durability of products and structures. The technology of preparation of a complex additive and recommendations for the selection of the composition of fine-grained concrete are presented in [9].
2 Methods In this work, the following materials were used to optimize the structure and properties of fine-grained concrete: Cement Cem I 42,5 was used as a binder for the control compositions of concrete. Cements with an expanding additive in the amount of 10 and 20% of the cement weight, respectively designated as RD-10 and RD-20, were prepared. The preparation of RD-10 and RD-20 involved thorough mixing of Portland cement (joint grinding for 20 min) with the additive components - alumina cement and gypsum in a ratio of 1:0.5 by weight [9]. As a fine aggregate, local sand from the Samara deposit was used with a fineness modulus of Mk = 1.7; packed density of 1470 kg/m3 ; specific gravity of 2.63 g/cm3 ; voidness of 44%.
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The C-3 superplasticizer used in the work, obtained on the basis of naphthalensulfonic acids and formaldehyde, meets the requirements regulated by GOST 24,211. The addition of this superplasticizer exhibits a high plasticizing effect, helps to increase the connectivity of the concrete mixture, as well as to slow down the processes of macro- and micro-stratification of it over time. The fly ash of dry sampling from the electrofilters of Novocherkassk GRES power plant has a specific surface area of about 3000 cm2 /g, its average density is in the range of 1250 … 1300 kg/m3 . The bulk density of fly ash is 700…900 kg/m3 ; the true density is 2.1 … 2.4 g/cm3 . According to its chemical composition, the fly ash under study, according to GOST 25,818, is classified as low-calcium, with practically no hydraulic properties. Since the ash under study does not have hydraulic activity, it was introduced into the composition of a fine-grained mixture instead of a part of sand with a constant consumption of cement. The optimal consumption of the fly ash filler was determined by the results of strength tests of 40 × 40 × 160 mm-sized beam samples from equally mobile sand-concrete mixtures with the same flow, determined according to GOST 310.4. When studying the properties of cements, aggregates and concretes, test methods regulated by regulatory documents were used, as well as devices and equipment that meet the requirements of current standards. To study the construction and technological properties of fine-grained concrete, a fine-grained concrete mixture of a given composition was prepared in accordance with the model of a complete factorial experiment according to the Hartley-5 plan [10]. To study the structure and properties of fine-grained concrete it was proposed to use technological factors (Table 1). The methodology of mathematical planning of the experiment, the rationale for the choice of composition factors are presented in detail in scientific article [9]. This research paper presents an analysis of response functions—indicators of the quality of the material structure—the volume of open capillary pores, the average pore size, water resistance (filtration coefficient), compressive strength. Fine-grained concrete, like ordinary concrete, is a capillary-porous material, the structure of which is characterized by one or another content of both macro- and Table 1 Factors and variation levels №
Technological factors
Variation levels −
0
+
1
Water-cement ratio (W/C)
0.4
0.5
0.6
2
Concentration of ash microparticles (ASM), %
0
15
30
3
Concentration of the expanding additive (RD), %
0
10
20
4
Concentration of the plasticizing additive (C-3), % 0
0.7
1.4
5
Degree of formation of the concrete structure by the end of hardening in water (τ), %
70
100
40
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micropores and capillaries. Its permeability depends on the properties of the binder and fillers and the quantitative ratio between them, the pore structure and total porosity. The most objective characteristic of concrete permeability is water resistance. This property characterizes the ability of the material to resist the filtering penetration of water through its thickness under pressure. Water resistance of capillary-porous bodies such as concrete is determined by the parameters of the pore structure, the size and total volume of pores, the ratio between large and small pores, as well as the volume of so-called “through” and closed (or conditionally closed) pores. Since it is not possible to determine analytically the degree of influence of the introduction of additives of micro-fillers and superplasticizers into the composition of fine-grained concrete, direct comparative tests have been carried out in this work by the standard method. Determination of density, kinetics of water absorption, total and open porosity of concrete was carried out in accordance with the methodology of GOST 12,730.112,730.4. Water resistance of the compared compositions of fine-grained concrete was determined by testing the cylinder samples by the “wet spot” method according to GOST 12,730.5-2018, according to which the maximum water pressure is determined, at which water seepage through the sample is not yet observed.
3 Results Table 2 presents the compositions of fine-grained concrete and the test results. Figure 1 shows the analysis of the effect of the concentration of the micro-filler (ASM, %) on the concrete strength. The results in Fig. 1 show that the optimal ratio between screening and sand in the composition of fine aggregate is in the range of 45/55–55/45 (wt., %). As it can be seen from the above figure, the optimal consumption of fly ash as a micro-filler in sand concrete is about 15% of the sand mass. At the same time, an increase in the strength of concrete over 40% is achieved. Experimentally, the optimal dosage of the superplasticizer was established – 0.7% by weight of cement, providing equal mobility of mixtures with a decrease in the water-cement ratio from 0.56 to 0.41. Figure 2 shows the impact of expanding additives RD-10 and RD-20 on the main characteristics of capillary-porous structure of the state of fine-grained concrete with optimum amount of ash (15%). Figure 3 presents data on the water resistance assessment of samples of experimental compositions. The effect of the reaction of the interaction of ash and the expanding additive is clearly illustrated in Fig. 4. The effect of the interaction of ash and expanding additives.
390
430
390
14
15
1670
1670
1170
1420
1420
1170
1420
1670
1170
1670
1170
1420
1420
1170
1420
1670
3
Sand kg/m3
0
0
500
250
250
500
250
0
500
0
500
250
250
500
250
0
4
ASM kg/m3
80
40
80
80
40
0
0
0
40
40
80
80
40
0
0
0
5
RD kg/m3
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
6
W C
9.3
9.8
7.8
7.7
8.1
8.4
8.0
9.1
9.1
9.3
9.6
7.8
8.7
10.7
11.2
11.5
7
W28 0 ,%
8.0
8.3
6.9
6.8
7.0
7.1
7.6
8.1
8.0
8.0
7.2
6.8
7.1
8.4
9.6
14.6
8
W250 0 ,%
0.49
0.51
0.42
0.43
0.46
0.52
0.50
0.51
0.65
0.50
0.48
0.47
0.55
0.62
0.70
0.76
9
λ
Permeability indicators
0.17
0.19
0.11
0.11
0.14
0.26
0.28
0.30
0.18
0.18
0.14
0.17
0.24
0.30
0.31
0.34
10
A
7.1
7.9
7.0
6.9
7.0
8.1
7.0
9.1
9.6
9.4
9.4
8.2
9.4
9.7
11.8
12.4
11
Porosity, %
W10
W10
W12
W12
W12
W10
W12
W8
W8
W8
W8
W12
W10
W8
W8
W6
12
Water resistance, mark
41.1
40.8
42.2
45.0
44.3
43.7
44.0
41.2
40.8
30.2
40.8
40.2
39.2
31
35
25.0
13
R, MPa
Operating indicators
Note *–water consumption–190 l/m3 ; placeability of concrete mixtures was achieved by the introduction of superplasticizer C-3 in an amount of 0.7% of cement consumption **–Control composition of fine-grained concrete
390
470
8
13
380
7
12
380
6
430
330
5
11
330
4
470
380
3
470
380
2
10
380
1
9
2
380
1**
Cement kg/m3
Material consumption *
1
№
Table 2 Test compositions and test results
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Rb, MPa
1628
40 35 30 25 20 15 10 5 0 0
5 10 15 20 Part of sand replaced by ash, %
25
, Structure quality indicators %
Fig. 1 The effect of the ash micro-filler (ASM) on the sand concrete strength 20 W0250
15 10
W028
Pо
Pо
W028
W0250 W028 Pо W0250
W028 Pо
W0250
5 0 1**
0
10
RD,%
20
Waterproof grade, W
Fig. 2 Characteristics of capillary-porous structure of the state of fine-grained concrete control structure (1**) and filler ASM (15%) and RD-10 and RD-20: —volumetric water absorption in 28 days (W28 −volumetric water absorption in 250 days (W250 0 ); —full porosity (Po), %; 0 )
14 RD-20
12 RD-10
10
RD-10 Cem
8 6
RD-20
Cem
RD-10 RD-20 Cem
Cem
4 1**
0
15
30
Compositions with ASM micro-filler, % sand replacement
Fig. 3 The effect of RD-10 and RD-20 expansion additives on the water resistance index (water resistance grade, W) of fine-grained concrete with ASM micro-filler
Compressive strength, MPa
Reduction of Permeability of Fine-Grained Concrete
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45 40 35 30 25 20 0
15
30
ASM,%
Fig. 4 Dependence of concrete strength on its composition
- Control cements composition of fine-grained concrete. - RD-10 - cements composition with an expanding additive in the amount of 10% of the cement weight. ◦ – RD-20 - cements composition with an expanding additive in the amount of 20% of the cement weight.
4 Discussion The introduction of fly ash in the amount of 15–20% into the composition of finegrained concrete instead of sand and an expanding additive in the amount of 10– 20% has a positive effect on the formation of the basic functional properties of concrete – density, strength, water resistance, frost resistance. The structure of concrete is constantly changing as a result of the external environment and changes in internal physical–chemical processes. At the same time, constructive processes that improve the structure of concrete, increase its properties, and destructive processes that lead to the destruction of the material, which prevail one over the other at different stages of concrete maturity, take place simultaneously. The study of the kinetics of water absorption of fine-grained concrete, hardened in adverse atmospheric conditions for 250 days, showed the predominance of destructive processes in the structure of Portland cement concrete. This is primarily expressed in an increase in the value of volumetric water absorption W250 0 by 8–10% and an increase in the average pore size (λ) to 15% (Fig. 2). In concretes with ash microparticles and cements with RD, the processes of structural change are of a relaxation nature. The kinetics of water absorption of fine-grained concrete with ash microparticles in the amount of 15% and expanding additives is characterized by an increment in the mass of samples over time. Volumetric water absorption of fine-grained concrete with ash microparticles and expanding additives is 25–30% lower than that of the control composition; the average size of open capillary pores (λ) decreases depending on the composition of the concrete mixture and the concentration of ash microparticles by 35–40% with an
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increase in the uniform size of open capillary pores (λ) by 12–20%. An increase in the concentration of RD to 20% leads to an increase in the index of homogeneity of the indirect structure (A) by 12% and a decrease in total porosity (Po) by 15–18%. It is obvious that if the initial water absorption value of W28 0 does not exceed 80– 95 g/l (8–9.5%), then there is a tendency for subsequent self-healing of microdefects of the concrete structure after the prolonged exposure in the atmosphere. In this case, it is allowable to talk about the predominance of structural processes over the processes of destruction. In concretes with ash microparticles introduced instead of a part of sand in the composition of 15–20% and modified with an expanding additive, there is a significant decrease in the amount of water absorption by the end of the tests for 250 days. An increase in the water resistance class of compositions with ash microparticles to W8 values has been experimentally established, and using modifying compositions with ash and expanding additives RD-10 and RD-20 to W10 and W12, respectively. The positive role of the complex interaction of fly ash and the components of the expanding additive is manifested in the activation of the processes of hydraulic activity of ash microparticles. In the subsequent periods of hardening, the number of pores decreases due to the complete or partial filling of the capillary pores with pozzolanic reaction products. A decrease in the volume water absorption of W250 0 to 50–65 g/l (40%) is recorded, an increase in the degree of uniformity of the size of capillary pores (A) to an average of 20%, which indicates the formation of a discrete, less defective capillary-porous structure. Such concretes, in accordance with the terminology of GOST 12,730.5, are classified as materials with a particularly low degree of permeability. Such concretes are characterized by the resistance to damaging effects of various media, which significantly expands the scope of their application.
5 Conclusions Resource-saving technologies for the production of building materials involve the economical use of natural resources and the active reuse of industrial waste. The properties of such innovative materials have not been fully studied, which is a good scientific potential. Optimization of concrete composition using various industrial wastes with highly effective chemical and mineral additives with a known positive effect, allows you to optimize the structure and properties of new materials. It was found that ash microparticles exhibit a sufficient plasticizing effect due to the high specific surface area. The positive effect of the sulfoalluminate type expansion additive on the activation of ash microparticle components has been established. The exothermic effect that occurs in the process of increasing the hydraulic activity of ash contributes to the formation of a finely porous, low-defect structure of concrete.
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Heat generation in winter concreting conditions is of great technological importance. The amount of heat generated depends on the fineness of the grinding and the mineral composition of the cement-ash composition. Replacement of sand with microparticles of ash in an amount of 15–20% and modification of cement with an expanding additive in an amount of 10–20% reduces the overall porosity by 18–20%, increases compressive strength up to 40%, increases the water resistance class to the values of W12 class. Fly ash of thermal power plants is a high-quality mineral additive. Its application leads to the saving of natural resources and the improvement of the ecological situation in the areas of thermal power plants.
References 1. Kravtsov AV, Tsibakin SV, Evseeva TM, Sobolev KG, Potapov VV (2017) Cast concrete with the use of copper production wastes and nano silica. Vestnik MGSY 12(9):1010–1018. https:// doi.org/10.22227/1997-0935.2017.9.1010-1018 2. Sobolev K (2015) Nanotechnology and nanoengineering of construction materials. In: Sobolev K, Shah S (eds) Nanotechnology in Construction, pp 3–13. Springer, Cham. https://doi.org/10. 1007/978-3-319-17088-6_1 3. Panchenko AI, Kharchenko IYA (2005) Particularly finely dispersed mineral binder of Microdur type: technology and prospects for utilization. Stroitel’nye Materialy 10:76–80 4. Kuznetsova EF, Sobolev GM, Sobolev K (2014) Self-consolidating green concrete based on metakaolin and aggregate fines. Mater Res Soc Proc 1611:75–80 5. Samchenko S, Krivoborodov Y, Burlov I, Krivoborodova S (2018) Sulfoaluminate cements based on technogenic waste. In: 18th International Multidisciplinary Scientific Geo Conference SGEM2018, Section: 26. Green Buildings Technologies and Materials, vol 18, pp 341–348. https://doi.org/10.5593/sgem2018/6.3/S26.045 6. Salamanova MS, Saydumov MS, Murtazaeva TS, Khubaev MS (2015) High quality modified concrete based on mineral admixtures and different nature superplasticizers. Innov Invest 8:163–166 7. Mailyan DR, Nesvetaev GV, Koryanova YI, Lesniak EV (2021) Strength and deformation of bending normal sections made of concrete frame structure. In: International Scientific Conference “Construction and Architecture: Theory and Practice for the innovation Development” (CATPID-2019). https://doi.org/10.1088/1757-899X/1083/1/012034 8. Kharchenko I, Panchenko A, Kharchenko A, Alekseev V (2018) Modeling of structuring processes at hardening of expanding cements and concretes on their basis. In: MATEC Web of Conferences 196:04035. https://doi.org/10.1051/matecconf/201819604035 9. Shlyakhova EA, Serebryanaya IA, Egorochkina IO, Matrosov AA, Soloviev AN (2021) Compositions based on expansion additive for the repair of reinforced concrete structures. In: IOP Conference Series: Materials Science and Engineering, vol 1029, no 1, p 12047. https:// doi.org/10.1088/1757-899X/1029/1/012047 10. Rebrova IA (2010) Planning the experiment: a training manual. SibADI, Omsk
Strength and Deformability of Bent Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) Using a New Technology Sergey Georgiev , Dmitry Mailian , and Elnar Huseynov Abstract In recent decades CFRP-based composite materials have been gaining rapid growth in the field of strengthening of reinforced concrete structures, which have a number of advantages over traditional reinforcement options based on metal, concrete and mortar. The greatest effectiveness is observed in reinforcing bent elements, especially flat floor slabs or girders of bridges, flyovers and overpasses. It is known that approximately 70% of all reinforced concrete constructions make up bent elements and therefore all researches in this area are promising and urgent. This article is devoted to determining the effectiveness of composite materials in reinforcing bent elements. In carrying out the reinforcement work, a new technology has been used, which is described in detail in this paper, and previously unexplored carbon fiber based materials have been investigated. As a result of this study, all the qualities of the technology used were examined and the reliability and effectiveness of the composite materials were verified. Keywords Concrete · Transport infrastructure · Reinforced concrete · Composite material · Carbon fiber reinforcement · External reinforcement · Deformations · Bent elements
1 Introduction As the experience shows, strengthening of reinforced concrete structures or restoration of capacity is much easier and cheaper than construction of new ones [1], especially it concerns buildings and structures located in conditions of tight housing development. The existing methods of strengthening [2, 3] allow to solve the tasks repair of reinforced concrete structures repair, but there is a number of drawbacks, which is mainly reflect on labor intensity and cost of work. S. Georgiev (B) · D. Mailian · E. Huseynov Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_168
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The study of composite material properties [4, 5] has shown the possibilities and prospects of their use in the field of strengthening of reinforced concrete structures [6– 8]. The scientific research conducted in Russia [9–11] and abroad [12–14] confirmed this opinion. The search for new methods of strengthening of reinforced concrete structures with composite materials and carrying out experiments is an advanced and urgent work [15–17]. It is worth noting that the department of reinforced concrete and masonry structures of Don State Technical University (DSTU) has been studying the properties of composite materials and their influence on increasing the capacity of reinforced concrete structures for 10 years in a row [18]. The first researches were based on the products of “BASF” company: positive testing results were received, processing of the obtained data has allowed developing a number of proposals for perfecting of normative calculation techniques [19]. Nowadays the most perspective materials for strengthening of reinforcement concrete constructions with composite materials are products of the OOO Gidrozo Company. The study of their materials and technology for strengthening has shown that there are a number of essential differences in the similar technology, when using BASF Company materials. There are a number of advantages, which reduce labor intensity, however, the problem of reliability of strengthening remains poorly studied. Search of earlier experiments on determination of effectiveness of composite materials of Gidrozo Company regarding reinforced concrete structures didn’t give results and it was decided to carry out a number of researches on determination of effectiveness and reliability of glue system and reinforcement materials for the most widespread in practice structures, namely, reinforcement of bent elements in the normal cross-section. These experiments will replenish the experimental database of similar research in Russia.
2 Materials and Methods The experiment program involved the manufacture and testing of 4 bent elements. The experiment can be divided into two stages. The first stage involved the testing of reference samples and the second stage involved the testing of reinforced beams to determine the effect of carbon steel on the increase of the bent elements strength in the normal cross-section. Reinforcement schemes included the most common options used in practice. It was decided to determine the effectiveness of composite reinforcement on increasing strength and deformability of a beam reinforced with carbon fabric of 100 mm width in two layers and to test a similar beam with anchoring devices located in the area of structural support. The characteristics of the girders and reinforcement schemes are given below: 1. (Girder code is BE-1). Reference beam, dimensions 2200 × 125(h) × 250 (mm), reinforced with longitudinal reinforcement located in the tensile zone (2Ø10A500), in the compressed zone (2Ø6B500). Transverse reinforcement
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Table 1 Test results of concrete cubes Code
Average cubic strength of concrete R
ex p
, MPa
Prism strength of concrete ex p Rb , MPa
Concrete grade B
BA-1
46.05
33.3
35.85
BC-1, BC-2
51,4
36.9
40
Ø6B500 with spacing s1 = 100 mm and s2 = 150 mm. Design concrete class B35. 2. (Girder code is BE-2). Reference beam - dimensions, reinforcement and design class of concrete are the same as beam BE-1. 3. (Classification of the girder is BC-1). Reinforced girder. The dimensions, internal reinforcement and characteristics of the materials used are the same as the BE-1 girder. In addition, the beam is strengthened in the stretched area with a canvas 100 mm wide and 1600 mm long, with two layers of carbon steel fabric (Armoshel KV500). 4. (Girder code: BC-2).Reinforced girder. The same as the BC-1 girder in all respects, but additionally reinforced with U-shaped anchors in two layers of carbon fiber reinforced plastic (Armoshel KV500). Concrete characteristics of the test specimens: Cement of 500 grades, sifted sand of 1600 kg/m3 density and crushed stone 5–20 mm fraction were used for the concrete mixture. To determine the compressive strength of concrete and the corresponding concrete class, a series of cubes with the edge width of 15 cm were tested. The concrete cubes were tested in a 250 tons press in accordance with GOST 10,180-2012. The results of the test are given in Table 1. Characteristics of the internal reinforcement of the test samples: The metal frame of the internal reinforcement consisted of 2 rods of diameter 10 A500, located in the tensile zone and two rods of diameter 6 B500 in the compressed zone. The transverse reinforcement was placed with different spacing, made of 6 mm diameter B500 rods. Characteristics of the composite material: To reinforce the beams Armochel KV500 carbon fiber reinforcement material was used as an adhesive, and Monopox 372 epoxy two-component carbon fiber impregnation compound was used as a primer and leveling putty. The characteristics of the reinforcement materials are shown in Table 2. All the test beams had the same length, height and width, which were 220, 25 and 12.5 cm. The reinforcement technique was carried out in stages as follows: The first stage was surface preparation. The concrete surface was cleaned of cement mortar by machining the surface with an abrasive tool. After grinding the surface was cleaned from dust and degreased with acetone. Prior to laying the impregnated composite canvas, uneven surfaces were leveled with Monopox 372, a thickened epoxy compound. A layer of epoxy primer was applied to the concrete surface
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Table 2 Armochel KV 500Technical data Properties of composite material Property
Typical value icpytanix
Standard znaqenie
Main fibers tensile strength
1062 MPa
903 MPa
Tensile modulus of elasticity (GPa)
102 GPa
86.9 GPa
Nominal thickness of laminate
0.42 mm
0.42 mm
for installation of the system. Differences of more than 2 mm in length per 30 cm in the direction of the fiber orientation axis on the concrete surface were leveled out by grinding, while small differences of up to 2 mm were leveled out by Monopox 372 epoxy thickener. Before applying the composite reinforcement systems, the surface of the structure was roughened, level, clean, dry and dust-free. When preparing the surface of the post reinforcement, corners were rounded to a radius of 2.2 cm with an abrasive tool. The irregularities in the corners and potholes in the concrete were filled with Monopox 372 thickened epoxy. The second stage of the reinforcement was the preparation of Armochel KB500 reinforcement canvas. Armoshel KB500 roll material was laid on a clean, even surface, and covered with film, rolled to the required length and cut to length and width according to the reinforcement scheme. The fabric was cut according to the number of layers required by the project. Cutting was carried out with scissors transversely by cutting the fibers and longitudinally by cutting the bonding strands. The next strengthening step was impregnation of the material with Monopox 372 epoxy. Epoxy Monopox 372 was prepared at 25 °C ambient temperature, which meets the requirements of work performance technology. Quantitative preparation of epoxy and canvas was carried out in exact accordance to the technical descriptions of the materials used and applied evenly and in the amount specified in the manufacturer’s recommendations. Components A and B of Monopox 372 were mixed by pouring component B into a container with component A. Mixing was carried out for 5 min with a mixer for polymer formulations at a speed of 300–400 rpm until a homogeneous mixture was obtained. Impregnation with the adhesive was carried out on the material, pre-cut according to the required dimensions, laid out on a clean flat surface on the film. The entire surface of the canvas was impregnated with Monopox 372 epoxy using brushes and rollers, the penetration was visually recorded and then the process was repeated on the second side of the canvas until it was saturated. The application of the reinforcement material was carried out as follows. The cleaned and levelled surface was primed with Monopox 372 epoxy primer. The primer was applied with a brush. The carbon fibre-reinforced canvas was applied onto the concrete surface one layer at a time, following the orientation of the fibres according to the application scheme. When laying the impregnated canvas, care was taken to avoid air bubbles between the concrete substrate and the composite material
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by smoothing the canvas with a plastic trowel and hands. The first layer of Armosil KB500 was applied to the primed concrete surface. A further layer of impregnated canvas was then laid “fresh on fresh”. All intersections and overlaps of the composites were epoxy grouted to even out the differences. When reinforcing the girder with anchoring devices, the longitudinal reinforcement and the anchoring devices were glued alternately. The design of stands and the development of test plans were carried out in accordance with the requirements of GOST 8829-94. The test procedure for beams was performed according to the following algorithm. Test specimens were tested for a short-time load on a specially equipped stand under the scheme of single-span freely supported beams. The load N was transferred on a beam by two concentrated forces F symmetrically placed in thirds of the span which were applied through supporting plates 20–25 mm thick and 100 mm wide. The calculated beam span is 180 cm and the shear span is 60 cm. All the specimens were tested until failure by stepwise increasing load, the intensity of which (Ni) was controlled by the clock type indicator, which was set on the reference dynamometer of the Turner system with a maximum strength of 500 kN. The beams were loaded in steps with an incremental load and an exposure time of 10–15 min at each stage of loading. During this time, instrumentation was taken, the girders were inspected and photographed, and cracks were sketched and measured. The accepted load level was approximately 1/20 and 1/10 of the Nexp limit value. The width of the opening of the normal and inclined cracks was recorded digitally and determined by computer software. The normal cracks were measured at the center of gravity of the steel reinforcement and the inclined cracks were measured together with their largest opening.
3 Research Results Fracture pattern of bendable elements: 1) Beam BE-1. Fracture in the pure bending zone from concrete crushing, due to the development of the main crack. 2) Beam BE-2. Fracture similar to Beam BE-1. 3) Beam BC-1. The beam collapsed along the normal section with simultaneous tear-off of composite material from the body of concrete at the end of the structure (Fig. 1). The composite reinforcement detachment from the concrete was accompanied by partial detachment of the concrete protection layer section. 4) Beam BC-2. Collapse in the shear span with incomplete utilization of the bearing capacity of the normal and inclined sections due to slippage of the carbon fiber reinforcement along the anchor. The failure of the structure occurred from crushing of the concrete, due to the development of a main crack (Fig. 2).
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Fig. 1 Reinforced stand BC-1 after testing
Fig. 2 Reinforced stand BC-2 after testing
Table 3 Results of strength test of experimental beams Beams codes
Concrete grade
1
2
BE-1
B36
BE-2
Load capacity N s exp , N f exp , kH
Experienced beam moments M s exp , M f exp , kH*m
Reinforcement coefficient, crein1
Ultimate deflection strength of beams N exp , kH
Reinforcement coefficient, crein2
Ultimate crack strength N s exp , N f exp , kH
Reinforcement coefficient, crein3
3
4
5
6
7
8
9
57,9
17,4
−
57,7
−
57,9
−
−
60,6
−
60,6
−
B36
60,6
18,24
Average value
59,25
17,82
BC-1
B40
119,0
35,7
2,0
BC-2
B40
125,4
37,6
2,11
59,25 100,5 103
59,25 1,7
119,0
2,0
1,74
111,3
1,88
Numerical values of bending strength as well as reinforcement coefficients, relative to reference specimens are given in Table 3.
4 Discussion The effectiveness of composite materials in reinforced concrete bending members was determined for 3 load levels and for each beam. All strength values and the corresponding reinforcement coefficients are given in Table 3. Plots of the deflection values and crack widths are shown in Figs. 3 and 4.
Strength and Deformability of Bent Reinforced Concrete Structures …
BE-1
BC-1
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BC-2
BE-2
Fig. 3 Comparison of deflections of etalon (BE-1, BE-2) and reinforced (BC-1, BC-2) beams as a function of load magnitude
N, кН
140 120
BE-1
100
BC-1 BC-2
80
BE-2
60 40 20 0
0
0.1
0.2
0.3
0.4
0.5
0.6
acrc, mm
0.7
Fig. 4 Comparison of normal crack opening width of reference (BE-1, BE-2) and reinforced (BC-1, BC-2) test beams in terms of load intensity
The first load level is the ultimate or breaking strength of the specimen. The strength value of the reinforced elements is compared with the strength of no reinforced specimen while a reinforcement factor is determined. The second level of loading is measured at the maximum deflection of the elements. According to SR 63.13330.2018 for all bendable elements the deflection limit values must not exceed the value calculated according to the formula fult = lo /200. For the test specimens l0 = 160 cm, this distance is measured from the points of the beam supports, hence the limit deflection will be 8 mm.
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The third level of loading is measured at the ultimate crack opening width acrc , the value of which is 0.3 mm. according to SR 63.13330.2018. Results of comparison of parameters, reinforced samples, in comparison with the reference one showed the following picture. Reinforcement coefficients of specimens BC-1 and BC-2, compared with the average strength of the reference specimens, were 2,0 and 2,11, respectively, at the limit deflections the increase was 1,7 and 1,74, and at the limit value of crack opening width was 2,0 and 1,88. At the same time, the load resistance of the reference beam when it reached the ultimate crack in the cross-section, practically ceased to increase during three test stages before failure. For the reinforced beam BC-1, the crack opening width did not reach the limit value; the element was destroyed at crack opening width equal to 0.2 mm, at a load level of 110 kN. During the next loading up to the 120 kN, the composite material, having torn off part of the concrete protective layer, delaminated from the structure. The failure occurred brittle concurrently with the delamination of the composite material.
5 Conclusion The following conclusions can be drawn from the test results and the strength and deformability analysis carried out on the test specimens: – the ultimate deflections and crack opening widths were achieved during the test, with a strength gain of around 200%; – the difference in effectiveness of composite reinforcement with and without anchoring devices varies by up to 10%; – these results indicate that composites with a high percentage of reinforcement are indeed effective in reinforcing bending members. The application of composite materials to concrete structures is reliable and ensures that beams and reinforcement systems work together until they reach their deflection and crack width limits; – The installation of U-shaped anchors in the supporting sections of the beams, if gluing is possible, is recommended, but the expected increase in strength will not exceed 10%. This applies to reinforcement of concrete bending members with carbon fiber in two layers, with a total cross-sectional area of 0.54 cm2 . Considering the above, the use of composite materials from the company Hydrozo Ltd. makes it possible to significantly increase the strength and deformability of bended reinforced concrete structures. The reliability of the reinforcement method was checked and confirmed, which is less labor-intensive and less complicated in carrying out the reinforcement processes. As a result of the experiment, the values of structural deflection and crack opening widths were recorded in almost all cases within the normative limits. The tear-off of the composite material from the concrete was accompanied by explosion of the
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protective layer of the concrete, which means that the concrete and the reinforcement material are reliably bonded.
References 1. Ivanov YV (2012) Reconstruction of Buildings and Structures: Reinforcement, Restoration, Repair. A.S.V., Moscow, p 312 2. Bedov AI et al (2021) Vosstanovlenie i usilenie osnovanij i stroitel’nyh konstrukcij ekspluatiruemyh zdanij i sooruzhenij. Problemy stroitel’nogo kompleksa Rossii: Materialy XXV Vserossijskoj nauchno-tekhnicheskoj konferencii, 31 Mar 2021. Ufimskij Gosudarstvennyj Neftyanoj Tekhnicheskij Universitet, Ufa, pp 3–6 3. Bedov AI, Znamenskij VV, Gabitov AI (2014) Ocenka tekhnicheskogo sostoyaniya, vosstanovlenie i usilenie osnovanij i stroitel’nyh konstrukcij ekspluatiruemyh zdanij i sooruzhenij. V 2-h chastyah. CH.I. Obsledovanie i ocenka tekhnicheskogo sostoyaniya osnovanij i stroitel’nyh konstrukcij ekspluatiruemyh zdanij i sooruzhenij. Pod red. A.I. Bedova: Ucheb. pos. ASV, Moscow, p 704 4. Shilin, AA, Pshenichny VA, Kartuzov DM (2007) External reinforcement of the reinforced concrete structures by composite materials. OAO Izdatel’stroyizdat, Moscow, p 184 5. Ustinov BV, Ustinov VP (2009) Research of the physical-mechanical characteristics of the composite materials (KPM). Izvestia vuzov. Construction 11–12:118–125 6. Skrypnik ME (2017) Primenenie kompozitnyh materialov dlya usileniya vneshnim armirovaniem zhelezobetonnyh konstrukcij. Mezhdunarodnyj studencheskij stroitel’nyj forum. Belgorodskij gosudarstvennyj tekhnologicheskij universitet im. V.G. SHuhova, Belgorod, pp 231–234 7. Litvinov AG (2010) Restoration and Reinforcement of Reinforced Concrete Structures with Polymers, p 103. Publishing house Science, Education, Culture, Novocherkassk 8. Klevtsov VA, Fatkullin NV (20060) Calculation of Strength of Normal Sections of Bending Elements, Reinforced by External Armature of Composite Materials. Scientific & Technical Conference of Young Scientists and Postgraduate Students of Central Research Institute of Scientific Research 9. Kostenko AN (2010) Strength and Deformability of Centrally and Extra-Centrally Compressed Brick and Reinforced Concrete Columns Reinforced by Carbon and Glass-Fiber Reinforcement, Moscow, p 26 10. Podnebesov PG (2015) The results of studies of strength and deformability of reinforced concrete columns reinforced with cladding. In: Urban Planning, Reconstruction and Engineering Support for Sustainable Development of Cities of the Volga Region, pp 42–47 11. Cherniavsky VL et al (2006) Guidelines for Strengthening of Reinforced Concrete Structures with Composite Materials. InterAqua Ltd. 12. Afanas’ev AV (2018) Usilenie zhelezobetonnyh balok. Innovacionnoe razvitie regionov: potencial nauki i sovremennogo obrazovaniya: materialy Nacional’noj nauchno-prakticheskoj konferencii, Astrahan’, 09 fevralya 2018 goda.–Astrahan’: Astrahanskij gosudarstvennyj arhitekturno-stroitel’nyj universitet, pp 66–68 13. Arduini M, Nanni A (1997) Behavior of precracked RC beams strengthened with carbon FRP sheets. J Compos Constr U.S.A. 1(2):63–70 14. Nemcev IA (2013) Primenenie ugleplastikov dlya usileniya stroitel’nyh konstrukcij. Nauka i molodezh’: problemy, poiski, resheniya: trudy Vserossijskoj nauchnoj konferencii studentov, aspirantov i molodyh uchenyh, Novokuzneck, 14–15 maya 2013 goda. Novokuzneck: Sibirskij gosudarstvennyj industrial’nyj universitet, pp 57–60 15. Popov AY, Gosina KK, Petrov IV et al (2015) Classification, composition, advantages and disadvantages of multicomponent composite materials. Omsk Sci Messenger 3(143):42–45
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16. Bozhenko AM, Shevtsova MA (2021) Advantages and disadvantages of using composite materials in building. Perspect Sci 11(146):60–62 17. Grakhov VP, Popov VS, Shchuklina AY (2015) Analysis and advantages of non-metallic reinforcement from composite materials in construction. In: The Collection: Actual Questions of Theory and Practice of Composite Reinforcement in Construction. Responsible for the Collection, pp 42–51 18. Polskoy P, Georgiev S, Muradyan V, Shilov A (2018) The deformability of short pillars in various loading options and external composite reinforcement. In: MATEC Web of Conferences, p 02026 19. Georgiev S, Mailyan D, Blyagoz A: Proposals for determining the relative deformations design value of εb3 concrete in volumetric deformation conditions, pp 155–162. scientific.net/MSF.1043.
Creation of the Strength Design Methodology for Eccentrically Compressed Reinforced Concrete Structures Strengthened with Carbon Fiber Reinforced Plastic (CFRP) in the Longitudinal and Transverse Directions Sergey Georgiev , Dmitry Mailian , and Alik Blagoz Abstract The set of rules (SP 164.1325800.2014) on strengthening of reinforced concrete structures with composite materials, applied in Russia, a methodology for design of compressed elements, taking into account transverse and longitudinal reinforcement is absent. This fact does not allow to asses objectively the impact of composite materials on increasing the strength of reinforced concrete samples. In this work, existing design methods for strengthening flexible eccentrically compressed reinforced concrete structures were investigated. Seven test samples reinforced in longitudinal transverse direction were fabricated and tested. In the course of the experiment the deflections were measured and the strength of the structures was determined. Calculation algorithms have been compiled and the theoretical strength has been determined and the accuracy of the calculation methods has been evaluated according to the existing calculation methods considered by SP 164.1325800.2014, one of which takes into account only the longitudinal reinforcement and the other takes into account only the transverse reinforcement. According to the results of the analysis, recommendations have been made to create a calculation methodology that takes into account both longitudinal and transverse reinforcement. Keywords Concrete · Transport infrastructure · Reinforced concrete · Compressed elements · Flexibility · Reinforcement · Eccentricity · Strength · Carbon fiber reinforced plastic · Composite materials
1 Introduction Today, reinforced concrete is the most common material of load-bearing buildings and structures [1, 2]. The influence of various negative factors [3–5] leads to the S. Georgiev (B) · D. Mailian · A. Blagoz Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_169
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destruction and loss of bearing capacity of individual reinforced concrete structures and to the need to ruggedize a construction or build a new one according to research results. An experiment has shown that the construction of new structures is considerably more expensive and longer in time than the reconstruction of existing structures. Accumulated experience gives an opportunity to reinforce concrete structures recovering or increasing bearing capacity, by ensuring reliability for many years [6–8]. As a rule, concrete makes up more than 95% of the volume in reinforced concrete structures, therefore, all scientific research aimed at increasing the characteristics of concrete are promising, especially it concerns compressed reinforced concrete structures [9, 10]. Concrete and steel are traditionally used as reinforcement materials, moreover special attention is paid to combined action of reinforcement materials and the structure being reinforced. In this regard, concrete, mortar and metal are the main reinforcement materials for compressed reinforced concrete structures. It should be noted that traditional methods are characterized by their complex and labor-intensive workflow. For some objects such reinforcement can lead to a significant cost or it can’t be possible to do it at all. In addition to traditional reinforcement options, the use of composite materials has been gaining popularity in recent decades [11–13]. A number of studies have shown not only high efficiency [14–16], but also a number of additional advantages of the new reinforcement method [17–19]. The main advantages include the modern technology of work performance, which allows reducing labor costs and anti-corrosion measures, and, with the development of composite materials production technology, there is also a significant reduction in the cost of reinforcement work. Considering that composite materials have been studied not so long, a small amount of experimental data has been accumulated to create a reliable and calculated apparatus for strengthening most reinforced concrete structures, but the work in this direction is underway [20, 21]. In 2015, a set of rules (SP 164.1325800.2014) on strengthening of reinforced concrete structures with composite materials was issued in Russia. In the field of reinforcement of compressed structures the normative calculation has two directions: 1-Reinforcement in transverse direction, which is most effective for centrally compressed structures of low flexibility; 2-Reinforcement of non-centrally compressed flexible reinforced concrete samples in tensile zone herewith reinforcement material is located in longitudinal direction. The calculation technique on strengthening of reinforced concrete structures simultaneously in longitudinal and transverse directions is not considered in the normative document. This is justified by the set of rules and by the restrictions on the characteristics of structures designed for reinforcement with composite materials in the transverse direction. At the same time, the initial eccentricity of load application e0 is limited (the value must not exceed 0.1 h), the cross-sectional dimension ratio must not be more than 1.5 and the flexibility of the structure must not exceed λi = l0/i = 50. However, as the results
Creation of the Strength Design Methodology …
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of the experiments have shown, there is a reinforcement effect on increasing the strength and stiffness of the specimens beyond the limits recommended in the set of rules. Consequently, the set of rules for reinforcement, in some cases, underestimates the actual performance of composite materials. Taking into account that the results of calculations according to SP 164.1325800.2014 underestimate the effectiveness of composite materials in the field of reinforcement of flexible compressed reinforced concrete structures, the purpose of this study was to develop a calculation method for determining the strength of compressed reinforced concrete flexible struts at different eccentricities of load application, reinforced in the longitudinal and transverse directions. Another purpose was to detect a discrepancy of theoretical values of durability with experimental ones and to define possibility of using the calculation tool at designing of structures with different flexibility.
2 Materials and Methods In this work, experimental and theoretical strength values of specimens of different flexibility tested at 2 eccentricities of load application were compared. All specimens were reinforced with two lamellae placed in longitudinal direction on the tensile face of reinforced concrete flexible struts. As transverse reinforcement, clamps and semi-hoods made of 3 layers carbon fiber were used. The main characteristics of test samples are described below. Seven samples were manufactured, reinforced and tested. Three of them had flexibility λh = 10 and 4 pieces had flexibility λh = 20. Samples were tested at 2 eccentricities of load application equal to e0 = 2 and 4 cm, which correspond to 0.16 and 0.32 h. The eccentricities were taken in such a way that in the first case, the load did not go beyond the core of the section, in the second case the load was outside the core, that is, the cases of calculation were at small and large eccentricities. The concrete of the test samples was designed in class B30-B35. Metal frame consisted of 4 rods 12ØA500, transverse clamps were installed with 180 mm step and were made of B500 rebar. Reinforcement meshes were installed at the supporting areas to prevent crumpling. The samples analyzed in this article are part of a scientific study to determine the effectiveness of using composite materials to reinforce eccentrically compressed flexible reinforced concrete structures [16] and to find the most effective options for reinforcement. When assigning the experimental program and determining the most effective schemes of reinforcement of eccentrically compressed reinforced concrete struts using composite materials, non-typical options of reinforcement were considered. However, a comparative analysis made it possible to equate such struts to the counterparts described in the Set of rules SP 164.1325800.2014. In the paper [16] there is an evidence, which allows to state, that for the short strut VKU-X3 LP and for the flexible strut of the code BGU-X3 LP , VGU-X3 LP it is
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Fig. 1 Design procedure for composites arranged in transverse direction
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Creation of the Strength Design Methodology …
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possible to accept clamps, with a clearance of 140 mm, and for the flexible strut VGU-X4 LP, BGU-X4 LP -to the hood. The provisions of regulatory calculation methods (SP 164.1325800.2014) for the strength of reinforced concrete compressed elements show that it is impossible to simultaneously consider the effect of longitudinal and transverse reinforcement, that does not allow to fully take into account the full effectiveness of the composite material. The creation of a calculation procedure for combined longitudinal and transverse reinforcement of compressed reinforced concrete structures will be based on the results of calculations carried out according to two different methods. The first calculation method is as per clause 6.2.14 (SP 164.1325800.2014), takes into account only the longitudinal composite reinforcement. The block diagram is shown in Fig. 1 and the calculation results are shown in Table 1. The second calculation method is based on the provisions described in paragraphs 6.2.15–6.2.16 of SP 164.1325800.20140 and is presented in (Fig. 2) where the influence of composite materials in increasing the strength of reinforced concrete struts located in the transverse direction only is considered. The results of the calculations are given in Table 2. Table 1 Comparison of experimental and theoretical strength values of reinforced struts, out of transverse reinforcement effect № Sample
code
Calculation parameters
Experimental results
Calculation results
λh
e0, cm Sw , cm
Rb,n Ma E b , Ma N ex p KH N theor KH
N theor N ex p
3
4
5
6
7
8
12
13
ex p
1
2
1
BKU-X1 LP 10
2,2
14
29,5
36,080
790
800
1,01
2
VKU-X1 LP 10
4,2
14
29,6
36,120
530
552
1,04
3
VKU-X3 LP 10
4,2
14
36,4
38,120
608
621
1,02 2 = 0, 0023
4
BGU-X4 LP 20
2,4
0
36,7
38,220
714,5
549
5
BGU-X3 LP 20
2,4
14
28,5
35,730
510
509
0,77 1,00
6
VGU-X3 LP 20
4,4
14
33,1
37,160
503,5
376
0,75
7
VGU-X4 LP 20
4,4
0
36,7
38,220
504,5
390
0,77 2 = 0, 1693
Note Code of the test samples: The first letter of the code, “B” refers to samples tested at e0 = 2 cm, V to samples tested at e0 = 4 cm. The second letter indicates the flexibility of the design: “K”—λh = 10, “G”—λh = 20. The third letter “U” indicates that the struts are reinforced with composite materials. The fourth letter, “X”, indicates the presence of transverse reinforcement. The indices to the letter “X”, indicate the variant of transverse reinforcement: (1)—clamps with a width of Wf = 50 mm, with a clearance of Sf = 140 mm; (2)—also with a pitch of 95 mm; (3)—clamps of the type (1) but with a wide clamp with a width of 250 mm in the middle; (5)—hoods
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Fig. 2 Design procedure for composites arranged in longitudinal direction
3 Research Results According to the results of calculations in Table 2 the following can be concluded: there is an average underestimation of theoretical strength values for short struts by 17–13% in comparison with the experimental ones. The underestimation of theoretical strength for the majority of struts exceeds 30% for flexible samples. The sum of standard deviations has been used as the main indicator of efficiency of the developed suggestions for improvement of the calculation method. The sum of standard deviations has been determined according to the formula
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Table 2 Comparison of experimental and theoretical strength values of reinforced struts, out of longitudinal reinforcement effect № Sample code
Calculation parameters
Experimental results
Calculation results
λh
e0, cm Sw , cm
Rb,n M Pa E b ,M Pa N ex p K H N theor K H
N theor N ex p
3
4
5
6
7
8
9
10
ex p
1
2
1
BKU-X1 LP 10
2,2
14
29,5
36,080
790
687
0,87
2
VKU-X1 LP 10
4,2
14
29,6
36,120
530
442
0,83
3
VKU-X3 LP 10
4,2
14
36,4
38,120
608
502
0,83 2 = 0, 0733
4
BGU-X4 LP 20
2,4
0
36,7
38,220
714,5
510
0,71
5
BGU-X3 LP 20
2,4
14
28,5
35,730
510
444
0,87
6
VGU-X3 LP 20
4,4
14
33,1
37,160
503,5
311
0,62
7
VGU-X4 LP 20
4,4
0
36,7
38,220
504,5
332
0,66 2 = 0, 362
2 =
n i=1
exp 2 1 − Nitheor /Ni
4 Discussion In analyzing the obtained results (see Tables 1 and 2), we can say the following: 1. The convergence of the theoretical calculation results with the experimental ones is better for all samples calculated with the algorithm (Fig. 2), that is, without taking into account the transverse reinforcement which is logical, since all the samples are eccentrically compressed and have a sufficiently large flexibility. The reinforcement guidelines in the Set of rules recommend that longitudinal reinforcement should be used for such structures. 2. The theoretical strength of the flexible samples (lines 4–7) is underestimated by 23–25%, the BGU- X3 LP strut is the exception. Based on earlier studies [14, 16], where the effectiveness of transverse reinforcement of flexible reinforced concrete samples was determined, it can be clearly concluded that the increase in the experimental values of the strength depends on the influence of transverse reinforcement. 3. Theoretical values of strength for short struts (struts 1–3) differ from experimental values within 5%. It can be concluded that transverse reinforcement in this case is constructive and provides reliable anchoring of longitudinal reinforcement.
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4. The results of calculations for all experimental samples without taking into account the longitudinal reinforcement have shown a significant underestimation of theoretical strength in comparison with experimental values, and moreover the greater the flexibility and eccentricity of load application, the greater the underestimation of theoretical strength.
5 Conclusion As a basic calculation method for the design of reinforcement of flexible reinforced concrete and non-compressed structures, it is recommended to use the calculation algorithm without taking into account transverse reinforcement, however, it must be understood that for structures with flexibility λh = 20 and more, there will be an underestimation of the theoretical strength within 20% or more. Transverse reinforcement, which is a structural measure to ensure that the longitudinal reinforcement reliably attaches to the concrete, also has the effect of increasing the strength of the structure. This effect is not considered in the Set of rules SP 164.1325800.2014. Considering the above, it is determined that a further promising area of scientific research is the creation of a design calculation apparatus of combined reinforced eccentrically compressed structures in the longitudinal and transverse directions. It is necessary to combine two normative calculation algorithms and to take the methodology of reinforcement as a basis taking into account longitudinal composite reinforcement, and calculation formulas from the algorithm of calculation of transverse reinforcement will be introduced into it.
References 1. Rudenko VO, Sadykov TR (2021) History of development of reinforced concrete structures. In the collection: innovation development: technical and technological aspects. In: Collection of Articles of International Scientific-Practical Conference. Sterlitamak, pp 45–46 2. Tamrazyan AG (2014) Concrete and reinforced concrete: problems and prospects. Ind Civ Eng 7:51–54 3. Kolosova NB (2011) Problems of modern concrete and reinforced concrete. Eng Constr J 8(26):4 4. Savin AV, Lesovik VS, Alfimova NI (2013) To the problem of corrosion resistance of reinforced concrete. Bull Belgorod State Technol Univ Named After V. G. Shukhov 2:7–12 5. Shakir YA, Abd AYA (2019) Reinforcement of reinforced concrete slabs, the relevance of the problems. In the collection: problems and prospects in the international transfer of innovative technologies. In: Collection of Articles Based on the Results of the International Scientific and Practical Conference, pp 101–107 6. Rybin EN, Hambaryan SK (2019) Methods of strengthening of reinforced concrete structures. In the collection: Innovative methods of designing of building structures of buildings and constructions. In: Collection of Scientific Works of All-Russian Scientific and Practical Conference. Southwestern State University, pp 212–215
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7. Bedov AI, Gabitov AI (2021) Vosstanovlenie i usilenie osnovanij i stroitel’nyh konstrukcij ekspluatiruemyh zdanij i sooruzhenij. Problemy stroitel’nogo kompleksa Rossii: Materialy XXV Vserossijskoj nauchno-tekhnicheskoj konferencii, 31 Mar 2021, Ufimskij Gosudarstvennyj Neftyanoj Tekhnicheskij Universitet, Ufa, pp 3–6 8. Korsakov NV (2021) Analysis of damages and reinforcement types of compressed reinforced concrete structures. Competition of Research Papers of Students of Volgograd State Technical University. Volgograd, pp 468–469 9. Podnebesov PG (2012) Strengthening of concrete concrete columns with steel-fiber concrete. In the collection: urban planning, reconstruction and engineering support for sustainable development of cities of the Volga Region. In: Proceedings of the III All-Russian Scientific and Practical Conference, pp 93–98 10. Paula RF, Silva MG, Vinagre J (2006) Influence of cross section geometry on the confinement of reinforced concrete columns with CFRP composites. In: International Symposium Polymers in Concrete (ISPIC 2006) 11. Chikh N, Gahmous M, Benzaid R (2012) Structural performance of high strength concrete columns confined with CFRP sheets. In: Proceedings of the World Congress on Engineering, vol 3, 4–6 July 2012, London, U. K. 12. Sharipov SM, Bekpergenova ZB (2009) Sozdanie kompozicionnyh materialov iz othodov proizvodstva dlya vosstanovleniya i usileniya stroitel’nyh konstrukcij. Vestnik KGPI 3:81–83 13. Gavrilova EO (2021) Reinforcement of bendable elements by composite materials. Acad Public 8(2):111–119 14. Kostenko AN (2010) Strength and deformability of centrally and extra-centrally compressed brick and reinforced concrete columns reinforced with coal and fiberglass. In: Proceedings of the Science, Moscow, p 26 15. Merkulov SI, Esipov SM (2018) Increasing the bearing capacity of reinforced concrete bending structures by reinforcing with composite external reinforcement. BST Bull Constr Eng 2(1002):56–57 16. Polskoy P, Georgiev S, Muradyan V, Shilov A (2018) The deformability of short pillars in various loading options and external composite reinforcement. In: Web of Conferences, p 02026 17. Popov AY, Gosina KK, Petrov IV et al (2015) Classification, composition, advantages and disadvantages of multicomponent composite materials. Omsk Sci Messenger 143(3):42–45 18. Bozhenko AM, Shevtsova MA (2021) Advantages and disadvantages of composite materials using in building. Perspect Sci 146(11):60–62 19. Grakhov VP, Popov VS, Shchuklina AY (2015) Analysis and advantages of non-metallic reinforcement from composite materials in construction. In the collection: Actual questions of theory and practice of composite reinforcement application in construction. Responsible for the collection, pp 42–51 20. Georgiev S, Mailyan D, Blyagoz A: Proposals for determining the relative deformations design value of εb3 concrete in volumetric deformation conditions, pp 155–162. scientific.net/MSF.1043. pp 155–162 21. Mukhamediev TA (2013) Design of reinforcement of reinforced concrete structures by composite materials. Concr Reinf Concr 3:6–8
Optimization of Cargo Transportation Resource Allocation Based on Lean Manufacturing Elena Pinevich , Aleksandr Volokhov , Karina Mekhantseva , Vladimir Zinovev , and Diana Ganzhenko
Abstract The article presents an optimization problem that allows you to implement the principles of lean production, as well as to minimize such types of losses as “waiting” and “excessive processing”. The goal is to find the minimum number of vehicles and human resources required for transportation. Guided by the main provisions of lean manufacturing and transport logistics, the task of developing an optimal schedule for the operation of land vehicles and optimizing the number of labor resources was implemented on the example of the work of a conditional motor transport enterprise. We present an algorithm that allows us to solve this problem using a class of interval graphs. A mathematical model of cargo transportation is constructed using an algorithm for coloring the interval graph with a sequential distribution and uniform loading of colors. In the course of solving this problem, software was created that implements the operation of such an algorithm. This software tool allows you to perform calculations to find the optimal amount of resources under given initial conditions, with a uniform system load, provided that the colors of the interval graph are consistently distributed. The presented results can be implemented in the management systems of organizations-cargo carriers, logistics companies, freight aggregators. Keywords Resources · Graphs · Transportation · Transport · Models · Optimization · Intervals · Colors · Operations · Average daily cargo turnover · Productivity · Lean manufacturing
E. Pinevich (B) · D. Ganzhenko Don State Technical University, 1, Gagarin Square, Rostov-on-Don 344002, Russia e-mail: [email protected] A. Volokhov · V. Zinovev Rostov State Transport University, 2, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Square, Rostov-on-Don 344038, Russia K. Mekhantseva Rostov State University of Economics, 69, B. Sadovaya Street, Rostov-on-Don 344006, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_170
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1 Introduction The year that passed in the context of the pandemic required all enterprises and organizations to concentrate their forces in the restructuring of management systems, while management tools came to the fore due to the lack of a correct economic theory in this situation. Logistics became the most popular tool, and transport became the most needy industry. The digitalization of transport flows over the past decade has provided new opportunities for the development of both passenger and freight transport. The emergence and development of aggregators in passenger transport (Uber, Yandex taxi, Citymobil, etc.) has reshaped the market to a greater extent in favor of the end user. The situation is more complicated in the freight transport market (GroozGo, Transporeon, Loginet, Fura, ATI.su and other Internet solutions) due to the lack of common standards for all transportation in the Russian market. At the present stage of cargo transportation development, the best result so far is shown by the introduction of intelligent transport management systems (TMS) and warehouse management systems (WMS) by large cargo carriers. Both types of systems are industrial in their principles of construction and operation and include the principles of lean production. The continued integration of systems in cargo transportation based on the process approach will help to identify various types of losses of an intersystem nature and further standardize the services of the cargo transportation process as a whole. One of the ways to reduce losses will be the structuring and standardization of the truck fleet to reduce the largest material losses during its maintenance [1–3]. It is natural that over time there are more and more new branches of science and production, related tasks, as well as optimal ways to solve them. As a result, the scope of application of various scientific sections, including graph theory, is expanding. The graph coloring problem finds application not only in theoretical problems, but also in many practice-oriented projects. Thus, the problem of optimizing the “personvehicle” system, aimed at increasing the profitability of cargo transportation, can be reduced to the problem of graph coloring.
2 Methods In this paper, is presented and programmatically implemented an algorithm for the interval graph coloring method with a consistent, uniform distribution of colors. Using vertex coloring, you can formulate many planning problems. In the simplest formulation of this problem, there is a system “human resources—vehicles”, the work of which must be optimally planned, distributed over time periods. The distribution order should be constructed in such a way that there are no overlaps: two incompatible works cannot be performed simultaneously, that is, they will be considered conflicting. The graph corresponding to the model for each of the works of this
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system has its own vertex. An edge of such a graph displays conflicting vertices. The minimum number of objects that make up such a system, required to perform all the work without causing conflicts, is taken as the chromatic number of the constructed graph. For each individual problem, the graph structure may be different. So, for example, in the case of the problem of the distribution of vehicles for the transport of goods, the resulting conflict graph can be defined as an interval graph. In this study, we will consider an algorithm for coloring such graphs with a uniform sequential distribution of colors. Consider the problem of effective operation of the system “human resourcesvehicle”. Such a system is represented in the form of a graph, its vertices are labor resources that are interconnected with vehicles. The set of such vertices is defined as the set of intervals: Where xi is the start time of the work, and yi is the end time. The intervals v1 , … , vk are written out in non-decreasing order and numbered so that x1 ≤ … ≤ xk . The interval numbers define the numerical sequence P = (i1 , … , i2k ), which consists of the numbers 1, 2, … , k, and each of the numbers occurs in this sequence exactly 2 times, that is, the set of 2 k numbers xi , yi , where 1 ≤ i, j ≤ k. Thus, the set of intervals V1 , … , Vk corresponds to the graph G = (V, E), whose vertices display the intervals Vi , and if and only if Vi ∩ Vj = ∅. Let the optimal number of resources required for the full functioning of the enterprise be the number Copt . Let ui be the order of work performed by the i-th unit. Then the subgraph G generated by the set Ui does not have any edges, as a result of which the partition u1 , … , uk will be the correct coloring of the set of vertices V, and the minimal one, since is the chromatic number of the graph G. The sequence P in an ordered form is represented as follows: P = (1, 2, . . . , Copt1 , i optk1 , . . . , i optki , . . . , Copt1 + 1, Copt1 + 2, . . . , Copt2 , . . . Let’s introduce the notation {1, 2, . . . , Copt1 } = I1 , {Copt1 + 1, Copt1 + 2, . . . , Copt2 } = I2 {Copt2 + 1, Copt2 + 2, ..., Copt3 } = I3 , {Copt(n−1) + 1, Copt(n−1) +2, ..., Coptn } = In n = 1, k, i optk1 , ..., i optki = Ji , i = 1, k, Then inserts in the natural series 1, 2, …, k of the sets Ji will be selected by the rule J1 ⊂ I1 , Jn ⊂
n i=1
Ii \
n−1
Ji , n = 2, k.
i=1
Let’s define the list structure {Ci }, i = 1, k. In it there are C1 = I1 , Ci+1 = Ci ∪ Ii+1 \Ji , i = 1, k. The set Ci generates a complete subgraph closed by inclusion
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(clique). Using the clique system C1 , …, Ck a coloring of the graph G(V, E) is constructed, and the solution will not be the only one. To obtain the minimum vertex coloring, the following steps are performed: 1. Select the maximum click. The number of elements in it will determine the number of colors Copt ; 2. The vertices are sequentially assigned the colors 1, 2, …, Copt ., and the vertices of the clique Cn±1 , that are included in the intersection C ∩ Cn±1 get the colors by clicking Cn ; 3. After getting a certain vertex of the color Copt , the subsequent vertices get their coloring according to step 2, with a uniform distribution over different clicks of the same color.
3 Results The implementation of the algorithm at the software level is as follows: – – – –
to define a set of input data; to define the main data storage structures and indicator flags; to describe the functions that ensure the execution of the algorithm steps; to describe the main function that will run the additional ones and output the results of their work
The input data will be the number of specified intervals, a list of adjacent intervals, and the coordinates of intervals relative to some axis (Fig. 1) [4–6]. To store the data, you need: – array with the original init_sequence sequence; – dictionaries nat_nat and int_num for elements of a natural number series and elements of inserts in this series, respectively; – the keys of the first dictionary elements from the point above are markI and markJ, respectively; – dictionary for d_cliques clicks; – array of max_colors colors; – dictionary of colored vertices dict_colors intervals = 6 adjacency_list = {'1': [2], '2': [1, 3, 4], '3': [2, 4], '4': [3, 5], '5': [4, 6], '6': [5]} interval_boundaries=np.array([[0,2],[1,5],[3,6],[4,8],[7,10],[9,11]])
Fig. 1 Input data
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def init_list(intervals, sequence): for coordinate in range(2*intervals): for row in range(intervals): for column in range(2): if coordinate==interval_boundaries[row][column]: init_sequence.append(row+1) init_sequence.append(0)
Fig. 2 Getting the original numeric sequence
Functions that directly implement the operation of the algorithm: – a function that, based on the input data, makes up the original numerical sequence (Fig. 2); – the function of splitting the original numerical sequence into elements of a natural number series and elements of inserts in this series (Fig. 3): – a function that processes elements of a natural number series (Fig. 4): – a function that processes elements of inserts in a natural number series (Fig. 5): def cutting(n_array,mark1,mark2): for element in range(len(n_array)-1): if n_array[element+1]!=0: if n_array[element+1]!=n_array[element]+1: if n_array[element+1]maxC: maxC=len(dictionary[setC]) return maxC
Fig. 9 Finding the number of colors for coloring pages
– functions that define the construction of clicks (Figs. 6, 7 and 8): – maximum click detection function (Fig. 9): – coloring function (Fig. 10): def coloring(dictionary1, mas_colors,dictionary2,intervals): maxC=max_clique(dictionary1)[0] mas_colors=[i for i in range(1,maxC+1)] for vertex in range(1,intervals+1): dictionary2[vertex]=None color=mas_colors[0] for setC in range(1, len(dictionary1)+1): for value in dictionary1[setC]: if dictionary2[value]==None: dictionary2[value]=color color+=1 if color>mas_colors[-1]: color=mas_colors[0]
Fig. 10 Vertex coloring
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Fig. 11 Graphical representation
The main function will include calling the functions described above, as well as displaying the intermediate and final results of the algorithm. After that, a numerical sequence is calculated, which will include the elements of the natural number series I and inserts J1 , …, J4 into this series (Fig. 11). Next, the click system C1 , …, Ck is defined. The elements of the first click C1 will match the elements of I1 the subsequent ones will be determined by the rule Ci = Ci−1 ∪ Ii \Ji−1 (Fig. 12). The click containing the largest number of elements will be considered the maximum (in the case of determining several such clicks, the first of them is taken as the maximum). It also defines the chromatic number of the graph (Fig. 13). The final result of the program is shown in the Fig. 14.
C C C C
1 2 3 4
– – – –
[1, [2, [4, [5,
2] 3, 4] 5] 6]
Fig. 12 Received clicks
Max. clique: 2 Number of colors to paints: 3 Fig. 13 Maximum click and the number of elements in it
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Colored vertexes: Vertex 1 is colored Vertex 2 is colored Vertex 3 is colored Vertex 4 is colored Vertex 5 is colored Vertex 6 is colored
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in in in in in in
color color color color color color
1 2 3 1 1 1
Fig. 14 Colored vertexes
4 Conclusion The software tool presented in this paper allows the user to enter the initial data in the form of the number of system elements, types and time intervals of employment, to obtain the optimal possible distribution. The sequential assignment of colors makes it possible to set simple cycles for determining the workload of the elements of the “person-vehicle” system. The option to evenly distribute colors in the graph helps to increase the performance of lean production. It is aimed at distributing the types of work on the elements of the system with a uniform sequential loading of these elements. This software tool can be used rationally not only in transportation management organizations, but also can be used in the educational process as a testing tool for the correctness of the construction of mathematical models of the operation of ground vehicles [7–10].
5 Discussion The presented results can be implemented in the management systems of organizations-cargo carriers, logistics companies, freight aggregators. At the same time, it is possible to build a value stream both at the enterprise level and between them, which will reduce such loss classes as “waiting”, “excessive processing”. It is obvious that the solution of such problems can cover the growing market demand for mathematical optimization of business processes and value streams. The use of this software tool in the educational process increases the cognitive abilities of students and positively affects the level of training of specialists in general, developing the skills of building mathematical models for solving practical problems [11–14].
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References 1. Volokhov A, Fisenko K (2020) Experimental research of the directional stability characteristics of a passenger car when moving around. In: IOP Conference Series: Materials Science and Engineering, vol 971, p 052074. https://doi.org/10.1088/1757-899X/971/5/052074 2. Shapovalov VV, Kharlamov PV, Gorin SL, Mischinenko VB, Kornienko RA, Zinovev VE (2020) Optimization of dynamically loaded nonlinear technical systems. In: 16 International Scientific-Technical Conference Dynamics of Technical Systems, Rostov-on-Don, DSTU, pp 321–327 3. Lyashenko YM, Revyakina EA, Shurygin DN (2017) Application of the laws of mechanics of granulated solidsin studies to Llader bucket interaction with bulk. Mater Stack Procedia Eng 206:1388–1394 4. Cherckesova L, Safaryan O, Trubchik I, Yukhnov V, Yengibaryan I (2020) Modification and optimization of miller-rabin simplicity test algorithm implemented by parallel computation. In: IOP Conference Series: Materials Science and Engineering, vol 1001, no 1, p 012064 5. Razumov PV, Safaryan OA, Smirnov IA, Cherckesova LV, Osikov SA, Korochentsev D (2020) Developing of algorithm of HTTP FLOOD DDoS protection. In: ICCAIS–3rd International Conference on Computer Applications and Information Security, p 9096870 6. Pinevich E, Safaryan O (2020) Methods for improving the educational potential of students. In: E3S Web of Conferences, vol 210, p 18034 7. Duane BT, Satre ME (2014) Utilizing constructivism learning theory in collaborative testing as a creative strategy to promote essential nursing skills. Nurse Educ Today 34(1):31–34 8. Loureiro A, Bettencourt T (2014) The use of virtual environments as an extended classroom–a case study with adult learners in tertiary education. Procedia Technol 13:97–106. https://doi. org/10.1016/j.protcy.2014.02.013 9. Gallagher JR (2020) The ethics of writing for algorithmic audiences. Futur Gener Comput Syst 57:102583 10. Meskhi B, Ponomareva S, Ugnich E (2019) E-learning in higher inclusive education: needs, opportunities and limitations. Int J Educ Manag 33(3):424–437 11. Kalmykova OM, Ivushkina EB (2017) The idea of technology in scientific knowledge. Contrib Econ 9783319552569:351–358 12. Pishchik VI, Molokhina GA, Petrenko EA, Milova YV (2019) Features of mental activity of students–esport players. Int J Cognit Res Sci Eng Educ 7(2):67–76 13. Myzdrikov NY, Semeonov IY, Yukhnov VI, Safaryan OA, Cherckesova LV, Porksheyan VM (2019) Modification and optimization of solovey-strassen’s fast exponentiation probablistic test binary algorithm. In: Proceedings of 2019 IEEE East-West Design & Test Symposium (EWDTS), Batumi, Georgia, 13–16 September, pp. 392–394. 14. Zaitseva NA et al (2014) Elaboration of the methodology for assessing the development of managerial competences in university students taught with the use of case-technologies. Eurasia J Math Sci Technol Educ 13(11):7339–7351
Automation of the Transfer Department of a Premier League Football Club Tatiana Grober
and Oleg Grober
Abstract Any sports organization today operates in a competitive environment, which makes it necessary to restructure its management system, develop ways to improve the efficiency of its work. This article describes the developed user application designed to automate the work of the transfer department of a football club for the selection of players. The application allows you to import statistics on players from sports sites, such as Transfermarkt, into an MS Excel workbook, then the user has the opportunity to organize an automated sorting according to the following criteria: playing role, nationality, cost, xG indicator, age, height, impact leg. There are quite a lot of options for selecting players, the main feature of filtering is the selection by the indicator of “expected goals” xG. All the selected data is uploaded as a separate aggregate and the sum of the transfer cost of all the “newcomers” of the club is displayed. Since the application was developed for a poor club, a team organization model was created that takes into account resource constraints. As a criterion for the effectiveness of the model, the increase in the transfer cost of the “newcomers” and the team as a whole at the end of the playing season is considered. The application was developed using the Python programming languages version 3.9 with the connection of specialized libraries and Visual Basic for Application. Automation of the transfer department of the football club will simplify the process of finding and selecting players, reduce expenses and increase the economic efficiency of the club. Keywords Custom application · Databases · Organization model · Criterion for the effectiveness of the model
1 Introduction Football is one of the most popular and spectacular sports games. The popularity of football in the world allows us to call it “the religion of millions of people”, and its TV audience is truly huge. This focus on football is the basis that football clubs are T. Grober (B) · O. Grober Don State Technical University, 1, Gagarin Square, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_171
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trying to make the management system more efficient. Club football management is interested in the optimal use of available resources. In connection with the rapidly developing trend of informatization of society, as well as with the increasing share of the population with access to the Internet, the need for affordable information products in the sports field is increasing. A successful club needs a structure that makes it possible to effectively use the knowledge and experience of specialists of different profiles. Recently, among the Premier League clubs, transfer departments have begun to stand out, dealing with the selection of new promising players. Figure 1 shows the standard structure of a Premier League football club. There was a time when in a year 2–3 thousand players were offered to the club for viewing, or coaches-selectors traveled around the world in search of talent. Naturally, this is not economically profitable for the club. Now the situation has changed. A new term—scout-has become popular. This is the one, who finds the “newcomers” for the club. And now it is likely to be a person with a laptop, collecting and analyzing information on the Internet. The fact is that there is a recognized authority in the field of player databases around the world—the German website Transfermarkt. Transfermarkt is the largest football database with profiles for 800 thousand football players, containing lists of players from many world championships. Every month, the site gets a billion views, and it has versions in different languages, including Russian. It is used by fans, journalists, scouts, football players and even club owners. As for the Russian championship, there are also Russian websites that contain databases of players directly for it.
Fig. 1 Structure of a football club
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For the poor clubs of the Russian Premier League, the strategy is quite typical: find an inexpensive talented football player, then sell him dearly. But the selection of players is mainly due to the connections of the transfer department team with agents around the world, usually without the use of information technology. Many scientific papers have been devoted to the creation and use of databases, including the vast majority of them in the field of medicine [1, 2]. There are far fewer publications that link databases and sports [3–5]. To date, there are many publications devoted to modeling in such areas as economics [6, 7], agriculture [8], construction [9], hydrology [10, 11], information technology[12] and many others. The diversity of systems, manifested in the diversity of their structural and functional organization, determines the use of many different models and modeling methods [13–15]. Successful clubs of the English Premier League have shown that the use of various mathematical models of team formation, the analysis of statistical data on a number of indicators of the effectiveness of players—this is very useful for the club and brings great profit. The use of digital technologies in the economy and sports is very relevant today. In the Russian championship, the need for rational use of the budgets of Premier League football clubs is long overdue. Automating the work of the transfer department through the use of modern information technologies will allow you to correctly spend the club’s funds when buying players and increase its profit in the future.
2 Materials and Methods The purpose of this study is to automate the work of the transfer department of a football club for the selection of players. To do this, you need to solve the following tasks: 1. Create a custom application that allows you to take information from sites that have databases of players. 2. According to the selected criteria, issue ranked lists of players of a certain role, cost, nationality, xG indicator, physical parameters. 3. Create a team organization model (especially considering new players who joined the team during the transfer «window»), taking into account the resource constraints of a poor Premier League team. Python version 3.9 was used as the programming language for developing the application with the connection of the libraries pip install pandas, pip install openpyxl xlsxwriter xlrd, as well as the object-oriented programming language Visual Basicfor Applications.
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3 Results The work of the transfer department of a football club, first of all, is to find and select new players. The task was to develop a user application that could access sports sites containing information about players in the form of databases. The data is uploaded from the site to the MS Excel workbook that the user application is linked to. This application contains controls that allow you to implement criteria for selecting data from the database, such as playing role, cost, citizenship, xG, age, height, impact leg. For example, at first, sorting is performed by playing role, then by country (the player’s nationality), then by his transfer cost, then by the xG indicator. The results of sorting and filtering data should be output to the active MS Excel workbook.Moreover, the sorting of the database can contain different combinations of criteria for selecting players. For example, first we select players by country (the player’s nationality), then by role, then by xG, then by physical parameters. There are quite a lot of options for selecting players, the main feature of filtering is the selection by the “expected goals” indicator xG, which means how many goals a player can potentially score in the game. He may score a few goals at some point, but if his xG score is large enough, it means that just until the player is “unlucky” it is worth waiting a little—then there will definitely be goals. If you look at the goal as a random variable, then the indicator xG is a kind of analogue of its mathematical expectation. Using the achievements of modern science is the way to the success of the entire team, as recent research shows. The considered sequence of actions is repeated for each game role. After that, the specialists of the transfer department leave to see for themselves the merits of the players offered by the program. This is how the “newcomers” of the team are assembled (Fig. 2). Figure 3 shows an example of sorting by nationality. Figure 4 shows the result of sorting the database by nationality.
Fig. 2 User application before sorting
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Fig. 3 Sorting by nationality
Fig. 4 The result of sorting the database by country
We organize a sequential sorting: by role, citizenship, cost, and indicator xG, the result of which is shown in Fig. 5. The selected data is uploaded to the active sheet of the MS Excel workbook, and the transfer cost of the «new part» of the team is automatically calculated. Consider creating a team organization model (especially considering new players who joined the team during the transfer «window») that takes into account the
Fig. 5 An example of how sequential sorting works
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resource constraints of a poor Premier League team. This model must meet all the requirements for the organization of a game football team. We consider the time period of the so-called transfer «window», when the annual championship is already completed (or the middle of the championship). At this time, football clubs sell and buy players, and players, personal contracts with clubs are terminated and concluded. If a player does not have a valid contract with the club, he is considered a «free agent», and the club is only spent on a personal contract with the player. The fact is that not always the high transfer price of a player means that he will successfully play at a new club. An example of this is the Spanish “Barcelona” with a negative annual balance. And there are quite a lot of such examples. There are a lot of factors that affect the fact that a player will be effective in a new team, which can be considered as risks. This includes mutual understanding with the coach, the climate in the team, possible injuries, etc. Therefore, in this model, when selecting new players, a bet is made on the xG indicator. Let’s assume that the coaching staff is interested in acquiring 1–2 goalkeepers, 3–4 defenders, 3–4 midfielders and 2 strikers. This information is brought to the transfer department and work begins on the selection of players. Let’s build a model that describes the formation of the team before the new game season. As an objective function, consider the initial transfer cost of the team F1 – the cost of all players, according to the estimates of the Transfermarkt website. xi f i + β + yj gj + γ + zk hk + δ + m l nl F1 = α + i
j
k
l
(1)
where in the formula (1) α,β,γ,δ—the cost of the players of each role, respectively, remaining in the team, xi —the number of goalkeepers, fi —the cost of the i-th goalkeeper i = 1,2, yj —the number of defenders, gj —the cost of the j-th defender j = 3,4, zk —the number of midfielders, hk —the cost of the k-th midfielder k = 3,4, ml —the number of strikers, nl —the cost of the l-th striker l = 1,2 (the cost of players is given in euros). Restrictions the cost of players is determined by the financial capabilities of the club. It should be noted that the variables in the model can be considered as random variables. As a criterion for the effectiveness of the model, the increase in the transfer cost of the «newcomers» and the team as a whole is considered. At the end of the playing season, according to the estimates of the cost of players on the Transfermarkt website, the transfer cost of the team is calculated (denote as F2 ), which allows you to evaluate the effectiveness of the transfer department. If F2 > F1 , then the transfer department worked effectively.
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Fig. 6 Example of starting the model
Fig. 7 Example of another model launch
Figures 6 and 7 show examples of running a matchmaking model.
4 Conclusion Every football club is interested in finding a talented young player with a small transfer value, so that after a certain time period, they can sell him to their advantage. This is especially true for clubs in the Russian Premier League that have a small budget, such as FC Rostov or FC Ufa. But when buying a player, there are certain risks: the player will not be able to adapt to the team and will not show a good game, or he may get injured. It is not clear in advance whether the investment in the player will be justified or not. Therefore, it is quite difficult to build a strict analytical model of a football team, there are too many random factors that affect the development and implementation of a player’s talent. Creating a custom application that automates the work of the transfer department will reduce the number of its employees, and simplify the process of finding and selecting players. The ability to combine different criteria for selecting players allows you to take a fresh look at the composition of the team, revise the style of play, and vary the game patterns depending on the opponent. The use of such developments is becoming very popular in the world. Automation of player selection is a powerful tool for optimizing the club’s activities and increasing its economic efficiency.
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References 1. Foroutan A, Wishar D (2021) Food constituent and food metabolite databases comprehensive foodomics, pp 2–18. https://doi.org/10.1016/B978-0-08-100596-5.22772-8 2. Camargo M, González-Rojas ODM (2020) Smoking and obesity are associated with increased readmission after elective repair of small primary ventral hernias: a nationwide database study. Decis Supp Syst 134:113284. https://doi.org/10.1016/j.surg.2020.04.01 3. Sbrollini A, Morettini M, Maranesi E, Marcantoni I, Nasim A, Riccardi G and Burattin L (2019) Sport database: cardiorespiratory data acquired through wearable sensors while practicing sports. Data Brief 27:104793. https://doi.org/10.1016/j.dib.2019.104793 4. Xiao M, Donahue J, Safran M, Abram G (2021) Administrative databases used for sports medicine research demonstrate significant differences in underlying patient demographics and resulting surgical trends arthroscopy. J Arthrosc Related Surg 37(1):282–289. https://doi.org/ 10.1016/j.arthro.2020.09.013 5. Wasserstein D, Sheth U (2018) Administrative databases in sports medicine research. Clin Sports Med 37(3):483–494. https://doi.org/10.1016/j.csm.2018.03.002 6. Marek D, Doma´nski A, Doma´nska J, Czachórski T, Klamka J and Szyguła J (2021) Combined diffusion approximation–simulation model of AQM’stransient behavior. Comput Commun 166:40–48. https://doi.org/10.1016/j.comcom.2020.11.014 7. Sun Y, Liu H (2021) Crowd evacuation simulation method combining the density field and social force mode. Physica A Stat Mech Appl 566:125657. https://doi.org/10.1016/j.physa. 2020.125652 8. Grober T and Grober O (2020) Improving the efficiency of farm management using modern digital technologies. In: E3S web of conferences, vol 175, p 13003. https://doi.org/10.1051/ e3sconf/202017513003 9. Guan X, Burton H, Sabol T (2020) Python-based computational platform to automate seismic design, nonlinear structural model construction and analysis of steel moment resisting frames. Eng Struct 224:111199. https://doi.org/10.1016/j.engstruct.2020.111199 10. Wang H, Lu W, Li J (2020) Groundwater contaminant source characterization with simulation model parameter estimation utilizing a heuristic search strategy based on the stochasticsimulation statistic method. J Contaminant Hydrol 234:103681. https://doi.org/10.1016/j.jco nhyd.2020.103681 11. Saghi-Jadid M, Ketabchi H (2020) Result-based management approach for aquifer restoration problems using a combined numerical simulation – parallel evolutionary optimization model. J Hydrol 594:125709. https://doi.org/10.1016/j.jhydrol.2020.125709 12. Jin Z, Liang Z, Men W (2021) Mobile network traffic pattern classification with incomplete a priori information. Comput Commun 166:262–270. https://doi.org/10.1016/j.comcom.2020. 11.003 13. Liu Y, Guo X, We J, Zhang H (2021) Application of supercritical carbon dioxide jet: a parametric study using numerical simulation model. J Petrol Sci Eng 201:108422. https://doi.org/10.1016/ j.petrol.2021.108422 14. Grober T, Grober O, Savchenko O (2020) An innovative approach to the study of the model of a medical institution. In: E3S web of conferences, vol 210, p 11002. https://doi.org/10.1051/ e3sconf/202021011002 15. Peachey L (2021) Shaping clinical imagination as new graduate nurses in maternal-child simulation Nurse. Educ Today 97:104668. https://doi.org/10.1016/j.nedt.2020.104668
Influence of Technological Factors of Cement Mechanical Activation on the Strength Properties of Fine-Grained Concrete Sergei Stel’makh , Levon Mailyan , Alexey Beskopylny , Evgenii Shcherban’ , and Anatolii Shuiskii Abstract An urgent problem of current construction is the impossibility of using standard heavy concrete because of several factors: pouring densely reinforced structures, sealing joints, arranging waterproofing. At the same time, the Portland cement used plays an important role in the formation of the structure and properties of finegrained concrete. Thus, improving the operational properties of cement, including those that have been stored for a long time, is an urgent task for the construction industry. In the present study, the effectiveness of two different grinding devices (a material processing unit—UOM and a planetary ball mill—Activator-4 M) on the activity of stale cement was assessed. The greatest effect of increasing the specific surface area was obtained with mechanical activation in the CCM for 150 s—the specific surface area of the cement increased 1.4 times compared to the initial one. It is shown that an increase in the processing time of cement leads to an increase in the amount of fine cement fractions. The highest values of the strength characteristics were recorded in samples of fine-grained concrete made with the use of cement activated in the cement UOM for 120 s. Keywords Technological factors · Transport infrastructure · Portland cement · Concret · Mechanical activation · Cement activation · Strength properties
1 Introduction The impossibility of using standard heavyweight concrete is increasingly occurring on construction sites. This happens when pouring densely reinforced structures, sealing joints, arranging waterproofing. The solution to this problem can be the use of fine-grained concrete, however, its strength characteristics can be significantly lower than that of heavy concrete with the use of a large aggregate acting as a skeleton. S. Stel’makh · L. Mailyan · A. Beskopylny (B) · E. Shcherban’ · A. Shuiskii Don State Technical University, 1 Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_172
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Thus, fine-grained concrete, with all its technological advantages, has significant design and operational disadvantages [1–4]. And then the binder—Portland cement—comes to the fore in the formation of the structure and properties of fine-grained concrete. Portland cement is by far the most common and most commonly used hydraulic binder. However, this building material, despite all its advantages, also has a significant drawback—the loss of activity during long-term storage. Thus, improving the physical and mechanical characteristics of cement stored for a long time is an urgent task for the construction industry. Thus, the purpose of the study is to find a scientifically and technologically sound solution to two identified problems—increasing the activity of Portland cement and, as a result, the strength of fine-grained concrete. The object of research is fine-grained concrete, and the subject of research is the physics of the process and the increase in its strength characteristics due to the activation of the used Portland cement in various installations according to various technological methods. The main reasons for the decrease in the activity of cement during long-term storage are the aggregation of fine particles (the size of the cement particles approaches the size of the aggregate particles) and the carbonization of the cement surface due to the active absorption of moisture from the air first, and then carbon dioxide. The resulting crust reduces the rate of reaction of the particles of clinker minerals with water during mixing. Concrete made from such cement is characterized by many pores and high-water consumption, weak supersaturation of the solution, which ultimately leads to a decrease in its strength. Therefore, the task of restoring the activity of stale cement is reduced to removing the carbonate crust and dispersing the caked cement components [5–7]. To solve this problem, it is advisable to use mechanical activation technologies. Among all the variety of existing methods of grinding, the tendencies in the prevalence of impact action on the material, as one of the most effective methods of destruction of solid materials, are more and more clearly traced. The most important task of mechanochemistry is to elucidate the reasons due to which the activity of solids changes as a result of mechanical action [8, 9]. The mechanism of mechanical dispersion and activation in the process of impact action occurs according to several schemes. The first scheme is associated with the formation of radial annular cracks under the impact of impact. In the presence of surfactants, the cracks are covered with a monomolecular adsorption layer, which moves into the depth of the crack and exerts a wedging pressure (Rebinder effect— the second scheme), which increases with increasing pressure of the shock wave. The third dispersion scheme is carried out by breaking off the edges of the particles at the contact points. The fourth scheme is associated with the violation of interatomic and intermolecular bonds under the action of shear stresses. In practice, the dispersion process is carried out simultaneously according to all the presented schemes. It should be noted that shock-wave dispersion changes not only the surface, but also the
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structure and substructure of the particles [5–7]. All this leads to a significant increase in the activity of the dispersed material obtained at different types of grinding plants, which provides an additional resource for improving the physical and mechanical characteristics of building materials made from mechanically activated raw materials [10–14].
2 Materials and Methods As the main research material in this work, we used stale Portland cement that had been stored for one year CEM I 52.5 N produced by “NOVOROSCEMENT”. As a fine aggregate, quartz sand was used, according to the granulometric composition in accordance with GOST 8736, it belongs to the II class, to the category—fine. Sand fineness modulus Mf = 1.86, there are no grains over 5 mm, the content of dusty and clay particles is 0.86%. Mechanical activation of stale Portland cement was carried out on two types of installations: a material processing unit (UOM) and a planetary ball mill “Activator— 4 M”, manufactured by OOO “Plant of Chemical Engineering”, Novosibirsk. Externally, the apparatus is an inductor placed in a housing. The technical characteristics of the UOM are presented in Table 1. The mechanical activation process is carried out as follows. A chiller is fed into the unit’s cooling system, then power is applied and processing begins. Prior to this, ferromagnetic needles with a length of 20 ± 2 mm are preliminarily loaded into the working area, the diameter (d) of which is related to the length (l) in a ratio of 1:10 (l/d = 10). This ratio is optimal for the activation of cement in terms of impact efficiency and is selected empirically [12]. For a more accurate assessment of the effectiveness of grinding machines on the activity of stale cement, the granulometric composition of activated and non-activated cement, its specific surface area and strength characteristics of fine-grained concrete samples were investigated. Table 1 Technical characteristics of the UOM Indicator name
Index
Performance: – on water – for dry components
10 m3 /h 2 m3 /h
Power consumption
2 kw
Weight of ferromagnetic needles in the working chamber
550 ± 10 g
The ratio of the mass of the processed product to the mass of ferromagnetic needles
From 1:1.08 before 1:1.12
Dimensions
1600 × 600 × 1400 mm
Weight
0.250 t
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Investigations of the granulometric composition of mechanically activated cement powders were carried out by the method of laser granulometry on a Microsizer 201C installation. Microsizer 201C is a fully automated device designed for fast and accurate measurement of particle size distribution in the range of 0.2–600 µm. The PSKh-11 MSP device was used to control the specific surface area of the cement particles. The activation of cement in the UOM installation and the planetary ball mill was carried out for 0, 30, 60, 90 and 120 s. In total, 9 series of samples were made from fine-grained concrete (with the ratio C:S = 1:1.5 and W:C = 0.4). Each series includes 3 basic samples measuring 40 × 40 × 160 mm. Compression and flexural tensile tests were carried out in accordance with the requirements of GOST 10,180 “Concretes. Methods for strength determination using reference specimens”. The samples were hardened for 28 days in an aqueous medium [15–18].
3 Results and Discussion Cement grains range in size from 1 to 100 microns. Moreover, the smaller the size of the cement particles, the larger their specific surface area. Table 2 shows the results of a study of the specific surface area of cement mechanically activated on grinding machines of various types. From Table 2 it follows that storage of cement for 1 year leads to a decrease in the specific surface area. However, the use of any of the presented grinding machines allows you to increase the specific surface area of the stale cement. The greatest effect was obtained with mechanical activation in the UOM for 150 s—the specific surface of the cement increased by 2 times compared to the original cement. The results of studies of the granulometric composition of mechanically activated cement are shown in Figs. 1 and 2. Table 2 Values of the specific surface area of mechanically activated cement Number
Cement processing time, s
Specific surface of particles, cm2 /g UOM
Activator – 4 M
1
0
2432
2
30
2988
2902
3
60
3189
3055
4
90
3380
3172
5
120
3990
3530
6
150
4980
3887
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16 14 12 10 8 6 4 2 0
0, s 30, s 60, s 90, s 120, s 150, s 2.58 3.4 4.48 5.9 7.78 10.27 13.5 17.8 23.45 30.95 40.75 53.7 70.8 93.3 122.5 162 213.5 281.5
Fraction content, %
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Particle size, micron Fig. 1 Dependence of the distribution of cement particles by fractions when changing the processing time in the UOM
0, s 30, s 60, s 90, s 120, s 150, s
8 6 4 2 0 2.58 3.4 4.48 5.9 7.78 10.27 13.5 17.8 23.45 30.95 40.75 53.7 70.8 93.3 122.5 162 213.5 281.5
Fraction content, %
10
Particle size, micron Fig. 2 Dependence of the distribution of cement particles by fractions when changing the processing time in the Activator—4 M
Analysis of the data obtained shows that an increase in the processing time of cement leads to an increase in the amount of fine cement fractions. So, for untreated cement, the number of particles with a diameter of up to 20 microns is 30%, and for cement treated in the UOM for 150 s—78% and 61%—for cement activated in a planetary ball mill. Table 3 shows the average values of the strength characteristics of fine-grained concrete, determined from the test results of all samples of the series. The deviations of the values of the strength characteristics from the arithmetic mean did not exceed 6%. Studies of the compressive strength and flexural tensile strength showed that the maximum values are observed for samples of fine-grained concrete made with the use of cement, activated in the UOM of cement for 120 s. Compared with samples made on cement activated in a planetary ball mill, also for 120 s, the compressive strength is 11% higher, and the flexural tensile strength is 14% higher. When the cement is
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Table 3 Strength characteristics of fine-grained concrete made on activated Portland cement Number
Cement processing time, s
Compressive strength, MPa
Flexural tensile strength, MPa
UOM
Activator—4 M
UOM
Activator—4 M
1
0
44.3
2
30
49.6
46.6
5.9
5.2 5.5
3
60
53.7
50.8
6.4
6.1
4
90
56.8
51.0
6.8
6.2
5
120
59.7
53.1
7.2
6.2
6
150
54.5
57.5
6.5
6.9
activated in the UOM for 150 s, a drop in strength characteristics is observed. This can be explained by the fact that with an increase in the specific surface area of cement, the water demand also grows, so with an increase in the specific surface area above Ssp = 5000 cm2/g, the negative effect of an increase in water demand has a significant effect, which makes further cement grinding inappropriate. In the case of activation of cement for 150 s in a planetary ball mill, on the contrary, an intensive increase in strength characteristics is observed. The fact of higher quality activation in the UOM in comparison with the planetary ball mill can be explained by the differences in the mechanism of grinding and the induction of grinding bodies. In planetary mills, the rotation of the unbalanced shaft, and as a consequence of the mill housing, induces the grinding media to move under the action of inertial forces. Grinding bodies inside the mill body move along a complex trajectory, rub against the walls of the drum, collide with each other and with particles of the crushed material, while abrading and crushing them. In the UOM, when electricity is supplied, a powerful rotating electromagnetic field is created in the working space, which rotates the ferromagnetic elements placed in it. The latter become magnets and interact with the main field. As a result of the interaction, several effects are generated that affect the substance placed in the workspace. These effects can include—magnetostriction, mechanical striction, cavitation, electrolysis, torsion fields, acoustic waves. The specific power of these effects is very high. The consequence of this is a multiple increase in the rates of physicochemical processes in substances placed in the working space of the installation. The processes move from the diffusion to the kinetic level, and as a result of the opening of chemical radicals, the reaction rates increase hundreds of times. Linear Eqs. 1 and 2 show the relationship between the processing time in the UOM (t) and strength characteristics of fine-grained concrete (Rb , Rbtb ). Linear Eq. 3 show the relationship between the processing time in the Activator—4 M (t) and the strength characteristics of fine-grained concrete (Rb , Rbtb ). Rb = 0.0804 · t + 47.071 R 2 = 0.6818
(1)
Compressive strength, MPa
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y = 0.0804x + 47.071 R² = 0.6818
80 60 40 20 0 0
50 100 150 Processing time in the UOM, s
200
Flexural tensile strength, MPa
Fig. 3 Influence of cement processing time on compressive strength of fine-grained concrete specimens
y = 0.0103x + 5.5619 R² = 0.6737
8 6 4 2 0 0
50
100 150 Processing time in the UOM, s
200
Fig. 4 Effect of cement processing time in the UOM on flexural tensile strength of fine-grained concrete specimens
Rbtb = 0.0103 · t + 5.5619 R 2 = 0.6737
(2)
Rb = 0.0816 · t + 44.429 R 2 = 0.9561
(3)
Figures 3, 4, 5 and 6 show the correlation between grinding time and compressive strength and flexural tensile strength. The above values of the coefficients of determination show a good relationship between the regression curve and data points of processing time in grinding machines and test results.
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Compressive strength, MPa
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y = 0.0816x + 44.429 R² = 0.9561
80 60 40 20 0 0
50 100 150 Processing time in the Activator - 4M, s
200
Flexural tensile strength, MPa
Fig. 5 Effect of cement processing time in the UOM on compressive strength of fine-grained concrete specimens
y = 0.0102x + 5.2524 R² = 0.9146
8 6 4 2 0 0
50 100 150 Processing time in the Activator - 4M, s
200
Fig. 6 Effect of cement processing time in the Activator - 4M on flexural tensile strength of fine-grained concrete specimens
4 Conclusion Scientifically and technologically sound solutions have been found for two urgent problems of modern construction—increasing the activity of Portland cement and, as a result, the strength of fine-grained concrete. Evaluation of the effectiveness of two different grinding devices (material processing unit—UOM and planetary ball mill—Activator-4 M) on the activity of stale cement has been carried out. The greatest effect of increasing the specific surface area was obtained with mechanical activation in the UOM for 150 s—the specific surface area of the cement increased 1.4 times compared to the original cement. It is shown that an increase in the processing time of cement leads to an increase in the amount of fine cement fractions. The highest values of the strength characteristics were recorded for samples of fine-grained concrete made with the use of cement activated in the UOM for 120 s. The higher quality activation in the UOM in comparison with the planetary ball mill is explained by the differences in the grinding mechanism and the motivation of the grinding bodies.
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The studies performed have shown that the use of mechanical activation technologies allows one to regulate the surface characteristics of cement, its granulometric composition and, accordingly, the strength characteristics of concrete products, within a wide range. It is shown that the efficiency of grinding devices, which implement various mechanisms of dispersing action, is not the same. The highest indicators are characterized by concrete containing cement mechanically activated by means of the UOM installation. Thus, in order to solve the problem of increasing the activity of stale cement used in the technology of fine-grained high-functional concretes, it is advisable to use activation devices immediately before receiving the concrete mixture.
References 1. Zajceva L, Lucyk E, Latypova T, Latypov V, Fedorov P, Salamanova M (2021) Influence of the type of aggregate from industrial waste on corrosion resistance of modified fine-grained concrete. Buildings 11:352. https://doi.org/10.3390/buildings11080352 2. Okolnikova GE, Grishin GE, Kurbanmagomedov AK, Shchedrin NI (2019) Experimental study of the physical and mechanical properties of high-strength fine-grained modified “powdery” concrete. Syst Technol 31:41–46 3. Klyuev S, Klyuev A, Vatin N (2018) Fine-grained concrete with combined reinforcement by different types of fibers. In: MATEC web of conference, vol 245, p 03006. https://doi.org/10. 1051/matecconf/201824503006 4. Begich YE, Klyuev SV, Jos VA, Cherkashin AV (2020) Fine-grained concrete with various types of fibers. Maga Civil Eng 97(5):9702. https://doi.org/10.18720/MCE.97.2 5. Kopylov VE, Burenina ON (2019) Influence of oil sludge on properties of asphalt concretes used in regions of the far north. Mater Sci Forum 945:158–162. https://doi.org/10.4028/www. scientific.net/MSF.945.158 6. Lesovik VS, Ahmed AA, Fediuk RS, Kozlenko B, Mugahed Amran YH, Alaskhanov AK, Asaad MA, Murali G, Uvarov VA (2021) Performance investigation of demolition wastes-based concrete composites. Maga Civil Eng 106(6):10608. https://doi.org/10.34910/MCE.106.8 7. Andreeva AV, Burenina ON, Savvinova ME (2019) Activity improvement of sticky portland cements by methods of mechanical activation. Mater Sci Forum 945:3–8 8. Fedyuk RS, Mochalov AV, Lesovik VS (2018) Modern activation methods for binder and concrete mixtures (review). FSAEIHE Far East Federal Univ (FEFU) 4(37):85–99 9. Fediuk RS (2016) Mechanical activation of construction binder materials by various mills. In: IOP conference series: materials science and engineering, p 12019 10. Ibragimov RA, Korolev EV, Deberdeev TR, Leksin VV (2019) Efficient complex activation of portland cement through processing it in the vortex layer machine. Struct Concr 20(2):851–859 11. Ibragimov RA, Pimenov SI (2017) Features of the microstructure and phase composition of hardened cement paste prepared by mechano-chemical activation of the binder. ZKG Int 70(1–2):40–47 12. Shujskij AI, Torlina EA, Novozhilov AA, Javrujan KhS, Filonov IA (2015) Pat. № 2553893 RF, MPK, B01F 13/08., Rostov State University of Civil Engineering, N 2014119043/05, declared 12.05.2014, publ. 20.06.2015 13. Touil D, Belaadi S, Frances C (2006) Energy efficiency of cement finish grinding in a dry batch ball mill. Cem Conc Res 36(3):416–421 14. Celik B, Oner M, Can NM (2007) The influence of grinding technique on the liberation of clinker minerals and cement properties. Cem Conc Res 37(9):1334–1340
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15. Mailyan LR, Beskopylny AN, Meskhi B, Stel’makh SA, Shcherban EM, Ananova O (2021) Optimization of composition and technological factors for the lightweight fiber-reinforced concrete production on a combined aggregate with an increased coefficient of structural quality. Appl Sci 11:7284 16. Shuisky AI, Stelmakh SA, Shcherban EM, Torlina EA (2017) Recipe-technological aspects of improving the properties of non-autoclaved aerated concrete. In: MATEC web of conferences, vol 129, p 05011 17. Pavlov BN, Gol’tsov YuI, Mailyan LR, Shcherban’ EM, Stel’makh SA (2020) Relaxation processes during activation of cement mixing water. In: IOP conference series: materials science engineering, vol 896, p 012124 18. Mailyan LR, Beskopylny AN, Meskhi B, Shilov AV, Stel’makh SA, Shcherban EM, Smolyanichenko AS, El’shaeva D (2021) Improving the structural characteristics of heavy concrete by combined disperse reinforcement. Appl Sci 11:6031
On the Specifics of Investigation for the Dynamic Problems of Cracked Layer by the Gradient Elasticity Theory Oksana Yavruyan
and Khungianos Yavruyan
Abstract In the context of nonclassical theory of elasticity (gradient theory of elasticity (GTE), General theory of elasticity), the problem of antiplane oscillations of a homogeneous isotropic layer with delamination is investigated. The boundary integral equation (BIE) with respect to the strain component of the delamination boundary is formulated. The BIE in contrast to linear elasticity theory are represented by irregular integrals—Cauchy-type integral and cubic singularity integral. The obtained boundary integral equation investigated numerically on the basis of quadrature formulas for singular integrals and by applying the solution to Chebyshev polynomials. The corresponding gradient solution (the strain field) are regular. To investigate the stress state in the area of the crack tips, the General Lurie theory was used. The General theory is similar to the Ru-Aifantis theory, which involves splitting the original problem in the framework of GTE into two problems—constructing the corresponding classical solution and obtaining the gradient solution from the solution of the inhomogeneous second-order differential equation with constant coefficients. The problem is investigated numerically, crack swap functions depending on wave number and gradient parameter value are constructed, and the numerical results are compared with the elastic case. Keywords Layer · Steady-state oscillations · Antiplane · Delamination · Gradient elasticity theory · Transport infrastructure · Boundary integral equation · Deformation · Stresses
O. Yavruyan (B) Southern Mathematical Institute, VSC Russian Academy of Sciences, 53, Vatutin Street, Vladikavkaz 362025, Russia e-mail: [email protected] K. Yavruyan Don State Technical University, 1, Gagarin Square, Rostov-on-Don 344002, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_173
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1 Introduction The one of the effective solution schemes for dynamic problems of crack theory is the reduction to the systems of boundary integral equations (BIE). In the context of the linear theory of elasticity (LTE), the obtained BIEs are represented by singular integrals with respect to the derivative of the crack swap function, and the obtained solutions in the neighborhood of its tips are singular and do not correspond to the physical model of the problem. Therefore, the use of non-classical models of elasticity theory to clarify the behavior in the neighborhood of stress concentrators, such as the gradient theory of elasticity (GTE) is completely justified. Mathematical models of the gradient theory of elasticity were first proposed in the works of Mindlin R. D., Toupin R., Lurie M. V., Aifantis E. C.. The main difference between GTE and LTE is that the strain energy density representation also includes strain gradients with multipliers—parameters of the gradient model, which have length dimension, for example, in the case of cracks problems—relate to the crack length. Such a representation of the strain energy density allows one to take into account scale microeffects, to specify the behavior in the neighborhood of domains of interest—stress concentrators, however, along with the obvious advantages, it also leads to overcoming some difficulties associated with the study of differential operators of higher order than in LTE. One of the popular GTE models is the simplified model of Aifantis [1, 2], for isotropic medium the basic relations are written in the form W =
1 1 λεii ε j j + μεi j ε ji + λl 2 ε j j,i εkk,i + μl 2 ε jk,i ε jk,i , 2 2
(1)
m i jk = ∂ W/∂εi j,k = l 2 τi j,k σi j = τi j − m i jk,k = (1 − l 2 ∇ 2 )τi j Within the framework of the gradient theory of elasticity, various problems of crack theory have been investigated in the works [3–8].
2 Methods 2.1 Formulation of the Model Problem Let consider the model problem of antiplane oscillations of an isotropic layer with delamination on the lower boundary in the context of model (1). The lower boundary of the layer aligns with the axis x1 and is fixed except the delamination region x1 ∈ [−a, a]. The axis x3 is directed vertically along the layer thickness h. The
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oscillations of the layer are induced by a shear load applied to the point of the upper boundary of the layer σ23 = p0 δ(x1 − L)e−iωt . The crack banks do not interact during the oscillations. After separating the time multiplier, the equations of motion and boundary conditions will take the form 1 − l 2∇ 2 ∇ 2u + k2u = 0
(2)
x3 = h, σ23 = p0 δ(x1 − L) m 332 (x1 , 0) = 0 / [−a, a], x3 = 0, u = 0, x1 ∈ m 332 (x1 , 0) = 0
(3)
x3 = 0, x1 ∈ [−a, a], σ23 = 0 where a is the half-length of the crack, k is the wave number, and l is the gradient parameter. The wave propagation conditions at infinity are based on the principle of limiting damping. We obtained a GIE relating to the gradient of crack swap function which, in contrast to linear elasticity theory, is represented by a cubic singular integral of the form (N is a regular part of the GIE kernel, F1 is the right part of the GIE, which is defined by the applied load and boundary conditions) 1 π
1 −1
L1 2L 3 − 2 + a N (at, ax )
(t) dt = F1 (x1 ), x1 ∈ [−1, 1] 1 (t − x1 ) a (t − x1 )3 (4) L 1 = −1 +
l 2k2 , 2
L 3 = −l 2
The study of GIE is carried out using approximating Chebyshev’s polynomials, an asymptotic analysis of the problem for cracks of small relative length depending on the limit of the ratio l/a is carried out. The solution of (4) is obtained in the form of a Chebyshev polynomial expansion [3–9]
(t) =
M 1 − t2 An Un (t)
(5)
n=0
Note that, in contrast to the LTE, where the strein have singularities in the neighborhood of the crack tips, in the GTE the strein in the neighbor of the tips becomes regular (5). The stresses in the neighborhood of the tips in the case of LTE have −1/2 singularities of the form O( 1 − t 2 ), while in GTE the power of singularity
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Fig. 1 The real part of the shear stress in the area of the crack tip, p0 = 10, L = 0
−3/2 changes O( 1 − t 2 ) [9]. Thus, even using the Aifantis model of the GTE it is not possible to avoid singularities in the stress field. Figure 1 shows the real parts of the stress tensor components for various values of the gradient parameter l. In order to construct the regular solutions for the stress fields, it is necessary to use other models of nonclassical theory of elasticity. As such an approach, one may use the Ru-Aifantis method, which makes it possible to obtain the regular solutions or the General theory of Lurie S. A. [5–8], which makes it possible to investigate and correct the stress–strain behavior in stress concentrators and to define new strength criteria for bodies with cracks. The General theory is similar in many respects to the Ru-Aifantis theory and suggests using a singular solution of the classical elasticity theory in solving the Helmholtz equations whose right-hand side corresponds to the solution of the classical elasticity theory. Thus, it is possible to exclude singularity in the final solution and to obtain regular solutions, which subsequently make it possible to determine the final values of the maximum stresses active in the area of the crack tips, and thus to determine the stress concentration coefficient and evaluate the load capacity of the body with a crack according to the traditional criteria of strength.
2.2 The problem’s Investigation by the General Theory We investigate the considered dynamic problem of oscillations of a layer with the position of the General theory by using the classical solution of the corresponding problem obtained in [10], which satisfies the following boundary value problem σ2cj, j + k 2 u c = 0, j = 1, 3
(6)
On the Specifics of Investigation for the Dynamic Problems …
x3 = 0,
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u c = 0, x1 ∈ / [−a, a], ∂u c c σ23 = μ ∂ x3 = 0, x1 ∈ [−a, a]
c x3 = h, σ23 =μ
(7)
∂u c = p0 δ(x1 − L) ∂ x3
The displacement field is the sum of two fields u et , u cr —the reference field and the field determined by the occurrence of delamination, which is expressed through the crack swap function. u(x1 , x3 ) = u et (x1 , x3 ) + u cr (x1 , x3 ) u et (x1 , x3 ) =
1 2π
u cr (x1 , x3 ) =
1 2π
+∞
pshλx ˜ 3 −iαx 1 e dα λchλh
=
−∞
χch(λ(x ˜ 3 −h)) −iαx 1 e dα chλh σ
1 2π
σ
(8)
pshλx ˜ 3 −iαx 1 e dα λchλh
where the integration contour σ σ envelopes in someway the singularities of the subintegral function, which are found from equation ch(λh) = 0 (a finite number of real roots determines the number of propogate waves in the strip and a countable set of imaginary roots). The swap function is determined from the GIE a χ (ξ )K (x1 , ξ )dξ = f (x1 ),
x1 ∈ [−a, a]
(9)
−a
f (x1 ) =
p˜ eiα(L−x1 ) dα ch(λh)
σ
K (x1 , ξ ) = σ αn∗ = − k 2 −
=
p0 π h2
∞ n=0
(−1)n π (2 αn∗
∗
+ π n)e−iαn |L−x1 | , αn∗ = |αn |,
λsh(λh) iα(ξ −x1 ) e dα ch(λh) 1 π ( h2 2
+ π m)2
1/2
In the general case, the crack swap function is determined from the boundary integral equation, but if we consider a class of “small” cracks, i.e. asymptotic approach, it is possible to obtain a semi-analytical solution in the form of
0 (0) , x1 ∈ [−a, a] (a 2 − x12 )1/2 W0 , W0 = − f2π 0, x∈ / [−a, a] f 0 x1 2 (a − x12 )−1/2 , x1 ∈ / [−a, a] σ23c (x1 ) = μu c,x1 = 2π 0, x1 ∈ [−a, a]
u c (x1 ) =
(10)
According to the basic principle of the General solution of [5–8], the corrected regular solutions for x3 → 0 are determined from the Helmholtz equations with
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solutions (10) in the right-hand sides u − s 2 u = u c , |x1 | < a u (0) = 0, u(±a) = 0,
(11)
= σ23c , |x1 | > a σ23 − s 2 σ23
σ23 (a) = 0, σ23 (∞) = a f 0 , s = a/l where s is the parameter of the General model, which is similar to the gradient parameter l and has the length dimension. In [6], a scheme of the parameter determination from experimental data was proposed. The solutions of the boundary value problems (11), due to the semi-analytic asymptotic solution (10), can be obtained by the method of variation of an arbitrary constant. Solutions of (11) are searched for in the form u = C1 (x1 )ch(sx1 ) + C2 (x1 )sh(sx1 ) The functions C1 (x1 ), C2 (x1 ) are determined from the boundary conditions f0 C1 (x1 ) = − 2πs f0 C2 (x1 ) = − 2πs
a
x1 0
x1
(a 2 − t 2 )1/2 sh(st)dt + A2 (a 2 − t 2 )1/2 ch(st)dt
0
a A2 = − (a − t 2 )1/2 sh(st)dt − th(sa) (a 2 − t 2 )1/2 ch(st)dt 2
0
0
Thus, the solution of the first differential Eq. (11) will be in form
x1
a (a 2 − t 2 )1/2 sh(st)dt · ch(sx1 ) − ch(sx1 ) (a 2 − t 2 )1/2 sh(st)dt 0 0
a 2
x1 2 2 1/2 2 1/2 −th(sa)ch(sx1 ) (a − t ) ch(st)dt + sh(sx1 ) (a − t ) ch(st)dt
f0 u(x1 ) = − 2πs
0
0
The solution of the second differential equation of (11) is searched as the sum of the private and uniform solutions and obtained as
σ23 (t) =
t
t a2 f0 λ(2−t) + eλt ) + e−λt teλt (t 2 − 1)−1/2 dt − eλt te−λt (t 2 − 1)−1/2 dt 2 λ k1 (t)(−e 1 1
t −λt 2 −1/2 k1 (t) = te (t − 1) dt 1
Figure 2 shows the plots of the real and imaginary parts of the crack swap function calculated by the asymptotic method of LTE and by the General theory of elasticity. As can be seen from the graphs, the swap functions calculated by the General theory
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have a tangent at the crack tips, which is not inclined at a right angle to the abscissa axis, in contrast to the classical LTE, which is more in line with the real behavior of bodies with cracks. The stress plots in the area of crack tip Fig. 3 are also constructed, and due to the transition to a regular solution, it becomes possible to do so. The stress plots have a characteristic extremum, which corresponds to the point with the maximum concentration of stresses and determines the stress intensity coefficient.
Fig. 2 Plots of the real and imaginary parts of the swap function calculated by the asymptotic method of classical LTE (solid line) and General theory (dashed line), k = 10, a = 0.01, s = 0.001, L=0
Fig. 3 Plots of the real and imaginary parts of the shear stress calculated by the General theory, k = 6, a = 0.01, s = 0.001, L = 0
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3 Conclusion The model problem of steady-state oscillations of an isotropic layer with a crack on the lower bound was investigated. The study was carried out within the framework of the linear theory of elasticity based on the asymptotic approach for “small” crack, and investigated within the framework of the gradient theory. Numerical calculations proving the efficiency of the proposed techniques have been carried out. Acknowledgements The research was supported by RSF (No 22-11-00265).
References 1. Askes H, Aifantis K (2011) Gradient elasticity in static and dynamics: an overview of formulations, length scale identification procedures, finite element implementations and new results. Int J Solids Struct 48:1962–1990 2. Aifantis K, Askes H (2007) Gradient elasticity with interfaces as surfaces of discontinuity for the strain gradient. J Mech Behav Mater 18:283–306 3. Chan Y-S, Paulino GH, Fannjiang AC (2008) gradient elasticity theory for mode III fracture in functionally graded materials—Part II: crack parallel to the material gradation. J Appl Mech 75:061015–061021. https://doi.org/10.1115/1.2912933 4. Sladek J, Sladek V, Repka M, Schmauder S (2019) Gradient theory for crack problems in quasicrystals. Eur J Mech Solids 77:103813. https://doi.org/10.1016/j.euromechsol.2019. 103813 5. Vasil’ev VV, Lurie SA (2015) Generalized theory of elasticity. Mech Solids 50(4):379–388. https://doi.org/10.3103/S0025654415040032 6. Vasiliev VV, Lurie SA (2016) New solution to the equilibrium crack problem. Izv. RAS MSB. 5:61–67. https://doi.org/10.3103/S0025654416050071 7. Lurie SA, Volkov-Bogorodskiy DB (2020) On regularization of singular solutions of orthotropic elasticity theory. Lobachevskii J Math 41(10):2023–2033. https://doi.org/10.1134/ S1995080220100108 8. Vasiliev V, Lurie S (2021) On the failure analysis of cracked plates within the strain gradient elasticity in terms of the stress concentration. Procedia Struct Integrity 2021:124–130. https:// doi.org/10.1016/j.prostr.2021.09.018 9. Vatul’yan AO, Yavruyan OV (2020) An asymptotic method for solving the problem of identifying a curvilinear crack in an elastic layer. Russ J Nondestruct Test 56(10):810–819. https:// doi.org/10.1134/S1061830920100101 10. Yavruyan OV, Yavruyan KhS (2020) Asymptotic approach to the problem identification of a fringe delamination from the base. In: IOP conference series: materials science and engineering, vol 913, no 3, p 032055. https://doi.org/10.1088/1757-899X/913/3/032055
Improving the Quality of the Surfaces of Reinforced Concrete Products During the Transition to a Two-Stage Production Technology Khungianos Yavruyan , Evgeniy Gaishun , Ekaterina Dementieva , Evgeniy Staritskiy , and Stanislav Shahaliev Abstract The issues of improving the quality of the surface of monolithic reinforced concrete are relevant at all stages of the existence of this material, the resolution of which, even in narrow areas, at one time gave significant results in increasing the operational characteristics, the speed of installation and reducing the laboriousness of the assembling of reinforced concrete structures. It is very important to create a material, which would be economically sustainable and meet the quality requirements. The experience in creating material based on a traditional three-component system has led to creating new four-five-component systems, which will greatly affect quality from a better perspective. This leads to certain complications because such a change cannot happen quickly. It has to be approved and detailed: what fillers to add in order to create a material with specific characteristics. The article discusses the causes of defects in structures and concrete products as well as methods on how to avoid the consequences of appearing defects. Keywords Concrete mixes · Reinforced concrete · Transport infrastructure · Micro-fillers · Superplasticizing additives · Strength test · Mineral additives · Defectiveness reduction
1 Introduction The use of polymeric materials in reinforced concrete has formed a new branch of the development of this material. The advantages of such work in floor slabs and coatings are especially noticeable, since this type of structure has the largest specific weight in all reinforced concrete structures of buildings and structures after the foundation. A great importance lies in optimization of concrete mixes in production conditions, taking into account the requirements for product properties and for economic reasons. Companies, which are engaged in the production of reinforced concrete products and structures or concrete mixtures cannot do without the use of special K. Yavruyan · E. Gaishun (B) · E. Dementieva · E. Staritskiy · S. Shahaliev Don State Technical University, 1 Gagarin Sq., 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_174
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Fig. 1 Transition from three to five-component system when optimizing concrete
additives for concrete, which significantly improve the quality and characteristics of the mixture and regulate the processes of cement setting and hardening. Traditionally, concretes are a three-component system of cement, filler and water. Recently, there has been a transition from a three-component system to four-, fivecomponent systems using modern concrete modifiers, micro-fillers and other components (Fig. 1). They are induced in an insignificant volume (tenths and hundredths of a percent in relation to the mass of cement), but significantly affect the chemical processes of concrete hardening, ensuring the optimization and improvement of the physical and mechanical characteristics of products, including strength, frost resistance, water absorption, etc. Currently, the most important are superplasticizers based on polycarboxylate esters (PCE), the development of which is closely related to the creation of self-compacting concretes (SCC). The BASF concern played a significant role in the development and implementation of new types of superplasticizers. The superplasticizers created by PCE allow concrete manufacturers to obtain products with improved characteristics and optimize the production process, both from an economic and environmental point of view. The main positive property of polycarboxylates, and this new element in the way of developing additives, is that concrete manufacturers can first decide what properties they would like to see in the superplasticizer, and then design the molecules to achieve exactly the desired result [1–3]. The use of a highly mobile mixture provides the following advantages: • the possibility of concreting densely reinforced structures with the complete exclusion of vibration compaction, which helps to improve the environment, as well as reduces the level of noise and vibration impact on workers; • increasing productivity in the production (increasing the speed of concrete placement, a significant reduction in labor costs, an increase in the turnover of forms of formwork), an increase in the pace of construction;
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• with high mobility and resistance to delamination (high material coherency) of self-compacting mixtures, homogeneity, low porosity and improved physical and mechanical characteristics of concrete, higher surface quality are guaranteed, which significantly increases the durability of structures. A key factor in the fragility of reinforced concrete structures exposed to corrosive environments is insufficient compaction of the surface layer due to the difficulties of vibration compaction in narrow spaces between the formwork and reinforcing bars or other embedded parts (for example, channels for placing high-strength prestressed reinforcement). When selecting the concrete composition, the issues of ensuring the minimum consumption of cement were taken into account in terms of reducing the energy consumption and cost of the mixture, ensuring workability and defects associated with the collapse of the structure, as well as the quality of the front surface. The efficient production of products using this technology largely depends on the completeness of the involvement of local raw materials. In the selection of concrete compositions, the accumulated experience of optimization was used from the conditions of minimum void presence with the replacement of part of the traditional raw materials with secondary fine-grained industrial wastes. In addition, an important requirement was to obtain concrete with low shrinkage and the advantage of eliminating the prestressing of high-strength ropes which are used for the production of hollow core slabs. Purposeful optimization of the grain size composition of concrete mixtures was carried out using silica-containing fillers. In terms of fillers were used crushed granite with the fractions of 5–10 mm (GOST 8267–93), screenings of crushed granite and limestone with the fractions of 0–5 mm (GOST 31,424–2010), and quartz sand (GOST 8736–2014). Portland cement CEM I 42.5H (GOST 31,108–2003) of CJSC Oskolcement was used as a binder. The air-entraining additive “SikaPaver” HC-30 (TU No. 2499–004-13,613,997–2008) produced by the concern “Sika” was injected into the composition. To stabilize the rheological parameters, microsilica MK-85 produced by OJSC Novolipetsk Metallurgical Plant was used. The use of filler from crushed limestone, as well as the addition of microsilica, which provides a rational grain size composition of the components, made it possible to obtain the required technological characteristics of the concrete mixture for the line of formless molding of hollow floor slabs and other products. At the same time, the savings in cement amounted to 100 kg/m3 of concrete. The theoretical calculation of the compositions was carried out using the absolute volume method according to: • computational and experimental method developed by V.P. Sizov; • recommendations for the selection of compositions of heavy and fine-grained concrete (to GOST 27006–86); • according to the instructions of the departmental building codes (DBC 15093 “Instructions for increasing the frost resistance of concrete of transport structures”).
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Table 1 Characteristics of a reinforced concrete slab panel grade
the consignment
class and diameter of the working reinforcement
actual concrete strength, MPa, on the day of testing
design grade of concrete (class)
date of manufacture
of testing
PB 2–60. 12–8 9K7
1108
7Ø9K7
42
400 (B30)
24.11.15
10.12.15
The compositions of concrete mixtures adopted after experimental clarification ensure the requirements for compressive strength, frost resistance, retention of mobility and water resistance in accordance with the requirements of GOST 7473–2010 “Concrete mixtures. Specifications” and GOST 26,633–2012 “Heavy and fine-grained concrete. Technical conditions”. Based on the obtained test results of control and variable compositions (Table 1), the following conclusions were made: • it is possible to reduce the consumption of cement up to 10% with subsequent adjustment of the absolute volume of the mixture and testing for strength, frost resistance and water resistance; • ensuring the required indicators for the workability of the concrete mixture and the integrity of the formed array is possible only through the use of a complex of optimizing components. It was found that after stopping of vibration impact on the concrete mix, the samples retain their shape with immediate disassembling. The class of the surface obtained during the experimental molding of floor slabs corresponds to A2—A3 in accordance with GOST 13,015–2003. The obtained concrete mixtures have the best technological characteristics, which ensure the integrity of the formed array, dense structure and high quality of the front surface (Fig. 3). The optimized compositions of concrete mixtures were used in the production and testing of slabs of grade PB 2–60.12–8 9 K7 according to working drawings developed by UralNIIproekt RAASN, series 0–464-09 “Reinforced concrete floor slabs prestressed with stand-off formwork”, TU-5842 -001–89,328,839-09. The tests were carried out in accordance with SP 13–102-2003 “Rules for the Inspection of Load-Bearing Structures of Buildings and Structures”, as well as in accordance with GOST 8829–94. The data characterizing the PB 2–60.12–89 K7 slab are given in Table 1. Inspection before the start of control tests did not reveal deviations from the working drawings in the dimensions and reinforcement of the product. In accordance with the test scheme, the concrete slab was installed in the working position on a special stand (Fig. 2). The loading area was 5.9 * 1.2 = 7.08 m2. The slab was loaded in stages with special concrete weights weighing 110 kg. The value of each of the loading stages was determined in accordance with GOST 8829–94 and amounted
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90 76.3
Сompressive strength, MPa
80 70
73.3
76.3
66.3 59
60 50 40 30 20 10 0 SP-1(0,5%) SP-2(0,7%) SP-3(0,7%) SP-4(0,5%)
N/A
Fig. 2 Strength indicators of modified compositions
to 121.43 kg/m2. During the test, using PAO-6 deflection meters with a scale of 0.01 mm, the vertical displacements of the supports and the amount of slab deflection in the middle of the span were measured. After each stage of loading, the slab was examined for the appearance of cracks, and when cracks appeared, the opening width was measured using an MPB-2 microscope. In accordance with the standard parameters, the stiffness and crack resistance of the floor slab PB 2–60.12–8 9K7 were evaluated. The total weight of the concrete blocks and additional foundation blocks was 12,090 kg, which corresponds to a load of 17.08 kN/m2. The results of measuring the displacements of the supports and the magnitude of the deflections are given in Table 2. • During the strength test, the load-bearing capacity of the floor slabs was fully ensured at a test load of 13.2 kN/m2 with a safety factor of C = 1.4.Control observations did not reveal slippage of the working reinforcement rods and the development of cracks. The load-bearing capacity of the slabs was also ensured at a load of 15.6 kN/m2 with a safety factor of C = 1.6; in this case, the formation of cracks with an opening width δ = 0.15 mm was observed. The depletion of the bearing capacity occurred with an additional increase in the load, which was recorded by a strong deflection and cracks with an opening of up to 0.25 mm. The reason is the fluidity of the working reinforcement without crushing the concrete in the compressed zone. The control deflection of the slab should be fK = 6.7 mm at q = 8.5 kN/m2. The actual deflection measured during the test was fK = 4.4 mm at q = 8.5 kN/m2, which is lower than the control one; there were no cracks in the structure. The first cracks appeared when the load reached the value q = 15.58 kN/m2. Thus, it should be concluded that the studied panels, which were made on
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Table 2 Test result of reinforced concrete floor slab stage №
load, N
draft of the middle of the supports, mm left
right
draft of the center of the supports, mm
panel deflection in the middle of the span, mm without draft the supports
withdraft the supports (true deflection)
1
121.43
0.2
0.16
0.18
0.79
0.61
2
242.86
0.33
0.28
0.3
1.37
1.07
3
364.29
0.46
0.35
0.4
2.05
1.65
4
485.71
0.64
0.42
0.53
2.89
2.36
5
607.14
0.71
0.67
0.69
3.49
2.8
6
728.57
0.78
0.96
0.87
4.19
3.32
7
850
0.94
1.13
1.03
5.43
4.4
8
1083.33
no cracks appeared
9
1316.67
10
1558.33
appearance of cracks. δ = 0.15 mm
11
1742.65
the load-bearing capacity of the slab has been exhausted
the basis of selected compositions of concrete mixtures, withstood the strength test. The production of prefabricated products using the technology of stand-off formwork in combination with efficient methods of assembling of buildings and structures in the future will provide a significant economic effect in comparison with traditional monolithic and small-piece construction. When using superplasticizing additives based on polycarboxylate ether, mortar separation and settling of the coarse filler are excluded [4]. The following superplasticizers were used during the tests: Rheobuild 1000 (hereinafter SP-1), Glenium 116 (SP-2), Glenium ACE 430 (SP-3), Pozzolith MR55 (SP-4).
2 Materials and Methods At the first stage, the normal density of the tested compositions was determined. Based on the recommendations of the additive manufacturer, the studies were carried out for each additive in the concentration range from 0.1 to 3% by weight of the binder. The obtained results are presented in Table 3, which displays the quantitative decrease in the water-cement ratio (depending on the dosage of the additive) in relation to the non-additive cement (hereinafter N/A) in percent. A decrease in the water-cement ratio with an increase in the concentration of additives was established, however, the degree of decrease in W / C strongly depends
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Table 3 Decrease in water-cement ratio in relation to N/A Additive, %
0.1
0.3
0.5
0.7
1.0
SP-1
0
3.1
4.7
6.3
6.3
SP-2
0
1.6
6.3
6.3
6.3
SP-3
1.6
3.1
6.3
12.5
SP-4
1.6
6.3
9.4
12.5
1.2
1.4
1.6
1.8
2.0
2.2
2.5
3.0
9.4
12.5
12.5
18.8
21.9
21.9
23.4
23.4
6.3
6.3
7.8
6.3
9.4
9.4
12.5
15.6
15.6
15.6
15.6
17.2
18.8
18.8
20.3
21.9
21.9
12.5
12.5
12.5
12.5
12.5
12.5
12.5
12.5
12.5
on the type of additive. The introduction of SP-4 more than 0.7% by weight of cement does not lead to a significant decrease in the water demand of the cement paste. The presence of a given amount of additive in the mixture ensures the formation of a monomolecular adsorption layer by plasticizer molecules having a negative charge on the surface of cement particles, as a result of which an electrostatic repulsive effect between cement particles is observed (i.e., preservation of mobility by the mixture while reducing the amount of mixing water).A further increase in the content of the plasticizer does not show a significant effect on the value of the internal friction of the particles and no longer leads to a significant decrease in the water demand of the cement paste. It may even subsequently reduce the strength characteristics of the cement stone, especially in the initial periods of hardening due to the excessive mobility of the cement slurry [5, 6]. The most interesting compositions for research were selected and specimensbeams 1 × 1 × 3 cm were molded, hardened in humid conditions for 28 days. After that, the grade compressive strength was established and, based on the data obtained, The most effective dosages for each additive were selected. The values of the brand strength of the tested compositions are shown in Fig. 2. The obtained results show that the additives lead to a significant increase in strength. The most effective additives were SP-2 and SP-4, which increase the strength by almost 30% in an amount of only 0.7 and 0.5% of the cement mass, respectively. The study of strength characteristics led to the conclusion that plasticized compositions gain strength faster, compared with no additives, practically throughout the entire hardening interval. This can be explained by the fact that the adsorption layer of the additive formed around the surface of the cement particle is water-permeable. And thus, the deflocculating action of plasticizers provides greater contact of cement particles and water, due to which the hydration process is fuller and faster [7, 8].
3 Results In structures. Modern technology for the construction of monolithic structures involves the use of concrete mixtures with a cone draft of 16 cm or more. Such mixtures are prone to delamination and water separation. For this reason, various
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kinds of defects are inevitably formed, which further leads to a decrease in the bearing capacity and low durability of monolithic structures. It is believed that concrete mixtures for monolithic construction should contain a total of 500–600 kg per cubic meter of fine components in the form of cement and inert microfiller. However, finely dispersed components are represented only by cement and amount to 300–400 kg per cubic meter, in Russia. In combination with the use of plasticizers, this leads to delamination and water separation when laying mixtures in a structure. In products. The technology for manufacturing products has significant differences from the technology for assembling structures. The main difference is the use of concrete mixes with less plasticity. At the same time, higher requirements for surface quality are traditionally imposed on products. There are several reasons for the deterioration of the surface quality of products, the main of which can be recognized as uneven application of lubricant on the surface of the mold, insufficiently effective compaction of the concrete mixture and its incorrect formulation. With a thick lubricant consistency, air is trapped on the surface of the mold and the formation of air bubbles, especially on vertical surfaces. When using concrete mixtures with a cone draft of 2–6 cm, air bubbles are formed inside the concrete mixture, and during the formation of products, even with intense vibration action, shells are also formed on the surface. However, intense vibration is undesirable because it leads to delamination of the concrete mixture and uneven distribution of strength in the products. Increasing the mobility of the concrete mixture to solve the problemby adding plasticizers also does not lead to a positive result, since even with a slight vibration effect the concrete mixture stratifies with all the above consequences. The generally accepted solution to this problem is the use of self-compacting concrete mixtures, which necessarily contain a microfiller, but this way significantly increases the cost of finished products [9–11].
4 Discussions The identification of defects in our organization is carried out in a planned manner. However, it is undoubtedly necessary to continue to improve both methods and control instruments. After analyzing the existing and used methods of detecting and measuring defects, we would like to suggest the following: 1. Continue to clarify the list of defects that are to be identified during the inspection of structures and their more detailed linking to the classifier of the danger of defects. In particular, it would be possible to introduce an additional gradation of defects on the basis of maintainability, namely, to introduce such categories of defects as removable or irreparable; 2. During the measurements of the crack opening width with instruments, replace the Brinell microscope, which is inconvenient under construction conditions, with a set of needle-type probes, while ensuring the measurement accuracy with its help at the level of 0.02 mm (like a microscope);
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3. Legalize the determination of the depth of cracks, since this will allow at least to classify the detected cracks as shrinkage/surface cracks (for example, with a depth of up to 10% of the structure thickness) or to a force depth of more than 10% up to through (100% of the structure thickness); 4. Evaluation of the surface quality of reinforced concrete products and structures should be carried out only by categories of concrete surfaces. In this case, the assessment by the size of the shells should not be applied; 5. It is imperative to control the spreading of the cone and water separation of concrete mixtures when placing them in the structure. 1. In the manufacture of concrete mixtures, it is imperative to introduce a finely ground component (mineral additive). 2. Use cements containing at least 50% mineral additives. At the same time, increase the cement content per cubic meter of mixture by 30–40%. 3. Use concrete mixtures with a maximum particle size of 10 mm. 4. To restore the consistency of concrete mixes before placing them in the structure by introducing a plasticizer. 5. Apply lubricant to molds only in a mechanized way. 6. Apply a two-stage technology for the preparation of concrete mixtures. The first stage is mixing and joint grinding of cement, mineral additives and plasticizer. The second is the preparation of a concrete mixture according to traditional technology using existing batching plant equipment. In the first stage, it is recommended to use a conventional cement ball mill. The two-stage technology is especially beneficial in the manufacture of modern concrete mixtures containing a large number of components (cement, microfiller, plasticizer, hardening retarder or accelerator, antifreeze additive, stabilizer for underwater concreting, etc.)
5 Conclusion 1. It should be recognized that obtaining high quality surfaces of reinforced concrete products is possible only with horizontal molding of products (face down). 2. A significant improvement in the quality of reinforced concrete products and especially monolithic structures, including their surfaces, is possible only with the mandatory addition of a finely ground component to concrete mixtures 3. A radical improvement in the quality of products and structures can be achieved by switching to a two-stage technology. At the same time, the creation of a production of fractionated aggregates and microfillers will not be required.
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References 1. Klyueva NV, Gornostaev SI (2016) On the issue of choosing a computational model for assessing the stiffness of reinforced concrete structures. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta 1(64): 71–74. https://www.elibrary.ru/item.asp?id=26008670. 2. Bosakov SV, Belevich VN, Shchetko NS, Raichev VP (2010) Calculation and experimental assessment of the strength of hollow-core slabs without formwork, taking into account the requirements of EN. Constr Sci Eng 6: 47–54. https://rep.bntu.by/handle/data/2795 3. Goncharova MA, Ivashkin AN, Simbaev VV (2016) Development of optimal compositions of silicate concretes using local raw materials. Build mater 9:6–8. https://journal-cm.ru/index. php/en/journals/2016/all-articles-in-2016/development-of-optimal-compositions-of-silicateconcretes-with-the-use-of-local-raw-resources 4. Additives based on polycarboxylate esters for the manufacture of vibration and self-compacting concretes. Organization standard STO 70386662–306–2013. 5. Forster SW (2016) High-Performance ConcreteStretching the Paradigm. Concr Int 9:63– 66. https://cyberleninka.ru/article/n/vysokotehnologichnye-betony-s-ispolzovaniem-superplas tifitsiruyuschih-dobavok-na-osnove-polikarboksilata/viewer 6. Shtark J, Wicht B (2004) Durability of concrete. Oranta, Kiev. 7. Korchunov IV, Sidorova EN, Akhmetzhanov AM, Potapova EN (2016) Increasing the durability of products based on cement/problems of construction production and real estate management. In: Proceedings of the IV Mezhdunar scientific-practical conference, 23–24 November 2016, Kemerovo: FSBEI VO Kuzbass state technical university. 8. Bannikova AS (2018) Analysis of the development of the building materials recycling industry in the Russian Federation. Epoch Sci 14:159–165. https://doi.org/10.1555/2409-3203-2018-014-159-165 9. Lyubeshkina EG (2017) Municipal solid waste. Problems and solutions. Food industry 312:28– 30 10. Markhel NV, Maslennikova LL, Babak NA (2013) Geoecological assessment of technologies for obtaining building materials using waste from the construction industry. Izvestiya of the Petersburg University of Railways 2 (35). 11. Koroleva LP (2017) Contribution of recycling to neo-industrial development: classification of effects. Sci J NRU ITMO Ser Econ Environ Manag 2:29–38. http://economics.itmo.info/en/art icle/17013/vklad_reciklinga_v_neoindustrialnoe_razvitie:_klassifikaciya_effektov.htm
Preconditions for the Development and Production of Wall Materials in the Northern Ethiopia Berhane Gebru , Vladimir Kotlyar , Svetlana Kurilova , and Andrey Tolstorebrov
Abstract The general characteristics of the Republic of Ethiopia are given. The country is currently actively developing the construction industry, and in connection with this, there is a great need for various types of wall products. This problem is especially acute in the northern Ethiopia, including in the large industrial center of Mekelle city, which is the capital of the province of Tigray. There are cement and metallurgical plants, limestone quarries and small construction industry enterprises in the vicinity of the city. Various types of natural stone are widely used in local construction: granite, basalt, sandstone, limestone, marble, quartzite. Currently, in northern Ethiopia, including the city of Mekelle, and elsewhere in Ethiopia, local natural aggregate is used to manufacture hollow cement wall blocks using simple vibratory compaction plants. A method for producing unfired wall bricks by compression molding is considered. The analysis of the local raw material sources and the prospects for the method of obtaining non-fired wall products shows that the most relevant direction in the development of the manufacture of wall products in Mekelle city is the organization of the production of non-fired bricks by compression molding based on limestone screenings from local quarries and metallurgical slags. Keywords Bricks · Cement · Limestone · Metallurgical slag · Molding · Pressure · Technology
1 Introduction The Federal Democratic Republic of Ethiopia is a developing country whose economy is mainly based on agriculture. In recent years, thanks to the efforts of the government, the level of investment in the country’s economy has significantly increased and, as a result, there has been a significant development in the construction sector. B. Gebru (B) · V. Kotlyar · S. Kurilova · A. Tolstorebrov Don State Technical University, 1, Gagarin Square, 344000 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_175
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The construction sector in Ethiopia is a sector that opens the door for the growth of many additional macro and micro-industries. Building works require high input from other sectors. For instance, they require different metal products, clay works, and cement and cement products, etc. As such, the growth of these industries will surely follow the growth of the construction industry. Similarly, when the construction and renovation of housing increase, the demand for household furniture increases; thereby, indirectly, opening the door for the growth of the furniture industry. All in all, the construction industry is a sector that can entertain big micro companies, that is widely labour based. All these being taken into consideration, the industry policy of the Federal Democratic Republic of Ethiopia has sought to pay special attention to the construction industry of the country. This is also true for the northern part of the country and in particular for the province of Tigray, the capital of which is the city of Mekelle. Mekelle is located at 780 km north of the capital of Ethiopia in the Ethiopian Highlands at an altitude of 2250 m above sea level. This altitude provides the city a cooler climate compared to the surrounding plains. For Ethiopia, Mekelle is one of the largest industrial centres in the northern part of the country (Fig. 1). There is an airport at the outskirts of the city that provides both domestic and international air travel services. Among the largest enterprises in the city are metallurgical and cement plants. There are also small construction industry enterprises. The main wall products are obtained from wall sawing stones from rocks. Stones are used as main source of local building materials mainly in the northern Ethiopia including the city of Mekelle. Sandstone, marble, limestone, granite, basalt, quartzite, etc. are majority of stone types used in the local building construction. The main engineering properties that made stone a suitable local building material are its strength, durability, simplicity to form into desired shape, its resistance to the decomposition and chemical attacks, and its resistance to abrasion. Hollow cement blocks made by simple installations with vibration compaction of a concrete mixture also used as wall making materials in northern Ethiopia including the city of Mekelle as well as elsewhere in Ethiopia. The main colours that define the architectural features of the Mekelle city are yellow, beige and gray with various shades (Fig. 2). The growth in the pace of construction sector has significantly increased the demand and requirements for wall materials, of which there is an acute shortage in Mekelle city.
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(a)
(b) Fig. 1 Recent view of Mekelle city, Tigray, Ethiopia (Source: Mekele city—Google Search)
2 Methods and Materials A comprehensive analysis we have carried out has made it possible to determine that the most optimal solution to increase production and increase the variety of wall products is to organize the production of non-fired compression molding bricks (CB). Non-fired products, in contrast to products obtained from materials using hightemperature processing, have a number of features, which are subdivided into prescription and technological ones. The technical features of non-fired products for civil engineering construction include: • The raw (molding) mixture consists of a binder, fine aggregate and water; • Portland cement of the 400 and 500 brands is used as a binder; • The consumption of Portland cement is assigned as a percentage of the mass of dry components of the mixture; • The consumption of Portland cement is low and amounts to 10–15% for wall products;
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Fig. 2 Architectural view of Emperor yohannes IV pallace
• Screenings from crushing rocks and fine sands are used as fine aggregates; • The aggregate can be represented by one component (for example, screening crushed sand) or several components (for example, screening and sand); • The grain size composition of the aggregate must satisfy the recommended grain composition with the largest aggregate grain size of 2.5 mm for wall products; • If several components are used as a filler, then the grain composition of the mineral aggregate mixture is calculated through the percentage of each component in the mixture, ensuring the recommended grain composition; • Water consumption is assigned in excess of 100% of the mineral mixture, consisting of cement and aggregate; • Water consumption is set experimentally in order to ensure the necessary stripping strength of freshly formed products and the greatest strength of hardened products; • Water consumption depends on the structure of the aggregate and amounts to 10– 12% in compositions based on dense aggregates and up to 20–30%—on porous aggregates. The technological features of non-fired products for civil engineering include: • The raw mixture is prepared in two steps: first, for 1-min, dry components such as cement and aggregate are mixed and then the dry mixture is thoroughly mixed with water for 5 min, since there is little water in the mixture. • Mixing of the molding mixture is carried out in compulsory mixers;
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• The molding of products is carried out by the pressing method in order to ensure a tighter contact of the aggregate grains; • The pressing pressure is set experimentally to ensure the highest strength and the lowest water absorption of products; • The magnitude of the pressing pressure depends on the production capacity of the press and is usually 15–20 MPa, but can reach 40 MPa and more; • Depending on the direction of the applied pressing force, the molding of products can be single-sided and two-sided; • Double-sided pressing is more preferable, since it provides a more uniform structure of products and a more evenly distributed density in the volume of products; • Stripping of products is carried out instantly immediately after molding, which is associated with the molding of products in a press matrix, which has a certain productivity; • The stripped products are stacked on pallets to preserve their integrity and transported for hardening; • Hardening of products can be carried out under normal conditions and under conditions of heat and moisture treatment. Compliance with the features of obtaining non-fired compression molded products ensures their quality and durability. Unfired bricks of compression molding in Russia are often called hyper-pressed bricks, although this name from the technological point of view is not entirely true. The prefix “hyper” when added to a noun implies a phenomenon, property, process that is higher than any norm. The molding of bricks according to the specified technology does not exceed the specific pressure of 40 MPa. At such pressures, semi-dry pressing ceramic bricks are formed. Ceramic tiles are formed on modern presses at specific pressures above 50 MPa. Therefore, the specific pressures of brick pressing in the range of 20–40 MPa are common for the current level of development technology. The choice of non-fired compression molding technology for organizing the production of wall products in the northern Ethiopia, and in particular in the city of Mekelle, is due to interrelated factors. The organization of brick production using this technology makes sense in the immediate vicinity of finding the main raw material - a filler with a fractional composition of 0–5 mm, which is 88–94% of the mass of the products themselves. The geological structure of northern Ethiopia is characterized by the presence of a series of Mesozoic sedimentary and volcanogenic-sedimentary rocks, among which various types of limestones, dolomites, marble, volcanic tuffs and other rocks are found. Despite the fact that various sufficiently strong rocks and industrial wastes can be used as filler in developing the technology of compression molding, the carbonate rocks are used as the main raw materials in 90% of cases. This is due to the fact that these rocks are relatively soft. The hardness of the mineral calcite, of which they are composed, on the Mohs scale is only 3 units, whereas the hardness of other rocks is significantly higher. For example, the hardness of quartz, the main mineral in sands, is 7 units, and the hardness of granite sand is 6–7 units. This is a very important point
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Fig. 3 Limestone quarry in the vicinity of Mekelle City
in developing the technology of compression molding, since due to the high hardness of raw materials, rapid wear of the molds occurs, which significantly affects the cost and durability of the products [1–4]. At present, several quarries of carbonate rocks are being developed in the vicinity of the town of Mekelle - for the production of cement and for wall stones, which are obtained by direct cutting of rocks (Fig. 3). This technology is quite simple. A stone-cutting machine with horizontal and vertical cutting moves along the temporary rail tracks set at a certain level. After cutting at one level, the machine goes down.
3 Results and Discussion The next important point for organizing the production of non-fired wall products near the city of Mekelle is that the technology of compression molding, in comparison with ceramic bricks, does not require a large amount of investment, has a low energy capacity, and low consumption of the most expensive component - cement. The production itself can be literally under the open sky or hinged. The main operations in the production process of non-fired wall products are the preparation of raw materials, which consists in their crushing (on jaw, hammer, rotary and other crushers), their fractionation (screening), dosing and thorough mixing of crushed rocks with cement, pigments and water. The main point of this process is the selection of the grain composition of raw materials, which ensures the densest packing of the grains during pressing. This allows one to significantly reduce the consumption of cement and get more durable products. The tightest packing can be achieved both with a continuous grain composition, and with an intermittent one. Mixing homogeneity is achieved using high-speed intensive mixers or so-called mixer-mechanical activators. The molding of non-fired wall products in this process can be carried out on various types of presses and can be both double-sided and one-sided. Most expediently, it can be carried out on hydraulic presses with a double-sided load application. In Russia, Kanon has developed special presses for the compression molding technology, which are not inferior to imported ones in terms of technical characteristics, but their cost is significantly less and they are easier to maintain [5]. For example, the press A100.2,
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Fig. 4 Earthquake-resistant compression molded lego-brick
A300.4 with a capacity of 800–1200 pieces of items per hour (Fig. 4). Also, the “Canon” company has developed and sells ready-made technological lines for the production of non-fired compression molding bricks. In terms of price and quality ratio, non-fired compression molding bricks are the most acceptable products for Ethiopia. The replacement of molds on this press does not take much time. Laying of finished bricks (palletizing) can be carried out manually and with the help of automatic robotic stackers. Since the Ethiopian climate does not require steaming bricks to accelerate curing, stacking can take place on major trays sold. In this case, brick hardening occurs naturally at ambient temperatures. For this, the pallet with bricks is covered with plastic wrap. After hardening, it is possible to rusticate the brick by splitting the brick, chipping, tumbling, etc. It is also possible to produce earthquake-resistant bricks, the so-called Lego bricks (Fig. 4). Also, a very important advantage of the compression molding brick is its variety both in shape and color palette, which can significantly diversify the architecture of northern Ethiopia (Fig. 5). The introduction of finely ground metallurgical slag will allow to obtain brown colors on the basis of basic yellow, beige and light gray colors [6]. The introduction of small amounts of pigments will allow you to get a brick of green and blue palette. The variety of shapes also opens up great opportunities for national architects and builders [7]. It should be noted that the high density of compression molded bricks is very suitable for the climate of northern Ethiopia - the brick heats up slowly during the day and slowly releases heat at night.
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Fig. 5 Various types of compression molding bricks
4 Conclusion Thus, we can say that the developments in this direction and the equipment produced in Russia, in close cooperation with fellow builders from the city of Mekelle, will contribute to the growth of the production of wall products in northern Ethiopia.
References 1. Kotlyar VD, Kurilova SN (2014) Structure formation and properties of pressed cement-mineral composites with the addition of a porous low-modulus component. Monograph, Rostov State University of Civil Engineering. p 214 2. Ashmarin GD, Lastochkin VG, Kurnosov VV (2009) Theoretical foundations and ways to improve the technology of compression molding of ceramic wall materials. Build Mater 4:26–29 3. Ashmarin GD, Kurnosov VV, Belyaev SE, Lastochkin VG (2011) Justification of the effectiveness of compression molding of ceramic building materials. Build Mater 2:8–9 4. Ozhogina LV, Cherepakhina RG, Gaidina NM, Pribytkov AV, Parusimov IV (2020) Prospects for the development of non-firing technologies for the production of building materials, products and structures. Chem Phys Mech Mater 1(24):139–150 5. Zolotukhin SN, Kukina OB, Kukin LA, Shuvaev DI, Volkov VV, Gavrikova Ryu (2020) Features of innovative technology of non-firing production of building materials. In the collection: Innovative, information and communication technologies. In: Proceedings of the XVII international scientific and practical conference, pp 445–450
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6. Mohammed KJ, Abbas FO, Abbas MO (2009) Using of steel slag in modification of concrete properties. Eng Technol J 27(9):9–15 7. Kramorova VI, Kotlyar VD (2015) Sculptural brick in modern design. Construction and architecture, conference proceedings, pp 349–351. https://www.elibrary.ru/item.asp?id=248 75567
Rational Methods of Reinforcement of Monolithic Flat Slabs in Frame Buildings Viktor Muradyan
and Petr Polskoy
Abstract The main type of modern mass construction is the construction of girderless frame-monolithic buildings. With the increase in construction volumes, the volumes of repair and restoration work and reinforcement of structures are also growing. The main reasons for this are the mistakes made during the design. Such errors took place at one of the cultural and entertainment centers of the city of Rostovon-Don, which were discovered during the inspection of the building. The basis for the survey was the re-equipment of existing premises with an increase in the load on existing floors. The constructive solutions considered in this article to strengthen the floor slab are associated with a lack of load-bearing capacity. A feature of the reinforcement method is a one-sided extension of the 220 mm thick floor slab from above by 50 mm with capitals around the columns at a non-standard step of 8.4 × 6.4 m. The proposed design solutions are based on solutions aimed at including existing structures in collaboration with new ones. This applies to both “old” and “new” concrete, as well as existing and additional reinforcement. The proposed solutions make it possible to eliminate the need to strengthen the plate from the side of the stretched zone. Keywords Reinforcement · Reconstruction · Transport infrastructure · Design solutions · Concrete · Reinforced concrete · Reinforcement
1 Introduction The main type of modern mass construction is girderless frame-monolithic buildings. It is a known fact that with the increase in the volume of construction, the volume of repair and restoration work, as well as work on structures strengthening, is also growing. The main reasons for the decrease in the bearing capacity of structures are errors made in the design and construction process, as well as changes in the technology of production and reconstruction of buildings. Therefore, the determination V. Muradyan (B) · P. Polskoy Don State Technical University, 1 Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_176
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of the most effective methods of structures strengthening without stopping the main production activity becomes an urgent issue [1–3]. The proposals were implemented during the reconstruction of the cultural center in the city of Rostov-on-Don. A design solution for reinforcement has been developed (Fig. 1). The monolithic floor slab has a thickness of 220 mm with capitals and a non-standard column space of 8.4 × 6.45 m. With the reinforcement of the existing slab, the restoration of the floor slab with a size of 5.2 × 2.8 m is carried out within the stair opening, located in the most dangerous sections of the floor. The design solution in question was carried out in accordance with the design task and is based on the results of a survey of the technical condition of building structures using urban planning regulations, technical regulations, including those establishing requirements for ensuring the safe operation of buildings, structures and adjacent territories, and in compliance with technical conditions. The adoption of the proposed design decision was influenced by the inability to perform reinforcement work to the ceiling of the lower floor. The design decision to strengthen the floor slab was made taking into account the following factors: – due to the change in the load on the floor compared to the load at the time of the development of the floor main project. The consequence of this is a shortage of working reinforcement in both the lower and upper zones of the slab;
Fig. 1 Floor plan and installation diagram of additional reinforcement elements
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– correction of errors of the previously performed reinforcement of the floor slab, which consisted in the installation of reinforcement I-beams No. 55B2 in order to distribute loads from walls installed without directly transferring the load to the capitals from one end of the beam. Taking into account the above mentioned, the classical reinforcement method using concrete and reinforcement is adopted as the main one, since the modern reinforcement method using composite materials [4, 5] does not solve the raised issues without changing the cross-section dimensions of load-bearing structures.
2 Methods The technical inspection of the above structures carried out before the decision was made showed the following: – the slab has a significant crack width from the own weight of structures. As a result, deflections in some places are 56-68 mm, instead of 41 mm for this type of structures, according to SP 20.13330.2016 Loads and actions (Annex D). – the performed verification calculations, taking into account the results of the survey, showed a lack of reinforcement in both the upper and lower zones of the slab. The required reinforcement exceeds the actual reinforcement of the floor slab in both span and support zones. – the presence of cracks at the corners of the stairway opening with a width of up to 3 mm, which appeared after disassembling the stairway. Taking into account the above, it was found that the floor slab is in a critical condition. Further operation of this slab was suspended until the issue of strengthening the existing overlap was resolved.
3 Results and Discussion Taking into account the impossibility of carrying out work on reinforcement to the ceiling of the lower floor, a repeated verification calculation of the bearing capacity of structures using a one-sided slab extension was performed. It was found that the thickness of the build-up of 50-60 mm eliminates the shortage of reinforcement in the lower zone and provides the possibility of placing additional upper reinforcement consisting of the main background reinforcement with a diameter of 10 A500C at 200 mm intervals in both directions, and additional reinforcement located between the rods of the main grid both along the letter and digital axes.
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Fig. 2 The layout of the beams of BUS-1 ÷ BUS-7, 7a, 7b and the places of opening of the protective layer of concrete to include them in joint work with the floor reinforcement
Taking into account the obtained results, a reinforcement project was developed, the main task of which was to ensure the joint operation of the existing floor slab and a 50 mm thick concrete slab on top. The joint work of “old” and “new” concrete is provided by the following factors: 1. The inclusion in the joint work of the floor slab and the existing single and paired I-beams B-1, B-2 made from No. 55B2 and B-3 from I-beams No. 26SH1 (Fig. 2) installed earlier as reinforcement options. 2. The inclusion in the work of horizontal bent profiles installed for fixing the wall envelope by attaching them to the floor slab and cutting through the walls to install the reinforcement (Fig. 3). 3. Complete release of the floor slab from the screed and sound insulation elements, removal of cement-sand slurry from the wall surface, hacking and opening of the protective layer of concrete in order to connect the existing reinforcement of the floor slab with the reinforcement of an additional reinforcement grid along the letter and numeric axes. Figure 4 shows the layout of the locations of the opening of the concrete protective layer on the surface of the reinforced plate, and Figs. 5 and 6 show the general view of the overlap in the process of reinforcement, with the installation of additional bends. 4. Setting the upper and lower reinforcement within the staircase of the opening in the floor slab, as well as additional working reinforcement, bent and cross rods (Fig. 7).
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Fig. 3 General view of the bent elements for fixing wall panels that are attached to the floor slab
5. Inclusion in the joint operation of the additional reinforcements that are installed in the locations of the walls, with the existing slab at the place of installation of the walls (Fig. 8). The joint operation of the existing reinforcement in the floor slab and the additional reinforcement is ensured using additional bends welded to the reinforcement rods
Fig. 4 Layout of places of the opening of the concrete protective layer on the surface of the reinforced plates
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Fig. 5 General view of the slab in the process of reinforcement after bends welding
Fig. 6 General view of the slab in the process of reinforcement with an installed bend for coupling with the reinforcement of an additional grid
Fig. 7 General view of the places of opening of the concrete protective layer in a checkerboard pattern and the location of the stairway in the immediate vicinity of the inter-column sections along the letter and numeric axes
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Fig. 8 Inclusion in the joint work of reinforcement elements with an existing slab in the places of installation of walls (reinforcement beam BUS-1)
located both along the letter and along the digital axes. The bends are installed in chessboard order with a distance of 1200 mm on the total reinforcement area and in increments of 600 mm on the end sections of the additional reinforcement slab. In order to ensure the anchoring of the reinforcement at the ends of the rods, in addition to the bends, U-shaped and L-shaped elements are installed, welded to the main reinforcement. All components and details are presented in the working drawings of the reinforcement project. In addition to the above, the instructions for the production of preparatory, reinforcement and concrete works are attached to the working drawings [6–9]. – provision of a concrete protective layer for reinforcement along the letter axes by laying additional structural rods with a diameter of 8 A240 on the existing floor slab. Ensuring the thickness of the protective layer of concrete for the upper reinforcement located along the digital axes and the total thickness of the concrete buildup equal to 50 mm. The thickness of the concrete should not depend on the existing deflection of the existing floor slab. A prerequisite after performing all the types of reinforcement work with additional reinforcement is the installation of tell-tales from individual rods with a diameter of 10 A240 mounted on welded studs. – use of concrete class B30, which according to the norms for Class 1 should exceed the strength of concrete reinforced slab.
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– use of normal Portland cement of a grade not lower than 400 to exclude the use of fast-hardening cements that have increased shrinkage. – use of a filler with a size of no more than 5 ÷ 10 mm with mandatory vibration by an area or poker vibrator. – use of a concrete mixture with a cone slump of at least 6-8 cm to ensure workability. – 1.0–1.5 h before laying new concrete, the concrete surface of the existing floor slab should be moistened using a spray. Do not allow accumulation of puddles of water in hackings and places of opening of the concrete protective layer. The concrete surface should be moist, but not wet. – concreting process should be continuous starting from the areas most remote from the concrete pump. – pours for concreting should be selected in such a way that the gap in concreting on the pours does not exceed the start time of concrete setti.
4 Conclusion The use of the above mentioned measures to ensure the joint operation of the existing reinforcement and the additional reinforcement in the slab, as well as “old” and “new” concrete, makes it possible to increase the load-bearing capacity of the reinforced floor (both in strength and deformability) and ensure further trouble-free operation of the facility in accordance with the functional purpose and requirements of current regulatory documents.
References 1. Muradyan VA, Zaguzov AD (2019) Comparison of the effectiveness of traditional and innovative methods of strengthening flexible racks with large eccentricities. Eng J Don 4(55):49 2. Serbinovsky PA, Mailyan DR (2016) Optimization of reinforcement structures of hollow floor slabs. Eng Bull Don 2(41):70 3. Aksenov VN, Mailyan DR (2008) Work of reinforced concrete columns made of high-strength concrete. Conc Reinf Conc 6:5–8 4. Polskoy P, Mailyan D, Georgiev S, Muradyan V (2018) The strength of com-pressed structures with cfrp materials reinforcement when exceeding the cross-section size. E3S Web of conferences. p 02060 5. Polskoy P, Georgiev S, Muradyan V, Shilov A (2018) The deformability of short pillars in various loading options and external composite reinforcement. MATEC Web Conf 196:02026. https:// doi.org/10.1051/matecconf/201819602026 6. Vinogradova EV (2012) Problems of quality management of concrete works. Eng Bull Don 3. http://ivdon.ru/magazine/archive/n3y2012/1001 (free access) 7. Zilberova IYu, Vysokovskaya LV (2012) Features of design in Russia. Eng Bull Don 3. http:// ivdon.ru/magazine/archive/n4p1y2012/1081 (free access) 8. John SS Oakland, Marton Marosszeky (2012) Total quality in the construction supply chain. Routledge 9. Huan Chen (2012) The quality risk management in residential building across the construction process. Dept Build Real Estate
Influence of Various Factors on the Strength of Oblique Section of Beams Reinforced with Double-Sided Composite Clamps Petr Polskoy
Abstract Most tests of beams reinforced with composite materials were carried out in the absence of initial inclined cracks. However, in real constructions, inclined cracks always take place. Therefore, they should affect the strength of the beams. This influence is greater the greater the width of the opening of these cracks. The type of reinforcement—double-sided or three-sided clamps—also affects the strength. Normally, they are combined into one group. To answer the question about the influence of the type of clamps, prototypes reinforced with these carbon fiber clamps were tested according to a single method. The paper presents the research results of the strength of oblique sections of reinforced concrete beams reinforced with doublesided carbon fiber clamps. The efficiency of composite reinforcement is estimated when the value of the cut span changes, which is equal to 1.5; 2 and 2.5h0 . At the same time, the degree of influence of the initial cracks on the bearing capacity of the oblique section was analyzed. Recommendations for taking into account the influence of the width of the initial inclined cracks on the strength of beams are proposed. Keywords Reinforced Concrete · Transport Infrastructure · Beam · Reinforcement · Composite Materials · Carbon Fiber · Inclined Sections · Clamps · Reinforcement
1 Introduction In recent years, Russia has been paying more and more attention to the use of composite materials in construction. It is the introduction of glass and carbon fiber plastics for the manufacture of various types of reinforcement in order to use it for internal and external reinforcement of structures. However, the introduction of everything new and progressive should be based on a broad experimental base. P. Polskoy (B) Don State Technical University, 1 Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_177
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Taking into account the above, the Department of Reinforced Concrete and Stone Structures of Don State Technical University continues comprehensive studies of structures, which began in 2012. The main part of this research has already been published in the open press not only in Russia, but also abroad. In particular, works [1, 2] provide data on the use of internal round glass and carbon fiber working reinforcement as the main one, or in complex reinforced structures with a different combination of steel and composite reinforcement. Works [3–6] is devoted to the study of the strength of normal cross-sections of reinforced concrete beams reinforced with external composite reinforcement, with different percentages of composite reinforcement. A large volume of research is associated with the reinforcement of compressed elements by external composite reinforcement under various types of stress–strain state. These are conventionally centrally compressed elements [7–9], as well as elements operating at small and large load application eccentricities [10, 11]. No less important are the issues related to the external reinforcement of the supporting sections of the beams under the action of transverse forces. These studies are partially reflected in [12]. In 2014, a set of rules for strengthening reinforced concrete structures with composite materials came into force in Russia. This regulatory document opened the way for the use of these materials as elements of external reinforcement when strengthening structures. However, this document does not provide answers to many questions, including controversial ones. We should note at the same time this is also characteristic of the rules of foreign countries. The controversial issues include, among others, issues related to the strengthening of oblique sections of beams by the action of transverse forces. In particular, this is due to the choice of composite reinforcement schemes for oblique sections with different values of the cut span and the presence or absence of initial cracks. According to SP 164.1325800.2014 “Strengthening of reinforced concrete structures by FRP composites. Regulation of design”, the magnitude of the transverse force Qfw perceived by the composite reinforcement is determined by the formula (1): Q f w = ψ f (A f w R f w sinα C f w )/S f
(1)
where the coefficient ψf, is used, which takes into account the type of transverse composite reinforcement. It is equal to 0.95 for closed clamps and has the same value equal to 0.85 for U-shaped and double-sided clamps. It is controversial that the same efficiency of their work is accepted for the types of clamps that differ in the degree of anchoring. However, everyone knows that the degree of participation of any reinforcement—working or transverse, largely depends on the length and quality of the anchorage zone. With oblique cracks on the tension side, the length of the anchorage zone of the double-sided clamps near the support is close to zero. By the middle of the cut zone, the anchoring gradually increases. However, near the point of application of force, it decreases again with the development of an oblique crack towards the action of a vertical load. For U-shaped
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clamps, there is always the problem of their anchoring in the tension side at the support of the beams. And there is no anchoring for double-sided clamps. Therefore, the answer to the question about the reality of the same value of the coefficient ψf can only be given by experiment.
2 Methods To evaluate the effectiveness of the work of clamps made of various types of composite materials, special experiments have been carried out using double-sided clamps and the results obtained were compared with the results of testing of beams reinforced with U-shaped clamps [7, 8]. To obtain reliable results, the samples were used, the design of which was similar to the previous ones. The reference samples without reinforcement were similar. The beams had a cross section of 125 × 250(h) and a length of 2.0 m. The estimated span was assumed to be 1.6 m. The longitudinal and transverse reinforcement was also the same. The working reinforcement was presented by 2Ø18 A500, and the mounting fittings were presented by 2Ø6 B500. Tied clamps were made of Ø3 B500 and installed in 150 mm increments on the supporting sections of the beams and in 200 mm increments in the simple bending zone. Figure 1 shows the construction of the frames for reference and reinforced samples. To strengthen the beams, single-layer double-sided clamps made of carbon fiber MBrace Fib CF 230/4900/800, 0.166 mm thick and 20 mm wide. The step of the
Fig. 1 Construction of frames for reference a and ordinary b prototypes
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Fig. 2 Layout of double-sided composite reinforcement clamps and tests at different cut spans
Fig. 3 Scheme of testing of experimental beams
composite clamps was 140 mm. The strength of these clamps according to the tensile test result was 3200 MPa. Figure 2 shows the scheme of composite reinforcement of the supporting sections of the beams. A total of 12 beams, or 25 prototypes, were tested, 6 of which were reference. Two samples had initial cracks at the section span a = 2h0 only on one of the supporting sections. The second supporting section was reinforced with a steel casing during the test. Figure 3 shows the scheme of reinforcement and testing of experimental beams. The reinforced experimental beams, as well as during the formation of cracks, were tested at three different cut spans—1.5, 2, and 2.5h0 . Each experimental beam was tested twice with a stepwise increasing load according to the scheme of a single-span pivotally supported beam loaded with two concentrated forces. Prior to testing the reinforced samples, one of the supporting sections was also reinforced with a steel casing, according to Fig. 3. After the destruction of one of the supporting sections, it was also reinforced with a steel casing, after which the beam was re-tested until the destruction of the second span section.
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This test procedure makes it possible to double the number of samples and, using the method of direct comparison of experimental data, to obtain reliable results with absolutely identical values of the strength of concrete, sections of steel, longitudinal and transverse reinforcement.
3 Results and Discussion The results of the strength tests show that the effectiveness of transverse composite strengthening by double-sided clamps, as in U-shaped clamps, depends on varied factors, namely: the presence or absence of initial oblique cracks, the span of the cut, which formed initial cracks and the reinforced samples were tested; composite cross clamps. Table 1 provides the comparison of the coefficients of composite reinforcement of the experimental samples reinforced with U-shaped and double-sided clamps with a change in the cross-section spans. The data in Table 1 show that the efficiency of composite reinforcement of oblique sections decreases with a decrease in the span cut. This is due to the fact that when the span cut changes from 2.0h0 to 1.5h0, the tensile strength of concrete gradually changes to the strength of concrete on the cut. Analyzing the effect of the type of clamps on the bearing capacity of the reinforced ∗ oblique section, using a direct comparison of the transverse force Q f,1 perceived by U-shaped clamps in samples with initial cracks with a similar value Q f,1 —samples without cracks show that the efficiency of composite reinforcement in beams with cracks is on average 31–37% lower. Table 1 Comparison of composite reinforcement coefficients of prototypes when changing the cut span Cut span at testing
Composite gain coefficient эт k f = Qred ult / ult Beams:
Average coefficient value kf
Q
1
2
3
4
5
6
1.281 1.078 1.223 1.159 1.424 1.117
1.339 1.007 1.234 1.029 1.307 1.053
1.39 1.154 1.309 1.049 1.309 1.307
1.24 1.048 1.266 1.136 1.374 1.024 1.165 − 1.195 1.036 1.226 −
Elements reinforced with U-shaped clamps 1.5h0 2.0h0 2.5h0
1.194 1.084 1.238 1.035 1.418 1.308
1.16 1.021 1.359 1.308 1.304 1.258
1.079 0.941 1.234 1.234 1.456 1.357
Elements reinforced with double-sided clamps 1.5h0 2.0h0 2.5h0
1.216 −
– –
1.114 −
–
–
–
–
–
1.129 1.066
1.262 1.004
–
–
–
1.21 −
1.243 −
–
–
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The samples reinforced with double-sided clamps with a similar comparison ∗ showed on average an even greater decrease in value Q f,2 , compared with the value Q f,2 , which was 80%. A direct comparison of the reinforcement options among themselves for elements ∗ ∗ Q f,1 /Q f,2 and Q f,1 /Q f,2 showed an even greater difference, especially for elements with initial cracks. In our opinion, this is due to two factors – the width of the initial cracks and the lack of sufficient length of the anchorage zone of the double-sided clamps, especially in beams with initial cracks, the trajectory of which can be either convex towards the compressed zone or concave towards the working reinforcement. In any case, in beams of relatively small height (in our case it is 250 mm), the distance from the crack to the end of the clamp will always be less than 150 mm. As a result, none of the double-sided clamps broke when the samples were destroyed. All this should be reflected in regulatory documents, i.e. it directly concerns the coefficient ψf, which takes into account the option of gluing of composite reinforcement elements. Assessing the effect of the width of the initial oblique cracks on the strength of reinforced elements, first of all, we note that the Set of Rules for strengthening reinforced concrete structures with composite materials does not stipulate the effect of the existing oblique cracks on the strength of oblique sections under the action of transverse forces. However, most structures have such cracks, because during operation they are at load levels that often exceed operational and is equal to 0.8 of their maximum value. At the same time, it should be noted that during the reconstruction of buildings, the layout of new equipment is repeatedly changed, which leads to the formation of new cracks already at other cross-section spans. And the presence of these cracks, especially with a width of more than 0.4–0.5 mm, should affect the effectiveness of reinforcement, in our case, composite one. The magnitude of the transverse force Q∗f 1 and Q∗f 2 , in elements with initial cracks, perceived by U-shaped and double-sided clamps is significantly less compared to similar variants of reinforcement of samples that do not have initial cracks. The efficiency of double-sided clamps in comparison with U-shaped ones in experimental samples with initial cracks is also lower. ∗ The magnitude of the transverse force Q f perceived by the external composite clamps decreases with an increase in the width of the initial cracks. It should also be noted that the bearing capacity of reinforced elements is influenced not only by the width of oblique cracks, but also by the level of load at which they are formed. The simultaneous dependence of the decrease in the efficiency of composite reinforcement is traced not only on the width of the cracks, but also on the reduction of the cut span. All of the above points to the need to take into account the initial cracks in the calculation of composite reinforcement elements. Comparing the efficiency of elements reinforced with U-shaped clamps, which do not have initial oblique cracks and tested at spans cut (2.0 and 2.5)h0 , we got almost the same values Q f 1 . With a value of a = 1.5h0 , the decrease was only 8.4%.
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The prototypes reinforced with vertical double-sided clamps showed almost the same effect of reinforcement, regardless of the length of the cut. However, in comparison with U-shaped clamps, their load-bearing capacity is much lower. The decrease, depending on the cut span, varies between 45–63% or on average is 55.5%. Vertical double-sided clamps with the initial oblique cracks formed during the cut span 2.0h0 , showed an even greater decrease in this coefficient, which is equal to ψf = 0.85* 0.19 = 0.16. It follows from this that the recommendations of the norms regarding double-sided clamps require adjustments. The explanation for this is quite objective. The reason lies in the constructive length of the anchorage zone of the clamps, or rather in its absence at a small height of the prototypes. In our opinion, the structural length of the anchorage zone should be at least 150 mm on both sides of the crack, especially with two oblique cracks, which often occur. The minimum height of beams reinforced with double-sided clamps increases to 450 mm. The second reason is the Sf gap between the composite clamps, consciously assumed to be 12 cm and twice the constructive gap equal to 3 Wf. From all of the above, it follows that double-sided clamps with a beam height of less than 450 mm are generally impractical with initial cracks with an width of more than 0.4 mm. For elements without initial cracks, the coefficient ψf should be reduced to an experimental value of 0.55.
4 Conclusion Taking into account all of the above, the following conclusions can be drawn. 1. The bearing capacity of oblique sections in our experiments turned out to be directly dependent on the amplification option. U-shaped clamps glued from bottom to top in the support area and from top to bottom in the area of concentrated loads turned out to be more rigid compared to vertical-double-sided ones, which is clearly seen by the nature of the destruction of oblique sections and by the magnitude of the transverse force perceived by the clamps. Compared with Ushaped ones, it is, on average, 55.5% lower, regardless of the cut span. The latter requires an adjustment of the coefficient ψ f for both reinforcement options. 2. The change in the cut span had a slight effect on the efficiency of composite reinforcement for double-sided clamps. It turned out to be almost the same for all values of the cut span. The U-shaped clamps showed almost the same, but there were higher values of the transverse force Qf perceived by the clamps at the cut span of 2.0 and 2.5h0 . With a value of a = 1.5h0 , the efficiency decreased by 8.4%. 3. The greatest effect on reducing the bearing capacity of oblique sections reinforced with external clamps was exerted by the width of oblique cracks of more than 0.6 mm. To a greater extent, this also applies to vertical double-sided clamps. The
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presence of oblique cracks with the specified width and even more negatively affects the work of reinforced concrete. 4. If there are initial cracks in the beams of low height with a width of 0.6 mm or more, the question arises about the expediency of using double-sided clamps. 5. In the presence of elements with initial oblique cracks, it is proposed to take into account their influence using the differentiated value of the coefficient ψ f = ψ ∗f , 2 determined by the formula: ψ f ∗ = 0, 85 − 0, 63 · acr c − 0, 07acr c . The proposed coefficient depends only on the width of oblique cracks, regardless of the size of the cut span 6. Vertical double-sided clamps at the height of the prototypes of 250 mm, do not confirm the same efficiency with U-shaped clamps. The values of the coefficient ψ f are proposed to be equal to ψ f = 0.9 and 0.6, respectively, for U-shaped clamps glued from top to bottom and double-sided clamps.
References 1. Mailyan DR, Polskoy PP, Mervat Kh, Kurgin KV (2013) About the question of deformability flexural elements of heavy concrete with the location carbon fiber and composite reinforcement in two rows. Eng J Don 4. ivdon.ru/magazine/archive/n4y2013/2096 2. Muradyan V, Mailyan D, Lyapin A, Chubarov V (2017) Energy-efficiency increase of reinforced concrete columns with recessed working fittings. IOP Conf Ser: Ear Environ Sci 90:012032 3. Polskoy PP, Mailyan DR, Dedukh DA, Georgiev SV (2016) Design of rein-forced concrete beams in case of change of cross section of composite strengthening reinforcement. Glob J Pure Appl Math 12:1767–1786 4. Demchenko DB, Mayatskaya IA, Fedchenko AE (2017) Strengthening of building structures with polymer composite materials. Solid State Phenom 265:91–96 5. Zagutin DS, Mayatskaya IA, Fedchenko AE (2017) Strengthening of the mini silo construction made of reinforced concrete blocks with carbon fiber lamellae. Solid State Phenom 265:86–90 6. Mayatskaya IA, Eremin VD, Fedchenko AE (2017) Prefabricated reinforced concrete structures and their reinforcement with polymer composite materials. Innovative technologies in solving technical problems: collection of articles of international scientific and practical. Conference, September 5:37–39 7. Granovsky AV, Kostenko AN, Molchanov AL (2007) Reinforcement of reinforced concrete columns of frame buildings in earthquake-prone areas using carbon fiber external reinforcement elements earthquake-resistant construction. Safety Struct 2:36–38 8. Shchutskiy VL, Nasevich AS, Chubarov VE, Blyagoz AM (2019) The research on bearing capacity of supports with annular section (Investigation of the bearing capacity of the annular cross-section compressive struts) CATPID-2019. IOP Conf Ser: Mater Sci Eng 698:022089. https://doi.org/10.1088/1757-899X/698/2/022089/ 9. Shchutskiy VL, Nasevich AS, Holodnyak MG, Blyagoz AM (2020) Strength, crack resistance and deformability of the power lines’ cylindrical supports. IOP Conf Ser: Mater Sci Eng 913:032075. https://doi.org/10.1088/1757-899X/913/3/032075. 10. Mailyan DR, Nesvetaev GV (2012) The dependence of the relative bearing capacity of the columns on the relative eccentricity 4–2(23):183 11. Aksenov NB, Aksenov VN (2017) Investigation of the work of compressed reinforced concrete elements made of high-strength concrete. Construction: new technologies – new equipment 1:27–31.
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12. Polskoy PP, Mailyan DR, Shilov AA (2019) The Cut Span Effect on the Beams Inclined Sections Strength Reinforced with External Composite Reinforcement. Materials Science Forum 974:633–637. https://www.scientific.net/MSF.974.633.
Optimization of Structure Parameters of Semi-trailer-tank for Hydraulic Fracturing of Formation Alexey Lebedev , Sergey Kireev , Marina Korchagina , and Andrey Efimov
Abstract A preliminary parametric model of a semi-trailer-tank for storage, loading, delivery of process liquids used during hydraulic fracturing in oil and gas wells has been developed. Studies of target parameters of metal consumption, rigidity and strength of profile sheet and tank design were carried out. Regression multifactor dependencies were built, including five variable geometric characteristics of tank parts, on the basis of which recommendations for multivariable design of such objects were developed. Processing of these numerical experiments was carried out using the method of multifactorial regression analysis with subsequent optimization of the obtained empirical dependencies to minimize metal consumption of the design. An example is given of optimizing the design parameters in order to obtain a minimum weight of the semi-trailer-tank. The optimal composition of the profile parameters of the tank skin sheet has been determined. Compared to the base version of the profile, the weight of one sheet is reduced by 10 kg. As a result of optimizing the tank parameters, the semitrailer weight was reduced by 414 kg compared to the original base version. Keywords Semi-trailer-tank · Transport infrastructure · Sheet profile rolled stock · Solid parametric model · Multivariable design · Regression analysis · Optimization
1 Introduction The practical application of fracturing techniques requires a large volume of water to be stored in the tank in the immediate vicinity of the well. Therefore, the task of designing semi-trailers for the prompt delivery of as large tanks as possible to the well is an important and relevant task in the oil and gas complex [1]. In the process of designing a semi-trailer tank, the problems of optimal combination of strength, stiffness and material capacity of parts and assemblies of the structure [2, 3] are solved. In this case, as a rule, an analysis of a large number of A. Lebedev (B) · S. Kireev · M. Korchagina · A. Efimov Don State Technical University, 1, Gagarin Sq., 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_178
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permissible versions of combinations of various design parameters is carried out. The use of computer solid-state models of the plant significantly expands the possibilities of multivariable design and subsequent optimization of the result by the overall, weight or strength characteristics of the machine [4, 5]. When designing process machines that include massive sheet structures for storing liquids, the problem of assessing the strength, stiffness and metal consumption of sheet metal parts always arises [6–8]. The covering of the case of a tank consists of welded among themselves and on beams of profile metal sheets from the alloyed steel 09G2S. The search for the standard of the Russian Federation for profile bent sheets, unfortunately, did not lead to success. The most suitable is GOST R 24,046– 2004(RU), which regulates the dimensions of sheet shaped rolled stock up to 4,5 mm thick. However, this standard does not contain sheet profile size information. In another GOST R document 24,045–2016(RU) there are dimensions of the sheet profile, but for thin sheets up to 1.5 mm thick. To design the shell of the tank body with a volume of up to 80 m3 , a profile sheet with a thickness of about 5 mm is required and for it there are no recommendations on the size of the profile sheet in domestic standards. The search for the optimal variant of the profile sheet of the tank shell can also be carried out by means of computer simulation, which will allow to determine effective versions of the sheet profile, reducing the cost of physical experiments [9–13]. Examples of computer modeling of similar technical objects are considered in works [14–16]. The purpose of the study is to optimize the material capacity of the semi-trailertank structure for storage of liquid of 80 m3 volume based on the analysis of relationships of structural parameters of tank parts. The objectives of the study are to develop solid-state models of the shell sheet of the tank walls and other equipment of the semi-trailer-tank. Models of tank parts shall be made taking into account the target and changing parameters to be developed. Develop a multi-variance tank design methodology to optimize the minimum material capacity based on the stiffness and strength limitations of the entire structure.
2 Methods A parametric model based on the ratios presented by the diagram (Fig. 1) has been developed to carry out studies of the profile sheet of the tank skin. Enter the following values: L—half the width of the sheet (mm); b is the width of the sheet profile projection (mm); h—height of sheet profile protrusion (mm); α—angle of sheet profile trapezium side inclination, (degree). If you specify the initial parameters L, b, h, α, then the value of the width of the depression a is a=
L − 1.5 · b − 3 · h · tg(α) 1.5
(1)
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Fig. 1 Diagram for calculating the geometry of the shell sheet profile
The parametric model of the skin sheet is based on the relations presented. Figure 2 shows examples of how to obtain profile sheets when changing model parameters. The preliminary calculation determines that for one version of the sheet profile geometry, a thickness change of 1 mm entails a change in the total weight of the semi-trailer structure by about 650 kg. Studies of sheet strength and stiffness were carried out in a CAD system. The “Fasteners” were set to the fixed state of the peripheral faces of the profile sheet. Sheet loading conditions were simulated by setting gravity and uneven pressure on one side of the sheet to 13,000 N/m2 (specific water pressure per 1 m2 of sheet area). The calculation type is static linear. An example of the stress and displacement pattern obtained for the profile sheet with the dimensions of Fig. 2 is shown in Fig. 3. Target parameters of profile sheet studies are: Y1 —sheet weight (kg), which characterizes the metal intensity of the tank design. Let’s choose this target parameter as the main one, that is, subject to unconditional minimization. The remaining target parameters in our task will be considered as limitations.
Fig. 2 Epures of equivalent stresses a and total displacements b of profile sheet under action of unevenly distributed load and gravity
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Fig. 3 Arrangement of semi-trailer-tank structure PTs-80. 1; 1—semi-trailer chassis; 2—tank; 3— manifold unit; 4—side manifold. 5—inspection hatch; 6—breathing valve; 7—rear platform with fencing; 8—rear staircase; 9- hatch; 10—level meter
Y2 —the largest sheet deflection (mm), which characterizes the rigidity of the tank skin. Since the rigidity of the structure directly affects the reliability of the welded joints, the parameter should be limited to 30 mm for the case when the distance from the lower to the upper edge of the bulge or dent is no more than 3000 mm. The length of the sheet is 2600 mm. Y3 —equivalent stress by Mises (MPa), which characterizes the strength of the tank walls. The parameter shall be limited to ensure that the yield stress (220 MPa) for the sheet material is not exceeded. Considering the stock, we assign the condition Y3 < 50 MPa. The numerical values of the target parameters are recorded using the appropriate sensors in the CAD system. The composition of the variable factors for the profile sheet studies is shown in Table 1. The established ranges of variation of each X1…X3 factor ensure the operability of the parametric model without loss of geometric shape and sheet stability. The number of factor levels, assuming the nonlinear form of their effect on the objective function, is proposed to choose three—the minimum, average and maximum level. This means that the number of calculated experiments for three factors will be N = 33 = 27. Each factor is set at its own level in the equation table of the parametric model of the profile sheet. Consider the composition of deliberately unchanged factors during the experiment. It is proposed to fix factor Z1—thickness of profile sheet (mm) at the level Table 1 Composition and ranges of changes factors X 1 … X 3 No.
Name of factor
Levels variations
Units of measure
1
X 1 —width of profile protrusion
100–150–200
mm
2
X 2 —angle of profile inclination
10–25–40
degree
3
X 3 —profile depth
20–50–80
mm
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of 5 mm. Of course, this factor greatly affects the selected target parameters of our facility. It is proposed to carry out a study of this effect when studying the entire model of a semi-trailer-tank, and in this study to focus on the influence of the geometric parameters of the sheet profile. Therefore, the sheet thickness factor remains unchanged. The experiment is carried out on a sheet model with constant dimensions of width Z2 = 1080 mm and height Z3 = 2600 mm. These are dimensions of profile sheets installed on a semi-trailer-tank. The sheet model is examined with the same finite element mesh parameters under the same anchoring and external load conditions. A design model of the semi-trailer-tank (Fig. 3) has been developed to carry out studies of metal consumption, stiffness and strength of the tank. Tank 2 is installed on chassis 1 of semi-trailer through 10 mm gasket from conveyor belt, the frame of which is welded by means of horizontal and vertical beams from rectangular profile 80 × 120 GOST8645-68 (RU). The side, front and rear walls of the tank are sheathed with sheet metal with a special profile. The floor and ceiling of the tank are sheathed with sheet metal according to GOST 19,904–90(RU). Unit of receiving and output manifolds 3 is installed in front part of tank. Bottom valve serves for final cleaning of tank from liquid by means of side manifold 4. Inspection hatch 7 is installed on the left side of the tank. Two breathing valves 6 for tank vessel ventilation are installed on tank roof. The rear platform 7 of the tank is covered with a fence and covered with a sheet with anti-slip coating according to GOST R 34,180 – 2017(RU). Access to the landing using stair 8. Through the hatch 9 you can get inside the tank through the inner ladder to service the inner surfaces of the tank. Tank filling level is monitored using level gauge 10. Studies of the strength and rigidity of tank parts were carried out in the CAD system. The fixed condition of the wheel axles of the semi-trailer-tank chassis was set as “Attachments.“ Sheet loading conditions were simulated by setting gravity and uneven pressure on tank walls to 13,000 N/m2 (specific water pressure per 1 m2 of sheet area). The calculation type is static linear. The target parameters of tank design studies are: Y4 —the total weight of the semi-trailer-tank (kg), characterizing the metal consumption of the entire structure. This target parameter is principal, i.e. subject to minimization. The remaining target parameters in our task will be considered as limitations. Parameter measurement is carried out in the CAD system when analyzing the mass characteristics of a parametric sketched tank model. Y5 —the greatest deflection of the tank skin sheet (mm), which characterizes the rigidity of the tank skin. Since the rigidity of the structure directly affects the reliability of the welded joints, the parameter should be limited to 30 mm. Y6— equivalent stress by Mises (MPa), which characterizes the strength of the tank parts. The parameter shall be limited by the condition of guaranteed non-exceeding yield stresses (220 MPa) for materials of tank parts. The parameters of variable factors for tank studies are given in Table 2. The number of factor levels, assuming the nonlinear form of their influence on the target parameters, is proposed to choose four. This means that the number of
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Table 2 Ranges of varying factors for tank studies No.
Name of factor
Levels variations
Units of measure
1
X 4 —thickness of profile sheet of tank
4–5–6–7
mm
2
X 5 —thickness of tank rectangular beam
5–6–7–8
mm
calculated experiments for three factors will be N = 24 = 16. Factors are set at selected levels by setting parameters in the semi-trailer-tank model. The experiment is carried out on a semi-trailer-tank model in which all dimensions (except variable), interfaces and materials are constant. The semi-trailer-tank model shall be examined under the same parameters of the finite element grid under the same conditions of fixation and application of external loads. Processing of these numerical experiments was carried out using the method of multifactorial regression analysis with subsequent optimization of the obtained empirical dependencies to minimize metal consumption of the design.
3 Results The results of the profile sheet model studies are shown in Table 3. Since the obtained regression relationships use coded factors, in setting the problem we include restrictions on the values of varying factors X1 , X2 , X3 in the range from -1 to + 1. We accept that in the problem it is necessary to minimize the function Y1 (X1 , X2 , X3 ) of the sheet weight. The movement function Y2 (X1 , X2 , X3 ) is limited to 30 mm. The stress function Y3 (X1 , X2 , X3 ) is limited to 50 MPa. As a result of solving the problem, a set of optimal levels of variable factors is obtained, but in coded form: x1 = 0.284; x2 = 1; x3 = -1. In decoded form, the values of factors: X1 = 164.2 mm; X2 = 40°; X3 = 20 mm. With this set of factors, we Table 3 Regression analysis results for Y 1 -Y 3 parameters Model coefficients
Y1 Factor
Significance
Y2
B0
129.72
Yes
4.95
Yes
33,53
Yes
B1 ·X 1
0
No
-0.047
No
-3,45
Yes
B2 ·X 2
-6.63
Yes
-0.098
No
-0,87
Yes
B3 ·X 3
12.12
Yes
-4.89
Yes
-21,18
Yes
B4 ·X 1 X 2
0
No
Yes
2,14
Yes
B5 ·X 1 X 3
0
No
0.374
Yes
4,04
Yes
B6 ·X 2 X 3
-3.52
Yes
0.44
Yes
2,32
Yes
B7 ·X 1 X 2 X 3
0
No
-0.155
No
-0,58
No
F(P0.95) = 1.98
F p = 2898
Factor
0.365
Y3 Significance
F p = 5.76
Factor
Significance
F p = 7.71
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Table 4 Results of the semi-trailer-tank experiment Model coefficients
Y4 Factor
Significance
Y5
B0
8190
Yes
7.87
Yes
87,9
Yes
B1 *X 4
945.3
Yes
-1.52
Yes
-56,6
Yes
B2 *X 5
342.5
Yes
-1.11
Yes
B3 *X 4 X 5
7.35
Yes
-0.14
No
B4 *X 4 2
26.57
Yes
-0.83
Yes
B5 *X 5 2
-3.23
No
0.1
No
F(P0.95) = 1.98
F p = 2898
Factor
Y6 Significance
F p = 5.76
Factor
-8,64 3,67 28,2 1,66
Significance
Yes Yes Yes No
F p = 7.71
obtain the following values of the target parameters of the study: Y1 = 114,5 kg; Y2 = 9.4 mm; Y3 = 50 MPa. Thus, as a result of optimization, a reduction of the material capacity of the sheet by 10 kg with respect to the base value is achieved. In the following study we apply the obtained set of optimal parameters of tank sheet profile. The results of the semitrailer-tank model studies are given in Table 4. So, as a result of solving the problem, a set of optimal levels of variable factors is obtained, but in the encoded form: x1 = 0.752; x2 = 0.444. After reverse coding, we get X4 = 6.62 mm; X5 = 7.16 mm; With this set of factors, we obtain the following values of the target parameters of the study: Y1 = 9069 kg; Y2 = 5.73 mm; Y3 = 60 MPa—stress at the point of maximum displacement of the sheet under load. Thus, as a result of optimization, savings can be obtained by reducing the material capacity of the tank relative to the base value of the weight of the semi-trailer-tank by 414 kg.
4 Discussion Analysis of regression dependencies (Table 3) shows the following: All constructed dependencies adequately describe the process with a probability of 0.95. This is seen by the condition FP0,95 < Fp. The sheet weight parameter (Y1 ) is most directly influenced by the depth of the profile (X3 ) and the most backward influenced by the angle of the profile (X2 ). The combined effect of the two depth and profile angle factors (X2 X3 ) has a significant inverse effect. The width factor of the protrusion (X1 ) is recognized as insignificant both in individual influences and in interactions with other factors. Thus, to minimize sheet weight, a separate study is required by optimizing the resulting regression relationship. The movement parameter (Y2 ) is most significantly affected by the profile depth (X3 ). The angle of the profile (X2 ) shows a significant direct influence in interaction
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with X1 and X3 . The width of the protrusion (X1 ) also exhibits a significant direct influence in interaction with X2 and X3 . Thus, unambiguously it is very difficult to tell about simple increase or decrease in levels of factors for an exit to an optimum profile on an indicator of movement of Y2 . Therefore, it is necessary to set and solve the optimization problem. All three factors have a significant inverse effect on the stress parameter at the point of maximum displacement of sheet points (Y3 ). The strength of the sheet is most affected by the depth factor of the profile. With double interaction, factors already have a significant direct effect. The joint influence of the three factors is insignificant. Thus, as for the parameter Y2 it is necessary to set and solve the optimization problem. Studies on the semi-trailer-tank model (Table 4) show: All constructed dependencies adequately describe the process with a probability of 0,95. This can be seen by the condition FP0.95 < Fp. The weight parameter of the tank semitrailer (Y4 ) is most directly influenced by the thickness of the tank wall sheet (X1 ). The thickness of the beam walls (X2 ) also has a direct and significant effect. The product of the factors and the square of the first factor also has a direct and significant effect on the weight of the tank. Thus, to minimize weight, two factors must be set to minimum values. The thickness of the tank wall sheet (X1 ) has the most significant inverse effect on the displacement parameter of the tank walls of the semi-trailer (Y2 ). The thickness of the beam walls (X2 ) also has an inverse and significant effect. The product of the factors and the square of the second factor has little effect on the movement of Y2 . The square of the sheet thickness has a significant inverse effect on the movement. Thus, to increase the stiffness of the tank parts, the weight of the tank requires the installation of two factors at maximum values. The stress parameter in the tank parts of the semi-trailer-tank (Y3 ) is most significantly affected by the thickness of the tank wall sheet (X1 ). The thickness of the beam walls (X2 ) also has an inverse and significant effect. The product of the factors and the square of the first factor has a significant direct effect on Y3 . The square of the beam thickness has little effect on the Y2 . Thus, to increase the strength of the tank parts, the weight of the tank requires the installation of two factors at maximum values. To solve the main problem of reducing the material capacity of the half-trailer-tank design, the obtained ratios were applied within the framework of one optimization problem, in which the minimum function Y4 is defined, and the functions Y5 and Y6 are limited.
5 Conclusion 1. The resulting regression relationships were analyzed for the extent and direction of influence of each variable factor and their interactions. It has been found that the most significant factor is the depth factor of the sheet profile. The contradictory influence of factors and their interactions on the selected target parameters of the
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object of research led to the need to optimize the profile parameters of the tank shell sheet of the semitrailer tank. 2. In the optimization task, the main sheet weight is selected from the three target parameters. The remaining target parameters—hardness and strength of the sheet, were set in the form of restrictions. In such an arrangement, the optimal profile of the tank skin sheet is determined. Compared to the base version of the profile, the weight of one sheet is reduced by 10 kg. 3. The resulting regression relationships were analyzed for the extent and direction of influence of each variable factor and their interactions. It has been found that the most significant factor is the sheet thickness factor. The conflicting influence of factors and their interactions on the selected target parameters of the object of research led to the need to optimize the parameters of the tank parts of the semitrailer tank. 4. In the optimization task, the main one is selected from the three target parameters—the weight of the tank. The remaining target parameters—the stiffness and strength of the tank wall, were set in the form of restrictions. This setting defines the optimum sheet thickness and tank beam wall values. As a result of optimization, the weight of the semi-trailer was reduced by 414 kg compared to the original base version.
References 1. Nosachev SV, Chuveiko MV, Zhukova MY, Kuzin GA, Khozyaev IA (2018) Effects of deformation dynamics in problems of heavy transport. MATEC Web Conf. https://doi.org/10.1051/ matecconf/201822602006 2. Kasyanov V, Deryushev V, Kosenko E, Kosenko V, Golubeva AY (2018) Synthesis of methods and principles of ensuring the reliability of one-off and serial production machines. MATEC Web Conf. https://doi.org/10.1051/matecconf/201822402106 3. Badalyan LK, Kurdjukov VN, Ovcharenko AM (2018) Assessment of car emission masses at the change of kinetic energy of the engine—transport vehicle system. https://doi.org/10.1051/ matecconf/201822604041 4. Efimov AV, Kireev SO, Korchagina MV (2018) The efficiency is a single criterion for choosing the type of interaxle drive. MATEC Web Conf. https://doi.org/10.1051/matecconf/201822 604002 5. Lemeshko MA, Molev MD, Iliev AG (2018) Adaptive drive of the technological machine with two working movements of the executive body. MATEC Web Conf. https://doi.org/10.1051/ matecconf/201822602014 6. Kaderov KK, Kireev SO, Korchagina MV, Osipuk AY (2018) Improved seals in pipelines and high-pressure hoses. Russian Eng Res 38(3):241–243. https://doi.org/10.3103/S1068798X180 30061 7. Mailyan DR, Trufanova EV (2016) Planning of multilayer cylindrical wall reservoirs. Procedia Eng. https://doi.org/10.1016/j.proeng.2016.07.193 8. Kaderov K, Kireev S, Korchagina M, Lebedev (2020) A Determination of technological parameters and tool for flanging holes from sheet blanks. E3S Web Conf 164:14019. https://doi.org/ 10.1007/978-981-16-3844-2_10 9. Lemeshko M, Molev M, Golovin I (2018) Hydraulic technological machines with adaptive drive structure. MATEC Web Conf. https://doi.org/10.1051/matecconf/201822402087
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10. Ivanov Y, Pakhomov V, Kambulov S, Rudoi D (2018) Determination of the parameters of the hydrodynamic mixer. MATEC Web Conf. https://doi.org/10.1051/matecconf/201822405023 11. Rybak AT, Temirkanov AR, Lyakhnitskaya OV (2018) Dynamics of synchronous hydromechanical drive in mobile machine. Russian Eng Res. https://doi.org/10.3103/S1068798X180 90253 12. Kaderov KK, Korchagina MV, Kireev SO, Nikishenko SL (2018) Solution of problems of gasketing of joints of units of machines and equipment of oil and gas enterprises when in use in high- and low-temperature regimes. Chem Petrol Eng. https://doi.org/10.1007/s10556-0180461-8 13. Rybak AT, Temirkanov AR, Lyakhnitskaya OV (2018) Synchronous hydromechanical drive of a mobile machine. Russian Eng Res. https://doi.org/10.3103/S1068798X18030206 14. Lapshin VP, Turkin IA (2017) Modeling tractive effort torque of wheel in deformation movements of pneumatic tire wheel. Procedia Eng. https://doi.org/10.1016/j.proeng.2017. 10.522 15. Ovchinnikov NA, Zhigulsky VI, Kozyreva EA, Chefranova OV (2017) Modeling and estimate of the strain-stress state of a bus body pillar with account for geometrical nonlinearity. ARPN J Eng Appl Sci. https://www.scopus.com/inward/record.url?eid=2-s2.0-85015224140&partne rID=40&md5=8d5793552517df70f8f493a4689ec682 16. Panasyuk LN, Kravchenko GM, Matua VP (2018) Numerical method for solving the problems of the building structures dynamics with a mobile massive load. Mater Sci Forum. https://doi. org/10.4028/www.scientific.net/MSF.931.72
Development of Methods for Controlling the Chip Form via Intensified Chip Curling in the Cross-Sectional Plane Stanislav Mikhailov
and Nikolai Kovelenov
Abstract A new direction is defined for the development of methods to control the chip form via intensified chip curling in the cross-sectional plane. Additional rotation of the chip in the transverse plane offers the way to effectively control the rotation angle of the chip helix axis relative to the cutting plane, as well as to regulate chip diameter and helix pitch. A calculation method to design the chipbreaker elements of the tool with variable geometry parameters along the cutting edge has been developed, which provides an approach to design complex-shaped indexable cutting inserts with regard to the transverse rotation of the chip. Altered parameters of spatial chip curling lead to improved chip flow conditions and better reliability of chip breaking. Keywords Workpiece cutting · Transport infrastructure · Tool design · Indexable cutting inserts · Chip breaking · Spatial chip curling
1 Introduction Advances in machining are primarily brought about by the automation of processing operations, the use of CNC machine tools, automated machine sets, and flexible production systems. The problem of predicting and controlling the chip form is one of the most relevant among those that affect organization of cutting operations in automated production. Technical assurance of accuracy, quality and productivity of cutting largely depends on conditions for removing chips from the cutting zone. Any interruption to continuous chip removal can cause many problems, up to chip
S. Mikhailov (B) · N. Kovelenov Kostroma State University, 17 Dzerzhinskogo Street, Kostroma 156005, Russia e-mail: [email protected] Peter the Great Saint-Petersburg Polytechnic University, 29 Polytechnicheskaya Street, 195251 Saint-Petersburg, Russia Virial LTD., 27 Engelsa Pr., 194156 Saint-Petersburg, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_179
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jamming and tool failure. The chip evacuation is typically ensured by careful selection of cutting conditions and cutter geometry of the tool. Setting up reasonable conditions for chip formation is usually based on production experience or time- and effort-intensive experimentation. The empirical approach is not conducive to development of clearer guidelines for application of various chip form management techniques, reducing machining efficiency of the tools based on indexable cutting inserts (ICIs), limiting the development of new tool designs, and hindering the progress of automated systems for designing processing operations and cutting tools.
2 Methods The ability of chip to curl and break depends on many factors. The necessary prerequisites for chip breaking are: Stability of the chip form under constant cutting conditions, stable chip-barrier contact, high chip rigidity and low chip flexibility. The mechanism that governs the influence of cutting process conditions on these factors is complex, and, despite extensive research, has not been thoroughly studied. Additionally, to date there have been developed a large number of methods and devices aimed at solving the problem of obtaining a favorable chip form. Vast practical experience has been accumulated for some of these methods. The problem is actively discussed in both national and international journals. The most prominent research in this area includes the works of K. Nakayama, N. Fang, X. Yang, J. Okida [1–4]. Among Russian scientists, the greatest contribution to the development of the theory of chip formation was made by G.L. Kufarev, V.F. Bez’yazychnyi, S. Mikhailov among other researchers [5–7]. Analysis and systematization of research showed that the problem could be split into two: Management of chip curling and control of chip breaking. Conversely, the solution to the problem of chip breaking is founded on the tasks of modeling and controlling the chip form. In natural chip curling the main trends are curling in the tool rake plane and in the chip flow plane. Predominant effect on chip form (as it forms during cutting) exerted by the chip rotation direction led to establishment of two independent areas of research into the process of chip formation, their subjects being 1) processes of chip curling in tool rake plane, and 2) in the main secant plane. Most of the published works ascribe paramount importance in obtaining a stable chip form and optimal chip dimensions to the methods of chip curling in a plane normal to the tool rake. Almost all commercially available cutting inserts for turning applications are made with a curved rake designed to curl the chip in the chip flow plane.
3 Discussion A common disadvantage of the known cutting inserts with chip-curler elements is the limited ability to control chip flow. When using standard ICIs, chip is formed under
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predominant impact of two rotational movements: In the tool rake plane, and in the main secant plane normal thereto. Superposition of these two rotational movements results in forming a spiral-shaped chip with main axis located in a plane parallel to the cutting plane. Kinematic analysis of the chip flow shows, that when cutting with a tool with a complex curved rake (with rake angle and chip-curler groove being variable along the cutting edge), the chip form is additionally influenced by the rotation of the chip in its cross-sectional plane, ωs . Experimental assessment of the degree of influence of ωs on the chip form is difficult. Therefore, the analytical method is used as the basis for the study of spatial curling of shavings with three rotational movements. When cutting with a tool with a complex curved rake featuring variable rake angle along the cutting edge and variable profile of the chip-curler groove, the chip f is additionally influenced by its rotation in the cross-sectional plane ωs. Transverse curling of the chip is caused by non-uniform plastic deformations in the primary shear zone caused by variable chip flow conditions along the primary cutting edge of the tool (Fig. 1). Due to inhomogeneous deformation along the width of the cut layer, caused by the variable rake angle and variable profile of the chip-curling groove along the cutting
Fig. 1 Transverse curling diagram and overall view of the chip with predominant rotation ωs
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edge, the longitudinal layers of the chip exiting from the cutting zone have different curvature and flow direction. When chip separates from the tool rake, there arise variable normal components of the chip velocity υc.n: υc.n (x) = νc (x) sin[ρ(x)]
(1)
where υc (x) and ρ(x) are the velocities of the longitudinal chip layers, and the function governing variation of the rake angles of the chip flow along the line of chip separation from the tool, respectively. As a result, in addition to rotational movements in the rake plane and in the plane normal to the cutting edge, the chip takes additional rotation around the axis parallel to the direction of the chip flow off the tool. With a uniform change in the normal component of the chip velocity νc.c = k · x, the expression for the angular velocity of the transverse chip rotation could take the form: ωs =
vc.c · sinρc b2
(2)
where vc.c is the chip speed in point C; ρc —variation of the rake angle of the chip flow along the line of its separation from the tool rake; b2 —chip width. Change in the flow direction of the longitudinal layers of the chip along the cutting → v c.c , „ of the average edge is defined by the angle ρc formed by the vectors vc.o , − initial chip flow speed in the extreme planes of its longitudinal sections corresponding to points O and C. If we ignore the lateral chip curling (having little effect on the angle ρc ), one could assume lo = lc = lcp , and β1.o = β1.c = β1.cp , where, lcp , β1.cp are the average (over width) chip-cutter contact lengths and inclination angle of the conditional shear surface. In this case, the value of ρc for any shape of the chip-curler surface on the tool could be calculated by: l ·cos β −γ l ·cos β −γ ρc = ar csin cp (Rn.c1.cp c ) − sin β1.cp − γc − −ar csin cp (Rn.o1.cp o ) −sin β1.cp − γo .
(3)
The resulting expression is applicable for any chip-curler shape on the tool surface. The values of the chip curvature radii Rn.c (o) , the tool-chip contact length lav, and the angle of inclination of the conditional shear surface, featuring in Eq. (3), are defined by the cutting process conditions and tool rake geometry [7]. It follows from Eq. (3) that rake angle γ which is variable along the cutting edge, has maximum effect on ρs , and, consequently, on ωs , see Fig. 2. The shape of the chip-curler groove has an indirect effect on the rotation ωs via change in the angle of inclination of the shear surface β1.cp , the tool-chip contact length lav, and chip curvature radii Rn.c , Rn.o . Through adjusting the tool rake geometry it is possible to control not only the value, but also the direction of rotation ωs , and, consequently, to influence the direction of the chip flow off the tool (see
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Fig. 2 Influence of tool rake geometry on ωs
Fig. 3). Altered parameters of spatial chip curling lead to higher chip stiffness and more reliable chip fragmentation [8]. These conclusions are well supported experimentally by the appearance of the chips formed when cutting with a tool with a helical rake with both positive and negative gradient of the rake angle. An accurate quantitative verification of the particular relationships to calculate ωs is difficult, due to overlapping effects of the chip flow conditions (variable along the cutting edge) on both transverse and lateral curling of the chip. The rotational movement of the chip, like any solid body, corresponds to a straightline law governing the change in the speed of movement of its points. Therefore, for optimal chip-curling conditions in the cross-sectional plane of the chip, the normal
Fig. 3 Effect of ωs on the natural chip form (δs = 15°, ωn /υ = 0.1 mm−1 )
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components of the chip flow speed υn at the moment of chip separation from the tool rake should be variable along the chip width, according to the following equation: vc.n =
v · sinρc ·x b2
(4)
where x is the Cartesian axis aligned with the line of separation of the chip from the tool. According to Eq. (3), the law governing the variation of the angle ρc (x) along the chip width depends on the nature of the change in the chip curvature radius Rn (x) and rake angle γ(x) along the cutting edge of the tool: l ·cos β −γ (x)) lcp ·cos (β1.cp −γo ) − sin β − γ − −ar csin ρ(x) = ar csin cp (Rn1.cp (x) 1.cp Rn.o (x) −sin β1.cp − γo . (5) Substituting Eqs. (3–5) into Eq. (1), one obtains: ⎡
⎤
lcp ·cos (β1.cp −γ (x)) − sin β1.cp − γ (x) R (x) n sin ⎣ ⎦ l ·cos β −γ −ar csin cp (Rn.o1.cp o ) − sin β1.cp − γo ⎡ ⎤ lcp ·cos (β1.cp −γc ) ar csin − sin β − γ 1.cp c Rn (x) = bx2 sin ⎣ ⎦ l ·cos β −γ − − ar csin cp (Rn.o1.cp o ) − sin β1.cp − γo ar csin
(6)
It is established that the chip curvature radius Rn depends on the shape and dimensions of the chip-curling surface of the tool [7]. For example, for a tool with a flat step L n −lcp Rn = tg(ψ , for a tool with a groove Rn = Rk , where Ln is the distance between n / 2) the step and the cutting edge of the tool, ψn is the angle of inclination of the step relative to the tool rake. Consequently, the relationship governing the change in υn along the width of the chip is defined by the geometric parameters of the chip-curler surface in the main secant planes. Substituting the expressions for Rn into Eq. (6), we obtain general relationships for calculating the optimal combination of geometric parameters of the chip-curler tool surfaces to achieve transverse chip rotation. The obtained relationships enable one to determine the optimal laws of changing one or more parameters of the chip-curler surface of the tool along the cutting edge. To verify Eq. (6) we consider a particular case of cutting with a tool with a variable rake angle without any special chip-curling elements (see Fig. 4). If we consider only the tool geometry parameters, the normal components of the chip flow speed vn shall be: vc.n (x) = vc.M · sin(γ (x) − γ A )
(7)
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Fig. 4 Diagram to determine the law of changing the rake angle γ along the primary cutting edge
The straight-line law of variation of vc.n (x) is guaranteed if the condition vc.n (x) = a + cx is satisfied, where coefficients a and c are determined from the boundary conditions of chip formation. At point A: x = 0, vc,n = 0, a = 0. At point M: x = b1, vc.n = vc.M · sin(γ M − γ A ). Hence vc.M · sin(γ M − γ A ) = c · b1 , c =
vc.M · sin(γ M − γ A ) , b1
(8)
After substitution, we get: vc.n (x) =
vc.M · sin(γ M − γ A ) ·x b1
(9)
By equating (7) to (9), we find
γ (x) = ar csin
sin(γ M − γ A ) · x + γA b1
(10)
Equation (10) sets the optimal law of change in the rake angle along the cutting edge, and can be presented as a particular solution to the multi-parameter problem of optimizing the tool chip-curler surface. A special subroutine has been developed for rational design of the tool geometry, taking into account the transverse chip rotation, the said subroutine integrated into the “PrognosChip” software for computerized prediction the chip form. The subroutine is designed for calculation of the optimal cutter rake design for various processing conditions and chip curler control schemes. The results of relationship analysis show that effective control of the chip flow could be achieved by providing a chip-curler surface shaped as a groove with variable curvature along the cutting edge. For a groove-based chip control scheme, the condition of a straight-linear change in the
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velocity gradient along the chip width, dvn /dx = const, corresponding to the optimal chip curling parameters, is met by providing ICI with the chip-curler surface featuring variable curvature radius along the cutting edge, said radius being governed by inverse arcsine law. Depending on the desired chip form, the chip-curler surface can have a form of a groove with a curvature radius increasing or decreasing with distance from the insert tip, or, alternatively, chip curler can feature variable cross-section geometry changing from a concave circular arc to a convex one. With sufficient ICI strength its rake is made in such a way that the rake angles and curvature radii of chipcurler cross-sections in the main secant planes of the plate simultaneously increase or decrease with distance from the insert tip [9]. Creation of a variable rake angle, which changes synchronously with the chip-curler groove’ radius of curvature, improves chip evacuation from the cutting zone via additional chip curling in its cross-sectional plane and lateral plane.
4 Conclusion A technique has been developed for the optimizing calculation of the chip-former elements with variable parameters along the cutting edge, enabling the design of ICIs with improved chip evacuation from the processing zone. The proposed technique to control the transverse chip curling could be used to improve the design of the assembled cutting tools. A new direction is defined for the development of methods to control the chip form via intensified chip curling in the cross-sectional plane. Contrary to the conventional chip curling control techniques, additional rotation of the chip in the transverse plane offers the way to effectively control the rotation angle of the chip helix axis relative to the cutting plane, as well as to regulate chip diameter and helix pitch. By changing the parameters of the spatial chip curling, the chipbreaking efficiency can be significantly improved. The established relationships of spatial chip formation can be used to obtain favorable chip form, including for the most problematic operations with a limited space available for chip, for example, in hole drilling and boring operations.
References 1. Yang X, Marx T, Zimmermann M, Hagen H, Aurich JC (2011) Virtual Reality animation of chip formation during turning. Adv Mater Res 223:203–211. https://doi.org/10.4028/www.sci entific.net/AMR.223.203 2. Devotta A, Beno T, Ronnie L, Espes E (2015) Quantitative characterization of chip morphology using computed tomography in orthogonal turning process. Procedia CIRP 33:299–304. https:// doi.org/10.1016/j.procir.2015.06.053
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3. Okida J, Tayama T, Shimamoto Y (2016) Application of chip formation simulation to development of cutting tools. Sei Tech Rev 82:46–51. https://global-sei.com/technology/tr/bn82/pdf/ 82-08.pdf 4. Astakhov VP (2010) Geometry of single-point turning tools and drills. Fundamentals and practical applications. Springer, London. https://doi.org/10.1007/978-1-84996-053-3 5. Mikhailov SV, Kovelenov NY, Bolotskikh SV (2018) Simulation of chip formation and fracture in the design of complex turning inserts. Russ Eng Res 38(7):566–572 6. Vorontsov AL, Sultan-Zade NM, Albagachiev AYu (2008) Development of a new theory of cutting 5. Determining the kinematic, stress, and strain states of the blank. Russ Eng Res 28(5):461–471 7. Mikhailov SV, Danilov SN (2013) Helical-chip disintegration in the turning of plastic materials. Russ Eng Res 33(3):176–178. https://doi.org/10.3103/S1068798X13030131 8. Oleinik AP (2016) Kinematic model for spatial chip curving when cutting with a tool featuring variable rake profile. Metalloobrabotka Publ 1(91):2–8 9. Oleinik AP (2010) Morphological analysis of the rake surfaces of metal-cutting inserts based on modeling and classification of continuous chip forms. Mach Tools Tools 8:11–16
Development and Industrial Testing of a Method for Assessing the Deformation Properties of a Fixed Soil Massif Albert Prokopov
and Ilya Sychev
Abstract The are some actual problems in designing, construction and operation of buildings and structures based on subsident soils. The main points are: to search for the most relevant method and justification of the parameters of the soil base clamp; to ensure the relevance of physical and mechanical characteristics of the clumped soil mass and, finally, to keep on the quality. The development of an effective method for controlling the consolidation of subsidence soils of the foundation during new construction in regard to simultaneous determination of rational technological parameters of clamping at the control plot and stamp tests of the clamped body in order to determine the actual modulus of soil deformation. Keywords Subsidence soil · Cementation · Transport infrastructure · Stamp tests · Deformation and strength characteristics
1 Introduction The ensuring of the operational reliability and safety of facilities during natural and anthropogenic flooding is one of the main problems at all stages of design, construction and operation of buildings and structures on subsident soils. The subsidence phenomena occur in case of certain humidity, thereby causing the irregular vertical deformations of foundations and ground bearing structures. This leads to significant violations of building structures up to the loss of stability of the building or structure. Modern regulatory documents require the mandatory application of measures to reduce or completely eliminate the subsidence properties of the foundation soils in order to avoid such a negative impact. One of the most effective methods of eliminating the subsidence properties of soils being widespread in the Rostov region as well as in other regions of Southern Russia is the method of cementation of soils based on injection of cement or cement-sand liquid through drilled wells [1–4]. However, the complexity and insufficient accuracy of existing system of quality control is the A. Prokopov (B) · I. Sychev Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_180
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main issue of denial for this method application. This article describes the results of industrial testing of a new patented device, which allows to inject a liquid to clamp the soil base directly on the plot ground of the construction site with further control stamp tests being carried out to determine the deformation characteristics of the clamped soil mass at periods of both natural humidity and conditions of full water saturation. Also, there is an innovatively proposed method for the deformational characteristics’ estimation of a clamped soil base. The article also presents the results of experimental studies of factors, which affect the final results of clamp. The main purpose of the study is to develop a new integrated approach with a test bench for quality control of the clamped base, as well as to study its actual support in regard to the factors that affect the final deformation characteristics of the soil. Here are the issued tasks of this research: 1. Development of a test bench and a relevantly based method, which allows to accurately control the deformation modulus of the clamped soil both in natural and water-saturated states. 2. Experimental studies on several objects with different initial (natural) deformation modulus of subsident soil of the influence of the percentage of its reinforcement on the modulus of total deformation of the clamped soil. 3. Statistical processing of experimental data results and determination of multiple correlation between the percentage of soil reinforcement, initial and final modulus of total deformation. 4. Verification of the convergence of the results obtained by the theoretical equation and experimental data.
2 Materials and Methods The main task in the design of the test bench was covering a much larger area of the test area than in stated one by GOST 20,276–2012 in case of standard stamps. The dimensions of the new stamp should be located symmetrically relative to them with coverage of several injection wells. So, the load on the clamped body will be equally distributed. Another important task was to study changes in the deformation properties of the body during the injection of cement mortar, as well as to estimate the dependence of the modulus of deformation of the mortar on the percentage of reinforcement. The percentage of reinforcement of the soil mass is the volume ratio of clamping liquid to the total volume of the soil. As for the Rostov region [1–4], the percentage of reinforcement ranges from 6 to 16%, while the volume of the clamping composition and the corresponding decrease in porosity and increase in soil density sufficiently impacts on partial or complete elimination of the subsidence properties out of the body. With a reinforcement percentage of A < 6%, the reinforcement will be inefficient. The reinforcement at A > 16% usually leads to overspend of the liquid without a significant increase in the deformation modulus. Moreover, this percentage leads
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Fig. 1 The schematic design of the test bench for studying the deformation modulus of a clamped ground base with a non–standard stamp: a—plan; b—section; 1, 2—the main (2 pcs.) and secondary (4 pcs.) metal support joists; 3—hydraulic jack; 4—pumping station; 5—anchor screw steel piles (8 pcs.); 6—reinforced concrete stamp; 7—technological holes in the stamp for mortar injecting; 8—deformation measurement system
to technological difficulties associated with the need to significantly increase the injection pressure to ensure the design injection of the liquid. Since during clamping it is important to obtain soil with the required deformation modulus both in the natural state (with natural humidity) and in case of partial or complete water saturation of the soil mass, the experimental conditions and the test bench should be accounted with possibility of body soaking with water filtration through the entire clamped strata with power being initially equally assumed to the power of the subsidence soil layer. The design of the test bench was developed and patented in regard to the tasks above [Sychev I V, Targimanov M A Patent 160,099 of the Russian Federation. A device for testing soils reinforced with cement-sand grout, Publ. 03/10/2016. Bull. №7.]. It is shown in Fig. 1. The industrial testing of the developed method with a non-standard square stamp sized of 2.4 × 2.4 m and experimental studies on the effect of the reinforcement percentage on the modulus of general deformation were carried out on the construction site at the facility “Reconstruction of MBUZ “City Hospital No. 1 named after N.A. Semashko, Rostov-on-Don” with the construction of a unified building for surgical and therapeutic department, as well as the administrative block” (Fig. 2). The high accuracy provided by a large stamp area of 5.76 m2 (a square with a side of 2.4 m) is the main advantage of the proposed test method. This stamp, unlike the standard ones (with an area of 0.06—0.5 m2 ), covers the clamping zone of 4 injection wells at least and eliminates accidental errors caused by irregular distribution of the liquid over the square space and depth. The planned dimensions of the stamp are comparable or even equal to the dimensions of the sole, for example, typical isolated footing for columns of framev buildings, therefore, the provided tests
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c) Fig. 2 The industrial test of method for assessing the deformation properties of a clamped soil mass with a non–standard stamp: a—installation of a reinforced concrete stamp with main and secondary support joists; b—fixing of support joists with metal screw piles; c—installation of a jack with a pumping station and a deformation measuring system
make it possible to practically repeat the operation of the “foundation—clamped foundation soil” system in original scale. There will no possible errors caused by the up-scaling effect. So, it is possible to determine the actual filter cake arising under the foundation foot. The thickness of the stamp was also significantly more valued than for standard ones, and amounted to 600 mm due to the structural strength and protection from pushing, as well as ensuring the required rigidity and high accuracy of measuring vertical deformations of the soil under the stamp. The pressure on the stamp was created by a hydraulic jack DG200P150 with a maximum force of 200 t. The pressure adjustment was managed by a hydraulic station with manual control, whereas the control was held by a pressure gauge
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MA100VU100 (Fig. 2, c). A distinctive feature of the stamp is the presence of 4 symmetrical technological holes formed by embedded parts as metal pipes with a diameter of 89 mm. During the test, the cement-sand liquid was injected through these pipes via metal injectors with a diameter of 70–80 mm and length which is relevant to the depth of the current cover drill round of cementation. The support joints were fixed with metal screw piles (2 on each side of the main joints) to create rigidity of the bearing support of the main and secondary joints (Fig. 2, a) and the proof from significant pulling loads transmitted from the jack. The depth of the piles and the diameter of their blades were based on the excess of their bearing capacity to the pulling forces per each pile. The number of 8 screw piles with a length of 10 m each were required to perceive the load in the engineering-geological and technical conditions of the experiment. The parameters of injection at the test site were valued according to the soil clamping project, based on the physical, mechanical and deformation properties of the base soils: pressure—from 0.2 to 0.9 MPa, the working liquid was prepared with the proportion of C:P:V as 1:2:1. A partial exit of the liquid to the surface was recorded during the pumping at the first cover drill round. Then the position of the drillstring anchor was adjusted according to the well’s depth, and the injection of the liquid was successfully completed in regard to the designed volume. The stamp tests of the soil base were performed after the set of the design strength of the liquid in order to control the quality of soil consolidation and check the elimination of subsidence properties of soils. The soil was pre-soaked through drainage wells with a diameter of 300 mm in accordance with GOST 20,276–2012. Soaking for the entire subsidence thickness (up to a depth of 17.5 m) lasted 4 weeks until the soils reached the degree of water saturation in amount of Sr ≥ 0.8. The humidity and the degree of water saturation during soaking were determined as a result of a complex of drilling wells, sampling soil and determining their humidity by the standard weight method. The test of the clamped body with a stamp was carried out in accordance with GOST 20,276–2012 to determine the deformation modulus in the water-saturated state of Esat. The deformations were measured via a set of flexometers 6PAO. The deformation modulus was calculated with the use of the Schleicher-Boussinesq method. The above experiment was performed on several objects with different initial modules of soil deformation in the soaked state in order to study the effect of the reinforcement percentage on the modulus of total deformation of the clamped soil.
3 Results The dependence graphs were calculated based on the tests’ results of the deformation modulus of the fixed soil ER, MPa, on the percentage of reinforcement A, % for various values of the initial modulus of total deformation in the water-saturated state
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E0, which varies from 3 to 10 MPa for engineering and geological conditions of the Rostov region (Fig. 3). So, there is a correlation field in the form of a surface in order to determine both the type of multivariable correlation and the type of function ER = f (E0; A), (Fig. 4). There is a nonlinear correlation between the studied parameters. While the nonlinearity is observed with a percentage of reinforcement from 8 to 16%, the maximum increment of the soil deformation modulus is noted with an increase in the percentage
Fig. 3 The dependence graphs of the deformation modulus of fixed soils on the percentage of reinforcement
Fig. 4 The graph of points determining the dependence of the modulus of deformation of fixed soils on the initial modulus of deformation of the soil and the percentage of reinforcement (6–16%)
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of reinforcement from 8 to 12%, followed by a decrease in the growth rate. This effect is explained by an increase in the percentage of reinforcement, the decreased number of pores, thereby increasing the deformation modulus. However, the porosity decreases slowly with a certain saturation of the soil with a liquid, leading to a slower increase of the deformation modulus is observed. With a reinforcement percentage of A = 16%, the clamped soil modulus ER varies from 15 to 22 MPa in regard to the initial deformation modulus, which is sufficient for most buildings and structures designed on strip or slab foundations based on an artificial subgrade. Increasing the percentage of a reinforcement A above 16% is technically and economically impractical. The design on a pile foundation [5–8] or other methods of eliminating subsidence soils and increasing their deformation characteristics are reasonable according to the conditions of limiting the maximum precipitation [9–12]. According to the form of the curved surface (Fig. 3), the dependence ER = f (E0; A) can be described by the equation of the surface of the 2nd order of the general form: ER = aA2 + bE02 + cAE0 + dA + eE0 + f, where a, b, c, d, e, f—unknown ratios of approximation. Here are the values of the coefficients via the method of least squares (OLS): a = 2, 552 · 10 − 3, b = −0, 148, c = −9, 67 · 10 − 5, d = 0, 863, e = 3, 043, f = −5, 973
The third term does not affect the final result. The equation of dependence ER = f (E0; A) can be written with sufficient accuracy: ER = 2, 552 · 0 − 3A2 − 0, 148E02 + 0, 863A + 3, 043E0 − 5, 973 where ER is the deformation modulus of the clamped soil, MPa; E0 is the deformation modulus of the initial soil, MPa; A is the percentage of soil reinforcement with cement (cement–sand) mortar, %. The evaluation of the accuracy of the obtained equation shows that the average relative excursion between the theoretical values and the experimental data obtained from 42 test results is 8.5%, and the correlation ratio is close to 1. This indicates the reliability of the obtained equation.
4 Discussion Based on the conducted research, the following conclusions are made: 1. Most of the methods used in modern practice for assessing and controlling the quality of clamping subsidence soils have significant drawbacks that do not allow to
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reliably assess the deformation characteristics of the clamped soil mass that serves as the foundation of buildings and structures. This is primarily due to the chaotic distribution of the cores of cement-sand mortar in the clamped body and the irregular deformation characteristics, both in plan and depth of the clamping site. The standard stamps have dimensions that do not allow for such an irregular distribution of the properties of the base soil, which leads to a number of different errors. 2. The proposed experimental stand has an increased stamp area which is comparable to the area of the sole of real isolated footing and continuous footing foundations. This feature allows the most adequate and reliable assessment of the deformation modulus of the soil base after clamping by cementation, while the design of the stand allows to investigate the effect of the percentage of soil reinforcement on the deformation modulus of the clamped soil, both at natural humidity and water-saturated condition (when Sr > 0.8). 3. The industrial testing of the experimental stand was carried out successfully in terms of clamping soils at stages of construction and reconstruction in Rostovon-Don. It showed high accuracy and reliability of the results of measuring the deformation characteristics of the soil mass clamped by the cementation method. 4. As a result of the conducted experimental studies, there are a non-linear relation of the deformation modulus of the clamped soil base ER on the percentage of reinforcement A and the initial deformation modulus E0. These functions are described with high accuracy and reliability by the equation of the surface of the 2nd order of the general form. The average relative excursion of theoretical and experimental data is 8.5%. The correlation ratio is close to 1.
References 1. Nesterov IV, Smirnova OV, Merzliakova AD (2020) Software implementation of algorithms in jet grouting technology. In: Proceedings of the 2020 IEEE international conference quality management, transport and information security, information technologies, pp 395–399. https:// doi.org/10.1109/ITQMIS51053.2020.9322954. 2. Prokopov A, Prokopova M, Rubtsova Y (2017) The experience of strengthening subsidence of the soil under the existing building in the city of Rostov-on-Don. MATEC Web Conf 106:02001. https://doi.org/10.1051/matecconf/201710602001 3. Cheng L, Shahin MA, Mujah D (2017) Influence of key environmental conditions on microbially induced cementation for soil stabilization. J Geotech Geoenviron Eng—ASCE 143(1):04016083.https://doi.org/10.1061/(ASCE)GT.1943-5606.0001586 4. Prokopov A, Shuiskii A, Shcherban E, Zhur V (2020) Prediction of deformations in the subsiding soils of Eastern Donbass’ undermined areas. E3S Web Conf 164:07002. https:// doi.org/10.1051/e3sconf/202016407002 5. Akopyan V, Akopyan A (2016) Experimental and theoretical investigation of the interaction of the reinforced concrete screw piles with the surrounding soil. Proc Eng 150:2202–2207. https://doi.org/10.1016/j.proeng.2016.07.264 6. Veshnyakov VA (2020) Investigation of ground and foundation vibrations of an existing building during impact pile driving. IOP Conf Ser: Mater Sci Eng 945:012055. https://doi. org/10.1088/1757-899X/945/1/012055
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7. Moayedi H, Nazir R, Ghareh S (2018) Performance analysis of a piled raft foundation system of varying pile lengths in controlling angular distortion. Soil Mech Found Eng 55(4):265–269. https://doi.org/10.1007/s11204-018-9535-z 8. Mirsayapov I, Khasanov R, Safin D (2021) Ensuring the stability of the deep pit enclosure and foundation bases in the conditions of reconstruction of the architectural monument in the city of Kazan. E3S Web Conf 274:3022 https://doi.org/10.1051/e3sconf/202127403022 9. Shakirov I (2021) Bearing capacity of piles in a rein‘forced by pressure cementation soil massif. E3S Web of Conferences: 2nd International Scientific Conference on Socio-Technical Construction and Civil Engineering (STCCE—2021) 274:3023. https://doi.org/10.1051/e3s conf/202127403023 10. Cui M-J, Zheng J-J, Zhang R-J, Lai H-J (2020) Soil bio-cementation using an improved 2-step injection method. Arab J Geosci 13(23):1–9. https://doi.org/10.1007/s12517-020-06168-y 11. Dolzhikov P, Prokopov A, Akopyan V (2018) Foundation deformations modeling in underworking and hydroactivated rocks. In: Murgul V, Popovic Z (eds) International scientific conference energy management of municipal transportation facilities and transport EMMFT 2017, vol 692. Advances in Intelligent Systems and Computing. Springer, Cham, pp 647–654. https:// doi.org/10.1007/978-3-319-70987-1_69 12. Lv Q, Wu Z, Wang S, Wang D (2014) Water stability mechanism of silicification grouted loess. Bull Eng Geol Environ 73(4):1025–1035. https://doi.org/10.1007/s10064-014-0646-0
The Main Approaches to Defining the Boundaries of Agglomerations of Large Cities (Including Using the Capabilities of Big Data Mobile Network Operators) Dmitry Chebotarev Abstract The urbanization and trends in the spatial development of the settlement system require comprehensive research and analysis in order to find the most effective methods of management, sustainable development of the territory and improving the living conditions. The agglomerations are one of the most complex and developed forms of settlement. They are the points of growth and opportunities in most spheres of manifestation of the human community (economy, industry, culture, science). The stated fields attract special interest and a request for their research, both from urban scientists and from the administrative-state systems. One of the applied research tasks facing scientists and urban planning practitioners is to determine the boundaries within which the agglomeration effect is observed as realistically as possible. And one of the most reliable methods for studying the nature and parameters of population movement is the method of determining movements via “big Data” networks and stations of cellular mobile operators. Keywords Urbanization · Urban planning studies · Agglomeration · Geoinformation systems · BIG DATA · GIS · Transport accessibility · Territorial planning documents · Master plan · Cellular operators of mobile networks · Geospatial analysis · Sustainable development · Delimitation
1 Introduction The classical definition of the term agglomeration (from Latin agglomerare — to attach, to accumulate) is defined as a compact set of urban settlements (the most developed forms of settlement), being united by intensive industrial, labor, cultural, logistical and recreational ties [1]. In modern Federal legislation, the concept of “agglomeration” is used in a number of documents, but is not legally fixed. It is not used in federal laws and does not have a clear definition. D. Chebotarev (B) Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_181
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This concept is present and actively applied in the Spatial Development Strategy of the Russian Federation despite the fact that the draft Federal Law “About Urban Agglomerations” prepared by the Ministry of Economic Development of the Russian Federation is currently under approval. Currently, the Government of the Russian Federation is working on the development of an updated Strategy for the social and economic development of the Russian Federation until 2030. The balanced spatial development of the country, providing for the implementation of the initiative (project) “Cities of great Opportunities” is one of the strategic directions of Russia is. One of the points of this initiative is to ensure balanced spatial development through the creation of “territories of opportunity” for large agglomerations. The Ministry of Finance of the Russian Federation is working on proposals to create financial incentives for the development of the infrastructure of agglomerations as territories of advanced development and points of economic growth in order to solve this issue [2]. There are intensive actions on a regional level in the field of legislative initiatives, as well as the development of urban planning documents and research work on the definition and legislative consolidation of the boundaries of urban agglomerations. These points are necessary to enter the list of 40 presented agglomerations in the strategy. The desire of regional and municipal authorities to enter the National Project “Safe and high-quality Roads” is the most effective incentive for the work and legislative consolidation of the boundaries of urban agglomerations. There is a separate item, which provides funding for the development of road infrastructure of urban agglomerations. The agglomeration nature of the development of spatial urban formations contributes to a significant increase in the level of concentration and complexity of connections of various types of activities, creates a multiplicative effect, increasing the possibilities of engineering, transport and social services of the territory [3].
2 Materials and Methods The Main Approaches to Define the Boundaries of Agglomerations of Large Cities One of the tasks of the regional and municipal authorities (related with the legal registration of the agglomeration status) is to determine the real boundaries of the functioning for the agglomeration type of interaction of urban formations (the outer area of the agglomeration falling into the zone of gravity of the agglomeration core). The delimitation of agglomerations determines the actual number of people living in the particular one. Agglomerations can be an object of empirical and theoretical research, as well as an object of planning, design and management, which is impossible without solving the issue of boundaries’ definition [4]. The task of searching the ways of promising
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development of intermunicipal agglomeration formations is becoming more and more demanding in modern urban planning practice. The analysis of theoretical methods and practical approaches for determining the external boundaries of agglomeration (territories with an agglomeration effect) that have developed in domestic science and practice indicates a fairly wide range of main features (criteria) [5]. Some of the methods proposed by scientists of the Institute of Geography of the Russian Academy of Sciences and the CNIIEP of Urban Planning can be used for this task by determining the level of development of an urban agglomeration. A number of indicators are determined: population size and density, agglomeration ratio and agglomeration index, transport accessibility of the central core of the agglomeration [6, 7]. An analysis of the existing practice of recent years on the delimitation of the agglomeration territory indicates that this research is held via several basic methods: • Calculation of transport accessibility of the center (core) of the agglomeration (an isochron with 1.5–2— hour availability is taken as the base indicator); • Determination of the light imprint boundary using remote sensing data (analysis of night satellite images); • Analysis of satellite images to identify the most urbanized areas in the zone of influence of the proposed agglomeration; • Analysis of population density of various agglomeration territories. • Analysis of economic, production and logistics links within the study area and their indicators; • Determination of the volume of pendulum migration (daily and periodic movements of the economically active population) between cities and other settlements; • Determination of the amount and form of migration within the proposed boundaries of the agglomeration using “Big Data” networks and stations of mobile operators. This tool is innovative and has not been widely used for research in Russia yet. This method is highlighted in a separate paragraph and will be discussed in detail. Practice shows that initiated by administrative methods (in most cases by the administrative apparatus of regions or municipalities), the determination of the territory for an agglomeration often correspond to formal points with a maximum of two methods (criteria) being used. These methods are applied on the administrative map regarding the internal political processes and economic practicality, with no evidence-based information. Determining the boundaries of the agglomeration territory is a complex task that requires the use of several methods described above, complex studies in regard to a variety of criteria to obtain the most realistic and reliable picture.
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The author of this article has his own design experience in the preparation of urban planning documentation and on the analysis of domestic practice on the delimitation of the territory of agglomerations. He considers this research to be carried out within the framework of the following documents: • When developing documents of territorial planning at the regional level (as part of the preparation of the stage of the concept of spatial planning of the subject of the Russian Federation); • As part of the development of the social and economic development strategy of the region (for example, Stavropol Territory); • Within the framework of a separate research on the spatial development of the agglomeration territory; • Within the framework of international or state-wide competitions for the development of a Master Plan for the territory of several municipalities included in the proposed border of the agglomeration, usually supervised by regional authorities. It is necessary to carry out work on determining quantitative indicators of people’s movement between the core of the agglomeration and its suburban (peripheral) zone due to the fact that one of the necessary criteria for the agglomeration in the study area is the intensive pendulum migration (daily and periodic trips of the population), as well as identifying a differentiated distribution of migration volumes in accordance with actual locations. The method of determining migration via “big data” (Big Data) networks and stations of cellular mobile operators is suitable for this urban planning task. This approach has been used in our country for some time and has become one of the most accurate, regarding the right data processing algorithms. In practice, this method was used to determine the boundaries of the emerging Kazan, Kama and Almetyevsk agglomerations in the Republic of Tatarstan [8]. Also, it was used in Moscow, St. Petersburg and a number of other regions. The author of this article was a participant of the team of authors of OOO “SPA “Southern Urban Planning Center”, who had been working in the research project “The concept of the project of making changes to the territorial planning scheme of the Ivanovo region”. There are recommendations and suggestions for making changes to the territorial planning scheme of the Ivanovo region”, as well as in the further work on the development of urban planning documentation “Making changes (correction) of the territorial planning scheme of the Ivanovo region”. The rearrangements in the territory’s boundary according to Ivanovo agglomeration’s configuration were justified with a use of these documents by the author of this article [9, 10].
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3 Results The Approaches and Main Stages of Defining the Boundaries of Agglomeration Using “Big Data” Networks and Stations of Mobile Operators There are following research tasks being set as a part of the research in accordance with the customer’s wishes, as well as the need to analyze the planning structure of the Ivanovo region, and proposals for the spatial development of the territory: • Determination of the boundaries of agglomeration (agglomeration gravity zone) of the regional center—Ivanovo; • Determination of the volume of migration and its main directions, as well as geographical localization. In the course of the study, the movements of subscribers of mobile operators were studied, according to data provided by the federal mobile operator PJSC “Megafon”. Firstly, it was necessary to determine the goal (final result) required for the study (format and volume of necessary data). The mobile operator provides a service for geospatial analysis of “Big Data” for the formation of analytical reports on the dynamics of mobility of the population of various territorial zones in the territory of an administrative-territorial entity based on aggregated data in accordance with the contract and the terms of reference. It is necessary to prepare vector layers of the geoinformation system in a wellknown and widespread projection (in this case, the WGS-84 projection was used) containing data on the boundaries and the name of the studied territory in the context of municipalities, or another system of division of the territory as the initial data for determining the boundaries within which geospatial analysis is necessary (Fig. 1). Each location (administrative-territorial unit) has a unique cipher (number) defined in the attribute information. This cipher is subsequently verified according to the received data. Secondly, the customer and the mobile operator determine the requirement for analytical reports, which specify the criteria, structure and form of data provision. For this study, the time range for data has been determined as one month in September 2019. The type of geo-analytical report is a matrix (table), with the conditional name “Home - Work”, containing the following necessary fields: 1. The analyzed territory is a code of the Russian National Classification of Municipalities (RNCM), with defined “Zone of residence” and its “Subscribers”; 2. The name of the settlement in the Ivanovo region, where the “Zone of residence” of Subscribers is defined. 3. The longitude of the center of the analyzed quadrant in the territory- the “Zone of residence” of Subscribers; 4. The latitude of the center of the analyzed quadrant in the territory- the “Zone of residence” of Subscribers;
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Fig. 1 A vector layer of a geoinformation system containing data on the coordinated boundaries of an administrative territorial division with associated attribute information
5. RNCM code of the municipality of the Russian Federation, where the “Work area” is defined; 6. The name of the municipality where the Subscribers’ “Work Area” is defined; 7. The name of the settlement in the Ivanovo region, where the “Work zone” of Subscribers is defined; 8. The number of Subscribers living in the quadrant (“Living Area”) in the Ivanovo region and working in the quadrant (“Work zone”). The geo-analytical reports should be generated based on processing of technological events at the Operator’s base stations in accordance with the methodology of processing data on events of the mobile radiotelephone network. They should also be generated based on high-boundary zones and boundaries of administrative-territorial division or other type of differentiation of the territory. The data of the “Home-Work” matrix is processed and analyzed after receiving the geo-analytical report. A numerical value (number of subscribers) is determined for each location and these parameters are entered in the corresponding column of attribute data of the vector layer of the geoinformation system. According to Fig. 2 the location of the quadrant centers within the boundaries of locations, the frequency and dimension of which (quadrants) is determined taking into account the technical capabilities of the Operator in the corresponding territory. As a result of the subsequent application of geoinformation analysis tools, there is a “heat map” of the highest concentration of localized zones. The number of migrations between these zones and the agglomeration center was the highest (Fig. 3). The determination of population density and a number of other research activities and techniques (not included in the list given in this article), proposals were formulated to determine the boundary of the Ivanovo agglomeration based on the research
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Fig. 2 The location of quadrants within the boundaries of locations (formed according to the analytical report) in the Ivanovo region
Fig. 3 The localization of zones with the largest number of workers and students making daily pendulum migrations to the center (core) of the Ivanovo agglomeration
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Fig. 4 The proposals for determining the boundaries of the agglomeration of the center of Ivanovo region, in regard to the administrative-territorial structure
in combination with the calculation of the 1.5-h isochronal of transport accessibility. There is a considered number of 4 urban districts and 30 municipalities in 6 districts with a total population of 644,718, which is 64.2% of the total population of the Ivanovo region (Fig. 4). As a result, the obtained data was then applied to the development of materials for the territorial planning scheme of the Ivanovo region, as well as for the justification of a number of measures for the spatial and socio-economic development of the region.
4 Discussion Now we can propose an algorithm and a sequence of steps within this method according to the recent analysis of study’s results to determine the boundaries of the urban agglomeration: • Defining the goal and setting the task; • Development of technical specifications with a mobile operator; • Determination of the required form and content of the requested analytical information according to the task’s criteria;
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• Preparation of the initial vector layers in the geoinformation system (determination of the boundaries and degree of separation of the studied territory into the required number of locations); • Processing of the results of the analytical report received from the mobile operator; • Loading the obtained results of preliminary data processing into the vector and attribute format of the geoinformation system; • Application of geoinformation analysis tools in GIS software products (preparation of cartograms, diagrams illustrating the results obtained); • Formulation of conclusions and recommendations on the conducted research. Thus, this approach gives us a precise determination of the parameters and localization of the daily pendulum migration of the population (due to labor, educational and cultural purposes) within the boundaries of the studied territory. And finally, this method serves in the determination of the impact of the agglomeration center’s boundary.
5 Conclusion The definition of the actual existed boundaries of urban agglomerations should be a part of a comprehensive study that includes various methods and techniques, such as calculating the transport accessibility of the central core, in regard to the characteristics of the existed transport infrastructure, as well as the analysis of population density. And the list goes on with social, economic and industrial relations with a use of cartographic and geoinformation techniques. These methods can be characterized as traditional and practically proven techniques. Modern innovative technologies make it possible to supplement and significantly expand the research tools of an urban planner. The method of determining the migrations of the population using “Big Data” networks and stations of cellular mobile operators allows us to determine the actual indicators of pendulum migration and a complex system of intra-agglomeration migration with a high degree of accuracy and reliability.
References 1. Shmidt AB, Antonyuk VS, Francini A (2016) urban agglomerations in regional development: theoretical, methodological and applied aspects. Econ Reg 12(3):776–789. https://doi.org/10. 17059/2016-3-14 2. https://minfin.gov.ru/ru/document/?id_4=133245-pismo_minfina_rossii_ot_04.05.2021__0601-2934273_zapros_predlozhenii_subektov_rossiiskoi_federatsii_po_vozmozhnym_napravl eniyam_stimulirovaniya_razvitiya_infrastruktury_v_go 3. Kashin AV, Kravets AV (2017) Agglomeration processes and prospects of innovative development of the regional economy (on the example of the Novosibirsk region). Creat Econ 11(3):399–408. https://doi.org/10.18334/ce.11.3.37700
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4. Monastyrskaya ME, Peslyak OA (2019) Methodology for determining the boundaries of urban agglomerations. Bull V.G Shukhov BSTU 1:111–121. https://doi.org/10.12737/article_5c73 fc21703586.16507052 5. Monastyrskaya ME, Peslyak OA (2017) Modern methods of delimiting the boundaries of urban agglomerations (European science and practice). Urban Plann Archit 3(28):80–86 6. Lappo G, Polyan P, Selivanova T (2007) Agglomerations of Russia in the XXI century//Bulletin of the Regional Development Fund of the Irkutsk region 1:45–52 7. Kozhevnikov SA (2018) Agglomeration processes in the European North of Russia: experience of the Vologda region. Regionology 26(4):718–741. https://doi.org/10.15507/2413-1407.105. 026.201804.718-741. 8. Epstein MM, Pustovalova EA (2017) Defining the boundaries of agglomerations and calculating the volume of migrations on the example of the Tatarstan Republic. Socio-economic issues of development and functioning of transport systems of cities and their zones of impact: materials of the XXIII international (XXVI Yekaterinburg, I Minsk) scientific and practical conference, Minsk, June 16–17, 2017, BNTU, pp 139–147 9. Prokhorov AYu, Trukhachev SYu, Trukhachev YuN, Batunova EYu, Kryukova VV, Khokhlachev RV, Chebotarev DV (2019.) The concept of the project of making changes to the territorial planning scheme of the Ivanovo region. Recommendations and suggestions for making changes to the territorial planning scheme of the Ivanovo region. R&D report (final): 22–2019/OOO «SPA «URGC» pp 147–951 10. Chebotarev DV (2021) Transformation of the regional settlement system and the factors affecting the spatial development in the Ivanovo region. IOP conference series: materials science and engineering, international scientific conference “construction and architecture: theory and practice of innovative development” (CATPID 2020) 16th- 17th December 2020, Nalchik, Russian Federation, D. V. Chebotarev IOP Conference Series: Materials Science and Engineering vol 1083, p 012021. https://doi.org/10.1088/1757-899X/1083/1/012021
Warehouse Buildings Made of Wood Gennadiy Verzhbovsky
and Filipp Chervyakov
Abstract Foreign construction technologies find their application in Russia, but their wide application is hindered by differences in the requirements of domestic and foreign regulatory documents for the design and construction of construction projects. Thus, simple copying of solutions turns out to be impossible and construction organizations are forced to make changes to the designs associated with the processing of components and parts, the replacement of materials and the adjustment of design schemes. All of the above fully applies to wooden buildings and structures. At present, warehouse buildings with a frame made of sawn timber are being erected in Russia. They are widely used in agriculture. A construction organization from the city of Kirov produces sets of frameworks for warehouses for various purposes and performs the construction of facilities. The design of structures is carried out taking into account the requirements of domestic standards, with the involvement of specialists from the Don State Technical University. This approach ensures compliance with the requirements of domestic building codes and regulations, and hence the reliability of the structures being built. The article discusses the issues of design, construction and design of warehouse buildings with a wooden frame, describes a calculator developed to facilitate the design process, and also provides examples of actually built objects. Keywords Transport Infrastructure · Warehouse building · Timber · Lumber · Trusses on the metal toothed plates (MTP)
G. Verzhbovsky (B) Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] F. Chervyakov OOO «Stroysya Vyatka», 39, Mira Street, 610000 Kirov, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_182
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1 Introduction Warehouse buildings with a timber frame are in demand at certain span intervals. At the same time, a simple attempt to transfer Western technologies to Russia turns out to be impossible due to the restrictions imposed on the design by domestic regulatory documents. The article presents the results of the design, construction and engineering of such buildings taking into account a limited range of lumber.
2 Materials and Methods Hall-type buildings with open interior spaces are in demand all over the world. Their field of application is warehouses, hangars, exhibition and sports halls, municipal garages, various defense facilities, etc. The spans and length of such facilities vary widely, and various building materials can be used for their construction. The first place here is given to metal structures, followed by reinforced concrete and masonry. A mixed frame is possible, but wood is rarely used in such buildings due to the limited length of lumber, low strength characteristics compared to other materials, increased creep and low fire resistance. Nevertheless, in the forest regions of the Russian Federation, warehouse buildings (WB) with spans up to 24 m and a wooden frame are successfully built and operated. This article provides information about the WB, the design scheme of which is based on the solutions of the American company Hansen Pole Buildings [1, 2], where the frame is a system of single-span transverse frames, installed, as a rule, with a step of 2.4 m. The frames consist of boarded columns and gable trusses with knotty joints on metal toothed plates (MTP). At the top of the columns, crossbeams made of twin boards are placed in the longitudinal direction, where intermediate trusses are based on the MTP, and therefore the pitch of the load-bearing structures of the covering is 1.2 m. The geometric invariability of the building in the longitudinal direction is ensured by a system of ties in the coating and wall cladding oriented strand board (OSB) which is attached to the longitudinal beams. Wooden girders and solid OSB boarding are laid along the top chords of the trusses. Regulatory documents of different countries have different requirements for building structures, so a simple transfer of foreign solutions to Russia is hardly possible. For example, the frame posts in the buildings manufactured by “Hansen Pole Buildings” are embedded in the concrete foundation, which is not welcomed in our country. In a number of objects, realized by the mentioned company, there are no vertical connections on the longitudinal walls, as it is considered that OSB cladding plays their role. End walls of hangars are generally performed by the technology of light-frame houses. There are other features that exclude the possibility of simple copying of engineering solutions.
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3 Results Various firms are engaged in the construction of warehouse buildings made of wood in the Russian Federation. This paper describes the experience of OOO STROYSYA VYATKA (Kirov). The construction of all parts of the building from a limited range of lumber, which does not provide for the use of beams, is a peculiarity of the structures of this company. The frame is built from boards. If necessary, the latter can be spliced to create two and three-layer core elements—Fig. 1. As the bearing structures of the covering, pentagonal gable plank trusses with nodal joints on the MTP, installed in increments of 1.2 m, are used. The trusses are supported by longitudinal cross beams attached to the frame struts at the side. The pitch of the racks is 2.4 m. To reduce the load on the longitudinal cross beams, the trusses located above the racks are installed on a shortened board of the middle layer—Fig. 2. The erection of structures was preceded by their preliminary calculation with the choice of the most rational solution. The main issue that needed to be resolved was to support the frame racks on the foundations. Domestic building codes, such as revised edition of SNiP II-25–80 SP 64.13330.2017 Wooden Structures and traditional educational publications [3] consider dowel connections of elements of wooden structures to be hinged, which exclude the possibility of creating singlespan U-shaped frames made of wood, because the hinges, on the supports and in the cornice nodes, turn the structure into a mechanism. At the same time, it is quite common to see warehouse buildings abroad in which the longitudinal wall posts simply rest on a horizontal plank strapping and are fastened to the latter with nails at an angle. There is no rigid connection in this case, but the objects are successfully
Fig. 1 Composite post
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Fig. 2 Fragment of the warehouse building frame during construction with space for installing the truss (left column)
operated. This fact suggests the need to revise certain provisions of the Russian Code of Practice. The static calculation of the warehouse building frame was performed using the LIRA_CAD software package. The operation of one transverse frame with different combinations of coupling of the elements on the supports and in the cornice nodes was preliminarily considered. Calculations showed that the best option for the structure is a frame with a rigid pinch on the support and a hinge at the coupling of the post and the truss. In addition, it was found that the ratio of truss and post stiffness allows using the formulas for frames with transoms of unlimited stiffness, as it is usually done in steel structures, to be used for calculations as a safety margin [4]. This simplification made it possible to create a calculator to calculate the frames of warehouse buildings, which will be discussed below. The frame model of a warehouse building created in the LIRA CAD program is shown in Fig. 3. It shows the system of connections in the cover and on the columns. The connections are made from the same grade of lumber as the other elements of the structure. In the presented frame of the hangar, boards with cross-sections of 50 × 200, 50 × 100 and 45 × 95 were used. If necessary, the cross-section was performed as a composite. The next step in the design was the calculation and construction of the nodal connections of the frame elements. Due to the fact that the assembly of all structures, except for trusses, was assumed at the construction site, bolts, wood screw and nails were considered as connecting elements [5, 6]. The trusses with nodal connections on the MTP were assembled in the factory and delivered to the construction site by
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Fig. 3 Warehouse frame model
motor transport. The use of dowels required implementation of other construction standards—compliance with all the necessary distances between them along and across the wood fibers. One of the decisions is shown in Fig. 4 as an example.
Fig. 4 Example of the design of a warehouse frame unit
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After completing the design of the units, the design of the warehouse building was prepared, according to which the latter was erected. Figure 5 and 6 give an idea of this fact. The construction, nodal joints and installation methods proven on the shown building gave us an opportunity to think about the construction of other similar facilities. Due to the variability of warehouse spans and their varying lengths, an engineering tool was needed to enable the calculation of the frame without the use of complex computer programs. For this purpose, a wooden hangar calculator was created, which was used to calculate several buildings. Its peculiarity is the possibility of varying the assortment and selecting the most economical solutions. The calculator allows calculating all constructions and nodal joints of the elements of a warehouse
Fig. 5 Warehouse building under construction
Fig. 6 Final view of the frame structures
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frame, except for trusses on MTP, which are designed on the certified software product of MiTek Company. The information about the designed trusses is entered in the calculator, which makes it possible to take into account their features in the design. The calculator was created in Microsoft Excel [7] and has a modular principle that allows the designer to see not only the final results of calculations, but also calculations of individual elements and units, each of which is performed on a separate worksheet of the calculator. After completing the calculations, the results can be exported to Microsoft Word, where an explanatory note with calculations is automatically created to form project documentation. Separate worksheets of the calculator and a fragment of the explanatory note are shown in Fig. 7.
Fig. 7 Examples of calculator worksheets and a fragment of the explanatory note
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Fig. 7 (continued)
4 Discussion The conducted complex of calculations and design showed that single-span warehouse buildings with spans up to 21 m can be successfully erected in the Russian Federation in areas with a snow load corresponding to the IV snow district according to Russian State Standard SNiP 20.13330.2016 Loads and Impacts. In this case, a limited range of lumber and simple dowel joints can be used to make the nodal connections of the elements. Several similar objects erected by specialists of OOO «STROYSYA VYATKA» proved the applicability of the proposed system. Steel elements used in the frame structures are supporting shoes of columns and toothed plates of trusses. Low metal consumption makes it possible to erect cost-effective structures in areas of the Russian Federation rich in wood. Further improvement of the structures continues. At the present time, there is an object where lattice columns of variable cross section with nodal joints of the elements at MTP are used as frame posts.
5 Conclusion Wooden frame warehouse buildings are simple in manufacturing and assembling. The use of limited assortment of lumber and simple units design make it possible
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to erect them economically, which opens up new opportunities for small farms and private entrepreneurs. A number of completed constructions have proved the viability of such buildings. Preliminary calculations have shown that such facilities can be erected in Russia in compliance with all the requirements of regulatory documents. Blind copying of foreign technology for our country is not always applicable. On the one hand, it is limited by the excessively rigid requirements of building codes and regulations, and on the other hand, by the solutions of components and individual parts used abroad, which are difficult to implement in our country. Wooden structures are a promising type of building structures, which in some cases can successfully compete with reinforced concrete and steel [8].
References 1. Hansen buildings construction guide (2017) p 499 2. Post-frame building design manual. National frame building association (2015) p 42 3. Zubarev GN, Boitemirov FA, Golovina VM et al (2004) Constructions of wood and plastics. Academy, Moscow, p 304 4. Arleninov DK, Buslaev YN, Ignatyev VP et al (2002) Constructions of wood and plastics. Publishing house of the academy of sciences, Moscow, p 276 5. Uman AA (1972) Designer’s handbook of industrial, residential and public buildings and structures. SI, Moscow 1:599 6. Verzhbovsky GB, Shchutsky SV (2003) Comparison of domestic and foreign recommendations for the design of shear working nail joints. Lightweight building structures. Publishing house of Russian state university of civil engineering, p 37–43 7. Verzhbovsky GB, Eremenko NN, Shchutsky VL (2004) On shear work of nail joints of universal set panels. Lightweight building structures. Publishing house of Russian state university of civil engineering, St. Petersburg p 76–85 8. Walkenbach J (2019) Excel 2019. The user’s bible. An exhaustive guide. Dialectics, Moscow, p 1136
Methodology of Comparative Analysis of the Use of Leasing and Net Lending in the Technical Re-equipment of the Machine and Tractor Fleet Arthur Alukhanyan
and Olga Panfilova
Abstract The purpose of the study was to develop an economic mechanism to justify the profitability of leasing as a source of financing for the technical re-equipment of the machine and tractor fleet of agricultural enterprises in comparison with other instruments (in particular, credit). The article describes the process of economic and mathematical modeling of a leasing transaction, consisting of the stages of algorithmization and programming. A block diagram of the algorithm for determining the profitability of leasing has been developed. The software implementation uses the capabilities of the multi-window structure of the Pascal programming language. The main indicators of leasing are: lease payment, payment to the lessor for additional services, commission fee to the lessor, etc. The paper also substantiates the main advantages of a leasing transaction over a conventional loan. Keywords Leasing · Leasing transaction · Technical re-equipment · Economic and mathematical modeling · Pascal programming language
1 Introduction The socio-economic environment of the Russian market determines the exceptional importance of the agricultural sector for the sustainable development of the national economy, which is the key to political and social stability in the state [1]. At the same time, the Russian agriculture is characterized by a significant deterioration of the machine and tractor fleet, as a result of which the question of the need for systematic technical re-equipment of agriculture, including through the use of financial instruments of lending and leasing, is acute [2–11]. The most widespread in our country are such areas of agricultural lending as bank lending for up to one year, state lending, mortgage lending, credit cooperation and leasing [12]. At the same time, the use of leasing, at present, should become the main direction of renewal of the machine and tractor fleet of agricultural enterprises. A. Alukhanyan (B) · O. Panfilova Don State Technical University, Square Gagarina, 1, Rostov-On-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_183
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Leasing has a number of advantages over conventional lending, among which it is necessary to emphasize the following: 1. In the case of leasing, the full value of the object of the transaction is credited and no immediate start of payment under the contract is required. A regular loan involves a down payment of at least 15% of the value of the fixed asset. At the same time, leasing provides for the conclusion of a contract for the entire value of the property. The beginning of payments under the lease agreement usually follows the delivery of the property to the lessee. 2. It is easier for a borrower to get a lease contract than a loan from a bank. Most often, this applies to small and medium-sized businesses. In some cases, the lessee is not even required to provide additional guarantees. The equipment itself acts as collateral for the lease agreement. It is assumed that the lessee’s failure to fulfill its contractual obligations leads to the return of the property that is the object of the transaction. 3. A leasing agreement is more flexible than a loan [13–15]. As a rule, a loan always involves restrictions on the terms of the loan and the amount of payments. The lessee can develop together with the lessor a payment scheme that corresponds to its financial capabilities. Payments can be made once a month, once a quarter, etc. At the same time, the amount of payments may be unequal. Often, the lessee makes payments at the expense of the income obtained from the sale of products produced on the leasing equipment. Among other things, both fixed and floating rates are applied. 4. The risk associated with the physical and moral wear and tear of the equipment is borne by the lessor. The lessee thus gets the opportunity to renew its fixed capital on an ongoing basis. 5. Leasing allows the lessee to reach a greater production capacity than when using a bank loan. In addition, in the case of leasing, significant funds are released, which can be used for other purposes.
2 Materials and Methods The process of economic and mathematical modeling of a leasing transaction includes the formulation of the problem, which consists of the following stages: 1. Algorithmization and programming of the calculation of the main leasing indicators (W —annual revenue, Z—annual costs, P—profit). 2. Comparison of leasing with conventional lending. 3. Conducting a computational experiment. The profit, in general, is calculated by the formula: P = W − Z.
(1)
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Revenue is calculated as follows: W = Pr × N ,
(2)
where Pr is product sale price; N is production volume (number of products produced per year). Annual costs are calculated using the formula: Z = Z 0 + Z 1 + L P,
(3)
where Z 0 is annual fixed costs; L P is lease payment. The summand Z 1 in (3) is calculated by the formula: Z 1 = N × Cs f + N × Co × (1 + q1 ),
(4)
where Cs f is the price of purchased semi-finished products (per product); Co is own costs (per product); q1 is VAT expressed in decimals. The amount of lease payments is calculated as follows: L P = (Q a + Pcr + Pas + C F) × (1 + q1 ),
(5)
where Q a is an amount of depreciation; Pcr is payment for the credit resources used by the lessor for the purchase of property; Pas is payment to the lessor for additional services to the lessee; C F is commission fee to the lessor for the provision of property under the lease agreement. The amount of depreciation (Q a ) can be calculated using the formula: T
Q a × (qslsl
−1
T
+ qslsl
−2
+ . . . + 1) = Q(N ) × qslTsl ,
(6)
where qsl is discount rate; Tsl is equipment service life. Calculate qsl using the formula: qsl =
1 + psl = 1 + rsl , 1+g
(7)
where psl is profit share for depreciation calculation; g is inflation expressed in decimals. Thus, we have Q a = Q(N ) × Asl ,
(8)
qslTsl × (qsl −1 )
(9)
where Asl =
qslTsl − 1
.
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The amount of payment for the credit resources used by the lessor for the purchase of property can be calculated in the same way. The discount rate in the case of using credit (qc ) can be calculated as: 1 + pc = 1 + rc , 1+g
qc =
(10)
where pc is profit share for credit calculation. The amount of credit payments (Cr ) can be calculated using the formula: Cr = Cr 0 × Ac ,
(11)
Cr 0 = D × Q(N ),
(12)
where
Ac =
qcTc × (qc − 1) qcTc − 1
,
(13)
where D is the share of credit in the cost of equipment; Tc is loan term. The payment to the lessor for additional services to the lessee (Pas) is calculated depending on the source data according to two schemes: a) the service fee is charged for the year Pas = Pas 0 ,
(14)
b) the fee is charged as the services are rendered for the entire duration of the lease (Pas all ) Pas × q Tsl −1 + q Tsl −2 + ... + 1 = Pas all .
(15)
Therefore, Pas is calculated as: Pas = Pas all ×
q −1 . q Tsl − 1
(16)
The commission fee to the lessor for the provision of property under the lease agreement (C F) is calculated using the formula: C F = Q(N ) × a × A z ,
(17)
where a is correction coefficient. Az =
qlTl × (ql − 1) qlTl − 1
,
(18)
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where Tl is lease agreement term. The discount rate for leasing (ql ) is calculated as: ql =
1 + pl = 1 + rl , 1+g
(19)
where pl is profit share for leasing calculation. The profit in the case of using leasing is calculated as: P = K 1 × N − K 2 × Q(N ) − K 0 .
(20)
The coefficients K 1 , K 2 , K 0 are calculated using the following formulas: K 1 = P − Cs f + Co × (1 + q1 ) ,
(21)
K 2 = (Al + a × Ac + D × A z ) × (1 + q1 ),
(22)
K 0 = Z 0 + Pas × (1 + q1 ).
(23)
3 Results of Scientific Research It is obvious that it is advisable to conclude a leasing transaction in the case when the profit will be greater than in the case of ordinary net lending. Denote by Pl the profit on leasing and by Pc the profit on net lending. To determine the conditions under which Pl > Pc , you need to write down the formula for the profit when lending. Let’s represent Pc in the form: Pc = K 1 × N − K˜ 2 × Q(N ) − Z 0 ,
(24)
K˜ 2 = A z × (1 + q1 ).
(25)
where
Based on (20) and (24), we write the inequality Pl > Pc (the condition of profitability of leasing) in the form: Q(N ) × K˜ 2 − K 2 > Pas × (1 + q1 ).
(26)
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It follows from (26) that leasing is not profitable when K˜ 2 < K 2 . At the same 1) , is satisfied, then the use of time, if K˜ 2 > K 2 , but the inequality Q(N ) < Pas×(1+q ( K˜ 2 −K 2 ) leasing is also economically impractical. The software implementation of the algorithm for solving the problem of justifying the economic efficiency of a leasing transaction is carried out in the Borland Pascal 7.0 programming language. The program uses the graphical capabilities of the Pascal language and has a multi-window structure. It implements a system of menus and subscript hints, as well as a reference file that sets out the basic principles of calculations, which makes working with the program the most convenient. The program uses a large number of initial parameters of the leasing transaction, which makes it possible to obtain the most accurate results. In addition to the traditional indicators of the leasing transaction, the initial data also includes the rates necessary to bring the value of money to the initial moment. To enter the source data, the program provides 2 options: – enter data from the keyboard; – entering previously saved data from a file. The program implements the source data editor. It allows you to enter new data, save it to disk, and read it from disk. It is possible to correct already entered parameters, which allows you to evaluate changes in the results by varying the values of individual indicators. This feature is useful for making the final decision on the transaction. The program allows you to enter the parameter Pas in two ways. To do this, the “Options” menu item is provided. It also allows the calculation of profit on leasing and on net lending, while analyzing the profitability of the leasing transaction. The main result of the program is the values of the coefficients K 0 , K 1 , K 2 . Based on these coefficients, the components of lease payments are calculated. It is possible to save the results to a file, which allows you to compare the final results for different leasing transactions. Schematically, the algorithm of the program can be represented in the form of a block diagram (Figure). When implementing the program, a modular structure was used. The program consists of a main part called leasing and 3 modules: global, graph2, main. The main program prepares the values of the initial parameters, initializes the main menu, performs a dialog with the user, and transfers control to the procedure that processes the menu item selected by the user. A module called global contains descriptions of the data types and variables used by the program. The graph2 module contains procedures that allow you to implement a window interface. The full list of module procedures is given below: Procedure Grinit initializes the graphical mode; Procedure Unbutton (x, y, c, font:integer; s:string) displays the released button; Procedure PrButton (x, y, c, font:integer; s:string) displays the pressed button; Procedure Input (x, y, c:integer; var d:real) enters a number;
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Procedure GrWindow (x, y, x1, y1, c:integer; name, name1:string) displays a graphical window on the screen; Procedure Inverse (x, y, x1,y1:integer) auxiliary procedure for color inversion of a graphic image used by the Menus, EntrySt, Fileopen procedures; Procedure Menus (x, y, x1, y1:integer; name21:string; n:menuarray; var menx, meny:byte) the procedure that displays the menu and processes it; Procedure EntrySt (x, y, x1, y1, font, size, interval, c, r, rc:integer; var d:string) displays the input window and enters the string; Procedure FileOpen (var filename:string) displays a dialog box for opening a file and selects a file from the suggested list. The main module contains the basic procedures used for input of source data, calculations, and output of results. It includes the following procedures: Procedure Select2 (x, y, x1, inter, n:integer; var m:integer) is a procedure for selecting a vertical menu item; Procedure Select (x, y, x1, inter, n:integer; var m:integer) is a procedure for entering and correcting the source data. Organizes the vertical menu by items—names of the source data. Operates with the source data only in memory (Fig. 1); Procedure Pselect is procedure for entering parameters. Displays a vertical menu on the screen for options for the value of the Pas parameter. In accordance with the user’s choice, sets the value of the global variable that determines further calculations. Uses the Select2 procedure; Procedure NewFile (q:byte) is a procedure that displays a table of source data names. If you need to create a new file, the procedure clears the parameter values. Control is then passed to the Select procedure; Procedure Save allows you to save the original data to a file; Procedure Load loads the saved source data from the file. Outputs the downloaded data to the screen; Procedure Calculat is the main computational procedure. Using the original data, calculates the coefficients K 0 , K 1 , K 2 . Calculates the lease payment components. Then it calculates the profit on leasing and credit and analyzes the profitability of leasing. Displays the results on the screen: the values of the coefficients, the conclusion about the profitability of the lease (in case of unprofitability of the lease transaction, it provides explanations regarding the reasons for unprofitability), as additional information, it displays the components of lease payments; Procedure Saveres allows you to save the results of calculations to a file; Procedure Loadres allows you to load the results of past calculations from a file. Outputs these results to the screen; Procedure Help displays the help information, including the basic formulas and the calculation algorithm. The reference material is read from the text file leasing.hlp; Procedure About displays information about the program.
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Fig. 1 Block diagram of the algorithm for determining the profitability of leasing
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4 Conclusion The share of agricultural machinery products sold under leasing is decreasing from year to year. The reasons are both insufficient support from the state, and the lack of adequate financing schemes that meet the interests of consumers of equipment. The participation of commercial banks in leasing operations constrains the difficult financial situation of rural commodity producers, since banks do not have guarantees in the timely return of their invested funds. The share of state purchases of equipment for subsequent deliveries on the terms of leasing is from 70 to 90%. All this leads to a violation of the pricing mechanism and indicates the imperfection of this form of lending. Within the framework of the Federal Target Program for the Development of the Agro-industrial Complex, the following measures were developed: expanding the scope of leasing, creating special regional leasing funds, and attracting bank loans. The state selects leasing intermediaries on a strictly competitive basis in order to exclude the monopoly of suppliers. In order to bring the lessor closer to a specific consumer and take into account all their needs, a wide network of leasing companies is being created. Improving the quality of services and reducing the cost of equipment can be achieved by increasing the number of leasing entities, which will lead to the development of competition in this area. A retrospective analysis of the functioning of the leasing mechanism in the agricultural sector has shown that this financial instrument is insufficiently used for equipping and re-equipping domestic farmers with modern agricultural machinery. One of the reasons for this situation is the lack of development of the financial market, in particular the market of medium-and long-term lending, as well as insufficient support for various financial programs from the state. It is obvious that the further development of leasing as a financial mechanism for resolving contradictions between economic agents in the face of a plant-manufacturer of machinery, on the one hand, and an agricultural enterprise, on the other, should take place along the path of increasing competition in the market of leasing services and the creation of leasing units in the structure of the companies-manufacturers of agricultural machinery. In our opinion, these measures will have an effective impact on the situation with the renewal of the equipment fleet of agricultural enterprises.
References 1. Serbulova N et al (2019) Sustainable food systems and agriculture: the role of information and communication technologies. IOP Conf Ser Earth Environ Sci 403:012127. https://doi.org/10. 1088/1755-1315/403/1/012127 2. Borisova DV, Gorelova GV (2019) Cognitive instrumentarium for interregional economic integration investigation. Int Sci J «Stable Dev Mount Areas» 11(1):65–67 3. Seyyedhasani H, Dvorak JS (2018) Reducing fieldwork time using fleet routing optimization. Biosys Eng 169:1
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4. Shepelev S, Shepelev V, Almetova Z (2016) Optimization of technical equipment for crop sowing processes. Procedia Eng 150:1258 5. Bochtis D, Sorensen CG, Kateris D (2019) Choosing a machinery system. Oper Manage Agric 117 6. Karunarathna M, Wilson C (2017) Agricultural biodiversity and farm-level technical efficiency: an empirical investigation. J For Econ 29:38 7. Hu Y et al (2020) A two-stage dynamic capacity planning approach for agricultural machinery maintenance service with demand uncertainty. Biosys Eng 190:201 8. Vafador A et al (2016) Technical feasibility analysis of utilizing special purpose machine tools. J Manuf Syst 39:53 9. Kurdyukov V, Kanurny S (2020) Conditions for the effective functioning of the system of internalization of economic damage from emissions in the territory. E3S Web Conf 210:13005. https://doi.org/10.1051/e3sconf/202021013005 10. Zhukova T et al (2020) Peculiarities and development factors of modern agricultural engineering. E3S Web Conf 175:05028. https://doi.org/10.1051/e3sconf/202017505028 11. Sopegno A et al (2016) A web mobile application for agricultural machinery cost analysis. Comput Electron Agric 130:158 12. Vovchenko NG et al (2018) Formation of an adaptive personnel training system as a factor of ensuring the financial stability of leasing companies. Eur Res Stud J 21:3 13. Tieppo RC et al (2019) Modeling cost and energy demand in agricultural machinery fleets for soybean and maize cultivated using a no-tillage system. Comput Electron Agric 156:282 14. Alukhanyan A et al (2019) Risk management of innovative Russian companies in the context of interregional integration. IOP Conf Ser Earth Env Sci 403(1):012044 15. Orobinsky AS et al (2018) Development of risk-oriented technologies of the corporate financial controlling system. Eur Res Stud J 21:333–349
Choosing the Communication Technologies and Technical Means for the Transport Infrastructure in Rural Areas Marina Zvezdina , Yuliya Shokova , and Alexandr Eliseev
Abstract The article proposes to use a combination of solutions from economics, ICT, electrodynamics and meteorology to provide a scientific basis for the selection of technical means of communication systems in the transport infrastructure. The validity of this approach is stipulated by the need to consider many factors when solving this practical task. To justify the construction pace of communication network infrastructure, it is proposed to consider the correlation between economic indicators (gross regional index per capita) and the index of ICT development. It is also proposed to consider infrastructure evenness within the region and the degree of economic development between regions when justifying the choice of access technology. In order to eliminate the digital divide within a region, the peculiarities of its geographical location, territory size, population density, and proximity to backbone communication lines should be taken into account. The options of subscriber access lines construction are considered, as well as examples of their implementation within the framework of the program “Elimination of Digital Divide in Russia”. Recommendations on the choice of mirror antenna design with regard to regional climatic factors for the satellite-based subscriber line with VSAT stations are given. Keywords Transport infrastructure · Complex approach · Scientific rationale of communication network technology · Regional characteristics · Climatic features
1 Introduction It is known that transport infrastructure contributes to the competitiveness of the state economy. In this regard, a lot of attention is paid to its development. One of its components are communication systems that ensure the tracking of urban and external passenger and freight transport facilities, processing cargo movement data, as well as cargo storage at permanent and temporary locations [1]. The choice of the structure of communication networks, as well as their technologies is determined by M. Zvezdina (B) · Y. Shokova · A. Eliseev Don State Technical University, Gagarina Square, 1, Rostov on Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_184
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many factors. These may include the general and regional economic development level, the remoteness from major population centers, the ability to access global information networks (Internet), the population density in the location area, the digital technologies rate in the region’s economy, etc. [2, 3]. The analysis of the above factors shows that the task of selecting technologies and technical means for modern communication systems within the transport infrastructure is a complex task per se. However, the need to provide Internet connection to various facilities, as well as the need to take into account the differences in the digital rate for each region of the Russian Federation, calls for a modern approach to solving this problem. A common approach to broadband network deployment, the World Bank’s Toolkit [4], is now generally accepted. However, it does not reflect the local features specific to each country, which reflects the so-called digital divide [3, 5, 6]. For small countries, the digital divide determines the digital penetration in large cities and rural areas, while for the Russian Federation, which has a large territory; it is also the case between regions [7]. The statements above define the purpose of the article—a scientifically based choice of technology and technical means for the mobile communications system within the transport infrastructure in rural areas. The stated purpose is achieved by solving the following scientific problems: 1. Explaining the approach to selecting a broadband Internet access technology. 2. Choosing the way to organize a broadband Internet subscriber network, given the peculiarities of the region. 3. Selecting the node access point antenna design.
2 Rationale for the Broadband Internet Access Technology Selection Approach One of the challenges addressed by the transport infrastructure is to increase the degree of integration and balance of the country’s space, including the information space. Currently, the basis of the latter is information and communication technologies (ICT), which are based on the use of broadband 3G, 4G, and 5G networks. Given the correlation between broadband access technology (BBA) and the level of economic development, as identified in [8], we will use the approach and toolkit proposed by the World Bank for broadband strategies [4] when choosing Internet access technology. It should be noted that the transition from communication systems to Internet access systems is quite reasonable, because the range of services provided is significantly higher than just the transmission of a single voice, as in the 2G technology. We will not consider the political and social issues within the Toolkit in this article, as they are outside the research scope.
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2.1 Analysis of Russia’s Position in the Global Digital Space Taking into account the imposed constraints, we will assess only the technological component of the digital divide. The said component takes into account the development level of digital infrastructure, the presence or absence of communication networks, the Internet, mobile communications, as well as the level of automation and virtual activity [9]. The country’s position in the global digital space can most fully be estimated by analyzing the relationship between the value of gross domestic product per capita (GDP) and the ICT development index (I-DESI), as shown in [10]. This correlation is shown in Fig. 1 [5]. The country position in Fig. 1 corresponds to the 2011 data. The analysis in [10] showed that this curve makes it possible to determine the necessary time gap between the ICT development and the development of the economy; it also identifies the tipping point when ICT starts generating significant revenues. Thus, the initial section of the curve (< $10.0) determines the underdeveloped ICT infrastructure and relatively small impact on the economy of the country. This segment illustrates the economies of developing countries. Next comes the saturation point, when ICT begins to generate significant revenues. According to [10], this point corresponds to 20% of ICT penetration in a country’s economy and reflects the moment when developing countries become developed. Finally, the last segment of the curve (> $30.0) identifies the point at which a small increase in ICT brings the greatest effect. In fact, this segment corresponds to developed economies. It should be noted that the interpretation of Fig. 1 of [10] is in good agreement with the classification of countries from [6]. This paper introduces a classification of economies according to the pace of ICT infrastructure development. Four categories
Fig. 1 GDP per capita and I-DESI correlation, Source [5]
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are introduced: Stand Out, Stall Out, Break Out and Watch Out. The first category combines highly digitalized countries that lead innovation. However, to maintain their momentum, the countries in this group should keep their innovation activity up to date and create new demand for ICT development. This actually corresponds to the gentle part of the curve with Fig. 1 (areas above the curve). The second category countries are those with high digitization but sluggish growth rates. These countries are located on the gentle part of the curve of Fig. 1 below the curve. The third group of countries has significant potential for growth, but is characterized by weak infrastructure and relatively ineffective institutions for innovation. In Fig. 1, these are the countries in the initial section in the area above the curve. Finally, countries in the fourth category have low growth rates and low digitalization. The position of these countries in Fig. 1 corresponds to the initial section and the area below the curve. Given this classification, the Russian Federation belongs to the third group called Break Out, which determines the need for faster development of ICT infrastructure compared to the subsequent growth of GDP. The infrastructure growth rate should be high.
2.2 Analysis of the Regions’ Position in the Global Digital Space The recommendations on the infrastructure development pace formulated in Sect. 2.1 apply to the country as a whole. However, the Russian Federation is a set of regions with uneven economic development. Therefore, in order to specify the infrastructure development rates by region, it is necessary to analyze the gross regional product per capita. Figure 2 shows the gross regional product per capita according to Rosstat for 2010. To simplify the analysis, the regions in this figure are grouped according to the level of GRP corresponding to the known world regions: European, Latin American, Asian, and African. It is not difficult to notice that in terms of the economic development level Russian regions include almost all known categories. Consequently, each region is characterized by its own rate of infrastructure development.
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Fig. 2 Gross regional product per capita, Source Rosstat
2.3 Broadband Access Technology Selection by Russian Regions The choice of access technology is simultaneously affected by two contradictory requirements. On the one hand, in order to achieve the greatest economic growth with the use of ICT, it is necessary to provide the same access technology in all regions. On the other hand, regional economies differ and, consequently, the needs of subscribers differ in the access technology required. As we know, broadband Internet access technologies differ in many ways. Here we will focus on only two of them: data transfer rates and services provided. The differences in data transfer rates and services for broadband technologies are shown in Table 1 [11]. By analyzing this table and taking into account the sharp increase of network deployment over the number of services provided, the following conclusions can be made. 5G technology becomes effective and economically efficient with a large number of IoT devices connected to the communication network. In less developed regions of the Russian Federation it is necessary to deploy 4G communication networks. Moreover, in large cities it is reasonable to use 4G-Advanced technology, while 4G is still sufficient for rural areas. To support this conclusion, the Government of the Russian Federation issued a decree stating that until 2025, 5G systems are recommended only in large cities as pilot projects, and afterwards they will be used mainly in transportation management systems in large cities. These pilot projects are currently operating in Moscow, St.
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Table 1 Comparative data transfer rate characteristics for different broadband technologies Technology
Data transfer rate (max), Downstream/Upstream
Services provided
3G
up to 59.2/59.2 kbps
Data transmission with voice over IP, mobile Internet access
4G
up to 150 / 75 Mbps
High-speed mobile Internet access, voice over IP
5G
up to 20 Gbps
Advanced mobile broadband Internet access, ultra-reliable, low latency communications, massive machine-to-machine communications
Petersburg and Kazan, i.e. in the largest populated centers of the most economically developed regions, where subscribers already have a demand for the Internet of Things. In other regions, it is recommended to use 4G technology to organize cellular communication systems.
3 Choosing the Way to Organize a Broadband Internet Access Subscriber Network, Given the Peculiarities of the Region 3.1 Analyzing the Population Structure by Region in the Russian Federation There is an unsolved problem of providing even ICT penetration within the region, i.e. eliminating the digital divide between the urban and rural populations. It is rather easy to solve this problem in regions with a mostly urban population. Figure 3 show statistical data for Russian regions from Rosstat on the rural population share. According to the figures, areas with a mostly urban population and high population density are concentrated in the central and southern regions of the European part of the country. In the rest of the country, the regions are either sparsely populated or are areas with mostly rural populations. Furthermore, in both variants the regions occupy large territories, with sizes either comparable or many times larger than those of the European countries.
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Fig. 3 Rural population share by Russian regions in 2020, Source Rosstat
3.2 Analysis of the Broadband Subscriber Network Organization in the Regions Let us assess how the uneven development of regions affects the structure of the broadband Internet access network. The main elements of broadband access systems are backbone (transport) networks, access nodes that form the subscriber access network, and local networks, i.e. subscriber line networks [4]. An analysis of the backbone network coverage map in Russia from [12] showed that fiber optic communication lines (FOCL) cover densely the territory of the European part, passing through all the major cities. However, in Siberia and the Far East the main cables are concentrated along the Trans-Siberian Railway, leaving other areas outside the coverage area. This characteristic of laying FOCL in Siberia and the Far East is due to the sparsely populated areas, as well as the very large (more than 200 km) distances between settlements. This arrangement of backbone networks suggests various options for the node points connecting backbone networks with subscriber communication lines: – The FOCL backbone network is connected to a node located in a rural area, for example, at a post office or school, and then the distribution to subscribers is carried out over a wireless channel. This type of organization is implemented by the Government program “Elimination of digital divide in Russia” [13]. It is implemented by cellular operators, which are exempted from frequency fees by the Ministry of Digital Development, Communications and Mass Media of the Russian Federation as an incentive. Shortcomings: the population size of the settlement should range from 100 to 500; connection should be possible under geographical and climatic conditions. During the first phase (2014–2020), the subscriber network was formed via Wi-Fi, which resulted in a low exchange rate.
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In addition, there was only one connection per subscriber. At the second phase (2020–2021) the node point is implemented as a base station. This has increased the data transfer rate as well as the number of connections per user. By 2030 4G broadband Internet access will be available in 24 thousand rural areas. – The radio relay network is connected to a base station node. Then a cellular network can be organized, depending on the population size. The potential application area includes settlements located in a highly rugged terrain. – Satellite channel network connected to a node point via VSAT. An access point is installed in a dwelling with more than one family. Other people can come to this point to use the Internet connections. Moreover, if additional equipment for cellular signal amplification is purchased, it is possible to use internet connections in other dwellings as well. The “IT nomad camp” program implemented in the Khanty-Mansiysk and Kondinsk districts [14] is an example of this type of nodal point organization. In 2020, 17 access points were installed, providing broadband Internet access to 48.2% of the population of these districts. For remote areas in Zabaikalye and Chukotka, broadband Internet access is implemented by the operator Rostelecom according to the same scheme. The disadvantages are the high cost of the equipment set and the high subscriber fee. Benefits are the possibility to organize communication over long distances. Figure 4 shows the price ratio of solutions using different communication channels: terrestrial (1) and space (2). Obviously, at distances over 200 km, which are typical for regions of Siberia and the Far East, satellite channel communication is the most optimal solution. It should be noted that to eliminate the digital divide in European rural areas it is also possible to use space communication channels. However, nanosatellites are used for communication [15]. At the same time it should be noted that in the Republic of Sakha (Yakutia), where 99% of the population (73,000 people) live above the Arctic Circle, FOCL is being laid out above the Arctic Circle as part of the agreement between the Government and PJSC “Rostelecom”. In the project the nod points are connected according to the first variant. In 2020 the FOCL was laid to the district center of the Olenek area. Further it is planned to lay the FOCL along the Northern Sea Route to Tiksi settlement. In the Arctic regions the sparsely populated settlements will be connected via IT centers.
Fig. 4 Price ratio for communication solutions through different channels
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4 Selecting the Node Access Point Antenna Design 4.1 Regulatory Restrictions on the VSAT Station Design Parameters The use of satellite channels for the node organization is restrained by the rulings of the State Commission on Radio Frequencies of the Russian Federation (SCRF) on the necessity of a separate SCRF decision on the use of VSATs. These restrictions introduced in 1998 and amended in 2021 now apply to antennas over 2.4 m in diameter, with a transmitter power of over 2 W and an effective isotropic radiated power (EIRP) of over 50 dBW. In November 2021 it was permitted not to register VSAT stations working with the Russian satellites of the “Yamal” and “Express” series except for the stations located within 500 m to 3.5 km radius from the airports. The restrictions remain on EIRP value and antenna diameter only. However, VSAT registration will still be carried out under the license for the RF use issued to the owner of the central earth station of the corresponding satellite network who will monitor all VSAT stations of the satellite network for their radiation parameters 24 h a day, 7 days a week. We believe that one of the contributing factors to the Yakut government’s decision to lay FOCLs in the Arctic region was these regulatory documents, which would have greatly complicated the situation with the required amount of VSAT stations installed throughout the Republic.
4.2 Design Parameter Restrictions for the VSAT Station Due to Climatic Factors Possibility of operation under the influence of climatic factors is always stipulated when describing the options for selecting a node access point. This is due to the fact that mirror antennas are used in VSAT stations and their performance stability depends on the climatic factors. It is shown in [16, 17] that when VSAT stations are located in climatic areas with abundant precipitation (rain, snow), a large amount of precipitation can accumulate in the antenna reflector. As a result, in the precipitation layer on the reflector with a diameter of 1.5 m electromagnetic wave energy losses can reach 10–18 dB at frequencies up to 40 GHz for areas with a maximum snow intensity (for example, in the Far East, Kamchatka, as well as in the Arctic regions). The results obtained are in good agreement with the data of full-scale experiments given in [18, 19]. The conducted studies show that in such conditions, the antennas of VSAT stations should be additionally equipped with reflector heating and melt water removal systems.
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5 Conclusion Conducted studies on the scientific rationale behind the choice of technologies and technical communication systems for transport infrastructure in rural areas have shown the following: 1) The communication system of the transport infrastructure should be based on broadband Internet access technology. This will provide rural areas with the ability to track trucks, process data on the cargo movement, as well as its storage at permanent and temporary locations. 2) The specific type of broadband technology in use is determined by the level of the economic region and should be the same within that region. 3) The implementation of the government program aimed at eliminating the digital divide between urban and rural areas depends on the geographical location of the region (the European part, Siberia, the Arctic, the Far East, Kamchatka), population density and the territory size. 4) When backbone lines are close, the following infrastructure is implemented; it includes a FOCL from the backbone to a node access point in a rural area (post office, school, etc.). Subsequently, subscriber lines are formed by using either Wi-Fi (in pre-2020 versions of the government program “Elimination of Digital Divide in Russia”) or through a base station installed in a settlement with a population of 100 to 500 people (in the post-2020 version of the program). 5) If backbone lines are not available within acceptable distances, an infrastructure built on the use of satellite communication channels through VSAT stations is implemented. This option is most effective in inaccessible and sparsely populated regions of Russia. Currently, the main disadvantage is the necessity to obtain an operating permit for each VSAT station from the State Committee on Radio Frequencies. This drawback can be solved in two ways. The first one involves using Russian satellites “Yamal” and “Express” for organization of the space channel, as well as observing the restrictions imposed on the antenna diameter (less than 2.4 m), transmitter power (less than 2 W), EIRP (less than 50 dBW), station location (than 3.5 from the airport). The second one involves laying fiberoptic cable in the area (like in the Sakha Republic) with installation of access points in small populated settlements. 6) It is necessary to consider the climatic features of the region when selecting the design of the mirror antenna of VSAT station to provide a stable communication. In areas with intensive precipitation in the form of rain and snow, the reflector must be provided with systems of protection against snow and rain, for example, heating and water drainage systems.
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References 1. Krasyul I, Kolgan M, Medvedeva Y (2021) Development of an ecosystem approach and organization of logistics infrastructure. Transp Res Procedia 54:111–122. https://doi.org/10.1016/ j.trpro.2021.02.054 2. Kaneva M, Untura G (2019) The impact of R&D and knowledge spillovers on the economic growth of Russian regions. Growth Chang 50(1):301–334. https://doi.org/10.1111/grow.12281 3. Morris J, Morris W, Bowen R (2022) Implications of the digital divide on rural SME resilience. J Rural Stud 89(1):369–377. https://doi.org/10.1016/j.jrurstud.2022.01.005 4. Broadband Strategies Toolkit (2022). http://ddtoolkits.worldbankgroup.org/broadband-strate gies 5. Internet broadband for an inclusive digital society. Report of the Secretary-General United Nations (2013). https://unctad.org/system/files/official-document/ecn162013d3_en.pdf 6. Reggi L, Gil-Garsia R (2021) Addressing territorial digital divides through ICT strategies: are investment decisions consistent with local needs? Predict On-line Serv Gov Inf Quar 38(2):101562. https://doi.org/10.1016/j.giq.2020.101562 7. Grishchenko N (2020) The gap not only closes: resistance and reverse shifts in the digital divide in Russia. Telecommun Policy 44(8):102004. https://doi.org/10.1016/j.telpol.2020.102004 8. Schvab K (2013) The four industrial revolutions, p 216. https://doi.org/10.1007/978-981-161614-3 9. Digital in the Time of COVID (2020). https://sites.tufts.edu/digitalplanet/digitalintelligence 10. Zvezdina M et al (2022) Choosing a broad internet access network deployment model in the Republic of Guinea. ISJ Theor Appl Sci 01(105):701–712. https://doi.org/10.15863/TAS.2022/ 01/105/47 11. Rappaport T, Xing Y et al (2017) Overview of millimeter wave communications for fifthgeneration (5G) Wireless networks–with a focus on propagation models. IEEE Trans Antennas Propag 65(12):6213–6230. https://doi.org/10.1109/TAP.2017.2734243 12. The State of Broadband: Broadband as a Foundation for Sustainable Development (2019). https://www.itu.int/dms_pub/itu-s/opb/pol/S-POL-BROADBAND.20-2019-PDF-E.pdf. 13. Seven Trilateral Agreements Were Signed for Elimination of Digital Divide on the Forum Soch-2015 (2015). https://digital.gov.ru/en/events/34059/ 14. IT nomad camp (2022). https://depit.admhmao.ru/it-stoybishche/en.php 15. China A, Van der Wee M, Colle D, Verbrugge S (2019) Techno-economic viability of integrating satellite communication in 4G networks to bridge the broadband digital divide. Telecommun Policy 44(3):101874. https://doi.org/10.1016/j.telpol.2019.101874 16. Zvezdina M, Shokova Y, Shaposhnikova A (2021) Model parameters selection rationale for assessing the climate factors impact on 5G antennas losses. In: Proceedings of the IEEE International Conference RSEMW-2021, pp 345–348. https://doi.org/10.1109/RSEMW52378.2021. 9494109 17. Zvezdina M et al (2021) Climate factors impact on millimetre antenna losses. In: Proceedings of the IEEE International Conference RSEMW-2021, pp 349–352. https://doi.org/10.1109/RSE MW52378.2021.9494012 18. Ain F, Hassan S, Marzuki A et al (2012) Measurement of wet offset parabolic antenna at Ka-band with different elevation angles. Int J Electr Eng Tech 2:47–56 19. Sahaq K, Hassan S (2008) Measurements of the effect of simulated rain and wind on the offset parabolic receiver antenna at Ku-band frequencies. In: Proceedings of the IEEE International RF and Microwave Conference, pp 450–453. https://doi.org/10.1109/RFM.2008.4897458
Use of Crushed Materials for Decorative Self-compacting Concrete Lyubov Kastornykh , Vera Kosenko , Alexander Kaklyugin , Mikhail Kholodnyak , and Vladimir Khartanovich
Abstract Variants of the integrated use of construction waste–aggregates made of crushed materials–in the production of small architectural forms and other decorative products from self-compacting concrete are considered. It has been established that the aggregate grains from crushed concrete do not interfere with the high fluidity of the concrete mixture with an optimal amount of cement paste. In the production of decorative self-compacting concretes, the decisive technological factor is the use of the super water-reducing additive MasterPolyHeed 3545. The rheological compatibility with white cement and the high potential of the additive are realized due to the unique polymer structure, in which the rigid linear interaction of the polycarboxylate backbone with the cement surface is compensated by the flexible bulk action of polyaryl ethers. Evaluation of the decorative properties of concrete showed that the orange Bayferrox pigment in the amount of 2% of the cement mass gives the concrete a light terracotta color, but with an increase in consumption up to 4%, it leads to a drop in concrete strength by 8%. It has been established that the use of crushed fine-dispersed material (brick dust) as a mineral dye gives the concrete a weakly expressed terracotta color. Keywords Transport infrastructure · Decorative self-compacting concrete · Small architectural forms · Aggregates from crushed materials · Additive based on polycarboxylate and polyarylic esters · Pigments
1 Introduction One of the most important tasks set for the building materials industry in the Strategy for the Innovative Development of the Construction Industry of the Russian Federation until 2030 is to reduce the share of mineral raw materials and replace them with
L. Kastornykh (B) · V. Kosenko · A. Kaklyugin · M. Kholodnyak · V. Khartanovich Don State Technical University, Gagarin Square, 1, Rostov-on-Don 344000, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_185
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industrial waste. To accomplish this task, it will be necessary to achieve an economically justified level of self-sufficiency of the constituent entities of the Russian Federation with the production of building materials and structures. In the capital region of the country, the Program of Housing Renovation is currently in force, adopted in 2017 for a period until 2032 and designed to eliminate the accumulated imbalance in the development of the urban environment and prevent the massive emergence of emergency housing stock. The same task in the near future will have to be solved in other regions of the country, where due the post-war years apartment buildings of the first period of industrial housing construction were built. For example, in the cities of the Don region, dilapidated and emergency housing already includes apartment buildings made of volumetric blocks, large-block and large-panel buildings, as well as apartment buildings with brick load-bearing walls, built according to standard projects developed in the period from 1957 to 1968. The demolition of residential buildings will entail the formation of a huge amount of construction waste that must be disposed of and recycled. In such conditions, the recycling of construction waste will become a mandatory requirement to reduce the negative impact on the environment. In domestic and foreign construction practice, a fairly large experience has been accumulated in the use of construction waste as mineral raw materials [1]. For the recycling of construction waste from concrete and reinforced concrete (concrete scrap), a regulatory framework has been prepared–the Russian standard GOST 32,495–2013 “Crushed stone, sand and sand-crushed stone mixtures from crushed concrete and reinforced concrete. Technical conditions”. Crushed materials can be used as aggregates for concretes and mortars for various purposes, as well as components of ready-made mixtures, for reclamation, landscaping and planning of territories, for the foundations of highways, runways and aprons of airfields, construction of roadsides. The most studied area of application of aggregates from crushed concrete in concrete for general construction [2, 3] and mortars [4]. The possibility of effective use of aggregates from crushed materials and in self-compacting concretes has been established [5, 6]. Over the past two decades, revolutionary changes have occurred in building materials science, thanks to innovations in physics and chemistry. There are unique special-purpose concretes: translucent, self-cleaning, self-healing, graphic, textile-concrete, luminal concrete and others. All of these concretes belong to the group of modern decorative building materials, the market for which is constantly replenishing [7]. In world construction practice, decorative concrete, first patented in the United States in the 60 s of the last century, was used for colored, stamped and sprayed coatings. Currently, decorative concrete to achieve the required aesthetic properties is obtained by processing: painting, polishing, texturing, embossing, engraving, using toppings and other techniques. This material differs from traditional gray concrete not only in color palette, but also in texture, shape, and the ability to create any ornament. In the construction complex of Russia, decorative concrete is widely used for casting monolithic walls, for finishing surfaces, as well as for creating volumetric artistic and decorative products: sculptures, bas-reliefs, imitation of natural stone. A variety
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of decorative concrete is architectural concrete-a high-tech building material that opens up a wide range of possibilities for the implementation of the architect’s ideas. The surface of structures and structures made of architectural concrete, constantly accessible for viewing, should have an appearance that is functionally focused on creating a certain aesthetic effect. Products made of architectural concrete - small architectural forms (SAF), which simultaneously combine aesthetic appeal and functionality, are used for the improvement and organization of a comfortable urban environment. Concrete for SAF, in addition to high aesthetics (quality of the front surface, appearance, artistic expression), must meet the requirements for durability (frost resistance, water resistance, crack resistance). In addition, a specific feature of SAF is their complex geometric shape and small size, which complicates the use of traditional methods of manufacturing products with vibration compaction methods. Currently, 3D printing technology is available for the implementation of the most daring design solutions from decorative concrete [8]. The use of 3D printers will make it possible to obtain products of any shape and size. But for industrial production, the presented decorative materials and technologies for their production have so far been little studied and require additional research. Therefore, it is rational to organize the production of SAF to meet all the listed requirements from decorative self-compacting concrete using vibration-free technology. When designing the composition of self-compacting concretes, a scientific approach is required to justify the use of raw materials [9]. For self-compacting concrete mixtures, the rational amount of all components must be determined in the process of optimizing the granulometric composition of the mineral part, and the plasticizing chemical additive must be selected individually for a specific type of cement, taking into account its compatibility with all components of the mixture. The formation of the properties of self-compacting mixtures is greatly influenced by the shape, size and number of aggregates. It is known that to ensure high fluidity of the mixtures, the shape of the aggregate grains should approach the rounded one, the grain size of the coarse aggregate should be limited to 16 mm, and the proportion of the fine aggregate in the aggregate mixture (P/(P + W) should be at least 0.45 [10]. The properties of decorative concrete with aggregates from crushed materials have not been sufficiently studied, therefore, the purpose of this work was an experimental assessment of the possibility of the integrated use of aggregates from crushed concrete and mineral dyes in self-compacting mixtures for the production of small architectural forms.
2 Materials and Methods For the processing and integrated use of waste from concrete and reinforced concrete, technological complexes with efficient crushing plants are required. Research in this area has established that the most effective for crushing concrete of increased strength are vibroscopic crushers with multifunctionality and high power [11, 12]. In this work, crushed materials were obtained by crushing in a laboratory jaw crusher of
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the ShchD-10 brand. The raw materials for obtaining crushed materials were control samples of concrete after testing for strength and water resistance, as well as ceramic bricks after determining their physical and mechanical properties. Aggregates made of crushed concrete in accordance with GOST 32,495, after crushing, were scattered on a standard set of sieves, including sieves with round holes with diameters of 10; 5 and 2.5 mm and wire sieves with standard square meshes N 1.25; 063; 0315; 016 in accordance with GOST 6613. The studies used a coarse aggregate made of crushed concrete–single-fraction crushed stone of the largest size 10 mm: true density–2660 kg/m3 , bulk density– 1395 kg/m3 , voidness–47.5%, crushing strength 800. Sand was used as a fine aggregate. from crushed concrete, represented by particles of a mortar component with grain sizes of 1.25–5.0 mm: true density–2650 kg/m3 , bulk density–1420 kg/m3 , voidness–46.4%. Previous studies have established [13] that when using crushed materials in selfcompacting mixtures, a contradiction arises: an increase in the proportion of grains with a developed rough surface contributes to an increase in concrete strength, but at the same time the spreadability of the mixture and its ability to self-compacting decrease. Therefore, to ensure the required fluidity of the mixture, we used natural quartz sand with rounded grains according to GOST 8736: true density–2650 kg/m3 , bulk density–1413 kg/m3 , size modulus–1.61, voidness–46.68%. Iranian white Portland cement of the CEM I 42.5 N class was used as a binder for the preparation of concrete mixtures. To give decorative concrete aesthetic properties and a unique look, it is necessary to add dyes to the mixture–pigments of various origins [14]. In this work, we used the following dyes: white pigment Tongchem TD-R950: rutile titanium dioxide (TiO2 ) with dosage 2% the mass of the entire mixture of mineral components; color pigment Bayferrox 960 orange with a dosage of 2 to 4% by weight of the binder; brick dust– finely dispersed product of screening after crushing ceramic bricks with a particle size of less than 0.16 mm: true density–2640 kg/m3 , bulk density–1000 kg/m3 . To create a stable color of concrete, the dust dosage was 30% of the binder mass. Granulometric composition of finely dispersed materials–white Portland cement and mineral dyes (Fig. 1) were determined on a laser particle analyzer Microsizer201C. When choosing a chemical modifier, the need for high flowability of the concrete mixture and the absence of influence on the color change of decorative concrete were taken into account [15]. Therefore, to control the properties of self-compacting mixtures, we used a chemical additive in the form of a transparent liquid MasterPolyHeed 3545 (MPH 3545) manufactured by BASF. The additive made on the basis of polyaryl and polycarboxylate esters meets the requirements of GOST 24,211 for superplasticizing and super water-reducing additives. The dosage of the additive was 1.2–1.6% by weight of the binder. Preparation of decorative concrete mixtures was carried out according to the following scheme. At the first stage, dry aggregates and pigments were mixed, at the second, binder was added to the mixed mixture, and at the third, liquid components were added. The addition of MPH 3545 to the composition of the concrete mixture
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Differential particle distribution, %
Use of Crushed Materials for Decorative Self-compacting Concrete
White cement
Particle diameter, microns White Orange pigment pigment
Brick dust
Fig. 1 Granulometric composition of fine materials
was introduced into a premixed mixture of mineral components with a part (20%) of the mixing water shortly before the end of mixing. This method of preparation makes it possible to realize the maximum thinning effect of the additive [16]. In the course of the research, the OK cone draft and the average density of concrete mixtures were determined according to the method of the Russian standard GOST 10,181. The workability of decorative self-compacting mixtures was established by the diameter of the concrete cone outflow according to the EN 12,350-8: 2010 method. The diameter of the spreading of the concrete mixture SF, cm, was determined by measuring the diameter of the spreading cake d 1 and d 2 with a tape measure in two mutually perpendicular directions and was calculated by the formula: S F = (d1 + d1 )/2
(1)
Manufacturing, storage under normal conditions and testing for the compressive strength of decorative concrete cubes with a nominal rib size of 100 mm were performed according to the method of the Russian standard GOST 10,180. The assessment of the water-reducing efficiency of the chemical modifier in decorative concrete was carried out according to the coefficient of use of cement K c , kg/MPa, which was calculated by the formula: K c = C/R28 , where C—cement consumption per 1 m3 of concrete, kg, R28 —ultimate compressive strength of concrete at design age, MPa.
(2)
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3 Discussion and Results In this work, we investigated the possibility of using crushed concrete aggregates, the shape of the grains of which is characterized by an acute-angled, developed rough surface; therefore, the optimization of their grain size composition played a key role. The selection of compositions of decorative concrete was carried out on the basis of the results of earlier studies [13]. To determine the rational particle size distribution, the aggregates were dosed on a fractional basis. During the experiments, decorative self-compacting mixtures with aggregates made from crushed materials were investigated, the composition and characteristics of which are shown in Table 1. In the control composition 1D, prepared without mineral dyes, the volume concentration of coarse crushed aggregate was 0.37, the proportion of crushed grains in the fine aggregate was 40%, the volume of cement paste was 341 L, while the mixture was rheologically unstable and did not possess self-compacting properties. Therefore, in 2D-5D compositions, to ensure the fluidity and rheological stability of the mixtures, the volume fraction of crushed stone was reduced by 10%, the amount of cement paste was increased by 10%, and the dosage of the chemical modifier was increased to 1.6% of the cement mass. An increase in the volume of cement paste to 370–380 l led to an increase in the coefficient of expansion of aggregate grains and the creation of a “floating” structure of a coarse aggregate in concrete (Fig. 2). This technological factor ensured high flowability and rheological stability of self-compacting mixtures, even with a content of 40% of crushed grains in the composition of fine aggregate. The presence of finely dispersed materials–white and colored pigments in 2D-4D compositions-did not have a significant effect on the spreadability of the mixtures. This is due to the fact that the grain size composition of the dyes, represented mainly by grains of 7.0–75.0 microns in size, is close to the grain size distribution of white cement (Fig. 1). At the initial stage of structure formation, the dye particles, being located in the intergranular space of the binder, increase the proportion of the finely dispersed phase and, due to the presence of a highly effective chemical additive, contribute to an increase in the fluidity of the mixtures. In the 5D composition, in which brick dust in the amount of 114 kg/m3 was used as a dye, the role of the mineral filler manifested itself to a greater extent. The high dispersion and porosity of brick dust particles inevitably lead to an increase in the water demand of the concrete mixture and the manifestation of instability. Evaluation of the decorative properties of concrete by color (Fig. 2) showed that the presence of titanium dioxide gives the cement matrix of concrete a bright white color (composition 2D) and enhances the intensity of the color pigment (compositions 3D and 4D). In the absence of titanium dioxide, the use of brick dust as a mineral dye gives a weakly pronounced terracotta color (composition 5D). 2D-5D–compositions of decorative self-compacting concrete according to Table 2
Crushed sand fractions, mm
159
190
200
187
152
110
−
−-
−
−
1D
2D
3D
4D
5D
152
157
189
190
120
76
104
75
76
80
143
149
151
152
328
142
150
139
152
−
902
872
880
887
960
−
42
42
42
−
−
17
9
−
−
114
−
−
−
−
6.1
7.0
7.0
7.0
4.1
Crushed Titanium Pigment Brick Additive stone dioxide Bayferrox dust MPH 3545 1.25–2.5 0.63–1.25 0.315–0.63 0.16–0.315 2.5–5.0 1.25–2.5 fractions 5–10 mm
Natural sand fractions, mm
Composition Material consumption, kg/m3
Table 1 Composition and characteristics of concrete mixes
371
380
371
373
341
Volume of cement dough, l
−
−
−
−
21.0
The draft of the cone is OK, cm
55.0
55.0
56.0
55.0
−
Cone flow diameter SF, cm
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2D
3D
4D 5D 2D-5D – compositions of decorative self-compacting concrete according to table 2 Fig. 2 Macro-construction of samples of decorative self-compacting concrete on a cut Table 2 Physical and mechanical properties of decorative concrete Composition
Cement–water ratio
Average density, kg/m3
Compressive strength, MPa, age, day 7
14
28
Specific consumption of cement K C , kg/MPa
1D
1.44
2260
25.0
29.4
38.1
8.8
2D
1.93
2290
43.2
46.0
52.3
8.4
3D
1.92
2305
41.7
45.4
53.5
8.2
4D
1.82
2280
38.5
43.4
49.5
8.8
5D
1.53
2260
30.0
36.5
44.6
8.5
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The super water-reducing additive MPH 3545 plays a decisive role in the formation of the basic properties of decorative self-compacting mixtures. At the same time, having a water-reducing and water-retaining effect, it provides high fluidity, reduces the risk of water separation and stratification during the preparation and placement of mixtures, ensuring that the concrete reaches the required quality indicators. The high potential of the additive and the rheological compatibility with white cement are realized due to the unique polymer structure, in which the rigid linear interaction of the polycarboxylate backbone with the cement surface is compensated by the flexible bulk action of polyaryl ethers. This provides the required regulation of the rheological properties of the concrete mixture. The high efficiency of the super water-reducing additive MPH 3545 in decorative self-compacting mixtures is also evidenced by the physical and mechanical characteristics of decorative concrete (Table 2). Analysis of the strength characteristics of decorative concretes shows that the use of the super water-reducing additive MPH 3545 in the optimal amount increases the cement–water ratio and provides an increase in the strength of concrete (compositions 2D-4D). At the same time, even the presence of crushed flaky grains in the macrostructure of concrete (Fig. 2) does not reduce its strength. The use of brick dust, the dosage of which in the 5D composition was 30% of the binder mass, led to a noticeable increase in water demand and, as a consequence, to a drop in concrete strength. When comparing the strength characteristics of decorative concretes of 3D and 4D compositions, which differ in the dosage of Bayferrox colored pigment, a decrease in the strength of concrete with an increase in the consumption of orange dye was noted. This is due to the fact that pigment particles, being located in the intergranular space of the cement in large quantities, violate the solidity of the crystalline intergrowth of the cement matrix and reduce its strength. At the same time, an increase in the consumption of pigment up to 4% in the 4D composition did not lead to a noticeable increase in color. The kinetics of the strength gain of decorative concretes, shown in Fig. 3, confirms the previously obtained conclusions about the main increase in the strength of self-compacting concretes in the first seven days [16]. Evaluation of the effectiveness of decorative concrete compositions, performed according to the coefficient of use of cement Kc (Table 2), showed that obtaining self-compacting concrete mixtures with a minimum specific consumption of cement, ensuring the receipt of concrete of the required strength, is quite achievable due to the high water-reducing ability of the chemical modifier. Decorative self-compacting mixtures of 2D and 3D compositions with aggregates made of crushed materials at a nominal cement consumption of 440 kg/m3 , possessing high fluidity, at the design age reach a strength of 52–53 MPa. These compositions are characterized by the minimum value of the cement utilization factor Kc = 8.2–8.4, which confirms the realization of the high potential of the super water-reducing additive MasterPolyHeed 3545.
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60 55 Compressive strength, MPa
50 45 40 35 30 25 20 15 10 5 0
1D
Age of concrete:
2D
3D Composition
- 7 days
4D
- 14 days
5D
- 28 days
Fig. 3 Kinetics of the strength set of decorative concrete
4 Conclusions The research has revealed the fundamental possibility of the integrated use of construction waste–aggregates from crushed materials–for the preparation of decorative self-compacting concretes. With an optimal amount of cement paste, crushed grains with an acute-angled and rough surface do not impede the high flowability of the concrete mixture. It was found that the decisive technological factor in the production of decorative self-compacting concretes is the use of a new generation of super water-reducing additive MasterPolyHeed 3545. Due to the unique structure of polymers, the additive shows high efficiency and guarantees the achievement of the required quality indicators by concrete. It is noted that the inclusion of titanium dioxide in the composition of decorative concretes gives the cement matrix a bright white color and enhances the intensity of the colored pigment. Bayferrox orange dye in the amount of 2% by weight of the cement gives the concrete a light terracotta color. An increase in the consumption of this pigment to 4% did not affect the color change, but led to a drop in concrete strength by 8%. It has been experimentally established that the use of crushed finely dispersed material–brick dust–as a mineral colorant gives concrete a weakly expressed terracotta color. To ensure the required spreadability of the mixture and achieve the required strength of decorative concrete, the dosage of this dye in the absence of titanium dioxide must be adjusted. The studies performed allow us to recommend effective compositions of self-compacting mixtures with aggregates from crushed materials and a minimum
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specific consumption of cement for the production of small architectural forms and other products from decorative concrete.
References 1. Hendriks CF (1985) The use of concrete and masonry waste as aggregates for concrete production in the Netherlands. In: EDA/ILEM Conference Reuse of Concrete and Brick Materials. Rotterdam, pp 34–35 2. Pulyaev SM, Kaddo MB, Pulyaev IS (2012) Investigation of the process of early structure formation of concrete on crushed stone from concrete scrap. Vestnik MGSU 1:68–71 3. Goncharova MA, Borkov PV, Al’-Surrajvi Hamid Galib Hussajn (2019) Recycling of largecapacity concrete and reinforced concrete waste during the implementation of full-life cycle contracts. Constr Mater 12:52–57. https://doi.org/10.31659/0585-430X-2019-777-12-52-57 4. Pavlov AV, Korovyakov VF (2021) The effect of the addition of ground concrete scrap on the kinetics of changes in the strength of cement-sand mortar. Eng Bull Don 3. https://ivdon.ru/ru/ magazine/archive/n3y2021/6879 5. Modani PO, Mohitkar V (2014) Self-compacting concrete with recycled aggregate: a solution for sustainable development. Int J Civ Struct Eng 4:430–440 6. Larsen OA, Naruts VV, Voronin VV (2020) Technology of processing of concrete scrap in order to obtain self-compacting concrete. Constr Reconstr 2(88):61–66. https://doi.org/10.33979/ 2073-7416-2020-88-2-61-66 7. Trishchenko IV, Kaklyugin AV, Gurevnina ER, Karpov AA (2019) Modern decorative building materials, Actual problems of science and technology. In: Materials of the National Scientific and Practical Conference, (Rostov-on-Don, 26–28 March 2019), DSTU, pp 771–772. 8. Slavcheva GS (2021) Construction 3D printing today: potential, problems and prospects for practical implementation. Constr Mater 5:28–36. https://doi.org/10.31659/0585-430X-2021791-5-28-36 9. Nesvetaev G, Koryanova Y et al (2020) To the problem of assessing the level of self-stresses during the formation of the structure of self-compacting concrete. Mater Sci Forum 974:293– 298. https://doi.org/10.4028/www.scientific.net/MSF.974.293 10. Nesvetaev GV, Davidyuk AN, Khetagurov BA (2009) Self-consolidating concretes: some factors determining concrete mix fluidity. Constr Mater 3:54–57 11. Gusev BV, Kudryavtseva VD (2013) Crushing of reinforced concrete products and secondary use of concrete. Tech Technol Silic 20(2):25–28 12. Egorochkina IO, Kucherenko DY (2017) Upgrading jaw crusher agregate to improve the quality of reused crushed stone, Construction and Architecture-2017. In: Faculty of Civil Engineering: Materials of the Scientific and Practical Conference, Rostov-on-Don, DSTU, pp 76–80 13. Kastornykh L, Kaklyugin A et al (2021) Technology of small architectural forms for the improvement of rural settlements. In: XIV International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness–INTERAGROMASH 2021”, E3S Web of Conferences, vol 273, p 06003. https://doi.org/10.1051/e3sconf/202127306003 14. Labuzova MV, Ogurcova YuN, Balickij DA, Strel’cova TP (2016) Aspects of the use of pigments of various origins in building materials. In: High-tech Technologies and Innovations: Proceedings of the International Scientific and Practical Conference (XXII Scientific Readings), Belgorod, vol 3, pp 209–21 15. Kastornykh LI, Cherepanov VD (2019) Changing the spreadability of cement compositions with the addition of a multifunctional modifier. Young Res Don 5(20):27–33 16. Rautkin AV, Kastornykh LI (2017) The choice of chemical modifiers to ensure the spreadability of self-compacting concrete mixes. Young Res Don 4(7):118–126
Experimental Study of the Technology of Splicing Steel Rope on Machines with Rope Traction Edward Marchenko , Sergey Popov , Andrey Izyumov , Julianna Marchenko , and Evgeny Kosenko
Abstract The article presents the materials of an experimental study of the dependence of the formation of a “waviness” defect on the technologies for splicing a steel rope according to the factor of changing the resultant load applied to all strands under static loading of the rope in the splicing zone. The studies were carried out on a manufactured experimental setup, which makes it possible to implement this method and makes it possible to determine the magnitude of the resultant load applied to each strand. Experimental studies confirm that with the existing technology of splicing, the geometric integrity of the joint is violated, leading to an uneven distribution of the load between all the strands in the joint “lock” of the joint and, as a result, the formation of a “waviness” defect. In the section of splicing with the new technology using a conductor, a uniform distribution of the resultant load in all strands of the rope is observed, which confirms the effectiveness of the proposed technology for splicing steel ropes. Keywords Rope transport · Steel rope · Steel rope splicing
1 Introduction An experimental study was carried out in order to experimentally verify the theoretical calculations of the rejection indicators of “waviness” in the section of the steel rope splicing according to residual deformations with two different splicing technologies [1–5]. The methodology for conducting an experimental study involves determining the dependence of the waviness parameters on the magnitude of the loading of each strand of the rope during its static loading in the splicing zone. Previously, it was assumed that the most susceptible area to the formation of a structural defect in the form of “waviness” is the area of splicing of steel ropes. It has been theoretically proven that with the existing technology in the section of the link E. Marchenko · S. Popov (B) · A. Izyumov · J. Marchenko · E. Kosenko Don State Technical University, Gagarin Square, 1, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_186
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in the docking node “castle” the resultant load is shifted by the amount of eccentricity relative to the axis, therefore, the geometric integrity of the cross section of the steel rope is violated due to uneven loading of wires and strands. With this technology, the symmetry of the cross-section in the “locks” is violated, which, as a result of quasi-static loading, develops to critical values of the “waviness” rejection index. A new technology for splicing a steel rope has been proposed and patented, which consists in the use of a polymer core (conductor) [1, 2]. Mathematical modeling has established a dependence under which a steel rope is subject to rejection in the splicing area in the presence of a “waviness” defect with the ratio dw /dk > 1,33.
2 Methods and Materials To confirm the adequacy of the theoretical models and determine the empirical coefficients, studies were carried out on the dependence of the formation of the “waviness” defect on the splicing technologies in terms of the change in the resultant load applied to all strands under static loading of the rope in the splice zone. On the basis of this and taking into account the preliminary results, the studies were carried out on a manufactured experimental setup, which makes it possible to implement this method and makes it possible to determine the magnitude of the resultant load applied to each strand [6–9]. To determine the magnitude of the distribution of the resultant load applied to each individual strand of a steel rope, an installation was made (Fig. 1), which makes it possible to determine the magnitude of the application of the resultant forces through tensile forces and are determined by numerical values according to the readings of strain gauges connected to each strand. Resistor-type strain gauges (Fig. 2) are used as a measuring device, which make it possible to determine the magnitude of the tensile force by changing the electrical resistance. The sensors are glued with a special epoxy lacquer glue to the outer and inner sides of metal rings in the amount of 6 pieces, 1.5 mm thick and 40 mm in diameter, made of the material grade—steel 45, which makes it possible to well tolerate tensile forces during loading (Fig. 3). The principle of operation of strain gauges is as follows: under the action of a tensile force, the wire from which the sensitive element of the strain gauge is made increases its length in proportion to the force acting on the metal ring; when the length changes, the resistance also changes [10]. For a more accurate determination of tensile forces when exposed to a metal ring, two strain gauges were used, for each ring of the installation, connected to a bridge connection with two 100 resistors. To determine the accuracy of the readings of strain gauges, they were calibrated. Each metal ring with connected sensors was loaded on an exemplary dynamometer to a value of 25 kgf (250 N) at a constant applied voltage of 5 V. The readings were taken with an industrial analogue–digital millivoltmeter of pulsed current B3—52/1,
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1
2 3
4
5 load Fig. 1 Structural diagram of the installation: 1—steel rope; 2—a strand of rope; 3—strain gauge; 4—support platform of the installation; 5—counterweight
Fig. 2 Structure of resistor type strain gauge
Fig. 3 The layout of the strain gauge resistor type on a metal ring
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Fig. 4 Graph of calibration and determination of the range of readings of strain gauges
the value of the applied and received signal was set by a DSO1062S oscilloscope. The calibration results are shown in the graph (Fig. 4). The experiment was carried out using two types of steel ropes with a diameter of 10 mm with an organic core made of carbon and alloy steel according to GOST 1050 and GOST 14,959. The steel ropes were alternately loaded under the static weight of the counterweight and installation, which ultimately amounted to 25 kg with the possibility of a gradual increase in weight. A prerequisite for the performance of a steel rope is the uniform application of the resultant load to all wires and strands in the cross section of the steel rope [11–19]. Therefore, the design scheme of loading for a six-strand rope must fulfill the load distribution condition equal to the ratio of the entire resultant load Px applied to the steel rope by the number of strands nunt (Pp = Px /nun ).
3 Results and Discussion Table 1 presents the results obtained by measuring the distribution of the resultant load applied to each individual strand, subject to the study of various sections of steel ropes: without a section of a splice, with a section of a splice with an existing splicing technology and with a section of a splice with a new splicing technology using a conductor. Analyzing the results of experimental measurements, we can conclude that when checking the distribution of the resultant load on a steel rope without a splicing section, the resultant load is applied uniformly to each strand of the rope, which confirms the condition for the uniform application of the resultant load to each individual strand [20–26].
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Table 1 The results of measurements of the resultant load in each individual strand Strand №
Section of steel rope without splicing kgf (N)
kgf (N)
kgf (N)
1
4.16 (40.795)
4.16(40.795)
4.17 (40.893)
2
4.16 (40.795)
3.89 (38.147)
4.15 (40.697)
3
4.16 (40.795)
3.90 (38.245)
4.16 (40.795)
4
4.16 (40.795)
4.20 (41.187)
4.18 (40.991)
5
4.16 (40.795)
4.32 (42.364)
4.19 (41.089)
6
4.16 (40.795)
4.53 (44.424)
4.15 (40.697)
Section of a steel rope splice with existing splicing technology
Steel rope splicing area with new technology using a conductor
At the splicing site with the existing splicing technology, a redistribution of the resultant load is observed. The load between the strands is distributed extremely unevenly, strands numbered 2 and 3 are underloaded, and strands numbered 5 and 6 are overloaded, which leads to a displacement of the resultant load relative to the axis of the steel rope and causes torsion. The torsion of the steel rope in the splicing area is caused by a geometric change in the tangential gaps in the cross section between the strands in the locks “knots” provided by the splicing technology, which ultimately leads to its eccentric loading of the steel rope. An eccentric application of a load in the cross section of a steel rope in case of violation of the splicing technology can also lead to plastic deformation of the strands. During plastic deformation, the steel rope takes the form of a helix, characterized by a rejection indicator—"waviness” [27]. In the section of splicing with the new technology using a conductor, a uniform distribution of the resultant load in all strands of the rope is observed, which confirms the effectiveness of the proposed technology for splicing steel ropes [28]. To confirm the data on the results of measurements of the distribution of the resultant load applied to each strand of a steel rope, an experimental verification of two technologies for splicing a steel rope was carried out according to the ratio dw /dk > 1.33, formed waviness to the nominal diameter of the rope. According to the ratio established during mathematical modeling, a calculated one is given (Table 2), which allows you to establish the dependence of the value of the normalized waviness for a steel rope with dk = 10 mm. The complete absence of the manifestation of the “waviness” defect will be a value equal to 1.0. Figures 5, 6, 7, 8, 9 and 10 present the main results of experimental studies. The results of experimental studies have shown that under static loading, the formation of a “waviness” defect was observed only in steel ropes with splicing areas Table 2 The calculated values of the parameter “waviness” at dk = 10 mm dw / dk
8/10
9/10
10/10
11/10
12/10
13/10
14/10
15/10
Waviness value
0.8
0.9
1.0
1.10
1.20
1.30
1.40
1.50
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Fig. 5 The dependence of the indicators of the magnitude of the resultant load Px to the ratio of the magnitude of the waviness dw /dk for the section of the steel rope without splicing: a—steel according to GOST 1050; b—steel according to GOST 14,959
Fig. 6 Photo of a steel rope without a spliced section
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Fig. 7 The dependence of the indicators of the magnitude of the resultant load Px to the ratio of the magnitude of the waviness dw /dk for a steel rope with a splicing section according to the existing technology: a—steel according to GOST 1050; b—steel according to GOST 14,959
Fig. 8 Photo of a steel rope from a splicing site using existing technology
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Fig. 9 The dependence of the indicators of the magnitude of the resultant load Px to the ratio of the magnitude of the waviness dw /dk for a steel rope with a splicing section according to a new technology using a conductor: a—steel according to GOST 1050; b—steel according to GOST 14,959
according to the existing technology and according to the ratio dw /dk amounted to 1,40 and 1,50. The received values do not satisfy the condition dw /dk > 1.33, exceeding the calculated indicator, which is a rejection indicator and can lead to its structural destruction [20–26]. Experimental studies confirm that with the existing technology of splicing, the geometric integrity of the joint is violated, leading to an uneven distribution of the load between all the strands in the joint “lock” of the joint and, as a result, the formation of a “waviness” defect. The analysis of experimental studies confirms that the proposed theoretical models are adequate and can be used in the technical design of steel ropes, and splicing [1, 2, 7].
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Fig. 10 Photo of a steel rope from a splicing area using a new technology using a conductor
References 1. Marchenko E, Korotky A, Popov S, Marchenko J, Dontsov N, Kosenko E (2022) Investigation of the causes of defects in the section of steel rope splicing. In: Beskopylny A, Shamtsyan M (eds) XIV International scientific conference “INTERAGROMASH 2021,” vol 246. Lecture Notes in Networks and Systems. Springer, Cham, pp 226–234. https://doi.org/10.1007/978-3030-81619-3_25 2. Marchenko EV, et al (2021) Modelling of technological process of joining steel ropes with the use of powder antifriction material and a conductor. Intelligent information technology and mathematical modeling 2021 (IITMM 2021): J Phy: Conf Ser 2131:042060. https://doi.org/ 10.1088/1742-6596/2131/4/042060 3. Marchenko J, Korotky A, Popov S, Marchenko E, Galchenko G, Kosenko V (2022) unicipal waste management in an urbanized environment based on ropeway technology. In: Beskopylny A, Shamtsyan M (eds) XIV International scientific conference “INTERAGROMASH 2021,” vol 246. Lecture Notes in Networks and Systems. Springer, Cham, pp 235–241. https://doi. org/10.1007/978-3-030-81619-3_26 4. Popov S, Galchenko G, Marchenko J, Drozdov D (2022) Use of neural networks and autopilot for quick and accurate grain discharge on the elevator. In: Shamtsyan M, Pasetti M, Beskopylny A (eds) Robotics, machinery and engineering technology for precision agriculture, vol 247. Smart Innovation, Systems and Technologies. Springer, Singapore, pp 45–53. https://doi.org/ 10.1007/978-981-16-3844-2_6 5. Ivanov VV, Popov SI, et al (2021) Chemical and mechanical bases of coating application in vibration technological systems. XVI International scientific-technical conference «Dynamics of technical systems» (DTS-2020): IOP conference series: materials science and engineering, vol 1029, p 012052. https://doi.org/10.1088/1757-899X/1029/1/012052 6. Ivanov VV, et al (2020) The oxide film formation under vibration processing in the highresource parts manufacture in transport engineering. International Scientific Conference «Construction and Architecture: Theory and Practice for the Innovation Development» (CATPID2020): IOP conference series: materials science and engineering, vol 913, p 042056. https:// doi.org/10.1088/1757-899X/913/4/042056
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7. Korotky AA, et al (2020) Theoretical foundations of modeling the process of transport vehicles steel ropes structural defects formation. XIII International Scientific and Practical Conference «State and Prospects for the Development of Agribusiness—INTERAGROMASH 2020»: E3S web of conferences, vol 175, p 05018. https://doi.org/10.1051/e3sconf/202017505018 8. Korotky AA, et al (2020) The use of SmartBox container for agrobusiness logistic processes optimization. XIII International scientific and practical conference «State and Prospects for the Development of Agribusiness—INTERAGROMASH 2020»: E3S web of conferences, vol 175, p 13019. https://doi.org/10.1051/e3sconf/202017513019 9. Korotky AA, et al (2019) Model of forming vibration mechanochemical solid lubrication coating on surface of steel rope. XII International scientific conference on agricultural machinery industry (INTERAGROMASH 2019): IOP conference series: earth and environmental science, vol 403, p 012116. https://doi.org/10.1088/1755-1315/403/1/012116 10. Kostoglotov AA et al (2019) Meas Tech 62:497–502. https://doi.org/10.1007/s11018-019-016 52-8 11. Lazarenko SV, Kostoglotov AA (2017) J Commun Technol Electron 62(2):123–127. https:// doi.org/10.1134/S1064226917020061 12. Soloviev A, et (2020) Mathematical and laboratory modeling of resonant impact on the spike for the purpose of grain selection. E3S web of conferences, vol 210, p 05017 ITSE-2020 https:// doi.org/10.1051/e3sconf/202021005017 13. Matrosov M, et al (2020) Calculation of the movement trajectory of the grain mass in the field stripper. E3S web of conferences, vol 210, p 08015 (ITESE-2020) https://doi.org/10.1051/e3s conf/202021008015 14. Kostoglotov AA et al (2019). AIP Conf Proc. https://doi.org/10.1063/1.5138398 15. Lazarenko SV et al (2019) J Commun Technol Electron 54(4):431–438. https://doi.org/10. 1134/S1064226909040081 16. Solovyov S, et al (2021) E3S web of conferences, vol 273, p 07030. https://doi.org/10.1051/ e3sconf/202127307030 17. Lachuga Y, et al (2020) Innovative pneumatic device for combined seeding of various tilled crops. E3S web of conferences, vol 210, p 08016 ITSE-2020. https://doi.org/10.1051/e3sconf/ 202021008016 18. Solovyov SG, et al (2017) Improvement of the internal combustion engine control system. IEEE east-west design & test symposium (EWDTS), p 8110083. https://doi.org/10.1109/EWDTS. 2017.8110083 19. Meskhi B et al (2021) Finite element and applied models of the stem with spike deformation. Agric 11:1147. https://doi.org/10.3390/agriculture11111147 20. Solovyov SG,et al (2018) improvement of the design of a microprocessor-based power supply control system of an internal combustion engine, east-west design & test symposium (ewdts), p 8524841. https://doi.org/10.1109/EWDTS.2018.8524841 21. Meskhi B, Bondarenko V, et al (2020) Impact of globalization and digitalization on the efficiency of environmental development of territories. E3S web of conferences, vol 217, p 06012 ERSME-2020 https://doi.org/10.1051/e3sconf/202021706012 22. Kalmykov BY et al (2016) Effect of the bus bodywork on impact strength properties in roll-over. ARPN J Eng Appl Sci 11(17):10205–10208 23. Savenkov D, et al (2019) Static and dynamic friction coefficients of grain crops and mineral materials. IOP conference series: earth and environmental science, vol. 403, p 012069. https:// doi.org/10.1088/1755-1315/403/1/012069. 24. Kalmikov BY et al (2015) The use of additional devices for reducing the deformation of the bus body when tipping. ARPN J Eng Appl Sci 10(12):5150–5156 25. Panfilov IA, et al (2020) Finite element simulation of airflow in a field cleaner. IOP conference series: materials science and engineering 1001 012060. https://doi.org/10.1088/1757-899X/ 1001/1/012060. 26. Kalmikov BY et al (2015) Application of the method of distribution of the total energy of impact on the bearing elements of the body of the bus when calculating the failure loads. ARPN J Eng Appl Sci 10(10):4366–4371
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27. Kokieva GE, et al (2021) The mechanical life of implements operating in corrosive service, e3s web of conferences. XIV International scientific and practical conference “State and Prospects for the Development of Agribusiness–INTERAGROMASH 2021”. Rostov-on-Don. p 07004 28. Lachuga Y, et al (2020) Energy-saving tillage with a combined unit with universal working bodies. IOP conference series: materials science and engineering. The collection of conference materials. Voronezh State University of Engineering Technologies. p 012121
Improving the Safety of Operation of Handling Equipment During Container Transportation Aleksey Demyanov , Sergey Popov , Nikolay Dontsov , Julianna Marchenko , and Irina Pavlova
Abstract The efficiency and competitiveness of the transport system, ceteris paribus, directly depends on improving the safety of operation of all components of this system. To ensure the safety of rail hoisting and transport vehicles, the design of a crane buffer with a self-reinforcing effect is proposed, which ensures a smooth stop of a rail object during uncontrolled movement or emergency braking. At the same time, a smooth increase in braking power significantly reduces the likelihood of derailment and overturning of the crane in the longitudinal or transverse planes. An analytical dependence has also been obtained, which makes it possible to determine its dimensions, the configuration of power elements and other parameters, depending on the conditions of the problem due to the specific location of the buffer. The proposed solution is characterized by versatility, manufacturability and low resource consumption. Keywords Cranes · Emergency braking · Buffer · Accident-free · Safety
1 Introduction Based on the geographical location of Russia, it is difficult to overestimate the importance of the Russian transport system for the state. Firstly, it connects producers and consumers of material goods from significantly remote regions, and secondly, in the modern, yet global world, in the context of increasing interstate and transcontinental transit traffic, it provides excellent opportunities for effective participation in international trade. Obviously, the efficiency of all its subsystems significantly affects the current and future state of the country’s economy. A. Demyanov · S. Popov (B) · N. Dontsov · J. Marchenko Don State Technical University, Gagarin Square, 1, Rostov-on-Don 344003, Russia e-mail: [email protected] I. Pavlova Moscow State University of Technology and Management, 55, Semashko Street, Rostov-on-Don 344082, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_187
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Currently, according to various estimates, the world transports more than 13 billion tons of cargo per year, worth about 30 trillion. dollars, and by 2030, for example, its trade turnover is projected to increase by more than 30%, that is, up to about 17 billion tons of cargo per year. In addition to the observed increase in traffic volumes, there is also a fundamental change in logistics routes that have been established for decades. For example, in May last year, due to technical problems in the Suez Canal, Maersk began sending cargo from Southeast Asia to Turkey via Russia by rail, bypassing the canal. Under the current conditions, the favorable geographical position of our country is already contributing to a significant increase in the popularity of container transportation among domestic operators within the country, as well as increasing the attractiveness of its transport potential among foreign operators, even in a pandemic. So in August 2021, Maersk, as the world leader in container transportation, opened the first container warehouse in Russia in the port of Novorossiysk for 1,500 TEU and a throughput capacity of about 600 thousand tons per year, which in turn contributed to the further growth of transit container traffic on routes from Asia to Turkey, Europe, etc. In the first eight months of 2021, the Russian container market grew by 15.7%, and against the backdrop of a sharp increase in demand for container transportation, Russian cargo terminal owners began to actively build new facilities or convert existing ones for reloading containers. There is also a steady increase in the share of container transportation compared to carriage in wagons. The steady growth of the container market in Russia causes an increase in the intensity of the work of the existing transshipment equipment at transshipment terminals, as well as an increase in the fleet of such vehicles. The need for new crane and handling equipment is constantly increasing, and not only in Russia. Due to the growth in global trade turnover, which persists despite sanctions, rising fuel prices and instability in the foreign exchange markets, programs for the modernization and renewal of terminal equipment do not stop at almost any major terminal. Due to the fact that the Russian industry lags far behind other countries in terms of the degree of containerization, and in countries, for example, Europe, up to 70% of all cargo is transported by containers, the owners of domestic terminals are actively reducing the gap by increasing the fleet of specialized equipment, since its use significantly increases the profitability of their enterprises. Taking into account the high cost of new terminal machines in modern conditions, one of the ways to reduce the cost of transshipment operations with containers is to increase the actual service life of already operating ones, which largely depends on operating conditions. Trouble-free operation increases the actual performance and durability, which, of course, are one of the main consumer characteristics of any commercial vehicle. Among the constructive methods that ensure accident-free operation, one of the most important is the equipment of cranes with devices that should ensure their smooth stop during uncontrolled movement or emergency braking at the end sections of the track.
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2 Methods and Results As it is known, in accordance with Russian Standards, all machine-driven hoisting machines, as well as their trolleys moving along the rail track, must be equipped with an appropriate buffer device to mitigate a possible impact on the track limiters or each other. Buffers can be installed both at the ends of the track, and on the bogies and bridges themselves. On bridges they are attached to the end beams or balancers, and on bogies—to the frame on both sides or on the bridge. As you know, in accordance with Russian Standards, all machine-driven hoisting machines, as well as their trolleys moving along the rail track, must be equipped with an appropriate buffer device to mitigate a possible impact on the track limiters or each other. Buffers can be installed both at the ends of the track, and on the bogies and bridges themselves. On bridges they are attached to the end beams or balance beams, and on bogies – to the frame on both sides or on the bridge. At the moment, there are many options for the design of buffers, but the improvement of their designs in order to improve their characteristics continues at the present time. The main task of dead-end buffers is to stop the rail mechanism with maximum safety. In this case, the probability of its overturning in the longitudinal or transverse planes of the track will depend on the smoothness, “softness” of braking. Since in the case of container loaders we are talking about significant spans (up to 50 m) and masses concentrated in the upper part of the structure, the smoothness of braking is of fundamental importance here. To improve the smoothness and, consequently, the safety of braking of massive structures, a buffer based on the principle of the servo effect [1–4] is proposed, which provides a smooth increase in braking power and allows stopping the decelerated braking object without damage. The buffer (Fig. 1) works as follows. After hitting the wheel 1 of the hoisting and transport device on the brake shoe 2, their joint movement begins as a single system. The braking of the crane is carried out due to the friction of the wheel on the block, equipped with a friction lining, as well as due to the friction of the block, also equipped with a friction lining, along the rail. If the kinetic energy is not extinguished and the crane does not stop, then further movement through the rod 4 and thrust washer 3 through the cover 5 leads to the movement of the friction assembly, consisting of a cone 6 and a split cylinder 7 inside a round pipe–body 8. The split cylinder is supported by a spring 9 and resists movement, which leads to a wedging effect and an increase in frictional forces between the body and the outer surface of the cylinder in proportion to the compression of the spring and the speed of the compression itself. Due to the difference/lower coefficient of friction in the cone-cylinder pair and the cylinder-case pair, a reaction force is created in this unit, which ensures that the pad is pressed against the wheel. In the aggregate of the well-coordinated work of each of the nodes, a servo effect is obtained that provides an increase in friction forces and, as a result, the absorption of kinetic energy in proportion to the speed of movement. After stopping and leaving the crane in the
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Fig. 1 Buffer operation scheme: 1—crane wheel, 2—brake shoe, 3—thrust washer, 4—push rod, 5—case cover, 6—cone, 7—split cylinder, 8—draft gear body, 9—cylinder spring, 10—return spring, 11—thrust washer
working area, the return spring 10 through the thrust washer 11 return the mechanism to its original state. Based on the purpose of the dead-end buffer, it follows that the speed suppression range of the decelerated object is its main characteristic. At the same time, the parameters that determine this range are the processes occurring on the faces of the pads, in the elements of the wedge system and in the springs. To analyze the working conditions of the proposed design, we define the equation of movement of the mechanism. For mechanisms with one leading link, in particular, the equation of motion in integral form is used [1–5]. n i=1
Wi =
n i=1
Ti −
n i=1
Ti0
(1)
where n—number of moving links; Wi—work of external forces acting on the link i, on the final displacement for the period under consideration; Ti—kinetic energy of the link i at the end of the period under consideration. According to the condition of the stop, the speed at the end of the working stroke should be equal to zero, i.e., for our case, the work done by the buffer during braking (working stroke) will be determined by the total work nof the friction forces in the n W , in pair block-rail wheel-block friction pair i i=1 i=1 W2 and pair of cylindern W3 body i=1 n i=1
W =
n i=1
W1 +
n i=1
W2 +
n i=1
W3
(2)
Since in the real case the length of the permitted braking distance on the crane paths depends on the parameters of each particular transshipment yard, we will calculate for one turn. The work of the friction forces on the repayment of the kinetic energy Wi, performed by the wheel relative to the inclined face of the shoe during the working
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stroke, i.e. one turn will be W1 = Ff1 ∗ lk
(3)
where Ff1—friction force in a wheel-block friction pair. LK—wheel circumference Ff1 = F1 ∗ f1
(4)
In fact, the interaction of the wheel and pad occurs on the surface, but for the convenience of calculation, we will replace the dispersed force of action with the force concentrated at a point in the center of the pad (Fig. 2). In this case, the line of action of this force will pass at an angle α = 45◦ . With regard to our case, the force F1 by its nature will depend on the one hand on the inertia force of the moving crane, as a projection onto the line of action,
Fig. 2 Scheme of the forces of interaction between the wheel and the pad
Fig. 3 Contact diagram of the cone and split sleeve
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F1 = Fu /cos α
(5)
and on the other hand, from the weight of the crane per wheel and also as a projection onto the line of action, F1 = G/k ∗ sin α
(6)
where k—number of wheels on the crane support. Thus, the work of the friction force on the pad W1 = (Fu /cos α + G/k ∗ sin α) ∗ f1 ∗ lk
(7)
Consider a shoe-rail pair [6–12]. The work of the friction force W2 in this pair will depend entirely on the force of pressing the shoe against the rail, i.e. on the weight of the crane per wheel W2 = G/k ∗ f2 ∗ lk
(8)
Next, consider a cylinder-body pair. According to the proposed solution, the coefficient of friction between the split cylinder and the cone is much less than between the cylinder and the housing. The work of the friction force W3 in the elements of the wedge system will be determined by the inertia force of the crane remaining after braking by the block W3 = (Fu − Ff1 − Ff2 ) ∗ tgy ∗ f3 ∗ Lk
(9)
The total work of the friction forces will have the form of the following dependence (Fig. 3): W = Fu /cos45 ∗ f1 ∗ lk + G/k ∗ sin45 ∗ f1 ∗ lK + G/k ∗ f2 ∗ lk + (Fu − Ff1 − Ff2 ) ∗ tgy ∗ f3 ∗ Lk
(10)
It must be remembered that the buffer is placed on each rail, so the resulting value of the kinetic redeemed due to friction forces will double. Taking into account the nature of the acting forces, we will reveal the parameters included in the obtained dependence and determine the measured projections that determine the operation of the proposed buffer: V = ϕ[m, V, L, k, f1 , f2 , f3 , α] where m—mass of the braked object, V—initial speed of the braked object, L—permitted braking distance, k—number of rollers in the crane support,
(11)
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f1—coefficient of friction in a wheel-shoe friction pair, f2—coefficient of friction in a shoe-rail friction pair, f3—coefficient of friction in a friction pair split cylinder-buffer housing, α—the angle of inclination of the contacting faces in a split cylinder-cone. It should be noted that such parameters as the mass of the braked object, its initial speed, the number of rollers in the crane support and the permitted length of the braking distance are the parameters that form the conditions of the problem [13–27]. And such parameters as the coefficient of friction in pairs of wheel-block, block-rail, split cylinder-buffer body, as well as the angle of inclination of the faces in the split cylinder-cone are those parameters, varying which the task is solved, and for each specific case. This approach ensures the versatility of the proposed method of braking massive objects on rails, allowing you to adapt the buffer parameters of the proposed design to the required values of the permitted masses and speeds [28–30].
3 Conclusion The design of the crane buffer system is proposed, and based on the results of the analysis, a functional dependence of the braking process is compiled, the parameters of which determine the performance of the buffer and allow you to adjust them to solve the problems of safe operation of cranes in each specific case. Obviously, the development and implementation of technologies that increase the actual durability and performance of transfer cranes, without requiring significant capital investments, contributes to increasing the efficiency and competitiveness of transport and logistics processes in the country.
References 1. Demyanov A, Demyanov A et al (2019) IOP Conference Series: Materials Science and Engineering, vol 403, p 012015. https://doi.org/10.1088/1755-1315/403/1/012015 2. Demyanov A, Demyanov A et al (2019) IOP Conference Series: Materials Science and Engineering, vol 698, p 066028. https://doi.org/10.1088/1757-899X/698/6/066028 3. Demyanov A, Demyanov A et al (2019) IOP Conference Series: Materials Science and Engineering, vol 698, p 066044. https://doi.org/10.1088/1757-899X/698/6/066044 4. Demyanov A, Demyanov A et al (2021) IOP Conference Series: Materials Science and Engineering, vol 1029, p 012004. https://iopscience.iop.org/article/10.1088/1757-899X/1029/1/ 012004 5. Marchenko EV et al (2022) Investigation of the causes of defects in the section of steel rope splicing. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference INTERAGROMASH 2021. LNNS, vol 246, pp 226–234. Springer, Cham. https://doi. org/10.1007/978-3-030-81619-3_25 6. Marchenko EV et al (2021) J Phys Conf Ser 2131:042060. https://doi.org/10.1088/1742-6596/ 2131/4/042060
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7. Soloviev A, Matrosov A et al (2020) Mathematical and laboratory modeling of resonant impact on the spike for the purpose of grain selection. In: E3S Web of Conferences, vol 210, p 05017. https://doi.org/10.1051/e3sconf/202021005017 8. Marchenko J, Korotky A, Popov S, Marchenko E, Galchenko G, Kosenko V (2022) Municipal waste management in an urbanized environment based on ropeway technology. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference INTERAGROMASH 2021. LNNS, vol 246, pp 235–241. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_26 9. Meskhi B, Rudoy D et al (2021) Finite element and applied models of the stem with spike deformation. Agriculture 11:1147. https://doi.org/10.3390/agriculture11111147 10. Popov SI, Galchenko GA et al (2022) Smart innovation. Syst Technol 247:45–53. https://doi. org/10.1007/978-981-16-3844-2_6 11. Kostoglotov AA et al (2019) Meas Tech 62:497–502. https://doi.org/10.1007/s11018-019-016 52-8 12. Lazarenko SV, Kostoglotov AA (2017) J Commun Technol Electron 62(2):123–127. https:// doi.org/10.1134/S1064226917020061 13. Meskhi B, Bondarenko V et al (2020) Technical, technological and managerial solutions in ensuring environmental safety. In: IOP Conference Series: Materials Science and Engineering, vol 1001, p 012100. International Scientific and Practical Conference Environmental Risks and Safety in Mechanical Engineering (ERSME). https://doi.org/10.1088/1757-899X/1001/1/ 012100 14. Kostoglotov AA, Pugachev IV, Lazarenko SV (2019) AIP Conference Proceedings, p 1063. https://doi.org/10.1063/1.5138398 15. Efremenko I, Bondarenko V et al (2021) Application issues of spatial interaction marketing in the regional agribusiness sustainable development. In: E3S Web of Conferences, vol 273, p 08080. https://doi.org/10.1051/e3sconf/202127308080 16. Antipov S, Khozyaev I et al (2020) Food technologies and their environmental impact. In: IOP Conference Series: Materials Science and Engineering, vol 1001, p 012137. International Scientific and Practical Conference Environmental Risks and Safety in Mechanical Engineering (ERSME). https://doi.org/10.1088/1757-899X/1001/1/012137 17. Kholodov O, Kholodova M, Kolycheva Z et al (2020) Strategic planning system for agricultural production and agro logistic in Russia. In: OP Conference Series: Materials Science and Engineering, vol 918, p 012144. https://doi.org/10.1088/1757-899X/918/1/012144 18. Lazarenko SV, Kostoglotov AA, Kostoglotov AI (2019) J Commun Technol Electron 54(4):431–438. https://doi.org/10.1134/S1064226909040081 19. Solovyov S et al (2021) E3S Web of Conferences, vol 273, p 07030. https://doi.org/10.1051/ e3sconf/202127307030 20. Molochnikov D, Khalimov R et al (2020) The improvement of the technique for determining technical condition of repair and maintenance equipment. In: E3S Web of Conferences, vol 210, p 08006. https://doi.org/10.1051/e3sconf/202021008006 21. Solovyov SG, Milutin ER, Ryzhikov VA (2017) IEEE East-West Design & Test Symposium (EWDTS), p 8110083. https://doi.org/10.1109/EWDTS.2017.8110083 22. Meskhi B, Bondarenko V, Efremenko I, et al (2020) Impact of globalization and digitalization on the efficiency of environmental development of territories. In: E3S Web of Conferences, vol 217, p 06012. https://doi.org/10.1051/e3sconf/202021706012 23. Solovyov SG, Milutin ER, Ryzhikov VA (2018) East-West Design & Test Symposium (EWDTS), p 8524841. https://doi.org/10.1109/EWDTS.2018.8524841 24. Kalmykov BY, Stradanchenko SG, Sirotkin AY, Garmider AS, Kalmykova YB (2016) ARPN J Eng Appl Sci 11(17):10205–10208. http://www.arpnjournals.com/jeas/index.htm 25. Rudoy D, Murgul V (2019) Preface. In: E3S Web of Conferences, vol 135, p 00001. https:// doi.org/10.1051/e3sconf/201913500001 26. Kalmikov BY, Visotski IY, Ovchinnikov NA, Petriashvili IM, Kalmikova YB (2015) ARPN J Eng Appl Sci 10(12):5150–5156. http://www.arpnjournals.com/jeas/research_papers/rp_2015/ jeas_0715_2227.pdf
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Calculation of Resistance Due the Destruction of Soil by a Cutter Sergey Kuren , Sergey Popov , Nikolay Dontsov , Julianna Marchenko , and Nikolay Ryzhkin
Abstract Maintaining the surface of the irrigation canal dams in a leveled state, by periodically profiling them, will guarantee the high performance of the entire complex of canal care machines in their various operations. The issues of technology for processing canal dams are of great importance, taking into account the requirements of modern engineering hydrology, since the interaction of the working bodies of earth-moving machines with the soil causes a number of forces that impede the movement of the working bodies during the performance of technological processes. Channel profiling with the best quality and productivity can be carried out by means of mechanization due to working bodies capable of processing not only longitudinal, but also cross sections of channels. Profiling the surface of irrigation canals should be carried out only by redistributing the volume of soil from high places to low ones. When cutting with a cutter, resistance affects the destruction of the soil. By repeated pulling in the same place, the surface of the slopes is leveled. But due to the fact that the devices are extremely imperfect working bodies, this does not allow timely combating the deformation of the surface of irrigation canal dams. The creation of specialized working bodies of profilers, which make it possible to level the surface of canal dams by redistributing soil from high places to low ones, will not only combat deformation of the surface of irrigation canal dams, but also improve their mode of operation. Keywords Hydrology · Transport infrastructure · Melioration · Irrigation canal · Soil · Channel · Slopes · Cutting resistance · Cutter · Profiler · Dam
1 Introduction In the new economic, environmental, legal conditions of land use, there has been a revision of many parameters for the further development of irrigation systems. The issues of improving the technical level of irrigation systems, the reliability and S. Kuren · S. Popov (B) · N. Dontsov · J. Marchenko · N. Ryzhkin Don State Technical University, 1, Gagarin Square, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_188
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environmental friendliness of their work have come to the fore. Issues of operation of irrigation systems, management of water supply and water distribution are considered in a new way. Land reclamation, in general, and irrigation systems, in particular, are the most powerful environmental factor and can lead to negative environmental consequences in the region. The process of soil milling is determined by several phenomena in the process of movement of the working body. The destruction of the soil by the milling working body and its loosening is characterized primarily by the geometric parameters of the cutter, as well as the conditions for cutting the soil (hardness, moisture content, etc.). In addition, the milling process also depends on the technological scheme of profiling. During the operation of the cutter, chips of certain geometric dimensions are separated. Its shape and volume change and depend on the main parameters of the chips: Length, width, height. Taking into account the stated requirements, the calculation of resistance in the destruction of soil by a cutter was carried out [1–9].
2 Theoretical Part Under the conditions of profiling, the volume depends on the state of the microprofile, that is, the trajectory of the movement of the working body, which affects the quality of the surface profiling. Total resistance PF soil milling consists of several components. According to many authors, of no small importance in determining the resistance Pf when soil is destroyed by a cutter, they have such conditions as cutting soil particles, their deformation, friction of the cutting edge against the soil, friction of the soil against the back of the cutting edge. Many researchers still do not find the optimal mathematical relationship in determining the relationship between the soil and the cutting working body, and use empirical relationships obtained empirically. It is known that the friction coefficient of soil on steel is a variable [10–12]. Humidity plays an important role in the profiling process. Based on the research, it was found that the humidity varies along the length of the slope. Let us establish the relationship between the friction coefficient of soil on steel and soil moisture on the canal slope. Figure 1 shows a graphical dependence μ = f (W ). There are two points on the graph: W c—soil moisture at the top of the slope and W b—humidity at the edge of the rolling. The diagram (Fig. 2) shows the measurement of the required values. From the graphical definition it follows Wb − Wc μc − μb = μy − μb Wb − Wy This dependence is shown in the Fig. 3.
(1)
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Fig. 1 Addiction μ = f (W )
Fig. 2 Scheme for measuring humidity
Fig. 3 The dependence of the coefficient of friction of steel μ about the soil from moisture W
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To find a relationship
Wb−Wc W b−W y
use the Fig. 2
Wb − Wc Bo = Wb − Wy Bo − y
(2)
As field studies have shown, humidity changes along the length of the cultivated area, increasing its value at the bottom of the slope [13–17]. We assume that this change represents a straight line dependence. From Fig. 3, taking into account expression (2), we obtain μc − μb Bo = , μy − μb Bo − y therefore Bo · μy − Bo · μb = Bo · μc − Bo · μb − y · μc + y · μb Bo · μy = Bo · μc − (μc − μb) · y μy = μc =
μc − μb y. Bo
(3)
Analyzing formula (3), it can be noted that the friction coefficient of soil on steel μ varies along the width of the working bodies of the profiler, that is, the coefficient of friction in our case is a variable value and decreases as it approaches the “watersoil” boundary. Under the water layer, we assume that μb = const. It is known that the friction coefficient of steel on the soil increases as moisture increases, and then decreases at a certain value. Specific resistance of soil to cutting P directly proportional to cutting speed V P = K V + Po
(4)
where K –proportionality factor depending on the state of the soil; V –speed of the cutting edge relative to the ground; Po –specific cutting resistance at V = 1 m·s–1. Analytical expression (4) can be represented as: τ2 − 2W Po = σo δc · b · K nnp + δu · b · KGnn · μ + c · b 2G LH ×σb (sinα + μcosα) + L · S · ρ(sin α + μ cos α) · cos α where σo , τ , σb —soil resistance to uniaxial compression, shear and bending; S,W —chip cross-sectional area and its modulus; c —chip shear area;
(5)
Calculation of Resistance Due the Destruction of Soil by a Cutter
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δ c , δ u —area of blunting and wear of the knife; L H —front cutting-edge length; Kp , KG p —empirical reduction factors; α—angle of inclination of the tangent trajectory of the knife to the horizon; μ—friction coefficient of soil on steel. Since the cross section of the chip is bh, then, taking into account expression (3), it follows from (4) and (5) that y 1 σo δc · b · K nnp + δu · b · KGnn μc − (μc − μb) b Bo 2 τ y 2W +c b δb · sin α + μc − (μc − μb) + 2G LH Bo y × cos α + L H · S · ρ · sin α μc − (μc − μb) Bo × cos α) cos α + K V ] Po =
(6)
For the purpose of further transformations, we introduce the notation: 1 σo · δc · b · K = C1 , bh 1 σo · δ · b · K G (μc − (μc − μb)) = C2 , bh 1 τ2 c · b · = C3 , bh 2G 1 2W · · δb · sinα = C4 , bh L H 1 2W · · δb (μc − (μc − μb)) · cosα = C5 , bh L H 1 · L H · S · ρ · sin α · cosα = C6 , bh 1 · L H · S · ρ · cos2 α(μc − (μc − μb)) = C7 . bh μc − (μc − μb) = μy Taking into account the introduced coefficients, we finally write down: P = C1 + C2 · μy ·
y y + C3 + C4 + C5 · μy · + C6 + C7 Bo Bo
(7)
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Fig. 4 Scheme for determining the force of resistance to cutting soil with a cutter on the slope of an irrigation canal
This expression shows that the specific cutting resistance of the soil in the case under consideration is a variable value and depends on the value of the ordinate y, i.e. P = f (y). This means that each point of the line along the length of the slope of the channel corresponds to its own resistivity value. Based on the fact that in the underwater part of the slope the friction coefficient μb = const, the specific cutting resistance also remains constant. Therefore, it can be assumed that y ≤ Bo will be Po = const. Because P = f (y), then the elementary force of soil resistance to cutting will have the form ΔP = P · ΔF As follows from Fig. 4, on an elementary section of length Δy the average value of the resistivity will be equal to half the sum of the resistivities obtained in the section and. Using formula (7), we find the average value of the resistivity in the section Δy. The elementary cutting resistance force in the section will be equal to P = C1 + C2 · μy
y y y + C3 + C4 + C5 · μy + C6 + C7 · μy + K V. Bo Bo Bo
After the transformation, we write: P = Ci + C j · μy where Ci = C1 + C3 + C4 + C6 .
y + K V, Bo
(8)
Calculation of Resistance Due the Destruction of Soil by a Cutter
Denoting Cκ =
j
Bo
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we get: P = Ci + Cκ · μy · y + K V
(9)
Then the average value of the resistivity in the section will be equal to Δy = Pcp
P y + P y + y , 2
where P y = Ci + Cκ · μy · y + K V , therefore Δy
V +Cκ·μy· y Pcp = 2Ci +2Cκ·μy·y+2K 2 = Ci + Cκ · μy · y + K V + 21 Cκ · μy · y.
Then the elementary resistance force on the section Δy will be equal to 1 ΔP = Ci + Cκ · μy · y + K V + Cκ · μy · Δy h · Δy. 2 Passing to the differential form, we write: d P = Pcp · h · dy. Therefore, the resultant resistance force along the width of the profiler section B will be: B P= (Ci + Cκ · μy · y + K V )h · dy, 0
therefore B2 + K V h B, P = Ci · h · B + Cκ · μy · h · 2 finally we will have: B P = Ci + Cκ · μy · + K V h B 2
(10)
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3 Results The resulting expression for calculating the soil cutting resistance force, in contrast to the known formulas, takes into account the change in the coefficient of friction of steel on the soil depending on humidity [18–25]. The cutting resistance of a cutter knife on three surfaces can be determined by the following formula PH = PL + 2Pδ
(11)
where PL —soil cutting resistance on the frontal surface; Pδ—chip cutting resistance on one flank. In its turn PL can be defined PL = PF · B · S = PF · B · Sz · sin α
(12)
where PF —specific milling resistance; B—milling width; S—chip thickness. Soil resistance at the entry of the cutter knife during chip separation along the side surface is determined by the equation Bδ = K · B · S = K · B · S Z sin α.
(13)
where K —specific resistance when milling on the side surface; B—the width of the projection of the knife on a plane perpendicular to the direction of the translational movement of the cutter; S—knife cutting depth. Based on the foregoing, taking into account expression (13), it is possible to write the final formula for the specific destruction of soil by a cutter. B 2 Ci + Cκ · μ y · + K V h B + 2K · b h · sin α PF = 2
(14)
Analyzing the obtained formula (14), it can be noted that the cutting resistance of the soil depends on the coefficient of friction on steel, chip thickness, width of the profiler section, and also on the cutting speed [26, 27].
4 Conclusions The required accuracy of channel profiling is ensured by using machines capable of processing not only longitudinal, but also cross sections of channels.
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Soil cutting resistance primarily depends on the coefficient of friction against steel, chip thickness, profiler section grip width, and cutting speed [1–6]. The developed materials can be recommended to engineering and technical workers working on the construction and operation of irrigation systems.
References 1. Apalkov AF, Apalkov SA, Kuren SG, Popov SI, Marchenko JuV (2020) E3S Web Conf 210:04009. https://doi.org/10.1051/e3sconf/202021004009 2. Kuren SG, Galchenko GA et al (2020) E3S Web Conf 210:09005. https://doi.org/10.1051/e3s conf/202021009005. 3. Apalkov AF et al (2020) E3S Web Conf 175:09005. https://doi.org/10.1051/e3sconf/202017 509005 4. Ivanov VV, Popov SI et al (2021) IOP Conf Ser Mater Sci Eng 1029:012052. https://doi.org/ 10.1088/1757-899X/1029/1/012052 5. Nikolaev NN, Marchenko YuV, Filatov SK (2019) IOP Conf Ser Mater Sci Eng 698:066027. https://doi.org/10.1088/1757-899X/698/6/066027 6. Marchenko EV et al (2022) Lecture notes in networks and systems, vol 246, pp 226–234. https://doi.org/10.1007/978-3-030-81619-3_25 7. Marchenko EV, Korotky AA, Popov SI (2021) J Phys Conf Ser 2131:042060. https://doi.org/ 10.1088/1742-6596/2131/4/042060 8. Marchenko JuV et al (2022) Lecture Notes in Networks and Systems, vol 246, pp 235–241. https://doi.org/10.1007/978-3-030-81619-3_26 9. Popov SI, Galchenko GA et al (2022) Smart innovation, systems and technologies, vol 247, pp 45–53. https://doi.org/10.1007/978-981-16-3844-2_6 10. Kostoglotov AA et al (2019) Meas Tech 62:497–502. https://doi.org/10.1007/s11018-019-016 52-8 11. Lazarenko DV, Kostoglotov AA (2017) J Commun Technol Electron 62(2):123–127. https:// doi.org/10.1134/S1064226917020061 12. Kostoglotov AA, Pugachev IV, Lazarenko SV (2019) AIP Conf Proc 1063. https://doi.org/10. 1063/1.5138398 13. Demyanov A et al (2021) IOP Conf Ser Mater Sci Eng 1029:012004. https://doi.org/10.1088/ 1757-899X/1029/1/012004 14. Meskhi B, Bondarenko V et al (2020) Impact of globalization and digitalization on the efficiency of environmental development of territories. E3S Web Conf 217:06012. https://doi.org/10. 1051/e3sconf/202021706012 15. Lazarenko SV, Kostoglotov AA, Kostoglotov AI (2019) J Commun Technol Electron 54(4):431–438. https://doi.org/10.1134/S1064226909040081 16. Solovyov S, Astsaturov Y, Zhigulsky V, Sulak I (2021) E3S Web Conf 273:07030. https://doi. org/10.1051/e3sconf/202127307030 17. Efremenko I, Bondarenko V et al (2021) Application issues of spatial interaction marketing in the regional agribusiness sustainable development. E3S Web Conf 273:08080. https://doi.org/ 10.1051/e3sconf/202127308080 18. Solovyov SG, Milutin ER, Ryzhikov VA (2017) IEEE East-West Design and Test Symposium (EWDTS), p 8110083. https://doi.org/10.1109/EWDTS.2017.8110083 19. Soloviev A, Matrosov A et al (2020) Mathematical and laboratory modeling of resonant impact on the spike for the purpose of grain selection. E3S Web of Conferences 210, 05017 ITSE-2020 https://doi.org/10.1051/e3sconf/202021005017 20. Solovyov SG et al (2018) East-West Design and Test Symposium (EWDTS), vol 8524841. https://doi.org/10.1109/EWDTS.2018.8524841
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21. Kalmykov BY et al (2016) ARPN J Eng Appl Sci 11(17):10205–10208 22. Meskhi B et al (2021) Finite element and applied models of the stem with spike deformation. Agriculture 11:1147. https://doi.org/10.3390/agriculture11111147 23. Kalmikov BY et al (2015) ARPN J Eng Appl Sci 10(12):5150–5156 24. Rudoy D, Murgul V (2019) Preface. E3S Web of Conferences, 135, ctat № 00001. https:// doi.org/10.1051/e3sconf/201913500001 25. Kalmikov BY et al (2015) ARPN J Eng Appl Sci 10(10):4366–4371 26. Kokieva GE, Ivanova M, Trofimova VS (2021) The study of reducing soil mechanical deformation in tilling, E3S Web of Conferences. In: XIV International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness - INTERAGROMASH 2021”. Rostov-on-Don, p 05006 27. Lachuga Y, Akhalaya B et al (2020) Energy-saving tillage with a combined unit with universal working bodies. In: IOP Conference Series: Materials Science and Engineering. The collection of conference materials. Voronezh State University of Engineering Technologies, p 012121
Efficiency Analysis for Mechanical Mixing Systems of Cementing Units Valentin Stepanov
and Sergey Kireev
Abstract The goal of the present research is to analyze the efficiency of cementing slurry preparation systems in a form of an impeller slurry agitator and in a form of an impeller slurry agitator with a screw on one shaft. The present research employs a numerical simulation for a multiphase flow based on the Euler and Lagrange methods. The mathematical device of the Euler-Euler Multiphase Segregated Flow Model considers phase flows as continuous and interpenetrating at all points of the calculated volume. The mathematical device of the Euler–Lagrange Multiphase Model considers the dispersed phase as a set of individual particles of finite size in the finite volume of the main phase. The Euler-Euler Multiphase Model problems were solved in the steady mode, the Euler–Lagrange Multiphase Model problems were solved in the unsteady mode. This study analyzes the distribution of cement in the liquid phase over the volume of a mixing tank for three types of agitators: impeller slurry agitators, combined unidirectional helical screw agitators, combined multidirectional helical screw agitators. The analysis was carried out for the forward and reverse direction of rotation of the agitators. Based on the results of the analysis, the most effective layouts of the mixing systems for practical use were obtained. Keywords Cement slurry · Mixing system · Transport infrastructure · Volume fraction of cement
1 Introduction The process of creation and subsequent operational maintenance of oil and gas wells requires highly efficient and versatile cement mixing systems capable of producing mixtures of various densities and compositions. The slurry for cementing and repairing casing strings should have a homogeneous structure and density based on the operating conditions of the well. V. Stepanov · S. Kireev (B) Don State Technical University, 1, Gagarin Square, 344003 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_189
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The primary equipment used to prepare the cement slurry for the repairs of oil and gas wells in oil fields are mixing tanks with mechanical stirring. The purpose of stirring is to obtain homogeneous or heterogeneous systems with a minimum concentration gradient, that is, to obtain a system with the same parameters anywhere in the volume [1–3]. The principle of mechanical stirring consists in converting ordered mechanical energy into disordered energy of the stirred object’s resistance forces. Depending on the hydrodynamic mixing mode, mechanical stirrers are structurally subdivided into blade stirrer, screw, turbine, helical screw, ribbon, anchor, doubleturbine and gate agitators (Str˛ek, 1981). The most common equipment used in oil and gas fields are impeller and screw agitators, among which the most promising cement slurry preparation system designs are of an impeller slurry agitator and of an impeller slurry agitator with a screw on one shaft. The simplicity of the design, utilizing one or two electrically or hydraulically powered impeller slurry agitators, the ease with which it can be maintained and controlled have led to the massive use of this type of mixing system. The goal of the present research is to analyze the efficiency of cementing slurry preparation systems in a form of an impeller slurry agitator and in a form of an impeller slurry agitator with a screw on one shaft. This study examines the phase distribution of the components of the cement slurry in a mixing tank (reactor) with mechanical stirring by various types of agitators. The aim of the study was to determine the most efficient agitator design for an invariable mixing tank. The study used a numerical apparatus for modeling multiphase flow based on the Euler-Euler and Euler–Lagrange methods. The mathematical apparatus of the EulerEuler Multiphase Segregated Flow Model considers phase flows as continuous and interpenetrating at all points of the calculated volume. The Euler–Lagrange Multiphase Model considers a dispersed phase as a set of individual particles of a finite size in a finite volume of the main dispersed phase [4–10]. The Euler-Euler multiphase problems were solved in a steady setting, and the Euler–Lagrange multiphase problems were solved in an unsteady setting. This study analyzes the distribution of cement in the liquid phase over the volume of the mixing tank when using three types of mixers: paddle mixers, combined paddle mixers with screws with a unidirectional helical generatrix and combined paddle mixers with screws with a multidirectional helical line. The analysis was carried out with the forward and reverse direction of rotation of the stirrers.
2 Methods The processes occurring in the mixing tank are general for the motion of a continuous medium and can be described by a system of hydrodynamic equations. The main conservation laws in continuous medium mechanics are: the law of conservation of mass, the law of conservation of momentum, the law of conservation of energy. The mathematical description of a multiphase medium consists in constructing a closed system of equations and relations for the motion of a multiphase medium, taking
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into account the physical and chemical properties of each of the phases. The main dynamic characteristic of the medium is the density of mass distribution over the volume; in our case, the distribution of the cement phase over the volume of the liquid phase. The movement of phases in the mixing tank is described by a mathematical model based on the solution of the Navier–Stokes equations (for an axisymmetric flow) and the continuity equation [11–15]: 1 ∂ ∂ ∂υr ∂υr ∂ 1 ∂ r μT + r μT (rρυr υr ) + (rρυr υz ) = r ∂r ∂z r ∂r ∂r ∂z ∂z 2 ρυφ υr ∂P − − μT 2 + (1) ∂r r r ∂υφ ∂υφ ∂ 1 ∂ ∂ 1 ∂ rρυr υφ + rρυz υφ = r μT + r μT r ∂r ∂z r ∂r ∂r ∂z ∂z υφ ρυφ υr (2) − μT 2 + r r 1 ∂ 1 ∂ ∂ ∂P ∂υz ∂υz ∂ r μT + r μT − (rρυr υz ) + (rρυz υz ) = r ∂r ∂z r ∂r ∂r ∂z ∂z ∂r (3) divρ υ˜ = 0
(4)
where υz , υr , υϕ —are the axial, radial and tangential components of the velocity; P, ρ, μT —are the pressure, density and turbulent viscosity of the flow; Ú—is the velocity vector, in the coordinate system connected by the agitator’s rotation axis. The criteria of hydrodynamic similarity for the mixing process in a cylindrical mixing tank are: – the centrifugal Reynolds criterion, which characterizes the ratio of inertial forces to the internal friction forces: Reu =
ρ · n · d2 . μ
(5)
– the centrifugal Euler criterion, which characterizes the ratio of the pressure forces creating the fluid flow to the dynamic pressure forces: Eu u =
N . ρ · n3 · d 5
(6)
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– the centrifugal Froude criterion, which characterizes the ratio of inertial forces and gravity and takes into account the effect of fluid vortex on the mixing power (only consequential in the presence of a central funnel): Fru =
n2 · d . g
(7)
where N is the power consumed by the agitator in watts; ρ is the density of the liquid in kg/m3 ; μ is the dynamic fluid viscosity coefficient in Pa · s; n is the agitator’s rotation frequency, s−1 ; d is the agitator’s diameter in m; g is taken to be equal to 9.81 m/s2 . Depending on the values of the centrifugal Reynolds criterion, a laminar hydrodynamic mode of movement (Rec < 10), a transient mode with the formation of a vortex (10 < Rec < 103 ), and a turbulent hydrodynamic mode (Rec = 104 –106 ) may occur inside the mixing tank. In this study, a 3D model of a mixing tank with a volume of 2 m3 , the most common among the oil field cementing units, was used as an object for the calculation. The mixing is carried out by two vertical agitators. The study was carried out at an agitator rotation speed of 200 rpm. Three design versions of the mixing tank under consideration are shown in Fig. 1. The analysis was carried out with the numerical apparatus for modeling a multiphase system using the Euler-Euler multiphase model and Euler–Lagrange multiphase model. The physical meaning of the Euler–Lagrange method is to describe the motion of a continuous medium by describing the motion of individualized material points. The physical meaning of the Euler-Euler method is to describe the motion of a continuous medium at each point in space, through which individual points can pass.
Fig. 1 Design diagrams of the mixing tank: two impeller slurry agitators a, two combined unidirectional helical screw agitators b, two combined multidirectional helical screw agitators c
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3 Results The initial data used in solving the problem are: the working volume of the mixing tank is 2.0 m3 , the diameter of an impeller agitator is 0.68 m, the working area of one blade is 0.027 m2 , the angle of attack of the blade is 45°, the helical screw diameter is 0.3 m, the helical screw pitch is 0.2 m, the density of the liquid mix is 997 kg/m3 , the diameter of the cement particle is 0.001 m, the density of the cement part material is 2240 kg/m3 , the acceleration of gravity is 9.81 m/s2 . When solving the multiphase substance mixing problem by the Euler method, the parameters of the medium are the following: the volume fraction of the liquid phase is 80%, the volume fraction of the cement phase is 20%. When solving the multiphase substance mixing problem by the Euler–Lagrange method, the parameters for creating the environment are the following: first the liquid phase is mixed for 0.5 s, then the cement is fed through the injector for 1 s, after which further mixing of liquid and solid phases takes place. Based on the results of six simulations of a cement slurry mixing in a steady setting by the Euler-Euler method and six simulations of a cement slurry mixing in an unsteady setting by the Euler–Lagrange method, pictures of the solid phase distribution over the volume of the mixing tank were obtained. Figure 2 shows the distribution of the volume fraction of cement for a mixing tank with two impeller agitators, the most common design for oil field cementing units. Figures 3 and 4 show the distribution of the volume fraction of cement for combined impeller agitators with helical screws with a multidirectional generatrix of a helical line and a unidirectional generatrix of a helical line, respectively. Figures 5, 6 and 7 show the diagrams distribution patterns of the solid phase (cement) particles over the volume of the mixing tank for combined agitators.
Fig. 2 Distribution of the cement phase for two impeller agitators
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Fig. 3 Distribution of the cement phase for two combined multidirectional agitators
Fig. 4 Distribution of the cement phase for two combined unidirectional agitators
4 Discussion The analysis of the results, presented in Figs. 2, 3, 4, 5, 6 and 7, allows us to draw the following conclusions: 1. The size of the stagnant zones depends much more on the geometry of the mixing tank, rather than on the design of the mixing device.
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Fig. 5 Diagram distribution of the cement phase for two impeller agitators
Fig. 6 Diagram distribution of the cement phase for two combined multidirectional agitators
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Fig. 7 Diagram distribution of the cement phase for two combined unidirectional agitators
2. The traditional design of a cementing unit with impeller agitators creates an extremely uneven distribution of the cement slurry over the volume of the mixing tank. 3. The uniformity of distribution of cement particles over the tank volume (volume uniformity—VUI) for a two-blade agitator is 0.54, for combined unidirectional agitators it is 0.753 and for combined multidirectional agitators is 0.751. For (φc − φ) Vc . 2 φ Vc
VU I = 1 −
c
(8)
c
where ϕ is the average value of the volume; ϕc —the number of cells in the computational grid of the cement phase; Vc is the total number of cells in the computational grid of the tank.
5 Conclusion The performed analysis of mechanical mixing systems with impeller and combined agitators of three types at a rotation speed of 200 rpm demonstrated the superior efficiency of the combined agitators over the impeller agitators in the task of preparing
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a cement slurry, namely, the superiority of a combined impeller agitators with screws with a multidirectional forming helical line. As one of the directions of further research, it can be recommended to optimize the rotation speed of the agitators depending on the density of the prepared cement slurry.
References 1. Howaniec N, Smolinski A (2014) Effect of fuel blend composition on the efficiency of hydrogen-rich gas production in co-gasification of coal and biomass. Fuel 128:442–450. https:// doi.org/10.1016/j.fuel.2014.03.036 2. Moczulak B, Mi˛askowski W, Nalepa K, Jasi´nski J (2018) Numerical model of liquid phase mixer. Mechanik 91:555–557. https://doi.org/10.17814/mechanik.2018.7.82 3. Wallevik JE, Wallevik OH (2017) Analysis of shear rate inside a concrete truck mixer. Cem Concr Res 95:9–17. https://doi.org/10.1016/j.cemconres.2017.02.007 4. Li G, Gao Z, Li Z, Wang J, Derksen J (2018) Particle-resolved PIV experiments of solid-liquid mixing in a turbulent stirred tank. Transp Phenom Fluid Mech 294(1):389–402. https://doi.org/ 10.1002/aic.15924 5. Stepanov V, Kireev S, Korchagina M et al (2020) Analysis of efficiency of a system for heating the water-supply pump and high-pressure pump of a pumping station from the exhaust gases of an internal combustion engine. Chem Petrol Eng 55:829–834. https://doi.org/10.1007/s10 556-020-00700-3 6. Kireev S, Korchagina M, Efimov A, Stepanov V (2020) Heating system for measuring tanks of the cementing unit from the exhaust system of the base chassis. In: E3S Web of Conferences, vol 164, p 03015. https://doi.org/10.1051/e3sconf/202016403015 7. Shi B, Wei J, Zhang Y (2017) A novel experimental facility for measuring internal flow of solid-liquid two-phase flow in a centrifugal pump by PIV. Int J Multiph Flow 89:266–276. https://doi.org/10.1016/j.ijmultiphaseflow.2016.11.002 8. Chen Y et al (2019) Hydrothermal liquefaction of corn straw with mixed catalysts for the production of bio-oil and aromatic compound. Bioresour Technol 294:122–148. https://doi. org/10.1016/j.biortech.2019.122148 9. Shabani MO, Mazahery A (2012) Computational fluid dynamics (CFD) simulation of liquidliquid mixing in mixer settler. Arch Metall Mater 57(1). https://doi.org/10.2478/v10172-0120006-7 10. Li SP, Yuan YL, Shi G (2012) Research on CFD Simulation of the Cement Slurry. Adv Mater Res 621:196–199. https://doi.org/10.4028/www.scientific.net/AMR.621.196 11. Baranovskii E (2020) Strong solutions of the incompressible Navier–Stokes–Voigt model. Mathematics 8(2):181. https://doi.org/10.3390/math8020181 12. Daozhi H, Xiaoming H, Quan W, Yanyun W (2021) Existence and weak-strong uniqueness of solution to the Cahn-Hilliard-Navier-Stokes-Darcy system in superposed free flow and porous media. Nonlinear Anal 211. https://doi.org/10.1016/j.na.2021.112411 13. Acevedo P, Amrouche C, Conca C, Ghosh A (2021) Stokes and Navier-Stokes equation with Navier boundary condition. J Diff Equ 285:258–320. https://doi.org/10.1016/j.crma.2018. 12.002 14. Xu W, Yan G (2021) A lattice Boltzmann model for the Navier-Stokes equation. Microprocess Microsyst. https://doi.org/10.1016/j.micro.2021.104391 15. Wang R, Zhu Z, Su X, Mianowicz K, Jia H, Wu K (2022) Slurry pumps in deep-sea mining: a review of numerical and experimental studies. Ocean Eng 251(1). https://doi.org/10.1016/j. oceaneng.2022.111150
Application of the Aggregated Approach to the Development of the Strategy of Technical Re-equipment of the Machine and Tractor Fleet of an Agricultural Enterprise Lyudmila Borisova
and Arthur Alukhanyan
Abstract The research is devoted to the development and testing of an economic and mathematical model for choosing the optimal strategy for operating a machine in a machine and tractor fleet. Finding an effective strategy for technical re-equipment of the machine and tractor fleet is based on an aggregated approach consisting of a consistent solution of three tasks: determining the optimal service life of machines, developing a plan for the purchase and sale of machines, and selecting sources of financing for technical re-equipment. The article proposes a method for determining the optimal service life of machines in a machine and tractor fleet, based on the mathematical apparatus of dynamic programming. A model example is given that demonstrates the procedure for selecting the optimal strategy for the operation of the machine. Based on the model example, an algorithm for determining the optimal strategy based on the effects table is developed. Keywords Economic and mathematical modeling · Machine and tractor fleet · Technical re-equipment · Optimal service life of machines · Dynamic programming
1 Introduction Problems of technical re-equipment, that is, the choice of objects and terms of replacement of outdated equipment with new ones, are key for the practical activities of individual enterprises (both industrial and agricultural), and for assessing the prospects for the development of enterprises and equipment manufacturers themselves, and for training managers [1–8]. So far, in most cases, these problems have been solved on the basis of directive (normative) service life, which does not reflect either the specific conditions of operation of enterprises, nor the effect of the system interaction of machines and mechanisms, nor the dependence of the optimal strategy on the ratio of supply and demand for a particular product of enterprises, nor the capabilities of these enterprises. More correct is the approach associated with the formation of an L. Borisova (B) · A. Alukhanyan Don State Technical University, Square Gagarin, 1, 344003 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_190
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optimal fleet of machines and mechanisms [9], but this approach requires the collection of detailed information about the working conditions of the fleet and multiple computer calculations for quite complex programs [10–16]. It is essential that the important parameters, in this case, are exogenous and are considered to be set from the outside-first of all, the service life of individual machines and mechanisms. The problem arises of developing aggregated models that allow us to justify the above exogenous parameters and determine the strategy of technical re-equipment. The article offers an aggregated approach to assessing the prospects of technical re-equipment, based on the sequential solution of three tasks: 1. A priori clarification of the terms of replacement of equipment (machines and mechanisms) based on the dynamic programming problem [17]. 2. Selection of vectors of the number of machines and mechanisms of different types and ages to be sold (Y ) and newly purchased (X). This problem is formulated as a linear programming problem: A × X − B × Y ≥ b, X ≥ 0, Y ≥ 0, f = f 0 + c1 × X − c2 × Y → max. (1) Here, the restrictions are formed based on the assessment of the current state of the enterprise and take into account: – the necessary development of the system of machines and mechanisms, determined by the accepted production technology; – the financial capabilities of the enterprise, determined by the accumulated resources of depreciation and renovation, as well as its profit. The objective function is an estimate of the profit for the chosen strategy of technical re-equipment. It is significant that when calculating the parameters of restrictions, discounting of different-time costs is taken into account, and this is often ignored in the traditional practice of project feasibility studies [18–21]. Task (1) can be simplified by a priori limiting the options for implementing a part of the existing fleet, as well as generalized by analyzing the prospects for the development of the enterprise. A stochastic formulation of the problem is also possible, taking into account the random nature of the external environment and changes in a number of parameters. Naturally, this requires additional studies of the range of changes in random parameters and the laws of their distribution. Selection of sources of investment for the implementation of technical reequipment.
2 Materials and Methods For each machine used in any branch of the national economy, there is objectively a service life at which the efficiency of its use will be the greatest, i.e. the cost of its operation per unit of operating time (unit of production or work) will be minimal.
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Such service life of machines is the most cost-effective, optimal and their establishment is a necessary condition for updating machines in these estimated terms. Note that these optimal terms may differ significantly from the maximum (standard) service life (T ), the excess of which obviously leads to losses. The task of re-equipping the fleet of machines is closely related to the question: which machines and when should be replaced to achieve the maximum economic effect over the billing period? It is the economic effect that should be the criterion for determining the optimal replacement time. As one of the methods for determining the optimal service life of an individual machine, the dynamic programming method can be used, which considers the operation of the machine over a number of years as a discrete process. At each step of the calculation (in each year of operation), the machine is characterized by the following parameters: w(t) is performance of a machine aged t years (in value terms); c(t) is a cost of operating a machine of age t years. Then u(t) = w(t) − c(t) is the annual economic effect of operating a machine of age t years. The productivity of the machine and the cost of its operation are respectively decreasing and increasing functions of time. The progressive material wear of the machine with increasing service life significantly reduces the efficiency of its use, leading, ultimately, to such a state (Fig. 1), when further operation is generally unprofitable. In other words, the value of the annual effect of operation becomes negative. In addition to the above characteristics, in order to calculate the optimal service life of the machine, it must also be known: the cost of purchasing a new machine (c), the amount of cash inflow as a result of decommissioning (disposal, transfer on a paid basis to another economic entity, etc.) of a machine aged t years (a(t)). The solution of the problem is to determine the best strategy for the operation of an individual machine of age t years for a period of k years. Schematically, this is expressed in the form of a “strategy tree” (Fig. 2), each branch of which illustrates the process of making a decision to replace or leave the machine in operation for at least another year. As a result, the best (optimal) strategy for the operation of a single machine is formed. The optimal strategy criterion is the maximum income for k years from the best operation of a machine aged t years ( f k (t)). The total number of possible strategies for planning the operation of a machine for a period of k years is 2k . Moreover, the operation in this case is understood not only to leave the machine,
Fig. 1 Graphs of the dependence of the productivity and operating costs of the machine on time
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L
L
L
R
L
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Fig. 2 Strategy tree
but also to replace it within the billing period with a new one, which is covered by the further strategy. This process can be repeated several times during the billing period. At each i-th step, there is a comparison of 2 alternative options for further operation of the machine: leave it, or replace it with a new one. At the same time, the strategy of operating the machine for the previous i-1 steps for this forecast period is already optimal. It is noteworthy that the optimal strategy for operating the machine depends on the duration of the forecast period. If for a forecast period of n years at the i-th step for a machine of age t years, the optimal strategy is to leave the machine in operation, this does not mean that for a forecast of k = n years at the i-th step, the strategy will be the same. This statement follows from the fact that a strategy involving the replacement of a machine of age t years (t < T ) at the n-th step should ensure the return on capital investment for the replacement of the machine and the maximum effect of using the new machine for the next k − n steps. Otherwise, replacing the machine will be economically inefficient. The value of f k (t) for the first two calculation steps will be calculated as follows: f 1 (t) = max{u(t), −c + a(t) + u(0)},
(2)
f 2 (t) = max{u(t) + f 1 (t + 1), −c + a(t) + u(0) + f 1 (1)}.
(3)
In general, the criterion (income for k years from the best operation of a machine of age t years) will have the following form: f k (t) = max{u(t) + f k−1 (t + 1), −c + a(t) + u(0) + f k−1 (1)}.
(4)
Obviously, f 0 (t) = 0. For each type of machine in the fleet (according to the values c, u(t) and a(t) for all years of its standard service life), it makes sense to build a table of values f k (t) for any age and any forecast period of time. Then, using the finished table, it is easy to restore the best strategy for operating the machine. Despite the popularity of this scheme, its application to agricultural machines, unfortunately, was not practiced.
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3 Results of Scientific Research It should be noted that the problem of replacing equipment is illustrated by the same “classic” example, “wandering” from textbook to textbook. This example, in our opinion, is very conditional and does not reflect the whole model. In particular, it makes an assumption about zero values of the residual (liquidation) value of machines, which somewhat distorts the “real picture”. The article provides a model example that allows us to trace in more detail the dynamic programming procedure for solving the above-mentioned problem.
3.1 Model Example Let the cost of a new machine (c) be 1500 m.u. The data for the calculation is given in Table 1. The decrease in the value of the “annual” economic effect as a consequence of the aging of the machine (see Table 1) is an objective regularity. Such a reduction in the effect is not so much the result of a decrease in the performance of the machine as a result of physical wear, but rather an increase in the operating costs associated with it. Obviously, the residual value of the machine behaves in a similar way. It is essential that, starting from a certain age t1 , the liquidation value of the machine is so small that it can be neglected. The calculation begins with determining the effects of the operation of machines of all ages for a period of 1 year. In accordance with (3), a machine aged t years is subject to replacement if the expected effect (loss) from its operation in a given year is less than (greater than) the sum of the liquidation value of this and the annual effect of the new machine, less the cost of its acquisition. In our example, a machine older than 11 years is subject to unconditional replacement (when planning for 1 year) with a new one. This is not difficult to show. f 1 (11) = max{0, −1500 + 100 + 1400} = 0; Table 1 Project cash flow Age of the machine (t), years
Calculation steps 0
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f 1 (12) = max{−200, −1500 + 1400} = −100; f 1 (13) = max{−350, −1500 + 1400} = −100; etc. The strategy with the greatest effect is highlighted in bold. Next, the effects of operating for 2 years (k = 2) of a machine of age t years are calculated. f 2 (0) = max{1400 + 1350, −1500 + 1400 + 1400 + 1350} = 2750; f 2 (1) = max{1350 + 1300, −1500 + 1200 + 1400 + 1350} = 2650; f 2 (2) = max{1300 + 1200, −1500 + 1000 + 1400 + 1350} = 2500; f 2 (3) = max{1200 + 1100, −1500 + 800 + 1400 + 1350} = 2300; f 2 (4) = max{1100 + 1000, −1500 + 600 + 1400 + 1350} = 2100; f 2 (5) = max{1000 + 850, −1500 + 500 + 1400 + 1350} = 1850; f 2 (6) = max{850 + 600, −1500 + 400 + 1400 + 1350} = 1650; f 2 (7) = max{600 + 450, −1500 + 350 + 1400 + 1350} = 1600; etc. When planning for a period of 2 years, all machines of this type older than 5 years are subject to replacement. At the same time, the effects of the operation of the machines will differ by the difference in their residual values. And, thus, starting from a certain age t1 , the effect as a result of the optimal strategy of operation will not depend on the age (due to the zero value of the liquidation value). In our case t1 = 12. f 2 (12) = −1500 + 0 + 1400 + 1350 = 1250; f 2 (12) = −1500 + 0 + 1400 + 1350 = 1250; etc. Similarly, the effects are calculated for any values of k and t. For calculations, you can use the author’s program, which allows you to count not only the table of effects, but also has a “reverse course”, i.e., according to the table of effects, it allows you to restore the optimal operation strategy of the machine, as well as to give its average service life and the values of its upper and lower approximations. Table 2 shows the calculated (according to the program) effects for t = 0, …, 12; k = 1, …, 10. The bold line outlines the boundary of the unconditional replacement of the machine for various k. As can be seen from the table, a machine older than 11 years is subject to replacement when k = 1; when k = 2, it is economically feasible to replace machines older than 5 years, etc. To determine the best strategy for operating a machine aged t years on a planning horizon of k years, we use the following algorithm.
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Table 2 Effects of the best strategies, m.u
Step 1. We find in the table the effect corresponding to the given values of t and k. If the found effect is located to the right of the bold line (the age of the machine is greater than or equal to the age threshold of replacement for this planning horizon), then at the first step we replace the machine and go up the line to the cell corresponding to the age of the machine 1 year. Otherwise, go to step 2. Step 2. Increasing t and decreasing k by one, we move to the next cell, moving diagonally. At each such transition, we leave the machine in operation. Step 3. The procedure described in step 2 is repeated until the corresponding transition leads us to the cell located in the “replacement zone”. In this case, we again go up a line higher in the cell corresponding to t = 1, thereby replacing the machine at this step of the calculation. And so on, until we go beyond the table. Table 2 graphically demonstrates the described algorithm on the example of the strategy of operating a machine aged 4 years on the planning horizon of 10 years. The dotted arrows indicate the replacement of the machine, and the solid ones indicate the continuation of its operation. The optimal strategy for operating the machine is as follows: R, L , R, L , R, L , R, L , L , L , where R—replace, L—leave. At the same time, the effect will be 11,100 m.u. This strategy shows that on the planning horizon of 10 years, the operation of a 4-year-old machine is economically impractical, in other words, it requires replacing the machine with a new one at the first step of the calculation. Next, the new machine must be operated for 2 years (including the year of replacement of the previous one, since it is assumed that the replacement is made at the beginning of the year), then it is replaced with a new one (in the third step), which is also in operation for two years. At the fifth step (in the
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fifth year of the billing period), the machine is replaced again, and the new one is operated for 2 years. At the seventh step, the next replacement of the machine takes place and the new one has been in operation for 4 years. Thus, during the billing period, the machine is replaced 4 times. According to the found operation strategy, it is easy to calculate the average value of the service life of a machine of this type. To do this, we will introduce the concept of the operational cycle, by which we will understand the number of years of service of this particular machine until it is replaced. In our example, there are four such cycles. The first three last for 2 years, and the fourth for 4 years. Then the average value of the service life of the machine will be calculated as the arithmetic mean of the operating cycles. In our example, the average service life is (2 + 2 + 2 + 4)/4 = 2,5 years. It is interesting to compare the effect of the optimal strategy with the effects obtained with rounded (up and down) values of the average service life. In our case, these values will be the service life of 2 and 3 years. At the same time, if the age of the machine is greater than or equal to the service life, then it is certainly replaced at the first step, otherwise the machine remains in operation until its age becomes equal to the service life fixed by us. Thus, for a service life of 3 years, the operation strategy is as follows: R, L, L, R, L, L, R, L, L, R. It is not difficult to calculate the effect that such a strategy gives. E = (−1500 + 600 + 1400) + 1350 + 1300 + (−1500 + 800 + 1400) + 1350 +1300 + (−1500 + 800 + 1400) + 1350 +1300 + (−1500 + 800 + 1400) = 10550 m.u. The resulting effect is naturally less than the corresponding effect of the optimal strategy, which is equal to 11,100 m.u. Using the program, we get the effect with a service life of 2 years. It is equal to 10,850 m.u. We show that the effect of the optimal strategy is higher than the effect when using the standard terms of replacement of machines (T ). In our example, the standard service life of the machine is 11 years, in other words, machines older than 11 years must certainly be replaced in accordance with the accepted standards. As can be seen from Table 1, these machines have a negative annual economic effect, and therefore, their further operation is unprofitable. In accordance with the standard service life, the operation strategy of the 4-yearold machine is as follows: L, L, L, L, L, L, L, L, R, L. Calculate the effect of the operation. E = 1100 + 1000 + 850 + 600 + 450 + 300 + 150 + 0 + (–1500 + 1400) + 1350 = 5700 m.u. This value is almost half the value obtained above.
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4 Conclusion Thus, the economic impracticability of using the standard service life of machines and the urgent need to move from them to the optimal ones is obvious. The use of dynamic programming procedures can and should be widely used to solve the urgent problems of technical re-equipment of the agro-industrial complex. In this regard, in the Don State Technical University at the Department of “Management and Business Technologies”, a cycle of laboratory work is organized, aimed at developing students’ skills in solving such problems, and term papers and theses on the relevant topic are performed. The proposed system of models is supported by existing and specially developed programs for personal computers and allows conducting extensive computational experiments in order to evaluate various strategies for technical re-equipment and compare the results with calculations based on accepted methods and directive deadlines for replacing machines and equipment.
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13. Butsik KA, Tishchenko EN (2017) A mathematical model of a trusted download violator process hardware thin client. In: CEUR Workshop Proceedings. YSIP2 2017–Proceedings of the 2nd Young Scientist’s International Workshop on Trends in Information Processing, pp 32–37 14. Tishchenko EN, Zhilina EV, Sharypova TN, Palyutina GN (2019) Fuzzy models of the results of the mastering the educational programs in the field of information security. In: Aliev R, Kacprzyk J, Pedrycz W, Jamshidi M, Sadikoglu F (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing—ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896, pp 694–701. Springer, Cham. https:// doi.org/10.1007/978-3-030-04164-9_91 15. Borisova DV, Gorelova GV (2019) Cognitive instrumentarium for interregional economic integration investigation. Int Sci J Stable Dev Mt Areas 11(1):65–7 16. Chi-Chuan L, Chien-Chiang L, Yan-Yu C (2017) Insurance activities, globalization, and economic growth: new methods, new evidence. J Int Finan Mark Inst Money 51:155 17. Reina G, Milella A, Galati R (2017) Terrain assessment for precision agriculture using vehicle dynamic modelling. Biosys Eng 162:124 18. Tieppo RC, Romanelli TL, Milan M, Sorensen CG, Bochtis D (2019) Modeling cost and energy demand in agricultural machinery fleets for soybean and maize cultivated using a no-tillage system. Comput Electron Agric 156:282 19. Serbulova N et al (2019) Sustainable food systems and agriculture: the role of information and communication technologies. IOP Conf Ser Earth Environ Sci 403:012127. https://doi.org/10. 1088/1755-1315/403/1/012127 20. Alukhanyan A, Barmuta K, Panfilova O, Borisova D (2019) Risk management of innovative Russian companies in the context of interregional integration. In: IOP Conference Series: Earth and Environmental Science, vol 403, no 1, p 012044. https://doi.org/10.1088/1755-1315/403/ 1/012044 21. Orobinsky AS, Alukhanyan AA, Sychev RA, Kholina MG (2018) Development of risk-oriented technologies of the corporate financial controlling system. Eur Res Stud J 21:333–349
Truck Maintenance Frequency Optimization, Taking into Account an Increase in Its Operational Reliability Marina Zaitseva , Sergey Popov , Julianna Marchenko , Nikolay Dontsov , and Elena Nemtseva
Abstract A study was made of the operational reliability of the frame of a truck, taking into account the optimization of the frequency of maintenance. The KamAZ4308 vehicle was chosen as a technical object, as it is one of the best-selling and exported on the Russian market among heavy trucks with a gross weight of 14 to 40 tons in 2021. A technique has been developed to find the optimal value of the value of the frequency of maintenance of the basic parts of the car, taking into account operational reliability, as well as minimizing the initial data to obtain numerical results, which will reduce the time and laboriousness of the experiment and reduce the economic costs of its organization and implementation. When modeling the resource distribution, options were considered for strengthening the frame structure by changing the steel grade, wall thickness, cross-sectional area, and others. The empirical and approximating functions of the general population of the finite volume of the resource Tr of the KamAZ-4308 car frame are obtained. For a given failure rate λ = 10−7 h−1 , period value τ = 10 h and cost ratio U/C = 100 the optimal maintenance interval is T opt = 993 h ≈ 1,4 months, taking into account the minimum technogenic risk S min = 0,0513. Keywords Maintenance intervals · Optimization · Truck frame · Increased operational reliability · Unit costs
1 Introduction In modern conditions of constant development of the industrial machine-building sphere, the issues of ensuring the reliability of equipment remain relevant. Failures of machines, especially those operated in a mechanized complex, lead to a violation of the terms of work, an increase in the amount of time for repairs and restoration, equipment downtime, and an increase in economic costs. To solve the problem of increasing reliability by reducing labor, time and financial losses as a result of a M. Zaitseva · S. Popov (B) · J. Marchenko · N. Dontsov · E. Nemtseva Don State Technical University, 1, Gagarin Square, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_191
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malfunction of machines, it is proposed to develop a method for reducing the number and duration of tests, which will also reduce costs and reduce the time of the experiment. The proposed method is based on reducing the sample size for strength, load and service life when determining indicators that characterize the reliability of a truck. One of the objectives of the development of the method is also to minimize the cost of predicting the resource of equipment, the main indicator of operational reliability. No less relevant are the issues of optimizing the frequency and duration of maintenance and repair. Timely diagnostics of equipment and troubleshooting help to increase the operational reliability of the machine as a whole.
2 Selection of the Object of Research of Operational Reliability JSC “KamAZ” is the largest automobile corporation in Russia. The company cooperates in the sale of equipment with all major enterprises in Russia. Being the undisputed leader in the Russian truck market, according to the company itself in 2021, JSC “KamAZ” exported more than 5 thousand vehicles, while domestic sales amounted to about 35.6 thousand trucks. To ensure competitiveness and leadership in the market, the company must strive to increase the service life of vehicles, reduce the risk of loss of machine performance during operation, as well as increase the value of the fatigue life of parts. This problem is proposed to be solved by optimizing the frequency and duration of scheduled preventive maintenance and repair. The KamAZ brand is one of the most popular heavy-duty vehicles on the market (Fig. 1) in 2021, as well as the best-selling vehicle in the Russian Federation among vehicles with a gross weight of 14 to 40 tons. The frame of the KamAZ-4308 truck was chosen as the object of the study of operational reliability. This decision is justified by the fact that the frame is a highly loaded part, is the basic part of the car, provides fastening of the main units and assembly units (engine, body, transmission elements, cab). The reliable functioning of the car as a whole, increasing its service life and minimizing the economic costs associated with downtime largely depend on the frame performance. The frame of a truck during operation is subjected to alternating loads for torsion, bending, compression/stretching; various kinds of mechanical and manmade impacts, vibrations, the negative impact of precipitation, chemicals from road icing and other aggressive influences. Together, these factors reduce the durability of the part, reduce the defect-free service life. Thus, the frame is considered as an object of increased responsibility, the troublefree operation of which contributes to an increase in the reliability of the truck.
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MERSEDES MAN SCANIA VOLVO KAMAZ MAZ Other URAL ZIL KRAZ IVEKO 0
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Fig. 1 Distribution in the market of the Russian Federation of manufacturers of trucks weighing from 14 to 40 tons in 2021
3 Frame Maintenance Frequency Optimization Taking into Account Its Operational Reliability Ensuring the optimal reliability of a truck, its parts and assembly units includes the calculation, assessment and optimization of the probability of an object’s failurefree operation. To calculate the reliability indicators, the method [1–3] is applied, based on the use of small samples of strength, loading and resource to form sets of a finite volume of reliability indicators. The basis of this calculation is the use of the distribution of absolute ranges Wrs = xr − xs· (r, s = 1, . . . , n) W F(W ) =
f (W )dW, 0
where f(W rs )—span density (in general): +∞ f (Wr s ) = Cr s
P r −1 (x) p(x)[P(x + Wr s ) − P(x)]s−r −1 p(x + Wr s )
−∞
×[1 − P(x + Wr s )]n−s d x,
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Сi, С1i, С2i Сi Сimin С1i
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Варианты The options for рукояти making the frame
Fig. 2 Optimizing the probability of failure-free operation of a truck frame by modernizing its design
Cr s = (r −1)!(s−rn!−1)!(n−s)! ; P(x)—characteristic distribution function; p(x) is the probability density of the characteristic. It was decided to use unit costs as an optimization criterion Ci (Fig. 2) for maintenance and repair [4–7]. When ensuring the optimal reliability of machines, their units and assembly units, one should focus on the trend of reducing the duration and number of tests, their labor intensity, as well as the economic costs of organizing, conducting and analyzing the results [8–13]. The development of a method for calculating reliability indicators based on small samples is one of the ways to solve reliability optimization problems (Fig. 3). The frame of a truck is a basic part, the performance of which largely determines the reliability and safety of the equipment. An important aspect of the study is the substantiation of the interdependence of the optimal operational reliability and the frequency of maintenance. It is the prevention of failures that makes it possible to reduce the risk of their occurrence, increase the safety of the operation of machines and reduce the cost of extending the service life. The effectiveness of scheduled preventive maintenance in order to prevent failures largely depends not only on the equipment of the automotive service, the qualifications of specialists, monitoring and diagnostic tools, but also on the frequency of its implementation [14–30]. In this work, the problem of optimizing the value of the period between maintenance of an object (frame of a truck) is solved by determining the dependency functions of the probability of failure-free operation and the intensity of failures
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Calculation of reliability indicators based on small samples of initial data to reduce the duration and complexity of testing, reduce financial costs for organizing and conducting
Minimization of the volume of samples
The use of indirect correlation de-
for strength, loading and resource to form the
pendencies to obtain the strength value
general population of the final volume with a
of samples and machine parts
given error
Development of an algorithm for obtaining a general population of a finite volume based on minimizing the amount of initial data
Obtaining
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strength
values by using indirect correlation methods for the transition from hardness values to loading indicators
Obtaining indicators of the optimal reliability of the frame of a truck, which allows minimizing the unit costs for organizing and conducting tests, their labor intensity, production and operation of the part
Fig. 3 Optimizing the probability of failure-free operation of a truck frame
on time P(t) and λ(t) relatively. Denote the economic costs of eliminating implicit (hidden) failures U, then unit cost over time τ S(τ) = U p(t < τ) + C p(t ≥ τ) + u
τ
t f (τ − t)dt = U [1 − P(τ)] + C P(τ) τ τ +u [1 − P(t)]dt = U + (C − U )P(t) + u τ − [P(t)]dt . 0
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Average unit cost over time τ ⎧ ⎤⎫ ⎡ τ ⎬ 1⎨ s(τ) = U + (C − U )P(t) + u ⎣τ − P(t)dt ⎦ . ⎭ τ⎩
(3)
0
Differentiating the expression with respect to time and equating the derivative to zero, we obtain ⎤ ⎡ τ u ⎣ d P(t) U − , (4) P(τ) − τ τ − P(t)dt ⎦ = dt U −C U −C 0
Solving the equation will provide the optimal value for the frequency of preventive maintenance T opt . The task of finding the optimal solution is inextricably linked with risk minimization. In this paper, the risk function, which takes into account the costs of restoring and repairing a car, violation of work deadlines, downtime, is presented in the form S = CP2 (t) + UP3 (t)
(5)
Below are the practical results of optimizing the frequency of maintenance of a truck, taking into account the increase in its operational reliability. The frame of a KamAZ-4308 truck was chosen as the object of study.
4 Practical Results of the Study PThe results of mathematical modeling of the KamAZ-4308 truck frame resource are shown in Fig. 4. The empirical and approximating functions of the general population of the finite resource volume are obtained Tr of the car frame KAMAZ-4308 (Fig. 4). When modeling the resource distribution, options were considered for strengthening the frame structure by changing the steel grade, wall thickness, cross-sectional area, and others. The table shows the results of the optimization of the frequency of maintenance of the KamAZ-4308 truck. The minimum risk value is indicated Smin, the ratio of economic costs in case of a sudden failure to the costs of organizing, conducting, monitoring maintenance–U/C [31] (Table 1). Thus, the developed method allows optimizing the frequency of maintenance of the truck frame, taking into account its operational reliability. For example, for a given failure rate λ = 10–7 h–1, period values τ = 10 h and cost ratio U/C = 100 the optimal value of the frequency of maintenance will be Topt = 993 h ≈ 1,4 months, taking into account the minimum technogenic risk Smin = 0,0513 [32].
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Fig. 4 Empirical (1) and approximating (2) distribution functions of the general population of the finite volume of the frame of the KamAZ-4308 truck Table 1 The results of the optimization of the duration of the period between scheduled maintenance of the KamAZ-4308 truck Optimal maintenance interval Topt , h at τ, h = 10 h Failure rate
U/C = 10
U/C = 100
U/C = 1000
U/C = 10,000
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Topt , h at τ, h = 100 h Failure rate
U/C = 10
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U/C = 10,000
λ = 10−8 h-1
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5 Conclusions In this paper, the optimization of the frequency of maintenance of truck parts is carried out, taking into account its operational reliability. Empirical and approximating functions of the general population of the finite resource volume Tr of the frame of the KamAZ-4308 car are obtained. When modeling the resource distribution, options were considered for strengthening the frame structure by changing the steel grade, wall thickness, cross-sectional area, and others. The values of the optimal periodicity of maintenance are obtained, depending on the intensity of failures, the costs of restoring the facility’s operability in case of a sudden failure, the magnitude of the period and man-made risk.
References 1. Deryushev VV, Zaitseva MM, Kosenko EE, Kosenko VV (2020) IOP Conference Series: Materials Science and Engineering, vol 913, no 4, p 042059. https://doi.org/10.1088/1757-899X/ 913/4/042059 2. Deryushev VV, Kosenko EE, Kosenko VV, Zaitseva MM (2019) Making technical decisions in conditions of uncertainty in the presence of risk. Saf Tech Nat Syst 2:56–61. https://doi.org/ 10.13140/2.1.1324.2889 3. Kotesova AA, Teplyakova SV, Popov SI, Kopylov FC (2019) IOP Conference Series: Materials Science and Engineering, vol 698, p 066029. https://doi.org/10.1088/1757-899X/698/6/066029 4. Deryushev V, Zaitseva M, Megera G, Fedyanov A (2019) IOP Conference Series: Materials Science and Engineering, vol 698, p 066031. https://doi.org/10.1088/1757-899X/698/6/066031 5. Deryushev VV, Zaitseva MM, Evseev DZ, Kosenko EE (2020). Mater Sci Forum. https://doi. org/10.34031/2618-7183-2019-2-3-72-77 6. Teplyakova SV, Kotesova AA, Popov SI, Kotesov AA (2020) IOP Conference Series: Materials Science and Engineering, vol 913, p 042054. https://doi.org/10.1088/1757-899X/913/4/042054 7. Kuren SG, Galchenko GA, Popov SI, Marchenko JV, Dontsov NS, Drozdov DS (2020) E3S Web of Conferences, vol 210, p 09005. https://doi.org/10.1051/e3sconf/202021009005 8. Ivanov VV, Popov SI, Dontsov NS, Marchenko JV, Ryzhkin NV, Oleynikova JA (2021) IOP Conference Series: Materials Science and Engineering, vol 1029, p 012052. https://doi.org/10. 1088/1757-899X/1029/1/012052 9. Nikolaev NN, Marchenko YuV, Filatov SK (2019) IOP Conference Series: Materials Science and Engineering, vol 698, p 066027. https://doi.org/10.1088/1757-899X/698/6/066027 10. Marchenko E, Korotky A, Popov S, Marchenko J, Dontsov N, Kosenko E (2022) Investigation of the causes of defects in the section of steel rope splicing. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference INTERAGROMASH 2021. LNNS, vol 246, pp 226–234. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_25 11. Marchenko EV, Korotky AA, Popov SI, Marchenko JuV, Kosenko EE (2021) J Phys Conf Ser 2131:042060. https://doi.org/10.1088/1742-6596/2131/4/042060 12. Marchenko J, Korotky A, Popov S, Marchenko E, Galchenko G, Kosenko V (2022) Municipal waste management in an urbanized environment based on ropeway technology. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference INTERAGROMASH 2021. LNNS, vol 246, pp 235–241. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_26 13. Popov SI, Galchenko GA, Marchenko JV, Drozdov DS (2022) Smart innovation. Syst Technol 247:45–53. https://doi.org/10.1007/978-981-16-3844-2_6 14. Kostoglotov AA, Andrashitov DS, Kornev AS, Lazarenko SV (2019) Meas Tech 62:497–502. https://doi.org/10.1007/s11018-019-01652-8
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15. Molochnikov D, Khalimov R, Gayaziev I, Rudoy D, Olshevskaya A (2020) The improvement of the technique for determining technical condition of repair and maintenance equipment. In: E3S Web of Conferences, vol 210, p 08006 ITSE-2020. https://doi.org/10.1051/e3sconf/202 021008006 16. Lazarenko SV, Kostoglotov AA (2017) J Commun Technol Electron 62(2):123–127. https:// doi.org/10.1134/S1064226917020061 17. Lachuga Y, Akhalaya B, Shogenov Y, Meskhi B, Rudoy D, Olshevskaya A (2020) Innovative pneumatic device for combined seeding of various tilled crops. In: E3S Web of Conferences, vol 210, p 08016 ITSE-2020. https://doi.org/10.1051/e3sconf/202021008016 18. Kostoglotov AA, Pugachev IV, Lazarenko SV (2019) AIP Conference Proceedings, p 1063. https://doi.org/10.1063/1.5138398 19. Lazarenko SV, Kostoglotov AA, Kostoglotov AI (2019) J Commun Technol Electron 54(4):431–438. https://doi.org/10.1134/S1064226909040081 20. Altybayev A, Naydenko Y, Meskhi B, Mozgovoy A, Rudoy D, Olshevskaya A (2020) Creation of integrated system for feeding management activities automation in beef breeding. In: E3S Web of Conferences, vol 175, p 03019. https://doi.org/10.1051/e3sconf/202017503019 21. Solovyov S, Astsaturov Y, Zhigulsky V, Sulak I (2021) E3S Web of Conferences, vol 273, p 07030. https://doi.org/10.1051/e3sconf/202127307030 22. Soloviev A et al (2020) Mathematical and laboratory modeling of resonant impact on the spike for the purpose of grain selection. In: E3S Web of Conferences, vol 210, p 05017 ITSE-2020. https://doi.org/10.1051/e3sconf/202021005017 23. Solovyov SG, Milutin ER, Ryzhikov VA (2017) IEEE East-West Design & Test Symposium (EWDTS), p 8110083. https://doi.org/10.1109/EWDTS.2017.8110083 24. Solovyov SG, Milutin ER, Ryzhikov VA (2018) East-West Design & Test Symposium (EWDTS), p 8524841. https://doi.org/10.1109/EWDTS.2018.8524841 25. Meskhi B, Bondarenko V, Efremenko I, Romanishina T, Rudoy D, Olshevskaya A (2020) Impact of globalization and digitalization on the efficiency of environmental development of territories. In: E3S Web of Conferences, vol 217, p 06012 ERSME-2020. https://doi.org/10. 1051/e3sconf/202021706012 26. Kalmykov BY, Stradanchenko SG, Sirotkin AY, Garmider AS, Kalmykova YB (2016) ARPN J Eng Appl Sci 11(17):10205–10208. http://www.arpnjournals.com/jeas/index.htm.Accessed 11 Mar 2022 27. Milyutkin V, Buxmann V, Polushkin O, Rudoy D, Olshevskaya A (2022) Further improvement and adaptation of the primera DMC seeder, Germany. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference INTERAGROMASH 2021. LNNS, vol 246, pp 130– 137. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_14 28. Kalmikov BY, Visotski IY, Ovchinnikov NA, Petriashvili IM, Kalmikova YB (2015) ARPN J Eng Appl Sci 10(12):5150–5156. http://www.arpnjournals.com/jeas/research_papers/rp_2015/ jeas_0715_2227.pdf. Accessed 12 Mar 2022 29. Meskhi B et al (2021) Finite element and applied models of the stem with spike deformation. Agriculture 11:1147. https://doi.org/10.3390/agriculture11111147 30. Kalmikov BY, Ovchnnikov NA, Kalmikova OM, Guguyev IK, Kushnariva IV (2015) ARPN J Eng Appl Sci 10(10):4366–4371. http://www.arpnjournals.com/jeas/research_papers/rp_2015/ jeas_0615_2105.pdf. Accessed 19 Mar 2022 31. Kokieva GE, Dondokov YZ, Stepanova DI, Stroyev A, Filatov A (2021) Research of highperformance harvesting and transport equipment. In: E3S Web of Conferences. XIV International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness–INTERAGROMASH 2021”. Rostov-on-Don, p 07005, 2021 32. Rogovskii IL et al (2021) Modeling the weight of criteria for determining the technical level of agricultural machines. In: IOP Conference Series: Earth and Environmental Science. Krasnoyarsk Science and Technology City Hall. Krasnoyarsk, Russian Federation, p 22100, 2021
Vibroacoustic Characteristics of Flat Workpieces Hardening in Transport Engineering Alexander Isaev , Sergey Popov , Julianna Marchenko , Nikolay Dontsov , and Evgeny Kosenko
Abstract Taking into account that the technological process of surface plastic deformation during manual processing and processing on a machine tool is intensively used in various branches of mechanical engineering, it seems appropriate to study the vibroacoustic characteristics during hardening of flat workpieces, which will make it possible to achieve sanitary standards in the operator’s working area. Since ensuring safe working conditions is important in the processes of hardening slabs. This article presents the experimental results of studies of noise and vibration spectra during the processing of flat parts by the method of ball-and-rod hardening. In the course of the research, dangerous and harmful production factors that arise during the implementation of the processing of flat parts have been identified. The results of measuring sound pressure levels at the operator’s workplace during the operation of the compressor and the machine itself, as well as during the processing of flat parts, taking into account the number of indenters in the package and the preload of the hardener, are presented. The data obtained are confirmed by the correctness of theoretical conclusions about the patterns of formation of noise spectra and the contribution of noise sources to the sound field at the operator’s workplace. The research results allow us to confirm the validity of the theoretical approach to the description of the regularities of the noise generation process. Keywords Ball-and-Stick hardener · Transport infrastructure · Sound pressure levels · Noise spectra · Vibration spectra · Acoustic safety
A. Isaev · S. Popov (B) · J. Marchenko · N. Dontsov · E. Kosenko Don State Technical University, Gagarin Square, 1, Rostov-on-Don 344003, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_192
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1 Introduction The processing of flat parts by ball-and-rod hardening includes such noise sources in the acoustic system as: – – – –
compressor; hardener; products on which the surface layer is hardened; the carrier system of the equipment itself [1–3].
It should be noted that with ball-and-rod hardening on a milling machine, only the drive of longitudinal and transverse feeds is turned on, while the drive of the main movement is turned off. The hardening tool is attached with a clamp and does not have a rotational movement. In the course of research, it is necessary to obtain the frequency nature of the carrier system and the workpiece. Determine the regularity of the increase in the levels of vibration velocity depending on the frequency of exposure, and also confirm the validity of the theoretical approach in describing the regularities of the noise generation process [4–10].
2 Results of Experimental Studies of Noise and Vibrations During Ball-And-Stick Hardening of Flat Parts Based on the results of the research, it can be concluded that the noise of the milling machine in idle mode in the entire normalized frequency range is below the sanitary standard (Fig. 1): However, the noise levels during compressor operation exceed the maximum allowable values in the fifth and sixth tails by 3–5 dB in the frequency range of 110 100 Lp, dB
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Fig. 1 Machine and compressor noise spectra at idle: 1—limit spectrum, 2—compressor noise, 3—machine noise
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500–1000 Hz. In the fifth octave with a geometric mean frequency of 500 Hz, the maximum excess of noise levels is observed [11–15]. When conducting experimental studies of noise and vibrations during processing by ball-and-rod hardening, they were carried out with products of various configurations of flat parts, including rectangular beams, plates, and parts such as box-shaped shells from a rectangular hollow profile. In the course of experimental studies, the preload of the hardener is 1.5 and 4.5 mm with the number of rods in the tool equal to 19 and 40 and the impact frequency is 42 Hz. When installing on a milling machine, samples of parts were installed. The frequency of the force impact on the part was: – with the number of rods in the package 19 pieces, f = 798 Hz; – with the number of rods in the package 40 pieces, f = 1680 Hz. The experimental studies obtained showed equality in the patterns of noise generation during ball-and-rod processing of parts of similar configurations and process parameters. In this regard, the results of studies given below are for flat ones at exposure frequencies f = 798 and 1680 Hz [16–22]. However, under the influence of the technological process, the spectral composition of the noise generation of the machining process changes significantly compared to the idling of the milling machine (Fig. 2). The measurements were made for structures of various geometric dimensions, and taking into account all the technological parameters and design features of the process, the results showed almost complete identity in the formation of the spectra. The differences were only in the levels of the spectral components. When ensuring safe working conditions, it is necessary to take into account the scattering field of octave sound pressure levels associated with the geometric dimensions of products, technological parameters and design features of the hardening process, therefore, in the spectra presented in Fig. 2–3, the maximum values of octave sound pressure levels are shown [23–26]. 110 100 Lp, dB
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Fig. 3 Noise spectrum of a flat part at f = 1680 Hz: 1—limit spectrum, 2—noise spectrum
In the operating mode, the spectrum is transformed and has a medium and high frequency character. The sound pressure level reaches its highest value in the fifth and ninth octaves with a geometric mean frequency of 500–8000 Hz, as well as in the sixth octave with a geometric mean frequency of 1000 Hz. An increase in the sound pressure level by 3–4 dB is associated with a threefold increase in interference. An increase in sound pressure levels by 4–8 dB is at an interference fit of 1.5 mm, and 10–12 dB at an interference of 4.5. With an increase in the frequency of exposure to a technological load, it leads to an increase in sound pressure levels (preload value 4.5 mm) by 3–4 dB (Fig. 3). In this case, the composition of the spectrum becomes more high-frequency [27, 28]. In the frequency range of 500–8000 Hz, there is an excess of the maximum permissible values of sound pressure levels by 8–20 dB. At the same time, the vibration spectrum of the milling machine (Fig. 4) has a low-frequency character. The decrease in vibration velocity levels is 4–5 dB per octave. 110 100 Lp, dB
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Fig. 4 Vibration spectra during ball-and-stick hardening: 1—on the spindle head, 2—on the machine table
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Fig. 5 Vibration spectra 1—on the nozzle, 2—details
High vibration levels during experimental studies were recorded on the nozzle (Fig. 5).
3 Conclusion As you can see, a clearly defined high-frequency character on the carrier system is displayed on the workpiece in contrast to the vibration spectra. A fairly uniform distribution of the intensity of the spectral components of the vibration velocity occurs in the sixth and ninth octaves, where the difference in levels does not exceed 2–3 dB, which is within the measurement error. With an increase in the frequency of exposure by a factor of two, it leads to an increase in vibration velocity levels by 3–7 dB. The patterns of formation of vibration spectra on the workpiece also showed a high-frequency character. It should be noted that at the same frequencies of the force impact, the magnitude of the vibration velocity on the part is 5–8 dB less than on the nozzle. In this case, one should take into account the surface area of the nozzle, which emits sound energy, since it is much smaller than the surface area of the workpiece. In this regard, it should be assumed that despite the higher vibration activity of the nozzle, the sound radiation of the workpiece is more involved in the formation of the sound field in the working area in relation to the nozzle. Thus, the research results confirm the validity of the theoretical approach to the description of the regularities of the noise generation process. The dominant sources of noise, which create the excess of sound pressure levels in the operator’s working area over the maximum permissible values, are the workpiece and hardener.
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References 1. Beskopylny A, Meskhi B, Beskopylny N, Chukarina I, Isaev A, Veremeenko A (2022) Strengthening of welded joints of load-bearing structures of robotic systems with ball-rod hardening. In: Shamtsyan M, Pasetti M, Beskopylny A (eds) Robotics, Machinery and Engineering Technology for Precision Agriculture. Smart Innovation, Systems and Technologies, vol 247, pp 1–11. Springer, Singapore. https://doi.org/10.1007/978-981-16-3844-2_1 2. Beskopylny A, Chukarin A, Meskhi B, Isaev A (2021) Modeling of vibroacoustic characteristics of plate structures of vehicles during abrasive processing. Transp Res Procedia 39–46. Cep. International Scientific Siberian Transport Forum, TransSiberia 2020. https://doi.org/10.1016/ j.trpro.2021.02.045 3. Beskopylny A, Meskhi B, Chukarin A, Isaev A (2020) Spectral characteristics of noise during hardening of welds of rod structures. In: IOP Conference Series: Materials Science and Engineering. Collection of materials of the International Conference on Modern Trends in Manufacturing Technologies and Equipment: Mechanical Engineering and Materials Science (ICMTMTE 2019). Sevastopol State University, National University of Science and Technology «MISIS», Polzunov Altai State Technical University, Crimean Federal University, Inlink Ltd. and International Union of Machine Builders, p 044087. https://doi.org/10.1088/ 1757-899X/709/4/044087 4. Bozhko I et al (2020) Development and research of tillage operating device with polymeric materials. In: E3S Web of Conferences, vol 175, p 05025. https://doi.org/10.1051/e3sconf/202 017505025 5. Beskopylny A, Chukarin A, Isaev A (2019) Noise spectra of ball-rod hardening of welds of rod structures. In: Murgul V, Pasetti M (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. AISC, vol 983, pp 489–495. Springer, Cham. https://doi.org/10.1007/ 978-3-030-19868-8_48 6. Marchenko EV, Korotky AA, Popov SI, Marchenko JuV, Dontsov NS, Kosenko EE (2022) Investigation of the causes of defects in the section of steel rope splicing. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference “INTERAGROMASH 2021”. LNNS, vol 246, pp 226–234. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_25 7. Rudoy D, Murgul V (2019) Preface. In: E3S Web of Conferences, vol 135, p 00001. https:// doi.org/10.1051/e3sconf/201913500001 8. Marchenko JuV, Korotky AA, Popov SI, Marchenko EV, Galchenko GA, Kosenko VV (2022) Municipal waste management in an urbanized environment based on ropeway technology. In: Beskopylny A, Shamtsyan M (eds) XIV International Scientific Conference “INTERAGROMASH 2021”. LNNS, vol 246, pp 235–241. Springer, Cham. https://doi.org/10.1007/978-3030-81619-3_26 9. Popov SI, Galchenko GA, Marchenko JV, Drozdov DS (2022) Use of Neural Networks and Autopilot for Quick and Accurate Grain Discharge on the Elevator. In: Shamtsyan M, Pasetti M, Beskopylny A (eds) Robotics, Machinery and Engineering Technology for Precision Agriculture. Smart Innovation, Systems and Technologies, vol 247, pp 45–53. Springer, Singapore. https://doi.org/10.1007/978-981-16-3844-2_6 10. Savenkov D et al (2019) Study of the nature of the dynamic coefficient of internal friction of grain materials. In: E3S Web of Conferences, vol 135, p 01102. https://doi.org/10.1051/e3s conf/201913501102 11. Antipov S, Khozyaev I, Panfilov V, Rudoy D, Shakhov S (2020) Food technologies and their environmental impact. In: IOP Conference Series: Materials Science and Engineering, vol 1001 International Scientific and Practical Conference Environmental Risks and Safety in Mechanical Engineering (ERSME-2020), p 012137. https://doi.org/10.1088/1757-899X/1001/ 1/012137 12. Marchenko EV, Korotky AA, Popov SI, Marchenko JV, Kosenko EE (2021) Modelling of technological process of joining steel ropes with the use of powder antifriction material and a
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Method of Student Individuality Identification for Adapting and Intelligent Training Module Based on Soft Models Ilgar Alekperov , Gurru Akperov , Yuri Prus , Vladimir Khramov , and Safura Muradova
Abstract Cognitive possibilities of digitisation allow considerably increase individualisation of the training process, improve its quality due to introduction of artificial intelligence elements into the knowledge circuit. These elements will allow conducting continuous monitoring of the trainee’s current knowledge. By perceiving the training system as an active man–machine system, in which the machine, represented by artificial intelligence, plays a role of an equal partner, in terms of importance for forming the necessary student’s knowledge, all the advantages of this activity and ergativity should be involved. In conditions of remote training, the so-called hybrid intelligence, that provides the mutually supplemented image of a computer teacher, plays an important role. This work deals with the problems of using qualitative and, consequently, fuzzy characteristics of each individual trainee. Such characteristics are formed by means of artificial intelligence for training process management. The presented soft description of students’ personalities gives the possibility to perform modelling and to forecast training results in real time scale. Functioning of hybrid intelligence, as an information semantic man–machine system, in the context of knowledge and skills formation, may be effective due to indices of participants’ intelligent subjectivism of the training process and the respective software intelligence quality. Keywords Training individuality · Personality identification · Knowledge development dynamics · Psychological interaction · Soft model · Adaptation · Intelligent training module · Hybrid intelligence
I. Alekperov · G. Akperov · V. Khramov (B) · S. Muradova Southern University (IMBL), Mikhail Nagibin Ave., 33a / 47, 344068 Rostov-on-Don, Russia e-mail: [email protected] Y. Prus Federal State Budgetary Institution All-Russian Research Institute for Civil Defence and Emergencies EMERCOM of Russia, Federal Center for Science and High Technologies, Moscow 129337, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_193
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1 Introduction We will regard the trainee’s individuality as «the entirety of mental and physiological features, individually varying within the set scale. The record of the specified features allows a lecturer to apply methodical methods efficiently in conducting classes, thus improving the didactic process quality» [1]. The trainee’s individuality identification is the process of building a soft mathematical model according to the measurable input and output psychological characteristics. «We shall consider the trainee’s basic psychological characteristics as intelligence development, presence of positive training motivation, peculiarities of character and temperament» [2]. The general model of psychological activity at the informative level can be described as follows. Using the sensor system, the trainee creates an¬ individual information image of the certain situation in the context of the environment and further, by analysing the information obtained, broadly implements behaviour.
2 Materials and Methods Let W ei be a set of external actions at human sensor system in the certain situation, and J i will be its information image for the its individual. Then, Ji (t) = i Wei (t − τ ), t
(1)
Here, t—current time; J i —individual operator of information representation; τ— delay time, conditioned by the sensor system delayed action. The individual’s behaviour is described by the equation Pi (t) = Pi Ji (t), t
(2)
where Pi —individual behaviour operator. Models of active (conscious) behaviour, based on intelligent information processing, are considered further. At the trainee identification, the classic identification theory cannot be applied, because [2] it is impossible to measure the individual’s reaction only in terms of quantity. As a rule, only behaviour type and its qualitative characteristics are recorded. Here, two approaches are possible. One of them is encouraging a trainee to cognition and formalisation of the certain psychological process. Polls, peer inspections are the tools of this approach. The distinctive features of this approach are «subjectivism, information distortion, correlation of results and the poll method and procedure, the researcher’s ability to influence on the results» [3]. Aspiration to overcome the specified subjectivism leads to a different approach, which lies in conducting active and passive experiments with the subject, registering the type and available qualitative
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behaviour characteristics. Information, obtained in this way, is used to identify the trainee’s individuality. The role of identifiable operator F can be played by models of mental and physiological processes of environment representation (operator Odisp )—perception of visual, sound, tactile images, and models of intelligent data processing—(operator Oproc )—understanding, recognition, classification, selection, etc. Generalised behaviour model, independently on the certain intelligent process, may be expressed as Um = Fm (x, qm ),
(3)
where F m —behavior model operator, x—n-D quantitatively measured input impact (situation), qm —m-D vector of the model quantitative characteristics (parameters). In case of identifying intelligent processes, «experimental information allows distinguishing only equivalence classes and preference order on behavior sets (output actions x). In such conditions, the problem of identification lies in finding such F m and qm , that do not contradict equivalence and preferences ratio for each pair of situations x i , x j , resulting from respectively [4]. F(xi ) = F x j and F(xi ) > F x j
(4)
Solving the identification problem, similar to classic setting, requires determination of the, operator F m form (structural identification) and values of parameters qm (parametric identification). There are two approaches to F m identification. The first is the desire to synthesise an operator that describes the real processes occurring in the brain with the greatest accuracy. The second approach is in selecting a simpler operator F m , «the structure of which is not related to real one, but it provides the coincidence of reactions of the real system and the model with the required accuracy (equivalence in terms of reaction). The latter approach to a greater extent meets the task of formalising intelligent processes» [5] in the field of creating artificial intelligence systems. Therefore, the model of intelligent and mental and physiological processes of the trainee’s behaviour, described with Eqs. (1)–(4), can be used in test diagnostic procedures for his/her individuality identification for purposes of modern automated (digitised) training.
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2.1 Problem of Adaptation to the Trainees’ Intelligence Properties For the time being, there have been developed various theories, explaining the nature of intelligence and its notion. In the context of this paper, let us accept the notion of intelligence, given by M.A. Kholodnaya [4] as the form of the subject’s mental experience organisation. It is considered that the subject’s intelligent properties are the set of his/her intelligence activity manifestations in various types of activity, in particular, for the trainee, it is the activity within the didactic process. Intelligence structure analysis, conducted in research of psychologists, allows distinguishing qualitative and quantitative intelligence characteristics. Quantitative characteristics can be measured by various mental diagnostic methods (Amthauer, Wechsler, Raven, Eysenck tests). Formally, the trainee’s ith intelligence property can be given in the intelligent space as a fuzzy point X i with a certain fuzzy neighbourhood S i . For this purpose, let’s define the intelligent space as a pair IQ = áX i ,S i ñ, i = 1, k; where X—coordinate vector of fuzzy points X (X 1 , X 2 , …,X k ), corresponding to k—intellectual properties of trainees, and S—vector of fuzzy neighbourhoods S (S 1 , S 2 , …,S k ) points. Here, k is the number of recorded intelligence properties in the information space. Formulation of the task of the intelligent training module (ITM) of adaptation to the trainees’ intelligence properties starts from specifying conditions and requirements [4]. Training action management conditions are specified in the course of testing and determining the vector of the trainee’s intelligence properties. Depending on values of vectors X and S, ITM develops the control action vector H (H 1 , H 2 , …,H m ), aimed at maximal satisfaction of the trainee’s cognitive needs for minimal time. Control actions are performed with ITM software and hardware. They can be characterized by selecting the unit of training information portion submission, establishing the material presentation sequence, selecting the didactic material presentation form (means of multimedia), selecting the action implementation time, etc. The problem of the ITM adaptation to the trainees’ intelligence properties is considered as a problem of variable structure object discrete control. At each didactic process step, the trainee is transferred from the fuzzy state Oi to Oj by the controlling action H, that takes into account the trainee’s intelligence structure. Therefore, the problem of the ITM adaptation to the trainees’ intelligence properties has a formulation: accepting the trainee’s intelligence structure as initial data, form the ITM control vector H, providing the trainee transfer from the initial fuzzy stateO0 to the finite desired fuzzy state Om within the minimal training time m
τIQ =
1 Tmin (
X, S, O0 , Om , H) = min
n=1
t (Hn )
,
(5)
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where X—vector of trainees’ intellectual properties; S—vector of fuzzy properties neighbourhoods; O0 —initial trainee’s fuzzy state; Om —desired trainee’s fuzzy state; H—ITM control vector; m is the number of controlling actions. In the Eq. (5), τIQ is the training time dependence on the trainee’s fuzzy states Oi and selection of ITM control actions H n . The right part of the equation should provide the time optimum (minimum) of controlling actions taking into account the trainee’s intelligence structure.
2.2 Problem of ITM Adaptation to the Trainees’ Mental and Physiological Properties As discussed above, training effectiveness depends on regard of the trainees’ mental and physiological characteristics. The basic mental and physiological properties that affect the trainee’s preparation progress [5] are: low education motivation; trend to nervous system weakness in terms of excitation; extremely expressed nervous system strength in terms of excitation; expressed block of nervous processes; inadequately inflated self-assessment; inadequately increased level of aspiration; inadequately decreased level of aspiration. It is proposed to enter indicators for the specified properties (Table 1). It should be noted that the listed mental and physiological features have different nature. So, in separate cases, not only regarding individual properties, but performing their correction is also reasonable. For determining individual mental and physiological features, affecting the professional training efficiency, the known test methods should be used. Upon completing mental and physiological diagnostics, the trainee can be classified by mental and physiological signs. Further, at the training process organisation with the use of ITM, the training action selection should be conditioned by the trainee’s mental and physiological portrait [6], completed at the diagnostics stage. Formally, the set of the trainee’s mental and physiological properties can be given as a vector (1, 2, …, h), where h is the number of properties. Each property is associated with a certain fuzzy point in the mental and physiological space of signs, and the respective point fuzzy neighbourhood from the vector S (S1, S2, …, Table 1 Indicators of psychophysiological properties Psychophysiological properties
Test method
Indicator
1. Motivation
Professional motivation
M
2.The strength of the nervous system for arousal
Ilyin’s motor technique
SNS
3. The mobility of the nervous system
Ilyin’s motor technique
MNS
4. Self-esteem level
Self-assessment scale Ch. Spielberg, Yu. Khanina
SEL
5. Level of claims
Hoppe technique
LC
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Fig. 1 A multidimensional property space with the number of sections m = 3
Sh). By analyzing the trainee’s position in the space of mental and physiological states, ITM develops the control action vector H (H1, H2, …, Hm). Training management takes into account features of the trainees’ mental and physiological area and allows reducing the value of such training system quality indicator as training time [7–9]. Let n-dimensional space of personality traits Gn be described by the combination of m-dimensional sections (m < n). For example, on the Fig. 1 we can see such a section for m = 3. In Gn we know the location and dimension of the area of requirements Z m , which should meet the qualified specialist limited by a blurred hypersphere.
2.3 Features of the Thought Experiment Based on the results of the input testing let the data be about the location of the trainee in Gn . The destination will denote as T o . Generally speaking, taking into account the incomplete validity of test results we can only say that point T o belongs to a certain region bounded by hyper-spheres Z o . The adaptation task in n-dimensional space of properties [6] is the selection and application of control actions, with the help of which time-efficient transfer of the student from the initial point Z o to the desired area of Z m hypersphere is carried out. At the same the transition Z o → Z m is not carried by vector 1, but by polyvector, for example, 2 or 3 (Fig. 1). It should be noted that, firstly, vector 1 is not always effective enough [10] (when using the Veitch squares model) to solve the problem of correcting the learning process. It directs the difficulties of making the transition along the shortest path, and sometimes we do not implement it. Secondly, there are no training methods that provide a one-step transition from Z o to Z m. . The choice of the transition method depends on a number of factors [3, 11], such as the individual characteristics of the student, the personal qualities of the teacher, the variety of teaching methods, the availability of funds and the level of automation of training, etc. The areas of belonging of the models of the real and ideal learner in the ndimensional space of personality properties [10] can be characterized using the theory of fuzzy sets. This is due to the fact that, firstly, the field of knowledge has fuzzy boundaries [12], and secondly, there is a considerable amount of subjectivity in knowledge control procedures.
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3 Results Therefore, the problem of ITM adaptation to mental and physiological properties of trainees is the following: considering the values of vector of the trainee’s mental and physiological indicators (M, SNS, MNS, SEL, LC) as the set ones, build a vector H of ITM control actions, that provides the trainee’s transfer from the initial fuzzy state O0 to the required fuzzy state Om within the minimal training time [2, 8, 13] m
2 τ = Tmin (, S N S, M N S, S E L , LC, O0 , Om , H ) = min n=1
t (Hn )
,
(6)
where M, SNS, MNS, SEL, LC are parameters, specified in Table 1; O0 —initial trainee’s fuzzy state; H—ITM control vector; Om —desired trainee’s fuzzy state. In Eq. (6), the training time τ depends on the trainee’s fuzzy states Oi and on selection of ITM control actions H n . The condition of minimum for duration of controlling actions, taking into account the trainee’s mental and physiological characteristics (vector ), is fulfilled.
4 Conclusion Imparting a property of adaptation to training goals and conditions to ITM allows expanding beyond the training reproductive style [14]. At the same time, adaptation has the following orientation: the trainee’s individual characteristics, his/her current needs and state, the trainee’s current state. Functioning of ITM, as an information semantic man–machine system, in the context of knowledge formation and skills to use it, may be effective due to regard of indices of intelligent subjectivism in the training process participants, and software intelligence quality. Developing a method of adaptation of the automated training process to the trainee’s personality, his/her intelligence and psychology is an actual scientific problem. ITM adaptation to the trainee is required at the modern level of information technologies with the purpose to minimise the training time at the set quality, and it can be achieved by organising training portions of knowledge, depending on the trainee’s intelligence and mental and physiological features, and quality of material mastered by him/her. The approaches, used in this paper, are aimed at regarding the wide entirety of NO factors: incompleteness, inaccuracy, fuzziness, underdefiniteness, and so on, inherent to real training situations. For this reason, it is supposed to be reasonable to use fuzzy computing and soft models as the main instrument of the training process organisation.
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References 1. Akperov GI, Khramov VV (2020) A fuzzy semantic data triangulation method used in the formation of economic clusters in southern Russia. Adv Intell Syst Comput 1095:340–344. https://doi.org/10.1007/978-3-030-35249-3_43 2. Svyatkina MN, Tarassov VB, Dolgiy AI (2016) Logical-algebraic methods in constructing cognitive sensors for railway infrastructure intelligent monitoring system, vol 450, pp191–206. https://doi.org/10.1007/978-3-319-33609-1_17 3. Akperov GI, Khramov VV, Gorbacheva AA (2020) Using soft computing methods for the functional benchmarking of an intelligent workplace in an educational establishment. Adv Intell Syst Comput 1095:54–60. https://doi.org/10.1007/978-3-030-35249-3_6 4. Kholodnaya MA, Volkova EV (2016) Conceptual structures, conceptual abilities and productivity of cognitive functioning: the ontological approach. Procedia Social Behav Sci 217:914– 922 5. Kramarov S, et al (2020) Fuzzy models of educational process management: digital transformation. Commun Comput Inf Sci 1201:78–85. https://doi.org/10.1007/978-3-030-468 95-8_6 6. Akperov IG, Khramov VV (2019) Development of instruments of fuzzy identification of extended objects based on the results of satellite monitoring. Adv Intell Syst Comput 896:325–332. https://doi.org/10.1007/978-3-030-04164-9_44 7. Dosiyev AA, Celiker E (2014) Approximation on the hexagonal grid of the Dirichlet problem for Laplace’s equation. Boundary Value Prob 4(1):2014–2073. https://doi.org/10.1186/16872770-2014-73 8. Krivovichev SV (2012) Algorithmic crystal chemistry: a cellular automata approach. Crystallogr Rep 57:10–17. https://doi.org/10.1134/S1063774511060149 9. Akperov IG, et al. Fuzzy methods and algorithms in data mining and formation of digital planschemes in earth remote sensing. In: 9TH International conference on theory and application of soft computing, computing with words and perception, ICSCCW 2017, August 2017, Budapest, Hungary, pp 120–125. https://doi.org/10.1016/j.procs.2017.11.218 10. Kozlovsky AN, et al (2020) Fuzzy-logical modelling of the enterprise resilience: NONtraditional aspects. In: Proceedings of 2020 23rd international conference on soft computing and measurements, vol 23, pp 84–85. https://doi.org/10.1109/SCM50615.2020.9198785 11. Kramarov SO, et al (2017) The principles of formation of united geo-informational space based on fuzzy triangulation. In: 9TH international conference on theory and application of soft computing, computing with words and perception, ICSCCW 2017, Budapest, Hungary, August 2017, pp 835–843. https://doi.org/10.1016/j.procs.2017.11.315 12. Akl EA, El-Jardali F, Bou Karroum L, et al (2015) Effectiveness of mechanisms and models of coordination between organizations, agencies and bodies providing or financing health services in humanitarian crises: a systematic review. PLOS Med 10(9). https://doi.org/10.1371/journal. pone.0137159 13. Aggarwal CC, Subbian K (2012) Event detection in social streams. In: Proceedings of the 2012 SIAM international conference on data mining. (Disney’s Paradise Pier Hotel, Anaheim, California, USA, 26–28 April 2012, vol 12. SDM. SIAM/Omnipress, pp 624–635. https://doi. org/10.1137/1.9781611972825.54 14. Jamshidi M (2017) Systems of systems engineering: principles and applications. CRC Press, Baco Raton, pp 12–19. https://books.google.ru/books?id=YvxUon2vAfUC&lr=&hl=ru&sou rce=gbs_nav
Energy Saving in Hydraulic Testing Systems Alexey Pelipenko , Alexander Rybak , Natalya Vyborova , Sergey Zolotov , Vladislav Zubtsov , and Dmitry Lugantsev
Abstract In the modern world, one of the most important places both in the development of industry and in the social sphere occupies the problem of providing energy and its savings. It is not an exception and use and consumption of energy in hydromechanical systems of machine drives and technological equipment. At the same time, energy saving is particularly important to ensure with resource tests of hydraulic machines, during which useful work is not performed, and the useful effect is reduced to the proof of the fact that the test machine is operational and reliable. The article provides a stand diagram for testing hydraulic motors and pumps with energy recovery (RF Patent No. 204153). In the course of the study of the stand made under the proposed scheme, its mathematical model was obtained, calculations were made, evidence was obtained that it performs the required functions with the required quality. The coefficient of testing efficiency is proposed, showing the ratio of the test power of hydromachines to the power spent on their tests. The results of theoretical studies are confirmed on an experimental bench manufactured by the proposed scheme. Keywords Hydraulic machines · Energy efficiency in transportation · Testing · Energy saving · Energy recovery · Test bench · Simulation and calculation
1 Introduction In the modern world, one of the most important places both in the development of industry and in the social sphere occupies the problem of providing energy and its savings. It is not an exception and use and consumption of energy in hydromechanical systems of machine drives and technological equipment. One of the directions of energy saving in hydraulic drives is to use power sources with the discharge of the pump, in the absence of a payload on the actuator’s hydraulic motor [1, 2]. But the greatest interest is the solution to the problem of energy saving, A. Pelipenko · A. Rybak (B) · N. Vyborova · S. Zolotov · V. Zubtsov · D. Lugantsev Don State Technical University, Gagarin Square, 1, 344003 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_194
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both in mobile technique and in the technological equipment of energy recovery in various ways in the process of their functioning [3–13]. Technological machines of cyclic action, such as automotive boom hydraulic machines, hydraulic excavators, earthmoving equipment, forklift trucks, tractors and other machines that are used for lifting and lowering the working body with a load heavy loading mechanisms are characterized by large energy costs of the drive. The secondary use of lost energy can significantly increase the efficiency of hydraulic drives [14–19].
2 Materials and Methods A special place in technical systems requiring energy recovery in the process of their operation is occupied by means of testing and in particular resource tests of hydraulic machines of medium and high power. This is due to the stammer that in the process of testing and not produced useful work, that is, the energy spent on testing is completely lost, the positive effect on the test is in obtaining objective information about the performance and reliability of the subject. Particularly significant energy losses, and therefore be material costs, are observed when conducting inventory resusa tests, as they are conducted for a long time and on nominal capacities. The schemes of the methods of recovery of energy are known when conducting resource tests of plunger hydraulic cylinders [20, 21] Their essence is that part of the energy spent on conducting tests is returned as an energy source of energy. This article is devoted to the study of the testing process of hydraulic machines of rotational action with the recovery of part of the energy spent. Figure 1 shows a stand diagram for testing hydraulic motors and pumps with energy recovery (RF Patent No. 204153). The work of the stand occurs as follows. The electrical energy taken from the electrical network is converted to the ElM electric motor into the mechanical energy of rotation of its shaft Sh1, then, through the mechanical transmission Bel1, it is transmitted to the Sh2 of the hydraulic pump, which is summed with the mechanical energy generated by the HM hydraulic motor on the Sh3 shaft and the shaft Sh2 hydraulic pump through mechanical transmission Bel2. The hydraulic pump P converts the total mechanical energy of the rotation of the Sh2 shaft into the hydraulic stream energy, which through the pressure hydraulic line L1 is transmitted to the input of the hydraulic motor HM, through which the energy of the hydraulic stream is converted into the mechanical energy of the Sh3 shaft rotation. The pressure growth in pressure hydrolynes is ensured due to the fact that the flow rate of the working fluid created by the hydraulic pump P to some value exceeds the flow rate that consumes the hydraulic motor. This is ensured by variationing parameters such as working volumes of hydraulic machines and mechanical gear ratios. The growth of pressure in the pressure line is controlled by a PV safety valve.
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Sh1
Bel1
Sh2
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Bel2
Sh3
ElM HM
l1
PV
PV
Fig. 1 Scheme of the stand test of hydraulic pumps and motors
The CV check valve is designed to create a closed hydraulic system unloading at times of its output to the specified functioning modes when the HM hydraulic motor performs the functions of the pump. Figure 2 shows a general view of the test bench manufactured by the proposed scheme. The stand allows for resource tests of hydrogen pump P and HM hydromotor with energy recovery, but before proceeding with experiments, theoretically investigate its functionality.
3 Results In recent years, due to the rapid development of computing equipment and its software, as well as in view of the appreciation of the production of experimental samples and the requirement to reduce the timing of the production of new products, the modeling of a new product and its theoretical study [22–28] has become more widespread [22–28]. With the aim of a theoretical study of the technical capabilities of the presented stand scheme, its mathematical model has been developed. The mathematical model of the stand was developed using the theory of bulk stiffness [29–31], taking into account the coefficient of volumetric rigidity of hydraulic elements, which allows you to more accurately simulate the system approximated to the real characteristics of the stand.
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Sh2 T Bel1 Sh1 P Bel2
ElM
Sh3
HM1
Fig. 2 General view of an experimental bench for testing hydraulic pumps and motors
In accordance with the theory of volume rigidity, the pressure at any point of the hydraulic system can be determined from the equation dp = Cr c.i
Q in.i −
Q out.i dt,
(1)
where —amounts of expenditure of the working fluid included and outgoing from the considered (i) system volume during the time dt dt; Cr c.i —reduced coefficient of volume stiffness of the volume of the hydraulic system. The movement of hydromotor and hydraulic pump rotors are described by equations: 1 dω H M = w H M ( p H Min − p H Mout ) − M Sh3 , dt JM
(2)
1 dω P = (M Sh1 i 12 + M Sh3 i 32 − w P1 ( p Pout − p Pin )), dt JP
(3)
where wHM , wP —Characteristic volumes of HM and pump p hydromotor, respectively; ω H M and ω P —corner speed of rotation of the shafts of hydromotor Sh3 and pump Sh2 respectively; JHM , JP —central moments of inertia of rotors HM hydromotor and hydraulic pump P respectively; pHMin —pressure at the entrance to
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N, kW
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P2 HM1 HM2 HM3
ElM3 ElM2 ElM1
t,
Fig. 3 Calculated power values of: electric motor ElM, hydraulic pump P and hydraulic motor HN with different gear ratios i 2 : index 1 acc. i2 = 1.05, index 2—i2 = 1,25, index 3—i2 = 1,43
the hydraulic engine; pHMout —hydromotor outlet pressure; pP1in —hydraulic pump entrance pressure; pPout —hydraulic pump exit pressure P; MSh1 and M Sh3 —torque moments on the shafts of the electric motor and hydrometer, respectively; i1_2 and i3_2 —mechanical gear ratios Bel1 (From the electric motor shaft on the tree of hydraulic pump) and Bel2 (from the shaft of the hydromotor on the tree of hydraulic pump) respectively. Figure 3 shows, on the example, the calculated graphs of change changes in which the hydraulic pump, Hm hydraulic motor and an ElM electromotor, are functioning, with different mechanical transmission values of the mechanical transmission I2 from the HM hydraulic pump on the H hydraulic pump shaft. P. The graphics presented convincingly proving that on the tests of hydraulic machines at their rated power, the power of the electric motor is many times less [32–34]. To assess the effectiveness of the test process, the effectiveness coefficient of testing process is introduced equal to the ratio of power in which the test hydromachines are functioning to spent power during testing (power consumed by the electric motor) [35]
ke f f =
NH M , N El M
(4)
where N H M —power at which hydraulic machines occur, in this case—power generated by hydraulic pump; N El M —Power really spent on testing, in this case—power consumed by electric motor.
4 Discussion Analyzing the results presented in Fig. 3 it is easy to calculate the values of the efficiency coefficient of hydromachins under different test conditions (with different
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transmission values i2. Calculations showed that i2 = 1.05 test efficiency coefficient is equal ke f f = 11.1, at i2 = 1,25—ke f f = 3, 85 and at i2 = 1,43—ke f f = 2, 17. This means that, theoretically, in the first case, the test of hydromachins is expended by 11.1 times less than power, the test occurs, respectively, in the second case, this ratio is 3.85, and in the third 2.17.
5 Conclusions Thus, it is clear that the presented stand for testing hydraulic motors and pumps with energy recovery (Patent of the Russian Federation No. 204153) fully provides a significant reduction in the cost of energy to conduct resource testing of hydraulic machines of rotational action, in addition, the results obtained show that with a decrease in gear ratio i2 the efficiency of the recuperative booth system increases sharply, which indicates that energy costs for testing are reduced. The results of the calculations were confirmed experimentally.
References 1. Rybak A, Tsibriy I (2020) Simulation of the pump-battery power supply control system based on the unloading machine. E3S Web Conf 164:01004 2. Kobzev K, Vyalov S, Rybak A (2020) Pumping hydraulic systems and the use of an unloading valve in a hydraulic system. E3S Web Conf 175:05036 3. Nikonov VO, Drazhev VI, Kozlov EV, Borodkin VO (2019) Analysis of the structural energies of hydraulic technological machines with the recovery of the potential energy of the working body with a cargo. Voronezh Sci Tech Bull FSBEO Voronezh State Forestry Univ named after P. Morozov 1(27):4–17 4. Kuznetsova VN, Savinkin VV (2015) Development of the design of a hybrid drive of a turntable driving platform for performing construction work. Sibadi Bull 1(41):17–23 5. Khmara LA Improving the efficiency of the bulldozer by using a hydropneumous accumulating system. In: Hydra factory SDM, pp 1–5 6. Chmil VP (2016) Recompetitive drive of hydromechanism lifting the boom of excavator. Bull Civil Eng Transp Mt Constr Eng 4(57):167–169 7. Xia L (2018) Energy efficiency analysis of integrated drive and energy recuperation system for hydraulic excavator boom. Energy Convers Manag 156:680–687 8. Karpenko MM, Pelievin LE, Bogdavichus M (2017) Perspective of using a hydraulic energysaving drive. Tech Technol Prob Serv 3(41):7–12 9. Yu Y (2019) Optimization of energy regeneration of hybrid hydraulic excavator boom. Energy Convers Manag 183:26–34 10. Minav T, Hänninen H, Sinkkonen A, Laurila L, Pyrhönen J (2014) Electric or hydraulic energy recovery systems in a reach truck– a comparison. Strojniški vestnik – J Mech Eng 60(4):232– 240 11. Ho TH, Ahn KK (2008) Design and control of a closed-loop hydraulic energy-regenerative system. J Autom Constr 17:361–367 12. Xiao Q, Wang Q, Zhang Y (2008) Control strategies of power system in hybrid hydraulic excavator. J Autom Constr 17(4):361–367. https://doi.org/10.1016/j.autcon.2007.05.014
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13. Minav T, Immonen P, Laurila L, Vtorov V, Pyrhönen J, Niemelä M (2011) Electric energy recovery system for a hydraulic forklift - theoretical and experimental evaluation. IET Electr Power Appl 5(4):377–385. https://doi.org/10.1049/iet-epa.2009.0302 14. Chetverikova IV, Popikov PI (2016) Improving the effectiveness of road log trucks with hydraulic manipulators for the combined methods of delivery of wood in terms the North-West of Russia. Actual Areas Res XXI century Theory Pract 4(5–4):173 15. Posmetev VI, Nikonov VO, Posmetev VV (2018) Investigation of the energy-saving hydraulic drive of a multifunctional automobile with a subsystem of accumulation of compressed air energy. IOP Conf Series Mater Sci Eng 441:012041. https://doi.org/10.1088/1757-899X/441/ 1/012041 16. Posmetyev VI (2018) Perspective design of hydraulic actuator with gears of recovery of energy in forest cars with the trailer. Voronezh Sci Tech Bull 3(25):4 17. Rybak A, Lyakhnitskaya O (2017) Modelling the reduced coefficient of volumetric rigidity in high-pressure rubber-cord shell hoses. Matec Web Conf 132 18. Shcherbakov VF (2008) Recuperative drive system of hydraulic lifting machines. Constr Road Mach 9:49–51 19. Posmetyev VI, Bartenev IM, Malyukova MA, Malyukov SV (2019) Energy saving of hydraulic drives of machines due to increase of effectiveness of hydraulic cylinders cuffs according to the results of simulation modeling. IOP Conf Ser Mater Sci Eng 483(1):012107. https://doi. org/10.1088/1757-899X/483/1/012107 20. Pelipenko AYu, Rybak AT (2020) Stand for carrying out life tests of plunger hydraulic cylinders with energy recovery. IOP Conf Ser Mater Sci Eng 1001(1):012001. https://doi.org/10.1088/ 1757-899X/1001/1/012001 21. Rybak AT, Tsybriy IK, Nosachev SV, Pelipenko AY (2019) Simulation of the stand drive system for testing plunger hydrocylinders. AIP Conf Proc 2188:050042 22. Ivanovskaya AV, Rybak AT (2018) Simulation of drive of mechanisms, working in specific conditions. J Phys Conf Ser 1015(3):032054 23. Beskopylny A, Kadomtseva E, Strelnikov G, Berdnik Y, Morgun V (2018) Model of heterogeneous reinforced fiber foam concrete in bending. IOP Conf Ser Mater Sci Eng 365(3):032023 24. Beskopylny A, Lyapin A, Anysz H, Veremeenko A, Mozgovoy A (2020) Artificial neural networks in classification of steel grades based on non-destructive tests. Materials 13(11):2445 25. Litvinov S, Beskopylny A, Trush L, Yazyev S (2017) Optimization of thick-walled spherical shells at thermal and power influences. MATEC Web Conf 106:04013 26. Beskopylny A, Zhuravlev A, Shilov A (2020) Buckling analysis of rod structure of the two-tier dome. IOP Conf Ser Mater Sci Eng 913(2):022040 27. Petrenko L, Manzhilevskaya S, Shilov A, Abdullah Saleh A-HA (2018) The far-seeing planning systems and models for the construction management. MATEC Web Conferences 170:01007 28. Meskhi B, Golev B, Efros V, Zhurba V, Chayka Y (2019) Influence of parameters and location of the tumble inlet porton air charging in the diesel cylinder. E3S Web Conf 135:01083 29. Rybak AT, Shishkarev MP, Demyanov AA, Zharov VP (2018) Modeling and calculation of hydromechanical systems dynamics based on the volume rigidity theory. MATEC Web Conf 226:01001 30. Rybak AT, Pelipenko AY, Shishkarev MP, Nevzorova MY (2018) Projection of the hydraulic pressure drive with application of partial synthesis. MATEC Web Conf 226:01017 31. Rybak A, Lyakhnitskaya O (2017) Modelling the reduced coefficient of volumetric rigidity in high-pressure rubber-cord shell hoses. MATEC Web Conf 132:01001 32. Ivanov YuA, Pakhomov VI, Kambulov SI, Rudoi DV (ICMTMTE 2018) electronic edition. MATEC Web Conf 224:05023 https://doi.org/10.1051/matecconf/201822405023
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33. Parkhomenko G, Bozhko I, Kambulov S, Boyko A, Polushkin O, Lebedenko V, Beskopilniy A, Olshevskaya A (2020) E3S Web Conf 175:09006. INTERAGROMASH 2020. https://doi. org/10.1051/e3sconf/202017509006 34. Meskhi B, Bondarenko V, Efremenko I, Larionov V, Rudoy D, Olshevskaya A (2020) IOP Conf Ser Mater Sci Eng 1001:012100. https://doi.org/10.1088/1757-899X/1001/1/012100 35. Lachuga Y, Akhalaya B, Shogenov Y, Meskhi B, Rudoy D, Olshevskaya A (2020) IOP Conf Ser Mater Sci Engineering 1001:012121. https://doi.org/10.1088/1757-899X/1001/1/012121
Tillage Device of Precision Pocessing with Pulsed Blows of Compressed Air Yuri Lachuga , Badri Akhalaya , Yuri Shogenov , Besarion Meskhi , and Dmitry Rudoy
Abstract Multifunctional tillage device is presented, the basic principle of which is based on non-traditional technology. It is shown that the unconventional impact is carried out by pulsed air jet flows. To accomplish the task, the movement of the air stream from the cylinder to the launch system, the frame of the unit is used, which, in addition to its main purpose, performs the function of a receiver. It is noted that the tillage device, in addition to using non-traditional tillage technology, carries out milling, leveling the field surface and rolling. Keywords Tillage device · Air jet · Non-traditional technology · Hub · Spokes
1 Introduction One of the limiting factors in assessing the possibilities of replacing moldboard cultivation with non-moldboard and deep surface cultivation was considered to be the differentiation of parts of the arable layer according to fertility, which for a long time served as an important theoretical prerequisite for the need for annual cultural plowing. However, the studies carried out and the widespread use of non-moldboard tillage have significantly changed the idea of the different quality of soil profiles. The revealed patterns in some conditions refute the influence of the equal quality of the layers on its effective fertility and plant productivity, and in other cases allow us to determine the possible boundaries of the application of various treatments [1–11].
Y. Lachuga · Y. Shogenov Russian Academy of Sciences, 32A Leninsky Prospekt, 119334 Moscow, Russia B. Akhalaya Federal Scientific Agroengineering Center VIM All-Russian Institute of Agricultural Mechanization, 5, 1st Institute Passage, 109428 Moscow, Russia B. Meskhi · D. Rudoy (B) Don State Technical University, 1, Gagarin Square, 344003 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_195
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Wide opportunities in solving the problem of tillage are opened up by methods of combining various technological operations with combined units. Significant works have been carried out in this area [4, 5], which make it possible to realistically assess the prospects for creating new agricultural machinery based on combined machines. When using the “Strip-till” method in loosened strips, simultaneously with the application of fertilizers, depending on the readiness of the soil, seed material is often sown, as a result of which the plants during the period of active growth receive all the necessary nutrients in sufficient quantities right under the roots. Thanks to this technology, crops develop a powerful root system, which contributes to a good harvest in the future. The tangible results of this technology are observed during dry seasons, when a well-developed root system allows plants to receive moisture from deeper soil horizons and, in spite of everything, give abundant harvests, while about 2/3 of the land is not cultivated [6, 7]. An unconventional method of processing with an electric discharge when exposed to the soil can improve soil fertility, i.e. its properties and quality, and thereby enhance the growth and development of plants. The use of a promising technology of tillage with the help of compressed air impulses makes it possible to combine it with the rotation of the reservoir, while maintaining a large time interval between them. Positive effect on the preservation and increase of soil fertility is achieved if the soil is cultivated with a layer turnover of four to five years once, depending on the need, however, –1:(4–5). Before developing the design of the combined precision tillage device by the action of compressed air on the soil, a patent analysis of tillage machines and devices with different operating principles was carried out. (RU 2,335,107, MPK, 2008, SU 1,664,128 MPK, RU 2,335,107, MPK,2008, RF 2,491,807, MPK,2012; RU 136,275, MPK, 2013; RU 136,674, MPK, 2014). The majority of works are devoted to the traditional way of tillage. These devices belong to technologies in which mechanical impact on the soil occurs to varying degrees, which could serve as an example of the search for analogues. The priority choice in the right direction was a tillage device, the principle of operation of which is based on the use of a high-pressure air flow, a working body in the form of a slitter acting in the soil of the slot made [8, 9]. The fundamental disadvantage of the unit was its design feature, which consists in a high traction resistance of the unit, created vertically to the horizontal surface by the installed slotter, for this reason, and low operating speed, which reduces the performance of the device.
2 The Purpose of the Research Is to develop a tillage device for precision tillage with pulsed blows of compressed air, which reduces the traction resistance of the unit, increases productivity, and improves the quality of cultivation and environmental ecology.
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Tillage device for precision processing with pulsed blows of compressed air [10]. (Fig. 1), contains three sections, the first 1 and the third 2 of which are folding, the second Sects. 3—the base one—is made with a link 4, support 5 and transport 6 wheels and a compressed air cylinder 7. The front frame of each section is made in the form of a hollow shaft 8 connected to a compressed air cylinder 7, with working bodies rigidly fixed on it (Fig. 2) in the form of a rim 9, a hollow hub 10 and spokes 11. The spokes 11 are made with removable conical nozzles 12, containing the body 13, bushings—piston 14 with radial holes 15 and 16 on them and a pointed tip 17. Taper nozzles 12 are installed with the possibility of changing their number. The working bodies are made with the possibility of displacement along the frame when changing the type of tillage, i.e. from hollow tillage to continuous tillage. On the rear frame of each Sect. 1, 2 and 3,
Fig. 1 Tillage device for precision processing with pulsed blows of compressed air in two projections
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Fig. 2 The working body of the tillage device
tillage cutters 18 and ring-toothed rollers 19 are fixed on brackets, installed with the possibility of replacing them with the working width depending on the type (solid or strip) of soil cultivation with compressed air. Front frames of each Sects. 1, 2 and 3 are made in the form of a hollow shaft 8 and are connected to the compressed air cylinder 7 through pneumatic electro valves 20, micro-receivers 21 and pneumatic electro valves 22 (Fig. 3). Each microreceiver 21 has a device for changing the volume, for example, a piston 23, which is moved inside the cylinder 24 using a screw mechanism 25. Depending on the physical and mechanical properties of the soil, the required volume of compressed air in the microreceiver 21 is pre-set using a screw mechanism 25. At the command of the system control, microreceivers 21 are filled with high-pressure compressed air before the next impulse action on the soil from a high-pressure cylinder 7 through a common filling line due to the short-term opening of pneumatic electrovalves 20. Constant working pressure in cylinders 7 is maintained by a compressor (not shown). The cone nozzle 12 is a continuation of the spokes 11 with a threaded connection with them. Holes 15 and 16 are made for the passage of compressed air. Cylindrical body 13 contains a shank 26 holding the sleeve—piston 15 from falling out of the pneumatic channel 27. At the end of the pneumatic channel 27 there is a protrusion 28 of the body 13, which interacts with the shank 26 (Fig. 4). Tillage device of precision processing works as follows. Before moving the unit, with the help of hydraulic cylinders, the hollow shafts of all sections, together with the rims rigidly fixed to them, hollow hubs and spokes with conical nozzles at the end, are lowered to the setting depth of tillage. Compressed air to the nozzles comes from a high-pressure cylinder, passing through a common filling line, hub and spokes. The compressor maintains a constant pressure of compressed air in the cylinder. When the pneumoelectrovalves are opened, all micro-receivers of three sections (pipelines not shown) are filled with high-pressure compressed air. After filling them, the pneumatic electrovalves close and cut them off from the
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Fig. 3 Compressed air start system: 8—front frame of each section; 10—hollow hubs; 11—hollow spokes; 12—cone nozzles; 20, 21—pneumatic electrovalves; 22—microreceivers; 23—piston; 24— cylinder; 25—screw mechanism
common filling line. Thus, all microreceivers are prepared to supply a low-volume pulse of compressed air to the cone nozzles through a hollow shaft. At the command of the control system, pneumatic electrovalves are activated and provide high-pressure compressed air from the micro-reservoirs to the hollow shaft. Next, the compressed air flow is directed to the cone nozzles, following through the hub, spokes to the bushings—pistons, and forces the tip to extend to the stop. At this time, the radial holes are blocked, and the shank keeps the sleeve—the piston with a pointed tip from falling out of the pneumatic channel, resting on the protrusion of the tubular part. In this case, all cone nozzles rotating above the soil surface are not in the working position, i.e. before entering the soil and after leaving it. The rim, rotating, alternately immerses the spokes with conical nozzles into the soil. As the pointed tip of the cone nozzle sinks, the soil forces the sleeve—the piston to return to its original position, which contributes to the opening of the radial holes and the passage of compressed air. After that, microexplosive impact of compressed air pulses on the soil loosens. Then the cycle repeats. Tillage cutters located behind the wheels break up the soil, while ring-toothed rollers complete the tillage by compacting the surface. Agricultural machinery for precision tillage with pulsed compressed air is capable of simultaneously carrying out several operations, tilling the soil with pulsed high-pressure air to a standard
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Fig. 4 Cone nozzles a before starting compressed air; b in soil with closed tip in working position: 13—body; 14—hub—piston; 15, 16—radial holes; 17—tip; 26—shank; 27—pneumatic channel; 28—limiter
depth, then carrying out milling and completing tillage by rolling and compacting the soil. The tillage device for precision processing contains sections on the sides that easily transfer the unit to the transport position. The developed unit is able to reduce energy costs, increase its productivity and improve the environment [12–21].
3 Conclusions 1. The combination of passive and rotary working bodies in tillage devices will improve the quality of tillage with minimal energy consumption; 2. The precision tillage device can be used for pre-sowing continuous tillage or pre-sowing for crops with a long row spacing.
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3. Rollers are ring-toothed, less prone to clogging the surface with soil. And the use of rollers with different diameters makes it possible to intensify the impact on the surface layer. 4. Significant potential advantages of the universal working body of the combined unit for precision tillage creates the prerequisites and prospects for its wide application in order to increase the yield of cultivated crops, increase the productivity of tillage units, not only maintain, but also significantly increase soil fertility. Acknowledgments This work was carried out within the framework of the Presidential grant of the Russian Federation for state support of young Russian scientists (MK-1700.2021.5, agreement No. 075-15-2021-179).
References 1. Izmaylov AYu, Lobachevsky YP, Sizov, OA (2011) Resource and ecological processes and technical means in differentiated by year crop rotation system of soil treatment Collect Sci Pap VIM 1:54–62 2. Vanin DE, Krivitsky GN, et al (1979) About non-waste farming Agriculture 1:24–25 3. Lachuga Y, Akhalaya B, Shogenov Y, Meskhi B, Rudoy D, Olshevskaya A (2020) Energysaving tillage with a combined unit with universal working bodies. In: The collection of scientific papers of the IOP conference series: materials science and engineering. Cep. “international scientific and practical conference environmental risks and safety in mechanical engineering, ERSME 2020”, p 012121 4. Akhalaya BK, Shogenov YK (2017) Automated multifunctional tillage machine. Russ Agric Sci 6:55–58 5. Akhalaya BH, Shogenov YK (2017) Automated multifunctional tillage unit. Russ Agric Sci 6:55–58 6. Gattinger A, Jawtusch J, Muller A, Mäder P (2011) No-till agriculture – a climate smart solution? Published by: Bischö flichesHilfswerkMisereore.V. Mozartstraße 9, 52064 Aachen, Germany, p 24 7. Owenya M, Mariki W, Stewart A, Friedrich T, Kienzle J, Kassam A, Shetto R, Mkomwa S (2012) Conservation Agriculture and Sustainable Crop Intensification in Karatu District, Tanzania, Integrated Crop Management 15–2012. FAO, Rome, p 53 8. Izmailov AY, Lobachevsky YP, Akhalaya BK, Shogenov YK (2019) Patent RF №2679736. Tillage unit of alternative tillage 5, 12 Feb 2019 9. Izmailov AY, Lobachevsky YP, Akhalaya BK, Shogenov YK (2019) Patent RF №2679735. An aggregate for soil treatment with pulsating compressed air 5, 12 Feb 2019 10. Lobachevsky YP, Akhalaya BK, Starovoitov SI, Tsench YS (2019) Patent RF №2702863 IPC A01B 79/00. Precision tillage unit 11 Oct 2019 11. Lachuga Y, Akhalaya B, Shogenov Y, Meskhi B, Rudoy D, Olshevskaya A (2020) Innovative pneumatic device for combined seeding of various tilled crops. E3S Web Conf 210:08016 ITSE-2020. https://doi.org/10.1051/e3sconf/202021008016 12. Kambulov SI, Bozhko IV, Olshevskaya AV (2018) Calculation of the working element for layer-by-layer soil-free tillage. MATEC Web Conf 224:05022. https://doi.org/10.1051/matecc onf/201822405022 13. Altybayev A, Zhanbyrbayev A, Meskhi B, Rudoy D, Olshevskaya A, Prohorova A (2019) E3S Web Conf 135:01078. https://doi.org/10.1051/e3sconf/201913501078
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14. Meskhi B, Golev B, Efros V, Rudoy D, Olshevskaya A, Zhurba V, Chayka Y (2019) E3S Web Conf 135:01083 ITESE-2019. https://doi.org/10.1051/e3sconf/201913501083 15. Parkhomenko G, Kambulov S, Olshevskaya A, Babadzhanyan A, Gucheva N, Mekhantseva I (2019) IOP Conf Ser Earth Environ Sci 403:012144. https://doi.org/10.1088/1755-1315/403/ 1/012144 16. Milyutkin V, Buxmann V, Mozgovoy A, Rudoy D, Olshevskaya A (2022) Modern technology for cultivation of agricultural crops in zones of “risk farming” with conservation and accumulation of atmospheric moisture. In: Lecture notes in networks and systems book series (LNNS), vol 246, pp 138–146. https://doi.org/10.1007/978-3-030-81619-3_15 17. Kuren SG, Galchenko GA, Popov SI, Marchenko JuV, Dontsov NS, Drozdov DS (2020) Optimization of transport routes based on environmental indicators. In: VIII international scientific and practical conference «innovative technologies in science and education» (ITSE-2020): E3S Web of Conferences, vol 210, p 09005. https://doi.org/10.1051/e3sconf/202021009005 18. Kokieva GE, Ivanova M, Trofimova VS (2021) The study of reducing soil mechanical deformation in tilling. In: E3S web of conferences. XIV international scientific and practical conference “state and prospects for the development of agribusiness - INTERAGROMASH 2021”, Rostov-on-Don, p 05006 19. Panfilov IA, Soloviev AN, Matrosov AA, Meskhi BCh, Polushkin OO, Rudoy DV, Pakhomov VI (2020) Finite element simulation of airflow in a field cleaner. IOP Conf Ser Mater Sci Eng 1001:012060. https://doi.org/10.1088/1757-899X/1001/1/012060 20. Rudoy D, Egyan M, Kulikova N, Chigvintsev V (2021) Review and analysis of technologies for harvesting perennial grain crops. IOP Conf Ser Earth Environ Sci 937:022112. https://doi. org/10.1088/1755-1315/937/2/022112 21. Bozhko I, Parkhomenko G, Kambulov S, Boyko A, Kolodkin V, Magomedov M, Rudoy D (2020) Development and research of tillage operating device with polymeric materials. E3S Web Conf 175:05025. https://doi.org/10.1051/e3sconf/202017505025
Calculation and Optimization of Parameters of Standard Size Range of Unified Sections for Water Aluminum Radiators of Autotractor Engines Yekaterina Parluk
and Otari Didmanidze
Abstract The necessity of obtaining theoretical dependences of the thermal and aerodynamic qualities of the radiator on the geometric characteristics of its cooling surface is substantiated. A technique for estimating the heat transfer of the engine into the coolant and the heat transfer of the designed radiator is proposed. A technique for optimizing a finned surface for a section that is used in radiators of various machines is substantiated. In the real range of air mass velocities from 1 to 16 kg/m2 s, the dependences obtained by the optimization criterion make it possible to search for the maximum values of the complex (G) at any given value (γ Vl ) for various fin parameters. The developed method for calculating aluminum liquid radiators with a cassette or sectional assembly principle made it possible to construct an approximate standard size range of unified sections, on the basis of which a type of aluminum radiators for automotive engines can be built. The organization of the production of a size range of sections creates a new technical and economic basis for the introduction of the most economically feasible detailed specialization of production. At the same time, the organization of the production of a size range of aluminum sections will lead to savings in scarce metals: copper and tin, will allow the introduction of advanced and economic production methods, and will ensure maximum productivity and safe working conditions. Keywords Radiator · Heat exchanger · Cooling surface · Heat dissipation · Heat transfer
1 Introduction In connection with the successful development of the design of sectional-type aluminum radiators, the task of choosing the most advantageous geometric characteristic of their cooling surface seems to be very relevant [1–8]. Y. Parluk · O. Didmanidze (B) Russian State Agrarian University—Moscow Agricultural Academy named after K.A. Timiryazev, Timiryazevskaya Street, 49, 127422 Moscow, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_196
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2 Purpose of the Study Necessary condition is to obtain the theoretical dependences of the thermal and aerodynamic qualities of the radiator on the geometric characteristics of its cooling surface. The significance of such regularities is necessary for the design of any types of heat exchangers; it is all the more important when calculating the radiators of internal combustion engines in connection with the mass nature of their production and the various conditions of their operation [6]. At present, methods of preliminary theoretical calculations are practically not used for radiators used in ATTs.
3 Materials and Methods The geometric dimensions of the cooling surfaces and the dimensions of the core are usually chosen on the basis of available test data for similar radiators. In this case, it is often not taken into account that a change in the dimensions of the elements of the cooling surface does not ensure the reliability of the results obtained [9–15]. When designing radiators, as a rule, the calculation method does not take into account the type of cooling surface. In this connection, it is necessary to first estimate the heat transfer of the engine to the coolant (water) according to the formula: Q = 632 · a · Ne
kcal h
(1)
where a—coefficient, for carburetor engines (usually taken in the range from 0.6 to 1.2, i.e. fluctuating by 2 times); Ne —effective power of an internal combustion engine. The heat transfer of the designed radiator is proposed to be determined by the formula: Q=
tw − t L 1 K∗SL
+
1 2C pL ∗G L
+
1 2G w
(2)
where tw —water temperature in the radiator; t L —air temperature in front of the radiator; SL —radiator airflow cooling surface; C pL —specific heat capacity at constant air pressure; G w —water flow through the radiator [7]. In formula (2), an unknown value that cannot be calculated analytically is the value of the heat transfer coefficient K. Therefore, for a new radiator, one has to take the geometry of the cooling surface that repeats the geometry of the prototype, or estimate the value of K conditionally. The result of this calculation is the determination of the dimensions of the frontal part of the designed radiator and the process of its fine-tuning in relation to the ATT.
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When creating standard-size series of unified heat exchangers for tractor and combine engines, the most important place is occupied by determining the amount of heat transferred by the engine to the liquid cooling system [8, 9].
4 Results and Discussions Evaluation of the quality of aluminum water radiators from sections with different finning parameters is a difficult task and should be carried out based on taking into account a large number of indicators characterizing the radiator. Based on the relationship of various indicators characterizing the radiator as a whole, given in [1], it is possible to single out the main parameters characterizing the section. These parameters are: d e —equivalent air channel diameter; ψ—ribbing factor; ϕ—bulk compactness factor; β—air area coefficient; l1 /d7 —relative blade length [2]. Optimization of a finned surface for a section that is used in radiators of various machines should proceed, first of all, from the possibility of obtaining its minimum mass [3]. From the energy point of view and from the point of view of reducing the mass of the radiator core, let us agree to characterize the perfection of the cooling surface by the heat transfer ratio of the radiator Q P H , reduced to the unit of the initial temperature difference tst = 1K , to aerodynamic drag Pl and to the total mass of the radiator core G m , i.e. complex (G): G=
QPH Pl ∗ G m
(3)
Obviously, the higher the value of this ratio for a radiator with the same front value, the more efficient, in terms of energy costs and reduction in the mass of the radiator core, the cooling surface [10, 11]. It follows from the foregoing that the selected complex (G) as an objective function in solving the problem of optimizing the surface of the finning, allows you to find the best parameters of the ribbed section. Complex G can be represented in the following form: G = C0 ∗
1 (γ Vl )n−m ∗ vmq GM
(4)
where C0 —const; γ Vl − mass air velocity; n, m, q− characteristic values for the thermal and aerodynamic properties of the radiator cooling surface; vm − water speed. Analysis of formula (4) makes it possible to judge the nature of the complex (G) depending on the mass air velocity for a constant value of the coolant velocity (vm = 1 m/s) for different values of the finning parameters. At the same time, the exponent n − m in the experimentally substantiated range of variation of the finning parameters, it changes within one percent, and, therefore, in the real range
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of air mass velocities from 1 to 16 kg/m2 s, the obtained dependences according to the optimization criterion (Gi ) does not intersect in the logarithmic anamorphosis, which allows you to search for the maximum values of the complex (G) for any given value (γ Vl ) for various fin parameters [15]. Thus, the formulation of the problem of finding the optimal dimensions of the finning parameters when developing a standard-size series of sections is reduced to finding the maximum of the complex (G) under the restrictions: f in
d st ≤ de ≤ de ; f in est l1 ≤ dl17 ≤ dl17 d7 f in and (γ Vl ) L ∈ (γ Vl )stL ; (γ Vl ) L ;
(5)
vm ∈ vmst ; vmf in
(6)
The developed method for calculating aluminum liquid radiators with a cassette or sectional assembly principle made it possible to construct an approximate standard size range of unified sections, on the basis of which a type of aluminum radiators for automotive engines can be built. At the same time, it was assumed that several standard sizes of unified sections should be created, each of which is intended for radiators of a number of similar machines with similar heat removal values [12, 13]. The organization of the production of a size range of sections creates a new technical and economic basis for the introduction of the most economically feasible detailed specialization of production. At the same time, the organization of the production of a size range of aluminum sections will lead to savings in scarce metals: copper and tin, will allow the introduction of advanced and economic production methods, and will ensure maximum productivity and safe working conditions. The created size range of aluminum sections is based on the following principles [4]: 1. it is possible to fully satisfy the needs of the industry in aluminum radiators in the presence of a minimum number of standard sizes of unified sections.; 2. taking into account the experience of domestic science and industry, as well as the operation of machines in various climatic conditions of the Russian Federation; 3. taking into account the prospects for the development of related industries, and in the first place, mining, metallurgical and chemical; 4. ensuring high quality indicators of created radiators, as well as potential opportunities for improving their performance. Each of the radiators included in the type must ensure the removal of heat generated by the engine, and have overall dimensions and attach fittings that allow it to be installed on existing and future machines [5, 14]. According to the studies presented in [1], a diagram of an approximate size range of water aluminum radiator sections for automotive equipment was presented. The scheme is based on experimental studies. To clarify and justify the thermal parameters
Calculation and Optimization of Parameters of Standard Size Range …
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of modern radiators, two options for the size range of sections of cooling surfaces were calculated. An example of such a calculation is shown in Table 1. Table 2 shows the main geometric parameters of aluminum sections that make up the standard size range. Table 1 An example of calculating the parameters of ribbed sections I and II of standard size and a radiator based on them, obtained on a computer Parameters
Design options for sections and radiators I type/size
II type/size
Rib height, m
0.009
0.009
Fin pitch, m
0.0035
0.0035
Average rib thickness, m
0.00045
0.00045
Petal width, m
0.0046
0.0062
Opening width between petals, m
0.0005
0.0005
Wall thickness of the carrier pipe, m
0.00065
0.00065
Water channel height, m
0.002
0.002
Core height, m
0.55
0.64
Core width, m
0.45
0.6
Useful core depth, m
0.055
0.06
Number of sections, pcs
20
26
surface,m2
0.24
0.37
Air cooling surface,m2
7.35
12.03
Water cooling surface,m2
1.28
2.14
0.00275
0.0054
Front
Clear area in
water,m2
Mass air velocity, kg/m2 s
5.4
9.2
Section water speed, m/s
0.73
0.77
Heat transfer coefficient, W/m2 k
95
132
Heat transfer reduced to 60 K, kW
45.8
78.4
Aerodynamic drag, Pa
60
106
Core weight, kg
6.2
8.03
Table 2 Standardized range of unified aluminum sections for water radiators of tractor engines Parameters
Size number of unified aluminum sections I
II
III
IV
Section length, L, mm
550
640
760
850
Section width (depth), l, mm
55
55
92
128
Fin pitch, t, mm
3.5
3.5
3.5
3.5
Rib height, h, mm
9
9
9
9
Average fin thickness, δ, mm
0.45
0.45
0.5
0.5
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Y. Parluk and O. Didmanidze
5 Conclusions Sections of size I are designed for tractor radiators of class 14 and 30 kN, with engine power from 35 to 80 kW and heat transfer to water from 30 to 40 kW. Sections of size II are designed for tractor radiators of class 30 kN with an engine power of 70–150 kW and heat transfer to water of 55–80 kW. Sections III and IV of sizes are designed for tractors of class 50 kN and more with an engine power of 140 kW and above, with heat transfer to water for section IV of size 75–110 kW, and for section III of size 100 kW and above.
References 1. Delavar MA (2013) I using porous material for heat transfer enhancement in heat exchangers: review. J Eng Sci Technol Rev 6(1):14–16 2. Menon AC (2013) Experimental study of heat transfer through porous media during the application of radial heat flux condition. Int J Emerg Technol Adv Eng 3(10):81–84 3. Konovalov DA (2017) Analytical solution of hydrodynamics and heat exchange problem in a porous rectangular channel for thermal boundary conditions of the second kind PTPPE-2017. IOP Conf Ser J Phys Conf Ser 891:012103 4. Drelich R (2014) Identification of drag parameters of flow in high permeability materials by u-tube method. Transp Porous Med 101:69–79 5. Didmanidze ON (2021) Tribo-characteristics of promising cutting fluids for metal cutting. In: 2021 Systems of signals generating and processing in the field of on-board communications, conference proceedings, Moscow, 16–18 March 2021, p 9416068. https://doi.org/10.1109/IEE ECONF51389.2021.9416068 6. Khakimov R, Didmanidze O, Parlyuk E (2021) Improving the supply system gas engine to improve energy efficiency. In: MATEC web of conferences: the VI international scientific and practical conference “information technologies and management of transport systems” (ITMTS 2020), 19–20 May 2020. Orel: EDP Sciences, p 02016. https://doi.org/10.1051/matecconf/202 133402016 7. Parlyuk EP (2021) Mathematical efficiency model of the block-module cooling system of automotive vehicles and tractors. In: IOP conference series: earth and environmental science, Krasnoyarsk, 16–19 June 2021 Krasnoyarsk Science and Technology City Hall of the Russian Union of Scientific and Engineering. Krasnoyarsk: IOP Publishing Ltd, p 52061. https://doi. org/10.1088/1755-1315/839/5/052061 8. Bolshakov NA (2020) Modernization of the cooling system in tractors with gas engines. In: E3S Web of conferences, Moscow, 25–27 November 2020, p 04048. https://doi.org/10.1051/ e3sconf/202022404048 9. Didmanidze ON, Dorokhov AS, Sibirev AV (2021) The results of studies of specific energy intensity of the basin formation process of the onion harvester. In: IOP conference series: earth and environmental science: mechanization, engineering, technology, innovation and digital technologies in agriculture series 3, Smolensk, 25 January Smolensk. IOP publishing ltd, p 032109. https://doi.org/10.1088/1755-1315/723/3/032109 10. (2020) International conference on digital solutions for automotive industry, roadway maintenance and traffic control (DS ART 2020), 14–16 December 2020 Moscow: Institute of Physics and IOP Publishing Limited, p 815 11. Yerokhin MN, Didmanidze ON, Aldoshin N, Khakimov RT (2019) The combustion process and heat release in the gas engine. In: TAE 2019 – proceeding of 7th international conference on trends in agricultural engineering, Czech University of Life Sciences Prague, pp 607–611
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12. Didmanidze ON (2019) The non-stationary process of heat-mass exchange of liquefied methane in a cryogenic fuel tank of automotive and tractor equipment. In: IOP conference series: earth and environmental science, Russky Island, 04–06 March 2019. Institute of Physics Publishing, Russky Island, p 022239. https://doi.org/10.1088/1755-1315/272/2/022239 13. Gaidar SM, Karelina MY, Ershov VS, Quang HD (2021) Production of effective water-soluble corrosion inhibitors based on amino alcohols. Russ Eng Res 41(6):558–560. https://doi.org/ 10.3103/S1068798X21060071 14. Gaidar S, Karelina M, Laguzin A, Quang HD (2020) Impact of operational factors on environmental safety of internal combustion engines. Transp Res Procedia 14:136–144. https://doi. org/10.1016/j.trpro.2020.10.017 15. Didmanidze ON (2021) Heat and mass transfer of multicomponent gas mixtures in cryogenic tank of automotive. J Phys Conf Ser 012024. https://doi.org/10.1088/1742-6596/2061/ 1/012024
Effective Options for Strengthening Reinforced Concrete Compressed Columns in Terms of Technical and Economic Indicators Sergey Georgiev , Dmitry Mailian , and Valerii Chubarov
Abstract The choice of strengthening options for reinforced concrete structures is based on a large number of factors taking into consideration technical capabilities and economic efficiency. Modern construction requires new methods of reinforcement which reduce labor costs and time expenditure, while maintaining the aesthetic appearance of the building being constructed or restored. The stumbling point is the cost and the reliability of the new reinforcement methods. To this end, the best known reinforcement methods based on materials such as reinforced concrete and metal have been compared with fairly new methods based on composite materials. In making the technical and economic comparison, only the cost of the materials required for the reinforcement was taken into account. The cost of the work, the delivery of the materials, the cost of renting or purchasing the necessary equipment, etc. is beyond the scope of this research due to the huge number of factors that make it difficult to set final value. The materials of the study are the results of calculations of the materials volume for the production of a reinforced concrete centrally-compressed column with the most common characteristics. Keywords Concrete · Transport infrastructure · Reinforced concrete · Composite material · Carbon fiber reinforcement · External reinforcement · Deformations · Compressed elements
1 Introduction As the experience of construction practice shows, the most popular technologies of construction of residential and public buildings are monolithic prefabricated buildings. Modern technology allows designing and constructing buildings with beamless ceilings supported by reinforced concrete columns [1]. This solution makes it possible to fully implement new architectural ideas and to re-plan the interiors by shifting the partition walls at customer’s option. S. Georgiev · D. Mailian (B) · V. Chubarov Don State Technical University, 1 Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_197
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Due to imperfect concreting technology, the technology of monolithic construction often carries the risk of lowering the strength of concrete in structures [2]. This is linked with the influence of external factors such as concreting in a hot climate [3] or, conversely, negative temperatures [4], challenges of concrete delivery to the formwork [5], the quality of its vibration [6], etc. Human factor, connected with builders’ mistakes, is common. All this leads to deviations from the design and, as a result of the survey conclusions, leads to the need to replace or reinforce the structures. This is the case with bending and compressed elements, such as the girder slab and columns. Experience has shown that in bendable elements, namely in beamless slabs [7, 8], the compressed zone of concrete usually has a safety margin, so the most common solution is to reinforce the stretched zone, which is successfully achieved by bonding composite lamellas. As for compressed reinforced concrete columns, where concrete absorbs 70– 80% of the total load, understating the strength of concrete significantly reduces the strength of the structures. Most of the columns of monolithic buildings with girder less slabs have less than three meters long, operate in central compression or with small eccentricities of load application, have rigid embedding in the slab, hence the calculated length of the columns is reduced by half. All this leads to the conclusion that the effect of flexibility on the reduction of load-carrying capacity of structures is insignificant and the strength of a structure is defined as the joint resistance of concrete and reinforcement of the structure to axial compression [9]. Among the known reinforcement methods, the traditional methods based on the use of reinforced concrete and metal are considered the most popular [10]. Of the new methods composite reinforcement has recently gained popularity [11–13]. Each method has its own advantages and disadvantages, so to partly determine them is the purpose of this research. The main objective of the research is to determine the most effective method of strengthening compressed reinforced concrete structures in terms of technical and economic indicators. In this case, the technical and economic indicators are characterized by the amount of reinforcement materials used, their cost, the degree of material overspending, which is a consequence of design requirements, and the limits of all the methods under consideration. Based on the results obtained, to develop proposals for improving the method of composite reinforcement in order to increase efficiency and, consequently, to reduce the volume of reinforcement materials used.
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2 Materials and Methods A column, 3 m long, 40 × 40 cm cross-section and 4Ø25A500 internal reinforcement was taken as the materials studying. This column was reinforced using three methods at 10 different reinforcement ratios, ranging from a ratio of 1.1 to 2.0, with a step of 0.1. This number of coefficients was taken to get a complete picture of the research, to identify the most rational ways of strengthening all three methods, their positive and negative sides and the possible limits of increasing the strength of the column for each method. The cost of materials was taken as per the websites of the companies selling the materials. Concrete—“Beton YUG”, reinforcement—“MetTrans Terminal”, composite materials—“Hydrozo” OOO. As external composite reinforcement, carbon fiber was used, which was glued in the transverse direction and acted as a cage. The number of layers was selected according to the calculated cross-sectional area of the reinforcement materials. Three types of carbon fabrics from the available material were used: Armochel (KB 200, KB500 and KB900) with a carbon fabric thickness of 0.11; 0.27 and 0.48 mm, respectively. As an adhesive backing Monopox 183 and 372 were used, the latter was applied for the Armochel KB900 carbon fabric. Considering the huge number of calculations and further work with normative formulas, the examples of column reinforcement calculations using three methods at a reinforcement factor of 1.5, according to the current normative document SP 164.1325800.2014 «Reinforcement of reinforced concrete structures with composite materials», are shown below.
3 Research Results In order to obtain data on the volumes of reinforcement materials, calculation methods were developed in the Excel software package. The results are shown in Table 1. Notes to Table 1: 1. Line 1 shows the calculation results of reinforcement with concrete cage. For all strengthening coefficients the same reinforcement was taken as approximately 1–1.5% of the area of the concreted footing. The d-value refers to the thickness of the concreted footing. 2. In line 6, strips with a cross-section of 80 × 8 mm were taken as connection strips. For all reinforcement coefficients four angles were used, the cross-sectional dimension of which was determined by calculation. 3. In line 10, the calculation result was the number of collar layers and the thickness of the carbon fabric materials, t. 4. The lines 2, 3, 6, 8, 11 and 12 are the calculation results of the materials volume and corresponding reinforcing methods and their cost per column. The prices are taken in accordance with the price lists of firms selling
4Ø20A500 d = 6 cm
12/30
36/8
0.33
Concrete cage
Ø20A500, lin.m./kg
Ø6A240, lin.m./kg
Concrete, m3
12
11
Angle, L , lin.m
Strip, -, lin.m
11.5
Adhesive, kg
10
10.5
Carbon fiber, m2
Adhesive, kg
11,550
31,200
2 layer t = 0.11 mm
59,150
12,650
Composite cage rounded Sect. (1)
Cost, r
10
Carbon fiber, m2 46,500
2 layer t = 0.27 mm
7038
2838
4200
2800
1386r
145.6r
546r
Composite cage
Cost, r
4L 75 × 6 −80 × 8
Metal cage
Cost, r
1.2
Strengthening method
Table 1 Results of calculations of volumes of materials
11
12
0.33
36/8
12/30
28.75
15
5775
23,250 17.25
15
3 layer t = 0.11 mm
88,725
18,975
69,750
5 layer t = 0.27 mm
8298
2838
5460
4L 100 × 7 −80 × 8
2800
1386r
145.6r
546r
4Ø20A500 d = 6 cm
1.4
11,550
46,500
1 layer t = 0.48 mm
177,560
38,060
139,500
5 layer t = 0.48 mm
11,298
2838
8460
4L 140 × 9 −80 × 8
2800
1386r
145.6r
546r
4Ø20A500 d = 6 cm
1.6
5.25
5
25
25
11
12
0.33
36/8
12/30
2623
1932r
145.6r
546r
12,924 15,762
2838
332,500
38,500
294,000
17.25
15
19,000
69,750
3 layer t = 0.27 mm
35
35
7 layer t = 0.48 mm
11
12
4L 160 × 10 −80 × 8
0.46
36/8
12/30
4Ø20A500 d = 8 cm
1.8
2920
2226r
145.6r
546r
19,644 22,482
2838
427,500
49,500
378,000
17.25
15
(continued)
19,000
69,750
3 layer t = 0.27 mm
45
45
9 layer t = 0.48 mm
11
12
4L 180 × 11 −80 × 8
0.53
36/8
12/30
4Ø20A500 d = 9 cm
2.0
1916 S. Georgiev et al.
Adhesive, kg
5.25
Adhesive, kg
Cost, r
5
Carbon fiber, m2 21,375
5775
15,600
1 layer t = 0.11 mm
29,025
5775
Composite cage rounded Sect. (2)
Cost, r
5
5.25
Carbon fiber, m2 23,250
1 layer t = 0.27 mm
21,375
5775
Composite cage rounded Sect. (1)
Cost, r
Adhesive, kg
15,600
5
5.25
Carbon fiber, m2
42,750
1 layer t = 0.11 mm
1.2
Composite cage rounded Sect. (2)
Cost, r
Strengthening method
Table 1 (continued)
5 5.25
5 5.25
21,375
5775
15,600 5.25
5
1 layer t = 0.11 mm
29,025
5775
23,250
1 layer t = 0.48 mm
21,375
5775
15,600
1 layer t = 0.11 mm
29,025
1.4
29,025
5775
23,250
1 layer t = 0.27 mm
47,775
5775
42,000
1 layer t = 0.48 mm
42,750
11,550
31,200
1 layer t = 0.27 mm
58,050
1.6
5
5.25
5
5.25
5
5.25
88,750
46,500 58,050
11,550
69,750 88,750
19,000
5.25
5
47,775
5775
42,000
1 layer t = 0.48 mm
17.25
15
3 layer t = 0.27 mm
10.5
10
2 layer t = 0.27 mm
1.8 88,750
42,000 47,775
5775
69,750 88,750
19,000
5.25
5
47,775
5775
42,000
1 layer t = 0.48 mm
17.25
15
3 layer t = 0.27 mm
5.25
5
1 layer t = 0.48 mm
2.0
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building materials as of December 18, 2021. 5. Lines 5, 9 and 13 show the calculation results of the materials cost for reinforcing a column with appropriate reinforcement coefficients
4 Discussion The analysis of reinforcement methods was carried out without taking into account the cost of reinforcement works, delivery of materials, the cost of renting or purchasing the necessary equipment, etc., due to the huge number of factors that affect the final cost. Such a comparison should be made concerning specific items of reinforcement but not methods in general. The following is an analysis of the results obtained, in terms of the technical and economic performance of each method separately. For the reinforced concrete cage method with reinforcement factors of 1.1 to 1.6 the design variant with a thickness of 6 cm is used. With higher reinforcement coefficients, the thickness of the slab increases from 6 to 9 cm. Given the rather low cost of concrete, this method is the most efficient in terms of material costs. The cost of materials ranged from 2,800 to 2,920 rubles. The metal cage, where the main load-bearing capacity from the additional load was taken up by the angles, at all reinforcement ratios, made it possible to accept materials without overspending. The cost of materials increased in proportion to the increase of the reinforcement. Material prices were taken from the MetTrans Terminal website. The cost of reinforcement materials varied from 4362 to 22,482 rubles at coefficients of 1.1 to 2 respectively. The results of material volume and cost calculations for the composite collar reinforcement method showed the highest cost. The prices of materials were based on information received from representatives of the company “Hydrozo” OOO. Cost of materials for reinforcement of one column varied from 43,850 to 427500r, with reinforcement coefficients from 1.1 to 2 respectively. The analysis of the calculation results showed that the most expensive method of reinforcement, in terms of construction material costs, is the composite cladding. This can be clearly seen in the graphs (Fig. 1), which compare the cost of reinforcement materials in relation to the reinforcement factor for the 3 methods based on reinforced concrete, metal and composites. From the analysis it can be concluded that in the area of reinforcement of conventionally centrally compressed columns with a square cross-section, in terms of material costs, it is not appropriate to use the composite method of reinforcement. The cost of composite materials is significantly higher than metal and concrete; therefore, other factors aside, composite reinforcement is not competitive or requires improvement of the technology and methodology of reinforcement, which is the main objective of this research.
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Fig. 1 Graphs comparing the material cost of the 3 reinforcement methods at 10 reinforcement ratios. Herewith: 3. Reinforcement with reinforced concrete cage. 4. Reinforcement with metal cage. 5. Composite reinforcement with a cage
Analyzing formulas of design methodology for composite reinforcement of compressed elements, it was concluded that there are a number of reduction factors which significantly reduce the strength gain of the reinforcement system and, accordingly, increase the consumption of composite carbon fiber. The main reduction factor which reduces the efficiency of composite reinforcement by 81% is the kef factor (1). The value of this factor depends on the crosssectional dimensions of the reinforced element, the cross-sectional configuration and the angle radius of rectangular and square cross-sections of the structures. For the calculated column, the factor kef = 0.19, and if the column were of circular cross-section this factor would be equal to one. The authors of this paper have developed patents for inventions and utility models to give the column a circular cross-section. It is proposed to use these patents to develop an alternative method of reinforcement which uses the combined work of mortar or concrete rounding and a composite material covering the given concrete footing. The new method of reinforcement will eliminate the use of a metal frame, which is included in the reinforcement system of the concrete cage, and will also eliminate the use of external formwork and therefore the complicated concreting process. To determine economic efficiency of the developed new method of reinforcement, two examples of column calculations are given below: the first one—without taking into account work of rounding in compression, the second one, on the contrary, takes into account rounding in work of the whole column, equally with concrete structure, while the factor kef is also equal to unit, but the area of reinforced structure is calculated taking into account full section, that is column section with taking into account rounding elements. The results of composite reinforcement calculation considering the authors’ suggestions are given in Table 1, lines 13–21.
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Fig. 2 Graphs comparing three reinforcement options in terms of reinforcement factor and cost of work namely: 1. Composite reinforcement taking into account the authors’ suggestions for rounding the edges of the reinforced structure, while taking into account the strength of the rounding. 2. Composite reinforcement taking into account the authors’ suggestions without taking into account the effect of rounding. 3. Classic composite reinforcement in the form of a cage of reinforced element
Table 1 show the results of the composite cladding selection, which was based on the concept of minimum over-reinforcement. However, in some cases the lower the number of layers, the cheaper the reinforcement. This is due to the fact that there is no direct correlation between the material cost and the cross-sectional area of the carbon fiber and there is no additional cost for the adhesive backing. For example for a reinforcement factor of 1.2 it is reasonable to use for the first calculation one layer of 0.27 mm thick carbon fiber instead of two layers of 0.11 mm (see lines 14 and 22 in Table 1). The results of selecting composite reinforcements and calculating their cost, which was oriented on the minimum cost of the materials and not on the percentage of pre-reinforcement, are given in lines 22–29 in Table 1. The graphs below show the effect of the reinforcement factor on the cost of materials. According to Fig. 2, it can be concluded that with the authors’ suggestions for improving the amplification methodology, the cost of material is significantly reduced, without loss of efficiency. Figure 3 shows graph “cost of materials—reinforcement factor” allowing comparing the cost of composite reinforcement materials, according to the methodology proposed by the authors, with the traditional methods. In this case the increase in cost becomes not so striking in comparison with traditional methods and, all other conditions being equal, composite reinforcement becomes quite competitive in comparison with traditional options.
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Fig. 3 Graphs comparing the efficiency of the 4 reinforcement methods according to reinforcement factor and material costs. Namely: 1. Composite reinforcement taking into account the authors’ suggestions for rounding the edges of the reinforced structure, while taking into account the strength of the rounding. 2. Composite reinforcement taking into account the authors’ suggestions without taking into account the effect of rounding. 3. Reinforcement with reinforced concrete cage. 4. Reinforcement with a metal cage
5 Conclusion The following conclusions can be drawn as a result of this research: – According to the results of the comparison of the three reinforcement options calculated according to the standard methods, it was concluded that the most economical option was the use of reinforced concrete cage. Metal cage was one order more expensive but composite cage is 15 times more expensive than metal cage. These comparisons were made according to value of materials without taking into account the cost of work and the additional costs associated with the peculiarities of each method of reinforcement. – In the light of the suggestions developed by the authors of this article, it was possible to reduce the cost of composite reinforcement materials by 5–10 times, depending on the reinforcement factor. – Despite the cheapening of composite reinforcement with the improvement of the methodology proposed by the authors, traditional reinforcement options are still more economical. Considering that composites are rather new, innovative materials in most cases made abroad, its cost in Russia is rather high. Hence, the development of own technologies for the production of composite materials which will essentially reduce the cost of composite reinforcement takes the place.
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References 1. Phai P (2015) Effectiveness of reinforced concrete monolithic beamless slabs in the construction of frame civil buildings. In: International scientific and technical conference of young scientists of V.G. Shukhov Belarusian state technical university. Belgorod State Technological University. V.G. Shukhov, pp 2485–2489 2. Popov RA (2020) Economic and technological problems and prospects of prefabricated monolithic house building. In: Development and innovation in construction. Proceedings of the III international scientific and practical conference, pp 166–173 3. Baskakov KO (2020) Features of concreting during construction of high-rise buildings in dry hot climate conditions. Student 3(5):425–431 4. Chernova AR, Pyzhyanova DV, Terekhov IG (2016) Concreting in conditions of negative temperatures. In: Actual problems of technical, natural sciences and humanities. Proceedings of the international scientific and technical conference in memory of V.Kh., pp 148–150 5. Solodkova EV (2021) Features of transportation of commercial concrete in the Russian Federation. In: Almanac of scientific works of young scientists of ITMO University. Proceedings of the fiftieth scientific and educational - methodical conference, St. Petersburg, pp 210–213 6. Maksimovich SV (2020) Factors influencing the strength of concrete of monolithic structures. In: Dmitrieva MA (ed) Modern building materials and technologies. Collection of scientific papers of II international conference, pp 47–63 7. Spirin AS (2021) Methods of strengthening of monolithic beamless slabs. In: Days of student science. Collection of reports of the scientific-technical conference on the results of research works of students of the Institute of Construction and Architecture of Moscow State University of Civil Engineering. Moscow, pp 335–337 8. Nemcev, IA (2013) Primenenie ugleplastikov dlya usileniya stroitel’nyh konstrukcij. In: Nauka i molodezh’: problemy, poiski, resheniya: trudy Vserossijskoj nauchnoj konferencii studentov, aspirantov i molodyh uchenyh, Novokuzneck, pp 57–60 9. Kulebyakin IN, Toroshchin AS (2017) Rehabilitation of monolithic columns in framework buildings. In: Society, science, innovations (NPK-2017). colleCTion of articles. All-Russian annual scientific-practical conference. Vyatka State University, pp 1385–1389 10. Mulenkova VI, Artyushin DV (2014) Calculation and design of reinforced concrete and stone structures reinforcement. PGUAS Publishing House, Penza 11. Polskoy P, Georgiev S, Muradyan V, Shilov A (2018) The deformability of short pillars in various loading options and external composite reinforcement. MATEC Web Conf 02026 12. Mukhamediev TA (2013) Design of reinforcement of reinforced concrete structures by composite materials. Conc Reinforced Conc 3:6–8 13. Georgiev S, Mailyan D, Blyagoz A (2021) Proposals for determining the relative deformations design value of εb3 concrete in volumetric deformation conditions. Mater Sci Forum 1043:155– 162
Effective Options for Composite Strengthening of Eccentric-Compressed Reinforced Concrete Poles with Small Eccentricities of Load Application Petr Polsky , Sergey Georgiev , and Dmitry Mailian
Abstract A large volume of reinforced concrete non-centrally compressed structures cannot be strengthening with composite materials, due to the introduction of restrictions imposed by regulatory documents. This situation is due to the insufficient volume of scientific research in Russia. In this regard, research work was carried out to determine the effectiveness of composite materials of flexible non-centrally compressed reinforced concrete structures. The paper presents the following results. The paper deals with the results of experimental studies of strength and deformability of reinforced concrete eccentric-compressed poles strengthen with different variants of composite materials. The graphs of changes in the relative deformations of composite materials in the most characteristic zones are given in order to determine the most stressed areas. The results of experimental investigations were analyzed and recommendations on strengthening of eccentric-compressed reinforced concrete structures with composite materials operating with a small eccentricity of load application were worked out. New, previously unstudied ways of strengthening eccentric-compressed structures have been developed. Keywords Concrete · Reinforced concrete · Transport infrastructure · Compressed elements · Flexibility · Eccentricity
1 Introduction In modern construction, reinforced concrete is the most widely used material for load-bearing elements of buildings and structures [1]. Concrete is a relatively cheap material and its insufficient tensile strength is compensated by metal reinforcement [2, 3]. In turn, concrete protects the reinforcement from corrosion ensuring reliability and durability of structures [4]. Carbon fiber composite reinforcement along with metal one has recently been confidently used [5–7]. P. Polsky · S. Georgiev · D. Mailian (B) Don State Technical University, 1 Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_198
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Due to the high cost and the lack of ability to provide a reliable bond with concrete [8], composite reinforcement is not practically used in the manufacture of new structures. However, once the question arises reinforcing old structures, composite reinforcement methods [9] are quite viable compared to traditional ones. Most reinforced concrete elements operate eccentrically. Their distinctive feature is the uneven distribution of stresses in the concrete cross-section. In total, three cases of structural work can be distinguished according to the calculated loading diagrams: 1. Conditionally central-compressed or operating with random eccentricity of load application, where the entire cross-section of the element is compressed, however, the most and least compressed zones are observed. 2. Structures working with low eccentricity of load application, whereby the point of load application does not extend beyond the core of the cross-section. When subjected to this type of loading a compressed and a weakly stretched zone is distinguished. 3. Structures operating with large eccentricity of load application and compressed elements with great flexibility. In this type of loading, the working cross-section of the structure has a compressed and stretched face, and the strength calculation is carried out in accordance with the beam scheme. Depending on the nature of the structure and the eccentricity of the load application, a suitable method of reinforcement is adopted [10–12]. The current Set of Rules for Strengthening Reinforced Concrete Structures with Composite Materials SP 164.1325800.2014 relies on a number of scientific studies implying two options for reinforcing eccentric-compressed structures [13, 14]. The first method is based on the containment of concrete deformations by means of capping, i.e. the composite material is placed in the transverse direction. This method of reinforcement is well suited for central-compressed structures or those operating with low eccentricity of load application. The second method of reinforcement is based on gluing of composite materials on the tensile area of an eccentric-compressed structure in the longitudinal direction. This method of reinforcement is particularly effective in structures with high eccentricity of load application and with ease flexibility of the specimen to be reinforced. There are no recommendations for strengthening of eccentric-compressed structures operating in the second case, i.e. the case of small eccentricities of load application, in the standards. However, knowing the specifics of such structures, gluing longitudinally arranged composites to the weakly stretched area will not be effective. As for the application of the composite cladding in the transverse direction, the normative document imposes restrictions related to the limit eccentricity of the load application, not exceeding 0.1 h. This state of affairs, excludes the possibility of using new innovative composite materials when reinforcing the entire range of reinforced concrete structures.
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2 Materials and Methods Reinforced concrete poles with dimensions 1200 × 125(h) × 250 mm were taken as test specimens. Design concrete class was B35, internal reinforcement consisted of four 12 A500 bars. The transverse reinforcement was installed in 180 mm increments, 6 mm diameter B500. Reinforcement grids were installed in the supported areas to prevent concrete deformation. The specimens were tested with incremental load step of 10% from the breaking load at eccentricity e0 = 2 cm (0.16 h). At each step there was a 10-min exposure time, during which tensometers attached to the composites were registered. Tensometers were glued on each specimen at the most important areas of the external composite reinforcement. The length of the tensometers was 2 cm and the change in relative deformation was determined to an accuracy of 0.01 mm. In addition to the reinforced specimens, a standard pole was tested to compare and determine the effectiveness of the composite reinforcement. A total of 6 prototypes were tested, the descriptions of which are given below. Specimen code: B—indicates that the specimens were tested at eccentricity e0 = 2 cm (0.16 h); K—had a length of 1200 mm; Y—reinforced with composite materials; X—there is the presence of transverse reinforcement in the form of composite clamps; the digits 1, 2, 5 in the letter X indicate the pitch of composite clamps, namely 190 mm, 130 mm and 0 respectively; L—indicates the presence of longitudinal reinforcement consisting of two or four lamellas; the p, c in the letter L indicates that the lamellas are in a stretched or compressed area.
3 Research Results According to indicators of tensometers located in compression zone (T-12, T-13, T-14), change of relative deformations in composite clamps develops according to three linear dependences for different loading levels. From an initial loading level of 10% from the breaking load (Nult ) to a loading level equal to 500kN, or 64% Nult . The change in relative deformation develops according to linear relationship N = 47−1129ε. The minus sign obtained in the relative deflections calculations indicates tensile strains. When the structure is loaded from 500 to 660kH (85%Nult), the tangent to the curve changes and the pattern of development of relative deformations in relation to the force is distributed by another linear dependence N = 438−256ε. From the load level of 660 kH to the destructive load (Nult), the tangential curve changes its slope angle and the deformation develops according to the 3rd linear dependence N = 628−70ε. The fracture zone is located between the two central clamps to which tensometers T-12 and T-13 are glued. The changes in their deformations when loading the structure are almost identical and the maximum values reach 1.73*10-3. For the clamp located
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below, on which tensometers T-14 is glued, the character of changes of relative deformations develops according to similar dependences, but at loading level of 90% of breaking load, relative deformations reach the lower value, equal to 1,2*10−3 . The deformations in composite clamps are significantly lower in the lateral edge than in the compressed zone of concrete. The character of relative deformations development is determined by linear dependence N = 129−2447ε up to fracture of experimental specimen. The maximum deflection values are 4 times lower than in the compressed concrete zone. Tensometers located in the tensile zone of T-11 and T-12 up to the load level of 600 kH, which is approximately 80% of the fracture load, showed zero deformations. With increasing load, up to the fracture of the standard specimen, the composite material worked in compression, i.e. positive values of relative deformations were recorded, which is not at all logical, since the composite material should work in tension while restraining the transverse deformations of concrete. This indicates that the composite material is not working in the tensile zone. BKY-X2—Reinforced concrete pole strengthened transversely with composite clamps with 90–95 mm clear spacing. The pattern of development of relative deformations in the composite clamps with increasing load level is very similar to the previous pole. It is worth noting that the last tensometers’ readings were measured at a load level of 700 kN, which is 88% of N ult. In the compressed zone of the concrete, 5 tensometers were installed on all clamps. The development of relative strains at a load level of 500 kN, which is 63% of N ult had an almost identical pattern at all clamps. At higher load levels, according to tensometers T-13 and T-14, deformation in composite materials was greater than in the other clamps. Visual inspection of the structures after the experiment showed that the fracture zone was located between these load cells. The nature of the development of relative strains in the composite clamps in relation to the external force, up to a load level of 88% of N ult, is determined according to a linear function N = 103–798ε. Similar to the previous post, 2 tensometers glued in the tensile zone of the specimen showed compressive stresses, which confirms that the composite clamps are not stressed in the tensile zone. The gain compared to the reference sample was kys = 1.34. BKY-X5—pole reinforced with a composite cage in three layers of carbon fabric. According to the diagram of tensometers arrangement T1-T5 are located in the compressed zone, T6-T10 in the tensile zone and T11-T15 on the post edge. All sensors are glued evenly along the fibers of the carbon fabric through the full length of the column. According to the graph of changes in the relative deformations of the composite materials in relation to the level of load on the pole, the tensometers reading curves can be conditionally divided into three groups. The largest strains were recorded at the most compressed face (first group) at the top of the column T4, T5. As we move away from these tensometers, the deformation decreases. The maximum deformation was recorded at 800 kH, which was 95% of the breaking load. The strains in the compressed zone of concrete ranged from 0.7*10−3 to 1.62*10−3 .
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From this it can be concluded that the fracture zone was in the upper part of the column. The specimen itself collapsed due to loss of stability with sharp bending of the structure and appearance of cracks in the tensile zone of the concrete. The fibers of the compressed zone of the concrete ruptured in the central part of the structure 2 cm wide. The fibers ruptured at the same time as the structure abruptly bent. The second group of tensometers located on the side face of the pole showed strains from 0.2*10−3 to 0.4*10−3 . The third group of graph curves (N−ε) was located along the force ordinate. Relative strains did not exceed 0.1*10−3 , with some strain curves showing compression and others tension. The reading of σ−ε curve data for the strut reinforced by a cage confirmed the assumption that the deformation in the compressed zone of concrete is four times greater than in the lateral edges of the structure, while in the tensile zone the fibers are in a neutral position. It can also be argued that the greatest stresses in the composite carbon fabric depend on the location of the weakest section of the compressed zone of the concrete. For a given pole, this area was at the top of the column. BKY—X1Lp—Prototype reinforced with carbon fiber clamps arranged in transverse direction according to variant BKY-X1. Additionally, in the longitudinal direction, two carbon fiber lamellae are installed on the tensile face of the column. Five tensometers (T12-T16) were glued on the longitudinal lamellae. Up to a load level of 500 kN, which is 70% of the breaking load Nult, the tensometers hardly deformed, indicating that there was no stress in the lamellae. From this it can be concluded that the tensile edge was in the neutral line. When the load level was increased to 600 kN (85% of Nult), an increase in tensile strain up to 0.3*10-3 was recorded in the center of the lamellae. As the structure collapsed during exposure at 700 kN, deformations were recorded in the destructive stage of the pole. The deformation increased by a factor of more than 7 from 0.3*10−3 to 2.2*10−3 . From this it can be concluded that the composite lamellas only engaged in the fracture stage, which is logical and is explained by the failure of the compressed zone of the concrete and the increase in deflections. Two tensometers were glued to the central clamp in the tensile and compressed zones, which showed deformations similar to those in the clamps of a similar pole without BKY-X1 lamellae. Compression deformations are also observed in the tensile zone and only in the fracture stage they change sign. The tensometers located in the compressed zone shows significant tensile strains equal to 1.7*10−3 in the fracture stage. At the previous load level the value of strain was 0.5*10−3 . According to the data in Table 1, the reinforcement factor taking into account the difference in strength of the concrete is 1.13. BKY-X2Lc—Reinforced concrete pole strengthened with composite materials in transverse direction, according to the variant of BKY-X2 pole, additionally, two lamellas are installed in the compressed edge. The basic idea of this reinforcement scheme is to increase the strength of the compressed zone of concrete, by gluing high-strength lamellae located in the longitudinal direction with respect to the specimen to be reinforced. The clamps, in this case, are both anchoring devices and separate reinforcement elements that restrain
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Table 1 Test results of reinforced concrete poles Pole codes
1
Concrete strength R,MPa
Ultimate concrete strain Compression εe · 10−3
Tensile εet · 10−3
2
3
4
Strength Ny , k H
Strengthening kys = N y /N
5
6
BK
38.9
4.72
1.64
592.5
–
BKY-X1
38.6
5.88
2.24
778.9
1.315
784.9
1.325
BKY- X2
38.9
4.73
1.61
794.7
1.34
794.7 BKY-X2Lc
41.6
3.94
1.42
800
1.35
748.1
1.26 1.18
BKY-X1Lp
40.8
4.49
2.15
700 667.4
1.13
BKY-X5
41.6
6.81
2.63
844.0
1.42
Notes 1) The concrete compressive and tensile deformations and deflections of the poles are given in the pre-failure phase. 2) The strength of concrete and reinforcement has been determined by testing the specimens. 3) In the denominator of columns 5 and 7, the values given by the conversion factor to the concrete strength of the standard specimens kys = R R y ∗ (Ny N )
the development of lateral deformations in the concrete. It should be noted that this type of reinforcement is not considered by SP 164.1325800.2014. In order to determine how the composite materials and the concrete structure work together, 5 tensometers (T12 to T16) were glued on the lamellae in longitudinal direction. Similar to the previous pole, 2 tensometers were glued on the tensile area of the central clamp in the transverse direction. During the test, up to a load of 500 kN, the relative strains in the lamellae developed almost equally in all areas according to a linear pattern N = 17−308ε. When loaded up to 600 kH, which amounted to 75% of the destructive load Nult, the lamellas in the upper part of the structure cracked. With further increase in load, the fracture zone in the lamellae increased. The maximum relative strain of the longitudinal lamellae reached a value of 2.6*10−3 . Strain readings in the central clamp confirmed the assumption that there was no tensile or compressive strain in the tensile zone, which was confirmed by the T-11 tensometers readings. In the compressed zone, the development of relative strains is characterized by a linear relationship N = 86−1064ε.
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4 Discussion The search for the most effective options for reinforcing eccentric-compressed reinforced concrete posts operating with small eccentricity of load application has shown the following results: Reinforcement, using carbon fiber lamellae arranged longitudinally in both the tensile and compressed zones, is ineffective. The lamellae located in the tensile zone come into play in the destructive stage of loading. It is known that compressive loadbearing structures are designed with a safety margin and operating loads make up 80–85% from the destructive load. The lamellas located in the compressed zone of concrete work together with the reinforced structure up to a certain load level. Their brittle failure and further exclusion from joint operation with the reinforced concrete of the reinforced structure makes this type of reinforcement unsafe. Transverse reinforcement, in the role of composite clamps or a cage, does work in conjunction with reinforced concrete structures, up to the point of specimen failure. From the tensometers readings, it was found that when the structures are unequally compressed, where one side is most and the other is least compressed or stretched, the deformation in the composite transverse reinforcement does not develop uniformly. On the tensile (less compressed) face, the deformation in the composite clamps is either absent or positive. The latter indicates that the fibers are not being stretched but compressed, which is completely uncharacteristic of this type of reinforcement. On the compressed face of the structures, on all samples the transverse clamps are deformed; herewith the relative deformations in the composites develop approximately the same, regardless of whether it is a central clamp or an anchor clamp closer to the headband. From this it can be concluded that compressed elements must be reinforced uniformly along the entire length of the structure. The deformation on the lateral faces of the structure is approximately 4 times less than on the compressed face. It can be concluded from this that it is not necessary to provide a closed clamp or a cage for eccentrically compressed structures. The deformation in composite clamps reaches a value of 1,6*10–3 at the limit load. Considering that the modulus of elasticity of composite bonded carbon fiber, according to the data of the manufacturer “Gidrozo” OOO, is 102 GPa. From this it follows that according to Hooke’s law; the stress in the carbon fabric is 163.2 MPa. In turn, the ultimate tensile strength in the direction of the main fibers in the tests is 1062 MPa, which is 6.5 times higher. From this it can be concluded that a smaller cross-sectional area of the composite clamps is required, and hence a smaller number of layers of carbon fabric can be used. Based on the test results, the information processing and the analysis the following reinforcement options and schemes are recommended for eccentrically compressed reinforced concrete posts. It is recommended to reinforce structures only with clamps or cages, with composite materials arranged in transverse direction.
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In transverse reinforcement it is recommended: to use less number of carbon fiber layers; to use U-shaped bandages or half-bands instead of clamps, the carbon fiber located in the compressed zone will take the main load; to use different number of carbon fiber layers on the column faces and in the compressed zone, this proposal is based on deformation data which is 4 times less on the column faces than on the compressed face; to distribute composite reinforcement evenly along the length of the column. It is not recommended to use composite reinforcement, with positioning along the structure regardless of whether the composite material will work in compression or tension. All of the proposed recommendations should be further verified by experimental studies.
5 Conclusion The purpose of this study is to determine the most effective methods and schemes of composite reinforcement for eccentric-compressed reinforced concrete structures operating with small eccentricities of load application. To achieve this goal, the following tasks were carried out: – A number of reinforced concrete specimens differing in type and scheme of reinforcement were manufactured, reinforced and tested; – In the course of the experiment, deformations were replaced in the most important areas of composite reinforcement; – Based on the experimental data obtained, graphs (σ-ε) of load level dependence on relative deformations of composite materials were plotted; – Analysis of (σ-ε) curves identified areas of the most heavily loaded composite areas and those areas where the composite material did not work during the test; – On the basis of this analysis, the most effective schemes and reinforcement options were identified. The following conclusions can be drawn as a result of the experimental investigations, followed by processing of the data: – The variants of the most effective schemes of reinforcement of eccentriccompressed reinforced concrete posts working with small eccentricity of load application have been found; – It has been proved ineffective using of composite materials located in longitudinal direction both in compressed and stretched zones; – Areas where the composite material fails have been identified and recommendations for more effective reinforcement schemes have been proposed; – A large amount of information on the response of composite material in reinforced concrete structures has been obtained.
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References 1. Rudenko VO, Sadykov TR (2021) History of the development of reinforced concrete structures. In: Innovative development: technical and technological aspects: collection of articles based on the results of the international scientific and practical conference, Izhevsk, 09 June 2021, pp 45–46. https://cazi.me/oEogr 2. Kolosova NB (2011) Problems of modern concrete and reinforced concrete. Eng Constr J 8(26):4. https://lingen.ru/rovff 3. Al Qadi Ali (20163) Basic physical and mechanical properties of reinforced concrete. Bull Belgorod State Technol Univ V. G. Shukhov 5:39–42. https://lingen.ru/7dub8 4. Baskakov KO (2020) Features of concreting in the construction of high-rise buildings in a dry hot climate. StudNet 3(5):425–431 5. Kostenko AN (2010) Strength and deformability of central and extra-central -compressed brick and reinforced concrete columns reinforced with carbon fiber and glass fiber. Ph.D. thesis, Moscow. 6. Podnebesov PG (2015) The results of studies of strength and deformability of reinforced concrete columns strengthened with cage. In: Urban planning, reconstruction and engineering support for sustainable development of cities of the volga region, pp 42–47 7. Litvinov AG (2010) Restoration and strengthening of reinforced concrete structures with polymers. Novocherkassk, Publishing house “Science, Education, Culture” 8. Ustinov BV, Ustinov VP (2009) Research of physical and mechanical characteristics of composite materials (CPM). Izvestia Higher Schools Constr 11–12:118–125 9. Shilin AA, Pshenichny VA, Kartuzov DM (2007) External reinforcement of reinforced concrete structures by composite materials. Publishing house Stroyizdat 10. Shilov AV, Kuznetsov AI (2015) On the issue of designing the reinforcement of reinforced concrete structures with composite materials. In: Construction and architecture - 2015: materials of the international scientific and practical conference, Rostov-on-Don, 26–27 2015. Rostov State University of Civil Engineering, Union of Builders of the Southern Federal District, Association of Don Builders, p 28. https://lingen.ru/6qtc1 11. Mukhamediev TA (2013) Designing of strengthening of reinforced concrete designs by composite materials. Conc Reinforced Conc 3:6–8 12. Pol’skoj PP, Mailyan DR (2018) Usilenie zhelezobetonnyh konstrukcij kompozitnymi materialami na osnove ugleplastika. Nauchnoe obozrenie: stroitel’stvo i arhitektura 1:43–46 13. Polskoy P, Georgiev S, Muradyan V, Shilov A (2018) The deformability of short pillars in various loading options and external composite reinforcement. MATEC Web Conf 20–26 14. Georgiev S, Mailyan D, Blyagoz A (2021) Proposals for determining the relative deformations design value of εb3 concrete in volumetric deformation conditions. Mater Sci Forum 1043:155– 162
Investigation of the Mechanical Effect of Machinery on the Soil Galia Kokieva , Varvara Druzynova , Senge Yampilov, Daba Radnaev , Stanislav Shukhanov , and Akulina Popova
Abstract With an increase in the energy saturation of machines and an increase in their speed, the dynamic effect of the running system on the soil increases its compaction, which negatively affects the yield. The density of the soil in the subseminal layer is close to optimal when its humidity corresponds to the humidity at physical ripeness, and much more—in the dried state. Thus, by the beginning of pre-sowing treatment, the real parameters of the density of addition and structurality in the treated layer differ from the required (optimal) ones. The negative consequences of the unfavorable structure of the arable layer are obvious: poor seeding quality, unproductive moisture loss, slow swelling of seeds, sparseness of seedlings, slow and mostly superficial development of the root system, inefficient use of fertilizers. In years with favorable weather conditions, the negative impact of such a structure is less noticeable than in years with acute moisture deficiency. Great importance is given to mechanical processes occurring in the soil. Agricultural mechanics mainly studied the forces that affect the working bodies of tillage machines, the movers of tractors and mobile agricultural machinery, as well as the patterns of movement of machines and aggregates under the influence of these forces. The article provides G. Kokieva (B) · A. Popova Arctic State Agrotechnological University, Sergelyakhskoehighway, 3 km, b. 3, Yakutsk, The Republic of Sakha (Yakutia) 677007, Russia e-mail: [email protected] V. Druzynova North-Eastern Federal University named after M.K. Ammosov, Belinskogost, b. 58, Yakutsk, The Republic of Sakha (Yakutia) 677007, Russia S. Yampilov East Siberian State University of Technology and Management, Street Klyuchevskaya, 40V, Ulan-Ude 670013, Russia G. Kokieva · D. Radnaev The Buryat State Agricultural Academy of V.R. Filippova, Street Pushkin, h. 8, Ulan-Ude 670024, Russia S. Shukhanov Irkutsk State Agrarian University named after A.A. Yezhevsky, 1/1, Molodezhny Village, Irkutsk, Irkutsk Region 664038, Russia © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_199
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an analysis of the density of the subsurface layers of the soil at depth, the effects of mechanical effects after agricultural machinery on the soil, affecting crop yields. Keywords Tillage · Plowing · Agricultural machinery
1 Introduction Soil density is one of its main agrotechnical characteristics. This is especially evident when compacting the soil with running systems. The maximum reduction in the yield of corn in the tractor track is 33.1%, wheat—46%, potatoes—27%. With an increase or decrease in soil density from optimal by 0.1… 0.3 g/cm3 , the yield decreases by 20… 40%. At this time, quite a lot of time is devoted to research in the field of soil mechanics. One of the most important mechanical processes—the change in soil density—plays an essential role in obtaining a crop (Fig. 1). With the existing technologies of cultivation of agricultural crops, various machines pass through the field 10 … 15 times. The total area of tracks of wheels and tracks of tractors, harvesting vehicles is 100… 200% of the field area. The turning lanes are rolled by the wheels of cars 6…20 times (only 10… 15% of the field area is free from the impact of running systems). And since the average pressure generated by tracked tractors reaches 60…80 kPa, wheeled—85…165 kPa (maximum—320…560 kPa due to uneven distribution of pressure on the support surfaces), the density of the soil in the arable and sub-arable horizons increases [1–5]. Another source of mechanical compaction of the soil is the working bodies of tillage machines. It has been experimentally established that when a flat wedge moves at a depth of 110 mm, the pressures reach 300…600 kPa. The work of the plows is accompanied by pressures on the ploughshare and the blade of the order of 800 … 1000 kPa. Contact pressures on the surface of the working bodies of tillage machines are greater than leads to the formation of the desired sole and compacted clods of soil [6–8]. One of the most important mechanical processes—the change in soil density— plays an essential role in obtaining a crop (Fig. 1) [9–12]. In a dry year, the opposite pattern is found in the structural composition of the surface layer of chernozem—aggregates with a size of 5 …20 mm are significantly larger, and with a size of 0.25 …5 mm less than required. In order to eliminate the big difference between the real and optimal level of structurality, the redistribution of fractions alone is not enough. When cultivating the soil, more intensive crumbling techniques should be used by traditional or new technical means. The latter equally applies to the structural composition of the seed layer, which is below the optimum both in wet and (especially) in dry years. To build a general rheological model of the soil, it is necessary to build a rheological model of deformations of shape change (Fig. 2a) and volume change (Fig. 2b). The construction of a rheological model for the deformation of the first type consists of two stages. The first consists in constructing a rheological model of the soil in a stress–strain state before its destruction (the phase of
Investigation of the Mechanical Effect of Machinery on the Soil
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Mechanical impact of agricultural machinery on the soil
De-
Seal
Mixing, moving, turnover of the formation
struction
Changeinporosity (density)
Changingtheairmode
Changingthethermalregime
Chang-
Changingthewaterregime
Destruction
ingthebiologi-
of the structure
calregime
and root system
Conditions for the development of the root system
Mechanical resistance to root system growth
Biological conditions of root system development
Cropyields
Fig. 1 Diagram of the consequences of mechanical impact of agricultural machinery on the soil, affecting the yield of agricultural crops
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Fig. 2 Generalized rheological model of soil for shear a and volumetric b deformations
local shifts is the first phase of soil deformation). At the second stage, a rheological model is constructed under conditions of soil destruction, i.e. the formation of a sliding surface (the phase of final shifts is the second phase of soil deformation). These two models, combined into one, represent a rheological model of the soil for shape change [11–13]. A complete system of soil state equations in soil mechanics: τi j dγi j 1 dτi j = , τi j < τs ; + dt n 1 (ρ) G 1 (ρ) dt dγi j τi j τi j − τs G 1 (ρ) + G 2 (ρ) dτi j + , τi j ≥ τs ; = + dt n 1 (ρ) G 1 (ρ)G 2 (ρ) dt n 2 (ρ) σi j dεi j 1 dσi j = + ; dt E(ρ) dt μ(ρ) ρ = ρ0 + Bln[σm (1 + τmax )], where γi j —angular deformations; t—deformation time; τi j —tangential stresses; n 1 (ρ)—shear viscosity in the first phase of deformation; G 1 (ρ)—shear modulus in the first phase of deformation; G 2 (ρ)—shear modulus in the second phase of deformation; τs = C + σ tg(ϕ)—ultimate shear resistance; C—coefficient of adhesion; ϕ—the angle of internal friction of the soil; n 2 (ρ)—shear viscosity in the second phase of deformation; εi j —linear deformations; E(ρ)—modulus of elasticity; σi j —normal voltages; μ(ρ)—linear viscosity; ρ—current value of soil density; ρ0 —initial value of soil density; B—empirical coefficient characterizing soil compaction;σm = (σ1 + σ2 + σ3 )/3—average voltage; τmax —maximum voltage of three values τi j (Table 1). Analysis of the density of the subsurface layers of the soil at a depth of 30…60 cm, where its change is more clearly traced during the processing of the upper arable layer under the influence of machine-tractor units, shows that when plowing with a heavy tractor (traction class 3) of a deeply tilled (14…16 cm) field, the subsurface layers are compacted less than when plowing with the same tractor finely tilled (5…6 cm). A lighter tractor (traction class 1, 4) compacts the soil less when peeling than a
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Table 1 Shows the density of the soil, g/cm3 , depending on the methods of its processing Processing sequence
Soillayer, cm 0…10 10…20 20…30 30…40 40…50 50…60 30…60
Before processing
1.02
1.32
1.27
1.42
1.44
1.52
1.46
1.02 1.07 1.00 1.04
1.30 1.24 1.24 1.19
1.29 1.27 1.23 1.30
1.42 1.42 1.43 1.44
1.44 1.44 1.55 1.54
1.52 1.54 1.60 1.66
1.46 1.47 1.52 1.54
After peeling with a tractor unit: MTZ-50 DT-75 M
After plowing with an aggregate with a tractor DT-75 M of the tilled field with an aggregate with a tractor: MTZ-50 DT-75 M
1.16 1.15 1.17 1.16
After plowing an unflowed field 1.15
1.21 1.18 1.22 1.18
1.32 1.28 1.43 1.30
1.44 1.43 1.50 1.44
1.21
1.33
1.49
1.48 1.47 1.61 1.54
1.56 1.54 1.69 1.66
1.49 1.48 1.60 1.54
1.54
1.50
Note In the numerator at a processing depth of 5…6 cm, in the denominator—14… 16 cm
heavy one. The productivity of cultivated plants is affected by the effective fertility of not only the arable layer, but also the sub-arable ones, so it is necessary to take into account the impact of agricultural machines and tractors on them. However, the known methods of cultivating the arable soil layer take into account the improvement of physical conditions (density, humidity, porosity, etc.) only in it [3–8].
2 Research Methodology The actual density of the addition of the surface layer, despite the wide range of values of the optimal density (1.0…1.3 g/cm3 ), deviates from the optimum: in the wet year before sowing and during the growing season, it is less than it by about 0.05 g/cm3 , and in the dry year—more by 0.08 g/cm3 . In accordance with this, the soil has to be rolled or loosened. Thus, a working body with a minimum cutting angle and blade length can optimize the root-inhabited soil layer. This is best answered by a working body made of steel wire (flat or round). A circular wire with a diameter of 40 mm at a processing depth of 16 cm reduces the density of the soil by only 2.5… 3%, which fully meets the requirements for the processing of the subseminal layer. To do this, you can use working bodies consisting of vertical knife-shaped racks 1 (Fig. 3) and a flexible element 2 (steel wire) located between them. When moving, the knife-shaped racks cut the soil in the vertical plane, and the flexible element cuts the soil layer of the desired thickness in the horizontal plane, providing slight loosening. On knife-shaped racks, flexible elements of different diameters can be fixed in two tiers, obtaining a two-layer structure of the root-inhabited soil layer, the parameters of which will meet the requirements. There are two directions in the development of rheological soil models—their representation in the form of a differential equation and in the form of a Voltaire integral equation of the second kind. The use of two
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Fig. 3 Diagram of a flexible working body for processing the subseminal layer
rheological soil models (for volumetric and shear deformations) is an indispensable consequence of the use of continuum mechanics methods; this is due to the fact that the density of the soil changes during deformation. When the loosening working bodies interact with the soil, it is necessary to create conditions of destruction at minimum normal stresses. The main properties of the soil that determine such a condition are plastic and viscoplastic. Depending on the formulation of the tasks of interaction of tillage organs and movers with the soil, it is possible to use degenerate models that contain only those rheological properties of the soil that determine the main purpose of the technological task. Thus, the representation of the relationship between stress and strain during shear deformations depends on the formulation of the problem, on the purpose of the final study of the interaction of tillage organs with the soil. The use of two degenerate soil models (elastic-viscous and viscoplastic) is a consequence of the permissible simplification of the rheological model in each specific task. The peculiarity and positive property of the rheological model developed by us is the relationship between volumetric and shear deformations of the soil element, since the ultimate shear resistance depends on the normal stresses acting on the shear site. Table 2 shows the impact of tillage organs and movers on the soil. As a result of theoretical studies, the strength of the flexible element and its optimal parameters were determined. Energy indicators of agricultural aggregates are usually determined using various devices. Since the designs of the machines are diverse, it is often necessary to change the parameters of the devices. This circumstance complicates and complicates the organization of tests. When solving the problem, the main energy elements are taken as the starting ones, namely: the efficiency coefficient of the mover and the coefficient that takes into account the loss of mechanical energy for the deformation of the mover and the surface on which it rolls. The existing methods of studying aggregates require large monetary and material costs. To explain this phenomenon, in our opinion, it is necessary to develop a mathematical model of the process of interaction of deformable pneumatics with an elastic–plastic medium, which is considered to be the soil subject to modern processing.
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Table 2 Impact of tillage organs and movers on the soil n/a Interrelated stages corresponding to different goals 1
The spatial problem of the technological impact of working bodies and propellers on the soil is divided into two flat ones, considered on mutually perpendicular planes. The planes are chosen so that the nature of the impact of the working body or the mover on the soil reflects the most significant features of the technological process
2
The equation of state for plane problems is simplified depending on the characteristic features of the technological impact of the working body and the mover in the studied plane. If the working body (a mole, a caterpillar, a wheel and a low-pressure roller) does not separate the soil block, does not cause a shift of the soil block in front of it, then the first phase of soil change is most characteristic. According to the complete rheological model of the soil, the elastic-viscous properties of the soil are most significant in this phase. Consequently, the formulation of such problems is reduced to an elastic-viscous scheme If a block of soil is separated by a working body (this applies to all tillage implements loosening the soil), then the most significant property is the viscoplastic flow of the soil along the line (surface) sliding. In such problems, in accordance with the complete rheological model, it is advisable to consider the soil as a viscoplastic medium
3
Define boundary conditions. The latter in the tasks of technological impact of tillage tools or movers on the soil are of fundamental importance only before the onset of plastic flow along the slip line. From this moment on, the formed block of soil cannot be considered as a continuous medium and only deformable solid methods are applicable to it. Therefore, when determining the pressure distribution on the surface of the working body or the mover, the soil should be represented as an elastic-viscous medium or as a linearly deformable medium for the corresponding deformation rate
4
Stress and strain fields are determined or sliding lines are found in flat problems. To determine the stress and strain fields in technological processes without separating the soil block, you can apply the principles and methods of calculating a viscoelastic body
5
The solutions obtained for determining the distribution of pressures at the boundary “working body (mover)—soil” are analyzed. The study of stress and strain fields or the position of the sliding line makes it possible to formulate requirements for the geometry and kinematics of the working body or mover. At this stage, it becomes possible to develop a methodology for designing a working body or a mover that provides a given technological process of influencing the soil
3 Conclusion The main factor constraining the further growth of crop yields during layer-by-layer processing is the destruction of stubble, a decrease in the fertility of the lower part of the arable layer due to the lack of turnover of the formation and its removal to the surface. As a result of compaction, the physical condition of the soil worsens, and under some loosening conditions it improves. The intensification of work on the creation of new varieties of agricultural crops requires proper logistical support, and first of all, to perform field and laboratory technological processes in breeding and primary seed production. Subsequent tillage partially reduces the effect of the consequences of its compaction. Obviously, extensive research will make it possible to make corrective corrections in the form of coefficients in the pure formula. These
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studies should be of a multi-year nature and be carried out according to a special methodology that provides for various options for compaction of soils and their restoration.
References 1. Domrachev VA et al (2013) Substantiation of the parameters of active needle rotary discs for sowing on a stubble background. Equip Villages Work 2:10–11 2. Iwanicki SA, et al (2018) development of a combined working bodies for the surface treatment of the soil. Innovative science and technology. In: APK : collection of scientific works of the International scientific-practical conference. Samara state agricultural Academy, Kinel’, pp 392–396 3. Whom AA, Shevchenko AP (2019) Experimental study of the interaction of the working bodies of the needle drive with plant remains. Bull Omsk State Univ 1:134–141 4. Sizov IV, Kondrashov VA (2017) Analysis of structural features of non-water working bodies for soil loosening. In: Innovative developments for the production and processing of bast crops: materials of the international scientific and practical conference of the VNIIML. Tver State University, pp 187–190 5. Khmyrov VD et al (2015) Theoretical substantiation of the design of the needle disk of the litter manure loader. Bull Michurinsky State Agrar Univ 4:156–163 6. Schmidt AN et al (2020) Justification of the modes of operation of the needle disk of a new design. Tractors Agric Mach 4:70–75. https://doi.org/10.31992/0321-4443-2020-4-70-75 7. Milyutkin V, Buxmann V, Mozgovoy A, Rudoy D, Olshevskaya A (2022) Modern technology for cultivation of agricultural crops in zones of “Risk Farming” with conservation and accumulation of atmospheric moisture. Lect Notes Netw Syst Book Ser (LNNS) 246:138–146. https:// doi.org/10.1007/978-3-030-81619-3_15 8. Rudoy D, Pakhomov V, et al (2021) Review and analysis of perennial cereal crops at different maturity stages. In: IOP conference series: earth and environment science, vol 937, p 022111. https://doi.org/10.1088/1755-1315/937/2/022111 9. Molochnikov D, Khalimov R, Gayaziev I, Rudoy D, Olshevskaya A (2020) The improvement of the technique for determining technical condition of repair and maintenance equipment. In: E3S web of conference, vol 210, p 08006. https://doi.org/10.1051/e3sconf/202021008006 10. Lachuga Y, Akhalaya B, et al (2020) Energy-saving tillage with a combined unit with universal working bodies. In: IOP conference series: materials science and engineering, vol 1001. International Scientific and Practical Conference Environmental Risks and Safety in Mechanical Engineering 11. Meskhi B, Bondarenko V, et al (2020) Impact of globalization and digitalization on the efficiency of environmental development of territories. In: E3S web of conference, vol 217, p 06012. https://doi.org/10.1051/e3sconf/202021706012 12. Efremenko I, Bondarenko V, Romanishina T, Rudoy D, Olshevskaya A (2021) Application issues of spatial interaction marketing in the regional agribusiness sustainable development. In: E3S web of conference, vol 273, p 08080. https://doi.org/10.1051/e3sconf/202127308080 13. Rudoy D, Egyan M, Kulikova N, Chigvintsev V (2021) Review and analysis of technologies for harvesting perennial grain crops. In: IOP conference series: earth and environment science, vol 937, p 022112. https://doi.org/10.1088/1755-1315/937/2/022112
On Determining the Elasticity Modulus of Moso Bamboo Based on the Static Bend Test Results by Analogy with Wood and Engineering Plastics Gennadiy Verzhbovsky , Sergey Skuratov , and Sergey Shutskiy
Abstract The application of bamboo in the practice of modern construction is considered. The physical and mechanical properties of bamboo, the peculiarities of genera and species of bamboo, the structure of the trunk are described. The publications of ISO (International Organization for Standardization) concerning building codes and rules for the use of bamboos in construction are considered. The backlog in the release of manuals on the use of bamboo as a structural material in construction is determined. The peculiarity of the cross-section of bamboo samples for static bending testing is indicated. To determine the geometric characteristics of the crosssection of the samples, a diagram of a thin-walled ring segment bounded by a sector with a central angle is used. The features of differentiation of cylindrical compartments of the trunk by interstitial diaphragms are considered. Reducing the length of the cylindrical compartments of the bamboo trunk eliminates the possibility of manufacturing samples that do not contain “joints” along the length of the working area of the sample. The paper considers the possibility of using recommendations for determining the mechanical characteristics of wood and plastic composite materials when testing Moso bamboo samples for static bending to define the modulus of elasticity. A series of test samples were made, the geometric characteristics of the cross sections of the samples were determined taking into account the characteristics of the material. An experimental test facility was prepared, bamboo samples were tested for static bending. As supports for bamboo samples, special devices have been selected that allow the ends of the sample to be tightly placed on the surface of these devices. Keywords Moso bamboo · Transport infrastructure · Joint · Internodal diaphragm · Modulus of elasticity · Tray-likeness/Tray-shapeness · Static bending · Segment of a circular ringa
G. Verzhbovsky · S. Skuratov · S. Shutskiy (B) Don State Technical University, 1, Gagarin Square, 344002 Rostov-on-Don, Russia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Guda (ed.), Networked Control Systems for Connected and Automated Vehicles, Lecture Notes in Networks and Systems 510, https://doi.org/10.1007/978-3-031-11051-1_200
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1 Introduction In the practice of modern construction, along with traditional structural materials such as steel, aluminum, reinforced concrete, wood, and materials based on it, plastic composite materials, bamboo is something special as a renewable and environmentally friendly material. The analysis of various sources of scientific and technical literature on the study of the properties of bamboo and structures with its use allows us to conclude that the physical and mechanical properties of bamboo depend on various factors [2–5]. These include the geographical location of the growth, the genus and species of bamboo, the structure of the trunk (with account for the presence of interstitial diaphragms located in the places of external thickenings in the form of rings—“joints”), density (related to the age of bamboo, the growing environment, the structure of the trunk parts), moisture content (tensile strength, compression, and the elasticity modulus of dry bamboo material is higher than of fresh one). Currently, the results of studies on the physical and mechanical properties of various types of bamboos conducted by scientists from different countries [6–8, 11–13] show that they can be combined into three editions of ISO (International Organization for Standardization) concerning building codes and rules for the use of bamboos in construction [9, 10]. It should be noted that there are more than 300 regulatory documents and manuals for the calculation, manufacture, and testing of structures made of wood. This indicates a significant lag in the release of manuals on the use of bamboo as a structural material in construction. In our country, recommendations are applied to determine the mechanical characteristics of such traditional structural materials as wood and plastic composite materials. In this paper, the issues of the application of the above recommendations for determining the elasticity modulus when testing samples of Moso bamboo for static bending are considered.
2 Materials and Methods The selection of material for testing was influenced by the fact that more than 1,600 species of bamboo have been identified in nature, among them, Moso bamboo, which has appropriate mechanical properties and a peculiar aesthetic appearance, has become the most widespread [4]. Based on the recommendations of GOST 16,483.3–73*, it was decided to prepare five small samples (I-V) for testing. The geometric dimensions of the samples l0 and b meet the requirements of GOST, and are 300 and 20 mm. The size of the section in height h is regulated by the thickness of the bamboo wall. In addition, due to the natural features of the bamboo structure, the cross section of the samples has not a square shape b·h = 20·20 mm, as is customary for small wood samples, but the shape of a thin-walled ring segment bounded by a sector with a central angle of 2α (Fig. 1).
On Determining the Elasticity Modulus of Moso Bamboo …
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Fig. 1 Scheme of a thin-walled circular ring
Here, x–x and y–y axes are the main central ones; R1 and R2 —are, respectively, the radii of the outer and inner surfaces of a segment of a thin-walled circular ring bounded by a sector with a central angle of 2α; r—radius of the median surface of 2 . The thickness of the ring t = R1 –R2 is less than the ring defined as r = R1 +R 2 twice the radius of the median surface of the ring (t