Recent Developments in Geotechnics and Structural Engineering: Select Proceedings of TRACE 2022 (Lecture Notes in Civil Engineering, 338) [1st ed. 2023] 9789819918850, 9789819918867, 9819918855
This book presents select proceedings of the International Conference on Trends and Recent Advances in Civil Engineering
132 91 19MB
English Pages 517 [498] Year 2023
Contents
About the Editors
Improving Railway Track System Using Soil Nails for Heavy Axle Load
1 Introduction
2 Literature Review
3 Specifications for Blanket Layer
4 Performance Studies of Blanket Layer
5 Methodology, Results, and Analysis
5.1 Numerical Analysis Methodology
5.2 Discussion on Results
6 Concluding Remarks
References
Finite Element Analysis on Skew Box-Girder Bridges
1 Introduction
2 Methodology
3 Result and Discussion
3.1 Effect of Span-Depth Ratio
3.2 Equations for Forces and Deflection
4 Conclusions
References
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
1 Introduction
2 Study Area, Geology, and Seismicity
3 Site Characterization
4 VS, VSavg, and Its Correlation with SPT-N
5 Contour Plots
6 Comparison Between Uncorrected VS and Corrected VS
7 Average Shear Wave Velocity
8 Conclusions
Annexure
References
Numerically Investigating the Effect of Wind Load on Square and Setback Building
1 Introduction
2 Model Specifications
3 Fluid Domain and Meshing
4 Boundary Conditions and Solver Settings
5 Validation Study
6 Results and Discussion
7 Conclusions
References
Rockfall Hazard and Its Mitigation with Focus on Rock-Sheds: A Review
1 Introduction
2 What Causes Rockfall?
3 Rockfall Mitigation Techniques
3.1 Active Protection
4 Conclusions
References
Microstructure Investigation and Design of GFRP Reinforced Coastal Structures
1 Introduction
2 Methodology
2.1 Canal Lining and Seawalls
2.2 Scanning Electron Microscope (SEM)
3 Results and Discussions
3.1 Mechanical and SEM Tests
3.2 Canal Lining Field Implementation
4 Conclusion
References
Finite Element Analysis and Design of Concrete Bridge Deck Using GFRP Reinforcement
1 Introduction
2 Methodology
2.1 Theoretical Design
2.2 Finite Element Modeling and Analysis
3 Results and Discussions
4 Conclusion
References
“Experimental Study of Variation in Properties of Ultrafine Ground Granulated Blast-Furnace Slag (GGBS) and Steel Fibre Infused Concrete”
1 Introduction
2 Literature Review
3 Methodology
3.1 Materials
3.2 Experimental Work
4 Results and Discussion
4.1 Test Result (Compressive-Strength)
4.2 Test Result (Workability)
4.3 Test Result (Cost Analysis)
5 Conclusion
References
Analytical Hierarchy Process in the Maintenance Decision-Making of Interlocking Concrete Block Pavements
1 Introduction
2 Objective
3 Methodology
3.1 Selection of ICBP Road Network
3.2 Proposed Analytical Hierarchy Process (AHP) for Maintenance Prioritization
3.3 Estimation of Priority Ranking of ICBP Pavement Sections by SAW Method
3.4 Statistical Assessment of Priority Rankings Obtained from AHP and SAW Methods
4 Conclusions
References
An Effective Use of Agricultural Waste as Silpozz in Concrete
1 Introduction
2 Literature Review
3 Materials Used in the Work
3.1 Cement
3.2 Water and Chemical Admixture
3.3 Fine Aggregate
3.4 Coarse Aggregate
3.5 Silpozz
3.6 Mix Proportioning and Experimental Details
4 Results Obtained and Discussions
4.1 Workability and Density Measures of Concrete Mixes
4.2 Compressive Strength Test Results
4.3 Flexural Strength Test Results
4.4 Cost Estimation and Comparison
5 Conclusion
6 Future Scope
References
Influence of Concrete with Partial Replacement of Fine Aggregates with Crumb Rubber and Cement with Silica Fumes
1 Introduction
2 Materials
3 Experimental Program
3.1 Methodology
4 Mix Design and Specimen Preparation
5 Experimental Results and Discussions
5.1 Workability
5.2 Compressive Strength
5.3 Split Tensile Strength
5.4 Ultrasonic Pulse Velocity
5.5 Rebound Hammer Test
6 Conclusions
References
Partially Replacing Cement with Ground Granulated Blast-Furnace Slag (GGBS) and Fly Ash Changes the Mechanical Properties of Concrete
1 Introduction
2 Chemical Properties of GGBS and Fly Ash
2.1 Chemical Properties
2.2 Physical Properties
3 Methodology Adopted for Mixed Design
4 Testing of Specimens
4.1 Mechanical Properties
5 Split-Tensile and Compressive Strength
5.1 Case Study on Cement Replacement with GGBS
5.2 Case Study on Cement Replacement with the “Fly Ash”
5.3 Case Study on Cement Replacement with the “GGBS” and “Fly Ash”
6 Conclusion
References
Stabilization of Expansive Clays: A Micro-mechanistic Study
1 Introduction
2 Soil-Additive Chemical Mechanisms
2.1 Cement and Lime
2.2 Fly Ash and Pond Ash
2.3 GGBS and Silica Fume
2.4 RHA and Bagasse Ash
3 Micro-mechanistic Analysis
4 Conclusions
References
Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix
1 Introduction
2 Research’s Objective
3 Literature Review
4 Materials and Methodology
5 Findings
6 Discussion
7 Conclusion
References
Comparative Analysis of High-Rise Structure with Diagrid Lateral Load-Resisting System with Composite Members and Base Isolation
1 Introduction
1.1 Composite Construction
1.2 Diagrid System
1.3 Base Isolation
2 Methodology
2.1 Modeling
2.2 Response Spectrum Analysis
3 Results and Discussion
3.1 Maximum Story Displacement
3.2 Maximum Story Drift
3.3 Maximum Story Shear
3.4 Base Shear
3.5 Fundamental Time Period
4 Conclusions
References
Optimization of Mix Design for Concrete with and without Polypropylene Fibre
1 Introduction
1.1 Concrete
1.2 Grade of Concrete
1.3 Fibres
1.4 Polypropylene Fibres
2 Test Set-Up
2.1 Concrete Cube Mould
2.2 Concrete Mix
2.3 Test Performed
3 Results
3.1 Workability
3.2 Compressive Strength
4 Conclusions
References
Use of Stone Dust and Ceramic Waste in Fine Aggregate Replacement in RAC
1 Introduction
2 Methodology
3 Results
4 Conclusion
References
Prediction of Strength and Stiffness Behavior of Glass Powder Stabilized Expansive Clay Using ANN Principles
1 Introduction
2 Dataset Preparation
3 Effect of Ternary Additives on Expansive Clays
4 CBR and UCS Prediction Model Using ANN
5 Conclusions
References
Landslide Hazard Zonation Mapping of Champhai District of Mizoram, India
1 Introduction
2 Study Area
2.1 Location of Study Area
2.2 Site Investigation
2.3 Landslide Hazard Zonation
3 Methodology
3.1 Landslide Use Land Cover (LULC)
3.2 Relative Relief
3.3 Slope Morphometry
3.4 Hydrology Analysis
4 Results and Discussion
5 Summary and Conclusions
References
Numerical Analysis of Gravity Dam-Foundation and Comparison with Limit Equilibrium Method
1 Introduction
2 Gravity Dam Design Criteria
3 Material Properties Considered
4 Limit Equilibrium Method (Lem) Results
5 Finite Element Method (Fem) Results
6 Conclusions
References
Experimental and Prediction of Properties of Concrete Using Steel Slag by Taguchi Method
1 Introduction
2 Materials and Methodology
2.1 Taguchi’s Method of Design
3 Results and Discussion
4 Conclusions
References
Properties of Rice Husk Ash and Aluminium Slag-Based Sustainable Geopolymer Bricks
1 Introduction
2 Materials
3 Sample Preparation
4 Results and Discussion
4.1 Compressive Strength
4.2 Bulk Density
4.3 Open Porosity
4.4 Water Absorption
4.5 Acid Attack
5 Conclusion
References
Identification of Critical Project Success (CPS) Factors for Construction Projects in India: An Overview
1 Introduction
2 Methodology
3 Findings from the Study
4 Inferences and Recommendations
5 Conclusions
References
Effects of Confining Pressure on Intact Rocks’ Anisotropy
1 Introduction
1.1 Rocks’ Anisotropic Behaviour and Classification
2 Strength Anisotropy Review
3 Influence of the Confining Pressure on Anisotropy.
4 Test and Methods
5 Results and Discussion
6 Summary and Conclusions
References
Crack Instigation and Propagation of Transversely Isotropic Biotite Gneiss
1 Introduction
2 Geology
3 Theoretical Background
4 Sample Preparation and Experimental Methodology
5 Results and Discussion
6 Summary and Conclusion
References
Analytical Studies on the Fire Resistance of Reinforced Concrete Beams Exposed to Parametric Time–Temperature Curve
1 Introduction
2 Finite Element Procedure
2.1 Numerical Modeling Details
2.2 Material Properties
2.3 Deflection Failure Criteria
3 Validation of FE Model
3.1 Beam Details
4 Parametric Study
4.1 Reinforced Concrete Beams Details
4.2 Fire Exposure Details
5 Results and Discussion
5.1 Fire Resistance of the RC Beams Subjected to ISO 834 Standard Time–Temperature Curve
5.2 Performance of RC Beams Subjected to Parametric Time–Temperature Curves
6 Conclusions
References
Effect of Biopolymer on Water Retention Property of Red Mud
1 Introduction
2 Materials and Methodology
3 Result and Discussion
4 Summary and Conclusion
References
Numerical Analysis of Interference of Machine Foundations on Reinforced Soil
1 Introduction
1.1 Literature Review
2 Numerical Analysis
3 Result and Discussion
4 Summary and Conclusions
References
Development of Design Charts for Rectangular Barrettes
1 Introduction
2 Literature Review
3 Work Done in Present Study
4 Results and Discussion
4.1 Performance of Rectangular Barrette
4.2 Limitations of Present Study
5 Conclusions
References
Performance of Cantilever Retaining Wall with Deformable Inclusions under Dynamic Loading
1 Introduction
2 Literature Review
3 Experimental Investigation
3.1 Backfill Material
3.2 Inclusion Material
3.3 Test Methodology
3.4 Experimental Test Procedure
4 Result and Discussion
4.1 Dynamic Earth Pressure on the Wall
4.2 Horizontal Displacement of Retaining Wall
5 Conclusion
References
Numerical Analysis of H-Shape Barrette Pile Subjected to Vertical and Lateral Loadings
1 Introduction
2 Methodology
3 Results and Discussion
3.1 Percentage Increase in Vertical and Lateral Capacities in Clayey, Sandy and c-Φ Soils
4 Conclusions
References
A Study on Effect of Uncertainties in Standardizing Workflow in Construction Firm Using SPSS
1 Introduction
1.1 Objectives of Work
1.2 Scope of Work
2 Literature Review
3 Methodology
4 Data Analysis
4.1 Relative Importance Index
4.2 Exploratory Factor Analysis
4.3 Regression Analysis
5 Results and Discussion
6 Conclusion
6.1 Future Scope
References
Application of Artificial Intelligence, Machine Learning, and Deep Learning in Contaminated Site Remediation
1 Introduction
2 Emerging Technologies
2.1 Artificial Intelligence (AI)
2.2 Machine Learning (ML)
2.3 Deep Learning (DL)
3 Applications of AI, ML, and DL to Site Remediation
3.1 AI-Based Optimization of Pump–Treat–Inject Groundwater Remediation: Case Study
3.2 ML-Based Assessment of Electrokinetic Remediation of Contaminated Groundwater: Case Study
3.3 DL-Based Simulation of Contaminant Migration: Case Study
4 Concluding Remarks
References
Effect of Jute Fiber on Engineering Properties of Soil
1 Introduction
2 Materials Used
2.1 Soil
2.2 Jute Fiber as a Reinforcement Material
3 Methodology Adopted
4 Result and Discussion
4.1 Effect on Compressive Strength of Soil
4.2 Variation in California Bearing Ratio Characteristics of Soil Under Unsoaked Condition
4.3 Variation in California Bearing Ratio Characteristics of Soil Under Soaking Condition
5 Conclusion
References
Influence of Calcite Veins on the Failure Mode and Mechanical Behaviour of Basalt
1 Introduction
2 Experimental Work
2.1 Vein Characterisation
2.2 Specimen Preparation and Test Procedures
3 Experimental Results
3.1 Vein Characteristic Parameters
3.2 Mineralogical Composition
4 Discussion on Veins Influence
4.1 Influence of Vein Orientation
4.2 Influence of Vein Thickness
4.3 Influence of Minerology
5 Conclusions
References
Optimising Structures for Earthquake Impact in Seismic Prone Zone
1 Introduction
2 Literature Survey
3 Methodology
4 Results
5 Conclusions
References
Correlation Between Field and Laboratory Deformability Moduli of Himalayan Sandstones
1 Introduction
2 Methodology
2.1 Deformability Modulus of Rock Mass in Uniaxial Jacking Test
2.2 Young’s Modulus of Intact Rock in Uniaxial Compression Test
3 Data Analysis
3.1 Comparison Between Deformability Modulus Rock Mass and Intact Rock
4 Conclusions
References
Study on the Effect of Bottom Ash on the California Bearing Ratio of Clay Soil
1 Introduction
2 Materials
2.1 Clay Soil
2.2 Bottom Ash
3 Methodology
4 Results and Discussion
4.1 Impact of Duration Soaking on CBR Rates of Clay Soil
4.2 Impact of Various Content of Bottom Ash on CBR Rate of Clay Soil
5 Conclusions
References
Rainfall Impact Force Versus Rise in PWP: A Study of Darjeeling Himalayan Landslide
1 Introduction
2 Instrumentation and Measurement of Data
3 Results and Discussions
4 Conclusions
References
Design and Cost Analysis of Headed Bars as Mechanical Anchorage System for Reinforced Concrete Beam-Column Joints
1 Introduction
2 Headed Bars as Anchorage System for Beam-Column Joints
3 Pull-Out Tests
3.1 Experimental Methodology
3.2 Results and Discussion
4 Derivation of Development Length for Headed Bars in Beam-Column Joint
5 Cost Analysis
6 Conclusion
References
Technoeconomic Assessment of Iron Filings Blocks
1 Introduction
2 Materials and Methods
3 Results and Discussion
3.1 Particle Size Distribution of Aggregates
3.2 Sorptivity of Iron Filings Block
3.3 Compressive Strength of Iron Filings Block
3.4 Cost Analysis of Using Iron Filings in Masonry Block Units
4 Conclusion
References
Performance Evaluation of Activated Sugarcane Bagasse for Abattoir Wastewater Treatment
1 Introduction
2 Materials
2.1 Adsorbent Collection
2.2 Wastewater Collection
2.3 Sulphuric Acid
2.4 Distilled Water
3 Experimental Methods
3.1 Adsorbent Development
3.2 pH/TDS/EC, Determination
3.3 Batch Adsorption Study
3.4 Chemical Oxygen Demand (COD) Determination
4 Results and Discussion
4.1 Result
4.2 Discussion
5 Conclusion
References
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Lecture Notes in Civil Engineering
Sanjay Kumar Shukla Sudharshan N. Raman B. Bhattacharjee Priyanka Singh Editors
Recent Developments in Geotechnics and Structural Engineering Select Proceedings of TRACE 2022
Lecture Notes in Civil Engineering Volume 338
Series Editors Marco di Prisco, Politecnico di Milano, Milano, Italy Sheng-Hong Chen, School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, China Ioannis Vayas, Institute of Steel Structures, National Technical University of Athens, Athens, Greece Sanjay Kumar Shukla, School of Engineering, Edith Cowan University, Joondalup, WA, Australia Anuj Sharma, Iowa State University, Ames, IA, USA Nagesh Kumar, Department of Civil Engineering, Indian Institute of Science Bangalore, Bengaluru, Karnataka, India Chien Ming Wang, School of Civil Engineering, The University of Queensland, Brisbane, QLD, Australia
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Sanjay Kumar Shukla · Sudharshan N. Raman · B. Bhattacharjee · Priyanka Singh Editors
Recent Developments in Geotechnics and Structural Engineering Select Proceedings of TRACE 2022
Editors Sanjay Kumar Shukla Edith Cowan University Joondalup, WA, Australia B. Bhattacharjee Indian Institute of Technology Delhi New Delhi, India
Sudharshan N. Raman School of Engineering Monash University Malaysia Subang Jaya, Selangor, Malaysia Priyanka Singh Amity School of Engineering and Technology Amity University Noida, Uttar Pradesh, India
ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-981-99-1885-0 ISBN 978-981-99-1886-7 (eBook) https://doi.org/10.1007/978-981-99-1886-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 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 Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Contents
Improving Railway Track System Using Soil Nails for Heavy Axle Load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Amit Srivastava, Mehwish Hassan, and Rishi Gangwar Finite Element Analysis on Skew Box-Girder Bridges . . . . . . . . . . . . . . . . . Preeti Agarwal and Deepak Kumar Singh
1 15
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shashank Kumar, Neha Bhardwaj, and M. Abdul Akbar
27
Numerically Investigating the Effect of Wind Load on Square and Setback Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vinayak Gautam and Neelam Rani
43
Rockfall Hazard and Its Mitigation with Focus on Rock-Sheds: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Bilal, M. R. Sadique, and M. A. Iqbal
53
Microstructure Investigation and Design of GFRP Reinforced Coastal Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Madhuri Kumari, Sahil Singh Deshwal, and Prakash Gupta
65
Finite Element Analysis and Design of Concrete Bridge Deck Using GFRP Reinforcement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Madhuri Kumari, Prakash Gupta, and Sahil Singh Deshwal
77
“Experimental Study of Variation in Properties of Ultrafine Ground Granulated Blast-Furnace Slag (GGBS) and Steel Fibre Infused Concrete” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rahul Pandit, Prakhar Duggal, and Ravinder Kumar Tomar
87
Analytical Hierarchy Process in the Maintenance Decision-Making of Interlocking Concrete Block Pavements . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Ripunjoy Gogoi, Bhupali Dutta, P. Mahakavi, and Prince Akash Nagar v
vi
Contents
An Effective Use of Agricultural Waste as Silpozz in Concrete . . . . . . . . . 115 Lovely Sabat, Subhajit Dey, Arundaya Sabat, and Minakshi Mishra Influence of Concrete with Partial Replacement of Fine Aggregates with Crumb Rubber and Cement with Silica Fumes . . . . . . . . . . . . . . . . . . 131 Gurwinder Singh and Aditya Kumar Tiwary Partially Replacing Cement with Ground Granulated Blast-Furnace Slag (GGBS) and Fly Ash Changes the Mechanical Properties of Concrete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Hemant Kumar and Vikram Singh Stabilization of Expansive Clays: A Micro-mechanistic Study . . . . . . . . . . 159 T. V. Nagaraju, M. Venkata Rao, B. M. Sunil, and Babloo Chaudhary Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Akshima Gautam, Mahendra Kumar Singar, and Ravi Kant Pareek Comparative Analysis of High-Rise Structure with Diagrid Lateral Load-Resisting System with Composite Members and Base Isolation . . . 177 Harpreet Singh and Aditya Kumar Tiwary Optimization of Mix Design for Concrete with and without Polypropylene Fibre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Shivangi, Priyanka Singh, and Bashar S. Mohammed Use of Stone Dust and Ceramic Waste in Fine Aggregate Replacement in RAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Kuldeep Soni, Shashank Gupta, and Aditya Sharma Prediction of Strength and Stiffness Behavior of Glass Powder Stabilized Expansive Clay Using ANN Principles . . . . . . . . . . . . . . . . . . . . . 211 Shaik Subhan Alisha, T. V. Nagaraju, Kennedy C. Onyelowe, Venkateswarulu Dumpa, and Mantena Sireesha Landslide Hazard Zonation Mapping of Champhai District of Mizoram, India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Lalramngheta, A. Kumar, S. Dangayach, and D. Raj Numerical Analysis of Gravity Dam-Foundation and Comparison with Limit Equilibrium Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 P. Senthil and Hari Dev Experimental and Prediction of Properties of Concrete Using Steel Slag by Taguchi Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 P. Ramachandra, P. S. Niranjan, and Vibha N. Dalawai Properties of Rice Husk Ash and Aluminium Slag-Based Sustainable Geopolymer Bricks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Mahapara Abbass, Gyanendra Singh, and Vanita Aggarwal
Contents
vii
Identification of Critical Project Success (CPS) Factors for Construction Projects in India: An Overview . . . . . . . . . . . . . . . . . . . . . 269 Susan Jamuna Chacko, Charu Nangia, Radhe Shyam Rai, and Vanita Ahuja Effects of Confining Pressure on Intact Rocks’ Anisotropy . . . . . . . . . . . . 287 Bharti Chawre and Sachin Gupta Crack Instigation and Propagation of Transversely Isotropic Biotite Gneiss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Sachin Gupta, Sangeetham Aji, and Mahabir Dixit Analytical Studies on the Fire Resistance of Reinforced Concrete Beams Exposed to Parametric Time–Temperature Curve . . . . . . . . . . . . . 309 V. P. Amar Hebbar, V. Sachin, and N. Suresh Effect of Biopolymer on Water Retention Property of Red Mud . . . . . . . . 325 Shamshad Alam, Sakshi Agrawal, Mahasakti Mahamaya, and Sarat Kumar Das Numerical Analysis of Interference of Machine Foundations on Reinforced Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 P. R. Patil, D. B. Awachat, A. I. Dhatrak, and S. W. Thakare Development of Design Charts for Rectangular Barrettes . . . . . . . . . . . . . 347 Dipika P. Metange, S. W. Thakare, and A. I. Dhatrak Performance of Cantilever Retaining Wall with Deformable Inclusions under Dynamic Loading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 Rajani J. Vyawahare, A. I. Dhatrak, and S. W. Thakare Numerical Analysis of H-Shape Barrette Pile Subjected to Vertical and Lateral Loadings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 A. B. Khan, S. W. Thakare, and A. I. Dhatrak A Study on Effect of Uncertainties in Standardizing Workflow in Construction Firm Using SPSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Asra Fatima, Syed Thihamuddin, and S. M. Abdul Mannan Hussain Application of Artificial Intelligence, Machine Learning, and Deep Learning in Contaminated Site Remediation . . . . . . . . . . . . . . . . . . . . . . . . . 393 K. V. N. S. Raviteja and Krishna R. Reddy Effect of Jute Fiber on Engineering Properties of Soil . . . . . . . . . . . . . . . . . 409 Parvesh Kumar and Fayaz Ahmad Mir Influence of Calcite Veins on the Failure Mode and Mechanical Behaviour of Basalt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419 Dhirendra Kumar and P. S. K. Murthy
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Contents
Optimising Structures for Earthquake Impact in Seismic Prone Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 Daljeet Pal Singh and Divya Srivastava Correlation Between Field and Laboratory Deformability Moduli of Himalayan Sandstones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 P. S. K. Murthy and D. V. Sarwade Study on the Effect of Bottom Ash on the California Bearing Ratio of Clay Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455 Mohammed Faisal Noaman, M. A. Khan, and Kausar Ali Rainfall Impact Force Versus Rise in PWP: A Study of Darjeeling Himalayan Landslide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465 Singh Ankit, P. K. Kundu, and K. S. Rao Design and Cost Analysis of Headed Bars as Mechanical Anchorage System for Reinforced Concrete Beam-Column Joints . . . . . . 473 Shubham Singhal, Ajay Chourasia, and Pallavi Rai Technoeconomic Assessment of Iron Filings Blocks . . . . . . . . . . . . . . . . . . . 485 Abiola Adebanjo, Kehinde Oyewole, Vicky Kumar, Siti Nooriza Abd Razak, Eden Emmanuel, Priyanka Singh, and Adedamola Adebisi Performance Evaluation of Activated Sugarcane Bagasse for Abattoir Wastewater Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495 Ibrahim Mohammed Lawal, Shamsul Rahman Mohamed Kutty, Dalhatu Saleh, Vicky Kumar, Priyanka Singh, Abdullahi Haruna Birniwa, Sule Abubakar, and Ahmad Hussaini Jagaba
About the Editors
Dr. Sanjay Kumar Shukla is Founding Research Group Leader (Geotechnical and Geo-environmental Engineering) at the School of Engineering, Edith Cowan University, Perth, Australia. He is Founding Editor-in-Chief of the International Journal of Geosynthetics and Ground Engineering. He holds the Distinguished Professorship in Civil Engineering at Delhi Technological University, Delhi, VIT University, Vellore, Amity University, Noida, Chitkara University, Himachal Pradesh, and VR Siddhartha Engineering College, Vijayawada, India. He graduated in Civil Engineering from BIT Sindri, India, and earned his M.Tech. in Civil (Engineering Geology) Engineering and Ph.D. in Civil (Geotechnical) Engineering from the Indian Institute of Technology (IIT) Kanpur, India. His primary areas of research interest include geosynthetics and fibers for sustainable developments, ground improvement techniques, utilization of wastes in construction, earth pressure and slope stability, environmental, mining and pavement geotechnics, and soil–structure interaction. He is Author/Editor of 16 books, including seven textbooks, and more than 260 research papers, including 160 refereed journal papers. He has been honored with several awards, including IGS Award 2018 by the International Geosynthetics Society, USA, in recognition of outstanding contribution to the development and use of geosynthetics. He is Fellow of Engineers Australia, Institution of Engineers (India), and Indian Geotechnical Society, and Member of American Society of Civil Engineers, International Geosynthetics Society, and several other professional bodies. Dr. Sudharshan N. Raman is Associate Professor in the School of Engineering, Monash University Malaysia. He obtained his Ph.D. with a focus in structural engineering and infrastructure protective technologies from The University of Melbourne, Australia. He is Past President of the Malaysian Chapter of the American Concrete Institute (Malaysia Chapter—ACI); Fellow of the Chartered Association of Building Engineers (CABE), UK; Member of the American Society of Civil Engineers (ASCE); Member of American Concrete Institute (ACI); and Committee Member of the Civil and Structural Engineering Technical Division of The Institution of Engineers, Malaysia (IEM). Over the years, he has built his reputation as Active
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About the Editors
Researcher in concrete structures and materials and infrastructure protective technologies. He has published extensively in the areas of cement and concrete engineering and structural resilience; has served as Reviewer for prestigious journals in civil and structural engineering and built environment; and currently sits in the editorial boards of three international journals. Prior to joining the academia, he was in employment with an engineering design consultant and a specialist prestressed concrete contractor. Dr. B. Bhattacharjee is Emeritus Professor at the Department of Civil Engineering, IIT Delhi. He obtained B.Tech. (Hons.) degree from IIT Kharagpur, and M.Tech. and Ph.D. degrees from IIT Delhi. He worked for M/s Gammon India for two years after B.Tech. He is Nominated Fellow of Indian Association of Structural Engineers and Member of several professional bodies such as ICI. He was involved in academic activities with several international institutions, namely EPFL, Switzerland; University of Dundee, UK; University of Dresden, Germany; and Catholic University at Leuven, Belgium. He is involved with industry as Consultant also in training. He has supervised 162 M.Tech. and 26 Ph.D. theses till date and currently guiding seven ongoing Ph.D. research projects. He has published more than 150 papers in journals and conferences. He is active in several national committees involving DST, CBRI, NCCBM, Dr. Fixit Laboratory, BIS, etc. A bio-sketch of him titled “A Teacher and a Research worker” under the feature “People” is available in August 2012 issue of ICJ and also under the title “Gems of Structural Engineering” in SEFI. Recipient of ICI lifetime achievement award (North) 2012, he acted as Member of the editorial board of Magazine of Concrete Research and International Journal of 3Rs. He is Guest Editor of ICJ January 2015 issue on “Concrete Research” and also in 2019. Dr. Priyanka Singh is Associate Professor in the Department of Civil Engineering at Amity University Uttar Pradesh (Noida). She obtained her Ph.D. in Structural Engineering from C.U.S. University, Gujarat, and Master’s degree in Structural Engineering from M. S. University, Vadodara, Gujarat. She completed her B.Tech. in Civil Engineering with distinction from M.I.T. in year 2001. She has vast experience of 20+ years out of which 15 years in academics and 5 years in industry. She is Life Member of Indian Concrete Institute (ICI), Indian Society of Technical Education (ISTE), and Indian Association of Structural Engineers (IAStructE). She has presented/published technical papers more than 100 numbers so far on various subjects in national/international seminars/conferences and SCI/Scopusindexed journals. She has served as Reviewer for prestigious journals in civil and structural engineering. She is in the editorial board and scientific committee members of many international and national journals/conferences. She has also contributed as Co-author in chapters published by Springer. She has supervised 43 M.Tech. students and currently guiding five Ph.D. research scholars. Her main research interests are in the areas of innovative and sustainable construction materials, structural health monitoring and remaining service life of structures, green concrete, self-healing concrete, and neural networks in civil engineering domain.
Improving Railway Track System Using Soil Nails for Heavy Axle Load Amit Srivastava, Mehwish Hassan, and Rishi Gangwar
Abstract Purpose: With economic development, countries are now moving towards heavy axle load and high speed trains. Existing railway track system may not be able to support the future demand, and constructing a completely new corridor will be costly and time-consuming which will not fulfill the expectations in a short duration. Design/Methodology/Approach: One of the most widely used techniques to improve the strength and stiffness of soil is soil nailing. The technique has been successfully used in improving the stability of the natural or man-made slope. The concept is applied to improve properties of the subgrade of the railway track system to cater the need of the future heavy axle railway load. Findings: From the results of the numerical analysis, it is concluded that stability of the railway track system is considerable improved, and it can fulfill the needs of the future demand of heavy axle load without much efforts. Originality/Value Practically, the suggested soil nailing technique in existing track formation will not only be less time-consuming but also it will ensure cost saving. Construction of dedicated corridor for heavy axle high speed trains will be a costly affair. Also, provision of providing increased number of blanket layers is costly and consumes natural resources. Soil nailing is quite effective, and it can be implemented in situ without disturbing the existing set up. The solution in which soil nailing technique is proposed in an existing railway track system is unique in nature. Keywords Railway track formation · Soil nailing · Numerical analysis · Heavy axle load · Blanket layer
A. Srivastava (B) · M. Hassan · R. Gangwar Graphic Era University, Dehradun, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_1
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1 Introduction With economic development and increased demand, there is extensive increase in the traffic load and locomotive speed. This has brought tremendous pressure on existing track that are prepared on ballast and conventional in nature. Such ballasted tracks were designed to take axle load of 20–22.5 T which is now increased to 32.5–40 T due to heavy mineral loadings [1]. Conventionally, track systems are improved with improvement in the track superstructure, such as, rails, fastening, and sleepers. Recently, emphasis is also placed on substructure, below ballast, as poor subgrade puts limits on speed and requires costly maintenance. Subgrades are designed to ensure safety against shear failure and to control permanent deformation under repeated axle loads. Subgrade provides support to track system and take stresses under static and dynamic loads under moving loads. Various aspects like development of stresses in the slope due to the induced loads, bearing capacity of the reinforced foundation beds, and appropriate use of geosynthetics to augment their performance are interrelated. Many problems arise due to lack of appreciation of these aspects in the design, construction, and maintenance of such earth structures. India is a developing nation, and it’s growing in all fields including transportation infrastructure. Similar is the situation for other developing nations. With time, demand for high speed trains as well as heavy axle loads is increasing. Existing railways tracks may not be able to cater the growing demand as they were constructed for much lighter traffic. Although, enough work is done to improve the track support system, but they are mainly confined to track super structures, i.e., rails, sleepers, and fastening, etc. Not much work has been done to improve the substructure below sleeper, especially keeping in mind the geotechnical aspects of transportation infrastructure. Provision of blanket layer is considered to be one of the most viable solutions to meet the future demand of high speed and heavy axle load train operations as this avoids restricting speeds. Blanket is considered to be a layer of coarse grained material to improve the load carrying capacity as well as stiffness characteristics of formation for better riding quality and avoiding loss of ballast due to subgrade penetration. Primary function of a blanket layer is to reduce the stress below the tolerable limit on the soil subgrade. Other functions include provision of proper drainage facility, separation layer for ballast and subgrade as well as prevention of subgrade soil from mud pumping. A good blanket material should be strong enough to take static as well as dynamic load including vibrations, apart from having high resilient modulus and resistance to excessive strain accumulation for repeated loadings. Also, a durable material with less sensitivity to moisture variation is preferred over others. A well graded and hard coarse grained material (Cu > 4.0 and Cc 1–3) with 10–12% non-plastic fines (or 5% plastic fines) qualifies for the blanket layer. Traditionally, blanket layer of 1.0 m thickness of specified properties are recommended, which is sometimes difficult to implement and also proved to be very costly affair. In the present study, two-layer blanket system with provision of geosynthetics layers has been studied and it is verified that the same can be used in the top of
Improving Railway Track System Using Soil Nails for Heavy Axle Load
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the formation layer. Study incorporates numerical analysis of the formation layer using commercially available finite element code PLAXIS 2D [2]. It is found that the suggested revision not only improves the strength and stiffness characteristics but also proved to be economical which can be easily implemented in the existing track system. Geogrids have extensively been researched for improving the strength, stiffness, and performance characteristics of the railway track. Researchers [3–7] did extensive research on the performance evaluation of geogrid reinforced railway ballasts. Hussaini and Sweta [8] also provided comprehensive review of work done by several researchers in the field, and they also performed large scale direct shear test as well as tri-axial test to assess the performance of geogrid reinforced ballast layer under cyclic loading. Another researcher provided various strengthening methods for subsoil under existing railways track, such as, deep mixing, grouting, compaction piling, soil nailing, and concrete slab on piles (http://www.railway-research.org/IMG/pdf/i.3. 3.1.1.pdf, last accessed August 30, 2020). In spite of these developments, very little is reported on the numerical analysis of the railways track formation with provision of soil nails and how the deformation pattern will be affected with change in the safety value without and with provision of additional blanket layers. It is now understood that the provision of blanket layer can be made to an extent, and alternate solutions are needed to meet the sustainability aspects as it utilizes natural resources.
2 Literature Review Soil nailing is a well-established technique for enhancing the stability of natural or manmade slope. The first application was made in the year 1972 for a railroad widening project near Versailles, France. In 1975, Germany started using the technique for the construction of soil nail walls. During the same time, USA also started using technique for temporary excavation support system. After extensive research, now we have a comprehensive document on soil nailing by FHWA [9] on the topic “soil nail walls.” Several researchers in the past attempted this technique to stabilize the embankment and slopes for railway corridor for high speed trains. Fewer attempts have been made to use this technique for improving the strength and stiffness characteristics of the subgrade system of railways. The following section discusses the same in light of international research as well as design and development of railway track system in Indian Scenario. Zhang et al. [10] worked on 3D model for the deformation analysis of soil nailed structure using finite element approach. Model took into account the (i) nonlinear behavior of soil, (ii) interaction between soil and nail as well as (iii) construction in stages to predict the soil deformation in stages. Fan et al. [11] determined optimum layout for soil nails to stabilize slopes by using of numerical analysis. Effects of soil nail orientation and geometrical layout on stability were studies using nonlinear finite element approach. The element of safety is used to assess the stability of soil-nailed
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slopes. Zhou et al. [12] numerically built a plane–strain model to simulate loose filled soil slope with nailing and surcharge loading. The numerical model was used to evaluate the effects of a field test that looked at the actions of soil nails in loose fill slopes subjected to surcharge loading. The overall stabilizing mechanism relies on an increase in confining stress along the soil nails near the surcharge region. It was noted that nail forces mobilized near nail heads were much smaller and to the benefits of providing structural grillage device and restrictions in movement under the range of applied surcharge pressure. Rabie [13] has shown the results of instrumentation and monitoring of MSE or soil nail hybrid retaining wall system through 2D finite element models and results of global factor of safety were compared with traditional limit equilibrium approach. It was suggested that limit equilibrium approach should be used for the checking of internal stability and facing connection of the soil nail or mechanically stabilized wall. Rawat and Gupta [14] performed experimental and numerical studies of unreinforced and reinforced soil-nailed slopes having two distinct soil slope angles at 45° and 60° and increasing surcharge load gradually at the crest to study load-settlement response. To stabilize these soil slopes, soil nails were then mounted at three separate inclinations of 0°, 15°, and 30°. Not only the failure pattern matched with the numerical analysis using PLAXIS 3D and experimental studies, the highest increase in load bearing was observed at a 45° soil slope with a 0° nail inclination. Chavan et al. [15] prepared 2D finite element model (FEM) of typical nailed slope to accomplish seismic analysis with due thought to soil nonlinearity, pressure reliance of soil and separation sliding at soil-nail interface. Loading on the nails varies significantly in terms of overburden pressure during the earthquake, and it was found that when sliding and separation was permitted, variation was more in the soil. And it was acting as a rigid block when fixed. In Indian Scenario, Indian Railways (IR) made provision of blanket layer, which was instituted in the year 1978, with thickness varying from 30 cm to 60 cm depending on the quality and shear strength characteristics of the subgrade. Later, with experience, in 1987, thickness of blanket layer was further increased to 1.0 m to cater the need of future demand in terms of traffic density and axle load as well as consideration of factor of safety for drop in shear strength due to repetitive loading. Qualitatively, factors, such as, heavy rainfall and soil quality (poor) were also incorporated, but it was left to engineer in-charge to take a decision on provision of blanket and its thickness as well as provision of sub-ballast (30 cm thick) using locally available materials. These provisions lead to wide variation and ambiguity in the provision and scope for individual judgment and human interventions. In 1993, design charts were prepared to estimate the total thickness of blanket and ballast layer when clay is encountered in subgrade. Design charts were based on different axle loads and threshold strength of soil which was considered to be as 45% of the Unconfined Compressive Strength (UCS). For subgrade soil other than clay, it was recommended to design thickness based on the modulus of elasticity of the soil. In RDSO guidelines (2003), there were recommendations on blanket thickness based on soil type as indicated in Table 1. For heavier axle loads, provision of additional thickness of blanket layer, with superior quality material, 30 cm and 45 cm were
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Table 1 Provision of blanket thickness depending on soil type S. No.
Soil type
Blanket thickness
1
Rocky Bed, GW, SW, Soil with blanket specifications
Not required
2
GP, SP, GM, GM-GC
45 cm
3
GC, SM, SC, SM-SC
60 cma
4
ML, ML-CL, CL, MI, CI, Weathered rock
100 cm
5
Soil with dual symbol, e.g., GP-GC
As per second symbol
a
thickness to 1.0 m, if PI of soil > 7.0
made for axle load 22.5–25 T and 25–30 T, respectively. For detailed discussion on the topic, one may refer report by Research Design and Standards Organization [16–19].
3 Specifications for Blanket Layer On Indian Railways, specifications for suitable blanket material are defined based on particle size distribution, % fines (max), coefficient of uniformity, and coefficient of curvature, as discussed in previous section. In addition to that, hardness of material is measured in terms of Los Angles Abrasion value, with a limit of not more than 40%. Particle size distribution, as suggested, is given in the following Table 2. In addition to that, blanket material should also satisfy the filter design criteria to avoid upward migration of subgrade soil causing fouling of ballast material as given below:
Table 2 Particle size distribution of the blanket material
D15 f < 5.0 D85b
(1)
D15 f > 4.0 to 5.0 D15b
(2)
D50 f < 25.0, D50b
(3)
Size (mm)
% Finer (range)
Size (mm)
% Finer (range)
40
100
2.00
25–50
20
80–100
0.600
12–35
10
65–85
0.425
10–30
4.75
40–70
0.212
5–22
0.075
3–10
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where f stands for blanket layer and b stands for subgrade soil. Further to this, detailed specifications are given, if someone is interested, to provide geosynthetic layer in the form of woven/non-woven geotextiles, geogrids etc. Provision of geotextiles is kept optional and based on recommendations by engineer in-charge under special circumstances. In the present study, numerical studies have proved that provision of three layers of geosynthetics material enhances the strength and stiffness characteristics of the formation layer, and results are discussed separately. Additionally, in case of poor subgrade soil, having load carrying capacity less than 75 MPa, suitable ground improvement technique, such as, replacement with sand, stone column, lime/cement grouting should be adopted. For banks higher than 6 m, slope stability analysis should also be carried out and, if needed, suitable reinforcement technique should be adopted to improve upon the factor of safety. For saturated clay, as subgrade soil, having undrained cohesion value i.e. less than 25 kPa (or SPT value less than 4.0) may require ground improvement techniques like preloading as well as provision of vertical sand drains (or PVC drains) to negate the effect of time dependent consolidation settlement and to ensure long-term stability of the track formation as well as to avoid any distress to settlement. Poor soils having low CBR (< 4.0) or organic soils or soil types CH and MH should either be avoided or should be replaced with high quality material for preparing as subgrade. Other recommendations related to proper drainage conditions, good compaction with achievement of required relative compaction (RC) value, slope protection techniques, etc. should be adopted as per the relevant code of practice or guidelines issued time to time.
4 Performance Studies of Blanket Layer In 2007, field study was conducted to assess the performance of the track formation, without and with provision of blanket layers, on 21 various projects (10 blanketed and 11 non-blanketed) pertaining to different zones of Indian Railways for new lines, doubling as well as gauge conversion. Parameters studied were track attention, ballast penetration, GMT, etc., and it was concluded that blanket layer not only reduces the track maintenance efforts but also ensures less amount of ballast penetration in formations. In order to confirm these findings, in the present study, numerical analysis of the track formation having geometric design as indicated in Fig. 1 was performed. With reference to RDSO [16] guidelines, as depicted in Fig. 2a, b, thickness of blanket layer should be decided based on axle loads, speed, GMT, and soil category. Specifications for blanket materials, geosynthetic materials should be followed as per the laid guidelines. Other issues related to formation width, side slope stability, drainage, and ground improvement should be given due importance. The present study, numerically investigates the performance of railway track system without and with provisions of geogrids and soil nailing in the formation having layer of blanket system. Following five cases, as depicted in Table 3, is analyzed numerically to study the performance of the freight formation under 30 T
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Fig. 1 Track formation profile for dedicated freight corridor of Indian Railways as per RDSO
Fig. 2 a Two layers system of formation top: thickness of blanket material and prepared subgrade for different soil quality of subgrade layer (adapted from RDSO guidelines). b Proposed two layers system of blanketing on track formation for adoption on Indian Railways (adapted from source UIC Code 719R-1994 in RDSO guidelines
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Table 3 Combination of cases studied in the present work Case 1
Freight formation without provision of blanket layer under 30 T axle load
Case 2
Freight formation with provision of blanket layer under 30 T axle load
Case 3
Freight formation with provision of blanket layer under 50 T axle load
Case 4
Freight formation with provision of blanket layer and geogrid under 50 T axle load
Case 5
Freight formation with provision of blanket layer and soil nails under 50 T axle load
and 50 T axle load. Provision of non-woven geotextiles, as separator or filtration, is already made in RDSO [19] guidelines.
5 Methodology, Results, and Analysis 5.1 Numerical Analysis Methodology For the numerical analysis, commercially available finite element code PLAXIS 2D is utilized. Steps for the numerical analysis involve creation of geometry of the problem with given dimensions, assigning properties to each layer as well as boundary conditions, discretization of physical domain of finite element model into 15-noded triangular elements, setting up initial stress conditions and then performing the calculation for getting deformation pattern, stress analysis and other details as desired. For detailed discussion on the numerical analysis procedure and scientific input, one may refer user manual of the code.
5.2 Discussion on Results Figure 3a, b depicts the numerical model developed using the code for Case 1 and Case 2 study. Table 4 provides details of input properties used for embankment formation, subgrade layer, blanket layer, ballast layer as well as concrete sleeper. Soil and ballast layers are assumed to follow Mohr-Coulomb failure hypothesis with non-associated flow rule. Concrete sleeper material is assumed to be elastic. Input properties are, accordingly, taken as provided in Table 5. Figure 4a, b shows comparison of deformation pattern and contours (shading) for the two Cases 1 and 2 analyzed, and the same is presented in tabular form along with factor of safety estimated using strength reduction technique, available as inbuilt option in the numerical tool. Table 6 provides comparative results of the numerical analysis indicating improvement in performance in terms of deformation and factor of safety, without and with
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Fig. 3 a Finite element model of track formation without provision of blanket layer. b Finite element model of track formation with provision of blanket layer Table 4 Input properties of different materials used in the numerical analysis S. No. Physical parameter
Fond. layer SubG. layer Blanket layer Ballast layer Conc. sleeper
1
Cohesion (c, 8 kN/m2 )
9
30
0
–
2
Angle of friction (φ)
30
35
42
35
–
3
Unit weight (γ , kN/m3 )
18
18
20
20
24
4
Elastic 50 modulus (E, MPa)
5
5E + 4
5E + 4
15E + 4
5
Poison’s ratio (v)
0.3
0.37
0.35
0.15
0.30
Table 5 Input properties for geogrid and plate element S. No.
Physical parameter
Plate element
Geogrid element
1
EI (Flexure rigidity)
8500
–
2
EA (Axial stiffness)
5.000E + 06
1.000E + 10
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Fig. 4 a Deformation pattern and contour shading for track formation (without provision of blanket) (maximum displacement = 27.47 mm). b Deformation pattern and contour shading for track formation (with provision of blanket) (maximum displacement = 13.40 mm)
provision of blanket layer under axle load of 30 and 50 T. Case 3 analysis indicated obvious increase in deformation (24.66 mm) and reduction in the factor of safety (1.34) value. Results clearly indicate the existing provision is not sufficient for taking future axle load, and further improvement is needed in terms of either providing geogrids or incorporating soil nailing to improve the performance of freight formation. For Case 4 study, geogrid layer was provided in blanket and subgrade. Input property of geogrid is provided in Table 5. Figure 5a shows the numerical model, and Fig. 5b indicates deformation pattern of freight formation with provision of blanket layer and geogrid under 50T axle load. It is noted that the total deformation is reduced to 19.30 mm, and factor of safety is improved to 1.45. Similarly, for Case 5 study, soil nailing was done to strengthen the weak subgrade layer, and angle of inclination was in such a manner that it provides additional resistance to load and give extra stiffness. Figure 6a shows the numerical model, and Fig. 6b indicates deformation pattern of freight formation with provision of blanket layer and geogrid under 50T axle load. It is noted that the total deformation in this case is also reduced to 14.16 mm and factor of safety as 1.36. Although, Table 6 Comparison of results without and with provision of blanket Without blanket provision 30 T
With blanket provision 30 T
With blanket provision 50 T
Max. deformation
27.47 mm
13.40 mm
24.66 mm
FOS
1.57
1.64
1.34
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Fig. 5 a Numerical model with provision of blanket layer and geogrid. b Deformation pattern with provision of blanket and geogrid (maximum disp. = 19.30 mm)
Fig. 6 a Numerical model with provision of blanket layer and soil nails. b Deformation pattern with provision of blanket and nails under 50 T load (maximum disp. = 14.16 mm)
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much improvement in the factor of safety is not observed due to limitations of c − φ reduction technique [20] that is available as an inbuilt option in the numerical package for the calculation of factor of safety as it does not take into account the strength of nails and its contribution in the strengthening of freight formation.
6 Concluding Remarks • A small difference of safety factor between geogrid and soil nails improvements is observed. It is due to the fact that factor of safety is evaluated using strength reduction technique by successive reduction of cohesion and angle of internal friction parameters. • It is well understood that in the process of nailing, the shear strength parameters get improved which in turn will definitely improve the factor of safety. Since, major distress in railway track system is observed due to settlement; in the present work, it is demonstrated how nailing will help in improving the stiffness of the system and reducing the settlement at higher loads. • Use of either geogrid layer or soil nails provides additional strength and stiffness characteristics, and it is found to be very much useful in weaker subgrade soil. Geogrid layer or nailing helps in reducing the thickness requirements of the blanket layer without compromising on serviceability requirements of the track formation.
References 1. RDSO (2009) Guidelines and Specifications for Design of Formation for Heavy Axle Load, 2009 Research Design and Standards organization Report No. RDSO/2007/GE: 0014, Geotechnical Engineering Directorate, India 2. PLAXIS 2D (2019) Reference manual. Bentley, Delft, The Netherlands 3. Indraratna B, Shanin MA, Salim W (2007) Stabilisation of granular media and formation soil using geosynthetics with special reference to railway engineering. Proc Inst Civil Eng Ground Improv 11:27–43. https://doi.org/10.1680/grim.2007.11.1.27 4. Indraratna B, Thakur PK, Vinod JS (2010) Experimental and numerical study of railway ballast behavior under cyclic loading. Int J Geomech ASCE 10:136–144. https://doi.org/10.1061/(ASC E)GM.1943-5622.0000055 5. Indraratna B, Hussaini SKK, Vinod JS (2012) On the shear behavior of ballast-geosynthetic interfaces. Geotech Test J 35:305–312. https://doi.org/10.1520/GTJ103317 6. Indraratna B, Hussaini SKK, Vinod JS (2013) The lateral displacement response of geogridreinforced ballast under cyclic loading. Geotext Geomembr 39:20–29. https://doi.org/10.1016/ j.geotexmem.2013.07.007 7. Indraratna B, Biabani MM, Nimbalkar S (2015) Behavior of geocell-reinforced sub-ballast subjected to cyclic loading in plane-strain condition. J Geotech Geoenvironmental Eng ASCE 141(1):1–16. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001199 8. Hussaini SKK, Sweta K (2020) Application of geogrids in stabilizing rail track substructure. Front Built Environ 6:1–13. https://doi.org/10.3389/fbuil.2020.00020
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9. FHWA (2015) Soil Nail Walls—reference manual, geotechnical engineering circular No. 7. In: Lazarte CA, Robinson H, Gómez JE, Baxter A, Cadden A, Berg R (eds) U.S. Department of Transportation Publication No. FHWA-NHI-14-007 10. Zhang M, Song E, Chen Z (1999) Ground movement analysis of soil nailing construction by three-dimensional (3-D) finite element modeling (FEM). Comput Geotech 25(4):191–204 11. Fan CC, Luo JH (2008) Numerical study on the optimum layout of soil–nailed slopes. Comput Geotech 35(4):585–599 12. Zhou YD, Cheuk CY, Tham LG (2009) Numerical modelling of soil nails in loose fill slope under surcharge loading. Comput Geotech 36(5):837–850 13. Rabie M (2016) Performance of hybrid MSE/Soil Nail walls using numerical analysis and limit equilibrium approaches. HBRC J 12(1):63–70 14. Rawat S, Gupta AK (2016) An experimental and analytical study of slope stability by soil nailing. Electron J Geotech Eng (EJGE) 21(17):5577–5597 15. Chavan D, Mondal G, Prashant A (2017) Seismic analysis of nailed soil slope considering interface effects. Soil Dyn Earthq Eng 100:480–491 16. RDSO (2003) Report on various methods of Formation rehabilitation on railways. Geotechnical Engineering Directorate, Report No. GE-39, India 17. RDSO (2007) Guidelines for blanket layer provision on track formation with emphasis on heavy axle load train operation, 2007, Research Design and Standards organization report no. Report No. RDSO/2007/GE: 0011, Geotechnical Engineering Directorate, India 18. RDSO (2011) To assess the availability of sugrade soil on various part of India and its cost implication as per specification enumerated in guidelines for Heavy Axle Load (RDSO/2007/ GE: 0014), Report No. RDSO/2011/GE: SR-0029, May 2011, India 19. RDSO (2018) Specification on non-woven Geotextile to be used as separator/filtration in railway formation, 2018, specification number RDSO/2018/GE: IRS-004-Part 1), India 20. Matsui T, San KC (1992) Finite element slope stability analysis by shear strength reduction technique. Soils Found 32:59–70
Finite Element Analysis on Skew Box-Girder Bridges Preeti Agarwal
and Deepak Kumar Singh
Abstract This study examines the effect of skew angle and span-depth ratio on a reinforced concrete simply supported box-girder bridge. The cross-sectional area of the deck is slightly different for different span-depth ratios. The CSiBridge v.20, finite element method (FEM)-based software, is used to carry out this study. The mesh size is determined by the convergence analysis. Both girders are examined for variations in various responses (bending moment, shear force, torsional moment, and vertical deflection) when subjected to a dead load (DL) and an Indian live load (LL). The bridges are designed as straight if the skewness is up to 20°. The deflection is less in skew bridges, and it increases with span-depth ratio. The lowest value of response is obtained for a span-depth ratio of 10. Skew bridges with a higher span-depth ratio generate less bending moment; thus, the skew bridge is more advantageous than the straight bridge. The equations for the ratios of various responses are derived so that the response of skew box-girder bridges having different span-depth ratio may be calculated simply from the straight one. The findings of this study may be relevant to designers for skew bridge analysis. Keywords Reinforced concrete · Skew angle · Span-depth ratio · Dead load · Indian live load · FEM
P. Agarwal (B) Maharishi School of Engineering and Technology, Maharishi University of Information Technology, Lucknow, U.P. 226013, India e-mail: [email protected] D. K. Singh Amity School of Engineering and Technology, AMITY University, Patna, Bihar 801503, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_2
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1 Introduction Numerous bridges have been built, as a result of the tremendous growth in traffic over the last few decades. The majority of bridges are classed as straight bridges because they are orthogonal to the flow of traffic. However, due to economics, aesthetics, and torsional rigidity, the box-girder bridge is now being built and recommended. A skew box-girder bridge’s girders can form any angle other than 90 degrees with the abutment. The inner and outer girders of such bridges are specified by traffic direction, as shown in Fig. 1. The skewness is introduced mostly due to site constraints, mountainous terrain, complex crossings, etc. There are several research available on skew bridges, and this paper contains a number of them. Bakht [1] reviewed the skew bridges which are analysed as straight bridges having the skew angle less than 20°. Khaleel and Itani [2] proposed a technique to determine the moments in the skew slab and skew girder bridges under LL (HS20-44 lane load), using FEM. Khaloo and Mirzabozorg [3] used ANSYS to analyse I-section concrete girder bridges. Menassa et al. [4] used FEM to investigate reinforced concrete bridges subjected to AASHTO HS20 truck loading varying skewness. Mohseni and Rashid [5] used finite element (FE) software SAP2000 to analyse skewed box-girder bridges having multi-cell. The effect of different parameters like span, skew angle, no. of lanes, etc., on the deflection and stress distribution factors is considered in the study. Gupta and Kumar [6, 7] investigated the structural behaviour of skew and skew-curved box-girder bridges exposed to static and dynamic loadings, respectively. Gupta et al. [8, 9] used finite element analysis to determine Fig. 1 Deck of skew box-girder bridge
Finite Element Analysis on Skew Box-Girder Bridges
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the frequencies, stresses, and deflection of RC curved bridges. Agarwal et al. [10, 11] used FEM to examine the response of skew bridges. Further, by altering the skewness and curvature, Agarwal et al. [12, 13] examined the response of a skew-curved bridge. The frequencies of a skewed box-girder bridge were investigated by Agarwal et al. [14]. Agarwal et al. [15] demonstrated the modelling of different box-girder bridges. The aforementioned literature largely focused on the analysis of skew bridges having I-girder and very little with box girders. The impacts of both DL and LL are also not taken into account in the analysis, and very few considered the Indian loading. Based on the above discussion, the purpose of this study is to evaluate the effect of skewness and span-depth ratio on an RC bridge with the same crosssectional characteristics under DL and LL. Many equations are deduced using the statistical technique to assess the bending moment ratio (BMR), shear force ratio (SFR), torsional moment ratio (TMR), and vertical deflection ratio (VDR) of a boxgirder bridge. The BMR is the maximum bending moment (BM) of any span-depth ratio for any skew bridge divided by the maximum BM of a straight bridge with a span-depth ratio of 10. Other ratios are determined in the same way in this study. The analysis using the present approach, i.e. using CSiBridge v.20.0.0 [16] is performed, and it is validated with the published results (Gupta and Kumar [7]). The variation between the published results and obtained results from the present approach is within 5%. Hence, the CSiBridge v.20.0.0 is used for further analysis.
2 Methodology The response of the bridge is studied by varying skewness and span-depth ratios. A span of 35 m is considered in the analysis. Figure 2 and Table 1 show the crosssection and cross-sectional properties of box-girder bridge deck considered in this study. M40 concrete with density, Poisson’s ratio, and Elastic modulus as 25 kN/ m3 , 0.20, and 3.16 × 104 MPa are considered. Fe500 reinforcing steel with density, Poisson’s ratio, and Elastic modulus as 78 kN/m3 , 0.30, and 2 × 105 MPa are used. The girders and slab are modelled using a four-noded shell element with six degrees of freedom (DoF) at each node. Class 70R track loading is employed in this investigation; because when compared to other IRC loadings, Class 70R track loading produces more severe strains and deflection. The load is placed 1.2 m away from the kerb face, as specified by IRC6 [17]. It is observed that the results satisfy the strength and serviceability limits specified in IRC:21-2000 [18]. All bridge deck models are analysed using a simple supported boundary condition. The results converge at a mesh size of 100 mm, so it is used for further parametric investigation. Figure 3 depicts the bridges’ finite element (FE) model.
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Fig. 2 Bridge deck’s cross-section
Table 1 Cross-sectional characteristics of box-girder bridge 1 35
Cross-sectional properties
Span-depth ratio 10
12
14
16
Top flange thickness, ttf (mm)
300
310
320
330
Bottom flange thickness, tbf (mm)
320
340
345
355
Web thickness, tw (mm)
340
350
360
360
7.37
7.23
7.11
7.07
Cross-sectional area, A
(m2 )
(a) Straight bridge
(b) Skewed bridge (θ = 60°)
Fig. 3 FE model of the bridge
3 Result and Discussion 3.1 Effect of Span-Depth Ratio The effects of span-depth ratio and skew angle on various ratios are investigated. The box-girder bridges with span-depth ratio from 10 to 16 are considered, as per the recommendation of IRC 21:2000. Here, the depth of girder is varied, keeping the span length constant, i.e. 35 m to obtain different span-depth ratios. The BMRL/d is the ratio of the maximum bending moment at any span-depth ratio (10, 12, 14, and 16) to the maximum bending moment in a straight bridge at a span-depth ratio of
Finite Element Analysis on Skew Box-Girder Bridges
19
10. All the other ratios are defined and adopted similarly. The cross-sectional area of the deck is slightly different for different span-depth ratios. The cross-sectional area is varied slightly (difference between the minimum and maximum cross-sectional areas of the different decks is only 5%) so that the stresses are within the permissible limit. Figure 4 shows the variation of BMRL/d in both the girders with the span-depth ratio for different skew angles. The graphs are plotted separately for DL and LL. It is observed that for straight bridge the BMRL/d under DL (BMRL/d , DL ) decreases slightly with L/d. This is because the depth is decreased with the increment in L/d. For skewed bridges, the BMRL/d reduces significantly as the L/d increases, and even more so when the skew angle increases. The effects of span-depth ratio and skew angle on BMRL/d,DL are almost the same for both the girders. When L/d is varied, the BMRL/d,DL in both the girders decreases by about 1–20% for the skew angle 0–60°, compared to the straight bridge having L/d of 10. The BMRL/d under LL (BMRL/d,LL ) reduces significantly as the L/d increases, and this impact is more pronounced in the inner girder, however, negligible in the
(a)
(a)
(b)
(b)
Fig. 4 Variation of bending moment ratio with span-depth ratio for different skew angles
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P. Agarwal and D. K. Singh
outer girder. The BMRL/d,LL in both the girders decreases with the increase in the L/d; however, it increases with the skew angle, and the impact is prominent in case of the outer girder. When the L/d of the outer girder is increased from 10 to 16, the BMRL/d,LL of the straight bridge decreases by about 4%. When L/d and skew angle are changed from 10–16 to 10–60°, respectively, the BMRL/d,LL increases by about 3.5–5%, compared to the straight bridge having L/d of 10; while in case of inner girder, it decreases by about 18%. The influence of the L/d on SFRL/d for different skew angles is shown in Fig. 5. The effect is insignificant for a straight bridge under DL (SFRL/d,DL ); while for the skewed bridge, it increases with the L/d and the skew angle. The values of SFRL/d,DL are almost the same for both the girders. The increase in SFRL/d,DL is found to be about 1–64% for L/d 10–16 and skew angle 0–60°, irrespective of the girder type. The SFRL/d under LL (SFRL/d,LL ) slightly increases with the L/d. However, when the bridge becomes skewed, in general, in both the girders, it increases with both span-depth ratio and skew angle, and the effect is more and prominent in outer girder.
(a)
(a)
(b)
(b)
Fig. 5 Variation of shear force ratio with span-depth ratio for different skew angles
Finite Element Analysis on Skew Box-Girder Bridges
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The SFRL/d,LL in the outer girder rises by around 2–25% for a L/d 10–16 and skew angle 0–60° when compared to a straight bridge; however, the comparable increments in the inner girder are about 1–9%. Figure 6 depicts the variation of TMRL/d in both girders, individually under DL and LL, with L/d for various skew angles. It is observed that the TMRL/d under DL (TMRL/d,DL ) increases slightly with L/d for the straight bridge; while for the skewed bridge, it increases considerably with the L/d and increases further with the skew angle. The effect of L/d is more for skewed bridges having an angle greater than 30°. The TMRL/d,DL in both the girders increases by about 7–112% for L/d 10–16 and skew angle 0–60°. The TMRL/d under LL (TMRL/d,LL ) in outer girder decreases with the increment in L/d; while in inner girder, it increases. In both the girders, the behaviour of TMRL/d,LL in the skewed bridge is opposite to that of the straight bridge, in which it changes sign. L/d has a greater effect in the inner girder of both straight and skewed bridges. The impact of skew angle up to 30° on TMRL/d,LL of the outer girder is negligible; while for inner girder, the impact is more. In outer girder, the TMRL/d,LL decreases
(a)
(a)
(b)
(b)
Fig. 6 Variation of torsional moment ratio with span-depth ratio for different skew angles
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by about 8% for bridge having skewness less than 30°; while for skewed bridges having skewness more than 30°, it increases by about 15–125% for outer girder and by about 30–215% for the inner girder. The results of VDRL/d with L/d for different skew angles are shown in Fig. 7. The VDRL/d under DL (VDRL/d,DL ) increases with L/d. However, VDRL/d,DL decreases with increment in the skew angle. The effects are almost the same for both the girders. The deflection in skewed bridges is less than that in the straight bridges, and the least value is obtained at L/d 10. Thus, a skewed bridge is more beneficial than a straight bridge. When L/d is varied, the VDRL/d,DL in both the girders increases by about 144% and 29% for the skew angle 0–60°, the increment being greater for the lesser angles. The VDRL/d under LL (VDRL/d,LL ) increases with L/d in both the girders. The effect of L/d is more in the straight bridge. The impacts of L/d and skew angle are more in the outer girder, and it diminishes with the skewness. VDRL/d,LL is not significant for different skew angles for inner girder. The VDRL/d,LL in the outer
(a)
(a)
(b)
(b)
Fig. 7 Variation of vertical deflection ratio with span-depth ratio for different skew angles
Finite Element Analysis on Skew Box-Girder Bridges
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girder increases by about 135% and 50% for skew angles 0–60°, respectively, when the L/d is changed, while in the inner girder increases by around 90% and 65%.
3.2 Equations for Forces and Deflection For both the girders, a few equations are proposed and presented to analyse the influence of span-depth ratio and skew angle subjected to DL and IRC Class 70 R track load, LL. BMRDL represents the value of BMR under DL, while BMRLL represents the value of BMR under LL. Other ratios are also presented similarly. The followings are the proposed equations: (A) Under DL: • At outer and inner girders, BMRDL = 1.046 − 0.004(L/d) − 4.7888 × 10−5 θ (L/d) − 1.3614 × 10−5 θ 2
(1)
SFRDL = 0.918 + 0.0076 (L/d) + 0.00068θ (L/d)
(2)
TMRDL = 1.052 + 0.0026θ (L/d) − 0.021θ
(3)
VDRDL = 0.645 + 0.00044(L/d)3 + 1.891 × 10−6 (L/d)2 θ 2 − 3.135 × 10−8 θ 4 −1.0123 × 10−5 θ (L/d)3
(4)
(B) Under LL: • At outer girder, BMRLL = 1.094 + 3.773 × 10−5 θ 2 − 0.00067θ − 0.00887 (L/d) SFRLL = 0.958 + 0.00444(L/d) + 0.00025 (L/d)θ
(5) (6)
TMRLL = 0.0211 θ + 2.766/(1.1345 + θ ) − 1.477 − 9.894 × 10−6 θ 3 (7) VDRDL = 0.187 + 0.0181θ + 0.00819(L/d)2 − 0.00197θ (L/d)
(8)
• At inner girder, BMRLL = 1.656 + 0.000275θ + 0.00231(L/d)2 − 0.0893(L/d)
(9)
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Table 2 Verification of the equations Girder L/d
Forces
θ (°) DL
LL
Proposed FEM equation BM (kNm) Outer
10
10
Inner Outer
SF (kN)
14
20
Inner TM (kNm)
Outer
VD (mm)
Outer
% error
14,291
14,280 – 0.08
14,183
14,192
0.06
14,291
14,280 – 0.08
19,056
19,108
0.27
1984
1963
– 1.06
1855
1872
0.89
1984
1963
– 1.06
2805
2812
0.25
1624
1.68
– 1611
– 1680
4.08 1.83
12
40
1597 1597
1624
1.68
– 2827
– 2880
16
30
15.171
14.950 – 1.47
15.104
14.855 – 1.68
15.171
14.950 – 1.47
21.513
21.528
Inner Inner
% error Proposed FEM equation
0.07
SFRLL = 0.963 + 0.00232(L/d) + 0.00082(L/d) + 5.568 × 10−5 θ (L/d) (10) TMRLL = 0.484 + 0.1827θ + 0.0517(L/d) + 0.00535θ (L/d) + 1.623 × 10−5 θ 3 √ L 2 − 0.00312θ − 0.4126 θ d VDRDL = 0.5029 + 0.00539(L/d)2 − 0.000175θ (L/d)
(11) (12)
The influence of span-depth ratio and skew angle on BM, SF, TM and VD is investigated under DL and LL in a RC box-girder bridge. Table 2 shows some of the results from this study, which were used to validate the proposed equations. It is found that the proposed equations are quite correct in obtaining the results.
4 Conclusions A study is conducted to investigate the influence of span-depth ratio on skewed bridges subjected to DL and LL, and the following conclusions are obtained: 1. The influence of skew angle on the forces and deflection ratios is not significant up to 30°; so, they may be treated as a straight. 2. The influence of skewness on forces and deflection of both the girders due to DL is considerable; while, it is not much significant under LL.
Finite Element Analysis on Skew Box-Girder Bridges
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3. The BMRL/d decreases slightly with the increment in L/d for the straight bridge, but it decreases further considerably with the increment in skew angle. The skew bridges having more L/d attract a lesser bending moment; hence, skew bridges are more superior compared to straight one. 4. The SFRL/d increases slightly with the L/d. However, for the skew bridge, in both the girders, it increases with both L/d and skew angle. 5. The TMRL/d in the outer girder decreases as the L/d increases, but it increases in the inner girder. In both the girders, the behaviour of TMRL/d,LL in the skew bridge is opposite to that of the straight bridge. 6. The VDRL/d increases with the L/d. The skew bridge has less deflection than the straight bridge, and the smallest value is attained at an L/d of 10; consequently, the skew bridge may be preferred over the straight bridge.
References 1. Bakht B (1988) Analysis of some skew bridges as right bridges. J Struct Eng 114(10):2307– 2322. https://doi.org/10.1061/(ASCE)0733-9445(1988)114:10(2307) 2. Khaleel MA, Itani RY (1990) Live-load moments for continuous skew bridges. J Struct Eng 116(9):2361–2373. https://doi.org/10.1061/(ASCE)0733-9445(1990)116:9(2361) 3. Khaloo AR, Mirzabozorg H (2003) Load distribution factors in simply supported skew bridges. J Bridge Eng 8(4):241–244. https://doi.org/10.1061/(ASCE)1084-0702(2003)8:4(241) 4. Menassa C, Mabsout M, Tarhini K, Frederick G (2007) Influence of skew angle on reinforced concrete slab bridges. J Bridge Eng 12(2):205–214. https://doi.org/10.1061/(ASCE)1084-070 2(2007)12:2(205) 5. Mohseni I, Rashid AK (2013) Transverse load distribution of skew cast-in-place concrete multicell box-girder bridges subjected to traffic condition. Lat Am J Solids Stru 10:247–262. https://doi.org/10.1590/S1679-78252013000200002 6. Gupta T, Kumar M (2017) Structural response of concrete skew box-girder bridges a state-ofthe-art review. Int J Bridge Eng 5(1):37–59 7. Gupta T, Kumar M (2018) Flexural response of skew-curved concrete box-girder bridges. Eng Struct 163:358–372. https://doi.org/10.1016/j.engstruct.2018.02.063 8. Gupta N, Agarwal P, Pal P (2019) Free vibration analysis of RCC curved box girder bridges. Int J Tech Innov Mod Eng Sci 5:1–7 9. Gupta N, Agarwal P, Pal P (2019) Analysis of RCC curved box girder bridges. J Appl Inov Res 1:153–159 10. Agarwal P, Pal P, Mehta PK (2019) Analysis of RC skew box girder bridges. Int J Sci Innov Eng Tech 6:1–8 11. Agarwal P, Pal P, Mehta PK (2020) Finite element analysis of skew box-girder bridges under IRC-A loading. J Struct Eng (Madras) 47(3):243–258 12. Agarwal P, Pal P, Mehta PK (2020) Parametric study on skew-curved RC box girder bridges. Structure 28:380–388. https://doi.org/10.1016/j.istruc.2020.08.025 13. Agarwal P, Pal P, Mehta P K (2021) Computation of design forces and deflection in reinforced concrete skew-curved box-girder bridges. Struct Eng Mech 78(3):255–267. https://doi.org/10. 12989/sem.2021.78.3.255 14. Agarwal P, Pal P, Mehta PK (2022) Free vibration analysis of RC box-girder bridges using FEM. Sound Vib 56(2):105–125. https://doi.org/10.32604/sv.2022.014874 15. Agarwal P, Pal P, Mehta PK (2022) Box-girder bridges-modelling and analysis. Int J Eng Model 35(1):19–42. https://doi.org/10.31534/engmod.2022.1.ri.02m
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16. CSiBridge manual: a general finite element program for bridges, version 20.0 17. Indian Road Congress (IRC 6) (2016) Standard specification and code of practice for road bridges, section II-loads and stresses, New Delhi, India 18. Indian Road Congress (IRC 21) (2000) Standard specification and code of practice for road bridges, section III-cement concrete (planed and reinforced), 3rd Ed, New Delhi, India
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab Shashank Kumar , Neha Bhardwaj , and M. Abdul Akbar
Abstract Shear wave velocity (SWV) of soil has great significancei in seismicity studies and is an important parameter that is often used in site classification. In this paper, the SWV of Jalandhar, Punjab, is determined using a simplified procedure based on borehole data collected from 70 sites within the district. Using the available equation relating SWV with SPT-N values for Punjab–Haryana region, the average and spot values of SWV are determined for depths of 10 m, 20 m, and 30 m for both corrected and uncorrected SPT-N values. Contour diagrams were plotted using the latitude and longitude of the borehole locations for the 47 boreholes data clustered around the highly populated area of Jalandhar city. Regression equations were developed connecting SWV with depth based on the plots of the points fitted with the power curve. Based on the study, the variation of SWV is obtained along with the classification of soil according to NEHRP. Keywords Shear wave velocity · SPT · N values · NEHRP · Regression analysis · Borehole data · Soil classification
1 Introduction Natural disaster is often unpredictable, and it is impossible to get full control over them. An earthquake occurs due to the movement of plates or rupture of faults, which results in the release of energy in the form of waves through underlying rock [1]. In the Punjab–Haryana region (PHR) of India, deep basins have experienced significant S. Kumar (B) · N. Bhardwaj · M. Abdul Akbar Department of Civil Engineering, Dr B R Ambedkar National Institute of Technology, G.T. Road, Amritsar Bypass, Jalandhar, Punjab 144011, India e-mail: [email protected] N. Bhardwaj e-mail: [email protected] M. Abdul Akbar e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_3
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ground motions produced due to the seismicity associated with the Himalayan and Kashmir region tectonic province. There is a history of high frequency and high magnitude earthquakes in India. The main reason for these earthquakes is the effect of the Indian plate driving toward Asia at a rate of approximately 47 mm/year. From the available geological data, it is observed that almost 60% of Indian land is susceptible to seismic activity of varying intensities which is evident from the fact that more than 600 quakes with a Richter scale magnitude of 5.0 or greater were documented in the past 100 years [2]. The occurrence of earthquakes of large frequency and magnitude in the Himalayan segment, viz. Kashmir, Sikkim as well as in Himalayan arc, Arunachal Pradesh, and Bhutan is already predicted by many researchers [3]. Ambraseys [4] reported that Himalayan region has experienced large-scale damage on account of past earthquakes. Indo-Gangetic Basin (IGB) plays a significant role in the amplification of seismic waves due to deep deposits for forecasting seismic hazards [3]. Bajaj and Anbazhagan [3] concluded that the local sub-surficial layers of soil are among the major factors to be considered for study of causes and damages due to an earthquake. The two conventional examples of seismic excitation that illustrate the consequences of local sub-surficial soil effect due to ground amplification are 1989 Loma Prieta (Mw 8.0) and 1985 Mexico (Mw 8.0) earthquakes. Recent examples of earthquakes that demonstrate the effects of thick soil deposits as well as soft soil availability on site are 2001 Bhuj (Mw 7.7), 1999 Chamoli (Mw 6.8), 2011 Sikkim (Mw 6.9), and 2015 Nepal (Mw 7.8) [5]. The country’s seismic activity has been rapidly increasing in recent years, as earthquakes of large magnitude have occurred in both stable and less seismically active regions. Sub-surficial soil layer plays a significant role in the modification of seismic waves traveling from bedrock toward the site of interest. It is a complex problem for structural designers to estimate and predict the amplification of waves in the form of ground responses due to local sub-surficial soil [6]. The design of any structure against seismically induced waves should be carried out in such a manner that the rupture mechanism of the nearest fault to the site of interest must be considered. The earthquake induced waves propagated through the underlying medium such as rock and sub-surficial layer at the site location are as shown in Fig. 1. Previous studies have shown the importance of the soil layers underneath the site in ground motion amplification due to seismic waves traveling through rocks from the zone of rupture to the site having large distances (say tens of kilometers) [6]. SWV is known to be a valuable criterion to check the dynamic property of soil and rock. From various past earthquakes such as Shillong earthquake (1897), Assam earthquake (1950), Uttarkashi earthquake (1991), Jabalpur earthquakwe (1997), Kashmir earthquake (2005), Bhuj earthquake (2001), and Chamoli earthquake (1999) in India, it is observed that there is a change in topography with respect to change in ground motion features during the seismic motion, and there were great damages to those regions where predominantly loose deposits were present. Due to the variation in sub-surficial soil deposits, complexity in topography is seen, and to check the exact behavior which is complicated, various geophysical and geotechnical investigations
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
29
Fig. 1 Model of ground response mechanism with source of rupture
are performed, and Standard Penetration Test (SPT) is one of them. The work reported in this paper deals with SPT borings at 70 locations with most of them present at the heart of the city of Jalandhar. Empirical calculations are done between SWV (VS ) and reliable static field test data using N values obtained from SPT to estimate SWV or dynamic soil parameters. Both corrected and uncorrected values are taken for the calculation of SWV. The primary objective of this study is to calculate the average SWV values, viz. V Savg10 , V Savg20 , and V Savg30 for 10 m, 20 m, and 30 m depth for Jalandhar using available equation [7] and categorize the soil type as per NEHRP.
2 Study Area, Geology, and Seismicity Punjab shares its border with the union territory of Jammu and Kashmir, Himachal Pradesh, Haryana, Rajasthan, and Pakistan. Geological changes owing to the development of the Himalayas have given a bowl-like structure to Punjab (Fig. 2). The city of Jalandhar occupies 5.3% of the state’s total land area. It is one of the largest and densely populated districts of Punjab state and is a part of the prosperous Doaba region, and it is spread over a gigantic range of 3400 km2 . The region’s geography is typically described as an alluvial plain. Its origins can be traced back to the Sutlej River’s exacerbation work. A seismic zoning map of India has been prepared by a committee of experts under the auspices of the Bureau of Indian Standards, based on tectonic features and past earthquake records. Based on the map, most of the area of Punjab lies in
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Fig. 2 Location of the study area
Zone IV (high-risk zone) and Zone III (moderate risk Zone). The boundary region of Punjab shared with Himachal Pradesh is in close proximity to Zone V, which is a very high-risk zone, and it may be liable to shaking intensities up to IX and above [8].
3 Site Characterization SPT is one of the widely used in situ tests in site classification owing to its simplicity in procedure and testing equipment. SPT is done in the borehole to check the geotechnical properties of sub-surficial soil layers. SPT-N value is popular in site investigation owing to good correlations with an index of soil liquefaction. It provides the basis for site response and seismic microzonation work. In many researches, it has been observed that with the help of SPT-N values, site response parameter and liquefaction potential can be evaluated easily. For this study, a total of 70 borehole locations that lies within the coordinates of 31.1140° N and 75.47477° E to 31.4540° N and 75.67550° E are selected. The data for the sites were obtained from “Empire Geotechnique Pvt. Ltd.” and “MC office Jalandhar.” Both corrected and uncorrected values are taken to check the dynamic properties of soil. The total number of boreholes that lie between 31.28898°N and 75.5238° E to 31.3836° N and 75.6377° E are situated at the heart of Jalandhar, whereas this area is a highly populated area, and the rest of the boreholes lies away from the city. The locations of the borehole are shown in Fig. 3 plotted to scale using the latitude and longitude information of the boreholes. According to the collected soil investigation report for 70 boreholes up to 30 m depth, the approximate fill found in most of the report is around 2.5 m depth because of agricultural land available in these areas. Among the selected sites of Jalandhar city, most of the borehole’s first layer of soil has shown the presence of silt or silty
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
31
Fig. 3 Locations of boreholes
sand (SM), and in a few cases, there is clay of less plasticity (CL) seen. In most of the soil strata, it is observed that there is presence of sand of varying types ranging from poorly graded sand (SP) to silty sand (SM), whereas in a few boreholes, soil found is stratified by the silt and clay, but the major portion available is of sand. The soil profile of three boreholes used in this study with corresponding SPT-N values as a function of depth is shown in Fig. 4. The level of ground water table is 6 m, 6 m, and 8 m in BH35, BH37, and BH45, respectively. Fine sand is in a significant portion in BH35 and BH37 with small layers of sandy silt (CL), clayey silt (CI), and silty sand (SM), whereas silty sand (SM) and clayey silt (CI) are present in significant proportions in BH45 (Fig. 4).
4 V S , V Savg , and Its Correlation with SPT-N Estimation of SWV for near surface material such as soil and rock is of great interest in the field of geotechnical, structural, and earthquake engineering. As per literature review, many researchers have published regression equations between SPT-N and SWV for different regions and soil types. Very few regression equations are available for corrected and uncorrected SPT-N. The assessment of average SWV encourages the classification of sites, and there are numerous studies that support the extrapolation of values of V S beyond the available depth.
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Fig. 4 Soil profile of boreholes
V S and SPT-N correlation for the region studied is developed by Anbazhagan and Bajaj [9], and these correlations are derived for uncorrected and corrected SPTN values for deep soil sites in the IGB by dividing it into three regions, viz. (i) Punjab–Haryana region (PHR), (ii) Uttar Pradesh region, and (iii) Bihar region. These correlation equations derived for the PHR region are based on analysis of 76 V S profiles with SPT-N data, whereas they considered a total of 276 V S profiles with SPT-N data for all three regions. The equation considered in this study for uncorrected SPT-N values is given in Eq. (1). VS = 64.23 ∗ N 0.48 .
(1)
whereas the equation considered in this study for corrected SPT-N value is given by Eq. (2). VS = 62.55 ∗ N 0.54 .
(2)
Here, V S is the SWV, and N is the number of blows. The equations are used to calculate 974 shear wave velocities for all 70 boreholes corresponding to uncorrected and corrected SPT-N values.
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab Table 1 Values of V Savg30 suggested by NEHRP [9]
33
Site class
V Savg30 (m/s)
General description
A
> 1500
Hard rock
B
760–1500
Rock with moderate weathering
C
360–760
Very dense soil and soft rock
D
180–360
Stiff soil
E
< 180
Soft clay soil
For calculation of average SWV at 10 m, 20 m, and 30 m depth (V S30 , V S20 , and V S10, respectively) extrapolation is carried out using spreadsheet. For extrapolation, graphs between calculated V S and depth are plotted for 70 boreholes. Further, for calculation of V S30 , interpolation is done for a few boreholes by the Eq. (3) VSi = VS(i−1) +
(VS(i+1) − VS(i−1) ) ∗ (di − d(i−1) ). (d(i+1) − d(i−1) )
(3)
Average SWV (V Savg ) is calculated by using the Eq. (4) for V Savg30 , V Savg20 , and V Savg10 separately. VSavg =
i=n i=1
di/
i=n di VSi i=1
(4)
where V Savg is the average SWV of soil for 10 m, 20 m, and 30 m depth calculated separately. V Si is the SWV of particular soil strata at depth d i . For the classification of sites, the values of V Savg30 suggested by NEHRP (BSSC 2003) are given in Table 1.
5 Contour Plots When compared to the previous investigation by Anbazhagan and Bajaj, the results of the average SWV obtained from the current investigation are found to be acceptable [10]. In this work, average SWV calculated for 10 m, 20 m, and 30 m depth for all the 70 boreholes are given in Table 4 of Annexure. Out of the 70 boreholes, 47 borehole locations present near the highly populated area of Jalandhar city are analyzed separately using contour plots made in Surfer. The contours are plotted based on the observation that the values lies in the range between latitude 31.28898° N and 31.38363° N and longitude in between 75.5238628° E and 75.637786° E. The values of V S10 contours lie in between 205.65 m/s and 366.77 m/s, and the average of same obtained is 252.11 m/s. The values of V S20 contours lie between 257.24 m/ s and 433.77 m/s, and the average is 283.11 m/s. The values of V S30 contours lie between 279.37 m/s and 512.93 m/s, and the average is 308.99 m/s (Fig. 5a–c)). In
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S. Kumar et al.
Fig. 5 a Contour of average SWV for 10 m depth (uncorrected SPT-N). b Contour of average SWV for 20 m depth (uncorrected SPT-N). c Contour of average SWV for 30 m depth (uncorrected SPT-N)
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
35
Fig. 5 (continued)
the contour diagrams, the plus sign (+) represents the locations of boreholes. As seen from the scale of the contour, higher velocities are denoted by darker colors (starting from red), and lower velocities are denoted by lighter colors (with gray color for the least). Similarly, for corrected SPT-N values, the values of V S10 lie between 239.57 m/ s and 401.14 m/s, and the average is 298.01 m/s. The values of V S20 contours lie between 275.55 m/s and 493.54 m/s, and the average is 344.04 m/s. The values of V S30 contours lie between 285.18 m/s and 593.22 m/s, and the average is 379.29 m/ s (Fig. 6a–c). As per the results of avg SWV at 10 m, 20 m, and 30 m, the value of V Savg30 is highest, and the corresponding value is least for 10 m depth.
6 Comparison Between Uncorrected V S and Corrected V S For comparing the values of SWV for uncorrected and corrected SPT-N, a graph is plotted with both for all 70 boreholes data containing 974 values. A correlation coefficient (R2 ) of 0.7121 is obtained for uncorrected SPT-N as shown in Fig. 7 (red color) and 0.3336 for corrected SPT-N (blue color). The average values of uncorrected VS determined for shallow depth are slightly higher than the average of values of corrected V S ; whereas after 12 m, it is lesser (Table 2). The minimum of SWV calculated from corrected SPT-N is greater than the corresponding value for uncorrected SPT-N. However, the maximum of SWV calculated
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S. Kumar et al.
Fig. 6 a Contour of average SWV for 10 m depth (corrected SPT-N). b Contour of average SWV for 20 m depth (corrected SPT-N). c Contour of average SWV for 30 m depth (corrected SPT-N)
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
37
Fig. 6 (continued) 800
Uncorrected y = 160.62x0.3047 R² = 0.7121
700
Vs (m)
600
Corrected y = 207.45x0.1377 R² = 0.3336
500 400 300
Uncorrected Vs
200 Corrected Vs
100 0 0
10
20
30
Depth (m) Fig. 7 Correlation between uncorrected versus and corrected N with depth
40
38
S. Kumar et al.
Table 2 Summary of SWV for corrected and uncorrected value
SPT-N
Average V Savg (m/s)
Minimum V S (m/s)
Maximum V S (m/s)
Uncorrected
330.18
108.83
582.97
Corrected
338.95
132.23
718.91
from corrected SPT-N is lesser than the maximum of SWV calculated from uncorrected SPT-N as given in Table 2. In this study, correlation coefficient for uncorrected SWV data is 0.7121, which is far better than the correlation coefficient for corrected SWV data, i.e., 0.3336. Hence, for the study of the SWV or average SWV, uncorrected SPT-N values are more precise as compared to the corrected SPT-N values.
7 Average Shear Wave Velocity The average SWV for the Jalandhar region is calculated for 10 m, 20 m, and 30 m depth. The summary of the results obtained are given in Table 3. The values of average SWV are calculated at different depths, i.e., 10 m, 20 m, and 30 m, and the values of average SWV at 10 m depth varies from 205.65 m/s to 366.76 m/s for uncorrected; whereas for corrected, it varies from 239.57 m/s to 401.14 m/s. The values of average SWV at 20 m depth vary from 257.24 m/s to 433.77 m/s for uncorrected which is slightly higher than the values of average SWV at 10 m and 20 m; whereas for corrected, it varies from 275.55 m/s to 493.54 m/s which is also higher. The values of average SWV at 30 m depth vary from 279.37 m/ s to 512.93 m/s for uncorrected which is higher from both; whereas for corrected, it varies from 285.18 m/s to 593.22 m/s. Table 3 Summary of average SWV for corrected and uncorrected SPT-N values SPT-N Uncorrected
Corrected
V Savg
Average V Savg (m/s)
Minimum V Savg (m/s)
Maximum V Savg (m/s)
V S10
252.11
205.65
366.77
V S20
283.16
257.24
433.77
V S30
308.99
279.37
512.93
V S10
298.01
239.57
401.14
V S20
344.04
275.55
493.54
V S30
379.29
285.18
593.22
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
39
8 Conclusions In this study, based on collected geotechnical data (SPT-N) from 70 boreholes and using the correlation available for Punjab–Haryana region, an attempt is made to check SWV for Jalandhar up to 30 m depth. Further, average SWV for 10 m, 20 m, and 30 m depth is estimated using correlation derived for PHR. This relation is dependent on corrected and uncorrected values. The work is carried out to open the doors for empirical calculation and achieve the values of SWV as well as average SWV with the use of region-specific correlation between SPT-N and SWV. This procedure will eliminate the cost for practical test required for the calculation of SWV such as multichannel analysis of surface waves (MASW) and spectral analysis of surface waves (SASW). The work is carried out for a highly populated area, and the value obtained can be used for ground response analysis as well as microzonation of the same area. From the average SWV result obtained for Jalandhar, it is concluded that the average SWV lies in between 270 and 593 m/s which means that according to NEHRP, the study sites belong to class C and D, i.e., very dense soil and stiff soil, respectively.
Annexure See Table 4. Table 4 Values of V Savg10 , V Savg20 , and V Savg30 in units of m/s corresponding to uncorrected and corrected SPT-N values at 70 locations BH
Latitude
Longitude
Uncorrected V Savg10
V Savg20
V Savg30
V Savg10
V Savg20
V Savg30
BH1
31.34461
75.56272
244.55
306.73
368.20
258.78
292.32
329.45
Corrected
BH2
31.35077
75.56354
313.81
377.46
437.64
327.83
353.20
384.96
BH3
31.35742
75.56239
232.92
298.48
342.54
236.35
295.31
333.95
BH4
31.38363
75.54201
312.13
371.51
426.20
327.92
346.40
370.81
BH5
31.3032
75.56969
297.22
319.56
364.31
313.08
306.49
329.55
BH6
31.31611
75.57632
225.98
307.27
378.02
234.25
292.65
341.60
BH7
31.31176
75.58923
261.14
257.24
279.37
272.38
249.20
256.01
BH8
31.31033
75.57855
249.62
315.86
360.92
258.60
301.11
328.00
BH9
31.32153
75.5876
280.34
347.59
406.88
293.38
325.24
356.86
BH10
31.30737
75.59306
291.85
416.08
512.93
307.58
407.57
480.92
BH11
31.29716
75.58919
249.48
326.81
391.26
249.48
326.81
391.26 (continued)
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S. Kumar et al.
Table 4 (continued) BH
Latitude
Longitude
Uncorrected V Savg10
V Savg20
Corrected V Savg30
V Savg10
V Savg20
V Savg30
BH12
31.30084
75.59265
262.26
340.31
403.47
273.06
321.42
357.75
BH13
31.30357
75.60007
205.65
303.01
389.56
214.90
296.50
367.89
BH14
31.31414
75.60322
270.53
347.73
411.86
281.23
328.34
365.46
BH15
31.28898
75.59628
247.34
314.09
372.73
253.54
292.40
328.40
BH16
31.34913
75.55048
287.40
341.32
388.91
300.58
317.95
337.72
BH17
31.36228
75.54149
259.11
342.35
415.40
271.25
324.66
371.69
BH18
31.36574
75.56676
245.10
309.70
367.23
254.27
290.56
324.08
BH19
31.37636
75.58831
251.48
349.57
432.23
262.91
335.75
393.10
BH20
31.33412
75.61986
291.82
394.18
477.14
304.60
380.35
438.68
BH21
31.32522
75.63357
252.13
322.46
378.68
264.39
303.48
343.71
BH22
31.30695
75.63085
274.38
333.03
383.60
284.81
310.52
334.39
BH23
31.343664
75.5238628
252.34
313.14
355.77
258.04
293.27
315.81
BH24
31.343664
75.5238628
238.49
304.42
351.64
243.76
285.83
313.22
BH25
31.304519
75.5875257
232.95
308.62
367.23
240.33
292.91
331.38
BH26
31.304519
75.5875257
236.08
307.68
361.16
245.28
292.41
324.96
BH27
31.304519
75.5875257
247.71
316.17
366.98
255.65
298.16
327.36
BH28
31.316714
75.5810368
223.51
278.34
322.33
232.05
262.49
285.89
BH29
31.316714
75.5810368
225.91
283.00
329.00
235.25
268.12
293.61
BH30
31.114029
75.47477
259.93
325.46
369.80
260.62
301.56
327.12
BH31
31.114029
75.47477
265.09
321.57
358.50
265.56
299.25
319.67
BH32
31.337287
75.5632261
238.56
294.62
345.97
241.18
273.36
286.34
BH33
31.337287
75.5632261
250.07
303.16
331.81
252.87
278.15
278.43
BH34
31.337287
75.5632261
227.53
290.68
319.83
230.83
263.66
277.68
BH35
31.453047
75.6719625
283.57
320.72
357.57
277.02
284.80
295.68
BH36
31.452411
75.6744523
253.48
300.96
338.05
258.18
271.24
283.75
BH37
31.452405
75.6755047
248.55
290.27
331.13
252.06
265.29
278.32
BH38
31.451648
75.6737101
261.92
309.36
348.51
265.97
275.33
288.28
BH39
31.450493
75.6754173
270.13
315.84
353.83
266.01
280.30
293.90
BH40
31.451451
75.6734035
236.27
271.02
308.88
236.36
248.55
263.61
BH41
31.451322
75.6722449
241.84
281.24
320.60
246.83
259.97
274.68
BH42
31.451018
75.6717375
220.37
260.14
326.57
229.42
248.09
256.98
BH43
31.450469
75.6713547
226.01
264.16
288.06
236.61
252.55
263.94
BH44
31.449928
75.6713509
241.54
281.07
317.85
241.14
265.51
277.71
BH45
31.449835
75.6719711
253.27
301.22
351.45
255.27
280.04
331.48
BH46
31.449831
75.6726131
226.70
279.39
315.57
236.00
262.21
275.79
BH47
31.449653
75.6721908
244.76
281.47
320.30
253.86
287.82
297.95 (continued)
Estimation of Shear Wave Velocity at Varying Depth for Jalandhar, Punjab
41
Table 4 (continued) BH
Latitude
Longitude
Uncorrected V Savg10
V Savg20
Corrected V Savg30
V Savg10
V Savg20
V Savg30
BH48
31.449512
75.6731791
249.94
291.92
328.88
249.81
269.68
283.49
BH49
31.448754
75.6732158
275.12
306.20
338.02
262.54
275.56
291.06
BH50
31.449843
75.6737288
246.27
284.15
324.98
242.56
260.39
275.77
BH51
31.449688
75.6740328
277.76
313.31
352.41
280.03
287.57
299.51
BH52
31.449202
75.6738399
240.14
277.88
317.96
242.63
259.16
273.78
BH53
31.449199
75.6744608
239.50
287.38
327.95
236.46
255.35
272.09
BH54
31.44869
75.6752149
274.87
322.44
361.10
272.12
282.82
295.45
BH55
31.449728
75.675075
266.06
312.82
349.68
261.39
279.60
290.49
BH56
31.331793
75.5699732
217.05
272.09
298.42
225.96
250.85
257.45
BH57
31.331729
75.5698253
210.55
262.28
288.32
216.90
240.27
247.67
BH58
31.330954
75.5689954
212.20
265.32
291.57
219.11
243.41
250.51
BH59
31.330885
75.5677614
227.04
278.60
303.90
233.86
255.09
260.71
BH60
31.331037
75.5674062
218.01
269.70
296.41
224.98
246.49
254.32
BH61
31.332022
75.5696053
219.75
273.05
298.93
227.19
250.88
257.43
BH62
31.331269
75.5678236
216.07
269.08
295.17
223.53
247.11
254.00
BH63
31.331269
75.5678236
216.32
271.10
298.04
223.47
249.20
256.90
BH64
31.330562
75.56809
222.01
274.74
300.66
230.04
252.70
259.06
BH65
31.331971
75.567025
366.77
433.77
418.55
250.39
250.24
257.64
BH66
31.331971
75.567025
213.56
266.59
293.71
220.26
244.36
252.73
BH67
31.345742
75.5593952
249.10
289.16
322.00
253.35
273.67
280.97
BH68
31.318796
75.637786
280.55
307.19
351.78
285.67
302.91
321.02
BH69
31.360864
75.5776117
271.34
332.20
360.77
265.80
307.42
330.81
BH70
31.299983
75.5749809
329.29
360.99
391.27
335.19
355.19
361.85
References 1. Khan S, Waseem M, Khan MA, Ahmed W (2018) Updated earthquake catalogue for seismic hazard analysis in Pakistan. J Seismolog 22(4):841–861. https://doi.org/10.1007/s10950-0189736-y 2. Bhutani M, Naval S (2020) Assessment of seismic site response and liquefaction potential for some sites using borelog data. Civil Eng J 2103–2119. https://doi.org/10.28991/cej-2020-030 91605 3. Bajaj K, Anbazhagan P (2019) Comprehensive amplification estimation of the Indo Gangetic Basin deep soil sites in the seismically active area. Soil Dyn Earthq Eng 127:105855. https:// doi.org/10.1016/j.soildyn.2019.105855 4. Ambraseys N (2000) Reappraisal of north-Indian earthquakes at the turn of the 20th century. Curr Sci (Special Edition) 79 9(10):1237–1250 5. Rajendran K, Parameswaran RM, Rajendran CP (2017) Seismotectonic perspectives on the Himalayan arc and contiguous areas: inferences from past and recent earthquakes. Earth Sci Rev 173:1–30. https://doi.org/10.1016/j.earscirev.2017.08.0
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6. Phanikanth VS, Choudhury D, Rami Reddy G (2011) Equivalent-Linear seismic ground response analysis of some typical sites in Mumbai. Geotech Geol Eng 29(6):1109–1126. https:/ /doi.org/10.1007/s10706-011-9443-8 7. Bajaj K, Anbazhagan P (2019) Seismic site classification and correlation between VS and SPT-N for deep soil sites in Indo-Gangetic basin. J Appl Geophys. https://doi.org/10.1016/j. jappgeo.2019.02.011 8. IS 1893(Part 1): 2002 Criteria for earthquake resistant design of structure (Part-1) fifth revision. BIS Manak Bhavan, New Delhi, p 110002 9. FEMA 450 (2003) NEHRP recommended provisions for seismic regulations for new buildings and other structures. Part 1, Fema 450:338 10. Anbazhagan P, Bajaj K (2017) Site response study of a deep basin contagious to active region-an application to Punjab-Haryana Region. In: Indian geotechnical conference (December2017), pp 1–4
Numerically Investigating the Effect of Wind Load on Square and Setback Building Vinayak Gautam and Neelam Rani
Abstract Tall buildings have the major advantage of saving wide space by assimilating the settlements vertically which otherwise would have been spread over a large area. But with increasing heights of the buildings, the severity of wind loads also increases which may cause damage to the building as well as cause discomfort to the occupants. Hence, to reduce these effects, aerodynamic modifications are introduced in the buildings. This paper aims to present the effect of aerodynamic modification introduced in a basic square building in the form of setback. The numerical study was performed in ANSYS software based on Computational Fluid Dynamics (CFD) technique. Two models were compared in this study: a basic square model and a single-sided setback model with setback of 10% of lateral dimension provided at mid height. The variation of mean wind pressure coefficients along the face centerlines has been compared for both the square and setback buildings. Wind incidence angle (WIA) was varied from 0° to 90° at every 30° interval. It is observed that setback model registered the maximum increment in suction of 5.28% over the square model for the height where setback has been provided at the wind incidence angle of 90°. The values of pressure coefficients were found to be close to zero for two different faces at the wind incidence angles of 30° and 60°, respectively, for both the buildings. Keywords Tall buildings · Setbacks · CFD · Wind pressure coefficients
1 Introduction Computational Fluid Dynamics (CFD) is a science based upon the Finite Volume Method (FVM) to simulate the fluid flows variables [1]. It is a numerical approach that solves the equations pertaining to the fluid flow to obtain the desired results [2–4]. V. Gautam (B) · N. Rani Dr. B.R. Ambedkar National Institute of Technology, Jalandhar, India e-mail: [email protected] N. Rani e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_4
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The usage of CFD has increased in the last three decades owing to the several advantages it offers over the conventional methods of studying wind effects, namely wind tunnels [2, 5, 6]. CFD is cheaper, less time-consuming, and overcomes the many limitations that wind tunnels tend to possess [3, 4]. With the rapid growth in the construction of tall buildings, growing demand is being felt to counter many challenges that high-speed winds pose to buildings from the perspective of occupant comfort as well as structural safety [7–11]. Bairagi and Dalui [12] compared the area-average pressure coefficients of a square and a single-sided setback building having similar plan dimensions and height for attacking wind angles of 0° and 90°. Bairagi and Dalui [13] compared the pressure coefficients, force coefficients, torsional moment coefficient, and roof pressure variation of a square, single-sided, and double-sided setback building having similar plan area and height. Incident wind angles were changed from 0° to 180° at every 15° interval. Roy and Bairagi [14] conducted CFD analysis of wind pressure, velocity, and force coefficient on a stepped unsymmetrical plan-shaped building with wind incidence angle changing from 0° to 360° at 45° intervals. The objective of this study was to compare the external pressure coefficients obtained from wind tunnel testing and CFD simulation. Further, they compared pressure coefficient values with various wind codes and standards. Tominaga et al. [15] described the guidelines given by Architectural Institute of Japan (AIJ) for analyzing pedestrian wind environments around buildings using CFD. These guidelines were derived from several cross-comparisons between CFD results, wind tunnel tests, and measurements on field for seven test cases. Roy et al. [16] conducted CFD analysis on a square-shaped tall building. Wind pressure measurements were made at various wind incidence angles from 0° to 90° at every 15° intervals and compared the CFD results to results obtained from wind tunnel experiments. This paper aims to first validate the atmospheric boundary layer (ABL) velocity profile at the domain inlet obtained from the CFD simulation of a basic square model given in the experimental paper of Tanaka et al. [17]. Validation of mean pressure coefficient contours is also achieved by CFD simulation on faces of the square model at 0° WIA against the contours given in the experimental paper for the same. Finally, a study was carried out on the effect of wind load on the square and single-sided setback model under WIA of 0° to 90° at 30° intervals.
2 Model Specifications Two models were analyzed in this study: square and single-sided setback. The basic square model is based on the 1/1000 reduced scale of actual square-shaped building adopted in the wind tunnel experiment by Tanaka et al. [17]. The dimensions of the scaled model are L (length) = 50 mm and B (breadth) = 50 mm and H (height) = 400 mm; thus, L/B ratio is 1 and H/L = 8 (see Fig. 1a). The setback model is based on this square model, whose height and plan dimensions are similar to that of square model (see Fig. 1b). The setback is provided on one face (Face A) at height H/2 = 200 mm by a distance of 0.1 L = 50 mm. Angles of wind incidence were changed
Numerically Investigating the Effect of Wind Load on Square …
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Roof R-1 Face B Face C
Face-B
Roof R-2 Face A-2
H=400
Face C
Roof R-A Face A Face D Face A-1
0°
75° 15° 30° 45° 60°
90°
(a)
0°
15°
Face D
30° 45° 60° 75°
90°
(b)
Fig. 1 a Square and b single-sided setback model geometry (all dimensions are in mm)
in an anti-clockwise direction from Face A to Face D; 0° when wind acts parallel to Face A and 90° when wind acts parallel to Face D. The naming of the faces of the square building has been done as Face A, Face B, Face C, and Face D, and the faces of single-sided setback building have been named Face A-1, Face A-2, Face B, Face C, and Face D. Figure 1 shows the square and single-sided setback models used in this study under various WIA.
3 Fluid Domain and Meshing The fluid domain which has been modeled around the building model is as per the recommendations of Franke et al. [2] and Tominaga et al. [15]. The domain inlet and outlet are positioned at 5H and 15H from windward and leeward surfaces of the building, respectively. The top and sides of the domain have been positioned at 5H from the building (see Fig. 2). The distance from inlet of the domain to the building represents the area upwind of the building [15]. The top surface of the domain is provided at 5H to avoid the flow of artificial acceleration over the building, and the boundary layer height determined by the terrain category of surroundings is represented by the total height of the computational domain [2, 15]. The distancing of the domain sides from the building is kept sufficiently large to ascertain that the blockage ratio is within the allowable value of 3% [2, 15, 18]. Hexahedral meshing is as per the recommendation of Frank et al. [2] as hexahedrals result in smaller truncation errors and display better iterative convergence. ICEM-CFD software is
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5H 5H 5H
5H
Fig. 2 Domain used in the study
Fig. 3 Meshing at a domain’s bottom surface and b setback meshing
used for hexa meshing of the building model and fluid domain. 2,883,757 elements are generated because of hexahedral meshing. Figure 3 shows the hexahedral mesh generated.
4 Boundary Conditions and Solver Settings The specification of the inlet has been done as a velocity inlet, and the outlet has been specified as a pressure outlet with 0 Pa relative pressure for the fluid domain [7, 8]. Side walls and top walls of the domain are free slip, and bottom wall is no slip and rough. The building walls are no slip and smooth. The velocity profile specified at the inlet of the domain is power law and as per the experiment (see Fig. 4) given by Eq. (1) [15, 19].
Numerically Investigating the Effect of Wind Load on Square … Fig. 4 Experimental and CFD velocity profiles
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2 z/H
1.5 1 0.5 0 0
0.5
1
1.5
U/UH CFD
(
z U (z) = U (z 0 ) z0
)α
Experimental
,
(1)
where U (z) is the mean wind speed at height z, U (z 0 ) (11.8 m/s) is the mean wind speed at the reference height z 0 (0.4 m), and α (0.27) is the power law exponent which depends upon the terrain roughness. The turbulence model used is Realizable k − ε [20] which is an advancement over the standard k-ε model, to help achieve closure for governing equations. The k-ε turbulence models compute the value of eddy viscosity by solving the transport equations for turbulent kinetic energy (k) and dissipation rate (ε). The two transport equation (k) and energy dissipation rate (ε) are defined at inlet of domain given by Eqs. (2) and (3) [15] (
) σu2 (z) + σv2 (z) + σw2 (z) ∼ k(z) = = (I (z)U (z))2 2 ( )α−1 1 z U (z 0 ) 2 ε(z) = Cμ k(z) α , z0 z0
(2)
(3)
where k(z) is the turbulent kinetic energy, σu (z), σv (z)andσw (z) are standard deviation values of velocity fluctuations, I (z) is turbulence intensity, ε(z) is dissipation rate, and Cμ is model constant (= 0.09). ANSYS Fluent solver is used for simulation. The solver solves the governing equations of fluid flow at the centroid of each control volume by discretizing the differential equations, to finally obtain the flow parameters using iterative solution method. “Pressure-based” solver type is chosen for incompressible flow and simulation is steady state. SIMPLE pressure–velocity coupling algorithm is selected, and second-order differencing is used for pressure, momentum, and turbulence equations. The residual value is adopted to be 0.0001 for convergence. Along with residuals, force coefficients were also used for monitoring the convergence. The hybrid initialization method used and the number of iterations chosen was 1000.
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5 Validation Study The velocity profile of Tanaka et al. [17] used for pressure measurement experiment is compared with the CFD velocity profile at the inlet of the domain. The CFD velocity profile appears to be in good agreement with the experimental profile as shown in Fig. 4. The mean pressure coefficient contours obtained from CFD simulation on the faces of the square building model at 0° wind incidence angle are compared with the experimental result by Tanaka et al. [17] as shown in Fig. 5. The contour images in the experimental paper have been shown in the range of − 1 to 1 (Fig. 5b) [17], and also the contour images were shown for a portion of the face, i.e., the region of the face which was covered by the pressure taps; contours on the lower 50 mm from the bottom, the upper 10 mm and 5 mm from the side edges of the faces have not been shown; hence, the CFD pressure coefficient contour images have also been shown following similar constraints in Fig. 5a. The values of mean pressure coefficients on Face A (front) are all positive, and they reduce from top to bottom. The maximum value as per the color band is between 0.9 and 0.8; however, in the experimental paper, the contour values on the front face appear to be varying from slightly greater than 0.8 at the upper region to around 0.4 at the lower region which resembles the contour diagram shown here. The values on Face B (left face) and Face D (right face) in the experimental contours ranged from around − 0.9 at the top to around − 0.6 at the bottom which is similar to the contour diagrams shown here. It
Face D
Face A Face C
(a)
Face B
Face D
Face A Face C Face B
(b)
Fig. 5 Comparison of mean pressure coefficient on faces of the square model obtained from a CFD simulation and b Tanaka et al. [17]
Numerically Investigating the Effect of Wind Load on Square …
49
is to be noted that contours on Face B and Face D mirror each other since the wind flow is symmetric about the symmetry plane of the square building in the direction of wind flow. Face C (rear face) in the experimental contour varies from around − 0.7 at the upper portion and increases up to around − 0.3 toward the downward direction which is also similar to the CFD contour.
6 Results and Discussion For this study, the behavior of the pressure coefficients along the centerlines of the faces of both square and single-sided setback buildings has been studied. The centerline was drawn from the bottom of the faces, i.e., z = 0 mm up to z = 390 mm height, 10 mm short of the model roofs. The wind incidence angles of 0°, 30°, 60°, and 90° were chosen for comparison of mean pressure coefficients about the centerlines drawn on building faces. The vertical centerline on the setback face of the setback model was drawn from z = 0 mm to z = 200 mm on Face A-1 and then from 200 to 390 mm on Face A-2. Face A-1 and Face A-2 have been collectively referred to as Face A in this discussion. Figure 6 shows the mean pressure coefficient plots along the centerlines for Face A, Face B, Face C, and Face D of square (SQ) and setback (SB) models. The curves for the setback model closely follow that of the square model. However, a kink can be seen at 200 mm height, where a setback has been provided on the Face ASB of the setback model. The percentage change in mean pressure coefficient values at 200 mm centerline’s height for setback face (Face A-2) over the mean pressure coefficient values at the same height of square model’s Face A was observed to be − 1.53%, − 2.38%, and − 6.43% for 0°, 30°, and 90° wind incidence angles. For Face A, the maximum positive mean pressure coefficient value was seen at 0° WIA for the centerlines of both square and setback models, whereas the maximum negative (suction) pressure coefficient values were observed at 90° WIA for both models. The centerline mean pressure coefficient values on Face B of both models gradually become less negative with the increase in wind incidence angle. This is because Face B is transitioning from being a side face to a leeward face. The values of pressure coefficients for Face B centerlines remained negative throughout all the wind incidence angles. The least negative (least suction) values were observed at 90° WIA for both square and setback, whereas the most negative (greatest suction) pressure coefficient values were observed at 30° WIA for both models. The values on the centerline of Face C become more negative as the angle changes from 0° to 90°. The values on Face C remain negative throughout, with the least suction observed at WIA of 0° for both the models, whereas the maximum suction was observed at the angle of 60° both models. The values on centerlines of Face D become more positive as WIAs increase from 0° to 90°. The maximum mean pressure coefficients for Face D of both models are
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z (m)
-1.00
-1.00
0.35 0.3
0.25
0.25
z (m)
0.30 0.20
0.2
0.15
0.15
0.10
0.1
0.05
0.05
0.00 -0.50 0.00
0.50
1.00
-1.00
-0.50
0 0.00
CP
CP
(a) 0°
(b) 30°
0.35
0.35
0.3
0.30
0.25
0.25
z (m)
z (m)
0.35
0.2
0.15
0.1
0.10
0.05
0.05 0.50
1.00
-1.00
1.00
0.50
1.00
0.20
0.15
0 -0.50 0.00
0.50
0.00 -0.50 0.00
CP
CP
(c) 60°
(d) 90°
Fig. 6 Pressure coefficients along the centerline for a 0°, b 30°, c 60°, and d 90°
observed at the WIA angle of 90°, whereas the maximum suction was observed at 0° for both models. The maximum positive centerline mean pressure coefficient for the square model was observed at Face A for 0° WIA, and the same value was observed at Face D for 90° WIA, whereas the maximum suction mean pressure coefficient was observed on the centerline of Face C at 60° WIA. The maximum positive centerline mean pressure coefficient for the setback model was observed on Face D at 90° WIA, whereas the maximum suction mean pressure coefficient was observed for Face C at 60° WIA. Face B observed maximum % changes between centerline values of square
Numerically Investigating the Effect of Wind Load on Square …
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and setback for the angle of 30° WIA, the setback recorded a maximum decrease in suction at this angle over the square model of 23.61% at the height of 150 mm.
7 Conclusions This study compared the results of CFD simulation and those of the experimental paper written by [17] for validation, and it was observed that results obtained from CFD analysis closely followed that of the experimental paper. The study was further expanded, and comparisons were drawn in between mean pressure coefficient values observed along the centerlines of four faces of the square model and corresponding faces of the setback model. Some key observations were: • The maximum difference between the mean pressure coefficients of square and setback models for Face A at the height where the setback is provided was observed at 90° WIA where the setback building observed a decrement in the suction of 6.43%. • The maximum positive mean pressure coefficient value observed by the setback model was on Face D at 90° WIA. • At 60° WIA, both square and setback models observed near zero centerline pressure coefficient values for Face A; whereas at 30° WIA, they observed near zero centerline pressure coefficient values for Face D. • The maximum suction observed for both square and setback models was approximately at 390 mm height on Face C for 60° WIA. • Face B observed maximum percentage changes between centerline values of square and setback, and for the angle of 30° WIA, the setback recorded a maximum decrease in suction at this angle over the square model of 23.61% at the height of 150 mm.
References 1. Ma AM, Odhah A (2022) ANSYS from drawing to results visualization—CFD and FEA. https://www.udemy.com/course/ansys-proffessional-drawing-to-results-visualiza tion-cfd-and-fea/learn/lecture/17290362#overview. Accessed 23 Mar 2022 2. Franke J et al (2004) Recommendations on the use of CFD in wind engineering. In: COST action C14 impact wind storm city life Urban Environ, no January 3. Jameel A (2017) Study of wind forces on hip roof buildings using computational fluid dynamics techniques. Z.H. College of Engineering & Technology, Aligarh Muslim University 4. Weerasuriya AU (2013) Computational fluid dynamic (CFD) simulation of flow around tall buildings. Eng J Inst Eng Sri Lanka 46(3):43. https://doi.org/10.4038/engineer.v46i3.6784 5. Mendis P, Mohotti D, Ngo T (2014) Wind design of tall buildings, problems, mistakes and solutions. In: 1st International conference infrastructure failures consequences, no September 2015
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6. Vincent OC (2017) Application of computational fluid dynamics model in high-rise building wind analysis—a case study. Adv Sci Technol Eng Syst 2(4):197–203. https://doi.org/10.25046/ aj020426 7. Rajasekarababu KB, Vinayagamurthy G, Selvi Rajan S (2019) Experimental and computational investigation of outdoor wind flow around a setback building. Build Simul 12(5):891–904. https://doi.org/10.1007/s12273-019-0514-8 8. Sharma A, Mittal H, Gairola A (2018) Mitigation of wind load on tall buildings through aerodynamic modifications: review. J Build Eng 18:180–194. https://doi.org/10.1016/j.jobe. 2018.03.005 9. Irwin PA (2009) Wind engineering challenges of the new generation of super-tall buildings. J Wind Eng Ind Aerodyn 97(7–8):328–334. https://doi.org/10.1016/j.jweia.2009.05.001 10. Irwin P, Kilpatrick J, Robinson J, Frisque A (2008) Wind and tall buildings: negatives and positives. Struct Des Tall Spec Build 17(5):915–928. https://doi.org/10.1002/tal.482 11. Ilgin HE, Gunel MH (2017) Aerodynamic modifications and tall buildings. Metu Jfa 2007/2 242:17–25 12. Bairagi AK, Dalui SK (2018) Comparison of pressure coefficient between square and setback tall building due to wind load. In: Proceeding 11th structural engineering convention—2018, pp WA1–WA6 13. Bairagi AK, Dalui SK (2018) Comparison of aerodynamic coefficients of setback tall buildings due to wind load. Asian J Civ Eng 19(2):205–221. https://doi.org/10.1007/s42107-018-0018-3 14. Roy K, Bairagi AK, Water KM, Authority S, Bengal W (2016) Wind pressure and velocity around stepped unsymmetrical plan shape tall building using CFD simulation—a case study. Asian J Civ Eng 17 15. Tominaga Y 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. https://doi. org/10.1016/j.jweia.2008.02.058 16. Roy AK, Verma SK, Lather S, Sood M (2014) ABL airflow through CFD simulation on tall building of square plan shape. In: 7th National conference wind engineering (NCWE 2014), no November, 2014. https://doi.org/10.13140/2.1.3230.2881 17. Tanaka H, Tamura Y, Ohtake K, Nakai M, Y. Chul Kim (2012) Experimental investigation of aerodynamic forces and wind pressures acting on tall buildings with various unconventional configurations. J Wind Eng Ind Aerodyn 107–108:179–191. https://doi.org/10.1016/j.jweia. 2012.04.014 18. Baetke F, Werner H, Wengle H (1990) Numerical simulation of turbulent flow over surfacemounted obstacles with sharp edges and corners. J Wind Eng Ind Aerodyn 35:129–147 19. Architecture Institute of Japan (2019) AIJ Recommendations for Loads on Buildings (2015) Architectural Institute of Japan 20. Shih T, Liou W, Shabbir A, Yang Z, Zhu J (1995) A new k-∈ eddy viscosity model for high reynolds number turbulent flows. Comput Fluids 24(3):227–238
Rockfall Hazard and Its Mitigation with Focus on Rock-Sheds: A Review A. Bilal , M. R. Sadique, and M. A. Iqbal
Abstract Rockfall is a major problem in hilly areas. Falling rocks pose a great threat to human life and engineering structures lying in these areas. To mitigate the hazard of rockfall, broadly two types of techniques are used, namely active protection and passive protection techniques. Active protection measures are those which prevent the rockfall from occurring, whereas the passive protection measures reduce the damage caused by the falling rocks. Rock-sheds have been considered as important passive protection structures for protection of roads or railway lines in the areas which are prone to rockfall. Rock-sheds are made up of reinforced concrete with a cushion layer on the top. The cushion layer can be of soil or a composite layer having soil and some other energy absorbing material which can dissipate the impact energy of rockfall and protect the rock-shed. In this paper, the work done by various researchers in the field of rockfall hazard has been discussed. Various active and passive protection measures to mitigate the rockfall hazard along with the benefits and limitations of each measure have been highlighted. The paper focuses on the importance and design of rock-sheds. Therefore, this paper discusses the design of rock-shed, the thickness of cushion layer, the various energy absorbing materials which can be used as cushion layer, and the research carried out in this area so far, and exhaustive conclusion has been made in this regard. Keywords Rockfall · Active protection · Passive protection · Rock-shed · Soil cushion
A. Bilal (B) University Polytechnic, Aligarh Muslim University, Aligarh 202002, India e-mail: [email protected] M. R. Sadique Department of Civil Engineering, Aligarh Muslim University, Aligarh 202002, India M. A. Iqbal Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_5
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1 Introduction Rockfall is a major problem in hilly regions. Falling of heavy rocks causes a great loss of life and infrastructure. Rockfall often occurs in a series of damage, especially as a secondary disaster caused by an earthquake. Rockfall can cause roads to become unusable and blocked. Rockfall damage then makes rescuing injured people and rebuilding disaster areas more difficult [1]. Recently, in the regions of Himachal Pradesh, a large boulder fell on the deck of a bridge and the entire bridge collapsed [2]. Such incidents have occurred in the past also, in India, and as well as in other countries. A great loss of life and infrastructure may occur as the frequency, and magnitude of rockfall is unpredictable [3]. Various examples of loss of life and infrastructure can be found in [4–6]. For protection of structures in high risk areas and to safeguard human life, it is necessary to assess the risk posed by rockfall. Rockfall can be defined as a very rapid movement of slope where the material of bedrock is separated from the steep slope and descends by rolling, falling, sliding, or bouncing [7]. The size of rocks may vary from small gravel size particles to large masses of rocks. Rockfalls involve falling of individual rocks or several blocks of rocks, where there is little interaction among the individual rocks. Rockfall can be termed as a small landslide in which individual or superficial rocks are detached from the face of the cliff [8]. Movement of large rock masses can be a consequence of rockfall; however, such large-scale mass rock movements are called rockslides or rock avalanches [9, 10]. Very often, rockfall leads to initiation of debris streams, which can be catastrophic [11, 12] (Fig. 1). Fig. 1 Modes of descent of rocks for different degrees of slope [3, 49]
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2 What Causes Rockfall? Rockfall begins when the rocks split from the bedrock slopes, which in the case of a cliff face, are the source region of rockfall. The bedrock slopes are subject to varying degrees of weathering, which leads to rock fracture and joint opening and thus promote rockfall. The promotion of rockfall depends upon the environmental factors which are responsible for chemical and physical weathering and also on the type of bedrock [12, 13]. In addition to the rate of weathering, the occurrence of rockfall also depends upon the trigger mechanisms. There have been numerous discussions on rockfall trigger mechanisms and factors in the literature. The rockfall trigger mechanisms can be categorized into rockfall promoters and the ultimate cause that starts the rockfall. However, it is difficult to draw a clear line to distinguish between them because it often happens that a particular activity, like frost cracking, accelerates weathering and results in rockfall. The slope morphology and the rock’s surroundings are the two most crucial aspects in determining whether or not the rock will fall. A common promoter and cause of rockfall is the frost-thaw activity [4, 14–18]. The rockfall in the Canadian Rocky Mountains was observed by [19], and he came to the conclusion that the rockfalls especially occur on glacially over-steepened rock slopes are subjected to periodic freezing and thawing. The magnitude of these rockfalls was small, and the frequency was high, which is a typical behavior of rockfalls in Alpine areas [18, 20, 21]. Another cause of rockfall was described by [22–24]. They investigated the connection between rockfall and seismic activity and came to the conclusion that seismic activity can trigger rockfall. According to reports, there are many different things that can trigger rockfalls, including earthquakes, abrupt snow melt, rainstorms, root growth and wedging, and stress relief after deglaciation. Nearly 400 slope movements have been reported, with rockslides and rockfalls accounting for the majority of these [25–27]. Additionally, human activity can also cause hill-slopes to become less stable, which might result in rockfall. Although it is a minor contributor in comparison with other geological causes, it may become significant while undercutting slopes during quarrying or excavation for construction activities [8]. Rockfall has been attributed to a variety of causes, although the majority of the time, geological, topographical, and climatological elements interact to cause rockfall.
3 Rockfall Mitigation Techniques Different measures can be adopted for protection against rockfall. Examples of such measures are construction of catch or barrier fences and restraining nets [28–30], but these measures deteriorate with time and are also expensive. Maintaining forest stands having explicit protection function, or a protection forest, can be a sustainable and cost-effective measure in some cases [31, 32]. However, it is unclear if active forest
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Anchored Mesh System
Rockfall Mitigation Techniques
Active Protection
Rock-Bolts
Grouted Dowels
Catch Areas
Rock-sheds
Passive Protection
Flexible Barriers Earthen Embankments Rigid Barriers Rigid Walls Attenuators
Fig. 2 Different rockfall mitigation techniques
management will be useful in preventing rockfall in many mountainous locations. The rockfall mitigation measures can be classified into active protection and passive protection. Figure 2 shows a flow chart presenting the different types of rockfall mitigation techniques.
3.1 Active Protection Active protection measures are those which enhance the stability of slopes and improve the anchorage of rocks and thus prevent the rockfall from occurring. Anchored mesh system, rock bolts, and grouted dowels are some of the active protection measures.
3.1.1
Anchored Mesh System
Anchored mesh system improves the stability and strength of the rock mass. It is an active flexible system for prevention of rockfall. It consists of anchor rods, mesh, and supporting cables, to cover the slope and strengthen it as shown in Fig. 3. The
Rockfall Hazard and Its Mitigation with Focus on Rock-Sheds: A Review
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Fig. 3 Typical active flexible protection [33]
arrangement of anchor rods, supporting cables, and the mesh makes a cover over the slope and thus strengthens the slope by the action of prestressing force. When a rock falls down, it comes in contact with the mesh, which stretches and transfers the force to supporting cables, which in turn transfer it to the ground through anchor rods [33, 34].
3.1.2
Rock Bolts
Large jointed planes cause failure of rock mass, leading to rockfall. The rocks within the host rock mass can be strengthened by using rock bolts. The rock bolts enhance the naturally occurring self-supporting ability of rock mass. The studies on the rock bolts have been conducted by many researchers. Researchers have studied the properties and behavior of rock bolts using numerical simulations [35–38], experiments and field tests [39–43], and analytical methods [44–47].
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Grouted Dowels
Grouted dowels are used for increasing the stability of critical rock wedges. The dowels are deformed bars of steel, grouted in the rock. The dowel head is fitted with a faceplate and nut. The hole is drilled using a drilling machine. The hole is then filled with cement mortar, and the dowel bar is inserted in the hole [48].
3.1.4
Passive Protection
The engineered structures which are constructed at some distance from the rockfall source to intercept or divert the falling rocks are called passive rockfall protection structures. They are called passive protection structures because they do not prevent the rockfall from occurring, rather they mitigate the effects of rockfall. Some of the passive rockfall protection structures are flexible barriers, catch areas, attenuators, rigid barriers, and rock-sheds.
3.1.5
Catch Areas
Catch areas are ditches built with the goal of stopping and capturing falling boulders so they do not damage the vulnerable building. They are sometimes called rockfall catchment areas. Catch areas may be provided along the transportation routes where sufficient space is available and slope geometry is favorable. Where there is limitation of space, barrier systems may also be combined with catch areas. Catch zones have been built since quite some time now, and in the USA, research on their performance and design has been conducted [49, 50].
3.1.6
Rigid Barriers
Rigid barriers have sufficient stiffness to bear the impact of the falling rock, and they either contain or deflect the rockfall [7]. The rigid barriers can be constructed very close to the structure that are intended to be protected, as the deformation in the rigid barriers is very small. Different barriers have different energy absorbing capacities depending upon the geometry and material properties. Some basic type of barriers are: Earthen embankments (berms or bunds): Earthen dams can withstand large amounts of energy and can be constructed in various sizes and geometry. In these structures, the energy is absorbed by deformation and internal compaction. Rigid walls: Structural walls may be constructed to contain the falling rocks. They may be made of different materials like concrete, timber, steel, etc. The crosssectional area of such walls is less than earthen embankments and can be used along with the catch areas. These structures should be checked for stability.
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3.1.7
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Flexible Barriers
Flexible barriers are the flexible net structures which dissipate the energy of rock by deforming vertically. These are lightweight structures which are supported on cables and poles [33].
3.1.8
Attenuator Systems
Attenuator systems are flexible fence systems that reduce the energy of falling rocks instead of capturing them. The energy of the falling rocks is reduced by slowing the speed and controlling the trajectory. When the energy of the falling rocks is reduced, they can be captured by other passive protection measures. Attenuators are made using flexible net barriers which are appropriately installed to incorporate a draped net tail. Thus, the falling rock is forced to pass beneath the tail of the attenuator, losing energy by repetitive impacts with the ground. Though attenuator systems are in practice for more than two decades now, the design is based on judgment and empirical methods. There have been efforts to develop a design procedure for attenuator systems, and full scale testing of these systems have been carried out in North America and Europe [51–53].
3.1.9
Rock-Sheds
Rock-sheds are reinforced concrete slabs covered with cushion layer, which are constructed over highway stretches or railway lines located beneath a steep slope, where there are frequent rockfalls. Rock-shed can also safeguard the structure against avalanches. Rock-shed structures are used as a passive protection measure to mitigate the rockfall hazard. Rock-sheds must be able to withstand the impact load of rockfalls in order to safeguard roads and other infrastructure [1]. Direct impact of rockfall on the reinforced concrete (RC) rock-shed can damage the rock-shed. Structural damages are expensive to repair and cause a lot of unwanted disturbances in the operation of the structure for which the rock-shed has been constructed. Therefore, a cushion is provided above the RC slab, so that the impact load is dissipated over a larger area [54, 55]. Therefore, the rock-shed structure and the cushioning material comprise the two components of the impact-resistant system of a rock-shed. Conventionally, a sand cushion is provided above the RC slab to provide required damping. When it is desired to increase the impact resistance/absorption capacity of the rock-shed, the thickness of the sand cushion is increased. But, as the sand cushion increases, the dead load on the rock-shed also increases. And if the sand cushion is kept thin, then the impact load will not be mitigated appropriately, causing damage to the rock-shed. Hence, there is a need to find some cushion for the rock-shed structure which can mitigate the impact load and which is light in weight so that the total dead load on the rock-shed is reduced sufficiently.
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Fig. 4 a RCrock-shed structure having soil cushion and b RC rock-shed with composite cushion layer of soil and foam [1]
Therefore, if we use the industrial waste or rubber tire waste in making the cushion for rock-shed, then it will be a great step toward sustainable development. Zhao et al. [1] used sand and EPE to form a cushion layer and performed experiments on rock-sheds. Firstly, the authors proposed a new cushion layer, consisting of sand and expanded polystyrene (EPS) or EPE, for enhancing the durability and reducing dead load. The performances of EPE and EPS were compared by performing uniaxial compression tests. Finally, the authors conducted rockfall impact tests on sizable rock-shed models using sand, sand-EPS, or sand-EPE as different cushion layers (Fig. 4). Sand-EPE, according to the authors, was found out to be the best cushion layer for preventing rockfall impact and safeguarding rock-shed structure. Yan et al. [56] studied the effect of the shape of rock on the behavior of RC slabs under impact. Firstly, the authors established ellipsoidal models to approximately simulate the falling rocks and employed sphericity as the representative index of the rock shape. Then, they simulated the impact of falling rocks on the RC rock-sheds with different shapes of rocks. Finally, they analyzed impact forces and the dynamic responses of reinforced concrete slabs, while the focus was on the effects of rock’s shape and the impact angle. It was demonstrated that the sphericity and impact angle have considerable effects on the impact force and the dynamic response of reinforced concrete slabs. Thus, assuming the rocks to be spherical can lead to designing unsafe rock-sheds. To explore the impact of rockfall on rock-shed slabs, Zhong et al. [57] carried out nine rounds of impact tests with energies varying from 50 to 250 kJ. Spherical blocks were made to fall on the test models of the shed slabs. The slabs had a cushion layer of sand, the thickness of which was varied to study the effect of thickness of sand cushion on impact resistance. It was found that an increase of sand cushion thickness from 60 to 90 cm increases the impact resistance by 25–30%. The authors also compared the impact resistance of Ultra High Performance Concrete (UHPC) and normal C40 concrete and found that the use of UHPC doubles the impact resistance of the shed slab. The authors also created a SPH-FEM model using LS-DYNA to
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simulate the performed experiments. The model was validated using published experimental results and Japanese calculation technique. The primary controlling factors for damage evaluation were velocity and rock mass, and a damage assessment index based on punched bearing capacity was developed.
4 Conclusions Exhaustive review has been carried out on the rockfall hazard and its mitigation techniques. On the basis of this review, following conclusions can be drawn: (i) Falling of heavy rocks poses a great threat to the human life as well as the civil engineering structures, and thus, protection measures should be adopted at maximum locations. (ii) Proper study needs to be carried out before deciding which protection measure has to be adopted at a particular location. (iii) Active protection techniques prevent the rockfall from occurring and hence are very useful for mitigating the rockfall hazard, but these techniques cannot be used everywhere, and these can also be uneconomical in many cases. Therefore, passive protection techniques are used for protection of structures. (iv) Rock-sheds are passive protection structures used for protecting roads and railway lines. Rock-sheds are reinforced concrete structures having a soil cushion at the top. Other energy absorbing materials can also be used along with soil to act as cushion of rock-sheds. (v) Further research is needed to evaluate the energy absorption capacities of different materials which can be used in the cushion layer of rock-sheds.
References 1. Zhao P, Xie L, Li L, Liu Q (2018) Song Yuan”, Large-scale rockfall impact experiments on a RC rock-shed with a newly proposed cushion layer composed of sand and EPE”. Eng Struct 175:386–398. https://doi.org/10.1016/j.engstruct.2018.08.046 2. https://www.theguardian.com/world/video/2021/jul/26/nine-dead-after-boulder-destroys-bri dge-in-northern-india-video 3. Luuk KA (2003) Dorren, 2003, A review of rockfall mechanics and modelling approaches. Prog Phys Geogr 27(1):69–87 4. Porter SC, Orombelli G (1980) Catastrophic rockfall of September 12, 1717 on the Italian flank of the Mont Blanc Massif. Zeitschrift für Geomorphologie N.F. 24:200–218 5. Bunce, C. M., Cruden, D. M., & Morgenstern, N. R. (1997). Assessment of the hazard from rockfall on a highway.Canadian Geotechnical Journal, 34(3), 344–356. https://doi.org/10.1139/ t97-009 6. Badger TC, Lowell S (1992) Rockfall control in Washington State. In: Rockfall prediction and control and landslide case histories, transportation research record, vol 1342. National Research Council, Washington, pp 14–19
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7. Turner AK, Schuster RL (eds) (2012) Rockfall characterisation and control. In: Transportation research board. National Academy of Sciences, 658 pp 8. Selby MJ (1982) World atlas of geomorphic features. New Zealand Geogr 38:31–31. https:// doi.org/10.1111/j.1745-7939.1982.tb00975.x 9. Abele G (1994) Large rockslides: their causes and movement on internal sliding planes. Mt Res Dev 14:315. https://doi.org/10.2307/3673727 10. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Keith Turner A, Schuster RL (eds) Landslide investigation and mitigation. Transportation Research Board, Special Report 247. National Academy Press, Washington, pp 36–75 11. Hsü K (1975). Catastrophic debris streams (Sturzstroms) generated by rockfalls. Geol Soc Am Bull 86. https://doi.org/10.1130/0016-7606(1975)862.0.CO;2 12. Schumm S, Chorley R (1964) The fall of threatening rock. Am J Sci 262:1041–1054. https:// doi.org/10.2475/ajs.262.9.1041 13. DAY R (1997) Case studies of rockfall in soft versus hard rock. Environ Eng Geosci III:133– 140.https://doi.org/10.2113/gseegeosci.III.1.133 14. Grove JM (1972) The incidence of landslides, avalanches and floods in western Norway during the Little Ice Age. Arct Alp Res 4:131–138 15. Porter SC, Orombelli G (1981) Alpine Rockfall Hazards: Recognition and dating of rockfall deposits in the western Italian Alps lead to an understanding of the potential hazards of giant rockfalls in mountainous regions. Am Sci 69(1):67–75. http://www.jstor.org/stable/27850249 16. Coutard JP, Francou B (1989) Rock temperature measurements in two alpine environments: implications for frost shattering. Arct Alp Res 21:399–416 17. McCarroll D, Shakesby RA, Matthews JA (1998) Spatial and temporal patterns of late Holocene rockfall activity on a Norwegian talus slope: a lichenometric and simulation-modeling approach. Arct Alp Res 30(1):51–60 18. Matsuoka N, Sakai H (1999) Rockfall activity from an alpine cliff during thawing periods. Geomorphology 28(3):309–328 19. Gardner JS (1983) Rockfall frequency and distribution in the Highwood Pass area Canadian Rocky Mountains. Zeitschrift für Geomorphologie 27(3):311–324 20. Hungr O, Evans SG, Hazzard J (1999) Magnitude and frequency of rock falls and rock slides along the main transportation corridors of southwestern British Columbia. Can Geotech J 36(2):224–238 21. Jomelli V, Francou B (2000) Comparing the characteristics of rockfall talus and snow avalanche landforms in an Alpine environment using a new methodological approach: Massif des Ecrins. French Alps Geomorphol 35(3):181–192 22. Zellmer JT (1987) The unexpected rockfall hazard. Bull Assoc Eng Geol 24(2):281–283 23. Bull WB, King J, Kong FC, Moutoux T, Phillips WM (1994) Lichen dating of coseismic landslide hazards in alpine mountains. Geomorphology 10(1):253–264 24. Vidrih R, Ribicv icv M, Suhadolc P (2001) Seismogeological effects on rocks during the 12 April 1998 upper Socva Territory earthquake (NW Slovenia). Tectonophysics 330(3):153–75 25. Wieczorek GF, Jäger S (1996) Triggering mechanisms and depositional rates of postglacial slope-movement processes in the Yosemite Valley, California. Geomorphology 15:17–31 26. Wieczorek GF, Nishenkod SP, Varnes DJ (1995) Analysis of rockfalls in the Yosemite Valley, California. In: Daemen, JJK, Schultz RA (eds) Rock mechanics: proceedings of the 35th US symposium. Balkema, Rotterdam, pp 85–89 27. Wieczorek GF, Snyder JB, Waitt RB, Morrissey MM, Uhrhammer RA, Harp EL, Norris RD, Bursik MI, Finewood LG (2000) Unusual July 10, 1996, rock fall at Happy Isles, Yosemite National Park, California. Geol Soc Am Bull 112(1):75–85 28. Hearn G, Barret RK, McMullen ML (1992) CDOT Flexpost rockfall fence development, testing, and analysis. In: Rockfall prediction and control and landslide case histories. Transportation research record 1343. National Academy of Sciences, Washington DC, pp 23–29 29. Spang RM, Sönser T (1995) Optimized rockfall protection by ‘ROCKFALL’. In: Fuji T (ed) Proceedings of the 8th international conference on rock mechanics, 25–30 Sept 1995. A.A. Balkema, Tokyo, Rotterdam, pp 1233–42
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30. Peila D, Pelizza S, Sassudelli F (1998) Evaluation of behaviour of rockfall restraining nets by full scale tests. Rock Mech Rock Eng 31(1):1–24 31. Kienholz H, Mani P (1994) Assessment of geomorphic hazards and priorities for forest management on the Rigi north face Switzerland. Mt Res Dev 14(4):321–328 32. Motta R, Haudemand J-C (2000) Protective forests and silvicultural stability. An example of planning in the Aosta valley. Mt Res Dev 20(2):74–81 33. Yang J, Duan S, Li Q et al (2019) A review of flexible protection in rockfall protection. Nat Hazards 99:71–89. https://doi.org/10.1007/s11069-019-03709-x 34. Azzoni A, Freitas MHD (1995) Experimentally gained parameters, decisive for rock fall analysis. Rock Mech Rock Eng 28(2):111–124 35. Deb D, Das KC (2011) Modelling of fully grouted rock bolt based on enriched finite element method. Int J Rock Mech Min Sci 48(2):283–293 36. Hatzor YH, Feng X-T, Li S, Yagoda-Biran G, Jiang Q, Hu L (2015) Tunnel reinforcement in columnar jointed basalts: the role of rock mass anisotropy. Tunn Undergr Space Technol 46:1–11 37. He L, Zhang QB (2015) Numerical investigation of arching mechanism to underground excavation in jointed rock mass. Tunn Undergr Space Technol 50:54–67 38. Jia P, Tang CA (2008) Numerical study on failure mechanism of tunnel in jointed rock mass. Tunn Undergr Space Technol 23(5):500–507 39. Feng X, Zhang N, Yang S, He F (2018) Mechanical response of fully bonded bolts under cyclic load. Int J Rock Mech Min Sci 109:138–154 40. Ge X, Liu J (1988) Study on the shear resistance behaviour of bolted rock joints. Chin J Geotech Eng 10(1):8–19 41. Grasselli G (2005) 3D behaviour of bolted rock joints: experimental and numerical study. Int J Rock Mech Min Sci 42(1):13–24 42. Jalalifar H, Aziz N (2010) Experimental and 3D numerical simulation of reinforced shear joints. Rock Mech Rock Eng 43(1):95–103 43. Salcher M, Bertuzzi R (2018) Results of pull tests of rock bolts and cable bolts in Sydney sandstone and shale. Tunn Undergr Space Technol 74:60–70 44. Cai Y, Esaki T, Jiang Y (2004) A rock bolt and rock mass interaction model. Int J Rock Mech Min Sci 41(7):1055–1067 45. Cao C, Ren T, Cook C, Cao Y (2014) Analytical approach in optimising selection of rebar bolts in preventing rock bolting failure. Int J Rock Mech Min Sci 72:16–25 46. Ghadimi M, Shahriar K, Jalalifar H (2015) A new analytical solution for the displacement of fully grouted rock bolt in rock joints and experimental and numerical verifications. Tunn Undergr Space Technol 50:143–151 47. Liu J, Yang H, Wen H, Zhou X (2017) Analytical model for the load transmission law of rock bolt subjected to open and sliding joint displacements. Int J Rock Mech Min Sci 100:1–9 48. El-Mossallamy Y (2005) [Elsevier Geo-Engineering Book Series] ground improvement—case histories volume 3 In: Chapter 33 Geotechnical measures to increase the stability of rock cuts and to reduce rockfall hazards: case history “Makkah”, pp 947–964. https://doi.org/10.1016/ S1571-9960(05)80036-9 49. Ritchie AM (1963) Evaluation of rockfall and its control. In: Highway research record vol, 17, pp 13–28. Highway Research Board, National Research Council, Washington, DC 50. Pierson L, Gullixson C, Charrie R (2001) Rockfall catchment area design guide, final report SPR-3(032). Publication no.: FHWA-OR-RD-02-04 51. Arndt B, Ortiz T, Turner AK (2009) Transportation research E-Circular E-C141: Colorado’s full-scale testing of rockfall attenuator systems. Transportation Research Board of The National Academies, Washington, D.C., p 130p 52. Glover J, Denk M, Bourrier F, Gerber W, Volkwein A (2012) Kinetic energy dissipation effects of rock fall attenuating systems. In: Interpraevent conference 2012. Grenoble France 53. Wyllie D, Shevlin T (2015) Attenuators for controlling rock fall: do we know how they work? Can we specify what they thould do? In: 66th Highway geology symposium, Colorado Springs, United States of America
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Microstructure Investigation and Design of GFRP Reinforced Coastal Structures Madhuri Kumari , Sahil Singh Deshwal , and Prakash Gupta
Abstract Corrosion and carbon dioxide are two major and global problems that contribute hugely to emissions. Reinforced concrete structures in marine environments often deteriorate prematurely in the early stages of service life. The construction industry spends heavily on slowing down the deterioration process and repairing the damaged components of coastal structures. The coastal structures like seawalls and canal lining are very much important in protecting soil erosion and providing water to farmers in crop season, respectively. Further, any material or any technology has its own limitations as structures became older, and with increasing cases of rebar corrosion, older structures began to demand extra retrofits to increase their life and durability. In view of this, fibre reinforced polymers are inherently corrosion resistance and lightweight. These properties of FRP rebars strengthen reinforced concrete structures and help them fight corrosive environments for a long period. In the present study, a detailed experimental study has been carried out for mechanical and microscopic tests of GFRP rebars, for both raw samples and samples exposed to marine conditions, and field study has been carried out for GFRP rebars for its use in canal lining and seawall costal structures. Also, a design study has been carried out for seawalls and canal lining considering real exposed conditions. The canal lining design was discussed with Irrigation Department, Haryana, and implemented in the 50 m long stretch of Mahendergarh region under their guidance. It is recommended to coastal structure designers and engineers that in the pre-construction stage, the coast situation and weathering conditions in the area should be precisely studied to make sustainable decisions and long-lasting designs for construction of these structures. Keywords Corrosion · Glass fibre reinforced polymer · Marine environment · Seawall · Canal lining · Durability
M. Kumari · S. S. Deshwal (B) · P. Gupta Department of Civil Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida 201313, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_6
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1 Introduction Today’s emphasis is on the construction of long-term performing structures. Construction industries are constantly finding innovative ways to reduce the high maintenance cost of rusted structures including new and repair of these structures. Many concrete structures and sculptures are constructed worldwide, and there is a huge market for repairing and replacement of these structures for their safe use and increasing their life span. The construction industry spends strongly on rehabilitation of corroded steel rebars or in decelerating the deterioration activity. Corrosion of steel reinforcement is one of the key problems in these reinforced concrete buildings that reduces their serviceability and lowers their strength. There has always been an interest in materials that exhibit both extreme strength and ductility [1]. Strength gives members the ability to safely carry loads, and ductility avoids sudden failures. Steel has been the best choice for years, but corrosion reduces its overall performance. The use of fibre reinforced polymer (FRP) bar as internal reinforcement in concrete elements is one of the preferred solutions worldwide due to long-standing positive results [2]. Glass fibre reinforced polymer (GFRP) bar is considered as a next generation alternative material to traditional steel bars. GFRP is very efficient and has advantages equated to conventional materials and technologies in retrofitting of concrete structures. Figure 1 shows the stress–strain curve for various types of reinforcement including GFRP. Increase in use of GFRP over the years has proved to be efficient and cost-effective in its life cycle. They may cause retrofitting of the concrete structure with qualitative benefits, which are mostly corrosion resistance, very high strength to weight ratio, light weight, easy to install and maintain, i.e. man hours can be substantially reduced [3, 4]. The focus of the study is to perform microscopic study of GFRP reinforcement using Scanning Electron Microscope (SEM) in normal and used specimen under marine environment. Further, the case studies performed shall be used to select seawalls and a canal lining as two coastal structures and designing them suing completely GFRP reinforcement. Finally, a design for GFRP reinforced canal lining is to be prepared and implemented at Major district canal in Haryana region.
2 Methodology In this study, the case studies are performed after doing the detailed literature review. The case studies were performed considering the real-life projects that were conducted on different types of coastal structures like seawalls, bulkhead caps, drainage chambers, open flood mitigation, channels, and for retrofitting structures. Those projects were considered where steel was replaced with FRP reinforcement for various purposes. The various types of coastal structures are studied along with their design for steel reinforcement and for GFRP reinforcement. The mechanical tests were conducted on steel as well as GFRP reinforcement to do a detailed comparison
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Fig. 1 Stress–strain curve for different types of reinforcement
based on properties, durability, and costing. Figure 2 shows the samples of GFRP reinforcement that were procured from manufacturer in different sizes for various testing. Further, the two coastal structures named seawall and canal lining are selected for detailed design study and microscopic study. The Scanning Electron Microscope (SEM) analysis was used to study raw samples and samples exposed to marine environment, in both transverse and longitudinal views for better understanding of the GFRP reinforcement matrix. Finally, the design was done for both seawall and canal lining, and GFRP reinforced Canal lining was also implemented for a 50 m stretch in Mahendergarh region under guidance of Irrigation Department, Haryana. Fig. 2 Samples of GFRP reinforcement for mechanical testing
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2.1 Canal Lining and Seawalls An open canal, channel, or canal lining is an open waterway whose purpose is to carry water from one place to another. They help regulate the flow and deliver the correct amount of water to the different branches of the system and onward to the irrigated fields. They can be made of earthen, brick lined or lined with cement concrete and reinforced concrete lining. Figure 3 shows the use of GFRP reinforcement in open canal in Dubai in 2021 for a flood mitigation channel work. Seawalls are huge coastal structures built to protect against storm surges and high-altitude erosion. Marine structures such as seawalls, floating marine docks, water breaks, artificial reefs, and buildings near water structures are very vulnerable to chlorides or sea salt which can simply damage these RCC structures reinforced with steel reinforcement. The rehabilitation work of a reinforced concrete seawall in Germany built during 2018 is shown below in Fig. 4, where GFRP rebars are used in alternative to steel due to difficulty of regressive corrosion. Therefore, engineers choose to use superior-in-strength and corrosion-free GFRP rebar which is completely resistant to corrosion. Fig. 3 GFRP reinforced concrete lining in open channel (Dubai 2021)
Fig. 4 GFRP reinforcement in RCC seawalls (Germany 2018)
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Fig. 5 Two GFRP 13-mm-long samples under process of gold coating before SEM tests
2.2 Scanning Electron Microscope (SEM) A Scanning Electron Microscope (SEM) is a kind of electron magnifying lens that generates pictures by examining the surface with a connected light emission. The electrons link up with molecules creating various signs that include data about the surface geography of the sample [5]. The electron pillar is purified in a raster examine design, and the location of the bar is joined with the power of the recognized sign to produce a picture. In SEM, after slicing the GFRP specimen to a 13 mm thick slice, the surface of GFRP specimen was flattened using various levels of sandpaper. After that, an oven at 50 degrees Celsius was used to maintain the specimen dry state. Also, since GFRP is non-conductive material, a gold coating was used on the samples to make it sensitive and conductive to electrons that will be wielded from the SEM apparatus. Figure 5 shows two samples of GFRP reinforcement being gold coated before testing in SEM.
3 Results and Discussions 3.1 Mechanical and SEM Tests The various types of mechanical test were carried out, namely tensile test for tensile strength of GFRP rebars, pull out test for bond strength, and flexure test for GFRP flexure strength [6]. For all tests, on an average five samples were tested, and average strength was recorded, given as 1082 MPa tensile strength, 3.2 MPa bond strength, and 12.18 MPa flexure strength. The tensile strength of GFRP rebars is found to be satisfactory with the readings obtained from the manufacturer. As compared to steel
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Fig. 6 Flexure beam failure with graphs depicting cracks as originated
rebars, the ultimate tensile strength of same diameter of GFRP rebars is approximately double. Bond strength was also found to be approximately equal to the bond strength of deformed steel bars with concrete. Flexure strength was found to be much more than the steel and is a major factor determining its use in reinforced concrete structures requiring flexural strength under various loads [7]. Figure 6 shows the fractured beam tested in three-point loading in Universal Testing Machine. For both longitudinal and transverse views, no microstructural degradation was observed in the GFRP specimen where the scanning was performed. All fibres were complete, and the resin was appropriate and completely bonded to the fibres. Also, there was no damage in the cross-sectional area of fibres. However, some cracks and disproportionate shapes appear on one specimen, but are expected due to the improper preparation of the specimen. Therefore, the sample surface preparation should be clean with alcoholic solution before proceeding with tests [8]. Figure 8 shows the distorted surface preparation in highlighted 1.B due to normal cleaning process. The surface degradation of the reinforcement fibres was so small that it did not affect the durability of the material. It depicts that there are no irregularities in the cross-sectional view seen at different magnifications. All resin and fibre matrix are intact, and no voids are present. Figure 7 shows the cross-sectional view at 10 µm having intact resin and fibre matrix in 1.A. The longitudinal view of GFRP sample shows that the edges with deformation for bonding are much affected while preparing the samples and grinding them with sandpaper. Figure 9 shows the longitudinal view at 20 µm with deformed edges in 2.A due to use of sandpaper while preparation of the sample. Otherwise, no resin and fibre voids are seen, and there is an appropriate ratio of fibre matrix inside the reinforcement. It depicts that there are no deformations in the longitudinal view seen at different magnifications, and the resin matrix between fibres is in appropriate proportion; but at some place, it was found to be distorted. Figure 10 shows the longitudinal view at 2 µm with no deformations and perfect resin and fibre matrix in 2.B.
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Fig. 7 Cross-sectional view at 10 µm (3500X)—sample 1
1.B
Fig. 8 Cross-sectional view at 10 µm (4000X)—sample 2
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2.A
Fig. 9 Longitudinal view at 20 µm (1000X)—sample 1
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Fig. 10 Longitudinal view at 2 µm (5000X)—sample 2
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3.2 Canal Lining Field Implementation The canal lining design was implemented for a 50 m long stretch and 9 m wide girth in an open wide canal lining rehabilitation work at Palri village, Mahendergarh, under the guidance of Irrigation Department, Haryana. The design was finalized based on test performed for GFRP samples, and it was discussed thoroughly with the designers and engineers of Irrigation Department, and some changes were made accordingly to cater to the field conditions that they were aware of [9–12]. The steps followed for rehabilitation work are as follows: (a) the scrapping of mud was done from old brick lining for proper placing of concrete on top of it. The excavator is used to clean both beds and lining along with manual labours; (b) the 10 mm diameter GFRP reinforcement was placed, and binding was carried out as per drawings, i.e. 300 mm c/c in main bars and 200 mm c/c in distribution bars [13, 14]. The small mats were made and then placed continuously on the linings of the canal after scrapping was completed; (c) batching of concrete was done in self mixing type trucks or floris nearby the canal. The concrete was made as per weight batching and as per the design. The concrete was made and placed into the canal bed from where the excavator is used to pull off concrete to the linings; (d) the dumped concrete on the bed is placed on GFRP reinforced linings using excavator, and labours are used to manually finish the lining from top. Figure 11 shows the placing of concrete on slopes and canal bed. No compaction is done as thickness is just 30 mm and in slope in linings. Bed concreting is always done at the last after finishing off the linings; and (e) the contraction joints were made with 10 mm deep to fill hot bitumen inside them after drying of concrete. The finished bed is cured for at least 7 days, and then water is allowed to run through it. Figure 12 shows the finished canal lining with grooved out contraction joints for filling up of bitumen.
4 Conclusion GFRP rebars are a promising solution to substitute steel rebars and hence prevent corrosion problems. The GFRP rebars are found to be more satisfactory in terms of tensile strength as yield strength is higher even after applying reduction factor of 0.7 due to environmental conditions. Bond strength for GFRP rebars was also found to be approximately equal to that of deformed steel bars. The cost analysis also shows that when direct life cycle costs are considered, in many cases GFRP rebars already constitute an economically competitive alternative to conventional steel reinforcement. In Scanning Electron Microscopy analysis on exposed GFRP reinforcement, no microstructural degradation was observed in the GFRP rebars where the examining was conducted. All fibres were perfect, and the resin was appropriate and completely bonded to the fibres. Also, there was no damage in the cross-sectional
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Fig. 11 Placing and finishing of concrete work in lining
Fig. 12 Finished GFRP reinforced canal lining with grooved out contraction joints
area and longitudinal area of fibres due to exposed marine environment. Microstructure study concludes that the fibres and resin are not affected due to marine environment on samples used inside concrete in coastal areas. The field implementation was successfully carried out, and it was learned that few modifications are always
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required when the design is implemented on field in real-life conditions. It was well accepted and good results were seen so far in the GFRP reinforced canal lining. Based on this study, it can be concluded that GFRP rebars are preferred over the conventional TMT steel rebars as nowadays they are also easily and widely available in market like India. Especially for structures in coastal areas or structure exposed to marine environments, it is it most suitable and economically preferable over steel rebars due to the factors discussed above. Further, compared to previous studies, it is recommended to study the canals that are lined nowadays with concrete in a major rehabilitation programme undergoing in North Indian states as a heavy expenditure is being done for the same. The GFRP reinforcement can easily be added in this rehabilitation programme for lined canals, and based on the reviews, the design can be further studied to make it more sustainable and cost-effective solution.
References 1. Kivell APASA (2012) Corrosion related bond deterioration and seismic resistance of reinforced concrete structures. Structural Congress 1894–1905 2. Harik API (2009) Twelve years of field applications of FRP materials in Kentucky. FRPRCS 09 3. Kisicek ZSJGT (2009) Stress and strain distribution in concrete beams reinforced with FRP bars. FRPRCS 09 4. Balendran TMRTMWTRV (2002) Application of FRP bars as reinforcement in civil engineering structures. Strcutural Surveying 20(2):62–72 5. Hassan TEMHE (2019) Microstructure Characteristics of GFRP reinforcing bars in harsh environment. Adv Mater Sci Eng 19 6. Yu YPRZXMY (2021) Effects of water and alkaline solution on durability of carbon-glass hybrid fibre reinforced polymer bars. MDPI 13:3844 7. Mathieu BBR (2009) Characteristics and long term durability of GFRP reinforcing bars embeded in moist concrete. FRPRCS 09 8. Wen FLYJHLQWF (2022) Assessment and prediction model of GFRP bars and Durability performance in seawater environment. MDPI 12:127 9. ACI 440.1R-15 (2015) Guide for the design and construction of structural concrete reinforced with fiber-reinforced polymer bars. In: ACI committee, vol 440, American Concrete Institute 10. ACI 318 (1995) Building code requirements for structural concrete. American Concrete Institute 11. AASTHO (2020) LRFD bridge design specifications. AASTHO Provisional Standards, Washington, D.C 12. IRC SP 013 (2004) Guidelines for the design of small bridges and culverts. IRC, New Delhi 13. IS:456 (2000) Code of practice for plain and reinforced concrete. BIS, New Delhi 14. GangaRao HVS (2019) Reinforced concrete design with FRP composites
Finite Element Analysis and Design of Concrete Bridge Deck Using GFRP Reinforcement Madhuri Kumari , Prakash Gupta , and Sahil Singh Deshwal
Abstract Several transportation departments bear high maintenance expenditure during restoration required for bridge decks due to corrosion induced deterioration. The damage of RCC bridges due to corrosion requires expensive maintenance during the service life of bridges. A possible answer to save such expenditures is the use of fiber reinforced polymer (FRP) rebars in the bridge decks. These FRP rebars are unaffected by corrosion, and they have superior strength. Though numerous experimental studies are available for RCC reinforced with GFRP reinforcement, but very few field applications of RCC bridge deck reinforced with GFRP rebars are found. In this study, a RCC bridge deck slab reinforced with GFRP reinforcement is designed using ACI 440.1R-15 and the slab is then analyzed in Ansys static structural module and the outcomes are presented in this paper. Pedestrian crowd loading is considered as per IRC 6 for design of the deck slab. The virtual model thus prepared can be customized for respective dimension of bridge and for different loads condition. This design of deck slab has been proposed having clear roadway width between the parapets as 2.3 m to facilitate ease of commuting over a canal for pedestrians and bicyclists and two-wheelers only. Keywords Bridge deck slab design · Finite element analysis · Pedestrian Bridge · One way slab · GFRP rebars · Flexure stress · Deflection
1 Introduction Designs of bridges vary depending on factors such as the function of the bridge, the nature of the terrain where the bridge is constructed and anchored, and the material and the funds available to build it. The deck’s principal role is to distribute these forces in a way that is beneficial to the support elements below. Bridge decks are M. Kumari · P. Gupta (B) · S. S. Deshwal Department of Civil Engineering, Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh 201313, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_7
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vulnerable, subject to attack by water and chloride that can lead to deterioration and issues with durability of the bridge decks. Cracking on bridge decks is common, and bridge deck deterioration is a leading cause of structurally obsolete or deficient inspection ratings [1]. Glass fiber reinforced polymer (GFRP) reinforcement has developed as an appropriate substitute to steel reinforcement in certain bridge applications. GFRP reinforcement is well suited for use in corrosive environments in low dead load situations. The unique engineering properties of GFRP rebars necessitate different design criteria and design approaches than normal steel reinforcement. GFRP is noncorrosive and can be formed with strengths greater than normal reinforcing steel; however, it is also subject to creep under sustained loads, exhibits a brittle failure mode, is highly flexible, and is not effective in compression [2]. Due to these limitations, the design of many situations is governed by serviceability or creep rupture. The design and analysis of the GFRP reinforced bridge deck in this case is carried out for numerous load types and classes, which primarily included the live load applicable and the self-weight of the structure. Thereafter, the virtual model of design is prepared using Ansys SpaceClaim for precise analysis of the different loads and load combinations acting on modelled bridge deck. The results thus obtained can be studied accordingly. In this paper, the theoretical design of bridge deck reinforced with GFRP was carried out. The theoretical design was then analyzed using finite element analysis and a design of three span pedestrian GFRP reinforced bridge deck is proposed to cross a canal lining for pedestrians, animals, and two-wheelers only, in Haryana state. The bridge has two abutments and two piers. A 3D model of the bridge is shown in Fig. 1. The height of bridge is approximately 7 m from canal bottom surface as shown in Fig. 2.
Fig. 1 3D model of 3 span pedestrian bridge modeled in Ansys SpaceClaim
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Fig. 2 Elevation view of proposed 3 span pedestrian bridge
2 Methodology 2.1 Theoretical Design The theoretical design of pedestrian footbridge concrete deck slab is prepared for environment of Haryana state of India with M30 grade concrete and GFRP as reinforcement. The concrete cover to the top mat of GFRP reinforcement provided is 40 mm. The increased cover increases durability of the deck, prevents splitting and cracking, decreases development lengths, and to justify for concrete and reinforcement placement tolerances [3]. The length of bridge is taken as approximately 20 m with three number of spans. The width of bridge deck is taken as 2300 mm, the design thickness of deck slab is taken as 325 mm and the clear span of deck is taken as 6000 mm for the design purpose considering IRC guidelines for small bridges and culverts [4]. The design tensile strength of GFRP is taken as 1078 MPa, the modulus of elasticity of GFRP is taken as 44,829 MPa, and the Environment Reduction factor (C E ) is taken as 0.7 as per ACI 440.1R-15 [5]. The design moments were computed using approximate moment analysis permitted by ACI 318–11, Sec. 8.3.3 [6]. Due to lower modulus of elasticity of GFRP rebar compared to steel rebars, the deflection and crack widths will govern the design of deck slab. The design is considered on the end span because it will yield the highest moments assuming the end of span is integral with the support. In addition to flexural strength, the slabs were examined for shear and the serviceability criteria of crack control, deflections, and creep rupture stress limits [7]. The slab is designed to be 325 mm thick with 16 mm diameter GFRP bars at 95 mm for –M. By observation, the same minimum reinforcement will be required for + M, providing longitudinal 16 mm dia. @ 95 c/c, giving an area of 2011 mm2 , and providing transverse 16 mm dia. @ 95 c/c.
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Properties
GFRP
Modulus of elasticity
44,829 MPa
Ultimate tensile strength
1078 MPa
Poisson’s ratio
0.27
Diameter of rebar
16 mm
Surface texture
Deformed rebar
Unit weight
2020 kg/m3
2.2 Finite Element Modeling and Analysis The FE modeling was conducted using inbuilt CAD modeling software of Ansys Workbench. The material for modeling concrete is based on the stress normal to the crack direction decreases to zero, resulting in redistribution of stresses around the crack. Cracks are allowed to form in three directions and, once a crack forms, it may close and re-open but it cannot heal. Two mutually exclusive vertical load models were envisaged for the proposed footbridges. They were, the crowd effect on the bridge is represented by a uniformly distributed load. A loading of 5 kN/m2 was adopted as per IRC guidelines [8]. Also, one concentrated load, representing a maintenance load is also considered for local effect assessment, a 10 kN concentrated load representing a maintenance load was considered on the bridge, acting on a square surface of sides 10 cm. This concentrated load was applied separately than other variable non-traffic load (Table 1). Figure 3 shows the stress vs strain graph used to model for GFRP rebar in FEA. Figure 4 shows the loading conditions applied on bridge deck model in Ansys which is a combination of dead load and pedestrian live load.
Fig. 3 Stress versus strain graph of GFRP rebar
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Fig. 4 Loading conditions applied on bridge deck slab
3 Results and Discussions As the designed deck slab is not tension controlled, minimum necessary reinforcement to prevent the failure of bridge deck upon concrete cracking is achieved and the following FEA results mentioned below also confirms the design is safe and well within required limit of deflection and applicable stresses. Figure 5 shows the equivalent stress observed on 1 m width element of slab where 10.9 MPa maximum stress is observed and Fig. 6 shows the shear stress observed in concrete which is well within the permissible limits of concrete strength.
Fig. 5 Equivalent (von-Mises) stress output for bridge deck slab element
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Fig. 6 Shear stress output for bridge deck slab element
Fig. 7 Maximum principal stress output in longitudinal tension reinforcement at mid span
Figures 7 and 8 shows the stresses observed in the GFRP reinforcement which were well within the permissible stress values, as the design is reinforced enough so the failure begins by concrete cracking. Figures 9 and 10 shows the deflection observed in the deck slab which was well within the permissible values as the AASTHO design specifications. Table 2 shows the results obtained due to combined dead load and live load conditions in theoretical design and FEA.
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Fig. 8 Equivalent (von-Mises) stress output for reinforcement in deck slab
Fig. 9 Deflection output at center bottom most longitudinal fiber in deck slab for combined dead load and live load
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Fig. 10 Deflection output at longitudinal edge in deck slab for combined dead load and live load
Table 2 Results obtained due to combined dead load and live load
Theoretical
FEA
Property
Output
Max deflection
1.51 mm
Max shear force
66.45 kN
Max moment
83.088 kN-m
Max deflection
0.857 mm
Max shear force
54.45 kN
Max moment
57.5 kN-m
Max stress observed in concrete
3.5 MPa
4 Conclusion Based on the findings of this study of GFRP reinforced concrete bridge deck slab for pedestrian load, the FEA model successfully predicted the stresses developed in GFRP reinforced bridge deck slab for applied dead load and pedestrian loading conditions. Additionally, by conducting the FEA on the concrete deck, the practical effectiveness of the GFRP rebar in bridge deck was cross-checked and found to be satisfactory. A reasonably good correlation between the literature study and FEA results of the model were observed. The maximum shear stress during theoretical design was found to be 65.45 kN which is 15% more compared to shear stress results observed in FEA which is 54.45 kN. The maximum bending moment is observed at the longitudinal edges, and maximum shear force is obtained at the support. The stresses in longitudinal reinforcement at edges were 0.83% more compared to stresses in longitudinal reinforcement at mid-span while the strain at edge reinforcement was 0.8% more compared to strain in center span validating a linear relationship. The theoretical designs were found to be conservative than the results obtained from FEA, thus the final proposed
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design was improvised considering the results obtained from FEA, so that the design becomes cost-efficient. Further, it is recommended to study the cost-efficiency of bridge decks reinforced with GFRP rebars and similar structures to perform a comparative analysis based on previous literature and FEA improvised theoretical designs for a cost-efficient design.
References 1. Raju K (2019) Design of bridges. 4th edn. Oxford and IBH Publishing Co. Pvt. Ltd, New Delhi 2. Hota VS (2019) GangaRao: reinforced concrete design with FRP COMPOSITES. 1st edn, CRC Press 3. BIS (2000) IS 456 Code of practice for plain and reinforced concrete. New Delhi 4. IRC (2004) IRC SP 013 Guidelines for the design of small bridges and culverts. New Delhi 5. ACI (2015) ACI 440.1R-15 Guide for the design and construction of structural concrete reinforced with fiber-reinforced polymer bars. American Concrete Institute 6. ACI (1995) ACI 318 Building code requirements for structural concrete. American Concrete Institute 7. AASTHO (2020) LRFD bridge design specifications. AASTHO Provisional Standards, Washington D.C 8. IRC (2017) IRC 6 code of practice for road bridges, Section-II loads and load combination, New Delhi
“Experimental Study of Variation in Properties of Ultrafine Ground Granulated Blast-Furnace Slag (GGBS) and Steel Fibre Infused Concrete” Rahul Pandit , Prakhar Duggal , and Ravinder Kumar Tomar
Abstract We don’t imagine a living thing without a structure, yet this structure is made up of numerous materials such as RCC, cement, aggregates, sand, and water, with concrete being the most fundamental. Concrete is commonly utilised in building a variety of buildings; however, it is made up of cement, sand, gravel, water, and admixtures. Due to the scarcity of the components used in this type of concrete, several adjustments are being made in order to increase its compressive and tensile strength in the current environment. So in this paper, we enhance concrete strength using ultrafine ggbs and steel fibre in the concrete mix. The ultrafine ggbs and steel fibre provides a higher compressive strength and tensile strength to the structure. Durable of the design for a longer life span with their lightweight structure means in this structure thinner members are consistent and the area of the structure is reduced because the higher compressive strength and tensile strength of concrete are used. As a result, their structure is much thinner than traditional concrete. However, the cost of the concrete mix has increased due to the use of ultrafine ggbs, and steel fibre is relatively costly, so the entire cost of concrete has increased since it is not in line with the structure’s life span and strength gain as a result of these materials. In this study, we use ultra-fine ggbs in 4–8% and steel fibre in 1.5–2.5% in conventional concrete and find the results of some experiments performed in the concrete testing lab like compressive strength and workability. The materials are readily accessible in the market. Keywords Supplementary cementitious materials · Ultra-fine GGBS · Steel-fibre · Compressive-strength · Tensile-strength · Concrete mix
R. Pandit (B) · P. Duggal · R. K. Tomar Civil Engineering Department, Amity University, Noida, UttarPradesh, India e-mail: [email protected] P. Duggal e-mail: [email protected] R. K. Tomar e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_8
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1 Introduction Concrete is almost all useful products in the construction sector. We cannot imagine the construction of any structure, including skyscrapers, bridges, residences, and shopping malls, without concrete. However, in the current situation, ordinary Portland-based cement (OPC) has been accessible for almost 200 years. In terms of concrete strength, standard concrete, on either hand, doesn’t accomplish much. The long-term durability of the construction is insufficient. Because of this, the addition of certain chemicals to regular concrete changes the situation. By including a few alternative (pozzolanic) components, such as ultrafine GGBS and steel fibre, and replacing a part of the cement in the concrete. The properties are gained through ultrafine GGBS and steel fibre like workability, strength, durability, permeability etc. This type of component is easily available. According to Tang et al. [1], the renewal of cement with an optimum percentage of GGBS affects the strengthening of the matrix. According to Imbabi et al. [2], adding wood ash, fly-ash, rice-husk, silica fume, ground- granulated blast furnace-slag (GGBS), and other materials in concrete helps to minimise low carbon emissions. Oner et al. [3], conclude the substitution of 55–59% of GGBS with cement gives high compressive strength as compared with ordinary concrete. This type of concrete based mix is expensive in comparison to traditional concrete but it depend on the percentage of ultrafine GGBS and steel fibre. However, this kind will be described later. When assessing product durability, the price is not taken into account. When the strength of conventional concrete is compared to that of steel fibre concrete, traditional concrete has thicker thickness members to achieve its strength. Steel fibre concrete, on either hand, uses thinner components to produce its strength. The life of the construction is also extended. As a result, combining steel fibre and ultrafine GGBS to replace some of the cement in concrete is helpful. In this concrete we mixing of (a) (b) (c) (d) (e)
Steel Fibre Ultrafine GGBS Cement Fine aggregate Coarse aggregate
2 Literature Review Ahmad et al. [4]. According to their calculations, ordinary concrete with 20 GGBS and 2% SF has a 39% higher compressive strength and a 120% higher split tensile strength after 28 days of curing. At the ideal dose, acid resistance was 36% higher than normal concrete. Sadawy et al. [5]. After 28 days of cure, end-hooked steel fibre increased compressive strength by 19%, and 1.5% of steel fibre enhanced mechanical properties. Toxin
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ratios were between 0.2 and 0.22. At different ages, fresh water, as an aggressive medium, reduced the corrosion rate more often than the other corrosive media. Gupta et al. [6]. Mechanical qualities such as compressive-strength, flexural, tensile- strength, toughness, impact and others are highly influenced by the inclusion of fibres, ideal dose of fibre, and so on, according to their research. The addition of fibre indicates a unique category, such as self-compress concrete, high-performance concrete, and high-strength concrete, among others. Krishna et al. [7]. According to the results of the experiment, when 12% Alccofine is used in place of cement in concrete, the compressive strength increases by 39.5%, the flexural strength increases by 45%, and the split tensile strength increases by 38% when compared to control concrete. Saranya et al. [8]. According to their calculations, the setting time of concrete rises as the fraction of GGBS increases. The workability is increased with an increase in the quantity of GGBS but the workability decreases with an increase in the quantity of Steel fibre. The ductility of GGBS concrete is 11.43% higher than OPC concrete and it’s 2.5 times more. Mishra et al. [9]. According to their findings, replacing cement with 25% GGBS and 2.5% steel fibre results in higher compressive and split tensile strength. At 7, 14 and 28 days of cure, the compressive-strength is 24.46, 28.66, and 42.79 N/mm2 . 8.95 N/mm2 is the split-tensile strength. Tang et al. [1]. When an optimal amount of GGBS is used to replace cement, they detect an impact that leads to the strengthening of the concrete matrix. Teng et al. [10]. They conducted experiments on the substitution of GGBS for cement in ordinary concrete. To enhance the strength, workability and consistency of the GGBS concrete. Imbabi et al. [2]. They are confronted with a problem since the use of cement in concrete emits carbon into the atmosphere, causing global warming to worsen on the earth’s surface. The use of low-carbon industrial byproducts such as silica-fume, wood-ash, rice- husk ash, fly ash, ground-granulated blast furnace-slag (GGBS), and others. Naik et al. [11]. The notations in traditional concrete, GGBS are used in place of cement. Greenhouse gases pollute the atmosphere in large quantities. Because greenhouse gases are the major driver of global warming, it is critical to restrict.
3 Methodology In this article, the work on a novel form of concrete created in comparison to traditional concrete is described, as well as the creation of several grades of concrete like M25, M30, and M35 with the following elements. a. Ultrafine GGBS b. Cement c. Steel fiber
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d. Fine aggregate e. Coarse aggregate Firstly I procured all the material given above. Then the analysis of the material is of perfect quality. After that get permission for working in the lab. Now I calculated all the mix-design and the proportion of the materials than the preparation of the cube moulds with greasing and all. Now come to the mixing of all materials with their mix design guideline. So, firstly prepare a concrete mixture with SSD condition (Sub–Surface Dry condition) then put into it all the materials for mixing. After mixing all the material it will be concrete then calculate the workability of the concrete is put into the empty cube moulds for setting. The empty cube moulds were placed on the vibrating machine for the no voids present in the concrete cube. The empty cube moulds fill by concrete with three times and the filled cube moulds are taken out through a vibration machine. And after 24 h taken for setting the concrete moulds. Now it’s time to get all the concrete-cubes and put them into the water tank for 7, 14 and 28 days of cure. After cure perform the compressive- strength test through a Universal Tensile Machine (UTM machine) on the 7, 14 and 28 days. Then compare the compressive-strength of several grades of concrete like M25, M30, and M35.
3.1 Materials Cement—We employ the OPC 43 cement grade for our research with mixing of ultra- fine GGBS and steel fiber (Fig. 1). Aggregate—In line with IS: 383–1970, it employs both fine and coarse material, such as river sand. We also use fine and coarse material that has been angularly crushed. Steel-Fibre—STEWOLS INDIA (P) LTD, an ISO 9001:2015 certified firm, is India’s first and biggest manufacturer and supplier of high-quality steel fibres. Our steel fibres are protected by the registered trademark “SHAKTIMAN®.” ASTM (American Society for Testing and Materials)—A 820 [12] requirements are met by SHAKTIMAN® Steel Fibres. In the concrete mix, we employed hooked end steel fibre (Figs. 2 and 3). Ultrafine GGBS—The Ultra-Fine Ground-Granulated Blast-Furnace based Slag (GGBS) meets IS 16715:2018 requirements. Suyog MICROFINE [13] is GGBS powder that has been ultrafine ground. Ultra fineness improves the qualities of ordinary GGBS, such as surface area, penetrating properties, and chemical resistance (Fig. 4).
“Experimental Study of Variation in Properties of Ultrafine Ground …
Fig. 1 OPC 43 grade of cement and aggregate
Fig. 2 Property of steel fibre
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Fig. 3 Steel fibre and ultra-fine GGBS
Fig. 4 Chemical and physical properties of ultrafine GGBS
3.2 Experimental Work Mix Designs To determine the best way for combining the ingredients, an experimental approach was used [14]. A mixture of M25 grade of concrete with no pozzolanic material (Design Mix M25), concrete with 4% Ultra-fine GGBS and 1.5% Steel fibre (M25 + 4% GG + 1.5% SF), concrete with 4% Ultra-fine GGBS and 2.5% Steel fibre (M25 + 4% GG + 2.5% SF), concrete with 8% Ultra-fine GGBS and.5% Steel fibre (M25 + 8% GG + 1.5% SF) and concrete with 8% Ultra-fine GGBS & and.5% Steel fibre (M25 + 8% GG + 2.5% SF) was cast in a 5 mould of respective sizes (15 × 15 ×
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15 cm) to test the workability, compressive-strength and SEM analysis of the design combinations. Similarly, it same with M30 and M35 grades of concrete. A mixture of M30 grade of concrete and also, in mixture M35 grade of concrete. In both situations, there is a similar only difference in the grade of concrete. The cast in 5 moulds of respective sizes (15 × 15 × 15 cm) to test the Workability, compressive-strength and cost analysis of the design combinations (Tables 1, 2 and 3).
4 Results and Discussion 4.1 Test Result (Compressive-Strength) In this paper, the preparation of steel fibre, ultrafine GGBS, and cement in the concrete mix, as well as the finalisation of the casting of various types of concrete in comparison to ordinary concrete, are discussed. The compressive strength value is finalised through the UTM machine on curing of moulds for 7, 14 and 28 days. In accordance with IS: 516–1956 procedure (Tables 4, 5 and 6; Fig. 5). The Compressive − Strength = P/ A in N/mm2 where, P = failure load in N A = cube area [150 × 150 mm2 ].
4.2 Test Result (Workability) The test is designed to detect changes in the workability of concrete by measuring the consistency of new concrete. It is made up of a 300 mm high frustum metal cone with an interior diameter of 200 mm at the bottom and 100 mm at the top. The filling of the frustum with fresh concrete in three equal-volume levels and compacting each layer with 25 strokes of a tamping rod was the fundamental technique. The frustum was then removed, and the concrete sank. This method is done according to IS 456:2000, the slump cone test for workability (Tables 7, 8 and 9; Fig. 6).
4.3 Test Result (Cost Analysis) See Tables 10, 11 and 12.
M25 + 8% GG + 2.5% SF
2.5
1.5
M25 + 8% GG + 1.5% SF
8
2.5
M25 + 4%GG + 2.5%SF
400.497
405.383
418.441
423.32
752.71
752.71
752.71
752.71
752.71
1.5
448.6
0
4
Design mix M25
M25 + 4%GG + 1.5%SF
0
Fine-aggregate (Kg/m3 )
Ultra-fine Steel fibre Cement (Kg/m3 ) GGBS (%) (%)
Mix design
Table 1 The concrete mix design for M25 grade
1064.65
1064.65
1064.65
1064.65
1064.65
Coarse-aggregate (Kg/m3 )
35.888
17.944
0
Ultra-fine GGBS (Kg/m3 )
12.215
7.329
12.215
7.329
0
197.4
197.4
197.4
197.4
197.4
Steel fibre Water content (Kg/m3 ) (Kg/m3 )
0.44
0.44
0.44
0.44
0.44
Water-cement ratio
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M30 + 8%GG + 2.5% SF
2.5%
1.5%
8
M30 + 8%GG + 1.5% SF
1.5%
2.5%
4
M30 + 4%GG + 1.5% SF
0
Steel fibre (%)
M30 + 4%GG + 2.5% SF
0
Design mix M30
Mix design Ultra-fine GGBS (%)
352.63
356.57
368.39
372.33
394
Cement (Kg/ m3 )
Table 2 The concrete mix design for M30 grade
787
787
787
787
787
Fine-aggregate (Kg/m3 )
1082
1082
1082
1082
1082
Coarse-aggregate (Kg/m3 )
31.52
15.76
0
Ultra-fine GGBS (Kg/m3 )
9.85
5.91
9.85
5.91
0
Steel fibre (Kg/m)
197
197
197
197
197
0.5
0.5
0.5
0.5
0.5
Water content Water-cement (Kg/m3 ) ratio
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1.5%
M35 + 8%GG + 2.5% SF
2.5%
1.5%
M35 + 8%GG + 1.5% SF
8
2.5%
M35 + 4%GG + 2.5% SF
4
M35 + 4%GG + 1.5% SF
Steel fibre (%)
0
Ultra-fine GGBS (%)
Design mix 0 M35
Mix design
402.75
407.25
420.75
425.25
450
Cement (Kg/ m3 )
Table 3 The concrete mix design for M35 grade
664.83
664.83
664.83
664.83
664.83
Fine-aggregate (Kg/m3 )
1136.986
1136.986
1136.986
1136.986
1136.986
Coarseaggregate (Kg/m3 )
36
18
0
Ultra-fine GGBS (Kg/m3 )
11.25
6.75
11.25
6.75
0
Steel fibre (Kg/m3 )
202.5
202.5
202.5
202.5
202.5
Water content (Kg/m3 )
0.45
0.45
0.45
0.45
0.45
Water-cement ratio
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“Experimental Study of Variation in Properties of Ultrafine Ground … Table 4 At 7, 14, and 28 days of cure, the M25 compressive strength value
Table 5 At 7, 14, and 28 days of cure, the M30 compressive strength value
Table 6 At 7, 14, and 28 days of cure, the M35 compressive strength value
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Mix-design
7-Day period (MPa)
14-Day period (MPa)
28-Day period (MPa)
Design mix M25
18.85
25.75
29.88
M25 + 4% GG + 1.5% SF
20.52
28.23
30.951
M25 + 4% GG + 2.5% SF
21.852
29.345
31.825
M25 + 8% GG + 1.5% SF
22.84
30.15
33.432
Mix-design
7-Day period (MPa)
14-Day period (MPa)
28-Day period (MPa)
Design mix M30
22.87
31.69
35.553
M30 + 4% GG + 1.5% SF
25.624
32.862
37.92
M30 + 4% GG + 2.5% SF
27.108
34.242
39.224
M30 + 8% GG + 1.5% SF
27.32
37.39
40.23
Mix-design
7-Day period (MPa)
14-Day period (MPa)
28-Day period (MPa)
Design mix M30
27.558
34.57
40.525
M30 + 4% GG + 1.5% SF
29.80
37.93
44.20
M30 + 4% GG + 2.5% SF
30.992
40.15
43.45
M30 + 8% GG + 1.5% SF
32.276
41.14
45.595
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Fig. 5 Compressive strength testing machine
Table 7 M25 workability value
Table 8 M30 workability value
Table 9 M35 workability value
Design mix
Slump (mm)
Design mix M30
70
M30 + 4% GG + 1.5% SF
60
M30 + 4% GG + 2.5% SF
55
M30 + 8% GG + 1.5% SF
50
M30 + 8% GG + 2.5% SF
45
Design mix
Slump (mm)
Design mix M30
65
M30 + 4% GG + 1.5% SF
55
M30 + 4% GG + 2.5% SF
50
M30 + 8% GG + 1.5% SF
45
M30 + 8% GG + 2.5% SF
40
Design mix
Slump (mm)
Design mix M35
60
M35 + 4% GG + 1.5% SF
50
M35 + 4% GG + 2.5% SF
45
M35 + 8% GG + 1.5% SF
40
M35 + 8% GG + 2.5% SF
35
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Fig. 6 Slump cone test Table 10 Cost-comparison between conventional-concrete and M25 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) Concrete Material
Rate
Conventional concrete
M25 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) concrete
Quantity Cost
Quantity
Difference (%)
Cost
Cement Rs 400 per bag 1.514 kg Rs 12.11 1.355 kg (OPC 43 grade) (50 kg)
Rs 10.840 49.2
Steel fibre (Hooked End)
Rs 140/Kg
0
0
0.037 kg
Rs 5.18
Ultrafine GGBS
Rs 17/Kg
0
0
0.1211 kg Rs 2.05
Rs 12.11
Rs 18.07
Table 11 Cost-comparison between conventional-concrete and M30 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) concrete Conventional concrete
M30 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) concrete
Quantity
Cost
Quantity
Cost
1.329 kg
Rs 10.63
1.189 kg
Rs 9.517
Steel fibre Rs 140/Kg (Hooked end)
0
0
0.033 kg
Rs 4.62
Ultrafine GGBS
0
0
0.1063 kg
Rs 1.807
Material
Cement (OPC 43 Grade)
Rate
Rs 400 per bag (50 kg)
Rs 17/Kg
Rs 10.63
Rs 15.944
Difference (%)
49.9
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Table 12 Cost-comparison between conventional-concrete and M35 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) concrete Material
Rate
Conventional concrete
M35 (Steel fibre 2.5%) and (Ultrafine GGBS 8%) concrete
Quantity Cost
Quantity
Cement Rs 400 per bag 1.518 kg Rs 12.14 1.355 kg (OPC 43 grade) (50 kg)
Cost Rs 10.840 49.9
Steel fibre (Hooked end)
Rs 140/Kg
0
0
0.0379 kg Rs 5.306
Ultrafine GGBS
Rs 17/Kg
0
0
0.1214 kg Rs 2.06
Rs 12.14
Difference (%)
Rs 18.206
5 Conclusion In this experimental work the outcome of ultra-fine GGBS (4–8%) and steel fibre (1.5–2.5%) in substitute from cement in several grades of concrete. Some amount outcome is pointed out below: • The compression strength test is under the UTM testing machine. The outcome result is noticed through the entire mix design. The increment value is totally based on a high proportion concrete mix between conventional concrete like in the M25 design mix increases compressive strength by 15.03%. Similarly, M30 has an 18.28% increment and M35 has a 20.48% increment noted on 28 days of curing. • Increasing the proportion of ultra-fine GGBS and steel fibres to 8 and 2.5%, respectively, yielded good compressive strength results. The workability conducted through the Slump-cone test lies between 50 and 75 mm. The slump is reduced through the amount of ultrafine GGBS and steel fibres increase in the concrete mix. • A decrease is observed in the workability when adding ultra-fine GGBS and steel fibre to ordinary concrete. • We discovered that using ultra-fine GGBS and steel fibre in several grades of concrete overall 49.9% more money than using traditional cement concrete. When compared to standard concrete, this is a substantial investment. Even when substituting part of the cement, there is great potential for attaining good concretestrength at a comparably higher cost with ultrafine GGBS and steel fibre. Concrete containing ultrafine GGBS and steel fibre can be used as a partial-substitute for cement in mass concreting projects. However, the structure’s total size is reduced. • This type of work is used in the flooring of the building to provide greater strength at the bottom of the structure.
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• Moreover, optimum incorporation of ultrafine GGBS and steel fibre can effectively improve the concrete compression strength which may prolong the life of the concrete structure. The main conclusion of this report is that increasing the proportion of ultra-fine GGBS and steel fibre replaced with cement increases compressive strength while decreasing workability on similar several grades of concrete.
References 1. Tang K, Millard S, Beattie G (2015) Technical and economical feasibility of using GGBS in long-span concrete structures. Adv Concrete Construct 3(1):1–14 2. Imbabi MS, Carrigan C, McKenna S (2012) Trends and developments in green cement and concrete technology. Int J Sustain Built Environ 1(2):194–216 3. Oner (2007) Cement and Concrete Composites. An experimental study on optimum usage of GGBS for the compressive strength of concrete 29(6):505–514 4. Ahmad J, Martínez-García R, Szelag M, de-Prado-Gil J, Marzouki R, Alqurashi M, Hussein EE (2021) Effects of steel fibers (SF) and ground granulated blast furnace slag (GGBS) on recycled aggregate concrete. vol. 14. Multidisciplinary Digital Publishing Institute, pp 1–23 5. Jaya Krishna T, Venkatesh S, Murali K (2020) Influence on strength and durability analysis of concrete incorporating ultra fine slag. Int J Eng Adv Technol (IJEAT) 8(5):453–456. ISSN: 2249–8958 6. Gupta N, Rashid M, Jauhari N (2020) A review of GGBS and steel fibre performance in high performance concrete. Int J Scient Res Eng Trends 6(4):2540–2544 7. Ali Sadawy M, Faried AS, El-Ghazaly HA (2019) Influence of various types of steel fibre on the mechanical and physical characteristics of GGBS based geopolymer concrete. J Eng Res Reports 12(1):7–19 8. Saranya P, Nagarajan P, Shashikala AP (2019) Development of stress block parameters for steel fiber reinforced GGBS concrete. Songklanakarin J Sci Technol 43(1):8–13 9. Mishra M, Kirar KG, Sharma C (2018) Experimental investigation on the properties of M30 grade of concrete using steel fibre and GGBS (ground granulated blast furnace slag) as partial replacement of cement. Int J Eng Sci Res Technol 7(2):31–40. ISSN: 2277–9655 10. Teng S, Lim TYD, Divsholi BS (2013) Durability and mechanical properties of high strength concrete incorporating ultra-fine ground granulated blast1furnace slag. Constr Build Mater 40:875–881 11. Naik TR (2008) Sustainability of concrete construction. Pract Period Struct Des Constr 13(2):98–103 12. ASTM A-820 (2011) Standard specification for steel fiber reinforce concrete 13. “Alccofine–Micro Materials,” Counto Micro fine Products Pvt. Ltd. (http://www.alccofine. com/) 14. ASTM C 989–05, Standard Specification for Ground Granulated Blast—Furnace Slag for use in concrete and mortars 15. ISO 901:20089, “International Organization for Standard”
Analytical Hierarchy Process in the Maintenance Decision-Making of Interlocking Concrete Block Pavements Ripunjoy Gogoi, Bhupali Dutta, P. Mahakavi, and Prince Akash Nagar
Abstract Maintenance prioritization helps in the efficient allocation of resources and time to preserve pavement sections in their serviceable state. The present study illustrates the Analytical Hierarchy Process (AHP), a multi-criteria decision-making tool, to determine the maintenance requirements of Interlocking concrete block pavements (ICBPs) in a road network. The results show that the AHP method can consider multiple distress of concrete block pavements at once and can efficiently identify the severely distressed pavements for immediate maintenance work. Keywords Analytic hierarchy process · Interlocking concrete block pavement · Pavement distresses · Pavement maintenance · Priority ranking
1 Introduction Interlocking concrete block pavement (ICBP) has been used as low volume traffic roads and construction of parking lots and bays. The maintenance of ICBP depends on the type of distress and the extent of the distresses. Often, due to budget limitations, it is difficult for a highway agency to consider the maintenance need for all the pavement sections in a network simultaneously. Hence, the prioritization-ranking model helps to identify the severe pavement sections and schedule their maintenance. Analytical hierarchy process (AHP) can be used to develop such a maintenance prioritization model of ICBP. The primary advantage of AHP is that it incorporates the engineering R. Gogoi (B) · P. Mahakavi · P. A. Nagar Department of Civil Engineering, Amity University, Noida, Madhya Pradesh, India e-mail: [email protected] P. Mahakavi e-mail: [email protected] B. Dutta Department of Civil Engineering, NIT Jamshedpur, Jamshedpur, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_9
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judgment of experts in decision-making [1, 2]. In AHP, weights are assigned to various factors (criteria/sub-criteria) influencing the objective function. The weights are determined based on a pair-wise comparison of the factors obtained from experts [3, 4]. A factor is assumed significant if it is assigned a higher weight. The opinions of the experts can be obtained through a questionnaire survey [5, 6]. AHP is used in different decision-making areas such as (a) priority and ranking evaluation [5, 7], (b) development of efficient prediction models [8, 9], and (c) selection methodology [10]. Recently, Gogoi and Dutta [11] have used the fuzzy technique for the maintenance prioritization of interlocking concrete block pavements. However, from a review of past literature, it seems that AHP has not been employed for the maintenance prioritization of interlocking concrete block pavements. Moreover, due to advantages of AHP such as (a) formulating a comprehensive decision-making problem, (b) identification of analysis error by inconsistency coefficients, and (c) incorporating various suggestions in the group decision-making problem formulation; AHP seems to be an efficient tool for be employed for maintenance urgency prioritization of ICBP. This is the primary motivation of the present study. The outline of the present work is given here. The objective of the present study is stated in Sect. 2. The analysis using the AHP method is discussed in Sect. 3. The observation and conclusion of the study are summarized in Sect. 4.
2 Objective The present study is an attempt to develop a maintenance prioritization model for concrete block pavements in the roadway network by using AHP. A survey was conducted among experienced highway professionals to incorporate engineering judgment in decision-making. The pavement distress considered in this study is rutting (R), depression (D), pumping (P), damaged pavers (DP), faulting (F), missing pavers (MP), heaving (H), horizontal creep (HC) and patching (PG) [12]. For verification purpose, the results obtained from the proposed AHP method are compared with the Simple additive weight (SAW) method, a traditional ranking method [13, 14].
3 Methodology The methodology to develop the proposed method is discussed in the sections ahead. The distress data collected from the road network and pavement distresses used in the present study are discussed in Sect. 3.1. In Sect. 3.2, the present AHP methodology is discussed. The process to estimate the criteria weights and alternative scores are also discussed in Subsection 3.2.1. In the present study, the result obtained from the AHP is compared with a traditional ranking method called SAW and is discussed in Sect. 3.3. In SAW analysis, the condition of ICBP is measured in terms of the Pavement Condition Index (PCI) [12].
Analytical Hierarchy Process in the Maintenance Decision-Making … Table 1 Details of the studied ICBP road network
105
Section
Length (meter)
Average width (meter)
RKM road
1040
11
Bye lane 1
154
7.6
Bye lane 2
173
7.6
Bye lane 3
157
7.6
Bye lane 4
137
6
Bye lane 5
134
6
Bye lane 6
138
6
K.M. road
661
11
Khargeswar road
138
6
3.1 Selection of ICBP Road Network Visual assessments were carried out in Guwahati, a city in North East India to select an appropriate ICBP road network. For the present study, nine ICBP road sections were found suitable for the study. The following information has been collected for the road network: (a) road name, (b) road type, (c) road width, and (d) length of the road (refer to Table 1). The network of the road falls in a residential area and undergoes light traffic movement comprising cars, auto-rickshaw, minivans, twowheelers, etc. However, water tankers, school buses, and garbage trucks are also often seen plying on these roads during peak hours. It is observed that the selected ICBP sections were prone to distress such as rutting, pumping, depression, damaged pavers, missing pavers, edge restraint, patching, etc. The distress data were collected manually by carrying out an on-field survey.
3.2 Proposed Analytical Hierarchy Process (AHP) for Maintenance Prioritization The different features of the AHP decision-making model of the present study are shown in Fig. 1. A general AHP model consists of three major components, which are: an objective, criteria(s), and alternatives. Estimation of weights (or relative importance) of the criteria and the priority scores of alternatives with respect to the objective(s) will help to arrive at the problem objectives. As shown in Fig. 1, the objective of the study is defined and an expert survey was conducted to estimate the various weights of criteria and priority scores of alternatives. The experts’ opinion is based on the pavement distress type and its relative importance for maintenance prioritization. To estimate the weights of criteria and scores of alternatives, the pairwise comparison is performed through experts’. Experts were requested to participate in a questionnaire. In the questionnaire survey, experts compare factors at a certain level to each other regarding their impact on a factor that is at a higher level.
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The pair-wise comparison between various factors (criteria/sub-criteria) is made by using the Saaty scale (refer to Table 2). At first, priority weights are obtained for the criteria concerning their relative importance to arrive at the problem objective. Next, the scores are estimated for the alternatives with respect to each criterion. Pairwise comparison matrices were required to be formed based on the expert’s judgment on the relative importance of different factors as discussed above. For the detail on how to derive the decision matrix one may refer to [1, 5]. Finally, overall priorities for the alternatives were estimated by weighting and adding method to find how they contribute to the overall objective [3, 4]. However, if the consistency is greater than 10%, the set of judgments may not be acceptable because of their inconsistency [1]. The estimated priority weights of the distress are given in Table 3. The alternative priorities are estimated concerning the severity extent of the pavement distress. As discussed already, these priorities are estimated based on a pair-wise
Fig. 1 AHP framework of the study
Table 2 Relative importance of various factors based on Saaty’s scale [1] Scale
Importance
Description
1
Equal significance
Two factors have equal importance to the objective
3
Moderate significance
A factor is moderately important than the other factor
5
Strong significance
A factor is strongly important than the other
7
Very strong significance
A factor has given very strong importance than the other factor
9
Extreme significance
A factor is extremely important than the other factor
2, 4, 6, 8
Intermediate significance between two factors
Analytical Hierarchy Process in the Maintenance Decision-Making …
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Table 3 Priority weights of distresses Weights
R
D
DP
P
F
PG
MP
H
HC
0.19
0.15
0.12
0.13
0.06
0.11
0.12
0.06
0.05
R: Rutting; D: Depression; DP: Damaged Pavers; P: Pumping; F: Faulting; PG: Patching; MP: Missing Paver; H: Heaving; HC: Horizontal Creep
Table 4 Priority score of sections with respect to distresses Section
R
D
DP
P
F
PG
MP
H
HC
1
0.12
0.15
0.14
0.14
0.11
0.20
0.10
0.10
0.10
2
0.12
0.18
0.10
0.10
0.11
0.10
0.16
0.12
0.11
3
0.15
0.10
0.11
0.10
0.11
0.11
0.17
0.16
0.10
4
0.12
0.11
0.10
0.09
0.14
0.10
0.10
0.14
0.10
5
0.10
0.10
0.15
0.14
0.11
0.11
0.10
0.11
0.17
6
0.08
0.08
0.08
0.10
0.12
0.10
0.10
0.09
0.09
7
0.10
0.09
0.10
0.10
0.10
0.10
0.12
0.09
0.14
8
0.13
0.10
0.13
0.14
0.11
0.08
0.08
0.10
0.09
9
0.08
0.09
0.08
0.09
0.11
0.09
0.08
0.09
0.09
comparison based on Saaty’s scale. Table 4 shows the priority scores of the sections concerning the nine distresses.
3.2.1
AHP Priority Ranking of ICBP Sections
Finally, using the weighting and adding process, the overall priority scores of the pavement sections (alternatives) were obtained which contribute to the objective i.e. maintenance prioritization. The final score of each section is calculated as per the following formula shown in Eq. (1) [1]. The final rating is calculated by multiplying the final score with 100. TP =
n ∑
Cwi × S pi
i=1
where, TP = final score Cwi = Weight of ith distress (refer to Table 3) S pi = Score of ith distress of the pth section n = number of distresses considered.
(1)
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Table 5 Priority rank of ICBP sections as per the AHP method
Section
Priority rank
RKM road
1
Bye lane 1
2
Bye lane 2
3
Bye lane 3
5
Bye lane 4
4
Bye lane 5
8
Bye lane 6
7
K.M. road
6
Khargeswar path
9
Table 5 shows the final priority ranks of the pavement sections of the road network calculated by the method discussed above. It can be seen that the RKM road is in the worst state and needs immediate attention for maintenance. The results thus obtained will be cross verified by the SAW method which is discussed in the next section.
3.3 Estimation of Priority Ranking of ICBP Pavement Sections by SAW Method To verify the ranking results obtained from AHP, the simple additive weighted method (SAW) has been used. The priority ranks of the road sections obtained by both methods are compared. To estimate the SAW ranking, scores are calculated based on the distress severity rating and PCI value of the pavement sections [13, 14]. The severity rating of particular distress (refer to Table 6) and the individual PCI value of distresses are multiplied as shown in Eq. (2) to find the section severity ranking [15]. K i = PC Ii × Ri ,
(2)
where, K i = Individual score of alternative i. PC Ii = PCI value of each alternative i. Ri = Average severity rating of particular distress as per decision-makers.
Table 6 Rating of distresses from binning technique Avg. of rating
R
D
DP
P
F
PG
MP
H
HC
2.25
2.2
2
3
2
1.5
3.4
1.7
1.5
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Then, the score for a particular pavement section is determined using Eq. (3) [15]. ∑n ki EOSi = ∑ni , R i i
(3)
where, EOSi = Extent of severity for pavement section i. n = Number of distresses considered (in this case n = 9). The estimation of the PCI value of ICBP is discussed in the next section. An example problem is also presented to show the calculation of the PCI value of the RKM road section.
3.3.1
PCI Value Determination of Interlocking Concrete Block Pavements
Determinations of PCI value of pavements are discussed from Step 1 to Step 5. Two distresses: rutting and damaged paver blocks have been considered as an example to explain the method. However, all the possible ICBP distress types may be considered to estimate the distress density of individual distresses [12]. Step 1: Measure the severity extent (rutting and damaged paver blocks) and then measure the density for the pavement section by using the following equations:
Rutting density (%) =
Distress depth (mm) × 100 Area of section (sq.m)
Damaged paver block density (%) =
Distress area (sq.m) × 100 Area of section (sq.m)
Step 2: Chart (a) and Chart (b) are used to estimate the deduct values for distressed rutting and damaged paver blocks respectively (refer to Fig. 2). Step 3: Now, the algebraic sums of the two deduct values estimated from Step 2 would give the Total Deduct Value (TDV). Step 4: If required, Total Deduct Values would be adjusted. Further, the Corrected Deduct Value (CDV) would be estimated by using Chart (c). Step 5: By using the formula, Pavement Condition Index, PCI = 100−CDV, find the PCI value for all the Interlocking concrete block pavement sections.
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Fig. 2 Curves to estimate the PCI values of interlocking concrete block pavement [12]
A Numerical Example to Estimate the PCI Value of an ICBP Road Section with Rutting Distress An example problem is discussed here to estimate the rutting distress density of the RKM road below. Cross-sectional area of RKM road = 11, 440 m2 Low severity rutting present on the road = 175 m2 Moderate severity rutting present on the road = 375 m2 175 × 100 = 1.53% The density of distress (low) = 11440 375 The density of distress (High) = × 100 = 3.27% 11440 The charts have three categories of distress measurement, which are High (H), Medium (M), and Low (L). Thus, from the deduct value curve (using low (L), from Chart (a)), the estimated deduct value obtained is equal to 11. Similarly, from the same deduct value curve, the estimated deduct value (high (H), using chart (a)) is equal to 42. Therefore, the total deduct value of RKM road for rutting distress is = 11 + 42 = 53. As seen, there are two values greater than ten percent. Thus, the PCI value
Analytical Hierarchy Process in the Maintenance Decision-Making … Table 7 Maintenance ranking of ICBP sections as per SAW method
Section
111
SAW ranking
RKM road
1
Bye lane 1
2
Bye lane 2
5
Bye lane 3
8
Bye lane 4
3
Bye lane 5
7
Bye lane 6
4
K.M. road
6
Khargeswar path
9
needs correction [12]. Therefore, q is equal to 2 and for TDV = 53, Corrected deduct value, CDV (from Chart (c)) is equal to 35. The final PCI value of the RKM Road = 100−35 = 65. Similarly, the PCI values of all the sections concerning individual distress were found. In the present study, to estimate the SAW ratings, individual ICBP distresses are categorized into five different groups. To rate the distresses based on their severity and extent, the equal-width binning technique is adopted. For detail on the equal width binning technique, one may refer to [16]. The distress data, collected from the field, is in groups ranging from scale 1–5. A rating value of 1 here indicates that the pavement is in very poor condition and a rating of 5 indicates that the pavement is in very good condition. To analyze and classify the data by using the equal width binning technique, MATLAB software has been used. The ratings of individual distress are given in Table 6. The results obtained from the analysis (using Eq. 3) are given in Table 7 and Fig. 2.
3.4 Statistical Assessment of Priority Rankings Obtained from AHP and SAW Methods From Tables 5 and 6, it is seen that there is a difference in the ranking listing of ICBP sections obtained from the AHP and SAW analysis. From Fig. 3, it is seen that a possible linear trend exists between the rankings. To find the fitness of the trend, the Spearman correlation coefficient test was performed. The Spearman rank correlation coefficient, rs , is estimated using the following Eq. (4) [17]. The correlation coefficient will give the degree of correlation between the rankings obtained from the two methods. [ ∑ ] n 2 i=1 di ( ) , rs = 1 − 6 × (4) n × n2 − 1
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y = 0.8x + 1
8
SAW
7 6 5 4 3 2 1 0 0
1
2
3
4
5
6
7
8
9
10
AHP
Fig. 3 Comparison of maintenance rank of ICBP sections between AHP and SAW method
where, di is the difference in ranks obtained from AHP and SAW method for an individual ICBP section i; n is the total number of the alternatives. Results from the analysis show that the Spearman correlation coefficient is equal to 0.8 (refer to Table 8). It implies that the ranking of pavement sections produced by AHP is consistent with the SAW method. Hypothesis testing is done to find the significance of the Spearman correlation coefficient. Null and alternate hypotheses are mentioned in Eqs. (5) and (6) respectively. For n > 8, the significance of Spearman correlation is estimated using Eq. (7) [17]. H0 :rs = 0
(5)
H1 :rs > 0
(6)
t=√
rs (1−rs2 )
(7)
(n−2)
The results of the analysis are given in Table 8. Based on the analysis, the null hypothesis has been rejected, and thus, it shows that the ranking estimated by AHP and SAW methods are statically consistent.
Analytical Hierarchy Process in the Maintenance Decision-Making … Table 8 Statistical analysis results for rank co-relation
Statistic
AHP and SAW method comparison
Observations
9
Degrees of freedom
7
Confidence level tested
95%
Spearman rank correlation coefficient
0.8
Student’s t statistics (t n−2 )
3.57
Critical one-sided t-value
1.89
Result
t n−2 > t-value
Conclusion
Reject H 0
113
4 Conclusions The present study has illustrated the method of AHP for the maintenance prioritization of interlocking concrete block pavements in a road network. The rankings for the maintenance prioritization of the individual pavement sections of the roadway network as per the results obtained from the AHP analysis were subsequently compared with the SAW method. Spearman rank correlation test showed that there was no difference between the rankings obtained by AHP and SAW methods. The present study has demonstrated that AHP can work very efficiently in the maintenance prioritization of the ICBP road network.
References 1. Saaty TL (1980) The analytic hierarchy process, planning, priority setting, resource allocation. McGraw-Hill, New York 2. Ziara M, Nigim K, Enshassi A, Ayyub BM (2002) Strategic implementation of infrastructure priority projects: case study in Palestine. J Infrastruct Syst ASCE 8(1):2–11 3. Larson CD, Forman EH (2007) Application of analytic hierarchy process to select project scope for videologging and pavement condition data collection. Transp Res Rec 1990(1):40–47 4. Prakasan AC, Tiwari D, Shah YU, Parida M (2015) Pavement maintenance prioritization of urban roads using analytical hierarchy process. Int J Pavement Res Technol 8(2) 5. Farhan J, Fwa TF (2009) Pavement maintenance prioritization using analytical hierarchy process. Transp Res Record: J Transp Res Board 2093:12–24 6. Jain S, Parida M (2012) Evaluation of prioritization methods for effective pavement maintenance of urban roads. Int J Pavement Eng 1–13 7. Bandara N, Gunaratne M (2001) Current and future pavement maintenance prioritization based on rapid visual condition evaluation. J Transp Eng 127(2):116–123 8. Al-Barqawi H, Zayed T (2008) Infrastructure management: Integrated AHP/ANN model to evaluate municipal water main’s performance. J Infrastruct Syst 14(4):305–318 9. Ouma YO, Opudo J, Nyambenya S (2015) Comparison of fuzzy AHP and fuzzy TOPSIS for road pavement maintenance prioritization: methodological exposition and case study. Adv Civil Eng
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10. Dweiri F, Al-Oqla FM (2006) Material selection using analytical hierarchy process. Int J Comput Appl Technol 26(4):182–189 11. Gogoi R, Dutta B (2020) Maintenance prioritization of interlocking concrete block pavement using fuzzy logic. Int J Pavement Res Technol 13:168–175 12. ASTM E2840–11 (2011) American Society of testing and materials, standard practice for pavement condition index surveys for interlocking concrete roads and parking lots, ASTM International, West Conshohocken, PA 13. Memariani A, Amini A, Alinezhad A (2009) Sensitivity analysis of simple additive weighting method (SAW): the results of change in the weight of one attribute on the final ranking of alternatives. J Optim Indus Eng 4:13–18 14. Kanuganti S, Agarwala R, Dutta B, Bhanegaonkar PN, Singh AP, Sarkar AK (2017) Road safety analysis using multi criteria approach: a case study in India. Transport Res Proc 25:4649–4661 15. Zionts S, Wallenius J (1983) An interactive multiple objective linear programming method for a class of underlying nonlinear utility functions. Manage Sci 29(5):519–529 16. Han J, Pei J, Kamber M (2011) In: Data mining: concepts and techniques. Elsevier 17. Gujarati DN (2004) In: Basic econometrics. Tata McGraw-Hill Education
An Effective Use of Agricultural Waste as Silpozz in Concrete Lovely Sabat, Subhajit Dey, Arundaya Sabat, and Minakshi Mishra
Abstract The solid wastes are one of the major threats to our environment which can be naturally occurring, industrial or agricultural wastes. Dumping such wastes will cause adverse effect on the environment and human health, so better to use these as supplementary cementing materials. The production of cement results in CO2 emissions into the atmosphere and is also high in cost. In recent times, constant researches are going on for replacement of cement by such green materials with cementing and pozzolanic characteristics. The present experimental analysis aims at the effective usage of silpozz in the concrete for which M40 grade concrete has been designed by substituting OPC with silpozz in varying proportions of 5, 10 and 15%. The fresh concrete tests followed by the strength test were carried out, and comparison is done with the control concrete along with a brief cost analysis. The workability characteristics and the density of concrete reduce with enhancement of the workability up to 10%. It was observed that with 10% of replacement, the compressive strength and flexural strength obtained were 6.26 and 5.49% more than the strength attained in case of the control specimen, respectively, and further addition of silpozz resulted in reduction in strength and reduction in cost of concrete production up to 15–20% of cement content and resulted in cost-efficient concrete. Keywords Solid wastes · Silpozz · Pozzolanic material · Compressive strength · Flexural strength
L. Sabat (B) · M. Mishra REVA University, Bangalore, India e-mail: [email protected] M. Mishra e-mail: [email protected] S. Dey Hi-Tech Institution of Technology, Bhubaneswar, India A. Sabat Parala Maharaja Engineering College, Berhampur, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_10
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1 Introduction The solid wastes are one of the major threats to our environment. These wastes can be naturally occurring waste materials or as by-products obtained from some other source materials, or it may be some type of industrial wastes and agricultural wastes. Dumping these wastes on earth surface can cause adverse effect on the environment, so it could be better to use them as a cementing material in the concrete if possible. Industrial and agricultural wastes products like plastic wastes, GGBS, rice husk ash, and fly ash, fibers like timber or steel fibers and glass fibers can be used in concrete as a bending material up to some percentage as an alternate to cement. The production of the cement results in CO2 emissions into the atmosphere. It contributes nearly 5–7% of carbon dioxide emission globally [1–3]. So from a recent time, there is a constant research to replace the cement with green materials having pozzolanic characteristics by treating such wastes materials mentioned above and can be used to improve the concrete properties [7–9, 14]. Annual production of rice is about 600 million tons globally, and India being the second largest producer and produces more than 90 million tones every year. The rice husk left out as a waste after the milling of paddy can be used for effectively. After harvesting, the paddy is dried up to reduce the moisture content from about 25–14% followed by milling in which the husk is removed, and this husk is left out as a waste. This rice husk is generally used for feeding cattle or is simply dumped as a waste but nearly with 200 kg of rice husk from 1MT of rice grains (20% by weight) are left out as waste that can be used effectively by converting it into non-crystalline amorphous ash, i.e., rice husk ash [4, 5]. So the rice husk ash is a pozzolanic material, and the product is obtained from regulated burning of rice husk at a temperature ranging within 600–850 degrees is identified by the trade name Silpozz. It is highly reactive with super pozzolanic properties and can be used as an admixture to make special concrete. In the present time, silica fume or micro silica is being used as an alternative or mineral admixture in concrete as a replacement to cement in the concrete [6]. But due to its limited supply in India, the price of these admixtures has raised a lot. Thus Silpozz can be a cheap and effective admixture. The application areas are:1. 2. 3. 4. 5. 6.
High strength and low permeable concrete. Industrial flooring. Water tanks and sumps. Chemical storage tanks. Basements and sewerage pipelines. Refractory mixes etc.
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2 Literature Review With such amount of rice production and rice husk wastes, many experiments have been conducted to find the use of amorphous silica in the process of making concrete. The Indian standard code ‘IS 456: 2000’ has recommended that for plain and reinforced concrete, the rice husk ash may be used by the approval of the authority if it gives required performance and uniformity characteristics, but the specific amount is not mentioned in the code. So many research and experiments have been conducted to find the effectiveness of using silpozz as a pozzolanic material in the concrete and the amount of silpozz that can be used as a replacement of ordinary Portland cement [10]. It is seen that the replacement by rice husk ash has resulted in the decrease in the workability of concrete by a slump of 27% [13]. It is seen from the results that there are less deviations in the strength properties of rice husk ash concrete in the initial days of test whereas the strength of concrete increases at higher curing period [11]. Silpozz has a characteristic to react with calcium hydroxide, which is generated due to hydration process of cement and helps to form additional cementitious material [12]. The reactivity depends on the content of non-crystalline silica content and surface area of ash particles. Silpozz particles are of size of less than 25 microns which is much finer than cement particles. These Silpozz particles containing high content of amorphous silica fill the voids between the cement particles and aggregates. From various studies it is also observed that due to the presence of amorphous silica and due to large surface area, it can replace cement up to 15% by weight without causing much adverse effect on the strength of the concrete [14]. Minimizing the environmental issues of disposing or utilizing the solid wastes generated was discussed by many researchers, and they concluded the use of ash from burning of rice husk is an effective way to replacement cement in the concrete, especially for grades of M20 and M30 concretes. It is observed that by using rice husk ash which is generated from rice husks waste as a cement replacement in concrete can result in the decrease of the emission of greenhouse gases by lowering the demand for cement along with feasibility of production of low cost or economical concrete for the construction works [15, 16].
3 Materials Used in the Work 3.1 Cement The cement used in the present trial research is the Ordinary Portland Cement (OPC 53). Tests were conducted for the physical properties conforming to the requirements of IS 12269: 2013. From the tests carried out, the values obtained are stated in Table 1. The chemical properties as acquired from the supplier are stated in Table 2. The cement used can be seen in (Fig. 1).
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Table 1 Tested properties of OPC of 53 grade Sl. No.
Physical properties
Average
Value specified by IS 12269:2013
1
Normal consistency
31
–
2
IST (min)
140
30 (min)
3
FST (min)
260
600 (max)
4
Residue (by 90 micron)%
3.5
10% (max)
5
3 days compressive strength in N/ mm2
32.53
27 (min)
6
7 days compressive strength in N/ mm2
42.30
37 (min)
7
28 days compressive strength in N/ mm2
60.47
53 (min)
Table 2 Chemical properties of cement used (OPC 53) Chemical requirements
Results obtained
Value specified by is 12269:2013
CaO%-0.7 SO3 %/2.8 SiO2 + 1.2 Al2 O3 + 0.65 Fe2 O3
0.83
0.80–1.02
Al2 O3 %/ Fe2 O3 %
1.64
Minimum 0.66
Insoluble residue(% by mass)
1.85
Maximum 5.0
Magnesia (% by mass)
1.59
Maximum 6.0
Sulfuric anhydride (% by mass)
2.38
Maximum 3.5
Total loss upon ignition(% by mass) 3.47
Maximum 4
Chloride content(% by mass)
Maximum 0.10
Fig. 1 Ordinary Portland cement (OPC 53)
0.010
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Fig. 2 Chemical admixture (SIKA VISCOCRETE 2000NS)
3.2 Water and Chemical Admixture Clean water was used for mixing of all dry ingredients and making the concrete. The chemical admixture used in the work is super plasticizer SIKA VISCOCRETE 2004NS which is Polycarboxylate Ether (PCE) based super plasticizer confirming to IS 9103:1999 (Fig. 2).
3.3 Fine Aggregate Sand confirming to Zone-III specifications after gradation was used as fine aggregate. The specific gravity of sand was obtained as 2.64 and the water absorption as 1.317%. The bulk density of 1622 kg/m3 was obtained from the experiments conducted. The sieve analysis of fine aggregates was done as shown in Table 3 (Fig. 3).
3.4 Coarse Aggregate For coarse aggregate, crushed stones of 10 mm nominal size were used with respect to IS 383–1970. The fineness modulus 2.87 from the sieving carried out. The aggregate has water absorption 0.503%, bulk density of 1650 kg/m3 and bulk density of 1650 kg/ m3 . The sieve analysis has been carried out and the gradation is tabled as below in Table 4 and seen as in Fig. 4.
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Table 3 Gradation carried out for fine aggregate IS sieve size (mm)
Weight retained (gm)
Cum. weight of retained (gm)
% of cum retained
% of cum passing
Value specified by IS 383–1970 in % (Zone-III)
10.00
0
0
0.0
100.0
100
4.750
0
0
0.0
100.0
90–100
2.360
22
22
2.2
97.8
85–100
1.180
46
68
6.8
93.2
75–100
0.600
212
280
28.0
72.0
60–79
0.300
538
818
81.8
18.2
12–40
0.150
160
978
97.8
2.2
0–10
PAN
22
1000
100.0
0.0
– Fineness Modulus
Fig. 3 Fine aggregate (Sand)
Fig. 4 Coarse aggregate (10 mm size)
Remarks
ZONE-III
= 2.17
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Table 4 Gradation carried out for coarse aggregate Sieve arrangeme nt (mm)
Weight retained Cum. weight (gm) of retained (gm)
% of cum retained
% of cum passing
Value specified by IS 383–1970 in %
16.00
0
0
0
100
100
12.50
0
0
0
100
100
10.00
139
139
4.63
95.37
85–100
4.75
2521
2660
88.67
11.33
0–20
340
3000
100
0
0–5
PAN
3.5 Silpozz Silpozz is used as a mineral admixture to substitute the Portland cement. Silpozz is available in form of solid non- hazardous, gray-black color powder. The usage of rice husk ash in concrete is recommended in IS 456:2000, but the amount to be added is not specified. The properties of Silpozz are mentioned in Tables 5 and 6 (Fig. 5).
3.6 Mix Proportioning and Experimental Details The mix proportion for concrete of M40 grade was intended following the IS 10262: 2009 code. The ordinary Portland cement was substituted or replaced by Silpozz in proportions of 5, 10 and 15%. The control concrete was denoted as Table 5 Physical properties of Silpozz
Table 6 Chemical properties of Silpozz
Specific gravity of silpozz
2.3
Size of particle
Less than 45 micron
Bulk density
0.58gm/cc
Moisture content
1.87%
Oxides
Silpozz (%)
Silica
88.64
C
2.33
CaO
1.09
MgO
1.76
K2 O
1.98
Al2 O3
1.23
Fe2 O3
1.19
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Fig. 5 Silpozz
C1S0, i.e., Cement 100%, fine aggregate 100%, coarse aggregate 100%, and Silpozz 0%. Table 7 denoted as mix that shows varying proportion of silpozz as replacement of OPC in concrete. C2S1 denotes 5% of OPC is replaced by silpozz in the mix, similarly other two mixes can be recognized. Table 8 denotes the details of the quantity of mix design of the concrete mix (Fig. 6). The workability of all the concrete mixes was tested by adopting the slump cone test, and the density test was done following the specifications of IS 1199: 1959. After conducting the workability test and the density measurement, the casted cube and beam samples were casted and kept for curing, and the strength properties were tested later. The compressive and flexural strength tests were conducted for 7 and 28 days and for each day testing three samples were casted. The cube size for the Table 7 Nomenclature for various mix proportions Concrete mixes and its proportions
Mix identity
Cement 100% + FA 100% + CA 100%
C1S0
Cement 95% + FA 100% + CA 100% + S 5%
C2S1
Cement 90% + FA 100% + CA 100% + S 10%
C3S2
Cement 85% + FA 100% + CA 100% + S 15%
C4S3
Table 8 Details of concrete mix quantity per m3 of concrete Mix identity
Glass fiber (%)
Silpozz (%)
C1S0
0
0
Cementitious constituents (Kg) OPC
Silpozz
Fine aggregate (Kg)
430
0
1008.36
Coarse aggregate (Kg)
Water (Kg)
SP in (Kg)
901.02
165
1.29
C2S1
0
5
408.5
21.5
1008.36
901.02
165
1.29
C3S2
0
10
387
43
1008.36
901.02
165
1.29
C4S3
0
15
365.5
64.5
1008.36
901.02
165
1.29
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Fig. 6 Mixing of all the constituents
Fig. 7 Casted cubes and beam specimens for flexural strength test
compressive strength test is (150 × 150 × 150) mm, and the flexural strength test beams of size (150 × 150 × 700) mm were casted (Fig. 7).
4 Results Obtained and Discussions 4.1 Workability and Density Measures of Concrete Mixes The slump value of the control concrete (C1S0) is maintained to be 100 mm during the whole procedure. From Fig. 8, we can say that with 10% replacement of cement by Silpozz, the slump value decreased with enhancement of workability of the concrete, but with 15% replacement of cement by Silpozz was done a dry mix which is not suitable as concrete was obtained. This is because the particle size of Silpozz is smaller and its specific surface area is large, so some quantity of water is absorbed by the Silpozz particles making the concrete dry, and thus the water available for the concrete for its fluidity was decreased. The obtained values of slump and density of concrete are in Table 9 (Fig. 9).
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Fig. 8 Slump and density measurement of all concrete mixes
Table 9 Slump cone test and density of concrete results
Mix identity
W/C ratio
Slump value (mm)
Density of concrete (gm/cc)
C1S0
0.383
100
2.544
C2S1
0.383
95
2.527
C3S2
0.383
80
2.522
C4S3
0.383
65
2.518
Fig. 9 Slump test results of concrete
110 100 90
VALUE (mm)
80 70 60 50 40 30 20 10 0 C1SO
C2S1
C3S2
C4S3
MIX IDENTITY
The density of the control concrete (C1S0) was obtained as 2.544 gm/cc. From the density test results, it was detected that, as the percentage of replacement of cement increases, the density of the concrete slightly decreases. This is due to lower value of specific gravity of Silpozz that resulted in the decrease in the mass per unit volume as seen in Table 9 and Fig. 10.
DENSITY OF CONCRETE (gg/cc)
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2.63 2.48 2.32 2.17 2.02 1.86 1.71 1.55 1.40 1.24 1.09 0.93 0.78 0.62 0.46 0.31 0.16 0.00 C1S0
C2S1
C3S2
C4S3
MIX IDENTITY Fig. 10 Density test results of concrete
4.2 Compressive Strength Test Results From Fig. 11, it is noted that the 7 days and the 28 days average compressive strength of C1S0 mix were obtained as 59.9 MPa and 70.2 MPa. The compressive strength of mix (C2S1), i.e., with 10% replacement increased by 6.27% as compared to control concrete, but replacement beyond 10%, i.e., 15%, the compressive strength decreases by 5.27%. So the optimum replacement of cement by Silpozz is near to 10% (Table 10).
4.3 Flexural Strength Test Results From Table 11, the average flexural strength of the control concrete mix (C1S0) was obtained as 4.57 MPa and 6.19 MPa for 7 and 28 days, respectively. For the cement replacement by Silpozz up to 10%, the flexural strength of concrete is enhanced by 5.49%, but for replacement beyond 10%, the flexural strength decreased by 2.10%. So the optimum replacement of cement by Silpozz is near to 10% (Figs. 12 and 13).
4.4 Cost Estimation and Comparison The cost estimation of concrete includes the cost of the materials, mix design adopted, site conditions, machinery used, schedule of the project, cost for transportation, and the cost of mixing and placing the concrete in the frame. In the present study, the cost
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COMPRESSIVE STRENGTH (MPa)
126 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10
0% SILPOZZ 5% SILPOZZ 10% SILPOZZ
5 0
15% SILPOZZ
7 days test
28 days test
AGE OF CONCRETE Fig. 11 Comparison of compressive strength test results Table 10 Compressive strength test results of the mixes 7 Days results Mix identity
28 Days results Average compressive strength (MPa)
% Change in strength
Average compressiv e strength (MPa)
% Change in strength
C1S0
59.9
0
70.2
0
C2S1
60.0
0.1
71.1
1.2
C3S2
60.8
1.5
74.6
6.2
C4S3
57.1
−4.6
66.5
−5.2
Table 11 Flexural strength test results of the mixes Mix identity
7 Days results Average flexural strength (MPa)
28 Days results % change in strength
Average flexural strength (MPa)
% change in strength
C1S0
4.57
0
6.19
0
C2S1
4.68
2.40
6.33
2.26
C3S2
4.84
5.90
6.53
5.49
C4S3
4.52
−1.0
6.06
−2.10
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7.0
FLEXURAL STRENGTH (MPa)
6.5 6.0 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 0% SILPOZZ 5% SILPOZZ 10% SILPOZZ 15% SILPOZZ
1.5 1.0 0.5 0.0
7 days test
28 days test
AGE OF CONCRETE Fig. 12 Flexural strength test results Fig. 13 Compressive and flexural strength testing machine with beam sample
of 1 m3 of concrete was carried out, and other basic expenses for preparation and placing of concrete were included. The cost of each material was noted and multiplied with the quantity of materials used in making the concrete to get the estimated cost of the concrete.
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Considering the concrete mix of M40 (1:2.34:2.09), with coarse aggregate of size 10 mm and adopting w/c ratio of 0.383. The weights of materials for 1 m3 concrete for the control concrete are: Materials
C1S0
C2S1
C3S2
C4S3
Weight of cement (Kg)
430
408.5
387
365.5
No of bags
8.6
Weight of Silpozz (Kg)
0
No of bags
0
No. of bags of cement =
weight of cement Weight of 1 bag weight of silpozz Weight of 1 bag 3
8.1
7.7
7.3
21.5
43
64.5
1.07
=
430 50 21.5 20
No. of bags of silpozz = = Volume of fine aggregate = 0.62 m Weight of Fine aggregate = 1008.36 kg Volume of coarse aggregate = 0.546 m3 Weight of Coarse Aggregate = 901.02 kg Weight of Water = 165 kg. Weight of super plasticizer = 1.29 kg.
2.15
3.22
= 8.6 bags = 1.07 bag
As per latest market rate, the cost of control concrete will be Sl No.
Items
Cost of items for 1 m3 of volume (in Rupees)
Total cost of the items (in Rupees)
1
Cement
450/bag
3870
2
Silpozz
25/bag
0
3
Fine aggregate
1400
868
4
Coarse aggregate
2400
1310.4
5
Super-plasticizers
75
134.25
6
Water
1
165
The below table shows the cost of concrete for the control concrete of M40 grade and various other mixes formed by replacing cement by silpozz at different proportions (Table 12). The cost of control concrete with 0% replacement of ordinary Portland cement by Silpozz has come out to be 7347.65 rupees per cum as seen in Table 6. As the percentage is increased to 5% and then to 10%, the cost of concrete production is reduced by 2.7–4.78%. With further replacement of cement by Silpozz up to 15%, the cost of concrete further decreases by 6.86%. For bigger construction projects, the cost of concrete can be reduced by much higher percent. So from Fig. 14, it can be observed that we can produce low-cost concrete by replacing cement with Silpozz up to 10% effectively without adhering the basic properties of concrete.
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Table 12 Cost analysis of the concrete mixes Grade Sample Total cost Mixing and placing cost Total cost per % change in the cost of per Cum (Indian rupees) Cum of wrt to control concrete concrete concrete (Indian Rupees) M40
C1S0
6347.65
1000
7347.65
–
C2S1
6149.15
1000
7149.15
−2.70
C3S2
5996.40
1000
6996.40
−4.78
C4S3
5843.15
1000
6843.15
−6.86
Fig. 14 Concrete mix estimation results
5 Conclusion From the present experimental work, it was observed that there is reduction of the slump value as the percentage replacement of cement by Silpozz increases, and results in a dry concrete mix with a higher percentage of Silpozz. The density of the concrete is reduced after replacing cement by Silpozz. For the strength properties of the concrete, it was observed that with 10% replacement, there was an increase of compressive strength by 6.26% and in flexural strength by 5.49% than that of the control specimen, respectively, but further addition of Silpozz resulted in reduction of both the strengths. So the percentage of optimum replacement of Silpozz in cement was near to 10%. From the estimation carried out, it was concluded that as the amount of cement required was reduced that resulted in cost reduction for concrete production, i.e., as per the results obtained in the current experiments for M40 concrete, there is a reduction of 15–20% of cement to attain the better strength and other properties of concrete. From the estimation done, it can be seen that the cost of concrete with 10% replacement of cement by Silpozz is reduced by 4.81%, and resulted in cost-efficient concrete. So it can be said that the silpozz which is obtained by major agricultural waste can be effectively used as a cementing material in form of ash.
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6 Future Scope The future scope of the present work includes: • The study of finding the possible ways to extend the application of such concrete in most of the semi-urban and rural construction works. • To study the possibilities of the application of such concrete in rigid pavement constructions, paver blocks, concrete gratings, and etc. • To study the use of Silpozz effectively for all the grades of concrete.
References 1. Rashid R, Kumar N (2016) Study on effect of silica fume on properties of M40 grade of concrete. Int J Eng Res Technol 5(05). https://doi.org/10.17577/IJERTV5IS050849 2. Selvapriya R (2019) Silica fume as partial replacement of cement in concrete. Int Res J Multidisciplinary Technovation 1(6). https://doi.org/10.34256/irjmtcon43 3. Kumar JDC, Abhilash GVS, Khan PK, Sai GM, Ram VT (2016) Experimental studies on glass fiber concrete. American J Eng Res 5(5):100–104. https://doi.org/10.14445/23488352/IJCEV3I7P126pdf 4. Bheel N, Awoyera P, Shar IA, Sohu S, Abbasi SA, Prakash AK (2021) Mechanical properties of concrete incorporating rice husk ash and wheat straw ash as ternary cementitious material. Hindawi Adv Civil Eng 1–13 5. Gupta AI, Wayal SA (2015) Use of rice husk ash in concrete: a review. J Mechan Civil Eng 12(4):29–31. https://doi.org/10.9790/1684-12412931 6. Amin M, Abdelsalam AB (2019) Efficiency of rice husk ash and fly ash as reactivity materials in sustainable concrete. Amin and Abdelsalam Sustain Environ Res 29(30). https://doi.org/10. 1186/s42834-019-0035-2 7. Azhagarsamy S, Jaiganesan K (2016) A study on strength properties of concrete with rice husk ash and silica fume with addition of glass fiber 8. Kumar PC, Rao PM (2010) Benefits of use of rice husk ash in concrete. Jr of Indus Pollution Control 26(2):239–241 9. Kashyap R, Chaudhary M, Sen A (2013) Effect of partial replacement of cement by rice husk ash in concrete. Int J Sci Res 4(5):1572–1574 10. Kulkarni MS, Mirgal PG, Bodhale PP, Tande SN (2014) Effect of rice husk ash on properties of concrete. J Civil Eng Environ Technol 2349–8404 Print ISSN 11. Krishna NK, Sandeep S, Mini KM (2016) Study on concrete with partial replacement of cement by rice husk ash. In: IOP conference series: materials science and engineering, vol 149(1). pp 012109 12. Mude VP, Bhalme SP, Kamdi MS (2013) Strength comparison of ordinary Portland cement and rice husk ash. Int J Eng Res Appl 3(4):283–284 13. Moulick KK (2015) Prospective use of rice husk ash to produce concrete in India. Int J Civil Environ Eng 9(3):324–332 14. Obilade IO (2014) Use of rice husk ash as partial replacement for cement in concrete. Int J Eng 5(04):8269 15. Pande AM, Makarande SG (2013) Effect of rice husk ash on concrete. Int J Eng Res Appl (IJERA) 2248–9622 ISSN 16. Rao PP, Kumar PA, Singh BB (2014) A study on use of rice husk ash in concrete. Int J Educ Appl Res 4(2):75–81
Influence of Concrete with Partial Replacement of Fine Aggregates with Crumb Rubber and Cement with Silica Fumes Gurwinder Singh and Aditya Kumar Tiwary
Abstract Concrete is the most widely used building material, and waste material replacement in concrete is becoming more popular as governments focus on waste management. Crumb rubber can be used to substitute fine aggregates; however, its mechanical qualities suffer as a result of its soft nature. Mineral additives such as silica fumes can be utilized to improvement in the behavior of crumb rubber concrete. Fine aggregates are substituted with 5%, 10% and 15% crumb rubber in this study, and the qualities of concrete are examined and compared with crumb rubber concrete with and without 10% silica fumes as cement substitution. The (SCR5) silica fumes increased the compressive and split tensile strength of concrete formed by 16 and 11% as compared to results from CR5. So, the use of silica fume along with crumb rubber (up to 5% only) is advised use for the replacement of fine aggregates as well as cement for better results. Keywords Rubberized concrete · Silica fumes · Waste utilization · Crumb rubber
1 Introduction The top most commonly used construction material is concrete, used for building structures. Concrete production utilizes a total of 12 billion tons of natural aggregates which are also limited [1]. Then eliminating or replacing the aggregates is the prime concern of researchers. On the other hand, increasing solid waste is also an issue for society [2, 3]. Waste tire rubber is solid waste among other waste causing serious issues in the environment. Around one billion waste tires complete their life span out of which 50% go to landfills untreated. This causes an environmental issue as well G. Singh (B) · A. K. Tiwary Chandigarh University, Mohali, India e-mail: [email protected] A. K. Tiwary e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_11
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as a potential risk of accidental fire, as rubber is a highly flammable material [3, 4]. This waste generation is expected to reach 4–5 billion by 2030. The utilization of waste tires as crumb rubber for aggregate replacement is a good option for resolving both issues [5, 6]. The biggest concern with using waste materials in concrete is the impact on the concrete’s workability. The workability of rubberized decreases due to particle size, and variation in the content of crumb rubber used [7]. A 50% reduction in workability was observed with a 10% substitutions of aggregates with crumb rubber. The reduction is due to shape, size, and entrapped air in rubber particles increasing the ability to absorb more water, hence water reduces concrete flow [8, 9]. Although there is a lot of interest in using waste tires to replace aggregates, largescale application of crumb rubber is behind, because of differences in mechanical qualities of rubberized concrete [10]. Ataria et al. [11] examined the effect of crumb rubber on concrete by replacing fine aggregates in the proportion of 5–20%, crumb rubber shown negative effect on strength of concrete. A loss of 21% in strength was observed with 5% crumb rubber used. This decline in strength is large if beyond 5% replacement takes place. Also supported by other studies [12, 13]. Shah et al. [14] used crumb rubber for fine aggregates and concluded that has 5% has less or no effect on the behavior of concrete but beyond 5% use of crumb rubber, strength and unit weight of rubberized concrete decrease dramatically, but thermal performance improved to be used in slab for energy-efficient building. Rubberized concrete with only crumb rubber as replacement reduces the properties of concrete. Many researchers studied the behavior of rubberized concrete by introducing strength-increasing agents. In a study crumb rubber as a fine aggregated replacement along with 1% steel fiber was discussed by Eisa [4]. The author observed a 10% improvement in the toughness and performance of concrete. The introduction of steel fibers decreased workability but the improved unit weight of concrete. Crumb rubber enhances the ductility of concrete, although the detrimental influence of rubber on the mechanical characteristics of concrete can be minimized by adding steel fibers. As above discussed, substituting the fine aggregates with crumb rubber harms the mechanical properties of concrete, but also improved ductility. Several research has been conducted employing silica fume as a cement substitute to improve the quality of rubberized concrete. Fakhri et al. [15] substituted natural fine aggregates 5–25% crumb rubber with 0–20% silica fume replacement with cement. Concrete’s flexural strength was shown to rise by 24% when it had 5% crumb rubber; however, when it contained crumb rubber more than 5%, the strength of the concrete decreased. In another trial, fine aggregates and cement were replaced with pre-coated rubber particles and 15% silica fumes. It was observed, that silica fume has a great influence on rubberized concrete as it helps in improving strength by enhancing pozzolanic activity and fine particle filling voids [16]. The effects of replacing 5, 10 and 15% fine particles with crumb rubber on the fresh and hardened properties of concrete are explored in this study. Because the soft nature of rubber causes a deterioration in concrete qualities, a 10% replacement of silica fume as cement is employed to recover the properties of concrete. The concrete is compared to control concrete and crumb rubber concrete with silica fumes.
Influence of Concrete with Partial Replacement of Fine Aggregates …
(a) Crumb rubber
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(b) Silica fumes
Fig. 1 The image of crumb rubber and silica fumes
2 Materials For this study, the cement used was 43grade OPC cement with 46 MPa compressive strength, 3.15 specific gravity, and 32 consistency confirming IS 8113: 2013 [17]. Locally available crushed angular coarse aggregate and river fine aggregates from zone III were used as aggregates as per IS 383: 2016 [18]. The specific gravities of aggregates were 2.74 and 2.68, respectively and the fineness modulus of aggregates used was 7.95 and 3.48, respectively. 1mm to 2mm particle size of crumb rubber is used to substitute fine aggregates in proportions of 5, 10 and 15% by weight. Crumb rubber has a specific gravity of 1.15. Figure 1a displays the image of the crumb rubber used. For enhancement of pozzolanic activity in concrete, silica fume (shown in Fig. 1b) with a specific gravity of 2.57 for 10% of the cement was used for cement replacement. The particle size distribution of all materials is given in Fig. 2. Figure 3 displays the scanning electron microscope image of crumb rubber and silica fumes; the rough particle shape of the rubber particle can be seen in the figure. The elemental properties of crumb rubber and silica fumes are given in Table 1.
3 Experimental Program 3.1 Methodology The concrete mix grade employed in this study was M30 concrete. Conventional concrete (CC) without any replacement was prepared for the comparison. Crumb rubber was used to substitute for 5, 10 and 15% of fine aggregates in concrete. After preparing the sample with crumb rubber (CR5, CR10, and CR15), 3 more mixes (SCR5, SCR10, and SCR15), with the constant 10% substitution of cement with silica fumes. The letter CR in name of mixes is for crumb rubber with 5, 10, and 15
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Fig. 2 Particle size distribution curve
(a) Crumb rubber
(b) Silica fumes
Fig. 3 SEM image of particle of a crumb rubber and b silica fumes
representing the percentage use of CR, where S is used in mix with 10% replacement of cement along with CR as fine aggregate replacement. A total of 72 samples of the cube (150 × 150 × 150 mm) and cylinder (150mm dia. and 300mm height) were prepared for the testing of compressive and tensile strength of concrete on the 7th day and 28th days.
Influence of Concrete with Partial Replacement of Fine Aggregates … Table 1 % mass elements of crumb rubber and silica fumes
135
Elements
Crumb rubber
Silica fumes
C
69.70
–
O
22.60
48.14
Na
3.79
0.70
Mg
–
2.35
Al
–
0.97
Si
–
39.36
S
3.91
1.53
K
–
3.65
Ca
–
2.2
Fe
–
1.10
4 Mix Design and Specimen Preparation For the mix design of conventional concrete, a design mix of grade M30 concrete and designed as per IS 10262: 2019 [19] with a water-binder ratio of 0.5. The proportions of materials used are shown in Table 2 for the preparation of 7 different mixes of rubberized concrete with and without silica fumes. Following the mix design for conventional concrete, the other 6 mixes were created by substituting fine particles with crumb rubber and cement with silica in the proportions shown in Table 3. In Table 2, CC is conventional concrete without any replacement of materials. The concrete containing just crumb rubber as a substitute is labeled CR5, CR10, and CR15, where 5, 10 and 15 represent the percentage aggregates changed by crumb rubber. Similarly, SCR5, SCR10, and SCR15 refer to rubberized concrete with silica fumes as a cement substitute, where 5, 10, and 15 indicate the percent substitution of crumb rubber for fine aggregates, respectively, while silica fumes were kept constant at 10% replacement for cement. Table 3 shows the mixed proportion of materials. Concrete mixes were prepared to mix materials after weighing the weight of materials used for the mix. Hand mixing was used to make the concrete. First, a consistent dry mix was created, and then water Table 2 Percentage proportion of materials Mix
Cement
CC
100
0
CR5
100
CR10
100
CR15 SCR5
Silica fumes
Crumb rubber
Fine aggregates
Coarse aggregates
0
100
100
0
5
95
100
0
10
90
100
100
0
15
85
100
90
10
5
95
100
SCR10
90
10
10
90
100
SCR15
90
10
15
85
100
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Table 3 Mix design proportion of mixes Mix
Cement (kg/m3 )
Silica fumes (kg/m3 )
Crumb rubber (kg/m3 )
Fine aggregates (kg/m3 )
Coarse aggregates (kg/m3 )
CC
394
0
0
680
1134
CR5
394
0
34
646
1134
CR10
394
0
68
612
1134
CR15
394
0
102
578
1134
SCR5
354.6
39.4
34
646
1134
SCR10
354.6
39.4
68
612
1134
SCR15
354.6
39.4
102
578
1134
was introduced to the dry mix, to prepare concrete. Before pouring concrete into the samples, the workability of concrete was tested with a slump cone. After testing fresh properties, the concrete was poured into cube and cylinder molds. A 6 number of the cube and 6 number of the cylinder were cast for each design mix for testing age of 7th and 28th-day test. After 24±1h, concrete specimens were demolded and placed for curing in water till testing age was achieved.
5 Experimental Results and Discussions 5.1 Workability When concrete is prepared, for the fresh property, the slump value of concrete is measured for the workability of concrete as per IS 1159:1959 [20]. Concrete is poured in a slump cone mold of 200mm diameter 300mm height in three-layer and tamping each layer by rod 25 times. After lifting the cone, concrete is allowed to fall, and the change in height of concrete is measured for slump value. The variation in the slump value of concrete is shown in Fig. 4. With the substitutions of crumb rubber to concrete as 5, 10 and 15% of fine aggregate, the slump value decreased by 38–61%. The decrease in slump value may be due to crumb rubber only, the shape of rubber particles is irregular and can entrap air and water on the surface of particles [21]. The water used in concrete, when entrapped by rubber particles, results in a decline in slump value as not enough water is available for the flow of concrete. Similar results were observed in silica fumes and crumb rubber mix also. The slump value of rubberized show no change after the substitution of silica fume in cement. Whereas SF also needs more water as surface area increases for reaction, decreasing the workability of concrete [22]. But incorporating SF up to 10% of cement by weight has no or very little effect on the concrete’s workability as supported by Rao [23].
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Fig. 4 Variation in a slump value of concrete
5.2 Compressive Strength A cube sample size 150 × 150 × 150 mm was constructed for the test of compressive strength. For each testing age of 7 and 28 days, three samples were examined. Samples were taken out of the water tank before testing and waited for surface drying, then tested under a compression testing machine at a loading rate of 13.7 N/mm2 . The whole procedure was done as per IS 516:1999 [24]. Observed results as shown in Fig. 5, Figure shows a decrease in strength with the quantity of rubber particles surges. When 5, 10 and 15% crumb rubber by weight of fine aggregates were replaced. The 28th-day strength is reduced by 11.25, 21.8 and 34%, respectively, compared to ordinary concrete. The strength decreased may be due to the softness of rubber, rubber acts as a void in concrete hence decreasing strength [9]. The concrete prepared with silica fume and rubber shows some positive
Fig. 5 Variation in compressive strength
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results, as it can be seen from Fig. 5 that SCR5 showed improvement in concrete by increasing compressive strength by 3.5% as compared to CC and 16% as compared to CR5. The increase in strength is may be due to the pozzolanic reactivity of silica fume. But trend beyond 5% crumb rubber with silica fume in concrete is not maintained and follows fall as in the case of crumb rubber without silica fumes. It is also observed, that the strength of all mixes with silica fume was higher than samples without silica fumes.
5.3 Split Tensile Strength Cylindrical samples of 150 mm diameter and 300 mm height were used for the determination of split tensile strength as per IS 516:1999 [24] under a compression testing machine. Figure 6 depicts the concrete test results for split tensile strength. Figure 6 shows that the findings follow a similar trend as that of compressive strength results. Concrete with only crumb rubber shows a reduction, whereas concrete with crumb rubber and silica fumes shows a modest rise. In comparison to CC, the 5% substitution of fine aggregates with crumb rubber results in the lowest reduction of 8% in CR5 and the maximum decline of 28% in CR15. In contrast, SCR5 exhibits a 2.35% improvement in tensile strength compared to CC and an 11% increase in strength compared to CR5. The decline in strength is due to crumb rubber and the increase observed is due to silica fume’s fine particles filling small pores in concrete helps reduce the void ratio and increased tensile strength [9].
Fig. 6 Split tensile strength’s variation
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Fig. 7 Ultrasonic pulse velocity of concrete on 28th day
5.4 Ultrasonic Pulse Velocity The ultrasonic pulse velocity (USPV) test is a non-destructive method performed for the quality of concrete. USPV was done on a cube sample size of 150 × 150 × 150 mm in accordance with IS 13311 (part 1): 1992 [25] before the compressive strength test. Figure 7 depicts the variation in pulse velocity on the 28th day in a varied concrete mix. The presence of soft rubber and entrapped air owing to rubber leaving voids results in a drop in velocity, but the quality of concrete is still good according to IS 13311 (part 1): 1992. It can be observed that USPV decreased in the case of CR mixes as well as in SCR mixes as compared to CC. But the USPV in the case of SCR was slightly higher than CR mixes. The USPV of SCR5 was 7% lower than the USPV of CC but was 5% higher than the CR5 [11, 26].
5.5 Rebound Hammer Test The compressive strength testing with a rebound hammer on the 28th day and comparison with the normal concrete mix are shown in Fig. 8. The outline of the results is similar to the compressive strength. However, the value provided by the rebound hammer test was somewhat greater than the results of the compression testing equipment. When comparing the strength of crumb rubber to conventional concrete, the strength rose for 5% crumb rubber and 10% silica fume replacement as cement as compared to CC, but subsequently declined after the crumb rubber concentration was raised above 5%. Figure 9 depicts a comparison of compressive strength values obtained using a compression testing machine and a rebound hammer. Figure 10 represents the correlation between pulse velocity and compressive strength tested by rebound hammer. The figure shows a comparison of the relation of
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Fig. 8 Rebound hammer test of concrete
Fig. 9 Comparison of compressive strength from rebound hammer test (RH) and compression test machine (CTM)
crumb rubber concrete with and without silica fumes. The line shows decreasing trend due to reduction in compressive strength and pulse velocity of rubberized concrete due to varying content of crumb rubber.
6 Conclusions The properties of rubberized concrete prepared with crumb rubber for the substitution of fine aggregates with and without silica fumes as a cement substitute were investigated and compared to conventional concrete. Because crumb rubber reduces
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Fig. 10 Correlation of UPV and rebound hammer test results
the strength properties of concrete, silica fumes were substituted for 10% of the cement to increase the pozzolanic activity in concrete. The produced concrete is compared to conventional concrete and rubberized concrete in terms of workability, compressive strength, split tensile strength, and pulse velocity. 5, 10 and 15% fine aggregates by weight were partially substituted with crumb rubber with and without 10% silica fumes substituted for cement. The workability of rubberized concrete tends to decline with the increased content of crumb rubber. The 10% silica fume show very less effect on rubberized concrete in terms of workability: 1. The compressive strength was found to be reduced by 11.25, 21.8, 34% for 5, 10 and 15% of fine aggregates replaced with crumb rubber. Whereas in the case of rubberized concrete with silica fumes, strength increased by 16% for a 5% crumb rubber mix as compared to rubberized concrete and a 3.5% increase compared to CC. 2. The split tensile strength of rubberized concrete was decreased by 8, 16 and 28%, depending on the proportion of crumb rubber used. Moreover, in the case of rubberized concrete with silica fumes, strength increased by 11% for a 5% crumb rubber mix as compared to rubberized concrete and a 2.35% increase compared to CC. 3. In both rubberized concrete with and without silica fumes, the ultrasonic pulse velocity was reduced, but in concrete with silica fumes, it was greater than in concrete without silica fumes. 4. As a consequence of the foregoing findings, it can be inferred that replacing aggregates with crumb rubber reduces the characteristics of concrete; nevertheless, replacing silica fumes in cement and replacing up to 5% of fine aggregates with crumb rubber can improve the properties of concrete. Crumbs should not advise being used in amounts of more than 5%.
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References 1. Gorde PJ, Naktode PL (2022) Chemically treated tyre rubber concrete review. Mater Today: Proc 60(Part 1):508–512. ISSN 2214-7853. https://doi.org/10.1016/j.matpr.2022.01.421 2. Nur OF, Albarqi K, Melinda AP, Al Jauhari Z (2021) The effect of waste tyre rubber on mechanical properties of normal concrete and fly ash concrete. Geomate J 20(77):55–61 3. Awan HH, Javed MF, Yousaf A, Aslam F, Alabduljabbar H, Mosavi A (2021) Experimental evaluation of untreated and pretreated crumb rubber used in concrete. Crystals 11(5):558 4. Eisa AS, Elshazli MT, Nawar MT (2020) Experimental investigation on the effect of using crumb rubber and steel fibers on the structural behavior of reinforced concrete beams. Constr Build Mater 252:119078 5. Hasani H, Mojtaba S, Nezhad M, Soleymani A, Aval FS (2022) The influence of treated and untreated crumb rubber on concrete mechanical properties: a review. no. May, 0–9 6. Gupta T, Chaudhary S, Sharma RK (2015) Mechanical and durability properties of waste rubber fiber concrete with and without silica fume. J Clean Prod. https://doi.org/10.1016/j.jcl epro.2015.07.081 7. Karunarathna S, Linforth S, Kashani A, Liu X, Ngo T (2021) Effect of recycled rubber aggregate size on fracture and other mechanical properties of structural concrete. J Clean Prod 314:128230 8. Najim KB, Hall MR (2013) Workability and mechanical properties of crumb rubber concrete. Proc Instit Civil Eng-Construct Mater 166(1):7–17 9. Onuaguluchi O, Panesar DK (2014) Hardened properties of concrete mixtures containing precoated crumb rubber and silica fume. J Clean Prod 82:125–131 10. Ataria RB, Wang YC (2022) Mechanical properties and durability performance of recycled aggregate concrete containing crumb rubber. Materials 15(5):1776 11. Emiroglu M, Kelestemur MH, Yildiz S (2007) An investigation on ITZ microstructure of the concrete containing waste vehicles tire. In: Proceedings of the 8th international fracture conference, Istanbul, Turkey, 8 November 2007 12. Moustafa A, ElGawady MA (2015) Mechanical properties of high-strength concrete with scrap tire rubber. Constr Build Mater 93:249–256. https://doi.org/10.1016/j.conbuildmat.2015. 05.115 13. Shah SFA, Naseer A, Shah AA, Ashraf M (2014) Evaluation of thermal and structural behaviour of concrete containing rubber aggregate. Arab J Sci Eng 39(10):6919–6926 14. Eisa AS, Elshazli MT, Nawar MT (2020) Experimental investigation on the effect of using crumb rubber and steel fibers on the structural behaviour of reinforced concrete beams. Construct Build Mater 252:119078 15. Fakhri M, Yousefian F, Amoosoltani E, Aliha MRM, Berto F (2021) Combined effects of recycled crumb rubber and silica fume on mechanical properties and mode I fracture toughness of self-compacting concrete. Fatigue Fract Eng Mater Struct 44(10):2659–2673 16. Khalid FS, Saaidin SH, Shahidan S, Othman NH, Irwan JM, Guntor NAA (2020) Performance of concrete containing fine recycled concrete aggregate (FRCA) and fine crumb rubber (FCR) as partial sand replacement. In: IOP conference series: materials science and engineering, September, vol 917(1). IOP Publishing, pp 012017 17. IS 8112:2013 (2013) Ordinary Portland cement, 43 grade specification. Indian Standard: New Delhi, India 18. IS:383–2016 (2016) Coarse and fine aggregate for concrete—specification. Indian Standard: New Delhi, India 19. IS 10262:2019 (2019) Concrete mix proportioning guidelines. Indian Standard, New Delhi, India 20. IS 1199:1959 (1959) Methods of sampling and analysis of concrete. Indian Standard: New Delhi, India 21. Najim KB, Hall MR (2013) Workability and mechanical properties of crumb-rubber concrete. Proc Instit Civil Eng-Construct Mater 166(1):7–17
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22. Ali K, Qureshi MI, Saleem S, Khan SU (2021) Effect of waste electronic plastic and silica fume on mechanical properties and thermal performance of concrete. Construct Build Mater 285:122952 23. Rao GA (2003) Investigations on the performance of silica fume-incorporated cement pastes and mortars. Cem Concr Res 33(11):1765–1770 24. BIS:516–1999 (2002) Specification for methods of tests for strength of concrete. Bureau of Indian Standards (BIS): Old Delhi, India 25. BIS 13311 (Part 2) (1996) Non-destructive testing of concrete-methods of test. Bureau of Indian Standards, New Delhi, India 26. Gesoglu M, Guneyisi E (2007) Strength development and chloride penetration in rubberized concrete with and without rubberized silica fume. Mater Struct 40(9):953–964
Partially Replacing Cement with Ground Granulated Blast-Furnace Slag (GGBS) and Fly Ash Changes the Mechanical Properties of Concrete Hemant Kumar and Vikram Singh
Abstract Concrete cement is the widely frequently used building substance on earth. It works as a binder material. It sets and becomes adhesive due to hydration. Ordinary cement concrete has a very weak limited ductility, tensile, strength, and little resistance to cracking. When compared to standard Portland concrete, When GGBS is partially replaced with cement, the heat of hydration is lower, the resistance to the (cl) chloride and (SO4 ) sulfate attack is higher, and ductility is limited. On the other hand, it helps protect the environment by reducing the amount of cement used to make concrete. “Fly-ash”, on the other hand, is waste from a thermal power plant that is used to save money on concrete. Fly ash improves the workability of concrete while lowering its permeability. Concrete containing the fly ash also generates low heat of hydration due to which thermal cracking is avoided. Keywords GGBS · Fly ash
1 Introduction Concrete is the building element that is made of cement, coarse and fine aggregates, and water, and it’s widely used in construction. The iron and steel industries produce slag as a byproduct of blast furnaces. The furnace is filled with limestone, “iron ore”, and “coke”, and the molten form of the slags floats on top of the “molten iron” at temperatures between 1500 and 1600 °C. Between 30 and 40% (SiO2 ) silicon dioxide and approximately 40% (CaO) calcium oxide are found in the molten slag, which is similar to Portland cement (CaO). As remaining melted slags are rapidly quenched with water during the tap-off of molten iron, siliceous and aluminous byproducts are H. Kumar (B) · V. Singh Department of Civil Engineering, Chandigarh University, Mohali, Punjab, India e-mail: [email protected] V. Singh e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_12
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formed. Crushed granulated blast furnace slag is made by drying and crushing this glassy granulate to the desired particle size. Thermal power plants that use coal as fuel produce fly ash as a byproduct. Fly ash can harm agricultural land, pollute surface and groundwater, soil, and the air, and cause other diseases if it is not properly disposed of or released into the environment. Fly ash has been used as a partial replacement for cement, and it has become a major issue in the construction industry. It has benefited the economy, the environment, and technology. By incorporating fly ash into cement concrete, it is feasible to bring the total amount of heat that is produced during the process of mass concreting down to a more manageable level.
2 Chemical Properties of GGBS and Fly Ash 2.1 Chemical Properties Ca–O, Si–O2 , Al2 –O3 , and Mg–O are the main constituents of GGBS. It has a crystalline silica content of less than one percent and a chromium content of fewer than one part per million that is water-soluble. The primary chemical components of GGBS and ordinary Portland cement (OPC) are identical, but their proportions vary. “Fly ash” is often composed of the oxides of silicon, aluminum, iron, and calcium. Other elements may also be present. There are also minute quantities of the elements magnesium (mg), potassium (K), sodium (Na), titanium (Ti), and sulfur present. Depending on the chemical composition, fly ash added to the concrete as a mineral additive is described as either “Class C” or “Class F” ash (Table 1).
2.2 Physical Properties When water and GGBS are combined, the results are very similar to what happens when Portland cement and water are combined. When GGBS is mixed with water, an activator is used to speed up the reaction. Because CaOH2 is released when Portland cement and water are mixed, the Portland cement and GGBS are combined. Table 1 Composition of OPC, GGBS and fly ash
Chemical constituent Portland (%) GGBS (%) Fly ash (%) CaO
66
41
9
SiO2
21
36
55
AI2 O3
6
10
26
MgO
3
9
2
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Fig. 1 Concrete mix containing GGBS cement
While Portland cement concrete has more large capillary pores, when GGBS is added to the mix, the hard form of cement paste had a large number of small gel voids. Because of the finer pores structure in concrete created by the addition of GGBS, the concrete has lower permeability and is more durable (Fig. 1). In mass concreting, dams, roller compacted concrete pavements, and parking lots may contain up to 60% fly ash as compared to the total amount of the cement in structure member of the concrete. When employing fly ash to enhance the characteristics of concrete, particular measures must be taken. Both “F” and “C” fly ash are formed by burning bituminous coal and/or anthracite, whereas “F” fly ash is made when these kinds of coal are burnt.
3 Methodology Adopted for Mixed Design The design mix for M 40 should be produced with the compressive strength of concrete in mind, along with a suitable amount of workability, to ensure that new concrete can be mixed, put, and compacted correctly. The criteria for the water were taken from the document IS 10262–2009, and they were included in the calculations for the mix’s proportions. The proportioning of concrete mixes must be done in the following three steps in the correct order. (i) Choosing appropriate components, such as cement, supplementary cementing materials, aggregates, water, and chemical admixtures (if required). (ii) Determining the relative quantities of the components needed to produce concrete that is both cost-effective and possesses the rheological properties (such as strength and durability) that are desired. (iii) Meticulous quality control over each stage of the process of producing concrete. In the current research, Mix Design of M40 (Design value at the age of 28 days) grade concrete is done according to BIS: 10,262–2009.
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Table 2 Design mix properties Design mix Degree of quality control maintained on site
= Good
Size of aggregate use
= 20 mm
(i) Water/cement
= 0.45
Table 3 Mix proportion for 1 m3 Unit of batch Cement (kg)
Fine aggregates (kg)
Coarse aggregates (kg) 10 mm
20 mm
Cubic meter content
437
649.09
552.5
552.5
Ratio of ingredients
1
1.49
1.26
1.26
Plasticizer
Water (liters)
650 ml (Fosroc)
196.65
0.0014
0.45
The proportioning is carried out to accomplish defined characteristic compressive strength at a specified age, workability of new concrete, and durability criteria (Tables 2 and 3).
4 Testing of Specimens Following the casting step, specimens were evaluated 7 and 28 days following the curing process. To determine the different characteristics of concrete, such as its compressive strength, splitting tensile strength, and flexural strength, the technique that must be followed while conducting tests on specimens is outlined in this section of the article.
4.1 Mechanical Properties Compressive Strength:—Specimens After a casting period of twenty-four hours, specimens were opened. After that, they were dumped into the curing tank and left there for the allotted amount of time. When the specimens reached the appropriate age for testing, they were removed from the tank and surface dried for ten to fifteen minutes. Following the requirements of IS: 516–1959, specimens were subjected to compression testing using a machine known as a CTM. CTM is capable of bearing a force of 5000 kN. After that, an analysis of the failure load was carried out (Fig. 2).
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Fig. 2 Compression testing machine (CTM)
Split Tensile Strength:—steps for measuring of Tensile properties of Concrete: 1. The specimens will be taken out of the water and wiped dry after a predetermined amount of curing time. The specimen’s dimensions will be recorded to the closest 0.2 m. The compression testing device’s bearing surfaces will be thoroughly cleaned. Additionally, the surfaces of the specimens that will come into touch with the rollers will be cleaned of any loose sand or other debris. 2. For each specimen, two bearing strips made of nominally (1/8 inch, or 175 mm) thick plywood that are free of flaws and are 25 mm wide and somewhat longer than the specimen should be given. The specimen is positioned between these two bearing strips (plywood strips) and the top and lower bearing blocks of the strength testing apparatus. They may also be positioned in between the specimen and the additional bars or plates. 3. Now, using a tool that will ensure that they are in the same axial plane, draw diametric lines at either end of the specimen. The middle of the bottom bearing block will be lined with one of the bearing strips (plywood strips). Carefully aligning the specimen on the bearing strip (a plywood strip) will ensure that the lines marked on its ends are vertical and cantered over the plywood strip. The second plywood strip, known as the bearing strip, will be attached to the cylinder longitudinally and cantered along the lines shown on its ends. 4. Up until the specimen fails, the load will be delivered continuously, without shock, and at a steady rate between 689 and 1380 kPalmin splitting tensile stress (Fig. 3).
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Fig. 3 Universal testing machine (UTM)
5 Split-Tensile and Compressive Strength The compressive and tensile strength of cement concrete are affected by the addition of GGBS and fly ash as replacements for cement, according to the findings of the current study. The concrete mixture made with GGBS and fly ash replaces “0%”, “10%”, “20%”, “30%”, “40%”, and “50%” of cement by weight. The following are the conclusions regarding the origin of the results of the current experimental campaign. Twenty-four cubes sized 150 × 150 × 150 mm and 24 cylinders of 300 × 150 mm were cast to be tested on the 7th and 28th day of water curing by adding “ground granulated blast furnace slag (GGBS)” and “fly ash” with M40 aspect ratios with proportions by weight of cement. After the testing of each cube and cylinder, we got the values of compressive and split tensile strength for different batches (Fig. 4).
5.1 Case Study on Cement Replacement with GGBS An addition of GGBS to cement concrete was discovered to rises the compressive and tensile strength in the mix. Compressive strength increases by 0.45 MPa for a fixed 0.45 water cement ratio. 1.24 MPa in 7 days of curing on the replacement of 10% GGBS. On the other side, the value of compressive strength 28 days of curing is increased by 1.3 MPa. With the addition of 20% GGBS, the value of the compressive strength of cement concrete increases by 3.36 MPa after the 7th day of curing and the compression Strength after the 28th day of water curing also increases by 5.1 MPa further it started decreasing by 2.59 MPa for the 30% replacement of GGBS for 7 days as well as for 28 days of curing it decrease by 2.1 MPa. With the addition of 40% of GGBS, the value of compressive strength of concrete decrease by 0.66 MPa after the 7th day of water curing, and the compression Strength after the 28th day of curing also decrease by 6.5 MPa and last on the addition of 50% of GGBS the
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Fig. 4 Casting of cubes and cylinders and cubes and cylinders placed in water
compressive strength decrease by 2.37Mpa for 7 days and 28 days is decreased by 5.5 MPa. (Table 4). For a 0.45 water cement ratio, the value of tensile strength increases by 0.84 MPa in 7 days of curing on the replacement of 10% GGBS. On the other hand, the value of split-tensile strength 28 days after curing is increased by 0.3 MPa. In addition, at 20% of GGBS the value of tensile strength of concrete increases by 0.11 MPa after the 7th day of the water curing, and the tensile strength after the 28th day of curing also increases by 0.2 MPa. Further, it started decreasing by 0.15 MPa for the 30% replacement of GGBS for 7 days as well as for 28 days of curing, it decreases by 0.3 MPa. With the addition of 40% of GGBS, the value of tensile strength of concrete decrease by 0.16 MPa after the 7th day of curing, and Table 4 Compressive and tensile strength tested at 7 days and 28 days for GGBS Mix
Compressive strength (MPa) for GGBS
Split tensile strength (MPa) for GGBS
7 days
28 days
7 days
28 days
Control mix (CM)
28.50
46
2.4
4.1
G10
29.34
47.3
2.48
4.4
G20
31.36
52.4
2.51
4.6
G30
28.77
50.3
2.36
3.1
G40
28.11
43.8
2.20
2.8
G50
25.74
38.3
1.95
2.3
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Fig. 5 Compressive strength of GGBS concrete
Fig. 6 Split-tensile strength of GGBS concrete
the tensile strength after 28th day of curing also decrease by 0.3 MPa and last on the addition of 50% of GGBS, the tensile strength decrease by 0.25 MPa for 7 days and 28 days is decreased by 0.50 MPa (Figs. 5 and 6).
5.2 Case Study on Cement Replacement with the “Fly Ash” An addition of ‘fly ash’ to cement-concrete was discovered to fall the compressive and tensile strength in the mix. Compressive strength decreases by 0.40 for a fixed 0.45 water cement ratio. 0.4 MPa in 28 days of curing on the replacement of 10% ‘fly ash’. On the other side, the value of compressive strength 28 days of curing is decreased by 1.6 MPa. With the addition of 20% of ‘fly ash,’ the value of compressive strength of cement concrete decreases by 0.76 MPa after the 7th day of curing, and the compression strength after the 28th day of water curing is also decreased by
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Table 5 Compressive and tensile strength tested at 7 days and 28 days for fly ash Mix
Compressive strength (MPa) for fly ash
Tensile strength (MPa) for fly ash
7 days
7 days
28 days
28 days
Control mix
28.50
46
2.4
4.1
F10
28.10
44.4
2.1
3.8
F20
27.34
41.5
1.9
3.5
F30
26.21
38.6
1.7
3.1
F40
23.57
34.6
1.4
2.2
F50
21.24
27.5
1.3
1.5
2.9 MPa further, it started decreasing by 1.13 MPa for the 30% replacement of ‘fly ash’ for 7 days as well as for 28 days of curing, it decrease by 2.9 MPa. With the addition of 40% of ‘fly ash,’ the value of compressive strength of concrete decreases by 2.64 MPa after the 7th day of water curing, and the compression strength after the 28th day of curing is also decreased by 4 MPa, and last on the addition of 50% of ‘fly ash’ the compressive strength decrease by 2.23 Mpa for 7 days and 28 days is decreased by 7.1 MPa (Table 5). For a 0.45 water cement ratio, the value of tensile strength decreases by 0.3 MPa in 7 days of curing on the replacement of 10% ‘fly ash’. On the other hand, the value of split-tensile strength 28 days after curing decreases by 0.3 MPa. In addition, in 20% of ‘fly ash,’ the value of tensile strength of concrete decreases by 0.3 MPa after the 7th day of the water curing, and the tensile strength after the 28th day of curing also decreases by 0.3 MPa. Further, it started decreasing by 0.2 MPa for the 30% replacement of ‘fly ash’ for 7 days as well as for 28 days of curing it decreases by 0.4 MPa. With the addition of 40% of ‘fly ash,’ the value of tensile strength of concrete decreases by 0.3 MPa after the 7th day of curing, and the tensile strength after 28th day of curing also decrease by 0.9 MPa, and last on the addition of 50% of ‘fly ash’ the tensile strength decrease by 0.1 MPa for 7 days and 28 days is decreases by 0.7 MPa (Figs. 7 and 8).
5.3 Case Study on Cement Replacement with the “GGBS” and “Fly Ash” An addition of 10% GGBS and 40% fly ash in cement concrete were found to decrease the compressive value of concrete mixes. For 0.45 water-cement ratio, the value of compressive strength was reduced by 0.1 MPa in 7 days of curing on the replacement of 10% GGBS and fly ash. On the other side, the value of compressive strength 28 days of curing is decreased by 7.9. With the addition of 20% of GGBS and 30% of the “fly ash” the amount of the compressive strength of concrete increases by 1.94 MPa on the 7th day of curing, and the compression Strength after the 28th day
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Fig. 7 Compressive strength of fly ash concrete
Fig. 8 Split-tensile strength of fly ash concrete
of curing also increases by 3.2 MPa And further, it started decreasing by 3.98 MPa for the 30% replacement of GGBS and 20% fly ash for 7 days as well as for 28 days of curing it decrease by 1.9 MPa. With the addition of 40% of GGBS and 10% of fly ash, the value of compressive strength of concrete decreases by 0.59 MPa after the 7th day of curing, and the compression strength after the 28th day of curing also decreases by 3.26 MPa (Table 6).
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Table 6 Compressive strength tested at 7th and 28th days of GGBS and fly ash mix Mix
Compressive strength (MPa) for GGBS
Tensile strength (MPa) for GGBS
7 days
7 days
28 days
28 days
Control mix(CM)
28.50
46
2.4
4.1
G 10 + FA 40
26.40
38.1
1.2
2.8
G 20 + FA 30
28.34
41.3
1.6
3.1
G 30 + FA 20
24.36
39.4
1.4
2.6
G 40 + FA 10
23.77
36.1
1.1
2.3
Fig. 9 Compressive strength for GGBS and fly ash concrete
For a 0.45 water cement ratio, the value of tensile strength decreases by 1.2 MPa in 7 days of curing on the replacement of 10% GGBS and 40% of fly ash. On the other hand, the value of tensile strength 28 days of curing decreases by 1.3 MPa. With the addition of 20% of GGBS and 30% “fly ash” the value of tensile strength of concrete increases by 0.4 MPa on the 7th day of curing, and the tensile strength after the 28th day of curing also increases by 0.3 MPa And further, it started decreasing by 0.2 MPa for the 30% replacement of GGBS and 20% of fly ash for 7 days as well as for 28 days of curing it decreases by 0.5 MPa. With the addition of 40% of GGBS and fly ash value the tensile strength of concrete decreased by 0.3 MPa on the 7th day of curing, and the tensile strength on the 28th day of curing also decreased by 0.3 (Figs. 9 and 10).
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Fig. 10 Split tensile strength for GGBS and fly ash concrete
6 Conclusion 1. The addition of 20% of GGBS in “cement-concrete” is found to rise the compressive property of “cement-concrete” by 3.36 MPa on checking at 7 days of curing. The compressive property at 28 days also increases by 5.1 MPa. Similarly, on adding of 20% of GGBS, the value of tensile strength of concrete increases by 0.11 MPa which is very less on the 7th day of curing, and the tensile strength after the 28th day of the water curing also increases by 0.2 MPa the both 7 and 28th-day tensile strength value are very insignificant, and as the tensile strength of concrete without reinforcement is very low, So, we use steel reinforcement to increase the tensile strength of concrete. 2. With the varying percentage replacement of GGBS at 10, 20, 30, 40 and 50%, the compressive value increased up to 20% with the rate of by 3.36 MPa, and then it started decreasing as the percentage value of GGBS rises. This is because cementitious content decreases, due to which rate of reaction also decreases. 3. On adding the fly ash to the cement concrete, it is found that both compressive strength and the split tensile strength decrease and further as the amount of fly-ash increase in cement concrete both compressive strength values and split tensile strength values decreases. 4. When both fly ash and GGBS are used for the replacement of cement up to 50% we get varying results. As we increase the percentage of GBBS, we have to reduce the percentage value of fly ash to make cement content up to at least 50%. When GGBS is 20% and fly ash is 30% then we get the maximum strength up to 28.34 MPa for 7 days and 43.1 MPa for 28 days. Similarly, we get the highest value of split tensile strength of 1.6 MPa for 7 days and 3.1 MPa for 28 days at 20% of GGBS and 30% of fly ash replacement with cement.
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References 1. Mullauer W et al (2015) Leaching behavior of major and trace elements from concrete: effect of fly ash and GGBS. Cement Concr Compos 58:129–139 2. Awasare et al. (2014) Analysis of strength characteristics of GGBS concrete. Int J Adv Eng Technol. E-ISSN 0976–3945 3. Ling T-C, Poon C-S (2014) Feasible use of large volume of GGBS in 100% recycled glass architectural mortar. Cement and Concrete Compos 53:350–356 4. Mathew BJ et al. (2013) Strength, economic and sustainability characteristics of coal ash– GGBS based geopolymer concrete. Int J Comput Eng Res (ijceronline.com) 3(1) 5. O’Connell M et al (2012) Performance of concrete incorporating GGBS in aggressive wastewater environments. Constr Build Mater 27:368–374 6. McNally C, Sheils E (2012) Probability-based assessment of the durability characteristics of concretes manufactured using CEM II and GGBS binders. Constr Build Mater 30:22–29 7. Siddique R et al (2012) Use of iron and steel industry by-product (GGBS) in cement paste and mortar. Resour Conserv Recycl 69:29–34 8. Al-Otaibi S et al (2008) Durability of concrete incorporating GGBS activated by water- glass. Constr Build Mater 22:2059–2067 9. Cheng A et al (2005) Influence of GGBS on durability and corrosion behavior of reinforced concrete. Mater Chem Phys 93:404–411 10. Ramezanianpour AA et al. (2013) Durability of concretes containing ground granulated blast furnace GGBS against sulfate attack 11. Khan KM (2004) Effect of blending of portland cement with ground granulated blast furnace slag on the properties of concrete. In: 29th conference on our world in concrete and structures: 25–26 August 2004, Singapore Article Online Id: 100029040 12. Higgins DD et al (2003) Increased sulfate resistance of GGBS concrete in the presence of carbonate. Cement Concr Compos 25:913–919 13. Luo R et al. (2003) Study of chloride binding and diffusion in GGBS concrete. Cement and Concrete Res 33:1–7 14. Wainwright PJ, Rey N (2000) The influence of ground granulated blast furnace slag (GGBS) additions and time delay on the bleeding of concrete. Cement Concr Compos 22:253–257 15. Ganesh Babu K et al. (2000) Efficiency of GGBS in concrete. Cement and Concrete Res 30:1031±1036 16. Swaroop AHL et al. (2013) Durability studies on concrete with fly ash and GGBS. Int J Eng Res Appl (IJERA) 17. Nath P et al. (2011) Effect of fly ash on the durability properties of high strength concrete. In: The twelfth East Asia-Pacific conference on structural engineering and construction 18. Dhir RK et al. (1996) Chloride binding in GGBS concrete. Cement and Concrete Res 26(12):1767–1773
Stabilization of Expansive Clays: A Micro-mechanistic Study T. V. Nagaraju, M. Venkata Rao, B. M. Sunil, and Babloo Chaudhary
Abstract Stabilization of expansive clays is well known in practice worldwide. However, an additive and appropriate dosage is needed to understand blended clays’ chemical and micro-structural behavior. Moreover, in current practice, most studies rely on blended clays’ index and engineering properties even though the swell-shrink behavior of expansive clays chiefly depends on chemical constituents. Such exposition of selection of additives has chances of improper estimation of quantity. This paper presents the experimental investigation of index properties of soils by varying additives and their contents. The index properties were significantly improved with increasing additive content in the clays. Scanning electron microscopy (SEM) and energy dispersive X-ray spectrometry (EDS) were carried out to assess the long-term strength development. SEM and EDS micrographs revealed the potential role of the chemical composition in the strength development in chemically altered expansive clays. This study provides in-depth aspects of the role of chemical constituents indeed imperative to deciding the optimum dosage of chemical additives in the expansive clay blends. Further, this could be helpful to avoid over/under estimation of chemical dosage and economize project costs. Keywords Expansive clays · Chemical constituents · Cation exchange capacity · Pozzolanic reaction
T. V. Nagaraju (B) · M. Venkata Rao Department of Civil Engineering, S.R.K.R Engineering College, Bhimavaram, India e-mail: [email protected] B. M. Sunil · B. Chaudhary Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, Karnataka, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_13
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1 Introduction Expansive clays, as problematic soil, are also known as black cotton soil. Expansive clays exhibit swelling and shrinkage concerning variation in moisture presence. Since the early 1950s, infrastructure such as residential buildings, towers, bridges, pavements, retaining walls, dams, and heritage structures have experienced severe failures due to uniform and differential settlement of foundation soils [1]. Moreover, significant financial loss was witnessed worldwide, especially in developed countries such US and UK [2]. In the late 1990s, many techniques were practiced counteracting problems associated with expansive clays. The techniques such as pile foundations, cushion layer systems, mechanical stabilization, and chemical stabilization gained significant recognition for dealing with expansive clays. Among the techniques mentioned earlier, chemical stabilization was quite successful [1, 3]. Expansive clays treated with chemical and industrial by-products experience improvement in the geotechnical properties of blended clays [3, 4]. Much research has been carried out in terms of chemical additives and their significant effect on swell-shrink behavior, strength characteristics, durability, and micro-structural behavior [4, 5]. Moreover, most of the research trend is towards finding the optimum dosage of chemical additives based on the swell-shrink behavior and strength characteristics. Expansive clays blended with cement, lime, fly ash, pond ash, silica fume, rice husk ash (RHA), and ground granulated blast furnace slag (GGBS) show significant improvement in expansive clay’s index and engineering behavior [6, 7]. The swelling pressure of the blended clays with 30% fly ash and 30% RHA exhibits an improvement of 83% and 75%, respectively [6]. The free swell index (FSI) of expansive clays was significantly improved by adding chemical additives [7]. Generally, a free swell index of less than 50% is preferable for constructing earthen embankments. However, the chemical constituents such as Ca, Si, and Na present in the blended clays render the behavior of extreme swelling. Although researchers have different perspectives based on the chemical reactions involved in the blended clays, the influence of the chemical constituents varies with the nature of the additive [8]. The swell-shrink behavior of the expansive clays is mainly associated with the chemical constituents and exchangeable ions present in the clays. These can be identified by analytical analyses such as scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), and thermal analysis (TA). In general, chemical constituents such as Ca, Mg, K, and Na in the clays and additives in different forms like total and exchangeable ions [8]. However, determining these forms is complex and requires sophisticated, expensive equipment. In this regard, few researchers have conducted micro-structural studies to understand the blended clay’s surface texture, morphology, chemical compounds (calcium silica hydrates (C–S–H), calcium alumina hydrates (C-A-H), and calcium silica alumina hydrates (C–S–A–H)), and chemical reactions [9, 10]. Another hand, many researchers found that other factors such as suction, surface area, stress conditions, and moisture content affect clay’s swelling behavior. The literature also found no valid relations between the parameters mentioned above
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with volume change due to inadequacy or unjustified data. When a chemical additive was blended with clays, profuse chemical changes such as hydration, flocculation, agglomeration, cation exchange, and cementation were based on the nature of the additive [11]. So, the swelling behavior of blended clays relied more on the presence of chemical constituents and exchangeable forms. In this connection, the selection of additives on the free swell index or any other index property is scanty. As such, only limited research highlighted the influence of chemical constituents on the swelling behavior of clays. This paper presents the role of micro-structural analysis and chemical constituents on the chemically altered clays to select the optimum additive dosage.
2 Soil-Additive Chemical Mechanisms This section presents the brief details of the different chemical mechanisms involved when the expansive clays blended with different additives (chemical additives and industrial by-products). Table 1 shows the chemical composition of the additives. Figure 1 shows the SEM micrographs of the raw materials. SEM micrographs of the raw materials revealed that the morphology of fly ash and pond ash exhibits crystalline inclusions, whereas RHA and bagasse ash exhibit amorphous forms. From Table 1, among all the raw materials, silica fume and GGBS exhibit higher surface areas of 0.52 and 16.5 m2 /g, respectively. Higher surface area and rich silica in the silica fume and GGBS accelerate and enhance the C-S–H gel formation and effective pozzolanic reaction (Eq. 1). Silica(2 SiO2 ) + hydrated lime(3 CaOH2 ) → C − S − H(3 CaO · 2 SiO2 · 3 H2 O) (1) Agro-based wastes (rice husk and bagasse) are very cheaply available materials. Nowadays, these materials are utilized as boiler fuels in industries. For example, in the furfural oil industry, after burning, 20 and 4% ash were generated from the rice husk and bagasse, respectively [12]. So, grounding rice husk ash and bagasse ash into a fine powder cost (Indian rupees per kg ash) around 0.5–1.2 and 0.5–1.5, respectively.
2.1 Cement and Lime Cementitious materials, ordinary Portland cement, and lime are successful in the civil engineering infrastructure. The soil–cement blends initially allow hydration when the blend is exposed to the water content and releases slaked lime and Ca(OH)2 . Secondary reactions form cementitious compounds (calcium silicate and alumina hydrates), which help to bind the particles. The soil–lime blends allow cation
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Table 1 Chemical composition and properties of clay and additives Parameter
Type Clay
Lime
Cement
Fly ash
Pond ash
GGBS
Silica fume
RHA
Bagasse ash
Cost (rupees per kg)
–
5–8.5
6.2–6.8
2–2.9
0.7–1
1.8–2.1
16–24
0.5–1.2
0.5–1.5
Specific gravity
2.68
2.15
3.15
1.95
2.01
2.86
2.08
1.47
1.86
–
0.3
0.34
0.21
0.52
16.5
1.8
2.08
Surface – area (m2 /g) SiO2 (%)
63.1
1.6
21.1
33.5
60
40.0
84.6
95.49
74.5
Al2 O3 (%)
19.3
0.8
4.6
22.9
28.4
13.5
0
0
9.4
Fe2 O3 (%)
4.3
0.2
2.0
6.1
3.8
1.8
0
0.22
2.1
CaO (%)
0.6
91.6
65.1
27.4
0.8
39.2
7.3
0.29
4.42
MgO (%)
1.7
0
4.5
4.6
1.6
3.6
3.5
0
1.2
Na2 O (%)
8.7
0
0
0
0.28
0
0
0.41
0.2
K2 O (%)
1.7
0
0
0
0.68
0
0
0
2.4
SO3 (%)
0
0
2.8
2.8
0
0.2
0.48
0
0
Loss on ignition (%)
0.2
7.8
1.4
1.2
1.4
0
0
2.1
3.2
exchange. Ca(OH)2 contributes Ca+2 ions and OH− ions in the forms of divalent and monovalent, which dissociate with the solution and improve soil environment pH. This helps the cation exchange between the particles, Ca2+ cations from additive with clay surface monovalent cations. Further, cation exchange reduces double diffusion layer thickness and surface forces. Moreover, reduction in the thickness of the double diffusion layer of montmorillonite clay offers flocculation, agglomeration, and shear resistance. The phenomenon, as mentioned above, depends on the type of pore fluid present in the blend. In recent years, these additive’s utilization was decreased due to their carbon footprint and carbon taxes on these materials. Moreover, CO2 emission alone from the cement industry is 0.6 to 1.2 tons for one metric ton of cement manufacture. So, industrial by-products and agricultural wastes are gaining importance in the construction industry [1].
2.2 Fly Ash and Pond Ash Fly ash and pond ash are generated from coal combustion in thermal power plants. Both the coal ashes have high volume stability and exhibit many desirable properties to meet the requirements as a stabilizing agent. The primary chemical constituents
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Fig. 1 SEM micrographs of raw materials a expansive clay, b cement, c lime, d fly ash, e pond ash, f GGBS, g silica fume, h RHA and i bagasse ash
Si2+ and Al3+ present in fly ash and pond ash accelerate and enhance the hydration mechanism in the treated clays. The pozzolanic reaction was the prime positive mechanism involved in the clays blended with fly ash, which is dependent on curing conditions (temperature and time). Dissolving silica and alumina ions contributes to cementitious products such as C–A–H, C–S–H, and C–A–S–H. Moreover, the formation of cementitious products depends on the type of fly ash and the pH environment of the pore fluid.
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2.3 GGBS and Silica Fume GGBS and silica fume are the industrial by-products from the steel and elemental silicon industries, respectively. GGBS and silica fumes are very fine powders with higher surface areas ranging from 400–600 and 15,000–25000 m2 /kg, respectively. GGBS is the only industrial by-product rich in calcium and enough silica. So, GGBS is the best stabilizing agent compared to fly ash and pond ash [1]. Another hand, silica fume having a higher surface area contributes to effective pozzolanic reaction and cementitious compounds.
2.4 RHA and Bagasse Ash Agricultural such as RHA and bagasse ash are abundantly available due to higher production of paddy and sugarcane, particularly in Asian countries. RHA and bagasse ash were found very cheap compared to the industrial by-products such as silica fume, GGBS, fly ash, and pond ash. Cellulose and lignin are common in agro-wastes, which contribute to micro-porous cellular structure. Both agro-waste ashes are rich in silica content and lightweight material. Moreover, the lightweight and highly porous nature of RHA and bagasse ash are best suitable as a geomaterial in the backfill of retaining walls. The rich nature of Si ions in the RHA and bagasse ash contributes to the C– S–H gel around the clay particles, which flocculates and form a highly dense matrix. Further, the pozzolanic activity enhances the properties of the expansive clays.
3 Micro-mechanistic Analysis This section explains the influence of additives on the index properties of clays and cation exchange capacity (CEC). Also, it explores the micro-structural behavior of the blended expansive clays. The experimental investigation was carried out to determine index properties and scanning electron microscopy micrographs in accordance with Phanikumar and Nagaraju [6] and Nagaraju and Mounika [13]. Expansive clay generally consists of montmorillonite minerals with exchangeable cations (Ca+2 , Na+ , K+ , and Mg2+ ). Ca+2 and Mg2+ are major chemical constituents that influence the swelling behavior of expansive clays [14]. In this study, consistency limits liquid limit (LL) and plasticity index (PI) were correlated with FSI to understand the role of index properties in estimating the swelling phenomenon. Hence, there should exist a correlation between FSI on the one hand and LL and PI on the other. Figures 2 and 3 show the correlation between FSI and LL, FSI, and PI. The cluster of data points on both figures shows a reasonably good correlation.
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Fig. 2 Correlation between FSI and LL
Fig. 3 Correlation between FSI and PI
Figure 4 shows a better correlation between the FSI and CEC than the previous correlations. It is observed from the correlation data that CEC values significantly influence the FSI. Herein referred to literature, additional data was plotted CEC against FSI in Fig. 5 [15–17]. Figure 5 shows that CEC values drastically differ from the type of clay and mineral holding. Total CEC (meq/100 g) values vary from 10 to 100 due to the percentage of montmorillonite available in the blend. The exchange of cations and
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Fig. 4 Correlation between FSI and CEC
swelling phenomenon depends on the surface area and pore fluid. With the other factors, CEC can vary but not vice versa. So, CEC could be one of the significant parameters to decide the dosage of additive content without over/underestimation in soil stabilization. Furthermore, higher percentages of low-cost additives, RHA, and bagasse ash contents, up to 30%, can be utilized as an additive [6]. Employing a higher percentage of RHA and bagasse ash can reduce the environmental threat and economize project costs [18].
4 Conclusions This paper highlights the role of chemical constituents in selecting additives for soil stabilization. Based on the peer-glance of the published literature, as per carbon footprint and economic aspects, agricultural wastes such as rice husk ash (RHA) and bagasse ash were rich and dominant in silica, contributing to cation exchange and formation of cementitious products. However, the grounded process of these additives needs better equipment to improve the surface area of the RHA and bagasse ash. Further, the higher surface area of additives effectively reacted into pores and formed a dense matrix. Based on the micro-mechanistic analysis, confirming the additive dosage relies on the index and engineering properties only to a certain extent. Moreover, blended
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Fig. 5 Effect of CEC on FSI of expansive clays
expansive clay’s behavior was predominant in the presence of chemical constituents in clay (Ca+2 , Na+ , K+ , and Mg2+ ) and additive (Si+2 , Al+3 , and Ca+2 ). The results show that CEC values less than 40 meq/100 g exhibit less swelling. So, CEC values are the best and superior parameter to fixing additive dosage to avoid over/under estimation of additive content and economize project cost.
References 1. Ikeagwuani CC, Nwonu DC (2019) Emerging trends in expansive soil stabilisation: a review. J Rock Mech Geotech Eng 11(2):423–440 2. Perera STAM, Saberian M, Zhu J, Roychand R, Li J (2022) Effect of crushed glass on the mechanical and microstructural behavior of highly expansive clay subgrade. Case Stud Construct Mater 17:e01244 3. Barman D, Dash SK (2022) Stabilization of expansive soils using chemical additives: a review. J Rock Mech Geotech Eng 4. Indiramma P, Sudharani C, Needhidasan S (2020) Utilization of fly ash and lime to stabilize the expansive soil and to sustain pollution free environment–an experimental study. Mater Today: Proc 22:694–700 5. Dang LC, Khabbaz H (2018) Assessment of the geotechnical and microstructural characteristics of lime stabilised expansive soil with bagasse ash. GeoEdmonton 6. Phanikumar BR, Nagaraju TV (2018) Effect of fly ash and rice husk ash on index and engineering properties of expansive clays. Geotech Geol Eng 36(6):3425–3436 7. Phanikumar BR, Nagaraju TV (2018) Engineering behaviour of expansive clays blended with cement and GGBS. Proc Instit Civil Eng-Ground Improvem 171(3):167–173
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8. Rao BH, Reddy PS, Mohanty B, Reddy KR (2021) Combined effect of mineralogical and chemical parameters on swelling behaviour of expansive soils. Sci Rep 11(1):1–20 9. Reddy PS, Mohanty B, Rao BH (2021) Influence of Na and Ca contents on swelling behavior of Indian expansive soils. Arab J Geosci 14(23):1–22 10. Reddy PS, Yang YL, Mohanty B, Rao BH (2022) Assessment of testing method influence on swelling characteristics of expansive soils of India. Arab J Geosci 15(12):1–14 11. Sriram Karthick Raja P, Thyagaraj T (2021) Effect of short-term sulphate contamination on lime-stabilized expansive soil. Int J Geotech Eng 15(8):964–976 12. Jittin V, Bahurudeen A (2022) Evaluation of rheological and durability characteristics of sugarcane bagasse ash and rice husk ash based binary and ternary cementitious system. Construct Build Mater 317:125965 13. Nagaraju TV, Mounika KN (2022) Swelling characteristics of fly ash based geopolymer expansive clay blends. In: Ground improvement and reinforced soil structures, Springer, Singapore, pp 233–240 14. Jha AK, Sivapullaiah PV (2020) Lime stabilization of soil: a physico-chemical and micromechanistic perspective. Indian Geotech J 50(3):339–347 15. Elshater A, Khashab MA, El-Sherif MA, Abu Seif ES (2019) Geological and engineering characteristics of expansive soils in Western Desert, Egypt. Civ Eng Res J 7(2) 16. Hakami BA, Seif ESSA (2019) Geotechnical aspects and associated problems of Al-Shuaiba Lagoon soil, Red Sea coast, Saudi Arabia. Environ Earth Sci 78(5):1–19 17. Yao H, Cheng P, Yang Y, Wu W (2005) Theory and practice concerning classification for expansive soils using standard moisture absorption water content. Sci China Ser E: Technol 682 Sci 48(1):31–40. https://doi.org/10.1360/04ye0237 18. Vamsi Nagaraju T, Satyanarayana PVV (2019) Geotechnical aspects of various constructions along the canal embankment using rice husk ash as stabilizer. In: Ground improvement techniques and geosynthetics, Springer, Singapore, pp 143–150
Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix Akshima Gautam, Mahendra Kumar Singar, and Ravi Kant Pareek
Abstract Concrete structures got subjected by various chemical attacks such as sulfate, chloride, acid and alkali which indirectly effects the durability of the structure. An adhesive force is induced when polypropylene fiber is used in concrete mix which is a thermoplastic polymer and by its nature it holds the mix together very firmly. Concrete mix with PPF in it reduces so many adverse effects such as bleeding, plastic and elastic cracks and cracks generated due to these effects. During the casting of the cubes at the site slump test are done on fresh concrete with the addition of proportion of PPF (0–2%) so that the needed workability can be achieved. Keywords Polypropylene fiber · Marble dust · Strength · Workability
1 Introduction When coarse aggregates, fine aggregates, sand and cement mixed in proportion in result gives concrete as final product. Different type of additive, retarder or admixtures can be used as per the requirements of the structure. After cement the most important component of the concrete mix is aggregate. Due to relative economy and high versatility cement has become a very famous building material as compared to other materials. In recent times, demand of concrete structures is on peak which increases the expansion of the infrastructures. When concrete is used without reinforcement it becomes brittle in nature which decreases its tensile strength and strain capacity [3]. The fibers are in use from ancient times because fibers provide different types of A. Gautam (B) · M. K. Singar · R. K. Pareek Department of Civil Engineering, Vivekananda Global University, Jaipur, India e-mail: [email protected] M. K. Singar e-mail: [email protected] R. K. Pareek e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_14
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strength to the concrete fix such as flexural and tensile strength. So many researchers have investigated about the several effects using fiber in the concrete mix and noted the changes in the strength of it. There are many types of fibers which are in use since long time such as glass, carbon, steel and especially polypropylene fiber which is mostly used in the concrete mix. Ductility and brittleness get mostly effected when fibers get induced in concrete mix. Several properties are improved when PPF is used in the concrete mix which includes flexural, tensile, compressive strength, toughness, strength of impact, and the failure modes are also defined very firmly [6]. When PPF is used in particular proportion in the concrete mix it shows settlement of coarse particles which in result reduces bleeding of concrete and slow down the drying rate which indirectly reduces the shrinkage. In this research, the effect of PPF when replaced in a proportion is investigated with also addition of 10% of marble dust in the concrete mix. A comparison between M25 and M30 is also analyzed for a cost-effective parameter [8]. Marble dust is kept constant as 10% by weight in replacement of cement, and PPF is taken in variation of percentage as 0, 0.5, 1.0, 1.5 and 2.0%. The use of reinforcement with fiber can increase different properties of concrete which in result increases the age of the concrete structure gives proper durability, reduces shrinkage, provides toughness and mechanical strength of the mix [1]. Fiber when used in the concrete mix the compressive, flexural, impact strength gets increased and crack proportion get reduced. Hence, title of this research is selected as “Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix”.
2 Research’s Objective When marble dust and polypropylene fiber is used as the replacement of the cement partially various strengths increases such as compressive strength, tensile strength, flexural strength and workability of the concrete mix. · Reduction of cracks generation due to plastic shrinkage. · Different kinds of strength are increased due to addition of fibers. · Reduction of damage occurred due to chemical changes due to environmental effects on concrete [6]. · Decrease in impact load failure and for resistance properly in the concrete mix. · For the workability analysis of fresh concrete.
3 Literature Review See Table 1.
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Table 1 Overview of the studies on the effect of PPF on concrete mix References
Key issue addressed
[1]
The effects of polypropylene fiber use The findings demonstrate that using PPF on the mechanical characteristics of improves the qualities of concrete cement mortar were researched and analyzed
Outcome
[2]
The mechanical performance of PFRC under compression and split tensile loads
Increase in strength (compressive and tensile) was found. The samples with additional PPF of 1 and 1.5% produced better outcomes
[3]
The mechanical properties of Hybrid Fiber-Reinforced Concrete were investigated (HFRC)
The strength parameter increases as the proportion of fiber grows, and a hybrid ratio of 1.5% produces the best results when compared to other hybrid ratios
[6]
Different strength of polypropylene fiber reinforced concrete is evaluated and compared with plain concrete
When compared to plain concrete, there will be no substantial difference in compressive strength, but will be a large improvement in flexural, split tensile, and shear strength
[7]
The influence of polypropylene fibers In this study, there was a 47% ranging from 0.1 to 0.4%, as well as improvement in split tensile strength and a 0.8% steel fibers, on concrete 50% increase in flexural strength behavior was examined
[8]
The strength qualities of Polypropylene fiber reinforced concrete were investigated
In comparison to the others, it was discovered that Polypropylene fibers with a concentration of 1.5% produced better outcomes
[9]
Experimental investigation of mechanical properties of self-compacting concrete with PPF
According to the findings, the maximum amount of fiber in SCC was 0.75% to 1% of the total cement content per mix
[10]
Bottom ash has been utilized to substitute fine aggregate in concrete mixes, and PPF has also been used to improve the strength qualities of concrete
The study demonstrated that using bottom ash instead of fine aggregates had no effect on the strength of the concrete
[11]
The influence of PPF ranging from 0.1% to 0.4%, as well as 0.8 % Steel fibers, on the stress–strain behavior of fibrous concrete is investigated
The study shows adding PPF reduces the failure strain as the volume percentage of PPF increases
[12]
The inclusion of fibers and fly ash in Study shows a minor negative effect on different percentages and the effect of the workability of the concrete and PPF on concrete was tested increase the strength of hardened concrete
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4 Materials and Methodology In this research, the cement is used of grade 43(OPC) from Ultra tech Cement with G = 3.1645 and 93% of fineness from Bharuch plant. Crushed aggregates of 20 mm size are used with G = 2.76 and 0.5% absorption of water [12]. Natural sand from Narmada river is used with G = 2.66 and 1% absorption of water. Marble dust which is obtained from Kishangarh Marble Industry, Kishangarh, Rajasthan with G = 2.77 and 24.4% absorption of water (pH-8.89). All he materials are taken from Jay Goga construction, Ahmadabad (Gujarat). PPF used in this research which is NOKRACK from Dolphin Floats Pvt. Ltd., India · Technical details for Water Absorption Coarse Aggregate = 0.5% Fine Aggregate = 1% Marble Dust (%) = 1%. · Control Mix M25 and M30 Slump value M25 = 75 mm. M30 = 90 mm. · Slump value with 10% MDP & PPF 1. M25 at a. b. c. d. e.
Polypropylene fiber (0%): 70 Polypropylene fiber (0.5%): = 68 Polypropylene fiber (1%): = 64 Polypropylene fiber (1.5%):PPF = 61 Polypropylene fiber (2%):PPF = 59.
2. M30 at a. b. c. d. e.
Polypropylene fiber (0%): 80 Polypropylene fiber (0.5%): 78 Polypropylene fiber (1%): 75 Polypropylene fiber (1.5%): 72 Polypropylene fiber (2%): = 70 (Figs. 1, 2, 3, 4, 5 and 6).
5 Findings The use of fibers increases different types of strength and other properties of the concrete mix, and the induction of cracks are reduced due to plastic and elastic shrinkages [4].
Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix 7 Days
14 Days
28 Days
COMPRESSIVE STRENGTH (N/MM2)
40
30 25 20
34.82
33.64
35 29.93 26.82 21.46 16.09
173
26.94
27.85
20.52
21.24
23.78 17.95
27.70 22.24 18.17
15 10 5 0
0
0.5
1
1.5
2
POLYPROPLYENE FIBER %
Fig. 1 Comparison of strength (compressive) of M25
COMPRESSIVE STRENGTH (N/MM2 )
7 Days 40
14 Days
28 Days
35.84
36.79
35.60
28.46
29.47
28.76
22.8
21.71
1.5
2
35
32.67
33.47
30
32.67
26.12
19.60
20.41
21.5
0
0.5
1
25 20 15 10 5 0
POLYPROPYLENE FIBER %
Fig. 2 Comparison of strength (compressive) of M30 grade
Such that the title for this research is “Addition of Marble Dust and Polypropylene Fiber in the Concrete Mix”.
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SPLIT TENSILE STRENGTH (N/MM2)
7 Days
14 Days
3.5
3.26
3 2.5
28 Days
2.73 2.24
2.41 1.94
2
1.79
1.5
1.38
1.49
0
0.5
2.18
2.58 2.02
2.27 1.77
1.66
1.39
1 0.5 0 1
1.5
2
POLYPROPYLENE FIBER %
Fig. 3 Comparison of strength (splitting tensile) of M25 grade
SPLIT TENSILE STRENGTH (N/MM2)
4.5 4 3.5 3 2.5 2
3.33
7 Days
14 Days
3.97
4.12
3.33
2.97 2.42
28 Days
3.48
3.64
3.41
3.29 2.51
1.99
2.22
3.06 2.04
1.5 1 0.5 0 0
0.5
1
1.5
2
POLYPROPYLENE FIBER %
Fig. 4 Comparison of strength (splitting tensile) of M30 grade
6 Discussion For this research different tests are performed for strength check such as compressive, flexural and split tensile are done on the M25 and M30grade concrete with different percentage of PPF (0%,0.5%,1%,1.5% and 2%) and with partial replacement of marble dust by 10% by weight of cement. Total 60 PPF R/f Concrete cubes and cylinders were casted for the test performance with zero error and taken for curing for 7 days, 14 days and 28 days. During the casting of the cubes at the site slump test
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FLEXURE STRENGTH (N/MM2)
7 Days 4 3
2.6
2
1.58
3.4
3.3
2.9
2.7
1.76
2.01
2.07
1
1.5
1.67
1 0 0
0.5
2
POLYPROPYLENE FIBER %
Fig. 5 Comparison of strength (flexural) of M25 grade
FLEXURE STRENGTH (N/MM2)
7 Days
28 Days
4 3.38
3.5 3
2.70
2.97
2.5 2
1.64
1.81
3.26
3.12
2.06
1.98
1.93
1
1.5
2
1.5 1 0.5 0
0
0.5
POLYPROPYLENE FIBER %
Fig. 6 Comparison of strength (flexural) of M30 grade
are done on fresh concrete with the addition of proportion of PPF (0–2%) so that the needed workability can be achieved.
7 Conclusion · In this study, M25 and M30 grade of concrete were used along with water–cement ratio of 0.45. A total of 120 PFRC (polypropylene fiber reinforced concrete) was cast. The percentage of polypropylene fiber used in the current study was 0 to 2% with 10% marble dust. · Compressive strength increases of M25 and M30 with polypropylene and marble dust was found to be 29.82% and 12.61%, respectively.
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· Tensile strength increases of M25 and M30 with polypropylene and 10% marble dust were found to be 45.53% and 23.72%, respectively. · Flexural strength increases of M25 and M30 with polypropylene and 10% marble dust were found out to be 30.76% and 25.18%, respectively.
References 1. Alsadey S (2016) Effect of polypropylene fiber on properties of mortar. Int J Energy Sci Eng 2:8–12 2. Khan S, Khan RB, Khan RA, Islam M, Nayal S (2015) Mechanical properties of polypropylene fiber reinforced concrete for M 25 & M 30 mixes: a comparative study. Int J Sci Eng Appl Sci 1(6):327–340 3. Kumar SK (2016) Effect of steel and polypropylene fiber on mechanical properties of concrete. Int J Civ Eng Technol 7(3):342–346 4. Mohod M (2015) Performance of polypropylene fiber reinforced concrete. IOSR J Mech Civ Eng 12(1):28–36 5. Murahari K, Rao RM (2013) Effects of polypropylene fibers on the strength properties of fly ash based concrete. Int J Eng Sci Invention 2(5):13–19 6. Patel P, Desai K, Desai J (2012) Evaluation of engineering properties for polypropylene fiber reinforced concrete. Int J Adv Eng Technol 3(1):125–129 7. P & Sharma A (2013) Structural behavior of fibrous concrete using polypropylene fibers. Int J Mod Eng Res 3(3):1279–1282 8. Ramujee K (2013) Strength properties of polypropylene fiber reinforced concrete. Int J Innov Res Sci Eng Technol 2:3409–3413 9. Rani B & N (2017) Self-compacting concrete using polypropylene fibers. Int J Res Stud Sci, Eng Technol 4(1):16–19 10. Sathya Prabha K, Rajasekar J (2015) Experimental study on properties of concrete using bottom ash with addition of polypropylene fiber. Int J Sci Res Publ 5(8):1–6 11. Verma SK, Dhakla M, Garg A (2015) Experimental investigation of properties of polypropylene fibrous concrete. Int J Eng Innov Technol 4(10):90–94 12. Yeswanth M, Ragavan TR, Amarapathi G (2016) Experimental investigation on polypropylene fiber reinforced concrete with addition of fly ash. J Appl Phys Eng 1:1–4
Comparative Analysis of High-Rise Structure with Diagrid Lateral Load-Resisting System with Composite Members and Base Isolation Harpreet Singh
and Aditya Kumar Tiwary
Abstract Due to the dense population and lack of land for building developments, high-rise structures and flats are becoming increasingly important in metropolitan and sub-urban regions. The design and construction of tall structures should be efficacious, such that it should be adept at resisting the detrimental effect of earthquake and wind forces. As a result, composite construction is utilized, which combines the benefits of two materials, namely concrete and lightweight steel, and is used in both buildings and bridges with long spans. Bonding and friction between steel and composite structures withstand external loading in composite columns. Rigid MRF frame, RCC shear wall, RCC wall frame, braced tubular system, outrigger structural system, and steel tubular system are some lateral loads resisting structural solutions for high-rise structures. Because of its structural proficiency and versatility in space and esthetic planning, the diagonal grid structural system has recently been utilized in tall structures. One of the most recent methods utilized in construction to resist seismic waves induced by earthquakes is base separation or isolation design. The practice of base separation has been utilized to safeguard constructions from the devastating consequences of seismic forces. The positioning of isolators at the footing level improves the structural flexibility of the building. In this paper, behavior of composite column structure with the use of a diagrid structural framework as a lateral load withstanding system and base isolation technique was analyzed. The outcomes from the software analysis were collected in terms of shear force at each story level, story level displacement, total shear at the base and fundamental time period, etc., and analysis results were compared from all the models. After doing the analysis, it was concluded that including composite sections as diagrid members improves the rigidity of the structure, but the structure has to design for higher base shear. Base isolation is a very effective seismic response control system and improves the performance of a diagrid structural system under seismic loading. H. Singh (B) · A. K. Tiwary Department of Civil Engineering, Chandigarh University, Mohali, India e-mail: [email protected] A. K. Tiwary e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_15
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Keywords Base isolation technique · Diagrid structural system · Composite columns · Linear dynamic analysis · Story displacement · Base shear · Fundamental time period
1 Introduction Because of the rising urbanization and population needs, there has been an increase in the need for tall building development. The risk of lateral loadings grows as the building’s height increases. Thus, comprehensive modeling of such loadings is required in order to analyze the structure’s behavior with a clear image of the structural damage that is anticipated [1]. For more than three to four decades, reinforced concrete buildings have met increasing demands in the civil and structural engineering sectors. The widespread use of R.C.C. in structural and architectural applications bears testament to and demonstrates the material’s adaptability. The majority of building structures in developing nations such as India are low-rise structures. As a consequence, these traditional-reinforced cement concrete and pure sectional steel structures are convenient and affordable in nature and are extensively employed all over the world. However, when it comes to the necessity for vertical building expansion owing to a shortage of land-space area and rapid population increase, medium to high-rise structures emerge as a solution to meet this demand [2]. A high-rise building’s seismic behavior must be evaluated based on its general shape, scale, and geometry. The story shears in a building must be transported down to the basement in the shortest way; any discontinuity in the structural parts results in a change in the load path. As a result, a huge number of composite parts are presently being introduced for medium to high-rise structures to achieve this goal. It has been discovered that the use of composite members in the construction of high-rise structures is more effective and cost-efficient than reinforced concrete members [3]. The use of composite or hybrid materials continues to be of great interest, owing to its substantial potential for enhancing overall performance with minor modifications in manufacturing and building procedures. If appropriately constructed, steel-concrete-composite systems can provide cost-effective structural solutions with great durability, quick erection, and improved seismic performance [4].
1.1 Composite Construction One of the most effective approaches for meeting this criterion is composite construction. In addition, the behavior of steel tubes filled with concrete (CFST) and I Section encased with concrete composite columns, as opposed to reinforced cement concrete (RCC) columns utilized in high-rise structures, must be evaluated. The CFST and encased I Section composite column structure are a form of composite steel-concrete structure that is now being employed in the civil engineering profession [5, 6]. CFST
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and encased I Section composite columns are frequently employed in real civil engineering projects because of their superior static and seismic resistant qualities. They have great strength, ductility, and excellent energy absorption capability [7]. Concrete infilled steel tube/pipe (CFST) members take advantage of the benefits of these two different materials, viz. steel tube/pipe and infill concrete. They are made out of a circular or rectangular hollow section made up of steel filled with ordinary or reinforced concrete. They are commonly employed as columns and beam-columns in high-rise and multi-story structures, and as beams in smaller height industrial structures when a sturdy and proficient lateral load-resisting system is needed. In terms of structural performance and building sequencing, such structural systems provide a variety of distinct benefits. When compared to typical structural steel systems, the CFST idea may result in a total steel savings of 60%. Steel pipes/tubes were also employed as persistent shuttering, and the properly placed steel reinforcement was situated at the most appropriate position [8, 9].
1.2 Diagrid System The most common lateral load withstanding systems comprise rigid MRF frame, RCC shear wall, RCC wall frame system, braced tubular structural system, outrigger lateral load-resisting system, and steel hollow tubular system. The diagonal grid lateral load-resisting structural system has recently become trendy for tall structures due to its structural proficiency and look and useable space possibilities afforded by the system’s distinctive geometric layout [10]. Diagrid structures are made up of diamond-shaped modules, and they provide more lateral stiffness than other forms of buildings. Diagrid systems are very effective in limiting lateral deformation because diagonal components bear lateral force/loading [11]. The diagrid system has lately been implemented in a number of taller steel constructions because of its structural efficiency. This system is a sort of space truss system without the use of regular columns on the periphery border of the building. Diagrid is made up of a variety of triangulated truss systems and is built by crossing diagonal columns and horizontal beams [12]. Relative to traditional moment-resisting-frame construction, the periphery “diagrid” method saves roughly 20% of steel consumption. Because of their triangulated structure, diagonal elements in diagonal grid lateral load-resisting structural systems may handle both vertical loads and horizontal forces [13]. This design is distinct from the standard architecture, which consists of vertical columns and horizontal beams and is also known as an orthogonal structure. Inclined columns and ring beams are utilized in diagrid construction. A diagrid structure eliminates the second-order bending moment and maximizes element load-carrying capacity by bearing horizontal thrust and producing axial load in the column axis under horizontal load. In comparison with the rectangles created by upright columns and horizontal beams, the triangles created by ring beams and oblique columns are well firm [14]. A diagrid structure is depicted on the ground as a vertical cantilever beam that is longitudinally split into modules based on the repeating diagonal grid geometry. A
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single set of diagrids covering numerous levels characterizes each module [15]. The ideal diagrid structure is a circumferential resisting framework with a latticed design composed of small diagonal elements that can transmit both vertical and horizontal loads purely by axial behavior: compression and tension load with shortening and elongation deformations [16]. The diagrid system’s structural efficiency also assists in the elimination of interior and corner columns, allowing for greater floor design flexibility. Diagrid has a pleasing look and is easily identified. The layout and proficiency of a diagonal grid system decrease the no. of structural elements necessary at the building’s façade, resulting in less hindrance to the outside view. Because diagonal columns resist lateral pressures, top story displacement is far less in a diagrid design than in a typical frame building. The diagrid structural framework has much less story drift and shear.
1.3 Base Isolation In recent decades, the concept of base isolation has been presented, and existing technologies and knowledge of base isolation systems are becoming mature and well-established. Seismic isolation devices are more effective when fitted to highstiffness and low-rise structures because of their capacity to modify the stiffness of the structure from rigid [17]. The fact that a rising number of structures are being isolated underlines the fact that base isolation systems are fast becoming considered as a proven strategy in seismic hazard prevention [18]. A base isolation design, often known as seismic isolation, protects a building from the impacts of earth movements. When the seismic isolation system is installed beneath the structure, base isolation is employed. It separates the superstructure from the ground. By making the structure separated from ground disturbances, the building remains stationary in the disrupted configuration. The disturbances created by the earth can be decreased by lowering the natural frequency with a base isolation system. Base isolation is one of the most frequently used and acknowledged earthquake safety technologies [19]. The basic idea behind seismic isolation is to protect a structure from the damaging effects of an earthquake by incorporating flexible support that isolates the structure from the shaking ground. The building is literally removed from its foundations. In fact, a complete separation of the structure from its foundations is impractical since considerable relative horizontal displacements must be avoided during earthquakes or when other horizontal stresses, such as wind, are present. As a result, the standard answer is to utilize a layer, generally between the foundation and the superstructure that is more flexible than the other structural parts and can carry the vertical load while suffering lateral displacements without causing severe damage. As a consequence, inertial forces and accelerations are reduced many times [20]. The benefit of LRB is that it can perform both isolation and re-centering functions in a single unit, which provides the isolation system with lateral support, lateral flexibility, and re-centering actions. Many separation technologies, such as low damping rubber base-isolated bearings and friction pendulum systems, provide enough isolation and
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self-centering. In addition to dampening, sandwiched rubber layers between the steel plates may achieve a high vertical rigidity. Because of its high vertical stiffness, the LRB system can sustain a substantial vertical load while moving laterally with lesser stiffness than other isolation systems. As a result, a single system can hold a building or structure vertically while also providing lateral motion and enhancing damping in the structure to a desirable level [21, 22]. In this paper, effect of composite columns and base isolation technique on the diagrid structural system had been presented. The primary goal of the investigation is to increase the capacity of the diagonal grid lateral load-resisting system under the effect of seismic loading by utilizing composite columns and base isolator techniques. The results of the analysis had been collected in terms of maximum story level displacement, shear force at the bottom, fundamental period of the building, etc., and then compared to acquire the concluding remarks.
2 Methodology ETABS v19 is used to generate 3D models utilizing conventional RCC and composite columns. Four models were designed for the necessary investigation, two of them were of general diagrid systems and two of them were composite diagrid systems with and without base isolation. The seismic behavior of structures with RCC and composite columns using the diagrid system and base isolator technique is explored utilizing linear dynamic procedure. To obtain conclusions, the outcomes with regard of aspects such as maximum story level displacement, story level drift, shear force at the base, story level shear force, time period, and story stiffness were noted.
2.1 Modeling Eleven story structure including ground floor of plan area 20 × 20 m is selected. Story level height is taken as 3 m. The elevation and plan of diagrid structure with base isolator are presented in Fig. 1, and its 3D view is presented in Fig. 2. The cross section of the ordinary inclined column is used as 450 × 450 mm, and for composite column, tube of 6 mm thick is utilized as a casing to the concrete, and the size of the diagrid section was taken as 350 × 350 mm. Lead rubber bearing (LRB) base isolator was used for the study. Table 1 presented a model description with loading and other attributes required for investigation. Table 2 shows the properties of the base isolator used for the study, and details of isolator are presented in Fig. 3. For the investigation, four models were taken into consideration, as presented in Table 3.
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Fig. 1 Elevation of base-isolated model and plan of diagrid system Fig. 2 3D view of diagrid structural system
2.2 Response Spectrum Analysis Due to its ease of use and quickness, this approach of analysis is typically preferred by structural designers. The non-linearity of the structure is disregarded in this linear dynamic analysis method. Low-height structures can advantageously be designed by static analysis, but as the structure’s height increases, static analysis outperforms dynamic analysis in terms of results, and tall buildings need dynamic analysis to
Comparative Analysis of High-Rise Structure with Diagrid Lateral … Table 1 Model attributes
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Model description Plan size
20 × 20 m
Story height
3m
No. of story
G + 10
Total height
34.5 m
Bay width on both sides
5m
Ground level above base
1.5 m
Member properties Beam dimension
230 × 450 mm
Column dimension
450 × 450 mm
Thickness/depth of the slab
150 mm
Thickness of hollow tube
6 mm
Diagrid size
350 × 350 mm
Base isolator
Lead rubber bearing
General loadings Live load [IS 875, Part 2]
3 kN/m2
Floor finishing load
1.5 kN/m2
Material properties Grade of concrete
M25 and M20
Grade of steel
FE500
Seismic properties
Table 2 Properties of lead rubber bearing base isolator
Zone factor
0.24 (zone IV)
Importance factor
1
Response reduction factor
5
Soil type
Medium
Damping factor
0.05
Types of property Pre-yield stiffness, K e
1083.10 kN/m
Post-yield stiffness, K p
10,831.01 kN/m
Effective stiffness, K eff
1175.42 kN/m
Characteristic strength, Qd
30.97 kN
Yield strength, F y
34.703 kN
Yield displacement, Dy
0.0032 m
Maximum displacement, Dm
0.3355 m
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Fig. 3 Base isolator, a lead rubber bearing, b force displacement curve
Table 3 Forms of models established Model Id
Description
M1
Model with ordinary columns with diagrid system
M2
Model with composite columns with diagrid system
M3
Model with ordinary columns with diagrid system with base isolator technique
M4
Model with composite columns with diagrid system with base isolator technique
obtain the proper response in view of seismic loadings. In comparison with static analysis, dynamic analysis has proven to be cost-effective in design. Shear force at the base is determined in linear response spectrum analysis in the same way as in static analysis, but for the purpose of determining design spectral acceleration, based on the kind of soil and the natural period of the building, IS 1893 [23] provides a separate table. The results of each of the analyzed building models were collected and compared when the analysis was complete. The major purpose of the study was to ascertain the dynamic responses of the various models listed in Table 3 and compare the results to gage the effectiveness of base isolation and composite columns as well as the advantages and disadvantages of the models taken into considered.
3 Results and Discussion The seismic analyzes of the four models under investigation were completed, and the findings were compiled with regard of various response characteristics, including base shear, story shear forces, maximum displacement, inter-story drifts, fundamental time period, stiffness values, and others. Tables and graphs were used to present the ETABS results.
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14 M1
Story Displacement, mm
12
M2 M3
10
M4 8 6 4 2 0 Roof 10F 9F 8F 7F 6F 5F 4F 3F 2F 1F GF Base
Story Level Fig. 4 Maximum story displacement plot
3.1 Maximum Story Displacement Figure 4 presents the story displacement plot for investigated models. Model M1 leads to a greater amount of displacement than the other models at all story levels, and model M4 leads to a minimum amount of story displacement at the roof level. This large amount of reduction in displacement is due to the inclusion of a composite section as a diagrid section and the use of the base isolation technique. However due to composite diagrid members, reduction in story displacement is small but when base isolation has used, the reduction of displacement is very much high, because base isolation set apart the building from the ground, and the vibrations experienced by the ground will not be fully transferred to above structure, and superstructure is subjected to less lateral forces. Models M1 and M2 are without base isolation, and models M3 and M4 are with base isolator techniques as presented in Fig. 3. The displacement results for base-isolated models, i.e., M3 and M4, are shown with respect to the base and not the actual values.
3.2 Maximum Story Drift Figure 5 presented the graphical results of story level drift variation for four models. It is observed that models M1 and M2 show more drift values than model M3 and M4. This is because of using base isolation techniques with a diagrid structural system.
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0.0006
M2 M3
Story Drift
0.0005
M4
0.0004 0.0003 0.0002 0.0001 0 Roof 10F 9F 8F 7F 6F 5F 4F 3F 2F 1F GF Base
Story Level Fig. 5 Maximum story level drift plot
Composite diagrid sections also help to reduce the value of story drift, but the effect is small. For models M3 and M4 drift, values are almost the same at each story which shows that inter-story displacement values are equal, and structure displaces by equal amounts in a uniform way. At the ground level, a significant change of drift is happening because drift is the ratio of inter-story displacement and height of the below story. In the case of ground level, the bottom of the building is considered firmed so the displacement of the bottom will not happen, and the difference between ground displacement and the base is more than that of any other story. Also, the height of the ground level above the base is half to that of any other story, resulting in a high value of story drift.
3.3 Maximum Story Shear Figure 6 presented the graph for maximum story level shear for investigated models under study. Model M2 with composite diagrid sections shows more amount of story shear than M1. The composite section results in an increase in the dead weight of the building due to which the value of shear at each story level increases. Model M3 and M4 resulted almost same deviation of story shear results. The base isolation techniques are very much effective in reducing the value of shear at story levels. Due to the isolated base at the bottom, the forces transferred to the structure under seismic loading become less. And values of the coefficient of spectral acceleration reduce, resulting in a decrease in the story shear values.
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2000 M1
1800
M2
Story Shear, kN
1600
M3
1400
M4
1200 1000 800 600 400 200 0 Roof 10F 9F
8F
7F
6F
5F
4F
3F
2F
1F
GF Base
Story Level Fig. 6 Maximum story level shear plot
3.4 Base Shear Figure 7 presented the base shear results for four investigated models. Model M2 leads in a high value of base shear and model M3 resulted in a less value of base shear than other models. The weight of composite section in model M2 with diagrid structural system results in a high seismic weight of the model and due to which at each story level shear values increases, and base shear grows. As the base isolator approach is used in a diagrid structural system with ordinary column sections, base shear values decrease due to fewer forces transferring to the upper structure due to isolation at the base. However, when composite sections are used with the base isolation technique, there is little increase in the base shear value.
3.5 Fundamental Time Period Figure 8 presented the fundamental times period for all the models. Model M2 shows a very less time period and model M4 resulted in a greater time period than the other models. Owing to the inclusion of composite diagrid sections, the stiffness of the building increases because of which the natural time period of the structure reduces. However, when base separation technique is used in the building, the model is unrestricted to displace at the bottom and cycle length of the model increases which results in increases in the natural time period of the model. Models M3 and M4 show almost similar values of time period. Including composite sections with base separation raised the time period of the model but in little amount only.
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Base shear
Base Shear, kN
1600 1400 1200 1000 800 600 400 200 0 M1
M2
M3
M4
Type of Model Fig. 7 Base shear plot
2.5
Time Period, sec.
Time Period 2 1.5 1 0.5 0
M1
M2
M3
M4
Type of Model Fig. 8 Fundamental time period plot
4 Conclusions In the above investigation, an effort was done to check the influence of composite diagrid sections and base isolation techniques on the conventional diagrid structure. The main idea behind the study was to increase the capacity of the diagrid structural
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system by using composite sections and base isolation. After accomplishing the investigation and obtaining outcomes, below conclusions were spotted. 1. Composite columns provide more rigidity to the structure which leads to a reduction in the maximum story displacement. Base separation is significantly effectual in restricting the displacement values with respect to the base. Model M2 results in 12.5%, M3 results in 66%, and M4 results in a 72.5% reduction in displacement values at the top story of the model. 2. Due to more self-weight provided by the composite columns, the rigidity of the model enhanced due to which overall displacement of structure reduces, and story drift values go down. As in the view of base isolator, story displacement values are very less than conventional diagrid structures, and drift values are almost the same at each story level. Model M2 results in 13.5%, M3 results in 70%, and M4 leads in a 76.5% decrease in maximum story drift values. 3. As composite columns raised the self-weight of the structure’s story, shear values come out to be more in the case of composite diagrid structural system than conventional diagrid system. However, base isolation techniques reduce the amount of story shear due to the isolation of the building at the base level and the building encounter lesser value of horizontal forces in seismic event. Model M2 shows a 19% increase in the maximum story shear. M3 shows 67.5%, and M4 shows a 66.6% reduction in story shear. M4 shows less reduction than M3 due to the inclusion of composite sections in place of the conventional diagrid system. 4. As base shear is the sum of story shear at every story level, the effect of composite sections and base isolation on base shear value is the same as that of story shear results. M3 leads in a maximum percentage decrease in the base shear at the base than other models because of the base isolation technique. M2 shows a very higher amount of base shear due to using composite sections in place of conventional diagrid members. When both composite sections and base isolation were used as in the case of M4, there is a 2.8% increase in the base shear value. 5. Natural time period of the building is very much dependent on the rigidity and deadweight of the building. Composite columns add to the deadweight of the building so the time period of the building reduces owing to more rigidity and rise in the frequency of motion. But base separation releases the constraints at the base of the building owing to that the fundamental time period of the structure rises. M2 depicts a 14% reduction in the natural time period of the structure, but on the other side, M3 and M4 result in approximately 200% gain in the natural time period of the structure. From the present analysis, it is clear that although the diagrid structural system is very much effective in resisting lateral loading but including composite sections in place of diagrid members provides more stiffness to the structure and controls the overall displacement of the building but at the same time, it results in a rise in the base shear and reduces the natural time period of the building. This issue can be mitigated by employing the base isolator technique which overcomes the ill effects of more stiffness due to the composite diagrid system.
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References 1. Khansefid A (2021) Lifetime risk-based seismic performance assessment of buildings equipped with supplemental damping and base isolation systems under probable mainshock-aftershock scenarios. Structures 34:3647–3666 2. Hayashi K, Fujita K, Tsuji M, Takewaki I (2018) A simple response evaluation method for baseisolation building-connection hybrid structural system under long-period and long-duration ground motion. Front Built Environ 4 3. Chen X, Xiong J (2022) Seismic resilient design with base isolation device using friction pendulum bearing and viscous damper. Soil Dyn Earthq Eng 153 4. Xie Q, Yang Z, He C, Xue S (2019) Seismic performance improvement of a slender composite ultra-high voltage bypass switch using assembled base isolation. Eng Struct 194:320–333 5. Tiwary AK, Gupta AK (2021) Post-fire exposure behavior of circular concrete-filled steel tube column under axial loading. Int J Steel Struct 21(1):52–65 6. Tiwary AK, Gupta AK (2020) Mechanical behavior of circular concrete filled steel tube column under axial loading for sustainable building. J Green Eng 10(11):11116–11132 7. Tiwary AK, Gupta AK (2019) Nonlinear analysis of circular concrete filled steel tube columns under axial loading. Int J Innov Technol Explor Eng 8(12):688–692 8. Bhatia S, Kumar Tiwary A (2021) Concrete filled double skinned tubular columns subjected to different loading conditions. IOP Conf Ser: Earth Environ Sci 889(1) 9. Bhatia S, Tiwary AK (2021) Parametric analysis on behavior of concrete filled steel (single and double skin) tube columns under axial loading. Mater Today Proc 48:1364–1370 10. Shi Q, Cai W, Wang B (2019) Axial cyclic testing of concrete-filled steel tube columns in diagrid structures. Adv Civ Eng 2019 11. Liu C, Li Q, Lu Z, Wu H (2018) A review of the diagrid structural system for tall buildings. Struct Des Tall Spec Build 27(4) 12. Shi Q, Ying Y, Wang B (2021) Experimental investigation on the seismic performance of concrete-filled steel tubular joints in diagrid structures. Structures 31:230–247 13. Shi Q-X, Rong C, Zhang T, Ren H, Zhao D (2016) Analysis on bearing capacity of planar intersecting CFST connection in diagrid structure based on the twin shear unified strength theory. Gongcheng Lixue/Eng Mech 33(8):77–83 14. Udayakumar G, Anil K, Narasimhan MC, George V (eds) (2021) International conference on civil engineering trends and challenges for sustainability, CTCS 2019. Lecture notes in civil engineering, vol 99 15. Wang L, Shi Q, Rong C (2020) Analysis of basic mechanical properties of intersecting connection based on multi-scale model. Xi’an Jianzhu Keji Daxue Xuebao/J Xi’an Univ Archit Technol 52(3):409–415 and 438 16. Chen D, Zha X, Xu P, Li W (2021) Stability of slender concrete-filled steel tubular X-column under axial compression. J Constr Steel Res 185 17. Barakat S (2020) Design of the base isolation system with artificial neural network models. In: ACM international conference proceeding series, pp 79–83 18. Li B, Zhang Y, Yan G, Gu H (2022) Optimal design method for structures with viscous dampers in base isolation layer. Harbin Gongye Daxue Xuebao/J Harbin Inst Technol 54(4):101–110 19. Vu DC, Politopoulos I, Diop S (2018) A new semi-active control based on nonlinear inhomogeneous optimal control for mixed base isolation. Struct Control Health Monit 25(1) 20. Kalantari A (2017) Seismic response reduction in liquid storage tanks by simple smart base isolation systems. Iran J Sci Technol Trans Civ Eng 41(2):121–133 21. Yan B, Xia Y (2018) Base-isolation design of single-tower cable-stayed bridges: A case study in meizoseismal area. J Vibroeng 20(2):1075–1086 22. Sharma S, Tiwary AK (2021) Analysis of multi-story buildings with hybrid shear wall: steel bracing structural system. Innov Infrastruct Solutions 6:160 23. IS 1893-2016 (Part-1) (2016) Criteria for earthquake resistant design of structures, general provisions and buildings. Bureau of Indian Standards, New Delhi
Optimization of Mix Design for Concrete with and without Polypropylene Fibre Shivangi, Priyanka Singh, and Bashar S. Mohammed
Abstract In today’s era, construction is becoming demandable on a remarkably high pace leading to great utilization of underdone materials in concrete mix. While discussing foremost materials used in construction, fine aggregate and coarse aggregate are the materials that are used adequately. In this paper, we will be showering light on use of polypropylene fibres as an admixture in the bare concrete mixture. Many types of research are carried out in concrete using fibres proportions and different grades. This paper reflects the experimental results, demonstrating that the use of this polypropylene fibres in varying percentage (0.5, 1, 1.5, 2%) in M30 grade concrete mix leads to tremendous improvement in various properties of concrete. In this paper, compressive strength of concrete with and without polypropylene fibres at varying percentage has been exhibited for 7 and 28 days curing. The current research work designates the appropriate consumption of polypropylene fibres as a beneficial construction material. Keywords Fibre concrete · Polypropylene fibre · FRPC · Compressive strength · Curing · Workability of concrete · Specific gravity · UTM · Mix design
Shivangi (B) · P. Singh Department of Civil Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Sector-125, Noida, Uttar Pradesh 201313, India e-mail: [email protected] B. S. Mohammed Department of Civil and Environmental Engineering, Faculty of Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_16
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1 Introduction 1.1 Concrete After water, the material which is used widely is concrete. “Concrete is a composite material, which is a mixture of cement, coarse aggregate, fine aggregate and water”. Talking about the properties of concrete, it affects durability and workability [1–8].
1.2 Grade of Concrete Nominal concrete mixes are segregated based on their characteristic’s strength after 28 days of curing; Indian standard also highlights the classification of the concrete based on grade [9–17]. It is measured in MPa. M reflects mix, whereas MPa reflects the overall strength. Various grades of concrete are M15, M20, M25, M30, M35, etc., as per Indian standards [1–24].
1.3 Fibres While considering the properties and characteristics of these fibres as well as other fibre, there are various types of fibres that are added in the mix of concrete to increase various strength of the mix as well as contribute to the improvement of the properties of concrete mix during construction of numerous superstructures. Several types of fibres are “polypropylene, glass, steel, carbon, basalt, fibres”, etc. [25–30]. Fibres are available in different sizes. Figure 1 reflects different types of fibres available in market.
1.4 Polypropylene Fibres By the reason of outstanding mechanical properties polypropylene fibres as shown in Fig. 2 is preferred to enhance the compressive strength of the concrete. It has been experimentally predicted that adding different proportions of polypropylene fibre in concrete mix, consisting of “cement, fine aggregate, coarse aggregate and water”, improved the overall properties of the concrete mixture, leading to better strength of the structure.
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(a) Basalt Fibre
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(b) Glass Fibre
Fig. 1 Various types of fibres Fig. 2 Polypropylene fibres
2 Test Set-Up To carry out the experiment, to reach to the conclusion, the set-up has been done in the laboratory and following arrangement was done. Further Table 1 gives information regarding mix design proportioning for M30 grade concrete with and without fibres which has been considered in this project.
2.1 Concrete Cube Mould To carry out test, cubes are required, for which it needs to be casted in laboratory. There are different sizes of cube moulds available for casting different sizes of cubes, few of them are “(150 × 150 × 150 mm), (100 × 100 × 100 mm) and (50 × 50 × 50 mm)”. In the present set-up, (150 × 150 × 150 mm) cube has been preferred, which has been shown in Fig. 3.
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Table 1 Mix proportion for M30 Grade concrete with and without polypropylene fibre Cement
11.630 kg/m3
Fine aggregate
15.305 kg/m3
Coarse aggregate—10 mm
10.860 kg/m3
Coarse aggregate—20 mm
18.065 kg/m3
Water
06.865
Polypropylene fibre 0.5%
95.800 gm
1.0%
230.000 gm
1.5%
344.817 gm
2.0%
383.130 gm
Fig. 3 150 × 150 × 150 mm size cubes
2.2 Concrete Mix (i) Cement OPC 43 grade cement has been used for the experiment work as shown in Fig. 4, and as per the mix design 11.630 kg has been taken for casting of cubes. (ii) Coarse Aggregate Two sizes of aggregate have been used in M30 grade concrete mix, i.e. 10 mm and 20 mm, as shown in Fig. 5. (iii) Fine Aggregate Fine aggregate shown in Fig. 6 has been used in the mix. (iv) Water Desired amount of water has been used as per mix design proportion as seen in Fig. 7.
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Fig. 4 Cement
(a) 10mm
(b) 20mm
Fig. 5 Coarse aggregate of various sizes Fig. 6 Fine aggregate
(v) Polypropylene Fibre Polypropylene has been added in M30 grade concrete to see the impact on the properties of concrete after 7 and 28 days of curing. It is added in different percentages to know at what percentage best strength can be achieved (Fig. 8).
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Fig. 7 Water
Fig. 8 Polypropylene fibre (24 mm)
2.3 Test Performed After batching, various tests should be performed to know specific gravity as well as workability of concrete mix with and without polypropylene fibres. (i) Pycnometer Method This method has been preferred to know the specific gravity of the fine aggregate, which has been further used while doing mix designing for M30 grade concrete. Figure 9 demonstrates the apparatus pycnometer. Specific gravity achieved was 2.564. (ii) Buoyancy Method This method has been preferred to know the specific gravity of the coarse aggregate, which has been further used while doing mix designing for M30 grade concrete. Figure 10 demonstrates the apparatus pycnometer. Specific gravity achieved was 2.649. (iii) Slump Test This method has been used in the laboratory to know the workability of the mix that has been prepared for M30 grade concrete in the laboratory represented in Fig. 11.
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Fig.9 Pycnometer apparatus
Fig. 10 Buoyancy apparatus
Fig. 11 Slump test
For the M30 concrete with and without fibres has been noted and discussed in Results section.
3 Results 3.1 Workability After preparing M30 grade concrete in mixer, slump test was performed on concrete with and without fibres at different percentage, and slump value has been derived to know the workability of type of concrete as shown in Table 2 and Fig. 12.
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Table 2 Workability of concrete at varying % of polypropylene fibres M30 concrete without fibres M30 concrete with fibres
% of Polypropylene Fibres added
Slump value (mm)
0
65
0.5
60
1.0
55
1.5
40
2.0
35
(a) M30 concrete without fibres
(b) M30 concrete with fibres
Fig. 12 Slump test for workability
3.2 Compressive Strength To determine the compressive strength of M30 grade concrete with and without polypropylene fibre, universal testing machine (UTM) has been used. Compressive strength has been determined after 7 days as well as after 28 days of curing, for which after casting of the cubes that is 3 units for 7 days and 3 units for 28 days, cubes have been placed in the curing tank filled with water (Fig. 13). After 7 and 28 days of curing, it has been taken out and kept in universal testing machine (UTM) to get the desired compressive strength of the designed concrete with and without polypropylene fibres. The specimens have been tested under compression testing machine of 1000 ton capacity. Henceforth, output of compressive strength at different percentage of fibre addition (0, 0.5, 1, 1.5, 2%) is demonstrated in Fig. 14.
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Fig. 13 Sample in UTM
COMPRESSIVE STRENGTH (IN N/MM2)
COMPRESSIVE STRENGTH 35 30 25 20
29.00 22.40
15 10
20.17
21.158
12.70
11.77
14.90 11.21
15.11
0.5%
1%
1.5%
2%
9.89
5 0
0%
% OF POLYPROPYLENE FIBRE 7 DAYS
28 DAYS
Fig. 14 Comparison between compressive strength with different % of fibre
4 Conclusions • M30 grade concrete mix with 0% fibre content (bare concrete), when tested on UTM machine of 1000 ton after 7 days, seems to attain compressive strength of 22.4 N/mm2 , whereas concrete with 0.5, 1, 1.5 and 2% polypropylene fibre attains very low compressive strength of 12.7, 11.77, 11.21 and 9.88 N/mm2 at 7 days of curing and after 28 days of curing, compressive strength of 29.00, 20.17, 21.16, 14.90 and 15.118 N/mm2 was achieved.
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• After 7 days of curing, compressive strength of concrete at varying percentages of polypropylene fibres decreases when compared to bare concrete (0% polypropylene) and was found to be decreasing by 43.30, 47.45, 49.94 and 55.85%. • It was also seen that compressive strength gained at 7 days of curing was very low for M30 grade concrete mix with varying percentage of polypropylene fibre, but when tested after 28 days of curing, drastic increase was noticed in its compressive strength when compared to 7 days of curing. For varying percentages of fibre content in M30 concrete mix, following % of increase were noticed: for 0.5%— 37.03% increase, 1%—44.3% increase, 1.5%—24.8% increase and for 2%— 34.5% increase. • While adding varying amount of polypropylene fibres in M30 grade concrete mix, it was seen that maximum compressive strength was achieved at 1% and minimum compressive strength was achieved at 1.5%. • Despite of adding fibres in concrete at varying percentage, it can be concluded from the experiment which was carried out that the concrete mix with 0% polypropylene fibre has more compressive strength after 28 days of curing. • From now on, when polypropylene fibre is used as an additive, it affect the range of compressive strength by lowering the compressive strength in comparison with the identical conventional concrete mix. The decrease in compressive strength was thought to be caused by the inclusion of the fibres within the cement matrix of the concrete, which, due to their lower bond strength, forms a break in the “CSH bond between cement and surrounding aggregates”. • Thereafter, it can be concluded that M30 grade concrete with polypropylene fibre has low compressive strength, but it is found to be more durable and more economical, so it can be used as a hybrid fibre in combination with some other fibres in order to give more strength to concrete structure.
References 1. Khuc T, Catbas FN (2018) Structural identification using computer vision-based bridge health monitoring. J Struct Eng 144(2):04017202. https://doi.org/10.1061/(asce)st.1943-541x.000 1925 2. Luo L, Feng MQ, Wu ZY (2018) Robust vision sensor for multi-point displacement monitoring of bridges in the field. Eng Struct 163:255–266. https://doi.org/10.1016/j.engstruct.2018.02.014 3. Xu Y, Brownjohn J, Kong D (2018) A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge. Struct Control Health Monit 25(5). https://doi. org/10.1002/stc.2155 4. Acikgoz S, DeJong MJ, Soga K (2018) Sensing dynamic displacements in masonry rail bridges using 2D digital image correlation. Structural Struct Control Health Monit 25(8). https://doi. org/10.1002/stc.2187. 5. Lei B, Wang N, Xu P, Song G (2018) New crack detection method for bridge inspection using UAV incorporating image processing. J Aerosp Eng 31(5):04018058. https://doi.org/10.1061/ (asce)as.1943-5525.0000879
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6. Germanese D, Leone GR, Moroni D, Pascali MA, Tampucci M (2018) Long-term monitoring of crack patterns in historic structures using UAVs and planar markers: a preliminary study. J Imaging 4(8). https://doi.org/10.3390/jimaging4080099 7. Duque L, Asce SM, Seo J, Asce M, Wacker J (2018) Bridge deterioration quantification protocol using UAV. https://doi.org/10.1061/(ASCE)BE.1943 8. Omar T, Nehdi ML (2017) Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography. Autom Constr 83:360–371. https://doi.org/10.1016/j.autcon. 2017.06.024 9. Shrestha A, Dang J, Wang X (2018) Development of a smart-device-based vibrationmeasurement system: effectiveness examination and application cases to existing structure. Struct Control Health Monit 25(3). https://doi.org/10.1002/stc.2120 10. Feldbusch A, Sadegh-Azar H, Agne P (2017) Vibration analysis using mobile devices (smartphones or tablets). Procedia Eng 199:2790–2795. https://doi.org/10.1016/j.proeng.2017. 09.543 11. Ozer E Feng D, Feng MQ (2017) Hybrid motion sensing and experimental modal analysis using collocated smartphone camera and accelerometers. Meas Sci Technol 28(10). https:// doi.org/10.1088/1361-6501/aa82ac 12. Marulanda J, Caicedo JM, Thomson P (2017) Modal identification using mobile sensors under ambient excitation. J Comput Civ Eng 31(2):04016051. https://doi.org/10.1061/(asce)cp.19435487.0000619 13. Zhu D, Guo J, Cho C, Wang Y, Lee KM (2012) A wireless mobile sensor network for the system identification of a space frame bridge. IEEE/ASME Trans Mechatron 14. Velayutham G, Cheah CB (2014) The effects of steel fibre on the mechanical strength and durability of steel fibre reinforced high strength concrete (SFRHSC) subjected to normal and hygrothermal curing. MATEC Web Conf 10. https://doi.org/10.1051/matecconf/20141002004 15. Jagadeesh V (2018) Behaviour of steel fibre reinforced concrete under flexural failure. www. irjet.net 16. Dsouza N, Rajashekhar Swamy HM (2018) Strength and durability aspects of steel fibre reinforced concrete. Int J Civ Eng Technol (IJCIET) 9(7):948–957. Article ID: IJCIET_09_07_ 099. http://iaeme.com/Home/journal/[email protected], http://iaeme.com/Home/ issue/IJCIET?Volume=9&Issue=7, http://iaeme.com/Home/journal/IJCIET949 17. Sathe AP, Patil AV (2013) Experimental investigation on polypropylene fiber reinforced concrete with artificial. Int J Sci Res 4. www.ijsr.net 18. Mohammed BS, Adamu M (2018) Mechanical performance of roller compacted concrete pavement containing crumb rubber and Nano silica. Constr Build Mater 159:234–251. ISSN: 0950-0618 19. Mohammed BS, Khed VC, Liew MS (2018) Optimization of hybrid fibres in engineered cementitious composites. Constr Build Mater 190:24–37. ISSN: 0950-0618 20. Singh P, Tomar R, Agarwal K, Kaushik H, Singh S (2021) Synthesis of carbon fiber composites and different methods to improve its mechanical properties: a comprehensive review. IOP Conf Ser: Earth Environ Sci 889:012013. https://doi.org/10.1088/1755-1315/889/1/012013 21. Singh P, Bhardwaj S, Dixit S, Shaw R, Ghosh A (2021) Development of prediction models to determine compressive strength and workability of sustainable concrete with ANN. https:// doi.org/10.1007/978-981-16-0749-3_59 22. Mohammed BS, Foo WL, Hossain KMA, Abdullahi M (2013) Shear strength of palm oil clinker concrete beams. Mater Des 46:270–276. ISSN: 0261-3069. https://doi.org/10.1016/j. matdes.2012.10.021 23. Haruna S et al (2021) Effect of aggregate-binder proportion and curing technique on the strength and water absorption of fly ash-based one-part geopolymer mortars. IOP Conf Ser: Mater Sci Eng 1101. In: The 13th international UNIMAS engineering conference 2020 (ENCON 2020), Kuching, Malaysia 24. Mohammed BS, Aswin M, Liew MS et al (2019) Structural performance of RC and R-ECC dapped-end beams based on the role of hanger or diagonal reinforcements combined by ECC. Int J Concr Struct Mater 13:44. https://doi.org/10.1186/s40069-019-0356-x
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25. Mohammed BS, Haruna S, Abdul Wahab MMB, Liew MS (2019) Optimization and characterization of cast in-situ alkali-activated pastes by response surface methodology. Constr Build Mater 225:776–787. ISSN: 0950-0618 26. Singh P, Bhardwaj S., Dixit S, Shaw RN, Ghosh A (2021) Development of prediction models to determine compressive strength and workability of sustainable concrete with ANN. In: Mekhilef S, Favorskaya M, Pandey RK, Shaw RN (eds) Innovations in electrical and electronic engineering. Lecture notes in electrical engineering, vol 756. Springer, Singapore. https://doi. org/10.1007/978-981-16-0749-3_59 27. Garg C, Namdeo A, Singhal A, Singh P, Shaw RN, Ghosh A (2022) Adaptive fuzzy logic models for the prediction of compressive strength of sustainable concrete. In: Bianchini M, Piuri V, Das S, Shaw RN (eds) Advanced computing and intelligent technologies. Lecture notes in networks and systems, vol 218. Springer, Singapore. https://doi.org/10.1007/978-98116-2164-2_47 28. Singh P, Ahmad UF, Yadav S (2020) Structural health monitoring and damage detection through machine learning approaches. E3S Web Conf 220:01096. EDP Sciences 29. Singh P et al. (2023) Comparative study of concrete cylinders confined using natural and artificial fibre reinforced polymers. In: Prakash C, Singh S, Krolczyk G (eds) Advances in functional and smart materials. Lecture notes in mechanical engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-4147-4_8 30. Rahman I, Singh P, Dev N, Arif M, Yusufi FNK, Azam A, Alam MM et al. (2022) Improvements in the engineering properties of cementitious composites using nano-sized cement and nanosized additives. Materials 15(22):8066
Use of Stone Dust and Ceramic Waste in Fine Aggregate Replacement in RAC Kuldeep Soni, Shashank Gupta, and Aditya Sharma
Abstract Concrete comes 2nd highest usable material in the construction industry. Conventional fine aggregate leads to the mining of rivers and natural resource depletion. Fine and coarse aggregates are chemically inert; therefore, replacement of aggregate is possible with other inert materials that possess the same mechanical properties which fullfill the need for strength and durability criteria of concrete. Ceramic waste and stone dust are industrial waste having very limited utilization in the construction industry. Ceramic waste is also a large element of c&d waste produce by porcelain from material building demolition In this research, complete replacement of conventional fine aggregate is done with stone dust and then replacement of stone dust with ceramic waste is done as 10, 15, 20, and 25% by weight, to check the potential of stone dust and ceramic waste in complete replacement of conventional fine aggregate on the bases of durability and strength test, replacement of stone dust (SD) by ceramic waste (CW) leads to the increment in the compressive strength up to the optimum value of replacement as 20%. At the point of optimum replacement of stone dust with ceramic waste compressive strength is an increment of a maximum of 16.30%. Keywords RAC—Recycled aggregate concrete · RA—Recycled aggregate · CW—Ceramic waste · SD—Stone dust · RAC—Recycled aggregate concrete
1 Introduction The construction industry is based on concrete structures; in other words, concrete is playing a very important role in modern construction. It is a homogenous compound of coarse aggregate, fine aggregate, and cement [1]. Elements of conventional concrete—Conventional concrete made up of conventional materials such as stone chunks are used as coarse aggregate [2, 3], the coarse aggregate imparts strength to the concrete mixture, and river sand used as the fine aggregate used to fill the voids of K. Soni (B) · S. Gupta · A. Sharma Civil Department, ITM University, Gwalior, Mathya Pradesh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_17
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coarse aggregate and make the homogenous mix. Binder materials like cement and lime are used to bind this mix by filling the voids of fine aggregate, and water make a chemical combination with cement and binds the complete concrete matrix [1]. Need for sustainability in construction—sustainability is to fullfill the present need without compromising future needs, but continuing overgrazing of natural resources can be a big threat to construction sustainability so the construction industry facing many challenges to achieving sustainability [4]. Building scrap comprises numerous kind of strong squander like broken concrete from pieces of pillars and columns, broken chunks of bricks from stonework, wooden squander, ceramic squander, etc. Ceramic squander is broad categories as ruddy glue ceramic squander and white glue ceramic squanders (paste) [5–10]. In ruddy glue ceramic squander comprises fabric as brick tile and brunt clay military, and white glue ceramic squander comprises porcelain fabric like a china clay material [11–13]. Ceramic waste can be a great choice to supplant routine fine aggregate due to its inactive nature, less water assimilation, and great particular gravity [14, 15]. This consideration comprises of test investigation of customary fine total substitution with 100% stone dust; at that point, stone dust is somewhat substitution by ceramic waste as 10, 15, 20, and 25% for quality and toughness analysis. Strength examination is done with compressive as well as flexure quality test and workability test performed by slump cone workability test on a test of M25 concrete.
2 Methodology This research is an experimental approach; in this study, complete replacement of conventional fine aggregate with stone dust and ceramic waste is done. This study is done in two stages: in the first stage, conventional aggregate replacement is done with stone dust completely, and in the next stage, stone dust replacement with ceramic waste is done partially at 0, 10, 15, 20, and 25%.
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Control sample with conventional Agg.
Concrete samples produce by replacement ofifine aggregate with CERAMIC WASTE and STONE DUST
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Sample with stone dust.
Comparison of properties
Optimum % of CERAMIC WASTE and STONE DUST
Cement—For this study, PPC (Pozzolana Portland cement is used), it consists of 15–35% of pozzolanic material and approximate 4% of gypsum, cement is tested for consistency, setting time (initial setting time and final setting time) to choose appropriate cement for this experimental work. Conventional FA (fine aggregate)— Conventional fine aggregate is used as river sand (Sindh river sand) of Zone-II, and fine aggregate is tested for water absorption, and fineness modulus test. Stone dust—Appropriate stone dust is used and taken from local stone vendors. Ceramic waste—Ceramic waste is achieved by broken tiles and other porcelain materials. CA (Coarse aggregate)—20 mm granite stone. Nomenclature of the Samples Nomenclature of the concrete samples is done in the format of RC-CN, where RC implies recycled aggregate concrete, and CN represent the ceramic waste percentage (Table 1).
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Table 1 Sampling of cubes
RC-0 (control) Recycled aggregate concrete zero replacement RC-C0
100% stone dust + 0% Ceramic waste
RC-C10
90% of Stone dust + 10% ceramic waste
RCA-C15
85% stone dust + 15% ceramic waste
RC-C20
80% stone dust + 20% ceramic waste
RC-C25
75% stone dust + 25% ceramic waste
Concrete Design Specification The design of concrete is done as per IS 10262:2019 (Standard IS code for concrete mix design), M 25 concrete is used in this experimental analysis which a character strength is 25 MPa and target mean strength is 31.6 MPa. Found the ratio of cement(binder): FA: CA as 1:1.58:2.95.
Specification and size of sample1For compressive strength test 150x150x150mm Form is utilized and 3 example(sample) of each test taken.
3 Results 1. Fresh Concrete Workability—workability analysis is done with slump cone apparatus, procedure as per IS code prescription (Table 2). Graph of workability is in decreasing trend as shown in Fig. 1 Table 2 Slump value
Name of sample
Slump value (mm)
RC-0
38
RC-C0
35
RC-C10
34
RC-C15
32
RC-C20
30
RC-C25
28
Use of Stone Dust and Ceramic Waste in Fine Aggregate Replacement …
Slump Valuein mm
40 35
35
207 38
34
32
30
30
28
25 20 15 10 5 0
0%
10%
15%
20%
25%
%Replacement of Ceramic Powder
RACS0
Fig. 1 Slump value of concrete mix
40 35
34.44
36.11 33.6
36.66
36.71 34.37
30 25 20 14 Days 15
28 days
10 5 0
Fig. 2 Compressive strength of cubes
Maximum can achieve in the conventional aggregate where slump is dropping with concern to the addition of ceramic waste. Hard Concrete Test—Compressive strength test is performed on the sample of 14 day as well as 28 days samples, results are as follows (Fig. 2; Table 3).
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Table 3 Strength of sample Name of sample
Compressive-strength (N/mm2 )
Compressive-strength (N/mm2 )
14 Days
28 days
RAC-0
31.00
34.44
RAC-C0
30.24
33.6
RAC-C10
32.50
36.11
RAC-C15
33.00
36.66
RAC-C20
33.04
36.71
RAC-C25
30.94
34.37
The maximum value of strength is achieved on 20% replacement of stone dust with ceramic waste.
4 Conclusion The use of stone dust and ceramic waste has great potential to replace the conventional fine aggregate. This replacement shows three directional boons to the society and helps to achieve a sustainable future in the construction industry as an alternative to conventional fine aggregate leads the protecting and saving the natural resources of conventional fine aggregates, it control solid waste accumulation due to c&d waste, and future alternative material, or we can say gives derived material. Complete replacement of stone dust makes concrete a little stiff and weak due to decrement of slump value by 3 mm and a drop in compressive strength by 2.42%, but these values are comes under the permissible values; therefore, complete replacement of conventional sand can be possible with stone dust. Replacement of stone dust (SD) by ceramic waste (CW) leads to the increment in the compressive strength up to the optimum value of replacement as 20%. At the point of optimum replacement of stone dust with ceramic waste compressive strength is an increment of a maximum of 16.30%. But the workability of the concrete is decreasing with the ceramic waste increment in the concrete. The workability of the concrete lies between 25 and 50 mm; therefore, this concrete is recommended for mass concreting work with vibration. Workability drops in concern of increment of ceramic waste; therefore, this replacement cannot be possible in self-compacting concrete (SCC). The optimum value of ceramic waste is achieved by 20% with stone dust. In recycled concrete, complete replacement of conventional fine aggregate by stone dust and ceramic waste is possible to achieve strength as per mix design. In recycled aggregate concrete optimum ratio of stone dust to ceramic waste is 4:1. This research work conclude as there is good potential of the ceramic waste as a conventional fine aggregate and stone in concrete production (upto 20%).
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References 1. IS10262:2019. https://civiconcepts.com/wp-content/uploads/2020/11/4.IS-10262-2019-NewMix-design.pdf 2. International energy outlook 2007 with projections to 2020. https://www.osti.gov/biblio/129 6780 3. Rajpoot SPS (2018) An experimental study on crushed stone dust as fine aggregate in cement concrete. Mater Today: Proc 5:17540–17547 4. Sharma A, Tiwari A (2020) Recycled course aggregate concrete application for sustainable construction 5. Awoyera PO, Akinimusuru JO, Ndambuki JM (2016) Green concrete production with ceramic wastes and laterite. Constr Build Mater 117:29–36 6. Aly ST, Kanaan DM, El-Dieb AS, Abu-Eishah SI (2018) Properties of ceramic waste powder based geopolymer concrete. https://www.researchgate.net/publication/324269010 7. Bismark K, Meisuh C, Kankam T, Buabin K (2018) Case study effect of quarry rock dust on the flexural strength of concrete. Case Stud Constr Mater 8:16–22 8. Bonavetti VL, Irassar EF (1994) The effect of stone dust content in sand. Cem Concr Res 24(3):580–590 9. Wahab GMA, Gouda M, Ibrahim G (2019) Study of physical and mechanical properties for some of Eastern Desert dimension marble and granite utilized in building decoration. Ain Shams Eng J 129:291–300 10. Guideline of environmental management of construction and demolition waste (March 2017). https://cpcb.nic.in/openpdffile.php?id=TGF0ZXN0RmlsZS8xNTlfMTQ5NTQ0NjM5N19t ZWRpYXBob3RvMTkyLnBkZg 11. Lasseuguette E, Burns S, Simmons D, Francis EH, Chai HK, Koutsos V, Huang Y (2019) Chemical, microstructural and mechanical properties of ceramic waste blended cementitious systems. J Cleaner Prod 211:1228–1238 12. Nayana AM, Rakesh P (2018) Strength and durability study on cement mortar with ceramic waste and micro-silica. Mater Today: Proc 5:24780–24791 13. Senthamarai RM, Manoharan PD, Gobinath D (2011) Concrete made from ceramic industry waste: durability properties. Constr Build Mater 25:2413–2419 14. Zareei SA, Ameri F, Bahrami N, Shoaei P, Musaeei HR, Nurian F (2019) Green high strength concrete containing recycled waste ceramic aggregates and waste carpet fibers: mechanical, durability, and microstructural properties. J Build Eng 26:900–914 15. Wahab GMA, Gouda M, Ibrahim G (2019) Study of physical and mechanical properties for some of eastern desert dimension marble and granite utilized in building decoration. Ain Shams Eng J 10:907–915
Prediction of Strength and Stiffness Behavior of Glass Powder Stabilized Expansive Clay Using ANN Principles Shaik Subhan Alisha, T. V. Nagaraju, Kennedy C. Onyelowe, Venkateswarulu Dumpa, and Mantena Sireesha
Abstract In recent years, chemical and industrial by-products have been utilized to enhance expansive clays’ strength and stiffness behavior. Moreover, due to the carbon footprint concern and economic aspects, binary and ternary mixes of additives were emerging to meet the engineers’ requirements. This study used three different additives, glass powder, NaCl, and pond ash, to understand the unconfined compressive strength (UCS) and California bearing ratio (CBR) of the expansive blended clays. From test results, it was found that the addition of additives improved both UCS and CBR values of blended clays. This paper also explores the application of artificial neural networks (ANN) to predict UCS and CBR values of blended clays. The database was considered for developing the ANN model, including input layers (additives composition, plasticity characteristics, and compaction characteristics), hidden layers, and output layers (UCS and CBR). The prediction models show higher performance with correlation coefficients of 0.986 and 0.980, respectively. ANN model shows better performance and is an effective tool for the prediction of time-consuming variables in the field of civil engineering. Keywords ANN · Glass powder · Expansive clays · Soft computing
S. S. Alisha Department of Civil Engineering, Vishnu Institute of Technology, Bhimavaram, India T. V. Nagaraju (B) Department of Civil Engineering, S.R.K.R Engineering College, Bhimavaram, India e-mail: [email protected] K. C. Onyelowe Department of Civil Engineering, Michael Okpara University of Agriculture, Umudike, Nigeria V. Dumpa Department of Civil Engineering, Godavari Institute of Engineering, Rajahmundry, India M. Sireesha Department of Geo-Engineering, Andhra University, Visakhapatnam, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_18
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1 Introduction Expansive clays, an abundant deposit found worldwide, challenge engineers and researchers with their unique complex swell–shrink phenomenon [1]. Moreover, it is prone to severe cracks in structural elements lying on these deposits, resulting in tantamount financial loss. Numerous chemical and industrial by-products have been utilized to counteract the swell–shrink behavior of clays [2, 3]. However, nowadays, many additives are cost intensive due to their adequate demand. So, binary and ternary mixes of additive selection play an essential role in the chemical amelioration of expansive clays. The swelling phenomenon of clays was totally connected with the presence of chemical constituents in the clays (Mg2+ , Ca2+ , and Na+ ) and additives (Si2+ , Al+3 , and Mg2+ ) [4]. In this regard, even though expansive clay’s problems and mitigations are well addressed, still complex behaviors of stabilized clays are attention seekers for both the research and engineering fraternity. Strength and economic aspects are a significant concern in soil stabilization when volume change allows in the expansive clays. Chemical and pozzolanic additives endure cation exchange between particles, reduce double diffusion layer thickness, and control the volume change behavior of clays [4]. Fly ash and pond ash are fine particle residues from coal burning in the thermal plant. Fly ash has great demand than pond ash due to the higher surface area and potential chemical constituents (silica and alumina) [5]. Fly ash has recently been expensive due to its desirable properties and great demand. So, pond ash is viable for improving chemical constituents in the blend by economizing the overall blend [5, 6]. On the other hand, the glass industry is facing difficulties in recycling used and broken glasses due to the expensive process. In India, 21 billion tons of broken glass or glass waste were generated in 2019, in which only 45% of the waste was recycled [7]. So, glass material having dominant silica in amorphous form has good benefits in soil stabilization and concrete. The ground glass powder exhibits higher surface area, higher volume stability, and rich amorphous SiO2 (greater than 70% content). To date, glass powder has been utilized in soil stabilization, admixture in concrete, additive in bricks, and as an additive in pavement asphalt [8, 9]. In this regard, Zamin et al. [8] reported the influence of glass powder on the swelling phenomenon of clays. It is suggested that 20% glass powder can be utilized to minimize swelling and improve the blend’s density [8]. Baldovino et al. [9] reported that no hazardous elements were found in the chemical analysis of glass powder. Moreover, silica, calcium, magnesium, and sodium were found. These constituents contribute to effective pozzolanic reaction in the blended clays [9]. Ashiq et al. [10] reported that adding glass powder to the clay improves UCS and CBR values of 110% and 300%, respectively. Moreover, using glass powder could reduce the capital cost of up to 19% in constructing a two-way pavement of one kilometer [10]. The sodium and calcium ions influenced the swell–shrink and strength behavior of expansive clays. The addition of sodium chloride (NaCl) benefits the effective cation exchange in the blended clays. NaCl is a cheap material compared to other chemical additives and one of the successful chemical additives in altering clay properties [11].
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Sumalatha [11] and Prudhvi and Chellaiah [12] reported that plasticity and strength behavior were significantly improved with the addition of salts [11, 12]. Combining chemical additives and wastes for soil stabilization, the binary and ternary can bring desirable properties and low-cost blends compared to single additive usage. Understanding and determining the mechanical tests were difficult. So, many mathematical regression approaches and algorithms were successfully used. However, traditional regression analysis was based on simplified assumptions resulting in divergent simulations and higher errors. This study used a ternary blend with pond ash, NaCl, and glass powder to evaluate plasticity, differential free swell index (DFSI), compaction characteristics, UCS, and CBR tests. Further, based on the experimental database, the predictive ANN model was used to estimate UCS and CBR values of ternary blended expansive clays.
2 Dataset Preparation In this study, three additives and expansive clay were considered to perform series of experiments such as liquid limit (LL), plastic limit (PL), differential free swell index (DFSI), optimum moisture content (OMC), maximum dry density (MDD), CBR, and UCS of the blended clays with varying glass powder, NaCl, and pond ash. Strength and stiffness tests were conducted based on the standard codes ASTM D5102-09 and ASTM D1883-16, respectively. Artificial neural networks (ANN) are widely used in engineering to develop mathematical modeling with ease and higher performance. ANN works with the help of rational processing neurons to search the best global solution. Wide varieties of ANN models were in practice in which the feed-forward approach is the simple tool to solve linear regression problems. In recent years, ANN has been gaining importance in the field of materials optimization (both soils and concrete) [13]. An adequate database is required for any ANN prediction model to develop a high-performance model. In this study, glass powder content, NaCl content, pond ash content, liquid limit (LL), plastic limit (PL), free swell index (FSI), optimum moisture content, and maximum dry density were considered as input layers to predict UCS and CBR. Based on the normalized importance of the input variables, glass powder and NaCl contents exhibit relatively high to predict UCS and CBR. Figures 1 and 2 show the schematic view of the ANN model and sensitivity behavior of the input variables, respectively.
3 Effect of Ternary Additives on Expansive Clays Table 1 shows the effect of additives on the properties of expansive clays. Table 1 shows the influence of ternary additives such as X1 (2% glass powder, 3% NaCl, and 5% pond ash), X2 (4% glass powder, 6% NaCl, and 10% pond ash), X3 (6% glass powder, 9% NaCl, and 15% pond ash), and X4 (8% glass powder, 12%
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Fig. 1 Schematic view of ANN layers
Fig. 2 Sensitivity analysis Table 1 Effect of ternary additives on properties of expansive clay Quantity, %
Liquid limit, %
Plastic limit, %
Free swell index, %
Optimum moisture content, %
Maximum dry density, g/cc
CBR, %
UCS, mPa
0
50.4
33.3
110
21.1
1.34
1.83
1.23
X1
50
34.7
92
18.3
1.56
4.23
1.49
X2
47.8
35.3
87
16.7
1.59
7.76
2.18
X3
42.6
39.5
67
15.5
1.62
8.84
2.48
X4
41.9
40.2
52
14.2
1.75
10.24
2.77
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NaCl, and 20% pond ash) on the properties of expansive clays. DFSI and consistency limits were improved with increasing percentages of additives. Adding NaCl, pond ash, and glass powder contributes to effective cation exchange (with the help of Na+ ions in the NaCl and Ca+2 ions in the pond ash) and pozzolanic reaction (due to rich amorphous silica in the glass powder). Compaction characteristics, UCS, and CBR values show that increasing the ternary additives in the blend enhances the blended clay behavior. The amorphous silica of glass powder in the blend offers higher shearing resistance and stiffness due to their effective interlock between the cementitious products (C-S-H and C-A-H).
4 CBR and UCS Prediction Model Using ANN In this study, input and output layers were considered, as mentioned in the earlier section. The layers were connected by neurons (elements). Each element was processed with an input layer and hidden layer and generated the best output signal with the help of the transfer function. The database was divided into training (70%) and testing (30%) to validate the prediction performance. Moreover, the selection of input layers and the learning process of hidden layer neurons decide the effectiveness of the prediction model. Figure 3 shows the distribution characteristics of input variables, which measure the consistency of the variables during the training process. Figure 4 shows the distribution of the output variables. The frequencies in the UCS and CBR model of output variables exhibit the higher performance of the processing neurons in the ANN structure. The ideal train-to-test proportion for measuring soil stiffness and strength was chosen using an ANN model to assess the impact of various factors on the effectiveness of prediction models. Next, eight parameters were chosen using trial-and-error experiments to train the model, which was an ANN in this study. In essence, supervised learning was used to build the model, and testing information was used to evaluate the model’s ability to forecast. Finally, employing correlation coefficient to measure how well the ANN model performed on various proportion training and testing datasets. Figures 5 and 6 show the plots between the predicted and measured values of CBR and UCS, respectively. The plots show the higher R2 values with the CBR model of 0.980 and the UCS model of 0.986, indicating the higher prediction performance of the ANN model. The regression values indicate higher accuracy and can solve inverse problems with varying additives in the blended clays.
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Fig. 3 Distribution characteristics of input variables histograms
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Fig. 4 Distribution characteristics of output variables histograms
Fig. 5 CBR model using ANN
5 Conclusions For the current research work, series of experiments were carried out to strength and stiffness behavior of expansive clays blended with ternary additives. Further, the strength and stiffness of the blends were predicted with the ANN tool based on the experimental data. The findings from both experimental and prediction models are summarized below: 1. The plasticity characteristics obtained showed that LL, PL, and PI were improved by adding glass powder, NaCl, and pond ash to the blends. A similar phenomenon was observed in the compaction characteristics, UCS, and CBR results.
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Fig. 6 UCS model using ANN
2. The ternary blended expansive clays with 8% glass powder, 12% NaCl, and 20% pond ash exhibit higher strength and stiffness. Hence, ternary blended mixes give adequate strength and stiffness with low-cost additives. So, a proper selection of additives could reduce the project cost. 3. The strength and stiffness prediction using the ANN tool revealed higher efficiency with best correlation coefficients of 0.986 and 0.980, respectively. It is also found that glass powder and NaCl content significantly affect the UCS and CBR estimation based on the normalized importance. Prediction results could be helpful to the selection of proportions in the ternary blends.
References 1. Vamsi Nagaraju T, Satyanarayana PVV (2019) Geotechnical aspects of various constructions along the canal embankment using rice husk ash as stabilizer. In: Ground improvement techniques and geosynthetics. Springer, Singapore, pp 143–150 2. Aziz M, Sheikh FN, Qureshi MU, Rasool AM, Irfan M (2021) Experimental study on endurance performance of lime and cement-treated cohesive soil. KSCE J Civ Eng 25(9):3306–3318 3. Xu B, Yi Y (2021) Soft clay stabilization using three industry byproducts. J Mater Civ Eng 33(5):06021002 4. Yi Y, Gu L, Liu S (2015) Microstructural and mechanical properties of marine soft clay stabilized by lime-activated ground granulated blastfurnace slag. Appl Clay Sci 103:71–76 5. Varma N, Kumar T, Nagaraju V (2021) Compressive strength of high plastic clay stabilized with fly ash-based geopolymer and its synthesis parameters. In: Transportation, water and environmental geotechnics. Springer, Singapore, pp 25–37 6. Jakka RS, Ramana GV, Datta M (2010) Shear behaviour of loose and compacted pond ash. Geotech Geol Eng 28(6):763–778 7. De S, Debnath B (2016) Prevalence of health hazards associated with solid waste disposal—a case study of Kolkata, India. Procedia Environ Sci 35:201–208
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8. Zamin B, Nasir H, Khan BJ, Farooq A (2021) Effect of waste glass powder on the swelling and strength characteristic of District Karak expansive clay. Sir Syed Univ Res J Eng Technol 11(2) 9. Baldovino JJ, Izzo RL, Rose JL, Domingos MD (2021) Strength, durability, and microstructure of geopolymers based on recycled-glass powder waste and dolomitic lime for soil stabilization. Constr Build Mater 271:121874 10. Ashiq SZ, Akbar A, Farooq K, Mujtaba H (2022) Sustainable improvement in engineering behavior of Siwalik Clay using industrial waste glass powder as additive. Case Stud Constr Mater 16:e00883 11. Sumalatha J (2021) Bearing capacity and settlement analysis of black cotton soil amended with rubber powder using the GEO5 Software Tool. In: Advances in sustainable construction materials. Springer, Singapore, pp 291–302 12. Prudhvi M, Chellaiah G (2022) Comparative analysis of utilization of salts for stabilization of black cotton soil. In: Earthquake geotechnics. Springer, Singapore, pp 189–194 13. Nagaraju TV, Gobinath R, Awoyera P, Abdy Sayyed MAH (2021) Prediction of California bearing ratio of subgrade soils using artificial neural network principles. In: Communication and intelligent systems. Springer, Singapore, pp 133–146
Landslide Hazard Zonation Mapping of Champhai District of Mizoram, India Lalramngheta, A. Kumar , S. Dangayach , and D. Raj
Abstract Landslide hazard zonation is a method to assess the risk where there is a capacity for landslides. It is a technique in which an area is classified into different zones, and each zone is demonstrating the level of risk in that area. The demonstration of the area in zones is carried out by considering different causative factors and by giving weightage on how much influence they could be responsible for landslides. The study area Champhai, being a hilly terrain, is prone to landslides. A number of landslides are reported every year from various localities. These cause a lot of problem to public resulting in loss of life and property, blockage of roads, and disrupting communication network and also cause economic burden to society. The aim of this study is to prepare landslide hazard zonation (LHZ) map of Champhai district by following the steps and guidelines provided in IS 14496 (Part 2): 1998 (Anon in Bureau of Indian Standard, preparation of landslide hazard zonation maps in mountainous terrains guidelines, part 2 Macro-zonation, IS 1449, 1998). The methods in this study comprise identifying important causative factors such as slope morphometry, relative relief, land use land cover, and hydrological condition of the study area with the help of aerial photographs, satellite imageries, and toposheets. The map is then prepared with these causative factors for the study area Champhai by dividing it into four different areas of RD Blocks, and map is prepared for each block separately. Keywords Hazard zonation · Landslides · Mapping · Champhai district · ArcGIS
Lalramngheta · S. Dangayach · D. Raj (B) Department of Civil Engineering, MNIT Jaipur, Jaipur 302017, India e-mail: [email protected] A. Kumar Department of Civil Engineering, NIT Kurukshetra, Kurukshetra 136119, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_19
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1 Introduction Landslides, in general, are the most common disaster which affect the hilly areas [1– 5]. They are the most commonly occurring geological hazards in the world, causing serious damage to property and infrastructure, socioeconomic losses, and loss of human lives [6–8]. There are many factors which cause landslides, but the three most dominant attributes that contribute to their occurrence are Geology, Morphology, and Human activity. The State of Mizoram is prone to landslides because of its relatively young topography, active movement of its tectonic plates, and delicate geologic base. The geographical location of Mizoram is also subject to various climatic features like monsoons and tropical storms or cyclones. In recent years, improper planning and development of settlements and increase in population residing on slopes or areas with high risk of mass movement increase the vulnerability for landslides [9, 10].
2 Study Area 2.1 Location of Study Area The study area for this thesis is the Champhai district in Mizoram (see Fig. 1). Like other districts of the state, it is characterized by hilly terrain, steep slope, and high relief with complex structural dispositions and is considered geologically young. It is, therefore, prone to natural disasters such as landslides. Therefore, the study of landslides and preparation of landslide hazard zonation mapping is necessary to assess susceptibility and to mitigate loss of life and property for future events.
Fig. 1 Location map and RD blocks of Champhai district
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2.2 Site Investigation Administratively, Champhai district is divided into 4 blocks, namely Champhai RD Block, Khawzawl RD Block, Ngopa RD Block, and Khawbung RD Block (see Fig. 1).
2.3 Landslide Hazard Zonation Landslide hazard zonation is the separation of an area into different regions and providing these regions with rankings based on different factors related to the likelihood and occurrence of landslides. Landslide hazard zonation map displays an area with different hazard classes. There are two ways to approach landslide hazard zonation mapping: macro zonation and regional zonation. Macro-zonation is carried out by studying a smaller parcel of land as compared to regional zonation, which is carried out by studying a larger area such as districts or states. In this study, regional zonation is used.
3 Methodology The groundwork of landslide hazard zonation map in this study is done with the help of ArcGIS software. Each causative factor has a different set of steps for processing of data. The factors considered are land use land cover, slope morphometry, and relative relief. The relative weights assigned to each factor are based on previous studies of similar nature.
3.1 Landslide Use Land Cover (LULC) Any area having a better coverage of vegetation in land use and land cover (LULC) patterns is less vulnerable to landslides. This is because the root system of vegetation provides shear strength to the soil by holding it together. There is a lower probability of landslide or soil erosion in forest cover area, as it prevents denudation over the slopes. The empty and sporadically vegetated regions are prone to quicker erosion, resulting in more unstable slopes. The LULC was assembled into four groups in the Champhai region: settlement, agriculture, thick forest, and moderately thick forest [5]. The land cover was interpreted in ArcGIS software from LANDSAT 8 Satellite data. Table 1 shows the metadata of the satellite image as obtained from the LANDSAT 8, for the Champhai region. Image classification is a process of converting multiple-band raster imagery into a single-band imagery and provides classification into different categories based on
224 Table 1 Metadata of satellite image
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Data set attribute
Attribute value
Date acquired
20/4/2021
WRS path
135
WRS row
044
Day/night indicator
Day
Land cloud cover
0.77
Ground control points model
837
UTM zone
46
various land cover types. Classification of multiband raster image is of two types: supervised classification and unsupervised classification. The supervised classification is a technique of classifying image by obtaining reflectance values (also called spectral signature) from the training samples. These training samples are the polygons or circles which are drawn on the image for each separate class of the land cover. These samples are grouped into one class to create a signature file. The process is done with maximum likelihood classification on image using a signature file. LANDSAT Bands. The LANDSAT raster data contains several bands. Table 2 shows the description for each of the different bands. Color Band Combination. A LANDSAT 8 image shows several color bands. Information is extracted from these images by arranging the color bands, as shown in Table 3. Some of the popular band combinations are color infrared, natural color, and short-wave infrared (www. gisgeography.com). Table 2 LANDSAT bands
Landsat TM bands Type of energy
Wavelength (micrometers)
Spatial resolution (meters)
TM band number
Visible Blue
0.45 to 0.52
30
Band 1
Visible Green
0.52 to 0.60
30
Band 2
Visible Red
0.63 to 0.69
30
Band 3
Near Infrared
0.76 to 0.90
30
Band 4
Mid-Infrared
1.55 to 1.75
30
Band 5
Mid-Infrared
2.08 to 2.35
30
Band 7
Thermal Infrared
10.4 to 12.5
120
Band 6
Panchromatic
0.52 to 0.90
15
Band 8
Source https://mgimond.github.io/ArcGIS_tutorials/Image_classi fication.htm
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Table 3 Color band combinations for image classification Combinations of bands
Results
Natural color (4-3-2)
• • • •
Color infrared (5-4-3)
• Red color is healthy vegetation • Dark areas represent water body • Settlements are white in color
Healthy vegetation is green Brown color represents unhealthy vegetation Settlement is white and gray Dark blue or black means water body
Short-wave infrared (7-6-4) • Dark green means thick vegetation while light green color is sparse vegetation • Settlements are blue and various shades of brown are soils
3.2 Relative Relief Relative relief is the difference in elevation between the top and the bottom of the slope in an individual facet, measured in the direction of slope [9]. For landslide hazards, every relative relief is categorized into any of the three different zones: low hazard zone, medium hazard zone, and high hazard zone [5]. For the preparation of the relative relief map, digital elevation model (DEM) of the study area is first clipped out from the base DEM image downloaded from USGS Earth Explorer. First, a Fishnet Tool is used to create a number of grids on the study area so that the relative relief is calculated in each grid separately. The desired value of width and height of cell size and number of rows and columns are utilized for the creation of these grids with the Fishnet tool. After classification and processing of the properties, relative relief map was prepared separately for each RD Block of our study area. The different colors in the prepared maps Fig. 2(a–d) indicate the difference in the value of ranges of each grid. The higher ranges (more than 300 m) are shown in red color, the medium ranges (100 m to 300 m) are shown in brown color and the lower range (less than 100 m) is shown in yellow color.
3.3 Slope Morphometry Slope morphometry is the representation of different classes or categories of slopes based on the rate of incidence of the slope in terms of angle. For the preparation of slope morphometry map, the topographical map is divided into a number of small sections based on the same positioning of contour lines. These contour lines have same spaced per unit of horizontal distance. In this study, five slope classes were used to characterize the slopes [5], as shown in Table 4. The risk of landslides naturally has a high dependency on the slope morphometry.
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Fig. 2 Relative relief map of a Champhai RD block, b Khawbung RD block, c Khawzawl RD block, d Ngopa RD block
Landslide Hazard Zonation Mapping of Champhai District of Mizoram … Table 4 Description of results from slope map
Angle of slope (in degrees)
Description
227
Risk classification
> 45
Escarpment/Cliff
Very high risk
36–45
Steep slope
High risk
26–35
Moderately steep slope
Moderately high risk
16–25
Mild slope
Low risk
< 15
Very mild slope
No risk
3.4 Hydrology Analysis The hydrological analysis of an area is carried out with Hydrology Toolset in ArcGIS Software. This process gives us information about the earth’s surface such as flow direction of water, where it starts to flow, and where it ends. This analysis helps in extracting information about the hydrological condition from DEM image. It explains about the nature of water movement on the surface area and gives concepts about drainage system. The tools used in this study to create stream features network are shown in Table 5. Figure 3a–d show the maps of each block level of the study area, highlighting the areas having high risk of landslides based on slope morphometry. Figure 4a–d show the output maps from ArcGIS using the Stream to Features tool. Table 5 Description of tools used in preparation of stream features map Tools
Description
Fill
Removing the minor flaws in the data by filling sinks in a surface
Flow Accumulation
The accumulated flow is calculated for each cell
Flow Direction
Generates the direction of flow from each cell to its steepest down slope neighbor
Stream Link
Allocates distinctive rates to units of raster linear network between intersections
Stream Order
Allocates numeric order to sections of raster signifying a division of a linear network
Stream to Features Changes a raster signifying linear network to features representing the linear network
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Fig. 3 Slope map of a Champhai RD block, b Khawbung RD block, c Khawzawl RD block, d Ngopa RD block
Landslide Hazard Zonation Mapping of Champhai District of Mizoram …
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Fig. 4 Stream features map of a Champhai RD block, b Khawbung RD block, c Khawzawl RD block, d Ngopa RD block
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4 Results and Discussion For the preparation of our final output of landslide hazard zonation mapping, the maps which are already prepared with different factors are combined together with the help of Weighted Overlay Tool in ArcGIS software. In this process, the prepared maps depicting the LULC, relative relief maps Fig. 2a–d, slope morphometry maps Fig. 3a–d, and stream features maps Fig. 4a–d are considered with the addition of the road map of the area. The road map shape file (see Fig. 5) of the study area is downloaded from data prepared by Geological Survey of India (GSI). The road map has also been taken into consideration due to the high incidence of landslides occurring along the roads due to cut slopes. Improper drainage system along the roads also plays huge role in landslides. The final hazard zonation map was prepared by overlaying these three sets of features maps. Weightage for each factor is given in terms of percentage in Table 6. Fig. 5 Road map of Champhai district
Landslide Hazard Zonation Mapping of Champhai District of Mizoram … Table 6 Weightage of different factors
Factors
231
Weightage (%)
Stream features
35
Roads
30
Slope
20
Land use land cover
15
The output map was classified into five classes, and thereafter, the area of each class was calculated with the tool called ‘Zonal Geometry as table’: 1. 2. 3. 4. 5.
Very High Hazard Zone, High Hazard Zone, Moderate Hazard Zone, Low Hazard Zone, and Very Low Hazard Zone.
Figure 6a–d show the combined landslide hazard zonation map for each of the four blocks in the Champhai district. Table 7 shows the representation of the hazard classes with area cover for the 4 RD blocks.
5 Summary and Conclusions The following conclusions have been drawn from the present study: 1. The hazard zonation maps for landslide are prepared with factors such as land use land cover, relative relief and slope morphometry and regional hydrological distribution. 2. The maps are prepared with the aid of the ArcGIS Software, by acquiring the satellite data of DEM from USGS website for relative relief map and slope map while LANDSAT 8 image is acquired for interpretation of image classification for land use land cover map. 3. The study area is divided into four blocks namely Champhai RD Block, Khawzawl RD Block, Khawbung RD Block, and Ngopa RD Block. 4. The map of land use land cover, relative relief, and slope morphometry is prepared separately for each block, and the areas with high risk of landslides are identified. 5. The future scope of this work includes categorization of low hazard zone for the future development activities, identification of high hazard zones so that suitable mitigation schemes and policies can be adopted to minimize risk to life, property, and infrastructure. 6. Similar landslide hazard zonation maps can be prepared for other districts and towns around the country, which have not received proper attention in this regard.
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Fig. 6 Landslide hazard zonation map of a Champhai RD block, b Khawbung RD block, c Khawzawl RD block, d Ngopa RD block
Landslide Hazard Zonation Mapping of Champhai District of Mizoram … Table 7 Representation of different hazard classes with area cover
233
RD blocks
Hazard classes
Area (km2 )
Champhai
Very high hazard zone
42.81
High hazard zone
260.31
Moderate hazard zone
273.85
Low hazard zone
66.31
Very low hazard zone
3.47
Very high hazard zone
36.72
High hazard zone
325.95
Moderate hazard zone
367.37
Low hazard zone
153.2
Very low hazard zone
23.76
Very high hazard zone
26.84
High hazard zone
259.54
Moderate hazard zone
293.35
Low hazard zone
32.56
Very low hazard zone
0.44
Very high hazard zone
3.04
High hazard zone
451.76
Moderate hazard zone
249.6
Low hazard zone
0
Very low hazard zone
0
Khawzawl
Khawbung
Ngopa
References 1. Anbazhagan R (1992) Landslide hazard evaluation and zonation mapping in mountainous Terrain. Eng Geol 32:269–277 2. Anbazhagan R (1996) An overview of landslide hazards in Himalaya, available knowledge base, gaps, and recommendation for future research. Himalayan Geol 17:165–167 3. Anbazhagan R, Singh B, Chakraborty D, Kohli A (2007) A filed manual for landslide investigations. Department of Science and Technology, New Delhi 4. Anbazhagan S, Saranathan E (2001) Structure and its impact in Uthangarai and Thirthamalai region, Tamil Nadu, India—using remote sensing. J Indian Soc Remote Sens 29(4):187–195 5. Anbazhagan S, Ramesh V (2014) Landslide hazard zonation mapping in Ghat road section of Kolli Hills India. J Mt Sci 6. Anon (1998) Bureau of Indian Standard, preparation of landslide hazard zonation maps in mountainous terrains guidelines, part 2 Macro-zonation, IS 14496 7. Anon (2006) Manual of national land use and land cover mapping using multi temporal satellite data. National Remote Sensing Centre, Hyderabad 8. Gupta P, Anbazhagan R (1995) Landslide hazard zonation, mapping of Tehri Pratapnagar area, Garhwal Himalayas. J Rock Mech Tunnel Technol India 1(1):41–58
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9. Kannan M, Saranathan E, Anbazhagan R (2011) Macro landslide hazard zonation mapping— case study from Bodi—Bodimettu Ghats section, Theni District, Tamil Nadu-India. J Indian Soc Remote Sens 10. Sarkar S (2008) Landslide hazard zonation mapping and comparative analysis of hazard zonation maps. J Mt Sci
Numerical Analysis of Gravity Dam-Foundation and Comparison with Limit Equilibrium Method P. Senthil and Hari Dev
Abstract Gravity dams are subjected to complex loading conditions, and its stability analysis requires determination of properties of the foundation medium. The dam’s structural behaviour depends on the response of the foundation on which it is situated. In this paper, numerical analysis of the dam-foundation system has been carried out using finite element methods and compared with limit equilibrium or pseudo-static analysis results. The different types of loads acting on the dam body were considered as per IS: 6512 (IS 6512–1984 (Reaffirmed 1998), “Criteria for Design of Concrete Gravity Dams”, Bureau of Indian Standard, New Delhi), and safety criteria were checked for seven load combinations (A to G). A sample dam of 161.5 m height of non-overflow section has been considered for the study. The results obtained from the finite element method (FEM) have been compared with the limit equilibrium method (LEM). The advantages and limitations of numerical analysis for dams are also discussed. In general, the stresses at heel and toe of the dam section obtained from LEM analysis match with FEM analysis. Keywords Dam-foundation · Stability analysis · Finite element method · Limit equilibrium methods
1 Introduction Gravity dams are designed to resist the reservoir water pressure by its body weight constructed with concrete or masonry. Concrete gravity dam sections are divided into overflow (OF) and non-overflow sections (NOF). The OF and NOF parts of the dam are separated by a number of contraction joints. To optimize the dimensions of these sections, the NOF and OF blocks at deepest level are analysed individually for its stability. These individual blocks are called monoliths, i.e., forces acting on each block will be resisted by its gravity. The criteria for stability analysis of gravity P. Senthil (B) · H. Dev Central Soil and Materials Research Station, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_20
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Physical Structure (Dam, Foundation etc)
Assumptions for geometry, Loads and properties
Analytical Solutions – for simple geometry
Verification based on instrumentation data Final Results for the Physical structures considered Analyis Results (Displacement, Stresses, Factor of Safety etc)
Computer Programs FEM/FDM. (FLAC, PHASE2, Abaqus etc)
Fig. 1 Flow chart for numerical analysis of concrete dams
dams, loads, and combinations to be considered and permissible stress are given in IS: 6512 [1]. Limit equilibrium methods do not consider foundation properties. The linear stress distribution is assumed at the base of the dam. Moftakhar and Ghafouri [2] have studied three dam stability criteria, i.e., (i) U.S. Army Corps Engineers, (ii) US Bureau of Reclamation (USBR), and (iii) US Federal Energy Regulatory Commission dam with Finite element method (FEM) and stated that latter is more accurate as elastic properties of foundation affect the results. USBR [3] has published a guide for Analysis of Concrete Dam Structures using finite element method. The flow chart for numerical analysis of dams is shown in Fig. 1. Foster [4] studied that modelling a foundation with the depth and width equal to 1.5 and 3.0 times the base width of the dam, respectively, is sufficient to achieve accurate stresses results within the dam. In this paper, the non-overflow section of a sample dam of 161.5 m height has been analysed for stability using two methods, viz. limit equilibrium method (LEM) and FEM. The results of both methods are discussed.
2 Gravity Dam Design Criteria The guidelines for design of solid concrete gravity dams are given in IS: 6512 [1]. The dam is to be designed to satisfy the following stability requirement: (i) Dam shall be safe against sliding in any plane in the dam, at the interface, or within the foundation.
Numerical Analysis of Gravity Dam-Foundation and Comparison …
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(ii) Stresses in the dam body and in the foundation shall be within allowable limits as prescribed in code. (iii) The dam shall be safe against overturning in any plane within the dam, foundation, or at the interface. The dam design should be based on adverse load combinations A, B, C, D, E, F, and G given below using the partial safety factor prescribed as per IS: 6512 [1]: A. Construction condition—Dam completed but no water in reservoir and no tail water. B. Normal operating condition—Full reservoir elevation, normal dry weather tail water, normal uplift, and silt. C. Flood discharge condition—Reservoir at maximum flood pool elevation, all gates open, tail water at flood elevation, normal uplift, and silt. D. Combination-A, with earthquake. E. Combination-B, with earthquake. F. Combination-C, but with extreme uplift (drains inoperative). G. Combination-E, but with extreme uplift (drains inoperative) The typical dam NOF section of 161.5 m height considered for the study with all the loads/pressures acting on/in the dam is shown in Fig. 2. Self-weight of the dam is the main stabilizing force for gravity dam (W1 to W4). In addition, slit weights on u/s slope WS1, WS2, and tail water pressure act as stabilizing force. The destabilizing/overturning forces are reservoir water pressure (P1), silt pressure (PS1), hydrodynamic pressure, and uplift pressure (U1/U2).
Fig. 2 Loads acting in/on the Dam body
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Table 1 Material properties considered in the analysis Material/ properties
Unit weight (kN/m3 )
Poisson’s ratio Young’s modulus (MPa)
Concrete
24
0.17
Foundation rock
27
0.25
Interface
Normal stiffness (kn ) = 100 Gpa/m
Shear stiffness (ks ) = 10 Gpa/ m
20,000
Cohesion, c (Mpa)
Friction angle (ϕ) degrees
1.0
45
4250
0.4
45
–
0.6
35
3 Material Properties Considered The dam section is generally composed of M15 grade of concrete (Mass Concrete). The Mohr–Coulomb model is considered for both concrete and foundation. The strength and deformation properties of concrete considered for the analysis are given in Table 1. Partial safety factors on parameters “c” and “ϕ” have been applied for the different load combinations as given in IS: 6512 [1].
4 Limit Equilibrium Method (Lem) Results The forces acting on the dam body for various load combinations were determined and calculations for stresses at heel and toe of the dam, and factor of safety against sliding are carried out as per IS 6512 [1]. Stresses: Stresses at the heel and toe of the dam are worked out using Eq. 1. The forces at various loading conditions have been resolved, and using the equation given below, the stresses are determined for the NOF section under various loading combinations where, ∑V —sum of all vertical forces (kN), B—base width of dam (m), and e is eccentricity of the section (m). σHeel/Toe =
[ ] 6e ∑V 1± B B
(1)
Sliding: Factor of safety against sliding is found out using Eq. 2, and in no case, the factor of safety (FoS) shall be less than 1 where, W —total weight of dam, U—total uplift force, F ϕ —partial FoS in respect of friction, F c —partial FoS in respect of cohesion, ϕ—friction angle, C—cohesion, and A—contact area under consideration. Fs =
CA (W − U )tanφ + Fφ Fc
(2)
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Table 2 Stresses at base and FoS against sliding Load combination
Stress at heel Stress at toe (kN/m2 ) (kN/m2 )
FoS in sliding
Permissible tensile stresses (kN/m2 )
A (Construction stage)
2179
1127
–
NIL
B (Normal operation)
1193
1828
1.14
NIL
C (Flood discharging)
1057
1720
1.15
− 150 (0.01 fck )
D (Combination-A + EQ)
1594
1582
6.45
NIL
E (Combination-B + EQ)
309
2581
1.02
− 300 (0.02 fck )
F (Combination-C but drains inoperative)
476
1683
1.75
− 300 (0.02 fck )
G (Combination-E but drains inoperative)
− 392
2538
1.16
− 600 (0.04 fck )
Overturning: Once the dam is safe against sliding and there is no tension on the upstream face or heel, it will satisfy overturning criterion. The same judgement has been given in Duncan [5]. The summary of stresses at heel (upstream) and toe (downstream) and the FoS against sliding failure is given in Table 2. Compressive stress in the dam body shall not exceed 7 Mpa, and the allowable tensile stress for concrete gravity dam as percentage of compressive strength ( f ck ) is also mentioned in the table. As the material properties have been applied considering partial safety factors, the FoS against sliding more than 1 is sufficient. From Table 2, it can be seen that FoS is > 1 in all seven load combinations. The stresses at heel and toe of the dam are in compressive nature for load combinations A to F. In load combination-G, tensile stress of 392 kN/m2 is obtained in heel, which is less than permissible tensile stress of 600 kN/m2 . The maximum compressive stress obtained is 2581 kN/m2 at toe in load combination E.
5 Finite Element Method (Fem) Results The dam-foundation system is modelled as plane strain analysis in which out-ofplane strain components would be zero. An 8-stage modelling has been created for the analysis of the dam-foundation system. As per IS: 6512-1984 [1], there are 7 loading conditions (combinations A to G). Including the first stage of foundation excavation, a total of eight stages were modelled in the analysis. Due to constraints of applying seismic loading in Phase2 , the load combinations A to G are rearranged in such a manner that the load combinations having seismic load are grouped from stage 6 onwards. • Stage 1: Gravity analysis of foundation is completed, and the displacements are set to zero of the foundation. (In situ stresses are generated in the foundation)
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• Stage 2: Construction of the dam is completed, and the body weight is considered on the foundation. (Reservoir Empty) (Load Case-A) • Stage 3: Reservoir filled up to its full reservoir level (FRL), and the water pressure is resisted by the dam. (Reservoir Operation Condition) (Load Case-B) • Stage 4: Reservoir filled up to its Maximum Water Level (MWL), and the Tail Water Level corresponding to flood discharge. (Flood Discharging Condition) (Load Case-C) • Stage 5: Same as Stage 4 but drains are inoperative (Load Case-F) • Stage 6: Earthquake during Normal Operation, i.e., stage 3 + earthquake (Load Case-E) • Stage 7: Earthquake during Construction Stage. (Load Case-D) • Stage 8: Same as stage 6 but drains are inoperative (i.e. triangular distribution of uplift is considered) (Load Case-G) The model in FEM Phase2 software at different stages is shown in Fig. 3. The geometry of the dam as shown in Fig. 2, and 260 m on each side and 260 m depth of dam-foundation has been modelled. The model is discretized and meshed using an 8-noded quadrilateral element. Boundary conditions are given as displacement in X-direction is restrained in horizontal direction by providing rollers on both left and right vertical boundaries of the foundation. The displacements at the bottom of the foundation are restrained in Y-direction. Hence, corner node displacements are restrained in both X- and Y-direction. Field stresses in the foundation and body force were defined giving the unit weight, and external load acting on the dam has been applied in different stages defined above. As the model is defined, a maximum number of 500 iterations and tolerance limit of 0.001 have been considered for the FEM software computations. The stress plots obtained at different stages of FEM analysis are shown in Fig. 4. In stage 1, the in situ stress is generated and increases with depth. In stage 2 (caseA) and stage 7 (Case-D), the stress is more concentrated towards the heel as the centre
Stage-1
Stage-5 (Case-F)
Stage-2 (Case-A)
Stage-3 (Case-B)
Stage-6 (Case-E)
Stage-7 (Case-D)
Fig. 3 FEM model for Stage 1 to Stage 8
Stage-4 (Case-C)
Stage-8 (Case-G)
Numerical Analysis of Gravity Dam-Foundation and Comparison …
Stage-1
Stage-2 (Case-A)
Stage-3 (Case-B)
Stage-5 (Case-F)
Stage-6 (Case-E)
Stage-7 (Case-D)
241
Stage-4 (Case-C)
Stage-8 (Case-G)
Fig. 4 Maximum stress contour plots for Stage-1 to Stage 8
of gravity of the dam without reservoir falls towards upstream. In other cases, the stress concentration is towards the toe at the base of the dam, as the reservoir and other loads are applied in respective stages. The results of FEM analysis, i.e., stress at heel and toe of the dam and percentage of variation with LEM analysis, are given in Table 3. It is seen that maximum compressive stress of 2527 kN/m2 is obtained in load combination-A at the heel of the dam. In the LEM method, the maximum compressive stress was obtained at toe in load combination E. The minimum stress (tensile) is obtained − 875 kN/m2 in load combination-G at the heel of the dam. In comparison of stresses between LEM and FEM, it can be said that stresses contained in heel and toe portion are nearly matching with few exceptions. The stress at the heel portion in earthquake cases E, F, and G has shown a high amount of variation. Normal stress along the interface of dam-foundation at each stage is plotted in Fig. 5. The stress has been obtained from an interface element modelled in Phase2 software. It is evident that the distribution of stresses is not linear as considered in LEM, as the actual elastic properties of the material are considered. The stress at heel and Table 3 Stresses at base of dam from FEM analysis and comparison with LEM Load combination FEM analysis
% of variation with LEM analysis
Stress at heel (kN/ Stress at toe (kN/ Stress at heel (%) Stress at toe (%) m2 ) m2 ) A
2527
882
− 16
22
B
873
1855
27
−2
C
832
1842
21
−7
D
1556
1569
2
1
E
− 315
2326
202
10
F
107
1738
78
−3
G
− 875
2312
123
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Distance [m] 25
50
75
100
125
Toe 175
150
Normal Stress [MPa]
5 4 3 2 1
Stage-2
Stage-3
0
Stage-4
Stage-5
-1
Stage-6
Stage-7
Stage-8 -2
Fig. 5 Plot of normal stresses along the interface of dam-foundation
toe becomes more compressive or tensile due to redistribution of stresses at these points. ICOLD-61 [6] states that the tensile stresses in the FEM analysis could be as much as 12.5% of compressive strength of concrete (i.e., 1.87 MPa). It is seen that the stresses are within the permissible limits in both compression as well as in tension for the dam sections considered. FEM analysis also provides the deformation behaviour of dams in different load combinations. The deformation plots as obtained in different stages and the maximum deformation values are shown in Fig. 6. The maximum deformation of 169 mm corresponding to load combination-G has been obtained. The deformations under static conditions (without earthquake) are less than 80 mm. FEM analysis also provides mean stress, differential stress, stress trajectories, and deformation vectors. Instrumentation data after construction of the
Stage-1 0 mm
Stage-2 (Case-A) 70 mm
Stage-3 (Case-B) 80 mm
Stage-4 (Case-C) 76 mm
Stage-5 (Case-F) 77 mm
Stage-6 (Case-E) 161 mm
Stage-7 (Case-D) 66 mm
Stage-8 (Case-G) 169 mm
Fig. 6 Deformation contour plots for Stage 1 to Stage 8
Numerical Analysis of Gravity Dam-Foundation and Comparison …
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dam can be used for validation of assumptions in uplift, calibration of the stress, and deformation results.
6 Conclusions A typical non-overflow dam section of 161.5 m height has been considered and optimized by carrying out a limit equilibrium method of analysis as per IS: 6512 [1]. The optimized sections were modelled in the FEM software called “Phase2” to carry out 2D pseudo-static analysis. Eight-stage modelling has been adopted, so that seven load combinations along with the foundation could be simulated in the model and comparison is made between the LEM and FEM analysis. The following are the conclusions of the study made by conducting FEM study on gravity dams and comparison with LEM as per IS: 6512 [1]. • The pattern of deformation and amount of settlement expected to occur for the dam-foundation can be determined easily in the FEM method for complex shapes. LEM solutions are available for simple shapes with linear stress distribution assumptions. • Maximum and minimum stress obtained with LEM are 2582 kN/m2 and − 392 kN/m2 ; whereas with FEM, the maximum and minimum stresses obtained are 2527 kN/m2 and − 875 kN/m2 , respectively. • The results obtained in FEM analysis are well comparable with LEM analysis when the stresses are in compressive nature. In load combination E & G, especially at the heel portion, the FEM method gives higher tensile stress. However, ICOLD61 suggests that the permissible tensile stress could be of 12.5%fck for FEM analysis. This is due to the redistribution of stresses at the heel and toe due to varying stiffness. Acknowledgements This is an extension of first author’s M. Tech work and gratitude to Dr. K. G. Sharma for his guidance during the work. Authors are thankful to the Director, CSMRS, for the continuous encouragement and support. Disclaimer Authors find no conflicts of interest. No separate funding is received for this work. The views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of CSMRS.
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References 1. IS 6512-1984 (Reaffirmed 1998), “Criteria for Design of Concrete Gravity Dams”, Bureau of Indian Standard, New Delhi 2. Moftakhar M, Ghafouri HR (2011) Comparison of stability criteria for concrete dams in different approximate methods based on finite element analysis. Procedia Engineering 14(2011):1672– 1680 3. USBR (2018) Guide for analysis of concrete dam structures using finite element methods (DSO2018–09). U.S. Department of the Interior Bureau of Reclamation 4. Foster J (1994) “Procedure for static analysis of gravity dam including foundation effects using the FEM-phase 1B” published by US Army Corps 5. Wyllie DC (1999) Foundations on rock. E& FN Spon, New York 6. ICOLD-61, Dam Design Criteria-Philosophy and their selection, International Commission on Large Dam
Experimental and Prediction of Properties of Concrete Using Steel Slag by Taguchi Method P. Ramachandra, P. S. Niranjan, and Vibha N. Dalawai
Abstract The steel slags, a waste product of the steel industry, can be used in concrete as replacement of aggregates. On the other side, constant use of natural aggregates causes havoc on the ecosystem, necessitating the protection of the natural resources. The current work concentrated on the experimental investigation and prediction of the effects of steel slags as alternatives to natural coarse aggregate on the characteristics of freshly-mixed concrete and freshly-hardened concrete. Concrete’s properties were discovered using the slump flow, compressive strength (CS), and split tensile strength (STS). From the laboratory test of determination, it was seen that the slump flow of concrete decreases as the proportion of substitution of coarse aggregate (CA) with steel slag (SS) increases, while the density of concrete increases. At 28 days after curing, the strength of hardened self-compacting concrete was also evaluated. The material is composed of steel slag combined with natural aggregate to the extent that the maximum STS and maximum CS are used to confirm this. The prediction of a concrete property with steel slag and natural aggregate is investigated by using the Taguchi method. Design of experiment was performed via L9 orthogonal array, and the predicted model shows value close to the experimental results. Keywords Steel slag · Taguchi method · Regression
P. Ramachandra Department of Civil Engineering, PES University, Bengaluru, Karnataka, India e-mail: [email protected] P. S. Niranjan Department of Civil Engineering, New Horizon College of Engineering, Bengaluru, Karnataka, India V. N. Dalawai (B) CMR Institute of Technology, Bengaluru, Karnataka, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_21
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1 Introduction Integrated iron and steel mills in India currently produce up to 270 million tons of industrial solid waste each year, but barely use 30% of it [1]. Slag is a superior environmentally friendly alternative building material with greater product attributes [2]. The cement and concrete industries fully utilize the annual production of blast furnace slag because of its advantageous cementitious and pozzolanic qualities [3]. Most researchers have looked into and focused on the potential use of SS as a natural aggregate substitute for concrete and road construction, as well as cement manufacture [4]. Since the cost of steel slag is around half that of typical aggregates, using steel slag is cost-effective [5]. In a case study [6], sand made from granulated blast furnace slag (GBFS/GBS) is used in cement concrete as a partial replacement for crushed stone sand (CSS). Slag sand was substituted for 50% of the CSS fine aggregate used in cement concrete mixes in laboratory studies for grades of concrete from M30 to M70 (by weight of total fine aggregate). In comparison to a mix made entirely of CSS (as fine aggregate), these mixtures’ properties were examined. GBFS was used to substitute natural sand in varying amounts (25, 50, 75, and 100 percent), with a consistent water/cement ratio of 0.5 in each case [7, 8]. Steel slag, a pozzolonic substance, was researched in order to achieve the desired attribute. SS was substituted for CA in various amounts, including 0%, 25%, 50%, 75%, and 100%. Chinnaraju et. al. [9] studied using eco sand in place of fine aggregate and steel slag in place of coarse aggregate in concrete. Materials were first optimized with a 7-day strength. Concrete of grade M30 was utilized. [10] the results of replacing some of the coarse aggregate with steel slag For varying quantities of 0, 20, 40, 60, and 80% as well as with an M40 grade of concrete for a water cement ratio of 0.40, steel slag was used to replace coarse aggregate.
2 Materials and Methodology Materials used in this research include cement, fine aggregate (FA), CA. The cement used is Ordinary Portland Cement 53 graded which confirmed to IS 8112-1989 and the sample was tested as per IS-4031-1988 and IS 269-1976. Fine aggregate employed is the river sand and tests were conducted as per IS: 2386-1968, Part-III. The steel slag collected from JSW Bellary Karnataka, India, and tested as per IS 2386-3:1963 (Fig. 1). The proportion of water to cement, cement content, curing method, and compaction are held constant to account for the effects of SS replacement in part. Concrete is cast using SS as a substitute for both FA and CA. Natural FA is replaced 100% by ground granulated blast-furnace slag and natural CA is replaced from 0 to 100% with increments of 10% by 20 mm down size SS. The cement used is 53 Grade OPC and 0.47 water-cement ratio. The concrete mix is prepared for M25 grade, and expected characteristic strength after 28 days is 25 MPa.
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Fig. 1 Casting and testing of specimens
There were three cubes cast for each ratio. The cubes were tested for compressive test on the 7th day and 28th day test, respectively. The results of all the tests were tabulated for all the proportions ranging from 0 to 100%. The prepared concrete examples had dimensions of 150 × 150 × 150 mm. They were put through a 2000 kN capacity compression test in accordance with IS 58161959. With the use of a tamping rod, the concrete mix is poured into a cylindrical concrete mold that is 150 mm in diameter and 300 mm high. Each layer receives 25 blows after four subsequent layers, and the top surface is flattened (Table 1). Table 1 Composition of cement mix, curing period and varying percentages of steel slag used in preparation M25 grade mix concrete specimens S. No.
Mix proportion
Cement content (%)
Fine aggregate content (%)
1
M0
100
100
Coarse aggregates Natural coarse aggregate content (%)
Steel slag coarse aggregate content (%)
100
0
Curing period (days) 7, 28
2
M1
100
100
90
10
7, 28
3
M2
100
100
80
20
7, 28
4
M3
100
100
70
30
7, 28
5
M4
100
100
60
40
7, 28
6
M5
100
100
50
50
7, 28
7
M6
100
100
40
60
7, 28
8
M7
100
100
30
70
7, 28
9
M8
100
100
20
80
7, 28
10
M9
100
100
10
90
7, 28
11
M10
100
100
0
100
7, 28
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2.1 Taguchi’s Method of Design Taguchi is a reliable design that uses the orthogonal array method to cut out pointless test runs. When compared to standard experimental design methods, the orthogonal array is more cost-effective, resulting in fewer experiments and fewer uncontrollable parameters. It uses the signal-to-noise (S/N) ratio to analyze the data and forecast the best outcomes. The Taguchi method was employed in the current study to assess the attributes of fresh and hardened (SCRC). The same steel slag aggregate specific gravity was used to create four distinct concrete mixtures. The final mechanical behavior and concrete properties with steel slag are described and reviewed. The orthogonal array technique served as the foundation for the experiment’s design. A fractional factorial design is an orthogonal array.
3 Results and Discussion CS of concrete specimens was evaluated and tabulated after the addition of SS to concrete in varied quantities and curing for 7 and 28 days. Monitoring CS as a function of curing time allows researchers to evaluate the kinetics of cement reactions with SS aggregates for concrete. The impact of SS percentage fluctuation on the CS produced by concrete is assessed. The cement, slag, sand, and SS (fine and coarse) aggregate mixtures are molded with a particular water-to-cement ratio (W/C) and compressed under a constant compressive stress. The compacted specimens are allowed to cure for seven to twenty-eight days at room temperature. After curing, the compressive strength of a concrete sample is evaluated. Additional split tensile strength analysis is also done. Slump test results confirmed best results for combination of 2% steel fibers and 10% fly ash, when compared to other combinations and conventional concrete. Figure 2 depicts the variance in slump flow that resulted from the replacement of SS CA with respect to the reference concrete. As the amount of coarse aggregate replacement increases, the slump flow drops. However, a 10% steel Slag exhibits a maximum slump flow of 120 mm as opposed to a 127 mm slump flow for normal concrete. Figure 3 depicts the variation in CS of a concrete made with SS CA and reference concrete that was replaced in percentage. As the proportion of CA replacement with SS increases, so does the CS. However, a maximum amount of SS (60%) can be seen. Conventional mix of M25 grade of cement and sand shows compressive strength of 2.1 MPa. Mix proportions are substituted with natural CA in increments of 10% starting from 0% till 100%. In M0 mix, natural FA is replaced with 100% GBFS and cured at 28 days showed CS of 33.51 MPa. Similarly, mix M2 with 100% GBFS and 10% CA SS showed CS of 34.66 MPa and so on for all proportions up till M6. M6 mix with 100% GBFS and 60% SS, and 40% natural CA showed maximum compressive strength with 40 MPa. Whereas M7 mix with 100% GBFS and 70% SS and 30% natural coarse aggregate showed decrease in CS with 38.57 MPa. The CS goes on
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Fig. 2 Slump value for all the mix proortions
decreasing from 40 MPa till 35.25 MPa after M7 up till M10. The results implies that SS has high potential on substituting with natural aggregates when compared to M25 grade normal concrete which showed strength of 32.1 MPa. Further on replacing SS in coarse aggregates partially and on 100% replacement of natural fine aggregate by GBFS as fine aggregate showed promising results in CS development. Figure 4 depicts the variation in density of concrete made with SS CA and reference concrete that was replaced in percentage terms. The coarse aggregate made from steel slag is replaced, the density increases. However, when made entirely of steel slag, it has a maximum density of 2628 kg/m3 , as compared to the 2410 kg/m3 of normal concrete. When the ratio of CA substituted with SS increases, so does the STS. However, when made entirely of SS, it has a maximum split tensile strength of 3.85 N/mm2 , as compared to 2.40 N/mm2 for conventional concrete. Figure 5 depicts the variance in slump that resulted from the replacement of SS CA with respect to the reference concrete. The slump gets reduced when the amount
35.25
39.67
37.75
38.57
24.78
60
25.67
50
26.49
40
27.11
40 30.4
38.32 28.88
30
37.66
37.11
36 20
28 days
27.76
10
27.38
0
26.88
30
25.06
35
33.51
40
24.58
Compressive strength (MPa)
45
34.66
7 days
70
80
90
100
25 20 15 10 5 0
% Replacement of SS
Fig. 3 CS value for various percentage of SS
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2628
2600
2578
2591
2560
Density (kg/m3)
2546 2550
2530 2492
2500
2473 2454
2450
2425
2410 2400
2350 0
20
40
60
80
100
120
% Replacement of SS
Fig. 4 Density value for altered percentage of SS
of coarse aggregate made from steel slag is replaced. The maximum slump for steel slag, however, is 110 mm. Between reference concrete and slump flow of concrete with a percentage replacement of coarse steel aggregate, a regression model is created. Regression model and experimental data are found to be comparable, and the value of R2 is 0.99, very close to 1. Therefore, the formula Slump = 126.5–0.5362 can be used to forecast the slump values (Percentage of replacement of steel slag). Figure 6 depicts the difference in CS of a concrete made with SSCA and reference concrete that was replaced in percentage terms. As the proportion of CA replaced with SS rises, so does the CS. But compared to typical concrete, which has a CS of 33.5 N/mm2 and 60% of SS exhibits a maximum CS of 40 N/mm2 . Figure 7 depicts the regression model created between reference concrete and concrete with % replacement of SS CA for CS. Regression model and experimental data are found to be similar, and the value of R2 is 0.92, which is marginally close to 1. Consequently, using a formula, the compressive strength of concrete values can be predicted. Strength in compression: 34.04 + 0.07. The regression model created between the reference concrete and split tensile strength of concrete with percentage replacement of steel coarse aggregate is shown in Fig. 8. The experimental data and regression model are found to be similar, and the value of R2 is 0.98, which is marginally close to 1. Therefore, using the formula split tensile strength = 2.364 + 0.09, the STS of concrete values may be predicted (Percentage of replacement of steel slag).
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Fig. 5 Regression model of slump value for different percentage of steel slag 28 days
3.85
7 days
70
80
3.31 2.57
3.19
3.1
2.4
50
2.37
40
2.63 2.97
30
2.82
20
2.46
10
2.39 2.69
2.32 2.66
2.5
2.25 2.53
3
2.19 2.45
3.5
2.12 2.4
Split tensile strength (MPa)
4
2.67
4.5
2 1.5 1 0.5 0 0
60
% Replacement of SS
Fig. 6 STS value for all the mix proportions
90
100
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Fig. 7 Regression model of compressive strength for different percentage of SS
Fig. 8 Regression model of split tensile strength for different percentage of SS
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4 Conclusions 1. As the amount of CA replacement increases, the slump flow drops. However, at 10% SS exhibits a maximum slump flow of 120 mm as compared to 127 mm slump flow of normal concrete. 2. The density increases as there is rise in the proportion of replacement of SS CA. But for a 100% of SS shows maximum density of 2628 kg/m3 compared to a conventional concrete density of 2410 kg/m3 . 3. As the proportion of CA made out of SS replacement, the CS rises. The best CS with SS is 40 N/mm2 , whereas the SS of conventional concrete is 33.5 N/mm2 . 4. The STS rises together with the proportion of replacement of SS CA. But SS concrete has a maximum STS of 3.85 N/mm2 , as compared to normal concrete’s which has STS of 2.40 N/mm2 . 5. Regression model developed between slump flows of concrete with percentage replacement of SS CA value of R2 is 0.99 close to 1. Hence, the slump values can be predicting using formula, slump = 126.5–0.5362(Proportion of substitution of steel slag) 6. The value of R2 for the regression model between concrete’s compressive strength and the proportion of steel-replaced coarse aggregate is 0.92, which is quite near to 1. Hence, = 34.04 + 0.07 is used to forecast CS (percentage of replacement of steel slag). 7. Regression model developed between STS of concrete with percentage replacement of SS CA value of R2 is 0.98 close to 1. Hence, the STS can be predicted using formula, STS = 2.364 + 0.09.
References 1. Nadeem M, Pofale AD (2012) Experimental investigation of using slag as an alternative to normal aggregates (coarse and fine) in concrete. Int J Civ Struct Eng 3(1):117–127 2. Brindha D, Nagan S (2011) Durability studies on copper slag admixed concrete 3. Gokul J, Suganthan S, Venkatram R, Karthikeyan K (2012) Mild steel slag as a potential replacement for concrete aggregate. Int J Curr Res 4(11):l06–l09 4. Devi VS, Gnanavel BK (2014) Properties of concrete manufactured using steel slag. Procedia Engineering 97:95–104 5. Hatami F Kermani M, Effect of mechanical behaviour of steel making slags on the blended cements by experimental study 6. Rao MS, Bhandare U (2014) Application of blast furnace slag sand in cement concrete–a case study. Int J Civ Eng Res 5(4):453–458 7. Ramadevi K, Sindhubala S, Johnpaul V (2014) Determination of optimum percentage replacement of fine aggregate in concrete using GBFS (granulated blast furnace slag). IJREAT Int J Softw Hardware Res Eng 2(3). ISSN: 2347-4890 8. Sinha HM (2014) Experimental investigation in utilization of basic oxygen furnace steel slag in concrete. Int J Res Eng Appl Sci 2(2):1–4
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9. Chinnaraju K, Ramkumar VR, Lineesh K, Nithya S, Sathish V (2013) Study on concrete using steel slag as coarse aggregate replacement and ecosand as fine aggregate replacement. Int J Res Eng Adv Technol 1(3):1–6 10. Thangaselvi K (2015) Strength and durability of concrete using steel slag as a partial replacement of coarse aggregate in concrete. Int J Adv Res Trends Eng Technol 2(7):1–6
Properties of Rice Husk Ash and Aluminium Slag-Based Sustainable Geopolymer Bricks Mahapara Abbass, Gyanendra Singh, and Vanita Aggarwal
Abstract The manufacture of insulating geopolymer bricks (GPBs) utilizing rice husk ash and waste aluminium slag (ALW) has been described in this work. The GPBs were described using compressive strength, bulk density, normal and hot absorption of water, acid attack, and porosity. RHA has poor alumina content. ALW is, therefore, added to make up for this lack. The RHA sample was made with varying NaOH levels (e.g. 8, 10, and 12 M; sodium silicate to sodium hydroxide ratio = 2) and curing durations (e.g. 7, 14, and 28 days). The maximum compressive strength was obtained at a concentration of 12 M NaOH. Various Si/Al ratios were subsequently made and tested at 12 M sodium hydroxide. According to the results, adding more alumina improves the characteristics of the GPB but decreases its compressive strength. Following a 28-day curing period, the sample with a Si/Al ratio of 2 had a higher compressive strength (11.2 MPa) than the specimens with Si/ Al ratios of 3 and 1. The results are following Egyptian and ASTM C62 standards. Keywords Rice husk ash · Aluminium slag · Geopolymer brick · Acid attack
1 Introduction Industries are recognized for discharging enormous volumes of garbage, which poses a problem for both the economy and the natural environment [1–7]. The manufacturing of bricks from by-products could lessen the problems associated with disposal sites, cut down on the utilization of natural resources, and lower the expenses associated with extractive operations [8]. Because of the extreme manufacturing temperatures (900–1000 °C) in kiln blazing, which is characterized by significant carbon dioxide and NOX emissions, the fabrication of fired bricks requires a very large M. Abbass (B) · G. Singh Department of Civil Engineering, DCRUST, Murthal, Sonipat, Haryana 131039, India e-mail: [email protected] M. Abbass · V. Aggarwal Department of Civil Engineering, MMDU, Mullana, Ambala, Haryana 133207, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_22
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amount of energy [9–12]. Since clay and shale need a lot of energy to process and consume mineral resources, they are not thought of as being environmentally benign or economically advantageous for use in the manufacturing of bricks. So, nova days, there has been an increase in interest in researching alternate building materials to solve the above problems. By eliminating flaming or labour-intensive methods of trash removal and better utilizing them, this strategy also contributes to a reduction in the energy needed. Numerous waste products, including fly ash, cotton waste, slags, oyster shells, mine tailings, and wood sawdust, have been used as replacements or additives in the construction of bricks by researchers [13–27]. Due to the advantages of recycling waste to the ecosystem and the economy, GP innovation has been presented as an innovative method for producing bricks utilizing diverse trash from industrial wastes luxurious in silica and alumina minerals [28, 29]. A highly concentrated silicate solution or aqueous alkali hydroxide is used in this technique to chemically react with industrial waste silica and alumina materials to create a resilient substance with an indeterminate polymeric structure [9, 10, 13, 30–32]. The sodium aluminosilicate hydrate gel is created by the reaction between the geopolymer (GP) gel network and other components (N-A-S–H). The tri-structure of N–A–S–H is a product of the SiO4 and AlO4 tetrahedral Web with shared O2 atoms [29, 33]. Therefore, to create a GP, suitable Si to Al ratio must be kept. The N–A–S–H GP network’s development depends greatly on the alkali solution’s level. The multi-use concentration of NaOH in solutions with molarities of 8 M, 10 M, and 12 M has been the subject of several past research. [34–38]. To increase the properties of GP or manufactured GP pastes with a low SiO2 /Al2O3 (Si/Al) molar ratio, additional ingredients are needed in many cases where the starting materials for GP are lacking in aluminosilicate [39]. This proportion creates a GP with a large surface area, which improves the capacity of adsorption [40, 41]. Fly ash, slag from electric arc furnaces, and waste foundry sand were the three main components used to create the GP bricks [29] produced for pavement applications. Waste foundry sand, on the other hand, has low levels of calcium and alumina necessitating the addition of various amounts of fly ash and slag from electric arc furnaces to increase the calcium and alumina ratios and, in turn, increase the compressive strength. Similar to this, a GP made of rice husk ash (RHA) with better characteristics is made using a secondary supply of alumina [30, 42–46]. It is possible to overcome RHA’s drawbacks by using alumina sources [44, 45]. RHA including nano-Al2 O3 [47] to compensate for RHA’s lack of Al2 O3 leads to the preparation of highly reactive alkaline activated binder. The production of sodium aluminosilicate hydrate (N–A–S–H) and calcium aluminosilicate hydrate (C–A–S– H) or a GP gel in the alkali-activated matrix also contributed to an improvement in mechanical properties. Low-alumina materials, therefore, require the addition of alumina [47]. When high-purity quartz is reduced with coal in an electric arc furnace, ferrosilicon slag (FS) is produced as a by-product. As a result, it contains a lot of free silicon, which could discharge along with the slag. It is employed in the Portland cement and steel-making sectors due to its inexpensive cost. GP foams are created when free silicon is oxidized by water in an alkaline environment, generating H2 gas [48, 49]. GP foams are made at low temperatures (less than 100 °C) and resemble ceramic or glass foams, which are made at high temperatures (more than 900 °C) [48,
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50]. Additionally, GP’s tiles can be utilized in place of ceramic materials, which are typically made by calcining clay at 900–1000 °C [51–53]. GP foams are employed in high-temperature applications, such as thermal insulation, wall panels, and fireresistant coatings [48, 54, 55]. The majority of such foams are lighter, making them suitable for operations including fire resistance and thermal and sound insulation [48, 56]. However, FS lacks Al2 O3 ; thus, an alumina resource is required to make up for this shortfall and achieve the reaction between Si and Al in the presence of an alkaline solution to create a GP gel (N-A–S–H). After quenching smelted aluminium, considerable quantities of alumina waste (ALW) are created. The Al2 O3 shortage in FS can be made up for by using this slag, which is a free resource. In terms of performance as a building material, ALW is a cost-effective option [57]. Excellent refractoriness, good compressive strength, superior chemical integrity, good temperature resilience, and excellent impact characteristics are just a few of the benefits of ALW [58]. Additionally, AW can enhance fire resistance for applications involving high temperatures [59, 60]. Egypt produces about 258,000 tonnes of aluminium annually, according to the World Bureau of Metal Statistics [61, 62]. Only a few researches [39, 47, 57, 63] have employed alumina in the creation of GP composites to make up for the materials’ lack of alumina and enhance the GP’s characteristics. As per earlier work, there is a dearth of research that demonstrates the usage of RHA as a fundamental ingredient or supplementary component in the manufacture of cement or GP concrete. Furthermore, there have not been any prior investigations on the application of RHA and ALW in the creation of GP-based bricks Therefore, the value of this research work for the utilized of RHA in the preparation of bricks. The results of this study will broaden the field and promote the use of agricultural waste in GP in the building sector. As a result, in this investigation, bricks were manufactured for non-load carrying. The samples’ compressive strength, porosity, density, acid attack, and absorption of water were investigated. The specimens with a significant alumina content showed significant strength properties. The findings of the analysis can be utilized to develop ecologically friendly approaches to managing industrial by-products.
2 Materials Rice husk ash (RHA) is a waste generated from rice, which is a staple food cultivated all over the World. About 20 kg of ash is produced from one tonne of rice, which is rich in silica. The silica content in RHA is more than 91%. The chemical activators used were NaOH and Na2 SiO3 which were provided by a local commercial supplier. The concentration of sodium hydroxide was varied in three proportions, viz. 8, 10, and 12 M. The coarse aggregate size varied between 12.5 mm and 19 mm according to IS 2386 (part I)-1963 and zone II sand was used following IS 383: 1970. Waste aluminium slag (ALW) was provided by a local dealer which was rich in alumina. To maintain the Si/Al ratio for the development of aluminosilicate hydrates, ALW was used here. The Si/Al ratio was varied in three proportions, viz. 1,2, and 3.
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Table 1 Chemical composition of RHA, CBA, and B.S.F Material Al2 O3 SiO2 (%) (%)
CaO Fe2 O3 MgO Na2 O TiO2 FeO SO3 K2 O LOI Others (%) (%) (%) (%) (%) (%) (%) (%) (%) (%)
R HA
0.48 0.06
ALW
0.15 65.2
91.5
2.53 0.5
Table 2 Physical properties of RHA and ALW
0.45
Material
–
0.27
–
–
1.29 −
3.1
9.0
3.71
0.15
–
0.52
2.46 11.98
Specific gravity (kg/cm3 )
3.5
Fineness (Passing 45 µm)
3.15
Colour
RHA
2.13
3.00
Dark grey
ALW
2.48
2.7
Light black
The physical and chemical parameters of RHA and ALW are provided in Tables 1 and 2.
3 Sample Preparation According to the proportions of mixes provided in Table 3, the materials for making GP bricks were combined using the ratios listed in Table 3, the dry ingredients were premixed for 10 min. Following that, a small amount of the alkaline solution was gradually added to the RHA and ALW mixture. Various amounts of alkaline solutions were mixed with the samples with various molarities of NaOH (i.e. 8, 10, and 12 M). Casting of the fresh GP slurries into moulds followed by 24 h of ambient curing allowed for demolding. After seven, fourteen, and twenty-eight days of ambient curing, specimens of GP foam were examined for compressive strength. The sample that contained 12 M NaOH had the maximum compressive strength. To produce the additional formulations with various Si/Al ratios, this solution was therefore utilized. The open porosity accessible to water was tested using the direct water displacement method. Each specimen (30 mm thick) was weighed in both water (WR) and air after being vacuum-saturated to a consistent weight (WI). Once the specimen attained a steady weight then were dried in an oven at 110 °C and weighed once again (WO). Equation (a) helped to determine the porosity. Open porosity =
WI − WO WI −WR
(1)
The water absorption of bricks was assessed using the standard methodology. Following a 28-day curing period, testing for water absorption was done. In this investigation, specimens were dried in an oven for not less than 24 h at a temperature of 100 to 110 °C. They were weighed after being allowed to cool to ambient temperature (WT). After that, they were placed in a water for a minimum of 24 h
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Table 3 Mix proportions of bricks Mix
RHA (kg/m3 )
NaOH (kg/m3 )
Na2 SiO3 (kg/ m3 )
Si/Al
NaOH (M)
Extra water (kg/m3 )
1RB8
500
66.67
133.3
1
8
50
2RB8
500
66.67
133.3
2
8
50
3RB8
500
66.67
133.3
3
8
50
1RB10
500
66.67
133.3
1
10
50
2RB10
500
66.67
133.3
2
10
50
3RB10
500
66.67
133.3
3
10
50
1RB12
500
66.67
133.3
1
12
50
2RB12
500
66.67
133.3
2
12
50
3RB12
500
66.67
133.3
3
12
50
then, removed from the water and were dried on the surface and weighed (WR). The following equation was employed to calculate water absorption Water absorption (%) =
W R − WT × 100 WT
(2)
For acid attack resistance, ASTM C267 [64] was followed according to which cylindrical specimens of 50 × 100 mm were subjected to a 1% HCl solution, samples should be partly dipped in the solution for one week, then removed, rinsed by water, dried for 30 min, and weighed. For a total of 12 weeks, this cycle is repeated. It is also worth noting that the HCL solution is refreshed once a week and shielded with paraffin oil to avert its evaporation to the environment.
4 Results and Discussion 4.1 Compressive Strength The compressive strength (CS) for seven days varied between 5 and 6.8 MPa, for 14 days, the compressive strength varied between 5.8 and 10 MPa, and for 28 days, the CS varied between 6.5 and 11.2 MPa as shown in Fig. 1. The highest CS was obtained by 2RB12 for which the SI/Al ratio was kept at 2, and NaOH concentration was kept at 12 M. The lowest compressive strength was gained by 1RB8 for which the NaOH concentration was kept at 8 M, and Si/Al ratio was kept as 1. Once the Si/ Al ratio was increased by over 3×, CS two-dimensional cross-linked polysialate was reduced, however, when the ratio was increased by 1.5 to 2, a tri-network was created [65]. Better CS was obtained utilizing lighter-weight GP materials made with RHA, nano-alumina, polypropylene, and scoria particles [47]. Due to the production of
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Fig. 1 Compressive strength of GPC bricks
calcium and sodium aluminosilicate hydrates (C–A–S–H) and GP gel in the alkaliactivated mix, the inclusion of 20% nano-alumina to the mix may signify the strength characteristics [66].
4.2 Bulk Density Figure 2 demonstrates the bulk density (BD) of the bricks, the seven days bulk density varied between 830 and 1120 kg/ m3 , for 28 days, BD varied between 900 and 1300 kg/m3 , and for 24 days, BD varied between 980 and 1600 kg/m3 . The maximum BD was attained by the mix 2RB12. The minimum BD was attained by 1RB8. With the hike in Si/ Al ratio up to 2 and molarity of NaOH up to 12 M the BD increased and beyond that, it showed a decline. Due to the presence of insoluble components in the specimens, which serve as damage sites, the density dropped as the Si/Al ratio increased [41].
4.3 Open Porosity Figure 3 demonstrates the open porosity (OP) of the bricks, and the OP varied between 0.28 and 0.5%. The maximum OP was attained by 1RB8. With the hike in Si/Al ratio up to 2 and molarity of NaOH up to 12 M the OP decreased and beyond that, it showed the hike. The porosity was reduced with the hike in ALW content (low Si/Al
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Fig. 2 Bulk density of GPC bricks
Fig. 3 Open porosity of GPC bricks
ratio). Increased porosity decreased the compaction and density and result in lesser strength bricks. With an increasing Si/Al ratio, a significant rise in the GP’s pore volume was seen [41].
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4.4 Water Absorption Figure 4 demonstrates the water absorption (WA)) of the bricks in normal and hot water, and the normal water absorption (NWA) varied between 14 and 28%. The maximum NWA was attained by 1RB8 which is 28%. With the hike in Si/Al ratio up to 2 and molarity of NaOH up to 12 M the NWA decreased and beyond that, it showed the hike. The hot water absorption (HWA) varied between 24 and 35%. The maximum HWA was attained by 1RB8 which is 35%. The minimum NWA and HWA were attained by 2RB12 for which Si/Al ratio was 2, and the concentration of NaOH was 12 M. The low Si/Al ratio and increased ALW content resulted in a decrease in porosity. As porosity grew, compaction and density reduced, water absorption increased, and brick strength fell. As the Si/Al ratio increased, a significant rise in the GP’s water absorption was seen [41].
Fig. 4 Water absorption of GPC bricks
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Fig. 5 Acid attack resistance of GPC bricks
4.5 Acid Attack The % weight loss of bricks versus time is shown in Fig. 5 (weeks). The percentage weight reduction ranged from 20 to 59.4% after 12 weeks, with the mix 2RB12 showing no weight loss for the first three weeks before dropping to 20 per cent after 12 weeks, which is smaller than the weight loss in the all other mixes. The maximal loss of weight in 1RB-8 is 59.4%, RHA with Si/Al ratio 2 and NaOH concentration 12 GPC bricks proved to be more resistant to acid attack than any other mixes. Furthermore, GP cement can capture dangerous compounds and radioactive material even in their structures [67].
5 Conclusion The following are the conclusions of the study. RHA and aluminium slag-based bricks with Si/Al ratio 2 and NaOH concentration 12 M (2RB12) obtained: • high CS of 8.2, 10, and 11.2 MPa for 7, 14, and 28 days, respectively. • high bulk density of 1120, 1300, and 1600 kg/m3 for 7, 14, and 28 days. • low porosity of 28% which is lesser than all other proportions.
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• absorbed a lesser amount of water in both cases. The NWA was 14%, and HWA was 16% which was lesser as compared to all other bricks. • The reduction in weight after 12 weeks of immersion in 1% HCl solution was lesser which was only 20%. Therefore, it is acid resistant as compared to all other bricks with different Si/Al ratios and NaOH molarities.
References 1. Zeyad AM, Johari MAM, Abutaleb A, Tayeh BA (2021) The effect of steam curing regimes on the chloride resistance and pore size of high–strength green concrete. Constr Build Mater 280:122409 2. Faried AS, Mostafa SA, Tayeh BA, Tawfik TA (2021) The effect of using nano rice husk ash of different burning degrees on ultra-high-performance concrete properties. Constr Build Mater 290:123279 3. Zeyad AM, Johari M, Tayeh BA, Saba AM (2017) Ultrafine palm oil fuel ash: from an agroindustry by-product into a highly efficient mineral admixture for high strength green concrete. J Eng Appl Sci 12(7) 4. Tayeh BA, Hadzima-Nyarko M, Zeyad AM, Al-Harazin SZ (2021) Properties and durability of concrete with olive waste ash as a partial cement replacement. Adv Concr Constr 11(1):59–71 5. Amin M, Zeyad AM, Tayeh BA, Agwa IS (2021) Engineering properties of self-cured normal and high strength concrete produced using polyethene glycol and porous ceramic waste as coarse aggregate. Constr Build Mater 299:124243 6. Calis G, Yildizel SA, Erzin S, Tayeh BA (2021) Evaluation and optimisation of foam concrete containing ground calcium carbonate and glass fibre (experimental and modelling study). Case Stud Constr Mater 15:e00625 7. Hamada H, Tayeh B, Yahaya F, Muthusamy K, Al-Attar A (2020) Effects of nano-palm oil fuel ash and nano-eggshell powder on concrete. Constr Build Mater 261:119790 8. Zhang L (2013) Production of bricks from waste materials—a review. Constr Build Mater 47:643–655 9. CETCJC (2001) Tenth five-year program of building materials industry 7:7–10 10. Chen Y, Zhang Y, Chen T, Zhao Y, Bao SJC (2011) Hsp90 regulates NADPH oxidase activity and is necessary for superoxide but not hydrogen peroxide production, Preparation of ecofriendly construction bricks from hematite tailings 25(4):2107–2111 11. Tayeh BA, AlSaffar DM, Askar LK, Jubeh AI (2019) Effect of incorporating pottery and bottom ash as partial replacement of cement. Karbala Int J Mod Sci 5(4):9 12. Al Saffar DM, Tayeh BA (2018) Influence of pottery clay in cement mortar and concrete mixture: a review. Int J Eng Technol 7(4.20):67–71 13. Ahmari S, Zhang LJC (2012) Production of eco-friendly bricks from copper mine tailings through geo-polymerization 29:323–331 14. Zhang Z, Qian J, You C, Hu CJC (2012) Use of circulating fluidized bed combustion fly ash and slag in autoclaved brick 35:109–116 15. Kumar A, Kumar SJC (2013) Genetic predisposition for the development of nephropathy in type 2 diabetes mellitus. Development of paving blocks from synergistic use of red mud and fly ash using geo-polymerization 38:865–871 16. Wang L, Sun H, Sun Z, Ma E (2016) New technology and application of brick making with coal fly ash 18(4):763–770 17. Lin KL (2006) Feasibility study of using brick made from municipal solid waste incinerator fly ash slag 137(3):1810–1816 18. Malhotra S, Tehri SJC (1996) Development of bricks from granulated blast furnace slag 10(3):191–193
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Identification of Critical Project Success (CPS) Factors for Construction Projects in India: An Overview Susan Jamuna Chacko , Charu Nangia , Radhe Shyam Rai , and Vanita Ahuja
Abstract Successful project completion requires fulfilment of the specified objectives and involves the implementation of project processes in an environment which is conducive to performance. Construction projects due to their dynamic nature are especially vulnerable to several uncertainties which impact their goals. This study looks toward identification of the critical project success (CPS) factors which enhance construction project success through the study of prior data and project management theory. Similarly, from literature review and related case studies, the major risk factors in Indian construction projects are pinpointed. By linking the identified CPS factors with the significant risks, the study maps the critical enablers of success in the Indian construction industry and establishes that the major success determinants are both tangible and intangible in nature. These identified enablers of success are listed and categorised as per their area of project influence. The above findings are validated through a targeted questionnaire survey of key stakeholders, and the CPS factors are ranked as per their importance for project success. The study determines that the major factors which augment the chances of successful project delivery include effective stakeholder engagement, efficient project management processes, fulfilment of project specific requirements, proactive organisational procedures, and adept leadership. The research aims to enhance construction project achievement in the Indian scenario through identifying the critical factors promoting fruitful project completion. S. J. Chacko (B) · C. Nangia Amity School of Architecture and Planning, Amity University, Noida, India e-mail: [email protected] C. Nangia e-mail: [email protected] R. S. Rai Amity International Business School, Amity University, Noida, India e-mail: [email protected] V. Ahuja National Institute of Design Haryana, Kurukshetra, India e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_23
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Keyword Project success factors · Construction management · Project risks
1 Introduction Construction projects worldwide are exposed to numerous uncertainties which make them vulnerable to project failure. Projects of the built environment, according to Zawawi et al. [1], consist of numerous inter-linked processes. These processes are aligned to be flexible in their implementation and dynamic as per the evolution of the project, requiring the project manager to take suitable key decisions in accordance with the need and development of the work. Lapses in project operations can increase the susceptibility of construction projects to threats generated by the complexity of the construction process involving differing work typologies, project characteristics, multiple stakeholder expectations and organisational factors. The large failure rate of construction ventures is depicted through examples from across all over the world. Rivera et al. [2] in their global study on the performance of the construction industry noted that about 72% of projects face delays and that about 63% of them suffer cost overruns. In India, the data from the Flash report of the Ministry of Statistics and Programme Implementation [3] of the Government of India dated March 2021 depicts that out of a total of 1737 construction projects, each of value over 150 crore rupees, almost 32% face time delays and 84% experience cost overruns. These alarming facts confirm the dire need to improve the chances for success in construction delivery. Understanding the concept of project success and factors which contribute to it can help to reduce potential failures. This in turn raises the chances of project realisation. There is considerable academic debate on what defines project success. According to Belassi [4], a project is considered successful if it achieves its objectives whilst De Wit [5] observed that project management does not necessarily lead to project success. Munns and Bjeirmi [6] inferred that the “iron triangle” parameters of time, cost, and quality compliance are “short-term” success measures which are easily quantifiable on project completion. However, the “long-term” measures of success such as the perceived value of the project and stakeholder satisfaction are validated over the lifecycle of the project and are equally relevant for success. Kumar [7] observed that all the key stakeholders have a role in the success definition of a project in relation to their perceptions and expectations. Therefore, the perception of project success has evolved over time towards a complex multidimensional concept which embraces both quantitative and qualitative aspects [8]. The qualitative aspects include the satisfaction of stakeholder expectations, effective venture stewardship as well as external environmental and organisational aspects. Though the success definition criteria of construction projects of different typologies and complexities can be similar, the CPS factors which facilitate and improve project performance may vary greatly [9]. Several studies have attempted to identify these CPS factors which serve as “enablers” for effective project completion.
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Whilst it is widely accepted that project management techniques and tools are key aids to success [7], they need not be the sole enablers of it [5]. Current thinking projects project success as an outcome of quantitative and qualitative aspects [10]. Whilst many models for mapping CPS criteria exist, there is greater acceptance at present for models such as the Project Excellence Model (PEM) of Westerveld [11] and the Project Management Performance Assessment (PMPA) model of Bryde [10] which integrate project management (PM) concepts with the total quality management (TQM) approach through connecting project processes with continuous improvement and value addition [12].
2 Methodology The research looks towards deriving the CPS criteria which are significant to the Indian construction industry through inquiry into prior research on success factors in construction projects and the most prevalent causes of construction project failure in India. These findings are validated by mapping the views of key stakeholders in the construction domain. The initial part of the research pertains to the identification of CPS factors which are relevant to construction project achievement. These CPS factors or “success enablers” are identified from a systematic study of data and project management theory. The pin-pointed factors are drawn from their prevalence in the data studied. Based on their area of project influence, the mapped CPS components may be classified into two categories of “task-oriented” quantitative measures which are tangible as well as measurable or as “psycho-social” qualitative factors which are intangible as depicted in Fig. 1. The first category of “task-oriented” short-term measures includes project management processes which ensure adherence to the time, cost, and quality targets of individual projects. The second category of “psycho-social” factors is long-term measures of project performance assessed over the life cycle of the project and can be further subdivided as stakeholder-related characteristics, organisational factors, project specific aspects, leadership criteria and external influences on the project. The next stage of the research maps the major threats which impact construction projects in India through a systematic analysis of prior research and related case studies. Based on an analysis of data related to the causes of construction project failure, the critical threats are derived as per their prevalence in the literature. These risk factors or critical project failure (CPF) factors are also categorised as per the functional project area which they impact. The CPF risks are linked to the related CPS determinants to identify the crucial limitations which impact project success in the context of the Indian construction industry. To further substantiate and validate the findings from the literature study, a targeted questionnaire survey of key stakeholders and experts from the Indian construction industry is performed to understand the critical project success factors. The survey respondents include experienced professionals from the construction industry who
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Identification of Critical Succes Factors impacting Construction projects from prior data and project management theory.
Categorisation of the identified Success factors as per their area of functional impact
Mapping Success
of
Critical
Factors
to
Significant risks faced
Targeted questionnaire
Identification of the
survey of key stake-
short
holders and experts to
improvements
comings
and in
validate findings from
in Indian construction
success
factors
data study related to
projects
quired
to
enable
critical project success
success
in
Indian
determinants
construction projects
re-
Categorisation of the identified Failure factors as per their area of functional impact
Identification of Critical Risks or Failure Factors impacting Construction projects in India from prior data and Case Studies.
Fig. 1 Outline of research methodology
provide expert practical insight into the key areas which enhance construction project achievement. Based on the CPS factors identified from the literature review, the respondents are requested to rate the importance of each CPS factor on a scale of 1 to 5. This rating score signifies the importance of the specific CPS factor to construction project success in the Indian context, where a score of 1 shows very low significance, and 5 indicates very high significance. The research intends to provide knowledge on critical areas where the construction industry can improve in current practice and also generates awareness regarding the crucial success determinants for construction projects.
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3 Findings from the Study From the systematic analysis of the data, it is inferred that determinants of project success can vary with respect to project specifics, project environment, organisational aspects and external influences. The Project Excellence Model (PEM) of Westerveld [11] groups success factors under the two umbrellas of organisational leadership and project results. Gross and Wehnes [13] noted that “project definition” or the understanding of the project goals and objectives was a key success enabler [13]. Shamim [14] categorised CPS factors as dependent variables which are within the control of the project team or independent factors which are beyond the control of the project team. Alias et al. [1] included human factors and external factors as success enablers. Bryde [10] classified CPS determinants as either “subjective” factors which support the project or “objective” factors which are key success indicators. Aneesha et al. [15] expressed the importance of “psycho-social” aspects such as stakeholder engagement in facilitating project success. Atkinson [8] in his study stated that organisational aspects are important to project delivery. Stevens (1996) [16] suggested that CPS factors be segregated as “quantitative” factors which are indicative of project management competency or “qualitative” measures which showcase performance. Munns and Bjeirmi [6] proposed the “3 factor indicators” of project success as those related to implementation efficiency, the perceived project value, and client satisfaction. Gudiene [17] considered project specific factors and stakeholder satisfaction indicators as key factors to success. Therefore, the factors which facilitate project performance can be differentiated as either “output”-based measures related to short-term target achievement or “outcome”-based indicators of long-term benefits endowed by the project. Table 1 lists the key project success factors which are differentiated as “output-related or task-oriented” factors and “outcome-related or performance oriented” factors. The CPS factors thus differentiated are further grouped in accordance with the functional areas they impact. The subsequent part of the study relates to the mapping of the major project risks or critical project failure (CPF) factors in construction projects through the examination of prior research and related case studies of construction projects. The identified CPF factors are linked to the associated CPS components in terms of their ability to prevent the occurrence of the specific risk. Table 2 shows the linkages between the CPF risks and the CPS factors. In the last stage of the research, the questionnaire survey resulted in data being collected from 25 key stakeholders in the construction industry including architects, designers, engineers, consultants, project managers, and contractors amongst others. For each CPS factor, the individual scores related to its impact on project success were collected from each of the respondents on a scale of 1 to 5. For each CPS factor, the scores from various respondents were evaluated to a single indicator or index of its relevance to construction project success (R), calculated as below:
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Table 1 Critical project success factors identified from literature CPS factor type
Critical project success (CPS) factors as per category
References
Output or task-oriented
1. Project management efficiency: • Project management tools, methods, and processes • Budget finalisation and cost management • Work flow and time schedules • Quality definition and acceptance criteria • Monitoring and control • Knowledge management and documentation • Procurement and resource management • Contract management • Risk management • Handover procedures
[4, 5, 8, 10, 15, 18–20]
Outcome or 2. Stakeholder management: performance oriented • Coordination and collaboration with multiple teams • Communication protocol and information management • Client engagement and sign off • Stakeholder satisfaction and ownership • Customer/User delight • Recruitment and employee development 3. Organisation for project management: • Organisation, culture, and processes • Top management support • Decision-making processes • Organisational use of tools and methods, e.g. ERP
[4, 9–11, 15, 18–20]
[4, 8, 10, 11, 15, 18, 21]
4. Project specific criteria: [4, 11, 14, 15, 18, 20] • Project feasibility • Definition of project goals and objectives • Definition of performance indicators • Project typology, complexity, and lifecycle 5. Project leadership: • Strategy creation and communication • Project coordination and team building • Negotiation • Delegation • Trouble shooting
[5, 10, 11, 14, 15, 18–22]
(continued)
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Table 1 (continued) CPS factor type
Critical project success (CPS) factors as per category
References
6. External factors: • Policies and regulatory compliance • Economic, social, and political influences • Environment consideration and sustainability • Resource availability • Market competition • Access to funding • Technology availability • Natural forces
[4, 10, 14, 15, 18, 20],
Sum of respondent scores obtained for each CPS factor Highest possible score for the CPS factor ∑n (xn) or R = i=1 5n
R=
(1)
where R = Rank index of the individual CPS factor showing its importance to project success x = The scores provided by individual respondents for each CPS factor. n = Total number of respondents who provided scores for the CPS factor. Based on the analysis of data from the questionnaire survey, the rank index (R) of each CPS factor is evaluated as an indication of its relevance towards project success and is shown in Fig. 2.
4 Inferences and Recommendations The inferences drawn from the literature study on CPS factors depict that whilst the traditional “iron triangle” measures of project success related to time, cost, and quality management are important, the qualitative “outcome”-based aspects such as stakeholder management, project leadership and teamwork, organisational aspects, project specific criteria, and external factors are also critical success enablers. Through the identification of the critical risks affecting construction project success in India, it is understood that project failure is the result of lapses in one or more major enablers of success. These lapses pertain to the poor implementation of project management and the inefficiency of project organisational processes. Other major threats identified relate to ineffective project stewardship and the lack of stakeholder engagement. On a lesser scale, the lack of clarity in project definition and
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Table 2 Critical risks in Indian construction projects linked to CPS factors Critical project failure (CPF) risk factors identified
Critical project success (CPS) factors
1.Project feasibility is not prepared or incorrect [23, 24, 25, 26, 27]
✓
✓
✓
2. Site investigation information not available [24–27]
✓
✓
✓
Project Stakeholder Organisation Defining Project External management management and project leadership factors efficiency processes specific criteria
3. Poor ✓ coordination and collaboration on project [23–26, 28]
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
4.Lack of communication protocols and information management [23–26, 28] 5. Inadequate project leadership [24–26, 28]
6. Claims and ✓ conflicts in project [23–26]
✓
✓
7. Less experience of designers and consultants [23, 27, 28] 8.Poor drawing delivery [23, 24, 26–28]
✓
9. Lapses in contractor selection process [24–27]
✓
10. Exclusion of critical clauses from contract [23–28]
✓
✓
✓
✓
✓
✓
✓
(continued)
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Table 2 (continued) Critical project failure (CPF) risk factors identified
Critical project success (CPS) factors Project Stakeholder Organisation Defining Project External management management and project leadership factors efficiency processes specific criteria
11. Specifications, ✓ work method, and quality criteria missing in contract [23–26, 28]
✓
✓
✓
12. Time schedule is not part of contract [24–27]
✓
✓
13. Incorrect technology selection [23, 24, 26]
✓
✓
✓
14. Impractical time scheduling [24–28]
✓
✓
✓
✓
15. Incorrect budgeting [23–25, 27, 28]
✓
✓
✓
✓
16. Poor ✓ synchronisation of procurement, information, and aligned schedules [23, 24, 26, 28]
✓
17. Poor productivity [23, 26–28]
✓
✓
18. Inefficient site planning [23, 24, 26, 28]
✓
19. Poor quality materials usage [23, 25, 26, 28]
✓
✓
✓
20. Project scope variations [23–27]
✓
✓
✓
21. Defects in work execution [23, 24, 26–28]
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
(continued)
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Table 2 (continued) Critical project failure (CPF) risk factors identified
Critical project success (CPS) factors
22. Inefficiencies in contract execution and administration [23–28]
✓
✓
✓
✓
23. Lack of work ✓ supervision and checks [23–25, 27, 28]
✓
✓
✓
24. Deficiency in safety provisions [24–28]
✓
✓
✓
✓
✓
25. Risk management not incorporated [23, 26–28]
✓
✓
✓
✓
✓
26. Land acquisition time overruns [23, 24]
Project Stakeholder Organisation Defining Project External management management and project leadership factors efficiency processes specific criteria
✓
✓
✓
✓
27. Commodity price variation [24–28] 28. Government regulatory or policy changes [23, 25–28]
✓
✓
29. Difficulty in sourcing skilled workers [23–28]
✓
✓
✓
✓
✓
✓
30. Difficulties in accessing funding [23, 24, 26–28] 31. Nature-related factors [23–27] 32. Political climate risks [23, 24, 26, 28]
✓
✓
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CPS FACTORS FOR PROJECT MANAGEMENT (PM) EFFICIENCY 1. CPS FACTORS FOR PROJECT MANAGEMENT (PM) EFFICIENCY N O.
1a 1b 1c 1d 1e 1f 1g 1h 1i 1j
R A N KIN G IN D E X ( R )
C P S F A C T OR
PM tools methods and processes Budget finalisation and Cost management Work flow and time schedules Quality definition and acceptance criteria Monitoring and Control Knowledge management & documentation Procurement and resource management Contract management Risk management Correct handover procedures
0.79 0.81 0.88 0.88 0.88 0.86 0.85 0.85 0.82 0.87
PM tools methods and processes Correct handover procedures
0.9
Budget finalisation and Cost management
0.85 0.8
Risk management
Work flow and time schedules
0.75 0.7
Quality definition and acceptance criteria
Contract management Procurement and resource management
Monitoring and Control Knowledge management & documentation
CPS FACTORS RELATED TO STAKEHOLDER MANAGEMENT Coordination and collaboration with multiple…
2. CPS FACTORS FOR STAKEHOLDER MANAGEMENT
0.9 Recruitment and employee development
0.85 0.8
Communication protocol and information management
2c Client engagement & signoff
0.75 Client engagement & signoff
Customer delight
RANKING INDEX (R) NO. CPS FACTOR 2a Coordination and collaboration with multiple teams 0.89 2b Communication protocol and information 0.86 management 0.89
2d Stakeholder satisfaction and ownership
0.86
2e Customer delight
0.88
2f Recruitment and employee development
0.8
Stakeholder satisfaction and ownership
3. CPS FACTORS FOR PROJECT MANAGEMENT ORGANISATION RANKING INDEX (R) NO. CPS FACTOR 3a Organisation culture and processes
0.78
3b Top management support
0.85
3c Decision making process
0.83
3d Organisational use of tools such as ERP
0.74
CPS FACTORS FOR PROJECT MANAGEMENT ORGANISATION Organisation culture and processes
Organisational use of tools such as ERP
0.85 0.8 0.75 0.7 0.65
Top management support
Decision making process
Fig. 2 Rank index of categorised CPS factors as per relevance to project success
related objectives as well as uncertainties related to external project factors also fuel chances of project failure. A majority of the risks occur due to poor implementation of project management processes in combination with slippages of other success criteria. This represents a need to improve the management processes of projects alongside improving the delivery of other important outcome-based criteria. The analysis of the feedback from expert stakeholders collected through the targeted questionnaire survey strengthens the above findings. The most significant
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CPS FACTORS FOR PROJECT SPECIFIC CRITERIA
4. CPS FACTORS FOR PROJECT SPECIFIC CRITERIA RANKING INDEX (R) NO. CPS FACTOR 4a Project Feasibilty Definition of project goals & 4b objectives Definition of performance 4c indicators 4d
Project Feasibilty
0.9
0.84 0.88 0.81
Project typology, complexity and lifecycle
0.8 Project typology, complexity and lifecycle
Definition of project goals & objectives
0.7
0.79
Definition of performance indicators 5. CPS FACTORS FOR PROJECT LEADERSHIP RANKING INDEX (R) NO. CPS FACTOR Strategy creation & 5a communication 0.8
CPS FACTORS FOR PROJECT LEADERSHIP Strategy creation & communication
Trouble shooting
0.9 0.85 0.8 0.75 0.7
Appropriate Delegation
Project coordination & team building
6a
CPS FACTOR Policies and regulatory compliance
RANKING INDEX (R)
0.79
5c Negotiation
0.77
5d Appropriate Delegation
0.83
5e Trouble shooting
0.86
6. CPS FACTORS FOR EXTERNAL FACTORS Policies and regulatory compliance
0.81
Economic, social and political 6b influences
0.73
6c Environment considerationand sustainability
0.73
Natural forces
6d Resource availability
0.81
6e Market Competition
0.78
Technology availability
1 0.8 0.6 0.4 0.2 0
0.88
6g Technology availability
0.76
Economic, social and political influences Environment considerationan d sustainability
Resource availability
Access to Funds
6f Access to Funds
6h Natural forces
Project coordination & team building
Negotiation
6. CPS FACTORS FOR EXTERNAL FACTORS NO.
5b
Market Competition
0.77
Fig. 2 (continued)
categories contributing to construction project success were ranked as stakeholder management, project management efficiency, and the clarity of project objectives. The CPS factors ranked as the most important were proper coordination and collaboration between the stakeholders and ensuring client engagement and sign offs on completion of the project stages. Other important CPS factors included defining the project and its objectives clearly, access to sufficient funds for the project, ensuring customer delight, meeting targets of time, cost, and quality as well as efficient monitoring of project works and processes. Proper handover at the completion of the works, defining communication protocols and information management, fulfilling
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stakeholder expectations and effective trouble shooting by the project team were also found to be very important for project success. Table 3 outlines the CPS factors in their grouped categories, with their individual ranking on their importance to project success.
5 Conclusions The conclusions to the research pertain to the identification of the significant CPS factors and deriving the more important CPS factors for Indian construction projects in lieu of the risks experienced and related stakeholder perceptions. It is found that 24% out of the total 33% of crucial success factors with ranks 1 to 10 lie within the categories of project management efficiency and stakeholder management. However, other select success enablers also included within the top ranked success enablers fall under the categories of project specific factors, external environment influences, and project leadership. These include clear definition of project specifics, good access to funds, and effective crisis management. Other components listed within the top 20 ranked enablers as important to project success include proper procurement and resource management, efficient contract administration, ensuring risk management practices, effective decision making, top management support, and appropriate delegation of work (Fig. 3). Table 3 Ranking of critical project success factors as success enablers Critical project success (CPS) factors
Rank index
Factor rank
1. Project management efficiency
Critical project success (CPS) factors
Rank index
Factor rank
4. Project specific criteria
a. Project management tools, methods, and processes
0.79
27
a. Project feasibility 0.84
17
b. Budget finalisation and cost management
0.81
21
b. Definition of project goals and objectives
0.88
3
c. Work flow and time schedules
0.88
3
c. Definition of performance indicators
0.81
21
d. Quality definition and acceptance criteria
0.88
3
d. Project typology, 0.79 complexity, and lifecycle
27
e. Task monitoring and control
0.88
3 (continued)
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Table 3 (continued) Critical project success (CPS) factors
Rank index
Factor rank
f. Knowledge management and documentation
0.86
10
g. Procurement and resource management
0.85
14
h. Contract management
0.85
14
i. Risk management
0.82
20
j. Handover procedures
0.87
9
2. Stakeholder management
Critical project success (CPS) factors
Rank index
Factor rank
5. Project leadership
a. Coordination and collaboration 0.89 with multiple teams
1
a. Strategy creation 0.80 and communication
25
10
b. Project coordination and team building
0.79
27
c. Client engagement and sign off 0.89
1
c. Negotiation
0.77
32
d. Stakeholder satisfaction and ownership
0.86
10
d. Delegation
0.83
18
e. Customer/User delight
0.88
3
e. Trouble shooting 0.86
10
f. Recruitment and employee development
0.80
25
b. Communication protocol and information management
0.86
3. Organisation for project management
6. External factors
a. Organisation, culture, and processes
0.78
30
a. Policies and regulatory compliance
0.81
21
b. Top management support
0.85
14
b. Economic, 0.73 social, and political influences
36
c. Decision-making processes
0.83
18
c. Environment consideration and sustainability
0.73
36
d. Organisational use of tools and 0.74 methods, e.g. ERP
35
d. Resource availability
0.81
21
e. Market competition
0.78
30
f. Access to funding 0.88
3
g. Technology availability
0.76
34
h. Natural forces
0.77
32
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CPS factors ranked highest in importance to project success
The research on critical project success (CPS) factors highlights the deficiencies in success facilitating processes which impact construction project success in India. The inferences, both from the prior data analysed and the survey mapping stakeholder perceptions, depict that success is multifactorial depending both on project management efficiency as well as performance-based aspects related to stakeholder engagement, project definition, effective leadership, and organisational processes. However, current construction practice focuses less on these long-term measures of success, thereby negatively affecting the performance of construction projects. It is recommended that more weightage be given to outcome-based definers of project achievement such as user delight, sustainability, and stakeholder satisfaction which are important over the life cycle of the project. Therefore, whilst raising the standards of project management implementation in built environment projects would greatly augment the chances of their success, this would have to be done alongside with the improvements of outcome-based determinants to ensure meaningful success.
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References 1. Alias Z, Zawawi EMA, Yusof K, Aris NM (2014) Determining critical success factors of project management practice: a conceptual framework. Procedia Soc Behav Sci 153:61–69. https:// doi.org/10.1016/j.sbspro.2014.10.041 2. Rivera A, Le N, Kashiwagi J, Kashiwagi D (2016) Identifying the global performance of the construction industry. J Adv Perform Inf Value 8:7. https://doi.org/10.37265/japiv.v8i2.61 3. Ministry of Statistics and Program Implementation—Government of India, Flash Report, Project V (2021) 422nd Flash Report On Central Sector Projects (Rs.150 crore and above). http://www.cspm.gov.in/english/flr/FR_Apr_2021.pdf 4. Belassi W, Tukel OI (1996) A new framework for determining critical success/failure factors in projects. Int J Project Manage 14(3):141–151 5. de Wit A (1988) Measurement of project success. Int J Project Manage 6:164–170. https://doi. org/10.1016/0263-7863(88)90043-9 6. Munns AK, Bjeirmi BF (1996) The role of project management in achieving project success. Int J Project Manage 14(2):81–87 7. Kumar D (1989) Developing strategies and philosophies early for successful project implementation. Int J Project Manage 7:164–171. https://doi.org/10.1016/0263-7863(89)90035-5 8. Atkinson R (1996) Project management: cost, time and quality-other success criteria. Int J Project Manage 17:337–342 9. Alotaibi AB, Nufei EngAF al (2014) Critical success factors (CSFS) in project management: critical review of secondary data. Int J Sci Eng Res 5:325–330 10. Bryde D (2008) Perceptions of the impact of project sponsorship practices on project success. Int J Project Manage 26:800–809. https://doi.org/10.1016/j.ijproman.2007.12.001 11. Westerveld E (2003) The project excellence model®: Linking success criteria and critical success factors. Int J Project Manage 21:411–418. https://doi.org/10.1016/S0263-7863(02)001 12-6 12. Pinto JK, Mantel SJ (1990) The causes of project failure. IEEE Trans Eng Manage 37:269–276. https://doi.org/10.1109/17.62322 13. Gross B, Wehnes H (2015) The project excellence model revised. In: IPMA 29th world congress. Panama 14. Mahfuzul Islam Shamim M (2022) Exploring the success factors of project management. Am J Econ Bus Manage 5(7):64–72 15. Aneesha K, Haridharan MK (2017) Ranking the project management success factors for construction project in South India. IOP Conf Ser: Earth Environ Sci. Institute of Physics Publishing 16. Stevens JD (1996) Blueprint for measuring project quality. J Manag Eng 12:34–39. https://doi. org/10.1061/(ASCE)0742-597X(1996)12:2(34) 17. Gudiene N, Banaitis A, Banaitiene N, Lopes J (2013) Development of a conceptual critical success factors model for construction projects: a case of lithuania. In: Procedia engineering. Elsevier Ltd, pp 392–397 18. Ofori DF (2013) Project management practices and critical success factors–a developing country perspective. Int J Bus Manage 8. https://doi.org/10.5539/ijbm.v8n21p14 19. Chan APC, Chan DWM, Chiang YH et al (2004) Exploring critical success factors for partnering in construction projects. J Constr Eng Manage 130:188–198. https://doi.org/10.1061/ (asce)0733-9364(2004)130:2(188) 20. Mir FA, Pinnington AH (2014) Exploring the value of project management: linking project management performance and project success. Int J Project Manage 32:202–217. https://doi. org/10.1016/j.ijproman.2013.05.012 21. Iyer KC, Jha KN (2005) Factors affecting cost performance: evidence from Indian construction projects. Int J Project Manage 23:283–295. https://doi.org/10.1016/J.IJPROMAN.2004.10.003 22. Belout A, Gauvreau C, Arias JT et al (2014) Factors in project success. Prepared for: The Association for Project Management (APM). Int J Project Manage 11
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23. Debalina BC, Putta J, Rama Mohan Rao P (2021) Risk identification, assessments and prediction for mega construction projects. Buildings 24. Doloi H, Sawhney A, Iyer KC, Rentala S (2012) Analysing factors affecting delays in Indian construction projects. Int J Project Manage 30:479–489. https://doi.org/10.1016/J.IJPROMAN. 2011.10.004 25. Sharan Kumar K, Narayanan RM (2021) Review on construction risk and development of risk management procedural index—a case study from Chennai construction sector. Mater Today Proc 43:1141–1146. https://doi.org/10.1016/J.MATPR.2020.08.606 26. Konde Virak, Munde Pravin (2017) Identification and assessment of risks in construction projects. Int J Eng Sci Comput 7 27. Senthil J, Muthukannan M (2021) Predication of construction risk management in modified historical simulation statistical methods. Ecol Inform 66:101439. https://doi.org/10.1016/J. ECOINF.2021.101439 28. Metha RL, Gaikwad SV (2017) Delays and its analysis: Indian residential construction projects. https://doi.org/10.6106/JCEPM.2017.7.4.020
Effects of Confining Pressure on Intact Rocks’ Anisotropy Bharti Chawre
and Sachin Gupta
Abstract A “pattern” in the rock material, such as schistosity, foliation, or bedding, frequently causes anisotropy, which makes the qualities of the rock’s material directional dependent. Generally, rocks’ mechanical characteristics are described in the terms of strength. Therefore, in this study, only this parameter is taken to reflect the anisotropy. The strength anisotropy of intact rocks is prominently affected by the orientation angle and the magnitude of the confining pressure. So, in this study, three types of metamorphic rocks (schists, genies, and quartzite) from project sites in the Himalayan region have been examined by two different methods to ascertain the effect of the confining pressure (σ 3 ) on strength anisotropy. These methods are based on calculating the intensity of the strength anisotropy. (K 1 ) and the coefficient of strength anisotropy ( f ). The results of this study show that the confining pressure has a significant impact on strength anisotropy. As the confining pressure increases, the laminated structure of the rock samples consolidates and starts to behave like an isotropic material, which reduces the anisotropy effect. It has also been noted that schist and gneiss’s behaviour is almost identical to both of the proposed methods, except for quartzite. This study suggests that even for rocks with the same lithology, not all types of rocks can be predicted accurately by the general equation. To find other parameters, additional research is necessary. Although anisotropy can be crucial to the stability of underground excavations and subsequent geotechnical design, anisotropic properties of the rock are typically not taken into account in geotechnical designs. However, analytical techniques should take strength anisotropy into account in order to predict failure processes. Keywords Anisotropy · Strength anisotropy · Confining pressure · Gneiss · Quartzite · Schist
B. Chawre (B) · S. Gupta Central Soil and Materials Research Station, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_24
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1 Introduction Rock, a naturally occurring solid material, has inherent anisotropy due to various geological processes, its mode of formation, and settlement. Generally, there are two types of anisotropy first inherent and second induced. This anisotropy depends on the distribution, density, and orientation of these microscopic cracks, fissures, joints, beds, foliage, fractures, and minerals in addition to their presence. Shale, sandstone, salt, and schist rocks show the highest degree of anisotropy and exhibit this pattern more significantly.
1.1 Rocks’ Anisotropic Behaviour and Classification Generally, anisotropy is defined as a mechanical property of rocks, due to which the rock’s mechanical properties vary in all directions. From the strength point of view, anisotropic rocks can have much lower strength when loaded along their weak orientation than quasi-isotropic rocks, which have identical strength properties in all directions. It is generally caused by some typical “pattern or fabric” in rocks, like schistosity, foliation, or bedding, and the presence of flaky and elongated minerals in the rocks is usually responsible for the anisotropic behaviour. Even at the scale of a laboratory test specimen, this effect appears to be significant [1, 2]. Rock material usually shows two different types of anisotropy: (1) intact rocks’ anisotropy and (2) rock-masses anisotropy. In general, intact rocks’ anisotropy is caused by schistosity, foliation, and bedding. This contributes to directional dependence on very small scales, even in homogeneous, intact anisotropic rocks. In contrast, rock-mass anisotropy is large-scale and frequently occurs due to the presence of discrete and persisting joints in the rock-mass. Rock-mass anisotropy arises when constituent rocks show intact rock anisotropic behaviour. The mineral composition of a rock and the geological processes that create it governs its anisotropic behaviour, if minerals with substantial anisotropic characteristics are included, it may result in anisotropic behaviour in rock. Rock anisotropy is caused by flaky silicates, such as mica or clay minerals, which are orientated mainly during sedimentation (lamination, bed floor) or during metamorphosis (schistosity/foliation). Due to foliations and bedding, metamorphic rocks (phyllites, shales, schists, slates, and gneisses) are the most common rocks that possess anisotropy. Marbles may have a low degree of anisotropy, but overall behaviour is usually isotropic. Due to bedding planes, anisotropy in sedimentary rocks (siltstones, clay stones, and mudstones) is very common. However, sandstone and limestone possess moderate anisotropy because of the cementation of their rock-forming minerals. Due to the presence of flow structure, such as in rhyolites, anisotropy can be observed in igneous rocks too [3]. Basically, anisotropy is a characteristic of both metamorphic and sedimentary rock types. Even though isotropic behaviour is frequently seen in igneous rock types like granite and diorite, may be fluidal magmatic processes can also result in anisotropy in those rock types.
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Several indices have been proposed for classifying the inherent anisotropy of intact rocks, and they are categorised as follows: • Strength Anisotropy: this type of anisotropy can be prominently seen in some intact rocks because they contain flat minerals like mica, chlorite, and clay. • Deformability Anisotropy (Stiffness Anisotropy): Strong deformability anisotropy is seen in rocks from the sedimentary and metamorphic groups, including gneiss, sandstone, shale, limestone, schist, and slate. • Permeability Anisotropy: Rock orientations and micro-discontinuities cause significant permeability anisotropy in the rocks [4]. • Pulse Wave Velocity Anisotropy (Seismic Anisotropy): Velocity measurements in two or three mutually perpendicular directions were initially used to determine the anisotropy of ultrasonic wave velocity. According to numerous research that has been published, anisotropy in wave velocity is the variation in velocities with respect to the direction of measurement for the specimens. The ratios of maximum to minimum velocities have been used by researchers to quantify anisotropy [5].
2 Strength Anisotropy Review The mechanical behaviour of rock is primarily represented by strength, and many researchers have worked on the challenge of quantifying the strength anisotropy of various rock types, e.g. on shales, slates, gneisses, schists, and phyllites, on sandstones [6–8]. Schistose rocks such as phyllites and schists present a different behaviour from that of intact rock under uniaxial compression. Failure in such rocks can occur either along clearly defined structural features or through the intact rock pieces themselves. “Where the rock pieces are small compared to the size of the structure being analysed, it is reasonable to assume that there will always be a sufficient number of critically oriented pieces in the rock-mass and that failure of these pieces will occur along the schistosity” [9]. The two main parameters that prominently affect the strength anisotropy are the direction of the material bedding plane with the major principal-stress and the magnitude of the confining pressure. The maximum strength is often achieved when the applied load has an orientation of (90° and 0°) with the bedding plane, but the smallest strength has been observed between orientations of (30° and 45°). In general, various researches illustrate that the graph between the compressive strength and the orientation angle can be used to determine the strength anisotropy. Based on the pattern of these graphs, anisotropy is classified into three types of anisotropy: “undulatory type”, “U type”, and “shoulder type” as shown in Fig. 1 [10]. Table 1 shows the categorization of anisotropy based on the studies of many researchers [1, 10–13]. Niandou [14] represents the anisotropy of shale by two types of ratios. The first ratio K 1 is assumed to be equal to the ratio between the failure load in parallel and perpendicular directions to the bed, and the second ratio, K 2 , represents the relationship between both the highest and lowest values of the failure load in all test orientations. Tien [16] developed and analysed an artificial inter-bedded rock
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Fig. 1 Anisotropy patterns. Source [10]
Table 1 Classification of anisotropy intensity [15]
Anisotropy. classification
Anisotropy factor
Isotropic
1.0–1.1
Low-anisotropy
1.1–2.0
Medium-anisotropy
2.0–4.0
High-anisotropy
4.0–6.0
Very-high-anisotropy
More than 6.0
model to apply a failure criterion and studied the effect of confining pressure on the strength anisotropy of rocks. The relation between anisotropy strength (K 1 ) and confining pressure (σ 3 ) is correlated and illustrated by Cheng [17], in the study, a linear correlation was obtained and a study indicating that the strength anisotropy is inversely proportional to the confining pressure. In addition, Cheng [18] evaluated strength anisotropy of nine different shell types by two equations, as shown in Table 2.
3 Influence of the Confining Pressure on Anisotropy. The anisotropy decreases as confining pressure increases represented by various researchers, and variations of inherent anisotropy with confining pressure for various rocks have been studied by many shown in Fig. 2. In this figure, data of 15 anisotropic rocks are presented and show that the strength anisotropy deteriorates rapidly for compressive strength, and confining pressure (σ c /σ 3 ) ratio is less than 5. Majority of the rocks when this ratio is equal to 1 (σ c /σ 3 = 1), and the influence of anisotropy is as low 10%, which may be considered negligible for most practical purposes. Under confining pressure higher than the compressive strength, one would therefore expect complete suppression of anisotropy. In the unconfined state of the rocks, anisotropy’s effect is maximum. The suppression of anisotropy is essentially due to the onset of the ductile response in the rock [20].
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Table 2 Strength anisotropy review S. No. 1
Formula K1 = K2 =
2 3 4 5 6
σ1−σ3 // ⊥ σ1−σ3 σ max 1−σ3 σ1−σ3 min
σc max σc min σ c90◦ Rc = σ c ◦ 60 σ max K 1 = σ1−σ3 min 1−σ3
Rc =
(σ 1 max −σ 1 min) σ 1 max SA1 = σσ 11 max min
f =
Range
Rock type
K 1 ≈ (0.75–1)
Shale
K2 ≈ (1.4–1.55) Rc ≈ (7–14)
Angers schist
Rc ≈ (1.5–2.25)
Artificial inter-bedded rock model
K1 ≈ (2–3.5)
Coal measure shale Long maxi black organic-rich shale Nine types of shale
SA2 = σ1 max−σ1 min Note References [5, 14, 16, 19]
Fig. 2 Variation of inherent anisotropy with confining pressure [19, 21–23]
4 Test and Methods In this study, three types of metamorphic rocks (schists, genies, and quartzite) from project sites in the Himalayan region have been tested for the triaxial compression test. Conventional triaxial compression tests are carried out on rock core samples of NX size, with length to diameter ratio of 2. Saturated specimens are tested in a Hoek’s triaxial cell. The triaxial cell is an apparatus, in which the test specimen is enclosed
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in an impermeable flexible polyurethane membrane, and is placed between two hardened platens, one of which is spherically seated. There is an arrangement for applying constant lateral fluid (oil) pressure to the specimen in the triaxial cell. After enclosing the specimen in the triaxial cell, the cell is placed in a compression-testing machine, and the specimen, under constant lateral hydraulic pressure, is loaded axially to failure. The specimens are tested under different lateral/confining pressures.
5 Results and Discussion Triaxial compression test was conducted, on schists, genies, and quartzite at confining pressure from 3.0 MPa to 11.0 MPa, and experimental data were obtained from these test results. In this research, two methods have been used to determine the effect of confining pressure on the inherent strength anisotropy of rocks. These methods are based on the calculation of the intensity of the strength anisotropy. (K 1 ) and coefficient of the strength anisotropy ( f ). The first method is provided by Nasseri [6], who defined the intensity the strength anisotropy (K 1 ) for the strength of transversely isotropic materials with the following two parameters: K1 =
(σ1 − σ3 ) max (σ1 − σ3 ) min
(1)
Term K 1 defines the ratio of the maximum to the minimum values of strength obtained from Eq. (1). The high values of the index mean high degrees of rock anisotropy and vice-versa. It has been seen from Fig. 3 that the value of K 1 is varying from 2.16 to 1.20 for confining pressures from 3 to 21 MPa for schist. Figure 3 also shows the quadratic relationship between K 1 , and the confining pressure in decelerated decline shape and the value of the correlation coefficient (R2 ) is 0.92. Similarly, for gneiss, K 1 is varying from 2.36, to 1.26 for confining pressure 3 to 11 MPa, respectively (Fig. 4), and Fig. 4 shows the quadratic relationship between K 1 and the confining pressure in an accelerated decline manner with R2 which is equal to 0.98. The same analysis was further extended for quartzite, and the values of K1 for this rock type are varying from 1.66 to 2.52 for confining pressure 2 to 6 MPa (Fig. 5), and it is found that Fig. 5 shows the quadratic relationship in accelerated inclined shape (R2 = 0.89) which is different from above two rocks. As can be seen from Fig. 6, under low confining pressure (up to 3 MPa), all specimens had moderate anisotropy K1 between 1.85–2.36, whereas K 1 decreased to below 2.0 at high confining pressures (above 7 MPa), which shows that the influence of anisotropy is low at high confining pressure. The second approach adopted for the calculation of the anisotropy define by the parameter f introduced by Wu [24], which is reflecting the coefficient of anisotropy of strength (Eq. 2), as follows:
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ROCK TYPE: SCHIST
Intensity of Anisotropy, K1
2.50
2.00
y = 0.004x2 - 0.1485x + 2.5713 R² = 0.9176
1.50
1.00
0.50
0.00 0.00
5.00
10.00
15.00
20.00
25.00
Confining Pressure in MPa Fig. 3 Variation of the intensity of strength anisotropy (K 1 ) with confining pressure (σ 3 ) for schist
ROCK TYPE :GNEISS Intensity of Anisotropy, K1
3.00
y = -0.0141x2 + 0.0481x + 2.395 R² = 0.9777
2.50 2.00 1.50 1.00 0.50 0.00 0.00
2.00
4.00
6.00
8.00
10.00
12.00
Confining Pressure in MPa Fig. 4 Variation of the intensity of strength anisotropy (K 1 ) with confining pressure (σ 3 ) for gneiss
f =
σ1,max −σ1,min σmax
(2)
where σ 1,max and σ 1,min are the maximum and the minimum values of the compressive-strengths (σ c ) under the same confining pressure (σ 3 ), respectively. It has been seen from the graphical representation of all rock types (Fig. 7) that the coefficient of strength anisotropy of schist under confining pressure of 3 MPa, f is 0.54, 0.58, and 0.68 for schist, gneiss, and quartzite, respectively, which is almost
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ROCK TYPE:QUARTZITE Intensity of Anisotropy, K1
3.00 2.50 2.00
y = 0.0204x2 + 0.0282x + 1.5517 R² = 0.8982
1.50 1.00 0.50 0.00 0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
Confining Presure in MPa Fig. 5 Variation of the intensity of strength anisotropy (K 1 ) with confining pressure (σ 3 ) for quartzite
3.00
INT ENSIT Y OF ANISOT ROPY QUARTZITE
Intensity of Anisotroy, K1
2.50
y = 0.0204x2 + 0.0282x + 1.5517 R² = 0.8982
2.00
1.50
1.00
SCHIST
GNEISS
y = 0.004x2 - 0.1485x + 2.5713 R² = 0.9176
y = -0.0141x2 + 0.0481x + 2.3951 R² = 0.9777
0.50
0.00 0.00
5.00
10.00
15.00
20.00
25.00
Confining Pressure in MPa Fig. 6 Variation of the intensity of strength anisotropy (K 1 ) with confining pressure (σ 3 ) for all three variants of rocks
the same for all three variants of metamorphic rocks. Whereas, when confining pressure is 6 MPa, anisotropy of strength f is 0.39, 0.55, and 0.43 for schist, gneiss, and quartzite, respectively. As a result, the effect of anisotropy on the gneiss is stronger than on schist and quartzite. At the higher confining pressure of 11 MPa, it is found
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that the anisotropy of strength ( f ) is 0.32 for schist, 0.21 for gneiss, and 0.19 for quartzite (Table 3). Therefore, at higher confining pressure, anisotropy of gneiss is lower than schist but stronger than quartzite. Variations of the strength anisotropy with confining pressure for all three rock variants are shown in Fig. 7. It is noticed in this research that the level of anisotropy of all three rocks variant decreased with an increase in the confining pressure which is investigated by various researchers too. ANISOTROPY OF STRENGTH 1.00
Anisotropy of Strength, f
Quartzite 0.80
y = 0.005x2 - 0.1322x + 1.0395 R² = 0.988
0.60
0.40 y = 0.0005x2 - 0.0336x + 0.6368 R² = 0.9193
0.20
R² = 0.9957
0.00 0.00
Gneiss
5.00
Schist
10.00
15.00
20.00
25.00
Confining Pressure in MPa Fig. 7 Variation of the strength anisotropy of strength ( f ) with confining pressure (σ 3 ) for all three variants of rocks
Table 3 Results from two methodologies (K 1 and f ) S. No.
Confining pressure
Gneiss K1
Gneiss f
K1
Quartzite f
K1
f
1
3
2.16
0.54
1.64
0.58
1.85
0.68
2
6
1.64
0.39
2.17
0.55
2.17
0.43
3
11
1.46
0.32
2.52
0.21
1.99 (extrapolated)
0.19 (extrapolated)
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6 Summary and Conclusions This study on schists, genies, and quartzite from the Himalayan region show that: • Strength anisotropy decreases continuously as the confining pressure increases because, as the confining pressure rises, the laminated structure of rock samples gets consolidated, thereby increasing the shear strength of the laminated structure (the weakest plane or the plane of failure) and begins to behave like an isotropic material, which reduces the effect of anisotropy. • Schists show the quadratic relationship between K 1 and the confining pressure in decelerated decline shape, whereas gneiss shows the quadratic relationship between K 1 and the confining pressure in accelerated decline shape, and the quadratic relationship in accelerated inclined shape is extracted between K 1 and the confining pressure for quartzite. • The coefficient of anisotropy of strength ( f ) under confining pressure of 3 MPa is 0.54, 0.58, and 0.68 for schist, gneiss, and quartzite, respectively, which is almost the same for all three variants of metamorphic rocks. • At the confining pressure of 6 MPa, it is found that the anisotropy of strength ( f ) is 0.39 for schist, 0.55 for gneiss, and 0.43 for quartzite. However, gneiss anisotropy is significantly stronger than the other two rock variants at this confining pressure. • The high confining-pressures of 11 MPa anisotropy of strength ( f ) for schist and gneiss are 0.32 and 0.21, respectively. Therefore, the anisotropy effects on gneiss are lower than that of schist under high confining pressure. Although no data were available for quartzite rocks at 11 MPa, the value of anisotropy of strength ( f ) at this pressure has been extrapolated from the quadratic equation (Fig. 7). • In this study, two methods have been used to see the effect of confining pressure on anisotropy. The behaviour of schist and gneiss is almost identical to both of the proposed methods, except for quartzite. General equations encompassing all types of rocks do not give reliable results even for rocks with the same lithology, more research is needed to identify additional parameters. Although anisotropy can be crucial to the stability of underground excavations and subsequent geotechnical design, and anisotropic properties of the rock are typically not taken into account in geotechnical designs. However, analytical techniques should take strength anisotropy into account in order to predict failure processes.
References 1. Palmström A (1994) RMi—a rock mass characterization system for rock engineering purposes. PhD thesis, University of Oslo, Norway 2. Brady BHG, Brown ET (2005) Rock mechanics for underground mining. 3rd edn, pp 117–119 3. Ajalloeian R, Lashkaripour G (2000) Strength anisotropies in mudrocks. Bull Eng Geol Env 59:195–199. https://doi.org/10.1007/s100640000055
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4. Ayan C, Colley N, Cowan G, Ezekwe E, Wannell M, Goode P, Halford F, Joseph J, Mongini A, Obondoko G, Pop J (1994) Measuring permeability anisotropy: the latest approach. Oilfield Rev 4:24–35 5. Nur A, Simmons G (1969) Stress-induced velocity anisotropy in rock: an experimental study. J Geophys Res 74(27):6667–6674 6. Nasseri MH, Rao KS, Ramamurthy T (2003) Anisotropic strength and deformational behavior of Himalayan schists. Int J Rock Mech Min Sci 40:3–23 7. Singh VK, Singh D, Singh TN (2001) Prediction of strength properties of some schistose rocks from petrographic properties using artificial neural networks. Int J Rock Mech Min Sci 38(2):269–284 8. Ramamurthy T, Rao GV, Nasseri MHB (1998) Anisotropic strength behavior of Himalayan schists. In: Proceedings of Indian geotechnical conference, Golden Jubilee, New Delhi, pp 335–338 9. Hoek E, Brown ET (1997) Practical estimates of rock mass strength. Int J Rock Mech Mining Sci 34:1165–1186 10. Ramamurthy T, Rao GV, Singh J (1993) Engineering behaviour of phyllites. Eng Geol 33:209– 225 11. Tsidzi KEN (1986) A quantitative petro-fabric characterization of metamorphic rocks. Bull Int Assoc Eng Geol 33:37–42 12. Tsidzi KEN (1987) Foliation index determination for fine-grained metamorphic rocks. Bull Int Assoc Eng Geol 36:277–333 13. Tsidzi KEN (1987b) Compressive strength anisotropy of foliated rocks. In: Symposium on mechanics of jointed and faulted rock, pp 4217–428 14. Niandou H, Shao JF, Henry JP, Fourmaintraux D (1997) Laboratory investigation of the mechanical behaviour of Tournemire shale. Int J Rock Mech Min Sci 34(1):3–16 15. Singh J, Ramamurthy T, Rao GV (1989) Strength anisotropies in rocks. Ind Geotech J 19(2):147–166 16. Tien YM, Kuo MC, Juang CH (2006) An experimental investigation of the failure mechanism of simulated transversely isotropic rocks. Int J Rock Mech Min Sci 43(8):1163–1181 17. Cheng J et al (2015) Experimental study on anisotropic strength and deformation behavior of a coal measure shale under room dried and water saturated conditions. Shock Vib 18. Cheng C, Li X, Qian H (2017) Anisotropic failure strength of shale with increasing confinement: behaviors. Factors and mechanism. Materials 10(11):1310. https://doi.org/10.3390/ma1011 1310 19. Duveau G, Shao J (1998) A modified single plane of weakness theory for the failure of highly stratified rocks. Int J Rock Mech Min Sci 35(6):807–813 20. Ramamurthy T (2007) Engineering in rocks for slopes foundations and tunnels, eastern economy edition. Prentice-Hall of India Pvt. Limited, ISBN 812033275X, 9788120332751 21. Chenevert ME, Gatlin C (1965) Mechanical anisotropies of laminated sedimentary rocks. pp 67–77 22. McLamore R, Gray K (1967) The mechanical behavior of anisotropic sedimentary rocks. J Eng Ind 89(1):62–73 23. Horino FG, Elickson ML (1970) A method of estimating the strength of containing planes of weakness. US Bureau of Mines, Report investigation 7449 24. Wu YW, Xiao L, Jianming H, Bo Z (2016) Mechanical properties of longmaxi black organicrich shale samples from south china under uniaxial and triaxial compression states. Energies 9(12):1–24
Crack Instigation and Propagation of Transversely Isotropic Biotite Gneiss Sachin Gupta, Sangeetham Aji, and Mahabir Dixit
Abstract The physical characteristics of a well-defined transverse isotropy plays a significant role in the determination of the indirect tensile strength of intact biotite gneiss. The mineralogical elements and its alignment in its gneissosity plane of this rock are accountable for the said phenomenon. Crack instigation and propagation toward the loading plane are an indicator of the tensile failure of the specimen, which is mandatory. An experimental investigation to determine the impact of transverse isotropy on crack instigation and its propagation on intact biotite gneiss has been studied considering seven various loading angles with respect to gneissosity plane. Also, the tensile strength analysis to study the validity of the crack instigation whether the accuracy of the crack instigation is from the center or the loading plane, as still there are various arguments among various researchers. This study infers that the positioning of the rock core with respect to the foliation plays a vital role in determining the strength of samples in tension indirectly. The maximum sample’s strength where the crack instigated at the center was obtained when the plane is at 0°, and minimum strength was observed when the plane is at 90°. Further, 60° to 90° angle provides the most conservative value of indirect tensile strength and has highest possibilities of tensile failure. Keywords Biotite gneiss · Indirect tensile strength test · Transverse isotropy · Crack instigation at their uniaxial tensile strength
S. Gupta (B) · S. Aji · M. Dixit Central Soil and Materials Research Station, New Delhi, India e-mail: [email protected] S. Aji e-mail: [email protected] M. Dixit e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_25
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1 Introduction Indirect tensile strength test by Brazilian method, governed by the ISRM [1], is the preeminent procedure to access the tensile strength of an intact rock core. Indirect tensile strength test is centered on the experimentally established fact according to which, in biaxial stress fields, rock (most of the rocks) fails in tension, when the magnitude of finite compressive principle stress does not exceed three times of other principal stress (which is tensile), and the tensile stress so recorded is equal to their corresponding uniaxial tensile strength. The authority of the test is formulated on the condition that the crack must instigate from center of sample and must propagate toward the loading plane; else the test is considered to be void. However, the elastic theory is employed for assessment of indirect tensile strength through Brazilian test despite the fact that the rock is discontinuum, inhomogeneous, anisotropic, and nonelastic (DIANE) and not continuum, homogeneous, isotropic, and linearly elastic (CHILE) as is needed for application of elastic theory. This paper studies the crack instigation and propagation of the intact biotite gneissic rock specimen having a well-defined gneissosity plane. The indirect tensile strength is a vital part of the resistance of an intact rock or a rock mass to fail where crack instigation plays vital role in assessment of tensile strength. An enhanced understanding of the crack instigation and failure pattern is prepared for the transversely isotropic intact biotite gneissic rock for an accurate understanding of the strength parameter of different angles. The strengths of the various civil engineering issues occurring in borehole, stability of slope, underground excavations in tunnel engineering, etc., are affected by the transverse isotropy of rock [2]. Therefore, the study of properties on transverse isotropy of rock is a must to know about the characterization of such rocks. In general, it is found that the indirect tensile strength and the crack instigation depend on the orientation of rock foliation and angle of loading. However, crack instigation and propagation conception have continuously remained under heated discussion for decades. Different experimental observations from various researchers, intellectuals, and scientist have been undertaken to study the above said concept. Failure criterion theory proposed by Griffith (corrected) states that fracture must instigate from center of specimen [3]. Tensile strength for various materials was studied and proved that indirect tensile test is appropriate for assessing the values of uniaxial tensile strength [4]. Strain gauges were used for crack instigation and reported that initial crack does not start from point of instigation of stress but from zone of maximum tensile stress, i.e., center of specimen [5]. Subsequently, concept of crack instigation at center was evidently supported by Chen, Cai and Kaiser, Van De Steen, Zhu and Tang [6–9]. For minor angles of loading material with lesser ratio compression and tension, the crack instigation intends to be away from the center of the loading plane [10]. The concept of crack instigation from the center was not favored by many researchers [11, 12]. Brazilian test and the concept of crack instigation on transversely isotropic rocks were studied by many researchers, namely Chen, Claesson, Exadaktylos, Cai,
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Chou Tavallali, and Xin Tan [6, 7, 13–17]. Suggestions were made for clear depiction of stress and strains at any random point in the loading plane [18–20]. Indirect tensile strength of various rock cores has an effect of transverse isotropy. Hence, isotropic elastic solutions are not suggested for verifying the investigation on anisotropic rock cores. When the tensile stress meets the extreme tensile strength condition on the surface center, crack initiation point of the Brazilian test for rock cores is found near the loading plane. This phenomenon occurs only when the tensile strain meets the extreme limit of strain condition. Bearing capacity and failure pattern observed in the Brazilian tests for anisotropic rock cores are highly influenced by the micro-parameters. As the foliation angle increases (θ = 15°, 30°, 45°), shear failure pattern occurs along the schistosity plane, while the peak tensile stress increases with increasing θ [21]. Li et al. reviewed in detail about the Brazilian disk test and its applications [22]. Direct tensile strength and Brazilian tensile strength relationship and validity of tensile strength estimation have been reviewed and studied [23]. Analytical study was compared with experimental study in Brazilian test to locate the initial crack formation and cracking in specimen [24].
2 Geology The Himalayan region which lies to the north of the Indo-Gangetic Plain has been divided into four different zones from north to south, viz. Tethys Himalaya, Higher Himalaya, Lesser Himalaya, and Sub-Himalaya [25]. The Tethys Himalayan zone belongs to sedimentary rock sequence of Phanerozoic age and has an unconformable and partly tectonic contact with Higher Himalayan Zone. Higher Himalayas are mostly crystalline rocks (high grade metamorphic rocks), have been designated as central crystalline, and belong to Archean age. These are limited tectonically toward south by main central thrust (MCT) which demarcates the boundary with Lesser Himalaya. Lesser Himalayan zone is considered to range in age from Precambrian to Late Paleozoic [26]. These comprise mostly low to medium grade metamorphic rocks. The project falls in the Higher Himalayas (Archean age), made up of regionally met-amorphosed high grade Metasediments, Migmatites with Palaeoproterozoic Intrusive Gneisses, and Younger Granites. The intact rock cores were collected from different hydro electric power projects from Himalayan region of India and abroad. The maps from Himalayan Mountains of India and cross-sectional drawings of different hydroelectric structures like de-silting chamber, power house, and drill-hole logs infer that biotite gneiss with well-defined foliation with crenulations is the only rock variant found at the proposed elevations. Foliated metamorphic rocks of high-grade gneiss vary when compared to lesser grade foliated metamorphic rocks. Layers of dark and light minerals such as phyllite, schist, and slate are seen in these types of foliated high grade metamorphic rocks. Biotite mica has a very high dark layer when compared to light layer of feldspar and quartz and red crystals layers of garnet.
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3 Theoretical Background To find out the indirect tensile strength of intact biotite gneiss, the Brazilian test is adopted. This test is executed on a right circular cylinder (preferably not smaller than 45 mm) with length to diameter ratio of 0.5, and the compressive load is applied between two parallel platens through universal testing machine as shown in Fig. 1. The samples were oriented and loaded diametrically such that the angle of the foliation makes the desired angle with the loading plane. The load can be assumed to point load (per axial length of the specimen) as the platens are rigid in comparison with rock. The dimensions of the samples and marking of center were recorded to an accuracy of ± 0.5 mm. The samples were loaded (loading rate of 200 N/s) in such a way that the samples fail within 15–30 s. Tensile strength of the specimen, σ t (MPa), is calculated as shown in the below equation. σt = 2P/(π.D.t) where, P is the load at failure (N), D is dia of sample (mm) and t is thickness (mm). To avoid shear failure at contact points without effecting the induction of stresses at the center of the sample, a uniform normal stress is distributed over a small arc of angle 2α (15°). In the case of Brazilian test, it is necessary that fracture in sample must be in line of the load and should originate from the center, Fig. 2a; else the test is considered invalid, Fig. 2b.
Fig. 1 Brazilian test apparatus
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Fig. 2 a Crack instigation from center. b Crack instigation from edges
a
b
4 Sample Preparation and Experimental Methodology Biotite gneiss rock of extremely transverse isotropy from the Himalayan region of India has been selected for this experimental investigation. The rock core specimen for the investigational preparation of Brazilian test is shown in Fig. 3. Around 112 specimens having a length to diameter ratio of 0.5 are prepared as per ISRM recommendations. The dimensions of the sample are 30 mm in length and 58 mm in diameter. The rock samples for these experimental investigations are prepared by cutting the samples in respect to the apparent planes of transverse isotropy for various angles. The specimens were grouped as per the loading angle “θ” which is fixed at an interval of 15° starting from 0° to 90° (0°, 15°, 30°, 45°, 60°, 75°, and 90°). Corresponding angles were marked in respect to the apparent planes of transverse isotropy. Sixteen sets of specimens have been prepared in each angle (0°, 15°, 30°,45°, 60°, 75°, and 90°) for this experimental investigation. The rock samples of right circular cylinder (30 mm in length and 58 mm in diameter) are mounted, and the compressive load is applied between two parallel platens through universal testing machine. The samples were oriented and loaded as per the grouping of loading angle such that the angle of the foliation makes the desired angle with the loading plane. During this testing, precise video monitoring of the crack development of the rock samples has been done using a high-resolution digital camera. Video recording of all the samples was taken by reducing the speed of the video, so that the crack instigation and crack propagation shall be identified and recorded. The apparent gneissocity planes of rock core specimen and the path of diametric loading were prepared for the experimental investigation as shown in Fig. 3a and b.
5 Results and Discussion Tensile strength in a rock core is maximum tensile stress which the intact rock can withstand. 112 indirect tensile test was investigated, and it was inferred that, in most of the samples, crack has instigated from the center and propagated toward the loading plane. The crack instigation pattern observed for few transverse isotropic
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Fig. 3 Sample prepared for investigation
biotite gneiss with varying loading range, i.e.; angle between 0° to 90° is as shown in Fig. 4. The present investigation is limited to the rock sample of transverse isotropic biotite gneiss rock of the particular Himalayan region, where the sample is collected for experimental study. From the observations on the crack pattern developed for various loading plane, it can be stated that crack has instigated from the exact center for most of the specimens. Multifaceted crack pattern was observed such as near to center, on the right and left of the exact center, above and below the top and bottom of the exact center on the diametric line and also from the edges of the curved jaws of the loading plane. The crack instigated within 10% (5% on either side of the center) of the total dimension has also been considered as the crack generated at exact center by considering compatibility into account. Table 1 elucidates the percentage of the crack formation for the 112 samples investigated for varying loading angles. The percentage of crack instigated is classified as (i) percentage of crack which has been instigated at the exact center and is propagated toward the loading plane of various foliation angles as per ISRM suggested method. (ii) Crack which did not instigate either at the exact or near to the center or propagated toward the loading plane of various foliation angles. Among the samples tested at 75° and 90°, the percentage of samples in which crack instigated from center is 81%, which is maximum w.r.t. to angles as can be seen in Table 1. At 0° and 15°, the percentage of samples in which crack instigated from center is minimum (44%). For the foliation angle range varying from 30°, 45° and 60°, the percentage of samples, in which the crack instigated from center, is in between 56 to 75%. The result infers that the percentage of crack instigation at the center is highest when the loading direction is perpendicular to the angle of gneissosity plane and declines towards as the angle is reduced to 0°. The average tensile strength for the respective angles where the crack instigated at center is shown in Table 2. The maximum average tensile strength is 7.50 MPa for 0° and minimum of 6.06 MPa for 90° angle.
Crack Instigation and Propagation of Transversely Isotropic Biotite Gneiss
0o
15o
30o
45o
60o
305
75o
90o
Fig. 4 Crack pattern observed under different foliation angles Table 1 Percentage of crack formation Foliation angle →
0°
15°
30°
45°
60°
75°
90°
• Exact center
44
44
69
56
75
81
81
• Away from center
56
56
41
44
25
19
19
Percentage of cracks ↓
Table 2 Average tensile strength of the crack instigated at center Foliation angle →
0°
15°
30°
45°
60°
75°
90°
Average tensile Strength ↓
7.50
7.50
7.41
6.74
6.44
6.08
6.06
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Tensile strength
y = 7E-06x3 - 0.001x2 + 0.0157x + 7.5398 R² = 0.987
8
6
4
0
15
30
45
Foliation Angle
60
75
90
Fig. 5 Average tensile strength for the crack instigated in the center
As can be inferred from Table 2 and Fig. 5, with the increase in angle of foliation w.r.t. loading plane, the tensile strength reduces (only for the samples in which the crack instigated from center). This phenomenon might be because of the fact that the percentage of samples in which the crack instigated at center is maximum for 60° to 90° (as discussed and shown in Table 1), which in turn means that for the said angles, the setup could induce indirect tensile stresses more efficiently. And, as the rock is critical in tension, the tensile strength for 60° to 90° might turned out to be minimum. In view of foregoing, the following can be inferred: • For 0° to 45°, there are minimum possibilities that the sample will fail in tension. • 60° to 90° has the highest possibilities that the sample will fail in tension.
6 Summary and Conclusion The crack initiation and propagation concept have continuously remained under argument for decades. Different experimental observations have been undertaken to study the above said concept. For transversely isotropic biotite genesis rock specimen, it was observed that the gneissosity planes were closely packed so that the stresses where redistributed in an adverse pattern, which in turn instigated the crack in center and propagated toward the loading plane. Presence of minerals, joints, fractures, and micro-cracks in the intact biotite gneiss results in the low tensile strength of rock and thereby causing the rock to fail suddenly in tension with an infinitesimal strain. Positioning of the rock core with respect to the foliation plays a vital role in determining the engineering parameter in indirect tensile strength test maximum of the sample’s strength where the crack instigated at the center was obtained when the plane is at 0°, and minimum strength was observed when the plane is at 90°. Further,
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60° to 90° angle provides the most conservative value of indirect tensile strength and has highest possibilities of tensile failure. Future scope Investigation on crack instigation and propagation can be studied on other foliated rocks such as schist. And, the same can be correlated to direct shear strength of the foliations. Acknowledgements We are sincerely thankful to Dr. R. Chitra, Director, CSMRS for her continuous technical guidance and for according permission to publish this work. We are also thankful to our colleagues in RM-Lab of CSMRS for their involvement in conducting laboratory investigations. Therewithal, last but not the least, the cooperation of the project authority (M/s UJVNL) is gratefully acknowledged for providing the rock cores for the research purpose.
References 1. ISRM (1978) Suggested methods for determining tensile strength of rock materials. Int J Rock Mech Min Sci Geomech Abstr 15(3):99–103. https://doi.org/10.1016/0148-9062(78)90003-7 2. Brown ET, Green SJ, Sinha KP (1981) The influence of rock anisotropy on hole deviation in rotary drilling-a review. Int J Rock Mech Min Sci Geomech Abstr 18(5):387–401 3. Colback PSB (1966) An analysis of brittle fracture initiation and propagation in the Brazilian test. In: Paper presented at the Proceedings of the First Congress International Society of Rock Mechanics, Lisbon, Portugal 4. Mellor M, Hawkes I (1971) Measurement of tensile strength by diametral compression of discs and annuli. Eng Geol 5(3):173–225. https://doi.org/10.1016/0013-7952(71)90001-9 5. Yanagidani T, Sano O, Terada M, Ito I (1978) The observation of cracks propagating in diametrically-compressed rock discs. Int J Rock Mech Min Sci Geomech Abstr 15(5):225–235. https://doi.org/10.1016/0148-9062(78)90955-5 6. Chen C-S, Pan E, Amadei B (1998) Determination of deformability and tensile strength of anisotropic rock using Brazilian tests. Int J Rock Mech Min Sci 35(1):43–61. https://doi.org/ 10.1016/s0148-9062(97)00329-x 7. Cai M, Kaiser PK (2004) Numerical simulation of the Brazilian test and the tensile strength of anisotropic rocks and rocks with pre-existing cracks. Int J Rock Mech Min Sci 41(Suppl 1):1–6. https://doi.org/10.1016/j.ijrmms.2004.03.086 8. Van De Steen B, Vervoort A, Napier JAL (2005) Observed and simulated fracture pattern in diametrically loaded discs of rock material. Int J Fract 131(1):35–52 9. Zhu WC, Tang CA (2006) Numerical simulation of Brazilian disk rock failure under static and dynamic loading. Int J Rock Mech Min Sci 43(2):236–252. https://doi.org/10.1016/j.ijrmms. 2005.06.008 10. Fairhurst C (1964) On the validity of the ‘Brazilian’ test for brittle materials. Int J Rock Mech Min Sci Geomech Abstr 1(4):535–546. https://doi.org/10.1016/0148-9062(64)90060-9 11. Hooper JA (1971) The failure of glass cylinders in diametral compression. J Mech Phys Solids 19(4):179–200 12. Swab JJ, Yu J, Gamble R, Kilczewski S (2011) Analysis of the diametral compression method for determining the tensile strength of transparent magnesium aluminate spinel. Int J Fract. https://doi.org/10.1007/s10704-011-9655-1 13. Claesson J, Bohloli B (2002) Brazilian test: stress field and tensile strength of anisotropic rocks using an analytical solution. Int J Rock Mech Min Sci 39(8):991–1004. https://doi.org/10.1016/ s1365-1609(02)00099-0
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Analytical Studies on the Fire Resistance of Reinforced Concrete Beams Exposed to Parametric Time–Temperature Curve V. P. Amar Hebbar , V. Sachin , and N. Suresh
Abstract An accidental fire is an extreme event that may alter the performance and behavior of structural elements. The reinforced concrete (RC) elements have considerably better fire resistance than structural steel elements. Owing to this, reinforced concrete elements are widely used in the construction industry. It is evident from the previous literature that the actual fire resistance capacity of the reinforced concrete beams varies with the change in fire scenarios. However, the present Indian standard provides prescriptive tables to improve the fire resistance of RC structural elements. Therefore, a detailed study needs to be carried out to determine the fire resistance of reinforced concrete beams specified in the Indian Standard code by adopting the fire dynamics. In the present work, finite element analysis of RC beams is conducted using finite element software ABAQUS. The RC beams were subjected to parametric time–temperature curves and standard time–temperature curves to determine the equivalent fire severity of the Eurocode design fires (parametric time–temperature curve). The considered concrete and steel properties for the simulation are validated by the previous literature works. Further, the limiting fire load of the RC beams subjected to parametric design fires is determined. Further, the concept of duration of heating phase is applied to compare with the standard time–temperature fire, and the deflections of the fire-exposed RC elements are considered for detailed discussion and conclusion. Keywords RC beams · Fire exposure · Finite element analysis · Thermo-mechanical analysis
V. P. Amar Hebbar · V. Sachin (B) · N. Suresh The National Institute of Engineering, Mysuru, Karnataka 570008, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_26
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1 Introduction The accidental fire in buildings is a severe environmental condition where structural elements will be subjected to spontaneous increment in temperature. Fire in RC structures causes geometric (thermal expansion) and material effects (loss in stiffness and strength) in reinforced concrete elements. The exposure of structural elements to fire causes deterioration in structural elements’ material properties and may lead to the total collapse of RC structure [1]. The RC structural members should have minimum fire resistance usually known as standard fire resistance or a performancebased design needs to be adopted to overcome the catastrophic failure of the RC structure. A series of numerical and experimental analysis on RC beams has been done by various researchers in the past. During the analysis, the reinforced concrete beams were subjected to a parametric time–temperature curve and standard fire curve to determine the effect of permeability, concrete strength, support conditions, fire scenario, exposure face, and load level. Dwaikat and Kodur [2] observed that the fire resistance of reinforced concrete beams is observed to be higher with the normal strength concrete and axially restrained conditions. Also, the change in fire exposure period, fire exposure surfaces, and type of load acting on the element significantly affects the ultimate capacity of the reinforced concrete beams. [3]. However, the residual capacity of RC beams determined by applying the 500-isotherm method (EN-2) [4] shows that the influence of clear cover is maximum to the residual loadbearing capacity of fire-exposed RC beams than the grade of concrete [5]. To explore the outcome of significant parameters on the residual response of RC beams exposed to fire, a nonlinear finite element analysis is used [6]. It is inferred that the decrease in residual capacity of RC beams subjected to fire almost doubles when the load level increases from 30 to 60% of the room temperature capacity of the RC beams. To assess the performance of reinforced concrete beams subjected to natural or parametric time–temperature curves, a performance indicator called duration of heating phase (DHP) was developed by Gerney and Franssen [7]. The DHP represents the burning period in the parametric time–temperature curve. It is observed that the RC beams have a DHP value lower than the fire resistance of the beams [7]. However, an attempt is yet to be made to determine the actual fire resistance, limiting fire load capacity, and DHP of the RC beams considered as per IS 456:2000 and EN-2 standards by exposing parametric time–temperature curves. A limiting fire load capacity is the amount of combustible material that can be stored inside a compartment or under the beam. The present building standards IS456:2000 [8] and EN-2 [4] suggest guidelines in the form of prescriptive conditions such as clear cover, width and depth of the member, and protective coatings to increase the fire resistance of reinforced concrete (RC) structural elements. It has to be noted that the provided prescriptive conditions are limited for exposure of elements to a standard time–temperature curve. This means, that the prescriptive conditions neither consider the advanced fire behavior nor the performance of elements during the exposure to fire. Because of this, the behavior of structural elements either part of the building or global behavior of the building is
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difficult to estimate. Hence, there is a need for the application of performance-based design to predict the actual behavior of the reinforced concrete elements by incorporating the fire dynamics. In the current study, an effort has been made to determine the influence of fire load on the fire resistance of simply supported RC beams. It is understood from previous literatures that the fire resistance of the beams varies with the change in support condition. Hence, simply supported beam is chosen as it represents the most critical scenario compared to continuous or axially restrained condition. Further, to conduct performance-based design, finite element analysis (FEA) provides cost-effective and time-saving solutions compared to experimental-based studies. The FEA enables the simulation of fire behavior and determines the performance of structural elements. A sequentially coupled thermo-structural analysis is performed in ABAQUS [9]. The EN 1992-1-2 (2004) [4] suggested mechanical and thermal properties of steel and concrete at elevated temperatures. This data has been adopted to perform the sequentially coupled thermo-structural analysis.
2 Finite Element Procedure In the present study, sequentially coupled thermo-mechanical analysis is considered to determine the performance of RC beams subjected to parametric and standard fire. The sequentially coupled analysis is a two-phase analysis. In the first phase, the structural element under consideration is first exposed to a thermal field, and the results of the thermal field are coupled with the second phase mechanical analysis to determine the effect of the considered thermal environment on the stress and deformation of the element. The RC beams response is analyzed in the second phase of the analysis by changing the study parameters. The temperature-dependent mechanical and thermal parameters of reinforcing steel and concrete which change throughout the heating and cooling stages of fire exposure are given as input to both analytical phases.
2.1 Numerical Modeling Details The commercially available finite element package ABAQUS is considered to conduct the sequentially coupled thermo-structural simulation. In the ABAQUS standard, the first heat transfer case is executed, and then, the reading from the temperature solution is incorporated for mechanical analysis as a predetermined field. The element required to complete both analysis cases are detailed as under. Thermal analysis: An (DC3D8) eight-noded linear brick element is used to model concrete, and two-noded truss element or link element (DC1D2) is considered for reinforcement. To allow heat transfer from concrete to steel elements, a tie constraint is taken into consideration. The thermal boundary condition is assigned to the RC
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beam model. In the analysis, the convective heat transfer coefficient for fire-exposed concrete surfaces is 25 W/m2 °C, and the coefficient for the unexposed concrete exterior surface is 9 W/m2 °C is considered as per Eurocode 2 recommendations. Further, the emissivity factor of 0.7 was taken into account for exterior concrete surfaces [10]. Structural analysis: In the RC beam model after completion of thermal analysis, the thermal element property is changed to (C3D8R) eight-noded continuum elements for concrete and the reinforcing steel to two-noded (T3D2) link element. The interlinkage between reinforcing steel and concrete is completed through the embedded region. Further, a simply supported condition is assigned in the boundary condition to perform structural analysis.
2.2 Material Properties To complete the intended thermo-mechanical analysis, nonlinear material properties of steel and concrete are considered at each analysis phase. The mechanical analysis was performed by considering the damage plasticity model of concrete developed by Lee and Fenves [12] based on work by Lubliner et al. [11]. Concrete and reinforcing steel’s temperature-dependent thermal properties, namely specific heat, thermal expansion, and thermal conductivity, and in the two-phase study, the mechanical properties of concrete and reinforcing steel are assigned by considering the Eurocode 2 and 3 recommendations [13–15]. The stress–strain relationship of concrete and reinforced steel at elevated temperatures is presented in Figs. 1 and 2, respectively.
2.3 Deflection Failure Criteria The RC beams considered in the present study undergo predominantly larger deflection, owing to the increment in the exposure temperature. Hence, a limiting condition is required to define the failure criteria of the considered RC beam. The deflection limit state adopted for failure as per CEN (2012) [16] is as follows: a. The RC beam’s maximum deflection surpasses L 2 /(400d) (mm) at any fire exposure time or b. The rate of deflection exceeds L 2 /(9000d) (mm/min)
Where L = Span length of the beam (mm), d = Effective beam depth (mm)
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30
20C 100C 200C 300C 500C 400C 600C 700C 900C 800C 1000C 1100C
25
Stres, N/mm2
313
20 15 10 5 0 0
0.01
0.02
0.03
0.05
0.04
Strain Fig. 1 Stress–strain relationship of concrete at elevated temperatures
450 20C
Stress, N/mm2
400
100C
350
200C
300
300C 400C
250
500C
200
600C
150
700C 800C
100
900C 1000C
50
1100C
0 0
0.05
0.1
Strain Fig. 2 Stress–strain relationship of steel at elevated temperatures
0.15
0.2
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3 Validation of FE Model 3.1 Beam Details The adopted material properties and modeling technique are validated by considering the experiment conducted by Dwaikat and Kodur [2]. The RC beam B1 experiment details are considered to compare the results of the validated model. The RC beam B1 has a length of 3960 mm with a width of 254 mm, an overall depth of 406 mm and is subjected to ASTM-E119 standard fire [17] to a length of 2440 mm as shown in Figs. 3 and 4. A simply supported condition was considered for Beam B1 during the experiment. Three 19 mm tensile reinforcements were placed at the bottom of the beam, and at the top, two 13 mm compression reinforcements were installed. Along the length of the beam, the 6 mm diameter shear reinforcement was positioned at 150 mm center–center distance. The grade of longitudinal reinforcement was 420 MPa and transverse reinforcement 280 MPa, respectively. The concrete has a 55 MPa compressive strength. The RC beam was loaded with two 50 kN forces at 610 mm distance from the center of the beam. The loading of the beam started 30 min before the fire exposure and the same was maintained constant till the reinforced concrete beam fails [6, 18]. As indicated in Fig. 5, thermocouples were positioned at three positions (i.e., quarter depth 91 mm, mid-depth 203 mm, and bottom rebar 54 mm) to detect the temperature rise within the beam. In the present validation program, the RC beam was modeled using the procedure described in the preceding sections, and the outcomes of the finite element analysis and the outcomes of the experiment were compared. In Fig. 6, the illustration of temperature changes over time at three particular locations (i.e., quarter depth, middepth, and bottom rebar) of the RC beam B1, and exposure temperature is presented. In Fig. 7, the mid-span deflection of the present study model is compared with the
50kN
610mm
610mm
2440mm 3658mm 3952mm
Fig. 3 Elevation of beam ‘B1’
50kN
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203mm
(Mid-depth)
54mm
91mm
(Quarter depth)
Fig. 5 Location of thermocouples
(Bottom rebar)
Fig. 4 Cross section of beam ‘B1’
deflection response pattern from the experiment, and the considered material model is observed to be on the conservative side during the fire exposure.
4 Parametric Study The limiting fire load of RC beams after exposure to fire is determined using the validated finite element analysis approach for all eight beams. In this work, various parameters considered for the study are fire load, load ratio, and size of the beams.
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Fig. 6 Comparison of cross-sectional temperatures for beam B1
Fig. 7 Comparison of mid-span deflection for beam B1
4.1 Reinforced Concrete Beams Details In the present work, eight RC beams (B1 to B8) were considered for thermomechanical analysis. The beam width and clear cover of RC beams B1 to B4 are considered as per IS 456:2000 [8], and beams B5 to B8 are considered as per EN-2 guidelines [4]. The effective length of RC beams is considered as 6000 mm with simply supported boundary conditions. The grade of concrete and reinforcing steel considered in the present work is 25 MPa and 500 MPa, respectively. A uniformly
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Fig. 8 Typical RC beams dimensions and loading details considered for parametric study
Table 1 Details of RC beams considered for the parametric study Design standards
Beam designation
IS 456:2000
B1
200
450
20
412
1.5
2#20 + 1#16
B2
200
450
40
392
2
2#20 + 1#16
EN 1992-1-2 (2004): Eurocode 2
Beam dimensions (mm) Width B
Depth D
Clear cover CC
Effective depth d
Fire resistance as per the guidelines (h)
Tension reinforcement
B3
240
550
60
462
3
2#20
B4
280
550
70
452
4
2#20
B5
200
450
45
387
1.5
2#20 + 1#16
B6
240
550
60
462
2
2#20
B7
300
550
70
452
3
2#20
B8
350
550
80
442
4
2#20
distributed load of 21.75 kN/m2 is considered on all the beams for ambient temperature design. Further, the RC beams were designed as per IS 456:2000, and the depth of the RC beams is considered based on serviceability criteria. In Fig. 8, the reinforced concrete beams along with the considered loading arrangement are illustrated. The cross-section and reinforcement details of the RC beams are presented in Table 1. Further, the RC beams were provided with two-legged vertical stirrups of 8 mm diameter at 150 mm spacing for shear reinforcement and two numbers of 12 mm diameter bars considered for hanger bars. The material property relations for reinforcing steel and concrete at different stages of finite element analysis have been adopted for analysis as described in the preceding material property section.
4.2 Fire Exposure Details In the present work, the RC beams (B1 to B8) are subjected to ISO 834 standard time– temperature curve [19] and parametric time–temperature curves. The compartment
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Fig. 9 ISO 834 standard and parametric time–temperature curves
dimension of 9 × 6 m, ventilation factor 0.046, fire load density of 300 to 6400 MJ/m2 , and compartment lining is considered as concrete to generate the parametric time– temperature curves. In Fig. 9, the ISO 834 standard time–temperature curve and parametric time–temperature curves computed using Eurocode 1 [10] are illustrated. The influence of varied load ratios on the fire resistance of the RC beam during the standard time–temperature curve and parametric curve exposure is studied. A load ratio is the ratio of load existing on the reinforced concrete beam throughout the fire exposure to the ultimate load of the RC beam. In this work, two load ratios 40% and 60% are considered on the RC beams for fire curves exposure. In the next section, the results of RC beams analyzed in the present study are discussed.
5 Results and Discussion The RC beams considered in the present study were exposed to standard and parametric time-temperature curves to determine the actual fire resistance capacity of the by changing the load ratio on the beam. Also, the limiting fire load and the time at the failure of the RC beams are determined for all the exposure scenarios. A limiting fire load is the amount of combustible material that can be stored under the beam or inside the compartment of the present study. Further, the duration of the heating phase (DHP) is determined by the parametric time-temperature curve obtained during the parametric fire curve of the limiting fire load scenario. The duration of the heating
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phase is the total time of burning or total time to reach the highest temperature present in the parametric time-temperature curves.
5.1 Fire Resistance of the RC Beams Subjected to ISO 834 Standard Time–Temperature Curve The actual fire resistance of the RC beams subjected to the standard curve determined for 40% and 60% load ratio is presented in Table 2. The RC beams B1 to B8 considered in the present study are observed to have higher fire resistance capacity for all the load ratios than the fire resistance specified by IS 456:2000 and EN-2. The ratio of actual fire resistance to the code-specified fire resistance for all exposure conditions is represented in Fig. 10. Further, the actual fire resistance capacity of the RC beams considered as per IS 456:2000 is less than the RC beams considered as per EN-2 specifications. The difference between the actual fire resistance of reinforced concrete beams is owing to the increased beam width and clear cover of the RC beams. Furthermore, the actual fire resistance capacity of the RC beams reduces with an increase in load ratio, and beam B4 is observed to have only a 23% higher fire resistance capacity at 60% load ratio than the code-specified fire resistance.
5.2 Performance of RC Beams Subjected to Parametric Time–Temperature Curves The performance of RC beams B1 to B8 exposed to parametric time-temperature is determined and fire resistance of RC beams to parametric fire conditions is shown in Table 2. It is observed from Table 2 that the actual fire resistance of RC beams exposed to the parametric time-temperature curve is higher than the actual fire resistance capacity of the RC beams subjected to the standard time-temperature curve for both 40% and 60% load ratios. It is noted that the fire resistance capacity of reinforced concrete beams B5 and B6 exposed to parametric time-temperature fire at 40% load ratio is 3.52 and 3.86 times higher than EN-2 specified fire resistance. It may be noted that the RC beams subjected to parametric time-temperature curve is failed during the cooling phase of the curve unlike in the standard fire exposure. Hence, the duration of the heating phase (DHP) of each beam is determined and presented in Table 2. It is observed that the DHP of each beam is close to the standard fire resistance specified in IS456:2000. A ratio of DHP to standard fire resistance (SFR) is presented in Fig. 11 to understand the reduction in DHP from the SFR. The DHP of RC beams B2, B3, and B4 is 7%, 14%, and 18% lower than the standard fire resistance given by IS 456:2000. This indicates that the IS 456:2000-considered beams B2 to B4 will fail for an exposure length shorter than the fire resistance stipulated by design standards. However, it may be noted that the time of failure is larger than the standard
5.1
4.00
B8
8.3
5.1
6.4
2.00
3.00
3.8
6.0
B6
1.50
B5
2.8
3.6
2.3
6.8
5.2
4.4
2.7
4.9
4.4
2.6
4.2
10.6
8.1
7.7
5.2
7.9
7.7
5.3
3.6
8.9
7.6
6.7
4.2
6.9
6.7
4.8
7.5
4.5
3.2
2.7
4.2
3.2
2.4
2.1
LR 40%
5.0
3.5
2.5
1.9
3.2
2.5
1.8
1.7
LR 60%
Parametric fire LR 60%
Parametric fire LR 40%
ISO 834 fire
LR 40%
LR 60%
DHP (h)
Actual fire resistance (h)
B7
3.00
4.00
B3
B4
1.50
2.00
B1
B2
Code F.R (h)
Beam number
Table 2 Results from the parametric study
6400
3900
2800
2300
3600
2800
2100
1840
LR 40%
4300
3000
2200
1700
2800
2200
1600
1500
LR 60%
Fire load (MJ/ m2 )
199.11
194.80
190.67
232.55
194.80
190.67
229.00
218.40
mm
8.84
8.65
8.47
10.3
8.65
8.47
10.2
9.70
mm/min
Deflection failure criteria
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Fig. 10 Ratio of actual and code-specified fire resistance of RC beams
fire resistance capacity of the (RC) reinforced concrete beams. Further, the DHP of all the beams is reduced with the increase in load ratio to 60%. The limiting fire load obtained by exposing each beam to various parametric time-temperature curves is presented in Table 2. The limiting fire load value for the considered beam is increasing with the increase in the standard fire resistance of the beam. The limiting fire load capacity of the beams B1 to B4 considered as per IS456 has a lower limiting fire load capacity than the beams considered as per EN-2. Further, the percentage reduction in limiting fire load for B1 to B8 beams with an increase in load ratio to 60% is shown in Fig. 12. The beam B8 is noticed to have 32.81% lower fire load capacity during the 60% load ratio scenario.
6 Conclusions The RC beams considered in the present study were exposed to standard and parametric time–temperature curves, and the actual fire resistance capacity of the considered reinforced concrete beams is determined by varying the load ratio on the beam. Additionally, the following conclusions were obtained. 1. The actual fire resistance of reinforced concrete beams B1 to B8 is more than the standard fire resistance specified by IS456:2000 and EN-2. 2. The actual fire resistance of RC beams considered as per IS456:2000 is less compared to the beams considered as per EN-2 in all load ratios. This is owing to the increased beam width and clear cover of the beams. 3. The RC beams B5 and B6 at a 40% load ratio are 3.52 and 3.86 times higher than the standard fire resistance specified in EN-2.
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Ratio of DHP to SFR
1.60 1.40 1.20
1.88
1.80
1.80
1.64 1.43
1.32
1.17 1.23
1.09 0.93
1.00
0.86
1.28
1.05
1.52 1.17
1.26
0.82
0.80 0.60 0.40 0.20 0.00 B1
B2
B3
B4
B5
Beam number
B6 LR 40%
B7
B8 LR 60%
Fig. 11 Ratio of duration of heating phase (DHP) to standard fire resistance (SFR)
Fig. 12 Percentage reduction in fire load at 60% load ratio
4. The duration of the heating phase (DHP) of each reinforced concrete beam is close to the standard fire resistance mentioned in IS456:2000 and EN-2 standards. 5. The DHP of RC beams B2, B3, and B4 is consistently reduced to 7%, 14%, and 18% than the standard fire resistance given by IS456:2000. It means the beams B2 to B4 considered as per IS456:2000 will fail for an exposure duration less than the code-specified standard fire resistance.
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6. It is evident from the present study that the reinforced concrete beam’s fire resistance may reduce with the increase in the fire load and load ratios. The fire resistance of the reinforced concrete beams subjected to parametric time–temperature curves needs to be determined both during the heating phase along with the cooling phase of the curve to obtain the most critical scenario.
References 1. Bailey C (2002) Holistic behaviour of concrete buildings in fire. Proc Inst Civ Eng Struct Build 152(3):199–212. https://doi.org/10.1680/stbu.2002.152.3.199 2. Dwaikat MB, Kodur VK (2009) Response of restrained concrete beams under design fire exposure. J Struct Eng 135(11):1408–1417. https://doi.org/10.1061/(asce)st.1943-541x.000 0058 3. Xing Q, Liao J, Chen Z, Huang W (2020) Shear behaviour of fire-damaged reinforced-concrete beams. Mag Concr Res 72(7):357–364. https://doi.org/10.1680/jmacr.17.00529 4. ECS (2004) EN 1992-1-2: design of concrete structures. Part 1–2: general rules—structural fire design. ECS, Brussels 5. Vijaya Kumar S, Suresh N (2021) Study on the residual performance of RC beams exposed to processed temperatures and fire. J Struct Fire Eng 13. https://doi.org/10.1108/JSFE-08-20210051 6. Kodur VK, Agrawal A (2015) Critical factors governing the residual response of reinforced concrete beams exposed to fire. Fire Technol 52(4):967–993. https://doi.org/10.1007/s10694015-0527-5 7. Gernay T, Franssen J-M (2015) A performance indicator for structures under natural fire. Eng Struct 100:94–103. https://doi.org/10.1016/j.engstruct.2015.06.005 8. IS 456-2000 Indian Standard for Reinforced, Bureau of Indian Standards Manak Bhavan, 9 Bahadur Shah Zafar Marg New Delhi 110002 9. ABAQUS (2012) Version 6.12 Documentation. Dassault Systemes Simulia Corp., Providence, RI 10. ECS (European Committee for Standardization) (2002) EN 1991-1-2: actions on structures. Part 1–2: general actions—actions on structures exposed to fire. ECS, Brussels 11. Lubliner J, Oliver J, Oller S, Oñate E (1989) A plastic-damage model for concrete. Int J Solids Struct 25(3):299–326. https://doi.org/10.1016/0020-7683(89)90050-4 12. Lee J, Fenves GL (1998) Plastic-damage model for cyclic loading of concrete structures. J Eng Mech 124(8):892–900. https://doi.org/10.1061/(asce)0733-9399(1998)124:8(892) 13. ECS (2004) EN 1992-1-1: design of concrete structures. Part 1–1: general rules and rules for buildings. ECS, Brussels 14. ECS (2005) EN 1993-1-2: design of steel structures. Part 1–2: general rules-structural fire design, vol 2. ECS, Brussels 15. ECS (2005) EN 1994-1-2: design of composite steel and concrete structures. Part 1–2: general rules-structural fire design, vol 2. ECS, Brussels 16. CEN (2012) Fire resistance tests—part 1: general requirements, EN 1363-1. European Committee for Standardization, Brussels 17. ASTM E119-07 (2007) Standard methods of fire test of building construction and materials. ASTM International, West Conshohocken 18. Kodur VKR, Agrawal A (2016) An approach for evaluating residual capacity of reinforced concrete beams exposed to fire. Eng Struct 110:293–306. https://doi.org/10.1016/j.engstruct. 2015.11.047 19. ISO 834-1 (1999) Fire resistance tests-elements of building construction. Part 1: general requirement. ISO, Geneva
Effect of Biopolymer on Water Retention Property of Red Mud Shamshad Alam, Sakshi Agrawal, Mahasakti Mahamaya, and Sarat Kumar Das
Abstract Red mud (RM) is a toxic waste generated from the aluminium refinery during the extraction of aluminium from the bauxite ore. A significant amount of red mud is stored in ponds or as dry staking due to its low utilization and high generation rate. Either way of storage causes spreading of harmful red mud particle in the nearby area due to wind erosion or due to water erosion. In this research, an effort has been made to regulate the dispersiveness of red mud by employing the biopolymer to control the erosion of the red mud surface. Two different types of the biopolymer such as xanthan gum and guar gum have been used in this research. The biopolymer solution has been mixed with red mud collected from two different locations (i.e. NALCO, Koraput and HINDALCO, Muri) to prevent the dispersion of the red mud thereby preventing the water erosion. Further, the same quantity of biopolymer has been used to investigate the water retention capacity of treated red mud. The soil water characteristic curve (SWCC) has also been established by drying the sample to show the point of air entry and the leftover water content in the stabilized red mud. Keywords Red mud · Biopolymer · Dispersiveness · Water retention · SWCC
S. Alam (B) Department of Civil Engineering, Jazan University, Jazan, Kingdom of Saudi Arabia e-mail: [email protected] S. Agrawal · M. Mahamaya Department of Civil Engineering, O. P. Jindal University, Raigarh, India e-mail: [email protected] M. Mahamaya e-mail: [email protected] S. K. Das Department of Civil Engineering, Indian Institute of Technology, Dhanbad, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_27
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1 Introduction Red mud (RM) is a waste material generated during the extraction of the aluminium from the bauxite and is highly alkaline (pH > 11) in nature with high generation rate [1]. Owing to the poor application rate, majority of the RM is stored in the pond in the form of dry staking. Several studies have been proposed in the recent decay for the application of the red mud; however, the rate of utilization is very low [2–5]. Further, several researchers worked on the bulk application of the red mud [6–10]; however, still due to the unavailability of suitable solution for bulk utilization, most of the red mud is stored. The storage creates the geo-environmental problem due to the leaching as well as the due to the water erosion as shown in Fig. 1 and dust generation due to wind as shown in Fig. 2 at the surface of the surface and polluting the nearby area. So, the main objective of this research is to control the erosion problem of the red mud by binding the red mud particle together as well as to control the dusting problem by preventing the red mud surface from drying. Previous research in different forms shows that the mixing of the biopolymer increases the water retention capacity of the soil. The dusting problem can be controlled by preventing the red mud surface from drying which can be measured using the water holding ability and establishing the soil water characteristic curve (SWCC). Several researchers have developed the SWCC Fig. 1 Typical photo showing the erosion at the surface of red mud (Photo taken by S. Alam)
Fig. 2 Picture showing the dusting at the surface of red mud pond (Photo taken by S. Alam)
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and water retention characteristic for different types of red mud [11–13]. There is a record of utilizing the environmentally friendly biopolymer for the stabilization of the soil in the recent decade [14–16]. Several researchers studied the effect of biopolymer on the SWCC and water retention characteristics of different soils [17– 20]. To the best of the authors’ knowledge, there is no research on the SWCC and water retention properties of red mud treated with biopolymers. So, in this paper, an effort has been made to regulate the dusting problem of the red mud by applying the biopolymer at the surface of the red mud, and the result has been presented in terms of dispersiveness, water holding ability, and soil water characteristic curve (SWCC). Two different types of biopolymer such as guar gum and xanthan gum have been used in this research due to the easy availability. However, this study can be extended further with the different types of the biopolymer.
2 Materials and Methodology Two different aluminium industries, NALCO in Odisha and HINDALCO in Jharkhand, provided the red mud for this investigation, whereas the biopolymer (guar gum and xanthan gum) was obtained from the market. Before performing the test, the red mud is dried in the electric oven at 105–110 °C for 24 h. After drying, the red mud is crushed in the ball mill to break the lumps. The experimental investigations such as dispersiveness, water retention, and SWCC was done on the unstabilized red mud passing through 0.425 mm IS sieve. The biopolymer is used in form of solution with 0.5% biopolymer in 1 L water. The test was performed on the red mud only and after application of the biopolymer, and the results are compared. The dispersiveness property has been studied on the cylindrical sample of length to width ratio of 2, prepared by compacting the saturated red mud slurry in cylindrical mould and then submerging into the water. For the water retention test, the red mud is filled in tray, then the biopolymer solution is applied at the surface of the red mud exposed to the environment, and then, it is dried in the sunlight till its weight becomes constant. The SWCC is established using the WD4 Dew Point Potentiometer at Indian Institute of Technology Bhubaneswar. For the SWCC, the biopolymer solution in different percentages was mixed with the red mud, and the drying path has been established. The results obtained from the laboratory test have been discussed in the corresponding section.
3 Result and Discussion The creation of the channel due to water flow (Fig. 1) and the dust in the atmosphere (Fig. 2) are seen during the site visit for sample collection, showing that the red mud is dispersive in nature, which is also verified by the previous studies [21]. The biopolymer has been used effectively to stabilize the soil and other waste material and
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Fig. 3 Cylindrical dispersive test result (Reproduced from [24])
found environmentally friendly [22, 23]. In order to reduce the red mud’s tendency to disperse, guar gum (GG) and xanthan gum (XG) have been used in the current investigation. The result of the cylindrical dispersive test, which is a qualitative test, has been shown in Fig. 3. It is observed from the figure that as soon as the untreated red mud is submerged in the water, the red mud particles start leaving the surface of sample and remain suspended in the water due to which the water became blurred. To control the dispersiveness, the sample is prepared in the solution with different percentages of biopolymer, and the test is repeated. It was observed that 0.5% GG or 0.5% XG is sufficient to control the dispersiveness as shown in Fig. 3. Even after submerging the sample into the water, the water is clean and transparent showing no red mud particle suspended into the water. As the 0.5% biopolymer is found effective in controlling the dispersiveness, the other studies such as water retention and SWCC have been performed with only 0.5% biopolymer. For the water retention, three samples have been prepared with 750 g of dry red mud and are compacted in a tray at optimum moisture content. On the exposed surface of one sample, solution of 0.5% GG was spread, and on the other sample, 0.5% XG was spread. However, the surface of third sample was free from any biopolymer. After taking the initial weight of the sample, the sample was exposed to the direct sunlight for drying. During drying, the weight of the sample was measured every 24 h, and once the weight became constant, the test was stopped. The variation of the water content in the red mud with days is shown in Fig. 4 for red mud collected from NALCO (NRM) and in Fig. 5 for the red mud collected from HINDALCO (HRM). It is observed that after 7 days, the residual water content in the NRM treated with 0.5% GG is 1.47% and in the one treated with 0.5% XG is 2.27%, whereas the residual water in the untreated red mud is 1.07%. Similarly, Fig. 5 shows the variation of water content in HRM with time. It is observed that the residual water content after 7 days in the HRM treated with 0.5% GG and 0.5% XG is 2.13% and 3.20%, respectively. The increase in the residual moisture content after 7 days of drying may be due to the reason that the biopolymer increases the initial volumetric water content of the soil [17]. Furthermore, regardless of the type of red mud, it can be seen from Figs. 4 and 5 that xanthan gum (XG)
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Fig. 6 Typical photo of sample for SWCC (Photo taken by S. Alam)
is more successful at preserving moisture content. While comparing Figs. 4 and 5, it is also observed that any type of the biopolymer is more effective in HRM in comparison with NRM which may be due to the more porous structure of the HRM [25] which absorbs the water. However, there may be many more factors such as particle shape, size, and surface chemistry and needs further in-depth investigation. The SWCC is defined by the previous researcher [26] as the relationship between water content and suction for the soil. The suction is the difference between the pressures inside the pores for air and water [27]. In the present study, the SWCC has been developed using the WD4 dew point potentiometer at different moisture contents, and the drying path has been plotted because the red mud is disposed with high water content, and the water content decreases with time. The sample is prepared by making red mud slurry using only water or with 0.5% GG or with 0.5% XG solution, and then, it is filled in the cup supplied with the equipment. A typical photo of the red mud sample in the cup is shown in Fig. 6. After filling the sample in the cup, it is inserted into the potentiometer to measure the matric suction. After taking the measurement, the sample is taken out and dried to reduce the water content. To calculate the moisture content in every step, the weight of the sample is measured before inserting it into the potentiometer. The suction is measured till the residual water content in the red mud sample became constant. Initially, the SWCC of untreated NRM and HRM (Fig. 7) is developed which is comparable to the SWCC of clay soil [27], the SWCC of sample is prepared with 0.5% XG solution (Fig. 8), and sample prepared using 0.5% GG solution (Fig. 9) is developed and compared. It is observed from Fig. 7 that at higher moisture content, the suction in HRM is higher than that of NRM, and the difference decreases with the decrease in the moisture content. The residual water content in the HRM (approximately 5%) is higher than the residual water content in the NRM (approximately 1.5%). In Fig. 8, the SWCC of the NRM and HRM prepared with 0.5% XG solution presented which shows that 0.5% XG increases the saturated water content by 25% for both NRM and HRM. Similar effect of the biopolymer has been reported by the previous researcher [20], whereas the difference between the saturated water content of NRM and HRM which was around 20% increased to 25% after adding 0.5% XG. A negligible change in the residual moisture content is observed for HRM after adding 0.5% XG; however, for the NRM, the change is considerable. Further, after adding the XG, the SWCC becomes very similar to the silty soil as shown by the
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Fig. 9 Effect of Guar gum on the SWCC of red mud
previous researcher [27]. When the SWCC developed for NRM with 0.5% XG and HRM with 0.5% XG (Fig. 8) is compared, it is observed that at any suction, the moisture content in the HRM with 0.5% XG is higher which shows high water retention capacity of the HRM as also observed in the water retention test. The water holding capacity increases due to the fact that the residual water content is held by surface tension and also due to the absorption capacity of the biopolymer during saturation [17]. Figure 9 shows the SWCC of the red mud treated with 0.5% GG. It is observed from Fig. 9 that the saturated water content of the NRM with 0.5% GG is around 75% higher than the saturated water content of NRM which shows that the GG is more effective in increasing the saturated water content as compared to XG. However, in case of HRM, no considerable difference is observed between XG and GG in increasing the saturated water content. While comparing Figs. 8 and 9, no considerable change in the shape of the SWCC of HRM with XG and GG is observed, whereas there is a difference in the shape of SWCC of NRM with XG and GG due to increase in the air entry value and saturated water content after adding GG.
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4 Summary and Conclusion From the extensive laboratory experiments on the NRM and HRM with 0.5% guar gum or 0.5% xanthan gum, the following conclusion has been drawn. • Although the red mud is found highly dispersive in nature, after mixing 0.5% guar gum or xanthan gum, both the red mud (NRM and HRM) become nondispersive and hence prevent the water erosion of the surface of red mud. • After 7 days of drying, the residual water content in untreated NRM was 1.07% which increases to 1.47% and 2.27% after the treatment with 0.5% GG and XG, respectively. Similarly, in HRM, the residual water content after 7 days of drying increases to 2.13% and 3.20% after treatment with GG and XG, respectively. • The xanthan gum is found more effective as compared to guar gum by increasing the water retention capacity up to 2.27% and 3.20% in NRM and HRM, respectively. Also, the water retention capacity of HRM was found higher as compared to NRM with either of the biopolymer (guar gum or xanthan gum). • Initially at the low suction, the moisture content in the HRM is found higher as compared to NRM; however, the difference decreases with increase in suction value. • SWCC shows that the application of guar gum or xanthan gum increases the residual moisture content and air entry value of both the red mud; however, guar gum is found more effective as compared to xanthan gum in either of the red mud. • Based on the above conclusion, it can be recommended to treat the soil surface using the biopolymer (GG and XG) to prevent the surface from water or wind erosion. However, more in-depth studies are required to strengthen the recommendation.
References 1. Nath H, Sahoo P, Sahoo A (2015) Characterization of red mud treated under high temperature fluidization. Powder Technol 269:233–239. https://doi.org/10.1016/j.powtec.2014.09.011 2. Luu TT, Dinh VP, Nguyen QH, Tran NQ, Nguyen DK, Ho TH, Nguyen VD, Tran DX, Kiet HAT (2022) Pb(II) adsorption mechanism and capability from aqueous solution using red mud modified by chitosan. Chemosphere 287(3):132279. https://doi.org/10.1016/j.chemosphere. 2021.132279 3. Liu Y, Li B, Lei X, Liu S, Zhu H, Ding E, Ning P (2022) Novel method for high-performance simultaneous removal of NOx and SO2 by coupling yellow phosphorus emulsion with red mud. Chem Eng J 428:131991. https://doi.org/10.1016/j.cej.2021.131991 4. Wang Y, Li Y, Wang G, Wu Y, Yang H, Jin L, Hu S, Hu H (2022) Effect of Fe components in red mud on catalytic pyrolysis of low rank coal. J Energy Inst 100:1–9. https://doi.org/10. 1016/j.joei.2021.10.005 5. Chao X, Zhang T-A, Lyu G, Liang Z, Chen Y (2022) Sustainable application of sodium removal from red mud: Cleaner production of silicon-potassium compound fertilizer. J Clean Prod 352:131601. https://doi.org/10.1016/j.jclepro.2022.131601
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Numerical Analysis of Interference of Machine Foundations on Reinforced Soil P. R. Patil, D. B. Awachat, A. I. Dhatrak, and S. W. Thakare
Abstract Dynamic load acts on machine foundations due to induced vibrations of machines. These vibrations may cause the adjacent soil layers to settle, which may result in several issues. When two foundations are constructed, keeping the spacing between them to a minimum, they interfere with one another, due to which soil below the foundations shows different behaviors compared to an isolated foundation. Geosynthetic material is effective at controlling such settlement and preventing damage. In this paper, numerical analyses were performed to study the effect of interference between closely located machine foundations of various dimensions which are presented. MIDAS GTS NX 3D, which is the finite element software, is used for the modeling and analysis of adjacent machine foundations. The analyses were performed under dynamic loading of sinusoidal nature with varying frequencies. The settling behavior of the interacting foundations was explored under dynamic excitation by altering the spacing between the foundations. The geogrid mattress was kept at different depths and its effect on the settlement was analyzed. From the results of numerical analysis, it was concluded that geogrid reinforcement played a significant role in controlling the spread of vibrations, and thus, settlement of soil strata was reduced. Keywords Machine foundation · Reinforcement · Geogrid · Interference
1 Introduction The design of a machine foundation is considered complex due to the participation of dynamic loads created by the machine’s moving elements. The machine foundation structure vibrates in all the six directions. Translation along the vertical axis and rotation around the vertical axis are two of the six modes that can occur independently P. R. Patil (B) · D. B. Awachat · A. I. Dhatrak · S. W. Thakare Department of Civil Engineering, Government College of Engineering Amravati, Amravati, Maharashtra, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_28
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of any other motion and are referred to as decoupled modes. However, translation along the longitudinal or lateral axis, as well as the associated rotations, always occurs jointly and is referred to as linked modes. The machine foundation system is subjected to coupled sliding and rocking vibration in the field. As a result, dynamic analysis of machine foundations subjected to dynamic loading with different frequencies is required. The stresses created by the machine parts are repetitive in nature, resulting in the foundation soil to settle. The settlement caused by cyclic pressures can be reduced by enhancing the soil’s dynamic qualities. The stiffness and elasticity of the soil are the key qualities that govern its behavior. Soil reinforcement techniques have grown in favor as effective solutions to a variety of geotechnical engineering challenges. The idea behind reinforced earth is to improve the qualities of soil by incorporating metallic strips, fibers, and synthetic materials, among other things, into the soil. Among numerous materials, soil reinforcement using geosynthetics is the most sought-after technology for improving soil stiffness qualities. Geogrids are the finest geosynthetics for protection and stability purposes among the several types available. Several studies have demonstrated the effectiveness of geogrid in enhancing soil stiffness and elasticity. The purpose of this research was to investigate the dynamic response of interference of machine foundations embedded in the soil reinforced with geogrid for varied frequencies.
1.1 Literature Review To study the influence of geogrid to reduce dynamic settlement, various research papers were studied and the review of these papers is given below. Nader and Hataf [1] conducted research on the interference impact of closely located ring and circular foundations resting on reinforced sand using a model and numerical study. The purpose of the research was to assess the influence of interference on the bearing capacity of neighboring circular and ring foundations. The effect of footing distance and reinforcing layer on bearing capacity was evaluated. For numerical modeling, the PLAXIS 3D Foundation finite element computer program was used. According to experimental and analytical results, it was found that when two closely spaced circular and ring foundations stood immediately opposite one other, their ultimate bearing capacity was maximum and declined as the spacing to footing diameter ratio increased. Sahu et al. [2] investigated the dynamic behavior of a model footing on sand strengthened using reinforcement. The free vibration tests were conducted on experimental footings that were provided on unreinforced and reinforced soil beds. Hair strands of human and geogrids were used to strengthen the sand (PET and HDPE). The fiber addition was estimated to be 0.5% of the sand’s dry weight. To achieve the required relative density (80%), each layer of the sand was crushed with a standardized plate vibrator. The free vibration tests were performed in an experimental test
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tank by altering the depths of reinforcement while maintaining a fixed width of reinforcement. According to the findings, hair fiber reinforcement and geogrid reinforcement increased the natural frequency of the surrounding soil. When both reinforcing materials are used, damping was decreased. Sreedhar et al. [3] used block resonance experiments to find the influence of geosynthetic reinforcement on dynamic properties. Several laboratory model block vibration tests were carried out on the test bed, both with and without reinforcements. To reinforce the soil bed, a semi geotextile and a biaxial geogrid were utilized. The influence of these reinforcing components on the dynamic properties of the soil bed, namely the resonance frequency and peak amplitude, was investigated. It was observed that the frequency of vibration had changed, and the peak amplitude had decreased significantly. It was found that using geosynthetics beneath machine foundations assisted in regulating the frequency ratio and controlling the peak amplitude, both of which are essential factors of machine foundation design. Venkateswarlu et al. [4] studied the dynamic performance of a machine foundation supported on soil beds reinforced with geocell. PLAXIS 2D program was chosen for the dynamic analyses. Under the machine foundation, the effectiveness of a geocell with varied infill components was examined. Red soil, sand, and aggregate were examined as possible filling materials. The geocell-reinforced system’s dynamic response was evaluated in terms of settlement amplitude, maximum particle velocity, and soil modulus improvement. According to the findings, the impact of infill materials on geocell effectiveness was negligible. However, of the three evaluated filler materials, aggregate was the most effective. In the existence of aggregate filler material, the displacement magnitude and maximum particle velocity were dropped by 66% and 48%, respectively. Javdanian et al. [6] carried out an investigation into the interference caused by vibrating machine foundations built on sandy soils. FLAC, a numerical finite difference modeling software, was used to examine the dynamic bearing capacity of adjacent shallow foundation systems on sand. The response of shallow strip footings under various situations was evaluated. The impact of soil strength characteristics, shallow foundation design characteristics, and repetitive loads at various distance ratios on foundation carrying capacity was studied. The findings revealed that behavioral interference has a significant impact on the performance of shallow footings under repeated loading. As the spacing ratios between the foundations increased, the interference influence expanded and subsequently decreased. At a distance ratio of 2, behavioral interference had the largest impact on the bearing capacity of footings. When the distance ratio was more than 5, the interference effect was canceled out. Mahmood et al. [5] He carried out a three-dimensional study of the dynamic response of a piled raft foundation subjected to vertical forces. The research took into account numerous elements that influence the amplitude of displacement for deep foundations, including pile cap embedment, pile cap thickness, sand relative density, and the boundary impact. A validation for an experimental piled raft model with a scale factor of (20) was done using a computer software (Plaxis 3D). The sand was modeled using the Mohr–Coulomb model, while the concrete was modeled as a linear elastic material. It was discovered that embedding the pile cap in the soil
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and increasing its thickness resulted in a reduction in the maximum amplitude of displacement. Alzabeebee et al. [7] Using finite element analysis, he investigated the effect of interference on the dynamic response of two active machine foundations. The evaluations took into account loose sand, medium sand, and thick sand, as well as a vibration frequency range of 0.5–20.0 Hz. The results revealed that the interaction of two active machine foundations significantly boosts dynamic settling, with percentage increases ranging from 1 to 77%. The critical distance at which the interference effect ceases was also shown to be dependent on the frequency of vibrations and the rigidity of the soil, with the critical distance increasing as the frequency of vibration decreases or the stiffness of the soil rises. Literature Deficit According to the literature review, numerous investigations have been conducted to investigate the impact of soil type, foundation embedment, foundation type, interference with static foundation, frequency of machine vibration, and amplitude of vibration on the response of machine foundations. However, there has been relatively little research into the response of adjacent machine foundations lying on reinforced soil substrate. As a result, numerical study of adjacent machine foundations resting on reinforced soil bed is essential.
2 Numerical Analysis The current work involved the analysis of adjacent machine foundations placed in reinforced soil beds, as shown in Fig. 1. Foundation soil was reinforced using geogrid. The meaning of symbols used in the figures is as follows: B = width of foundation, L = length of foundation, z = the vertical distance between reinforcing layers, N = number of layers of reinforcement. The analyses of foundation system for adjacent machine foundations were performed using MIDAS GTS NX 3D. The various parameters considered for the study were spacing between footing, number of layers of reinforcement, and frequency of dynamic loading. Table 1 shows various parameters of machine foundation considered for the study and their selected values for analyses. Table 2 shows parameters of soil bed selected for analysis. Geometric models of soil bed and footing were developed according to required dimensions. Soil boundaries were considered at 10B from center of the adjacent foundations. For soil model, 3D line function was used to create outline, and then, ‘Extrude’ function was used to achieve required depth of soil model. For machine foundation 3D line was used to generate geometry and for the whole geometry created was joined using Boolean operation. Material properties were assigned to machine foundation and soil bed. As foundation are made up of concrete material, hence, model selected for machine foundation analysis in present study was ‘Elastic model’. For soil, the model selected for analysis was ‘Mohr–Coulomb’ model. Material
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Fig. 1 Schematic representation of the adjacent machine foundations placed in reinforced soil bed Table 1 Details of parameters selected for analyses of adjacent machine foundations on reinforced soil bed
Table 2 Properties of soil selected for the numerical study
Parameter
Values
Spacing between footings (S) m
3,4, 5, and 6
Number of reinforcement layers (N)
1, 2, 3, and 4
Frequency of dynamic loading ( f ) Hz
5, 10, 15, 20, and 25
Properties
Value
Unit weight
18 kN/m3
Young’s modulus
80,200 kN/m2
Poisson’s ratio
0.3
Angle of internal friction
29.51°
Cohesion
75.7 kN/m2
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Parameter
Value
Young’s modulus of concrete
2 × 107 kN/m2
Unit weight of concrete
24 kN/m3
Poisson’s ratio of concrete
0.15
properties of foundation block and geogrid used in MIDAS GTS NX for the analysis are given below in Tables 3 and 4, respectively. Separate meshing was provided for machine foundation and soil model. In the present study, automesh function was used for meshing. Geogrid layers were provided within the soil bed at different depths, and meshing was done after assigning the properties. Figure 2 shows model of adjacent machine foundations on reinforced soil in MIDAS GTX 3D. To apply dynamic load, cyclic load condition was created for time history analysis case. The foundation was assumed to be subjected to a vertical harmonic excitation with constant force amplitude represented as x(t) = a0 sin (ωt), where ‘x(t)’ was dynamic load intensity, ‘a0 ’ was amplitude, ‘ω’ was natural frequency, ‘t’ was time in seconds. Time forcing function was added by putting appropriate values of amplitude, frequency, and time in above equation. The reciprocating type of machine was considered. Weight of the machine was considered as 10 kN. The force amplitude of 25 kPa was selected. Frequency of machine was selected as 5, 10, 15, 20, and 25 Hz. Period of 5 s was considered. Damping ratio was taken as 0.05. For dynamic analysis, ground surface spring Table 4 Properties of geogrid reinforcement selected for the numerical analysis
Fig. 2 Model of adjacent machine foundations on reinforced soil in MIDAS GTX 3D
Parameter
Value
Young’s modulus
210 kN/m2
Poisson’s ratio
0.33
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boundary was created. It was created to analyze the response of ground for vibrations induced by machines. Cyclic load was applied on foundation surface. Load was selected as time function and further analysis was done.
3 Result and Discussion Figure 2 depicts the variation of dynamic settlements of machine foundation for different frequencies on unreinforced soil. It was found that as the spacing between footings is increased, the corresponding settlement decreased. Also with the increasing frequency, dynamic settlement increased, reaching its maximum value, and then dropped. Figure 3 shows the variation of dynamic settlements of machine foundations on soil bed reinforced with single layer of geogrid. After placement of single layer of geogrid, the dynamic settlement was found to reduce slightly. Further analyses were carried out for adjacent machine foundations on soil bed reinforced with two, three, and four layers of geogrid. Figures 4, 5 and 6 show the variation of dynamic settlements of machine foundations on soil bed reinforced with two, three, and four layers of geogrid, respectively. From the above results, it is observed that as the spacing between the adjacent foundations increases, the settlement of adjacent machine foundations also decreases. Settlement of adjacent machine foundations increases with increase in frequency of dynamic loading up to 20 Hz, and then, it drops for 25 Hz (Fig. 7). 4 3.5
f= 5 Hz
Settelement (mm)
3
f=10 Hz
2.5
f = 15 Hz
2 1.5
f = 20 Hz
1
f=25 Hz
0.5 0
0
2 4 6 Spacing between adjacent machine foundations (m)
8
Fig. 3 Variation of dynamic settlements of machine foundation for different frequencies on unreinforced soil
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Settlement (mm)
Fig. 4 Variation of dynamic settlements of machine foundations on soil bed reinforced with single layer of geogrid 4 3.5 3 2.5 2 1.5 1 0.5 0 0
f =5 Hz f =10 Hz f =15 Hz f =20 Hz f =25 Hz
1
2 3 4 5 6 7 Spacing between adjacent machine foundations (m)
Fig. 5 Variation of dynamic settlements of machine foundations on soil bed reinforced with two layers of geogrid 3.5 Settlement (mm)
3
f=5 Hz
2.5
f=10 Hz
2 1.5
f=15 Hz
1
f=20 Hz
0.5 0
f = 25 Hz
0
1
2 3 4 5 6 Spacing between adjacent machine foundation (m)
7
Fig. 6 Variation of dynamic settlements of machine foundations on soil bed reinforced with three layers of geogrid
Numerical Analysis of Interference of Machine Foundations …
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3.5
f = 5 Hz
Settlement (mm)
3 2.5
f = 10 Hz
2
f = 15 Hz
1.5 1
f =20 Hz
0.5
f =25 Hz
0
0
1
2
3
4
5
6
7
Spacing between adjacent machine foundations (m)
Fig. 7 Dynamic settlements of machine foundations on soil bed reinforced with four layers of geogrid
4 Summary and Conclusions 1. Geogrid reinforcement is found to be effective in limiting the dynamic settlements due to interference of adjacent machine foundations. Percentage drop in the settlement due to reinforcement is found around 41.23%. 2. As the frequency of dynamic loading of machine foundation increases, the dynamic settlement also increases. It attains the maximum value at 20 Hz and drops with further increase in frequency of vibration at 25 Hz. 3. Dynamic settlement reduces significantly as the number of reinforcement layers is increased up to three layers of geogrid reinforcement. With further increase in the number of layers of reinforcement beyond 3, there is no significant decrease in the settlement. Hence, three layers of reinforcement may be considered as optimal number of reinforcement layers. Practical Applications The practical applications of present study are as follows: (1) Optimal numbers of layers of reinforcement for machine foundation can be suggested depending upon the dimensions of adjacent machine foundation. (2) Damages of surrounding buildings due to vibrations of machine can be minimized due to provision of geogrid reinforcement.
References 1. Naderi E, Hataf N (2014) Model testing and numerical investigation of interference effect of closely spaced ring and circular footings on reinforced sand, Geotext Geomembr 42(3):191–200 2. Clement S, Ayothiraman R, Ramana GV (2015) Experimental studies on dynamic response of a block foundation on sand reinforced with geogrid. In: Proceedings of geosynthetics, pp 15–18
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3. Sreedhar MV, Abhishek J (2016) Effect of geosynthetic reinforcement on dynamic characteristics through model block resonance tests. In: Proceedings of Indian geotechnical conference, pp 15–17 4. Venkateswarlu H, Hegde A (2017) Dynamic response of the machine foundation resting on geocell reinforced soil beds. In: Proceedings of Indian geotechnical conference, pp 14–16 5. Mahmood M, Al-Wakel S, Abdulwahhab I (2018) Three-dimensional analysis for piled raft machine foundation embedded in sand. MATEC Web Conf 162:01023. EDP Sciences 6. Javdanian H (2018) Behavioral interference of vibrating machines foundations constructed on sandy soils. Int J Eng 31(4):548–553 7. Alzabeebee S (2020) Dynamic response and design of a skirted strip foundation subjected to vertical vibration. Geomech Eng 20(4):345–358
Development of Design Charts for Rectangular Barrettes Dipika P. Metange, S. W. Thakare, and A. I. Dhatrak
Abstract A cast-in-place-reinforced concrete pile that can withstand axial loads and high moments is called a barrette. This kind of foundation is suitable for all sorts of soil, including boulders and alluvial soil. When very heavy column loads need to be transmitted to a very deep bearing stratum, conventional piles can become unworkable and uneconomical. When there is a high water table and there are a variety of soil types, including sands, silts, and clay, the problem gets more challenging. In some circumstances, in addition to resisting vertical loads, the designer would also need the foundation elements to withstand lateral loads and bending moments in a preferred direction. In these circumstances, rectangular shapes would be preferable to circular shapes. A single laterally loaded large-section barrette may take the place of a group of circular piles due to the barrette’s better resilience to lateral stresses. To compare ultimate lateral capacities and calculate the percentage reduction in crosssectional area due to replacing a group of the circular pile with a single rectangular barrette, 3D barrette models of various sizes and groups of circular pile models were created in the MIDAS GTS NX programme and used in this study. Results showed that a group of circular piles may be replaced by a single rectangular barrette with reduced cross-sectional, which may be cost-effective alternative for conventional circular piles. Keywords Rectangular barrette · Lateral loading · Design chart
D. P. Metange (B) · S. W. Thakare · A. I. Dhatrak Department of Civil Engineering, Government College of Engineering Amravati, Amravati, Maharashtra, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_29
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1 Introduction Barrette foundations have grown in popularity during the past 15 years for numerous civil engineering constructions, including towering skyscrapers, in regions of Asia. Typically, barrette piles are rectangular piles. But many other shapes, such as the cruciform, H, and T shapes, may also be used. Barrettes serve many of the same functions and feature similar designs to traditional circular piles. Because of their excellent carrying capacity for both lateral and vertical loads, foundations for high-rise building barrettes are frequently used. The accomplishment of the necessary socket length in bedrock using rotary pile drilling rigs is widely recognised to be one of the main issues encountered during the building of circular cast in situ piles. The issue is exacerbated by the growing diameter of bored piles and the bedrock’s rising strength and hardness. Additionally, due to their limited capacity, cast in situ individual circular piles become impracticable and expensive when significant superstructural loads are carried to the deeper soil layers. In these circumstances, barrettes provide a deep foundation solution alternative to huge diameter cast in situ piles. By correctly positioning the barrettes, the designer may use barrettes to improve inertia and bend moment resistance without needing to increase the concrete area, in the desired direction. The rectangular design of barrettes prevents them from withstanding equal loads from all directions. This may present a challenge if loads are anticipated from all sides, but it can also be advantageous. The wind hardly ever comes from other directions and usually comes from a prevailing direction. Using this information, barrettes can be positioned so that the major axis is parallel to the direction of the prevailing wind, allowing this side to withstand heavier loads whilst the minor axis can easily handle lighter loads. Because the proportions can be modified to accommodate the loading, the material can be conserved when making the barrette.
2 Literature Review Investigators’ interest in the matter has been raised by the growing benefits of barrette foundations over circular piles. Numerous researchers have carried out experimental and numerical investigations to determine the impact of various parameters on the foundation of a barrette which are given below. Zhang [1] studied the reaction of laterally loaded large-section barrettes, to simulate the responses of the two test barrettes and analyse the impact of loading direction on the lateral response of barrettes. To simulate the lateral response of the test barrettes taking into account five loading directions, nonlinear p-y curves for soils and nonlinear stress–strain relations for barrette concrete and reinforcement are employed. Based on their research, they concluded that the direction of the
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corresponding horizontal displacement is different from the loading direction if the barrette is not loaded along the major or minor axis of the cross section. Karthigeyan et al. [2] performed finite element analyses in three dimensions that demonstrate the major impact of vertical loads on a pile’s lateral response. Both homogeneous clayey soils and homogeneous sandy soils were used for the analyses. According to the results, the lateral response of piles is greatly affected by vertical loads in sandy soils and only little by vertical loads in clayey soils. Additionally, it was discovered that the design bending moments in the piles that were laterally loaded depended on the intensity of the piles’ vertical loads. Wakil and Nazir [3] investigated the reaction of barrettes with a rectangular cross section when loaded laterally. The effects of sand relative density, pile aspect ratio, loading direction, and load eccentricity were examined using 28 model experiments for a laterally loaded barrette. According to this study, a barrette loaded in the direction of the major axis will have higher lateral resistance than a barrette loaded in the direction of the minor axis. The lateral capacity of the barrettes is significantly impacted by the relative density of the sand. The ratio of the lateral capacity of the barrettes loaded in the direction of the major axis compared to the barrettes loaded in the direction of the minor axis decreases as the relative density of the sand rises. Chavda and Dodagoudar [4] carried out the finite element (FE) employing plane strain idealisation and determine a single barrette’s maximum capacity. The evaluation of the ultimate capacity uses the four material models Mohr–Coulomb (MC), hardening soil (HS), hardening soil with small-strain stiffness (HSsmall), and soft soil (SS). It is discovered that regardless of the deformation parameter values and material models (MC, HS, Hssmall, and SS), the single barrette’s maximum capacity never changes. The ultimate capacity is influenced by the soil’s strength parameters, unit weight, surcharge at the ground level, interface strength, and barrette geometry.
3 Work Done in Present Study The detailed 3D model of a rectangular barrette with a soil block and circular pile was modelled in the FEM software programme MIDAS GTS NX 3D. Analyses were carried out on various sizes of rectangular barrette in different types of soil, viz. clayey, sandy, and c-F soil for lateral loading. The analyses in the present study consisted of modelling of the rectangular barrette and circular pile in different types of soil with influential parameters cross-section areas of barrette, the diameter of circular pile, number of piles in the group, and type of soil. Figure 1 shows a typical cross section of rectangular barrette. The various parameters considered for the study and their selected values for analysis are shown in Table 1. Length of the pile was kept constant, equal to 30 m in all cases. Material properties were assigned to a barrette, pile cap, and soil bed. For numerical analyses, the properties of clay and sand were selected from S. Karthigeyan et al. [5]. Properties of c-F soil were selected from GTI Report Gaddigodam [6] given in
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Fig. 1 Cross section of rectangular barrette considered for numerical analyses
Table 1 Details of variable parameters selected for analysis S. No.
Pile type
Parameter
1
Rectangular barrette
Breadth (B) = 0.8 and 1.0 m
Circular pile
Diameter (D) = 0.8 and 1.0 m
2
Width (W) = 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 6.0, 7.0, 8.0, 9.0 and 10 m Number of pile in group = 2, 4 and 6
Table 2, and properties of concrete for barrette and pile cap were selected from S. Karthigeyan et al. [5] given in Table 3. Lateral load and self-weight were applied, on the selected face of the pile cap, and the ‘pressure’ type of load was used with a required intensity of load. Figure 2 shows Table 2 Properties of soils used in the numerical analysis
Properties Unit weight, γ
(kN/m3 )
Clay
Sand
c-phi
18
20
18
Young’s modulus, E (Mpa)
40
50
50
Poisson’s ratio, v
0.3
0.3
0.3
Angle of internal friction, (°)
0
36
31
Cohesion, c (kPa)
100
0
12
Development of Design Charts for Rectangular Barrettes Table 3 Properties of concrete used in the numerical analysis
351
Properties
Value
Grade
M25
Unit weight (γ)
24 kN/m3
Young’s modulus (E)
25,000 Mpa
Poisson’s ratio (v)
0.15
Fig. 2 Window in MIDAS GTS NX 3D after application of load
the geometry of the rectangular barrette, pile cap, and soil block model developed in MIDAS GTS NX 3D after the application of load. Analyses were carried out for every individual case, by applying lateral load in increments. The ultimate lateral capacities were considered as per criteria laid down by IS: 2911-1985 (Part-IV). Ultimate lateral capacities were considered to correspond at 12 mm deflection.
4 Results and Discussion The parameters considered for the analyses were width and breadth of barrette, type of soil, viz. clayey soil, sandy soil, and c-F soil for lateral loading. The load– displacement curves for each case were generated, and ultimate loads were obtained
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for different cross sections of the barrette pile as per criteria laid down by IS: 2911– 1985 (Part-IV). Design charts were then developed by plotting the lateral capacities vs. breadth of the barrette. Such charts were developed for various widths of barrettes. Further analyses were carried out to determine the ultimate lateral capacities of a group of circular piles of diameters, viz. 0.8 m and 1.0 m in clayey soil, sandy soil, and c-F soil. Capacities of a group of circular piles were then compared with those of a single rectangular barrette, with the help of design charts developed. The percentage reduction in the cross-section areas due to the replacement of circular piles with single rectangular barrettes was determined. The optimum sizes of the single rectangular barrettes to replace the group of circular piles were then decided.
4.1 Performance of Rectangular Barrette Replacement of a group of circular piles in clayey, sandy, and c-F soil consisting of 2, 4, and 6 piles with a single barrette was considered using design charts for barrette of width 0.8 m and 1.0 m. A typical design chart for barrette with a width of 0.8 m and 1.0 m is shown in Fig. 3 for the replacement of group 2 piles in clay. Corresponding percentage reductions in the cross-sectional areas due to replacement were determined as given in Table 4 for lateral loading in clay. From above Fig. 3 and Table 4, it is seen that the group of two circular piles with a diameter of 0.8 m may be replaced by a single barrette of size 1.2 × 0.8 m, and the cross-section area is reduced by 4%. Whereas, the percentage reduction in area
Fig. 3 Replacement of group of two circular pile by single rectangular barrettes in clay
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Table 4 Percentage reduction in cross-section area due to replacement of group of 2, 4, and 6 circular pile with single barrette in clay and c-F soil Type of soil
Diameter of circular pile (m)
Clay
D = 0.8
D = 1.0
Sand
D = 0.8
D = 1.0
c-F soil
D = 0.8
D = 1.0
No. of circular pile in group
Lateral capacity (kN)
Area of group of circular pile, AC (m2 )
Single rectangular barrette dimension, W × B (m)
Area of single rectangular barrette, AB (m2 )
Percentage reduction in cross section area (%)
2
2007
1
0.8 × 1.2
0.96
4
4
3351
2
0.8 × 2.2
1.76
12
6
3951
3
0.8 × 3.1
2.48
17.33
2
2452
1.57
1.0 × 1.41
1.41
10.19
4
3603
3.14
1.0 × 3.14
2.5
20.38
6
4721
4.71
1.0 × 4.5
4.5
4.45
2
1580
1
0.8 × 1.02
0.816
18.4
4
2511
2
0.8 × 1.5
1.2
40
6
2979
3
0.8 × 1.75
1.36
82
2
2032
1.57
1.0 × 1.2
1.2
23.56
4
3022
3.14
1.0 × 1.8
1.8
42.67
6
4143
4.71
1.0 × 2.8
2.8
40.55
2
2095
1
0.8 × 1.2
0.96
4
4
3506
2
0.8 × 2.5
2
0
6
4019
3
0.8 × 3.4
2.72
9.33
2
2574
1.57
1.0 × 1.5
1.5
4.45
4
3833
3.14
1.0 × 2.9
2.9
7.64
6
5029
4.71
1.0 × 4.6
4.6
2.33
is 10.19% if the group of two circular piles of diameter 1.0 m is replaced by a single barrette of size 1.41 × 1 m. Similarly, the replacement of a group of 2, 4, and 6 circular piles by a single rectangular barrette was considered using design charts for clayey, sandy, and c-F soil developed, and corresponding percentage reductions in cross-section areas were determined as shown in Table 4.
4.2 Limitations of Present Study Limitations of the present study are that the design charts are developed for limited sizes of rectangular barrette subjected to lateral loading. Similar charts may be developed considering wide range of sizes of barrettes and also for different type loadings, such as vertical loading and combined loading.
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5 Conclusions Based on the results of the analyses, the following broad conclusions are drawn: 1. A group of circular piles may be replaced by a single rectangular barrette having equal lateral capacity but with a reduced in cross-section area, thus resulting in a saving in cost. 2. In the case of sandy soils, the percentage reduction in an area increases with an increase in the number of piles in a group of circular piles with a diameter of 0.8 m. 3. In the case of clayey soils, the percentage reduction in cross-section area due to replacement with a single barrette is highest (20.38%) in the case of four piles with a diameter of 1.0 m. 4. In the case of sandy soils, the percentage reduction in cross-section area due to replacement with a single barrette is highest (42.67%) in the case of four piles with a diameter of 1.0 m. 5. In the case of c-F soils, the percentage reduction in cross-section area due to replacement with a single barrette is highest (7.64%) in the case of four piles with a diameter of 1.0 m.
References 1. Zhang LM (2003) Behavior of laterally loaded large-section barrettes. Ascelibrary.org by University of Texas at San Antonio, ASCE 2. Karthigeyan S, Ramakrishna VV, Rajagopal K (2015) Numerical investigation of the effect of vertical load on the lateral response of piles. J Geotech Geoenvironmen Eng ASCE 3. El Wakil AZ, Nazir AK (2013) Behavior of laterally loaded small scale barrettes in sand. Production hosting. Ain Shams University 4. Chavda JT, Dodagoudar GR (2017) Evaluation of ultimate capacity of a single barrette using finite element analysis. In: Indian geotechnical conference. IIT Guwahati, India 5. Report on “Detailed geotechnical investigation for metro station on East-West corridor in Reach2 of Nagpur metro rail project”. ITD Cementation India Limited 6. El Gendy M, Ibrahim H, El Arabi (2017) Analyzing single barrettes as rigid support by composed coefficient technique. Malays J Civil Eng
Performance of Cantilever Retaining Wall with Deformable Inclusions under Dynamic Loading Rajani J. Vyawahare, A. I. Dhatrak, and S. W. Thakare
Abstract Earth retaining walls should be built to withstand both static and dynamic increments in earth pressure, particularly in earthquake-prone areas. Various earlier types of research suggest that geofoam inclusions are effective in reducing the dynamic earth pressure on the cantilever retaining wall. In this research, shake table tests on small-scale models of retaining walls were conducted to investigate the effectiveness of geofoam compressible inclusions as a seismic isolator to lessen dynamic loads against retaining wall structures. The results of these tests are compared to those of identical models of retaining walls with backfill only and without any inclusion. Experimental investigation shows that dynamic earth pressure and wall displacement reduced up to 35% and 40%, respectively. Keywords EPS geofoam · Shake table test · Horizontal displacement
1 Introduction Recent earthquakes in India, such as those in Latur (1993), Jabalpur (1997), and Bhuj (2001), have highlighted the need to understand how different infrastructures behave when subjected to seismic conditions. Several road embankments and embankment dams failed or experienced significant distress during the Bhuj Earthquake (EERI, 2001) [1]. Many experimental and numerical investigations were undertaken at the time to reduce dynamic earth pressures and their effect on retaining walls [2]. One of the challenges faced by civil engineers is mitigating the severe human and economic consequences of structural dynamic responses under earthquake vibrations. A model test on the shaking table is one of the ways to study the behavior of embankment slopes and retaining walls under dynamic loading in the laboratory [3]. The dynamic response of any type of retaining wall is quite complex. The static and dynamic R. J. Vyawahare (B) · A. I. Dhatrak · S. W. Thakare Department of Civil Engineering, Government College of Engineering Amravati, Amravati, Maharashtra, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_30
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responses of the wall depend on the response of the soil below the wall, the type of backfill, the inertial and flexural response of the wall itself, and the natural motions. The dynamic response of the retaining wall can be understood from the model test and numerical analyses [4]. The present study aims to investigate the reduction in dynamic earth pressure and wall displacement by the use of EPS geofoam [5]. Models of cantilever retaining wall were placed in a rigid solid box along with backfill and geofoam inclusion and subjected to dynamic loads of various amplitudes and frequencies of motion [6]. Various sensors were attached to the wall model such as an accelerometer, LVDT, and pressure transducers at selected locations to measure the accelerations, displacements, and pressures at required locations. Results obtained from experiments were compared with those of an identical model setup, but without any inclusion behind the wall. Investigations were also carried out to find out the effect of the height of the wall and the characteristics of the seismic excitation (frequency and amplitude of vibration) on the dynamic earth pressures and the displacements of the wall.
2 Literature Review Zekkos et al. [7] conducted numerical analyses by using 2D finite element code PLAXIS to investigate the effect of EPS geofoam compressible inclusions in the reduction of seismic earth pressure and horizontal displacement increment. When EPS 100 was used as compressible inclusion, reduction in the dynamic pressure and horizontal displacement was 20% and 50%, respectively. Bathurst et al. [4] tested expanded polystyrene (EPS) geofoam buffers for seismic load reduction against rigid basement and soil retaining walls. For the preparation of design charts, a numerical study was conducted using FLAC model. EPS geofoam of 15 cm thickness with five different densities, viz: 16, 14, 12, 6, and 1.3 kg/m3, was used. Reduction in dynamic earth loads was found up to 15–40%. The result shows that dynamic earth force reduction is more for geofoam buffers with the lowest density. Ertugrul et al. [3] performed 1-g shake table tests on reduced-scale flexible cantilever retaining wall models. Instead of conventional backfill, composite backfill was used which was made of a deformable geofoam inclusion and granular cohesionless soil. The granular material which was used as a backfill material was classified as poorly graded sand with maximum and minimum void ratio of 0.745 and 0.436, respectively. EPS and XPS geofoam materials having densities of 15 kg/ m3 and 22 kg/m3, respectively, were used as deformable panels for shake table tests. Dynamic earth pressures and displacements of the retaining walls at various locations, with deformable inclusions, were compared with the models without any inclusions. Komak Panah et al. [8] conducted a shake table test on soil retaining walls reinforced by polymeric strips and examined the seismic behavior of reinforced soil retaining walls with polymeric strips. A series of 1-g shaking table tests were
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employed on 80 cm high reinforced soil wall models. The amount of wall displacement increases substantially from 1.2 to 7 times under various waves when the reinforcing length is decreased from 0.7H to 0.5H at the bottom layer of the wall.
3 Experimental Investigation The experimental investigations were performed using a 0.6 m × 0.6 m shaking table facility in the Government College of Engineering, Amravati, as shown in Fig. 1. The maximum range of frequency and amplitude for the shake table was 0–10 Hz and 50 mm, respectively. Two prototype walls were selected with a heights of 6 m and 5.4 m. For the model study, a scale ratio of 1:15 was selected considering the dimensions of the available test facility. Cement mortar with a proportion of 1:2 was used for casting the wall models. Two model walls of heights 400 mm and 360 mm were tested during the experiment, as shown in Fig. 2. Wall models were placed on a 0.2 m thick foundation bed of soil having a relative density of 55%. Fig. 1 Shake table setup used in experimental investigation
Fig. 2 Retaining wall model
358 Table 1 Properties of the sand used for experimental investigations
Table 2 Properties of EPS geofoam material
R. J. Vyawahare et al.
Sr. no
Properties of sand
Values
1
Specific gravity
2.58
2
Bulk unit weight (γ) (kN/m3 )
15.95
3
Maximum unit weight (γmax )
(kN/m3 )
16.37
4
Minimum unit weight (γmin ) (kN/m3 )
14.41
5
Angle of internal friction (φ)
36°
6
Coefficient of uniformity (Cu )
3.03
7
Coefficient of curvature (Cc )
1.16
8
Relative density
55%
Size
Width
Length
Thickness
500 mm
1000 mm
50 mm
Density
18 kg/m3
Raw material
Expanded polystyrene
3.1 Backfill Material Locally available sand, called “Kanhan sand” passing through 4.75 mm, was used as a dry cohesionless backfill material. The properties of sand are listed in Table 1. The relative density of backfill was kept constant in all the tests.
3.2 Inclusion Material Commercially available EPS geofoam with trade name ‘EPS 18’ was used as deformable inclusions [9]. The properties of EPS material used for experimental investigation are shown in Table 2.
3.3 Test Methodology The experimental study included the testing of the retaining wall model in a shaking table test setup. The parameters considered for experimental investigations were the height of the model wall, frequency, and amplitude vibrations. Table 3 shows parameters considered for experimental investigations.
Performance of Cantilever Retaining Wall with Deformable Inclusions … Table 3 Details of parameters considered for experimental investigations
Parameters
Description
Wall height, H (mm)
400 and 360
Excitation frequency, f (Hz)
2 and 3
Amplitude ‘a’ (mm)
5, 7.5, and 10
359
3.4 Experimental Test Procedure A foundation sand bed of 20 cm thickness was prepared with relative density (Dr) 55% by rainfall method. The retaining wall model was then placed on the sand bed. Two accelerometers were placed, one at the base (A1) and the other at the top of the backfill material (A2). Pressure transducers were placed at the base and middle height of the wall [10]. The base of the wall was then embedded in the foundation soil bed for 50 mm on the front side of the wall. Backfill material was filled up to the full height of the wall. For the measurement of horizontal displacements, linear variable displacement transducers (LVDT) was attached horizontally at the top of the retaining wall. Figure 3 shows a diagrammatic representation of the test setup along with the model and locations of various measuring devices. Two different series of shaking table tests were conducted, viz., (i) Series A: shaking table tests on model retaining wall without any inclusions, and (ii) Series B: shaking table test on model retaining wall with provision geofoam. Two test setups are shown in Fig. 4.
Fig. 3 Schematic view of the experimental setup with model wall and geofoam
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Fig. 4 Shake table test setup of retaining wall: a without any inclusion provision b with the provision of inclusion
4 Result and Discussion Dynamic earth pressures, accelerations, and horizontal displacements of the wall models were observed during shake table tests for various amplitudes and frequencies of vibrations. Variation of dynamic earth pressure versus time was plotted from the values obtained from the data logger as shown in Fig. 5. The values of dynamic earth pressure on a wall at a given location were determined as the average of all the values of the pressure obtained from the data logger over the period.
Fig. 5 Typical graph of dynamic earth pressure at mid-height of a wall for 5 mm amplitude and 3 Hz frequency (without inclusion for H = 360 mm)
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Table 4 Dynamic earth pressure on retaining wall for H = 400 mm Amplitude (mm) ±5 ± 7.5 ± 10
Frequency (Hz)
Pressure (kPa) (without geofoam)
Pressure (kPa) (with geofoam)
P1
P2
P1
P2
2
1.29
2.3
0.94
1.76
3
1.9
2.9
1.34
2.14
2
1.89
2.89
1.31
2.08
3
2.4
3.34
1.61
2.34
2
2.9
3.16
1.89
2.21
3
3.3
3.63
2.12
2.48
Table 5 Dynamic earth pressure on retaining wall for H = 360 mm Amplitude (mm) ±5 ± 7.5 ± 10
Frequency (Hz)
Pressure (kPa) (without geofoam)
Pressure (kPa) (with geofoam)
P1
P2
P1
P2
2
1.03
1.91
0.74
1.41
3
1.6
2.3
1.12
1.65
2
1.57
2.68
1.08
1.91
3
1.88
3.37
1.24
2.26
2
2.66
3.09
1.68
2.1
3
3.21
3.65
1.97
2.37
4.1 Dynamic Earth Pressure on the Wall Dynamic earth pressure on a wall at mid-height (P1) and base (P2) for various frequencies and amplitudes of vibrations with and without geofoam is shown in Table 4 and 5 for wall heights of 400 mm and 360 mm, respectively. Table 6 shows the percentage reductions in dynamic earth pressures on the retaining wall at mid-height and bottom for various frequencies and amplitudes of vibrations. Variation of percentage reduction in dynamic earth pressure for wall of 400 mm height is shown in Fig. 6. Variation of percentage reduction in dynamic earth pressure for a wall of 360 mm height is shown in Fig. 7.
4.2 Horizontal Displacement of Retaining Wall Horizontal displacements of the retaining wall model during dynamic loading with and without geofoam for heights 400 mm and 360 mm are given in Table 7.
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Table 6 Percentage reduction in dynamic earth pressure on retaining wall Amplitude (mm)
Frequency (Hz)
Percentage reduction in dynamic earth pressure (%) H = 400 mm P1
±5 ± 7.5 ± 10
H = 360 P2
P1
P2
2
27.1
23.5
28.2
26.2
3
29.5
26.2
30
28.3
2
30.7
28
31.2
28.7
3
32.9
29.9
34
32.9
2
34.8
29.6
36.8
32
3
35.8
31.7
38.6
35.1
Fig. 6 Variation of percentage reductions in dynamic earth pressure at mid-height and bottom for 2 Hz and 3 Hz frequencies (H = 400 mm) with respect to amplitude
Fig. 7 Variation of percentage reductions in dynamic earth pressure at mid-height and bottom for 2 Hz and 3 Hz frequencies (H = 360 mm) with respect to amplitude
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Table 7 Horizontal displacements of retaining wall model and percentage of reduction in horizontal displacement during shake table tests Height of wall Amplitude Frequency Horizontal displacement of model Percentage of wall (cm) reduction in (mm) (mm) (Hz) Without inclusion With geofoam horizontal displacement (%) 400
±5 ± 7.5 ± 10
360
±5 ± 7.5 ± 10
2
0.8
0.5
37.5
3
1.5
1.0
33.33
2
1.3
0.9
30.76
3
2
1.4
30
2
1.9
1.6
15.78
3
2.3
1.9
17.39
2
1.5
0.9
40
3
1.8
1.1
38.88
2
1.9
1.1
42.10
3
2.4
1.5
37.5
2
2.2
1.7
22.72
3
3.4
2.4
29.41
Variations in percentage reductions in the horizontal displacement of a wall of height 400 mm and 360 mm for the amplitude of ± 5 mm, ± 7.5 mm, and ± 10 mm with frequencies of 2 Hz and 3 Hz are shown in Fig. 8.
Fig. 8 Variation of percentage reductions in the horizontal displacement of a wall of height 400 mm and 360 mm for frequencies of 2 and 3 Hz with respect to amplitude
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5 Conclusion 1. There is a reduction in dynamic earth pressure and horizontal displacement of the wall due to the provision of geofoam inclusion behind the wall. 2. Percentage reduction in dynamic earth pressure due to the provision of geofoam inclusion was higher at mid-height of the wall than at the bottom. 3. Reduction in dynamic earth pressure is higher in the case of a wall of 360 mm height (38.6%) as compared to that of a wall of 400 mm height (35.8%) at mid-height of wall. 4. Reduction in dynamic earth pressure is higher in the case of a wall of smaller height (35.1%) compared to that of a wall of greater height (31.7%) at base of wall. 5. Horizontal displacement of wall is reduced up to 42.10%. Percentage reduction in displacement increases as the amplitude and frequency of vibration decrease. Geofoam’s efficiency toward reduction of dynamic earth pressure increases with an increase in frequency and amplitude of vibration. 6. Maximum results obtained for dynamic earth pressure reduction are 35.8 and 31.7% at mid-height and base of wall, respectively, for a model of 360 mm height for 10 mm amplitude and 3 Hz frequency of vibration. 7. When wall is subjected to maximum dynamic vibrations (10 mm amplitude and 3 Hz), percentage reductions in settlements are 17.39% and 29.41% for 400 mm and 360 mm wall model, respectively. 8. The experimental result demonstrates that there are significant differences between the dynamic behaviors of retaining walls provided with and without geofoam.
References 1. Giri D, Sengupta A (2010) Performance of small scale model slopes in shaking table tests. IGC 2. Salem AN, Ezzeldine OY, Amer MI (2020) Seismic loading on cantilever retaining walls: full-scale dynamic analysis. Soil Dyn Earthquake Eng 3. Ertugrul OL, Trandafir AC (2014) Seismic earth pressures on flexible cantilever retaining walls with deformable inclusions. J Rock Mech Geotech Eng, ASCE 4. Bathurst RJ, Zarnani S (2013) Earthquake load attenuation using EPS geofoam buffers in rigid wall applications. Indian Geotech J 5. di Santolo AS, Evangelista A (2012) Active earth pressure on cantilever retaining walls 6. Ertugrul OL, Trandafir (2012) Reduction of lateral earth forces on yielding flexible retaining walls by EPS geofoam inclusions. GeoCongress 7. Athanasopoulos Zekkos A, Lamote K, Athanasopoulos GA (2012) Use of EPS geofoam compressible inclusions for reducing the earthquake effects on yielding earth retaining structures. Soil Dyn Earthquake Eng 8. Panah AK, Yazdi M, Ghalandarzadeh A (2015) Shaking table tests on soil retaining walls reinforced by polymeric strips. Geotext Geomembr
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9. Wang D (2010) Numerical analysis on vibration mitigation effect of EPS geofoam on retaining wall. Adv Mater Res, ASCE 10. Yang C, Zhang JJ, Honglue Q, Junwei B, Feichen L (2015) Seismic earth pressures of retaining wall from large shaking table tests
Numerical Analysis of H-Shape Barrette Pile Subjected to Vertical and Lateral Loadings A. B. Khan , S. W. Thakare, and A. I. Dhatrak
Abstract Due to a significant pressure transmission on the earth, deep foundations are required for the design of high-rise structures. The foundations of such high-rise buildings employ barrettes, which have enhanced lateral surfaces and can detect large, considerable vertical and horizontal stresses and so can replace conventional circular piles. In the present study, the ultimate vertical and lateral capacities of H-shaped barrette piles were determined by performing numerical analysis using MIDAS GTS NX in clayey, sandy and c-φ types of soil. In order to calculate the percentage increase in the ultimate vertical and lateral capacities, these results were compared with those obtained using circular piles with the same cross-sectional area. The results showed that H-shaped barrette pile shows greater ultimate vertical and lateral capacities as compared with conventional circular piles having the same cross-sectional area and so proves to be economical. Keywords H-shaped barrette · Vertical capacity · Lateral capacity · Percentage increase in ultimate capacities
1 Introduction Barrettes are cast-in-place reinforced concrete piles. It may also be defined as a rectangular diaphragm wall element that can be used as deep foundation. The word ‘barrette’ is of French linguistic origin. It describes a concrete replacement pile created in a compacted bentonite or polymer slurry beneath a short, deep trench created by diaphragm walling machinery. Barrettes provide many of the same functions and feature similar designs as conventional piles. As compared to conventional circular piles of the same cross-section, barrettes offer better resistance to both horizontal and vertical pressures. They offer an alternative to drilled shafts or broad A. B. Khan (B) · S. W. Thakare · A. I. Dhatrak Department of Civil Engineering, Government College of Engineering Amravati, Amravati, Maharashtra, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_31
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diameter boring and cast-in-place piles. In order to resist heavy vertical loads by shaft resistance as compared to a circular pile, a barrette has a higher specific surface. The capability of a single barrette can frequently substitute multiple conventional circular piles and thus result in a foundation system that is efficient, affordable and reliable. This has the added benefit of time and money savings. One of the key benefits of the barrette piles is that they have a significantly higher bearing capacity than the conventional circular pile, which is essential for being able to handle the rising large structures’ need of loading. Additionally, the time needed to trench barrette piles is shorter than the time needed to drill circular piles. Barrettes offer more resistance to bending moments and horizontal stress than circular piles. Without expanding the concrete area, it is possible to improve the inertia and bending moment resistance by precisely positioning the barrette. Barrettes are large concrete piers that are often rectangular in design but can be any other shape as long as the perimeter is primarily made of straight lines and correct angles. Different types of cross-sections can be created by employing drilling equipment. A standard barrette cross-section ranges from 2.22 to 7.0 by 0.62 to 1.52 m. The length of these barrettes can reach over 52 m down into the ground. Different types of cross-sections including T-shape, H-shape, I-shape, Y-shape, L-shape and cruciform are commonly used. These composite shapes are possible with two or more bites of grab equipment of construction. A review of literature related with field, numerical, analytical and experimental studies conducted on barrette piles is presented below. Submaneewong et al. [1] presented the performance of T-shape barrette pile against lateral force and compared the measured and predicted pile movements under lateral loading. To evaluate the lateral load capacity of T-shape barrette and bored piles, static pile load tests were performed. They found that in the numerical analysis, lateral pile head movement of both T-shape barrette and bored pile without considering cracked section tends to overestimate the pile capacity. EI Wakil et al. [2] discussed the findings from a study on how laterally loaded small-scale barrettes behave in sand. Their objective was to examine the response of rectangle cross-sectional barrettes with lateral loading. The lateral displacement of the barrette head was found to be decreased by adding rigidity to the flexure of the barrette. Chavda et al. [3] evaluated the ultimate capacity of a single barrette with the use of finite element analysis. The influence of factors like unit weight of the soil, strength parameters’ surcharge, deformation parameters, interface strength between the barrette and soil and geometry of the barrette on the ultimate capacity of a single barrette was evaluated. It was concluded that the ultimate capacity is influenced by the strength parameters of the soil, surcharge at ground level, interface strength and geometry of barrette. Poulos et al. [4] studied the application of fundamental analysis methods using common circular cross-section piles. The performance of the corresponding piles was matched with the finite element results of barrettes. The computer program CLAP was used to analyze single barrettes and groups of barrettes under either vertical or horizontal load. It was shown that for single barrettes and groups of barrettes under
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either vertical or lateral load, it is possible to model barrette behavior approximately but adequately using equivalent circular piles. Qureshi et al. [5] reported the results of experiment on barrette foundations of different shapes, including rectangular, T-shaped, cruciform and H-shaped, resting in sand and being loaded vertically. According to their results, barrettes have significantly higher ultimate vertical capacities than circular piles with the same crosssectional area. They concluded that shape of the barrette influences the ultimate vertical capacity of the pile.
2 Methodology In order to evaluate ultimate vertical and lateral load-carrying capacities, the analyses in the present work involved modeling of a single H-shaped barrette pile and a circular pile with the same cross-sectional area. The type of loading included vertical loading and lateral loading. These analyses were carried for different widths (B) of 0.8 and 1.0 m and breadths (W) of 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 and 5.0 m of H-shaped barrette piles in clayey soil, sandy soil and c-phi soil. The length of pile was fixed at 30 m in all cases. Table 1 shows the shapes of piles and their dimensions selected for the analyses. The material and soil properties of clay and sand were taken from Kartigeyan et al. [6] and properties of c-φ type of soil were taken from GTI report of Gaddigodam station [7], Nagpur, and are shown in Table 2. The geometry of H-shaped barrette pile along with its pile cap and soil block was developed in MIDAS GTS NX software. For creating H-shaped barrette pile, three rectangles of required dimensions were used and surface Boolean operation was used Table 1 Shapes of piles and their dimensions for analysis S. Cross-section of pile No.
Shape
Description
1
Circular D
Diameter 2.117, 2.451, 2.745, 3.01, 3.254, 3.481, 3.694, 2.646, 2.985, 3.289, 3.568, 3.826, 4.068
2
H-shape W
Breadth
2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0
Width
0.8,1.0
Symbol Meaning Dimensions (m)
B
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Table 2 Material and soil properties assigned for analysis [6, 7] Property
Unit
Pile, pile cap
Type of soil Clay
Sand
C-phi
Elastic model
Mohr–Coulomb
Mohr–Coulomb
Mohr–Coulomb
Elastic kN/m2 modulus (E)
25,000
40,000
50,000
50,000
Poisson’s ratio (ν)
–
0.15
0.40
0.30
0.30
Unit weight (γ)
kN/m3
24
18
20
18
Unit weight (saturated)
kN/m3
–
19
21
21
Cohesion (c) kN/m2
–
100
0
31
–
0
36
12
Material model
Friction angle (φ)
–
Deg
for joining the three rectangular geometries. Also, ‘Extrude’ function was later used to achieve the required depth of the H-shaped barrette pile. In the next step, material and attribute properties were assigned for the pile, pile cap and soil block. As pile and pile cap are completely made up of concrete material, hence model selected for analysis in the present study was ‘Elastic model’. For soil block, the model selected for analysis was ‘Mohr–Coulomb’ model. Piles were modeled as beam elements in 3D. The layers of the soil were modeled as plain strain elements in 3D. Also, separate meshing was provided for pile, pile cap and soil block. The automesh function was employed for meshing in the current work. The number of elements used to create a mesh varies depending on the dimension. In order to produce more precise results, finer meshing was given. Next, interface elements were created. If interface element is not provided, then results may vary more than 10% of those models used for validation. Thus, the most appropriate results are obtained with interface element factor 0.5. Then, autoboundary condition was defined. This means that the target mesh set is selected to automatically create constraint conditions. The ground conditions for general analysis are set automatically in this step. A uniformly distributed load (pressure type) was applied on the pile cap, and self-weight of geometry was provided. For the analysis, ‘Non-linear static’ solution type was selected. A typical H-shaped barrette pile along with its pile cap and soil block modeled for the analysis in MIDAS GTS NX is shown in Fig. 1. The analyses were performed for every individual case, by applying the load in increments. The typical load–displacement curves as shown in Fig. 2 can be used to visualize the relationship between the applied loads and the resulting displacements of a certain point in the geometry. In general, the X-axis relates to the load versus Y-axis which relates to the displacement (settlements) of a particular node. In this
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Fig. 1 Typical H-shaped barrette pile along with its pile cap and soil block modeled for the analysis in MIDAS GTS NX
way, ultimate load-carrying capacity was obtained for H-shaped barrette pile as per criteria laid down by IS: 2911-1985 (Part-IV). Later, percentage increase in ultimate vertical and lateral capacities of H-shaped barrette piles as compared to circular piles of same cross-sectional area was determined corresponding to various dimensions of H-shaped barrette pile. The various criteria for ultimate vertical and lateral load-carrying capacities are as follows [IS: 2911-1985 (Part-IV)]. In the case of a predominantly friction pile, the load versus penetration curve will either show a peak and a subsequent decreasing trend or a peak followed by almost a straight line, as shown in Fig. 3. The peak load marked as A in Fig. 3 will represent the ultimate load capacity of pile. For end bearing pile, the load that corresponds to the penetration equivalent to 10% of the pile diameter can be used to determine the ultimate load capacity, and the ultimate lateral capacities were considered corresponding at 12 mm deflection.
0
10000
Ultimate capacity (kN) Load (kN) 20000 30000 40000
Settlement (mm)
0 -50 -100 -150
Fig. 2 Typical load versus displacement curve
50000
60000
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Fig. 3 Friction pile criteria as per IS: 2911-1985 (Part-IV) [8]
3 Results and Discussion The parameters considered for the analyses were cross-sectional area of barrettes and types of soil and loading. The ultimate vertical and lateral capacities for H-shaped barrette piles of various widths (B) and breadths (W ) and circular piles of same cross-sectional area in clayey, sandy and c-φ soils for vertical and lateral loadings are shown in Tables 3, 4 and 5, respectively.
3.1 Percentage Increase in Vertical and Lateral Capacities in Clayey, Sandy and c-Φ Soils The percentage increase in vertical and lateral capacities of H-shaped barrette pile as compared to circular piles of similar cross-sectional areas in clayey, sandy, c-φ was calculated as shown in Table 6. The variation of percentage increase in vertical and lateral capacities of H-shaped barrette pile as compared to circular pile, with respect to widths of barrette in clayey soil, is shown in Figs. 4 and 5, respectively. These figures show that there is a decreasing trend in the percentage increase in the vertical capacities and an increasing trend in the percentage increase in the lateral capacities of H-shaped barrette piles in clayey soil. This indicates that the H-shape barrettes of smaller breadths (W ) are more effective for vertical loading and those of larger breadths are effective for lateral loading, in case of clayey soils. Similarly, the variation of percentage increase in vertical and lateral capacities of H-shaped barrette pile as compared to circular pile of similar cross-sections, with respect to widths of barrette in sandy and c-φ soils, were plotted and similar trends were observed in sandy soil.
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Table 3 Ultimate vertical and lateral capacities of circular and H-shaped barrette piles in clayey soil Single pile
Dimensions (m)
H-shape barrette
B = 0.8, W = 2.0
Circle H-shape barrette
Area (m2 )
Vertical capacity (kN)
Lateral capacity (kN)
3.52
34,000
2775
d = 2.117
3.52
27,000
2392
B = 0.8, W = 2.5
4.72
40,000
3273
Circle
d = 2.451
4.72
32,000
2580
H-shape barrette
B = 0.8, W = 3.0
5.92
45,000
3862
Circle
d = 2.745
5.92
37,000
2902
H-shape barrette
B = 0.8, W = 3.5
7.12
48,000
4710
Circle
d = 3.010
7.12
39,000
3031
H-shape barrette
B = 0.8, W = 4.0
8.32
50,000
4968
Circle
d = 3.254
8.32
42,000
3173
H-shape barrette
B = 0.8, W = 4.5
9.52
52,000
5638
Circle
d = 3.481
9.52
44,566
3385
H-shape barrette
B = 0.8, W = 5.0
10.72
53,000
6329
Circle
d = 3.694
10.72
47,928
3686
H-shape barrette
B = 1.0, W = 2.5
5.5
38,000
3299
Circle
d = 2.646
5.5
34,000
2836
H-shape barrette
B = 1.0, W = 3.0
7.0
44,000
4002
Circle
d = 2.985
7.0
39,000
2951
H-shape barrette
B = 1.0, W = 3.5
8.5
47,000
4512
Circle
d = 3.289
8.5
40,000
3225
H-shape barrette
B = 1.0, W = 4.0
10.0
48,000
5370
Circle
d = 3.568
10.0
44,000
3354
H-shape barrette
B = 1.0, W = 4.5
11.5
53,000
5850
Circle
d = 3.826
11.5
45,085
3813
H-shape barrette
B = 1.0, W = 5.0
13.0
54,000
6533
Circle
d = 4.068
13.0
46,000
3954
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Table 4 Ultimate vertical and lateral capacities of circular and H-shaped barrette piles in sandy soil Single pile
Dimensions (m)
H-shape barrette
B = 0.8, W = 2.0
Circle H-shape barrette
Area (m2 )
Vertical capacity (kN)
Lateral capacity (kN)
3.52
37,000
2126
d = 2.117
3.52
27,500
2082
B = 0.8, W = 2.5
4.72
40,300
2657
Circle
d = 2.451
4.72
33,000
2328
H-shape barrette
B = 0.8, W = 3.0
5.92
47,000
3215
Circle
d = 2.745
5.92
36,500
2662
H-shape barrette
B = 0.8, W = 3.5
7.12
52,000
4116
Circle
d = 3.010
7.12
39,864
2797
H-shape barrette
B = 0.8, W = 4.0
8.32
57,000
4556
Circle
d = 3.254
8.32
41,500
3070
H-shape barrette
B = 0.8, W = 4.5
9.52
59,000
5150
Circle
d = 3.481
9.52
46,000
3199
H-shape barrette
B = 0.8, W = 5.0
10.72
62,000
5699
Circle
d = 3.694
10.72
47,000
3529
H-shape barrette
B = 1.0, W = 2.5
5.5
41,000
2714
Circle
d = 2.646
5.5
34,500
2568
H-shape barrette
B = 1.0, W = 3.0
7.0
48,000
3370
Circle
d = 2.985
7.0
40,000
2757
H-shape barrette
B = 1.0, W = 3.5
8.5
54,000
4242
Circle
d = 3.289
8.5
41,200
3106
H-shape barrette
B = 1.0, W = 4.0
10.0
58,000
4853
Circle
d = 3.568
10.0
44,811
3283
H-shape barrette
B = 1.0, W = 4.5
11.5
60,000
5252
Circle
d = 3.826
11.5
47,200
3644
H-shape barrette
B = 1.0, W = 5.0
13.0
64,000
5840
Circle
d = 4.068
13.0
51,000
3832
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375
Table 5 Ultimate vertical and lateral capacities of circular and H-shaped barrette piles in c-φ soil Single pile
Dimensions (m)
H-shape barrette
B = 0.8, W = 2.0
Circle
Area (m2 )
Vertical capacity (kN)
Lateral capacity (kN)
3.52
28,000
2931
d = 2.117
3.52
22,200
2567
H-shape barrette
B = 0.8, W = 2.5
4.72
36,000
3526
Circle
d = 2.451
4.72
26,000
2864
H-shape barrette
B = 0.8, W = 3.0
5.92
41,000
3948
Circle
d = 2.745
5.92
30,000
3209
H-shape barrette
B = 0.8, W = 3.5
7.12
47,000
5236
Circle
d = 3.010
7.12
32,200
3361
H-shape barrette
B = 0.8, W = 4.0
8.32
49,000
5740
Circle
d = 3.254
8.32
35,490
3625
H-shape barrette
B = 0.8, W = 4.5
9.52
51,000
6370
Circle
d = 3.481
9.52
38,000
3800
H-shape barrette
B = 0.8, W = 5.0
10.72
58,000
6929
Circle
d = 3.694
10.72
39,000
4141
H-shape barrette
B = 1.0, W = 2.5
5.5
33,500
3584
Circle
d = 2.646
5.5
28,000
3127
H-shape barrette
B = 1.0, W = 3.0
7.0
42,000
4371
Circle
d = 2.985
7.0
33,000
3332
H-shape barrette
B = 1.0, W = 3.5
8.5
48,000
5689
Circle
d = 3.289
8.5
34,000
3719
H-shape barrette
B = 1.0, W = 4.0
10.0
51,200
6092
Circle
d = 3.568
10.0
37,500
3831
H-shape barrette
B = 1.0, W = 4.5
11.5
56,000
6707
Circle
d = 3.826
11.5
40,000
4313
H-shape barrette
B = 1.0, W = 5.0
13.0
60,000
7168
Circle
d = 4.068
13.0
43,026
4752
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Table 6 Percentage increase in vertical and lateral capacities of H-shaped barrette pile as compared to circular pile in clayey, sandy and c-φ soils Single pile
Dimensions Type of soil (m) Clayey
H-shape B = 0.8, barrette W = 2.0
Sandy
c-φ
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
25.925
16.011
34.545
16.011
26.126
14.179
25
26.860
22.121
14.132
38.461
23.114
21.621
33.080
28.767
20.773
36.667
23.028
23.076
55.394
30.443
47.157
45.962
55.786
19.017
56.571
32.349
48.403
38.067
58.344
16.680
66.558
28.260
60.987
34.210
67.631
10.582
71.703
31.914
61.490
48.717
67.362
17.556
16.325
18.840
5.685
19.642
14.614
17.391
35.615
20
22.234
27.272
31.182
16.5
39.906
31.067
36.574
41.176
52.971
12.82
46.107
29.432
47.822
36.534
59.010
Circular d = 2.117 H-shape B = 0.8, barrette W = 2.5 Circular d = 2.451 H-shape B = 0.8, barrette W = 3.0 Circular d = 2.745 H-shape B = 0.8, barrette W = 3.5 Circular d = 3.010 H-shape B = 0.8, barrette W = 4.0 Circular d = 3.254 H-shape B = 0.8, barrette W = 4.5 Circular d = 3.481 H-shape B = 0.8, barrette W = 5.0 Circular d = 3.694 H-shape B = 1.0, barrette W = 2.5 Circular d = 2.646 H-shape B = 1.0, barrette W = 3.0 Circular d = 2.985 H-shape B = 1.0, barrette W = 3.5 Circular d = 3.289 H-shape B = 1.0, barrette W = 4.0 Circular d = 3.568 (continued)
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Table 6 (continued) Single pile
Dimensions Type of soil (m) Clayey
H-shape B = 1.0, barrette W = 4.5
Sandy
c-φ
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
Percentage increase in vertical capacity (%)
Percentage increase in lateral capacity (%)
11.764
53.422
27.118
44.127
40
55.506
9.09
65.225
25.490
52.400
39.450
50.841
Circular d = 3.826 H-shape B = 1.0, barrette W = 5.0 Circular d = 4.068
Fig. 4 Variation of percentage increase in vertical capacities of H-shaped barrette piles in clayey soil
Fig. 5 Variation of percentage increase in lateral capacities of H-shaped barrette piles in clayey soil
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Fig. 6 Variation of percentage increase in vertical capacities of H-shaped barrette piles in c-φ soil
Fig. 7 Variation of percentage increase in lateral capacities of H-shaped barrette piles in c-φ soil
However, in case of c-φ type of soil, there is an increasing trend in the percentage increase in both the vertical and lateral capacities of H-shaped barrette pile. This indicates that the H-shape barrettes of larger breadths (W ) are more effective for vertical as well as lateral loadings in case of c-phi soils as shown in Figs. 6 and 7, respectively.
4 Conclusions The following conclusions are drawn from the numerical analysis of H-shape barrettes that were subjected to vertical and lateral loadings: 1. The H-shaped barrette pile has higher ultimate vertical and lateral load capacities than the circular pile with the same cross-sectional area.
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2. The percentage increase in vertical capacity of H-shape barrettes shows a decreasing trend with increase in the breadth of barrettes, in clayey and sandy soils, whereas it shows increasing trend in case of c-φ soil. 3. The percentage increase in lateral capacity of H-shape barrettes shows an increasing trend with increase in the breadth of barrettes, in clayey, sandy and c-phi soils. 4. In case of clayey soil, percentage increase in vertical capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 9–25%. 5. In case of clayey soil, percentage increase in lateral capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 16–65%. 6. In case of sandy soil, percentage increase in vertical capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 20–34%. 7. In case of sandy soil, percentage increase in lateral capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 16–52%. 8. In case of c-φ soil, percentage increase in vertical capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 26–39%. 9. In case of c-φ soil, percentage increase in lateral capacity of H-shape barrette pile compared to circular pile with the same cross-sectional area is in the range of 14–50%.
References 1. Submaneewong C, Teparaksa W (2009) Performance of T-shape barrette pile against lateral force in Bangkok subsoils. J Southeast Asian Geotech Soc 2. Wakil AZEI, Nazir AK (2012) Behavior of laterally loaded small scale barrette in sand. Ain Shams Eng J 4:343–350. https://doi.org/10.1016/j.asej.2012.10.011 3. Chavda JT, Dodagoudar GR (2017) Evaluation of ultimate capacity of a single barrette using finite element analysis. Indian Geotech Conf 4. Poulos HG, Chow HSW, Small JC (2019) The use of equivalent circular piles to model the behavior of rectangular barrette foundations. Geotech Eng J SEAGS & AGSSEA, 50(3) 5. Qureshi S, Thakare SW, Dhatrak AI (2020) Performance of barrette foundations in sandy soil subjected to vertical loading. In: Proceedings of Indian geotechnical conference, Andhra University, Visakhapatnam 6. Kartigeyan S, Ramakrishna VVGST, Rajagopal K (2015) Numerical investigation of the effect of vertical load on the lateral response of piles. J Geotech Geoenvironmental Eng ASCE 7. Report on “Detailed geotechnical investigation for metro station on East-West corridor in Reach2 of Nagpur metro rail project”, ITD Cementation India Limited 8. IS: 2911-1985 (Part-IV)
A Study on Effect of Uncertainties in Standardizing Workflow in Construction Firm Using SPSS Asra Fatima, Syed Thihamuddin, and S. M. Abdul Mannan Hussain
Abstract This study examines the potential for the application of processes for managing the workflow within the construction firm. While construction management has been integrated into many larger construction firms the ability to manage the workflow intelligently has been and remains a very elusive goal. Initially, various activities which are used in building construction projects are identified through literature review and expert opinion from construction industry. The data collection was performed using questionnaire survey which involves Likert scale of (1–5): 1 means “Strongly Disagree,” (2). Disagree, (3). Neutral, (4). Agree, and (5). Strongly agree. Data analysis was done by RII (top ten factors were identified based on their RII value and rank). SPSS software was used for identification of key factors affecting the standardization of workflow. Finally, a model was developed using Regression Analysis and an R value of .945 was achieved which indicates a good level of prediction. Keywords Construction management · Standardization · Workflow · RII · SPSS · Factor analysis · Regression Analysis
1 Introduction Profits in building projects can be increased by good management techniques. However, very few businesses have implemented formal procedures to control these behaviors. Fong Patrick and Yip Jimmy[3]. The construction industry is one of the most important areas that contribute to India’s economic growth. To assure the growth of organization, it is necessary to undertake a good long-term, logical, and economical project or construction. The construction sector’s discipline, which was impacted A. Fatima (B) · S. Thihamuddin Department of Civil Engineering, LIET, Hyderabad, Telangana, India e-mail: [email protected] S. M. Abdul Mannan Hussain (B) Department of Civil Engineering, NMREC, Hyderabad, Telangana, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_32
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by the diversity and separation of many construction firms, needs to be improved urgently by incorporating or adopting standardization, and 70% of the responder have stated that the reason for delay is procession of the site to make an effect in the timely completion of the project. Venkat Raman [5]. Despite the fact that empirical evidence from previous studies justified the existence of the concerns, the issue is still difficult and is continuing to affect academia and business in general due to a lack of coordination. Concerned parties have enquired regarding the evolution of the organizations difficulties. The contractors who are tired of rectifying typos and looking for lost documents and files. Standardization continues to support achieving uniformity in management and operations, indirectly lowering conflict among major stakeholder groups. According to lean principles, it is proposed that building procedures are more uniform in order to boost efficiency and eliminate waste, Sarhan [1] because standardization aids in the control of workflow processes, and it also aids in the reduction of errors and makes it easier to identify and correct faults if they occur. Akbar [4]. Workflows’ construction managers can take a more “set it-and-forget-it” approach to their day with configurable, automated processes that reduce project management and administration, so they can focus on the critical aspects of running a firm on a daily, weekly, monthly, or yearly basis to keep things running smoothly. You are inviting chaos if these processes are not standardized. The formulation of guidelines specify how employees of a company are expected to carry out a particular activity or workflow.
1.1 Objectives of Work • To identify factors affecting standardization of workflow through literature review. • To recognize factors affecting standardization of workflow using RII. • To analyze factors affecting standardization of workflow using factor analysis in SPSS. • To validate a developed model for the same using Regression Analysis in SPSS.
1.2 Scope of Work • The study goals were determined to be accomplished using following process. • After thorough literature review factors were identified and those factors verified by industrial experts which help in framing of questionnaire. • RII is used to rank the factors. • Factor analysis was used in SPSS to identify the factors. • A model was developed using Regression Analysis.
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2 Literature Review Projects experience time delays, cost over-runs, and significant waste processing. Although lean construction has been used by the Saudi construction sector, still it is in its infancy. Sarhan [1] Gowthami Vidya [2] evaluated Total Quality Management (TQM) in the construction industries by employing both its methodology and the crucial profitable processes (CSFs). A literature review is done to list out the processes that affect quality performance among the Quality Management processes in order to create a questionnaire. Fong Patrick and Yip Jimmy [3] state at various project stages in the construction industry, it is uncommon to document excellent or bad procedures, and there are three key ways that affect how construction workers record their lessons learnt. First, evaluation and study were conducted before LLS was used in a corporation. Second, training top management and staff members to make sure that all the members in the firm is knowledgeable about how to use LLS. Thirdly, a knowledge master is chosen early on to assist with the LLS execution. Nizam Akbar [4] Developing more realistic working techniques, implementing the SMM, and tracking the cost of the task, give the contractor more profit and clarity by profiting from the associated costs and efficient working practices, setting administrative and tendering cost control objectives, To meet the complexity and need of the current and forthcoming projects, it is necessary to upgrade or create new SMM frameworks and SMM contents. Kometa [23] suggested using the relative importance index approach to measure the relative weighting of client organization characteristics that could affect project consultants’ performance. Chan and Kumarswamy [21] explained the findings of a survey by evaluating and measuring the relative significance for Hong Kong building ventures. There were five most common causes for delays: inadequate maintenance and monitoring of projects, unpredictable situations on the field, low decision-making rates affecting all project staff, improvements prompted by customers and required job variations. Jyoti Bala [11] goals are to learn more about SPSS’s function in today’s social science research. SPSS is really impressive. It is frequently employed for generalpurpose survey analysis. Jha [22] mentioned that factor analysis and multinomial logistic regression are two methods used successfully in studying identification of the crucial failure and success factors and the crucial coordination activities. Factor analysis methods are frequently utilized for integrating variables that share the same variants in multiple aspects, known as “factors,” and are mostly used for determining profit and loss factors. Factor analysis can be used to analyze data for construction management and a variety of educational areas. Factor analysis identifies a group of dimensions also known as latent that are not present in large quantities of data or factors. The initial set of variables or factors that can be utilized for regression, correlation, or discriminant analysis can be completely or partially replaced by the latent variables produced
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from the factor analysis. Common factor vectors, factor loadings, and factor rotation are a few of the terms frequently used in factor analysis. Kim and Mueller [22] conducted the statistical technique of exploratory factor analysis (EFA), KMO values and the results of the Bartlett sphericity test were used to determine the factors’ appropriateness. The acceptability of the data is determined by comparing the output with reference values (Fig. 1). Fig. 1 Design flow for research methodology
Literature Review
Data Collection
RII
Factor Analysis of Data using SPSS
No
KMO Value > 0.70
Regression Analysis using SPSS
Validate the Model through Field Study
CONCLUSION
Yes
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3 Methodology To study on management system of construction industry for determining how contractors are tracking field production, a literature review and expert advice are collected from different companies. At the same time, the processes going on in the construction field are listed out by interviewing managerial staff. Contractor was interviewed personally to respond to specific interview questions about the process of following workflow. Processes were explained by contractors, how these methods benefit the company and any ideas for change. At last, the contractor was inquired about following a standard process for workflow and how this would profit the process of information to identify more standard workflow processes also to give more support to specific questions about the process of tracking workflow. Personal interview with academic expertise who are expert in Construction Management has been interviewed for same reason. From the data gathered, it was determined (50) Processes involved. Respondents to review and indicate the likelihood of following these standard factors on the scale of 1–5. A questionnaire is designed using Google Form which is then distributed among different contractors and construction professionals for investigation, and 112 questionnaires were responded fully.
4 Data Analysis 4.1 Relative Importance Index The Relative Importance Index is used to evaluate the relative importance of the primary factors involved (RII). The Likert scale’s numbers represent the value of W interviewing the respondents to get their opinions on the 50 listed factors that are influencing the development of construction processes and asking them to rate each one by using Likert scale of 1–5, with 1 means “Strongly Disagree,” (2). Disagree, (3). Neutral, (4). Agree, and (5). Strongly agree. Strongly disagree indicates that the element has no impact on the process’s progress, whereas Strongly agree indicates that the issue has a significant impact and requires additional attention (Table 1). The ranking shown in the above table were the results of RII, hard to plan and unlevelled schedule is given First rank with an RII value of 0.867857 which show that it is essential to level a schedule before planning. Second rank was given to lack of productivity benchmarks and standards with RII of 0.866071 followed by no list of resources with RII of 0.864286; both the factors are essential for project success. Insufficient time allotted to the design team for the facility’s design and document preparation ranked fourth and demotivation of team members who lost colleagues due to project downsizing ranked fifth with RII of 0.841071 and 0.821429, respectively, shows that staff of the company should be taken good care for project success. Sixth rank was given to fragments’ supply chain with RII of 0.816 which explains the need of proper planning of procuring resources. No use of software
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Table 1 RII result showing top ten factors affecting imperative processes Factors effecting imperative processes
RII value
Hard to plan for and unleveled schedule
0.867857
Rank 1
Lack of productivity benchmarks and standards
0.866071
2
No list of resources
0.864286
3
Insufficient time allotted to the design team for the facility’s design and document preparation
0.841071
4
Demotivation of team members who lost colleagues due to project downsizing
0.821429
5
A fragmented supply chain (i.e., lack of collaboration)
0.816071
6
No use of software or information systems (IS) to support activities
0.816071
7
No willingness to share resources among project participants
0.814286
8
Not using simple technical procedure to guide practitioners
0.8125
No commitment from top managers
0.805357
9 10
or information systems (IS) to support activities was given seventh rank followed by no willingness to share resources among project participants ranked eighth with RII 0.816071 and 0.814286, respectively, shows the need of proper distribution of resources among different project activities and use of software’s to track resource utilization. Not using simple technical procedure to guide practitioners ranked ninth with RII of 0.8125 shows the need to follow simple rules to guide during training of an employee. No commitment from top managers at tenth rank with RII of 0.805357 explains the importance of active involvement of top manager in project.
4.2 Exploratory Factor Analysis Using SPSS, it is determined whether the data are appropriate for factor analysis by using Kaiser–Meyer–Oklin (KMO) and Bartlett’s tests. The results of the KMO value are 0.761, which is more than the recommended value of 0.70, which is adequate, and the result of sphericity in the Bartlett’s Test is (Sig.000) with is statistical significance, which indicates the data is correct for conducting factor analysis. For factor analysis, all 50 factors were analyzed by Principal Component Analysis (PCA) using Varimax Rotation Method of Kaiser normalization. The factors with factor loadings of less than 0.50 are eliminated. Every factor in the result had factor loading greater than 0.50. Therefore, nothing needed to be excluded. As a result, all 50 items were allowed, and PCA showed that there were ten grouped components with Eigen values greater than 1 for these 50 items, representing a total variance of 79.410%. Individually, the supplied elements’ sum variance must exceed 60% in order for the approach to be considered suitable (Table 2). As a result of the data extracted from the factor analysis by Principal Component Analysis (PCA) using Varimax Rotation Method of Kaiser normalization, ten
A Study on Effect of Uncertainties in Standardizing Workflow … Table 2 Kaiser–Meyer–Oklin (KMO) and Bartlett’s tests’ results from SPSS
Kaiser–Meyer–Oklin measure of sampling adequacy Bartlett’s test of sphericity
Approx. Chi-square
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0.761 6195.479
df
1225
Sig
0.000
latent components with their meaning were derived as 1—Finalize Document Process Formats, 2—Finalize Shop Drawings, 3—Identifying Stakeholders, 4—Final Variation Cost Report, 5—Updating with Municipal Authorities, 6—Storage and Mobilization Plan, 7—Plan Communication, 8—Scheduling Activity (WBS), 9—Develop Project Charter, 10—Final Inspections Approval. After identifying the components, a model was created assuming that the components 1–9 as independent variable and component 10 as a dependent variable (Table 3).
4.3 Regression Analysis Regression Analysis is used here to predict relationship between (1–9) components as independent variable and (10th) component as dependent variable. SPSS is used for testing that the model performance is stable and in alignment with project objectives. Nathans (2012) found out that there is no single way of interpreting the Regression Analysis results.
4.3.1
Determining How Well the Model Fits
According to the multiple correlation coefficient results in the below table, the R value of 0.945 indicates a good level of prediction. The coefficient of determination R2 value of 0.894, which is 89.4% of variance in the dependent variable that can be explained by the independent variables (Table 4).
4.3.2
Statistical Significance of the Model
An ANOVA table below shows how well the regression equation fits the data (i.e., predicts the dependent variable). The effectiveness of the regression model’s ability to predict final inspection approval is seen in this table. The “Sig.” column, less than 0.05 in the “Regression” row, denotes the statistical significance of the regression model. The column value in this case shows that the regression model successfully fits the data and overall predicts the Final Inspections Approval (Table 5).
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Table 3 Factors’ extraction results with derived components and there latent meaning S. No.
Derived components with latent meaning
1
Finalize document Low process discipline, no standard methods process formats Information is not available in the format
Factors affecting imperative processes
Not following submittals and review processes Lack of technology adoption No contractor selection system 2
Finalize shop drawings
It is not clear how much front-end design matters Not taking shop drawings seriously? Structure cannot be built from contract documents? Lack of project specifications Unavailability of method statements
3
Identifying stakeholders
High variability, no feedback loops Project management is not aware of the different roles of stakeholders Distrust among the various stakeholders Severe lack of skilled workers Inadequate governance by owners and transparency
4
Final variation cost report
Ambiguous contractual obligations that are not obvious and focus on the obligations of each project part included in the contract Inappropriate approach to data collection on adverse variances in construction projects Owner directed change orders Inadequate quality Improper materials’ selection and changes in types and specifications during construction
5
Updating with municipal authorities
Not following state and municipal regulatory requirement Not following federal regulatory requirement Untimely contractual documentation Lack of urgency in approach, enthusiasm, and motivation of parties involved due to achieving substantial updating Improper contractual documentation
6
Storage and mobilization plan
Fragmented supply chain (i.e., lack of collaboration) Hard to plan, balance, and standardize work Hindrance to off-site (pre-cast/pre-fab) construction Poor supply chain management and the need to move to alternative contracting approaches Improper maintenance of equipment (continued)
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Table 3 (continued) S. No.
Derived components with latent meaning
7
Plan communication
Factors affecting imperative processes
No commitment from top managers No document storage, disposal, or transfer procedures No use of software or information systems (IS) to support activities Improper financing between the owner and contractor No establishment and communication of a conflict resolution strategy
8
Scheduling activity (WBS)
Hard to plan for and unlevelled schedule Insufficient time allotted to the design team for the facility’s design and document preparation Lack of productivity benchmarks and standards No willingness to share resources among project participants No list of resources
9
Develop project charter
Not using simple technical procedure to guide practitioners Not recognizing the “voiceless” individuals for whom special efforts may be required? Not identifying representatives of those likely to be affected? Not identifying whose behavior has to change for the effort to succeed? No clear definition of responsibilities
10
Final inspections approval
Project manager or superintendent demobilized before final completion Demotivation of team members losing their co-workers due to project downsizing Unclear closing instructions in contracts and specifications Architect or owner representative’s procedural inexperience Multiple punch lists
Table 4 Model summary of regression analysis from SPSS Model summary Model
R
R Square
Adjusted R Square
Std. error of the estimate
1
0.945a
0.894
0.884
0.32316
a
Predictors: (Constant), Develop Project Charter, Scheduling Activity (WBS), Finalize Document Process Formats, Updating with Municipal Authorities, Final Variation Cost Report, Finalize Shop Drawings, Identifying Stakeholders, Plan Communication, Storage and Mobilization Plan
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Table 5 ANOVA result from SPSS ANOVAa Model 1
Sum of squares
df
Mean square
F
Sig
95.306
0.000b
Regression
89.575
9
9.953
Residual
10.652
102
0.104
Total
100.227
111
a
Dependent variable: Final Inspections’ Approval Predictors: (Constant), Develop Project Charter, Scheduling Activity (WBS), Finalize Document Process Formats, Updating with Municipal Authorities, Final Variation Cost Report, Finalize Shop Drawings, Identifying Stakeholders, Plan Communication, Storage and Mobilization Plan b
5 Results and Discussion • Through literature review and experts’ advice were considered for identifying 50-factor affecting the workflow processes. • The top ten factors affecting Imperative Processes as shown in Table 1 by the RII result derived from the analysis of questionnaire responses. • Ten key factors were identified using factor analysis in SPSS as shown in Table 3. • A model was developed using Regression Analysis in SPSS and an R value of 0.945 was achieved as shown in Table 4.
6 Conclusion The study aims in implementation of standardization of workflow in construction firm which could be achieved by considering these factors before the start of the project resulting in reducing cost and time overrun.
6.1 Future Scope ANN, MATLAB, fuzzy logic, and other techniques could be used for further investigation of this study. The construction professionals who were consulted to validate the model found that the proposed model was a suitable instrument for defining the position and responsibilities of each project participant. The proposed model should be used by construction professionals, according to experts, to reduce harmful variances and improve firm performance.
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References 1. Sarhan JG, Xia B, Fawzia S, Karim A (2017) Lean construction implementation in the Saudi Arabian construction industry. Constr Econ Build 17(1):46–69 2. Gowthami Vidya G, Rai R (2016) Methodology for assessing TQM practices and critical factors affecting quality performance in construction industry. Int J Eng Res Technol (IJERT) ISSN: 2278-0181 5(05) 3. Fong Patrick SW, Yip Jimmy CH (2006) An investigative study of the application of lessons learned systems in construction projects. J Educ Built Environ 4. Akbar N (2018) Standardization in construction environment: adopting standard method of measurements. Asian J Behav Stud (AjBeS) 5. Venkat Raman K (2019) Study on time and cost management in construction. Int J Civ Eng Technol (IJCIET) 6. Jasper Mbachu (2008) Conceptual framework for the assessment of subcontractors’ eligibility and performance in the construction industry. Constr Manage Econ 7. Radujkovi´c M, Vukomanovi´c M, Dunovi´c IB (2010) Application of key performance indicators in South-Eastern European construction. J Civ Eng Manag 16(4):521–530. https://doi.org/10. 3846/jcem.2010 8. Park M, Lee H-S, Kwon S (2010) Construction knowledge evaluation using expert index. J Civ Eng Manag 16(3):401–411. https://doi.org/10.3846/jcem.2010.46 9. Teixeira JMC, Minasowicz A, Zavadskas EK, Ustinovichius L, Migilinskas D, Armiñana EP, Nowak PO, Grabiec M (2006) Training needs in construction project management: a survey of 4 countries of the EU. J Civ Eng Manag 12(3):237–245 10. Yaser G, Ismail AR, Sasitharan N (2019) Investigating the effect of poor communication in terms of cost and time overruns in the construction industry. Int J Constr Supply Chain Manage 9(2):94–106 11. Bala J (2016) Int J Adv Res Comput Sci 6(Special Issue):250–254 12. Heravi et al (2015) Int J Project Manag 33:985–997 13. Aapaoja A, Haapasalo H (2014) The challenges of standardization of products and processes in construction. In: 988 Proceedings IGLC-22, June 2014. Oslo, Norway 14. Macías-Jiménez MA, Acosta-Fontalvo LC, Jiménez-Barros MA (2019) Document management practices in SMEs: an information management capability-based approach. Records Manage J 30(1):63–79. https://doi.org/10.1108/RMJ-10-2018-0042 15. Varma V (2008) Advances in the production of shop drawings and their impact on constructability © American Society for Engineering Education 16. Aapaoja A, Haapasalo H (2014) A framework for stakeholder identification and classification in construction projects. Open J Bus Manage 2:43–55. http://www.scirp.org/journal/ojbm). https://doi.org/10.4236/ojbm.2014.21007 17. Mhando YB, Mlinga RS, Alinaitwe HM (2018) Variation mitigation model to enhance construction performance of public building projects in Tanzania. Am J Civ Eng Archit 6(3):105– 118. http://pubs.sciepub.com/ajcea/6/3/3 ©Science and Education Publishing. https://doi.org/ 10.12691/ajcea-6-3-3 18. Loganathan S, Srinath P, Kumaraswamy M, Kalidindi S, Varghese K (2017) Identifying and addressing critical issues in the Indian construction industry: perspectives of large building construction clients. J Constr Develop Countries 22(Supp. 1):121–144. https://doi.org/10. 21315/jcdc2017.22.supp1.7 19. Venkatesh MP, Renuka SM, Malathi B, Umarani C (2012) Evaluation of critical factors influencing resource allocation in Indian construction projects. Applied mechanics and materials, vol 174–177, pp 2774–2777. www.scientific.net © (2012) Trans Tech Publications, Switzerland. https://doi.org/10.4028/www.scientific.net/AMM 20. Jha KN (2013) Department of Civil Engineering Indian Institute of Technology Delhi New Delhi India ISSN 1566-0443 ISBN 978-94-007-6255-8 ISBN 978-94-007-6256-5 (eBook). Springer Dordrecht Heidelberg New York London. https://doi.org/10.1007/978-94-007-6256-5
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21. Chan DWM, Kumarswamy M (2018) Variation mitigation model to enhance construction performance of public building projects in Tanzania. Am J Civ Eng Archit 6(3):105–118. http:/ /pubs.sciepub.com/ajcea/6/3/3 ©Science and Education Publishing. https://doi.org/10.12691/ ajcea-6-3-3 22. Kim and Mueller (2008) Advances in the production of shop drawings and their impact on constructability © American Society for Engineering Education 23. Kometa (2014) Excessive delays in closeouts can be removed with the adaptation of better practices. Open Access Theses. 199. https://docs.lib.purdue.edu/open_access_theses/199
Application of Artificial Intelligence, Machine Learning, and Deep Learning in Contaminated Site Remediation K. V. N. S. Raviteja
and Krishna R. Reddy
Abstract Soil and groundwater contamination is caused by improper waste disposal practices and the accidental spills, posing threat to public health and the environment. It is imperative to assess and remediate these contaminated sites to protect public health and the environment as well as to assure sustainable development. Site remediation is inherently complex due to the many variables involved, such as contamination chemistry, fate and transport, geology, and hydrogeology. The selection of remediation method also depends on the contaminant type and distribution and subsurface soil and groundwater conditions. Depending on the type of remediation method, many system and operating variables can affect the remedial efficiency. The design and implementation of site remediation can be expensive, time-consuming and may require much human effort. Emerging technologies such as Artificial Intelligence, Machine Learning, and Deep Learning have potential to make the site remediation cost-effective with reduced human effort. This study provides a brief overview of these emerging technologies and presents case studies demonstrating how these technologies can help contaminated site remediation decisions. Keywords Site remediation · Artificial intelligence · Machine learning · Deep learning
K. V. N. S. Raviteja (B) · K. R. Reddy Department of Civil, Materials, and Environmental Engineering, University of Illinois Chicago, Chicago, IL 60607, USA e-mail: [email protected] K. R. Reddy e-mail: [email protected] K. V. N. S. Raviteja Department of Civil Engineering, SRM University, Amaravati, Andhra Pradesh 522240, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_33
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1 Introduction From the inception of environmental awareness during the mid-twentieth century, several regulations have been promulgated to mitigate the further impact on the environment from human activities. The population explosion, rapid urbanization, and increased living standards of people have all contributed to greater pollution. Until 1970, there was minimal awareness about the adverse effects of the wastes, which were disposed of carelessly without any environmental laws and regulations. The derivatives from chemicals and other toxic substances used on an industrial scale were disposed of without considering potential impacts on public health and the environment [1]. Though pollution control is becoming more mandated to prevent the creation of new contaminated sites, existing contaminated sites must be assessed and remediated. Recently, multiple technologies have been developed for site remediation, which include soil vapor extraction, soil washing, stabilization and solidification, electrokinetic remediation, bioremediation, phytoremediation, pump-and-treat, in situ flushing, and permeable reactive barrier [1]. Environmental site remediation is the process of removing, stabilizing, or degrading contaminants in the soil and groundwater, protecting human health and the environment. Site remediation is performed in multiple phases consisting of site characterization, risk assessment, risk management, and finally, selecting, designing, and implementation of a remediation technique. Remediation restores the contaminated site for redevelopment or to return it to its natural state [2]. Assessment of site contamination and selection of remediation method require significant input data, which is obtained by performing site investigations or estimated using existing site information. The advancement in computer-based technological analysis can simplify and improve the site assessment and remediation decisions. Emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have potential to be powerful tools for contaminant site assessment and strategy development for remediation. These technologies can provide a platform to support hierarchical integrated analysis of resources and environmental attributes and integrate the information into comparative theoretical ecosystem analysis. These technologies could overcome enormous challenges and improve the design of efficient site remediation systems. In this study, an overview of AI, ML, and DL is provided, and then, example applications of these technologies for site assessment and remediation are presented.
2 Emerging Technologies Figure 1 depicts the emergence of AI, ML, and DL technologies and the methodologies widely used for engineering systems. A brief description of these technologies is provided below.
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Fig. 1 Schematic representation of AI, ML, and DL technologies
2.1 Artificial Intelligence (AI) Artificial Intelligence (AI) is the simulation of human intelligence in machines and computers. It works on a foundation of specific hardware and software capable of writing and training Machine Learning algorithms. There are four general types of AI: (1) reactive machines, (2) limited memory, (3) theory of mind, and (4) selfawareness. The broad set of techniques that uses AI as a primary platform includes: Machine Learning, Neural Networks, Robotics, Expert Systems, Fuzzy Logic, and Natural Language Processing. Machine Learning technique is described in the next section, and the other techniques are briefly described below: • Neural Networks: It works similarly to nerves that transfer signals to the brain. A neural network implicates the brain that comprises neurons and replicates the brain–neuron to a system of network functions. Neural networks comprise a set of algorithms that determine the elemental relations between the various datasets. The data can be actual or artificial models known as perceptrons. The neural network works based on various statistical techniques to form networks. Neural
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networks have various applications in risk analysis, futuristic analysis, and data predictions. Robotics: A subset of AI mainly is focused on designing robots. AI is generally employed in robotics for assembly lines in automobile manufacturing, packing, and manufacturing industries, precise moving of heavy and oversized objects related to space technology. Expert Systems: These are one of the initial models of AI. Expert systems refer to a process depicting human expertise’s decision-making intelligence. This technology employs an extensive knowledge database and uses reasoning and insight regulations corresponding to the rising queries. Expert systems are very responsive, used for high executions and reliable. The models’ efficiency depends on the quality and quantity of the data in the knowledge base. Fuzzy Logic: This technique presents and transforms an uncertain condition by measuring the correctness degree of the hypothesis. Fuzzy logic can be used to implement ML techniques and logically depicts the human thought process. The standard logic can be determined in terms of degree of truth that ranges from 0.0 to 1.0, where 0.0 indicates complete false logic and 1.0 indicates complete true logic. Natural Language Processing (NLP): NLP is used for searching, analyzing, and deriving the data in text form. NLP libraries are used to train machines to interpret the text data logically. NLP has vast applications in consumer-based services, e-commerce websites, and email clients.
The above approaches can be used to formulate various models. Some of the widely used AI models are: Linear Regression, Logistic Regression, Deep Neural Networks, Linear Discriminant Analysis Naive, Bayes Learning, Vector Quantization, K-nearest Neighbors, and others. More details on these models can be found in Rusell and Norvig [3].
2.2 Machine Learning (ML) As a subset of Artificial Intelligence (AI), Machine Learning (ML) is the process used to build mathematical models that aim to make predictions and take decisions [4]. Generally, ML is based on training data (i.e., sample data), and it is highly affected by the completeness of this data. An inadequate or incomplete set of training data is likely to result in poor predictions [5]. Different ML algorithms are currently being used in the engineering field, such as extreme learning machines (ELMs), artificial neural networks (ANNs), and support vector machines (SVMs) [6]. Moreover, the following are different approaches to Machine Learning: • Supervised Learning: These mathematical models comprise input and output datasets. The training data can have multiple outputs. The training data contain multiple arrays known as future vectors represented in the form of a matrix. Supervised works on an objective function through iterations until convergence
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to the optimum point. The model can formulate a function that can accurately predict the output. • Unsupervised Learning: The data are latent with only input variables in unsupervised learning. The data get trained based on various operations like clustering and likelihood. The algorithm identifies the common features in the data to form clusters. Unlike supervised, in unsupervised learning, sorting happens after various iterations to identify the data with similarities prior to delivering the output. • Classification: Classifications are useful when the output has constrained boundary conditions. The objective is to classify the population into various sets based on similar quantifiable properties. The data analysis output is based on the classifications and population in each classified group. • Clustering: In clustering, the data are assigned to various subgroups known as clusters. The data variables in the same cluster are closely associated with similar properties. The dissimilarities form the distinctions between clusters. Clusters are formed by various techniques like similarity metrics and internal compactness. Although clustering is similar to classification, the primary assignment of data is different. In classification, the groups are pre-defined, and data are assigned to them. However, in clustering, groups are formed based on similarities in the data. Machine Learning approaches can be applied through various developed models. Some of the models that have wide applications in engineering are: Decision Tree (DT), Random Forest (RF), Multi-Layer Perceptron (MLP), Extreme Gradient Boosting (XGB), Support Vector Regression (SVR), etc. A detailed discussion of the ML models is provided by Ng [7].
2.3 Deep Learning (DL) Generally, DL is applicable to more complex and big data for which conventional ML models may result inaccurate assessments. Deep Learning typically employs neural networks with various layers in order to achieve a more precise estimation of output. DL models are very advanced and mimic human brain neural behavior for predicting outputs. DL has two types of algorithms, convolutional and recurrent neural networks. Most common DL model types include: • Discriminative: The discriminative models are applied for statistical classification in supervised algorithms. These models generate new instances using the joint probability density function of the data points. Discriminative models are more robust than generative models in terms of outliers. • Generative: As the name indicates, these models can generate new data instances. The generative models can assess the probabilities, model data points, and classify the data based on the differences in the probabilities. Generative models are mainly based on the Bayes theorem to deal with complex data analysis. Unlike discriminative models, generative models employ unsupervised learning to formulate the data phenomena.
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• Hybrid Learning: It combines Machine Learning and Deep Learning, resulting in a fusion network. In this model, Deep Learning models extract features from unstructured data and use Machine Learning approaches to form accurate classifications from the same unstructured data. The hybrid learning models are very accurate and yet computationally expensive. Most commonly used DL algorithms include: Convolution Neural Networks (CNNs), Long Short Term Memory Networks (LSTMs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Self-Organizing Maps (SOMs), Deep Belief Networks (DBNs), and Restricted Boltzmann Machines (RBMs). More details on these models are reported by Bagnio and Carville [8].
3 Applications of AI, ML, and DL to Site Remediation The application of AI, ML, and DL technologies in site remediation field is still in infancy. Very few professionals working in the site remediation field possess expertise on these emerging technologies. However, few research studies have reported on how these technologies could be potentially applied in site remediation projects. Selected example studies are presented in this section.
3.1 AI-Based Optimization of Pump–Treat–Inject Groundwater Remediation: Case Study Sadeghfam et al. [9] reported use of Optimum Control by Artificial Intelligence (OCAI) to regulate the pumping schedule to treat a critical aquifer in the East Azerbaijan region of Iran. The aquifer is an essential source of drinking water and irrigation for the region’s agriculture. However, the aquifer was contaminated by breaching of banks of wastewater lagoons during a significant storm event and the waste infiltrating into the soil, eventually reaching the aquifer. Groundwater samples from 29 monitoring wells showed high levels of total dissolved solids (TDSs). The pump– treat–inject (PTI) technology is proposed to treat the contaminated aquifer. OCAI determined the optimum pumping rate during the treatment process. The OCAI is implemented in three modules. In the first module, information about properties such as hydraulic head and contamination were collected using flow and transport models, respectively. The second module converted the outputs of the first model into two Sugeno Fuzzy Logic (SFL) models. The third module was user-defined unit that implemented OCAI as well as to run the genetic algorithm. Implementation of optimum pumping schedule through OCAI resulted in a substantial reduction in contaminant concentration to 3500 mg/L. The observations from nine different pumping wells over a remediation period of 27 years are shown in Fig. 2. The reduction in contaminant concentrations at each well can be noted.
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The concentrations were not reduced to the allowable maximum contaminant level (MCL) of 1500 mg/L. However, a substantial reduction in the concentration is desirable as the PTI remediation process is often limited in its effectiveness due to the rate-limiting desorption of contaminants [1]. Further, a significant reduction in operating costs for pumping and treatment was achieved. It is perceived that with the implementation of first two modules, the run time was nearly 60 days. In addition to OCAI in module 3, the time period was reduced to two weeks to process and less than 30 min for running. The output from OCAI included: identified optimum pumping schedule, minimized contaminant concentrations, and reduced costs. The results of this study reinforce the idea that AI provides an assortment of applications in the environmental remediation projects.
3.2 ML-Based Assessment of Electrokinetic Remediation of Contaminated Groundwater: Case Study American Geophysical Union (AGU) takes an initiative to solve the limitations of long run times with increasingly complex simulators and problem-solving techniques from Machine Learning surrogate models trained on the outputs of processbased simulations. The electrokinetic remediation process (EK), one of the remediation technologies, involves using Coulomb interactions between charges of cathode and anode along with geochemical and biological reactions. The two-dimensional process-based modeling of the cathode and anode interacting is considered with electrokinetic distributions reacting with the in situ biodegradation of the chlorinated compounds via simulation runs [10]. This remediation strategy aims lactate (C3 O5 H3 − ) to be electrokinetically delivered through electromigration and transport of charged species, from the cathode electrode to support this biodegradation of the chlorinated contaminants found in groundwater. The microbial activity of organohalide-respiring bacteria (OHRB) was simulated by lactate leading to degradation of tetrachloroethylene (PCE). The PCE is found in groundwater as both dissolved state and segregated non-aqueous phase liquid (NAPL). PCE degrades into trichloroethylene (TCE) and dichloroethylene (DCE). The addition of augmented OHRB (KB-1) supports absolute dehalogenation of the chlorinated solvents, which includes the conversion of DCE to vinyl chloride (VC) and finally into the targeted non-toxic ethene. This process could be accomplished with electroosmotic flow, transport of the non-charged chlorinated compounds, and KB-1 from the anode to the cathode. Figure 3 shows the detailed representation of the EK process. It should be noted here that KB-1 is the commercial name for natural non-pathogenic microbial culture that used to promote the complete dechlorination of chlorinated ethenes to non-toxic ethene. Sprocati and Rolle [10] simulated the electrokinetic remediation process using COMSOL (multiphysics flow and transport) model and Phreeqc (geochemical code) that calculates equilibrium and kinetic reactions. Different ranges of input parameters
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Fig. 2 Variation of hydraulic head and contaminant concentration at different well locations under optimum pumping schedule
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Fig. 3 Schematic representation of electrokinetic (EK) process
were assumed in simulations. Different explanatory variables were examined with Design of Experiment (DOE), divided into training, validation, and test sets used to obtain a simulation plan with multiple design sets. The number of process-based simulation runs were such that each design set displays a unique combination of the explanatory variables. Once the process-based simulations were executed with NP– Phreeqc–EK code, the approximation function was trained using training sets and cross-validated by testing model performances with test sets. The training procedure is involved using a stochastic gradient optimizer with a set momentum value of 0.9 with a learning rate of 0.46. This approximation function was used as a surrogate of the process-based model to explore similarities between inputs and outputs. Moreover, the approximation function was attained through a neural network that uses a stack of multilayer perceptrons (MLPs). An MLP is used with dense layers, representing all neurons within one layer connected to every neuron within a previous layer. In every dense layer, the outputs are calculated using Eq. 1. h W,b (X ) = Φ(X W + b),
(1)
where hW,b represents the output value; W is the weight matrix of all connection weights (not including bias neuron); b is the bias vector (weight of connecting bias
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Fig. 4 Process-based modeling with surrogate model framework
neurons and artificial neurons); and Φ is the activation function. A resulting calculation of the dense layer output value makes up the approximation function. MLPs are typically used for regression analysis within Machine Learning implementations. The surrogate models were developed for a better understanding of the analysis and performances of the EK remediation process and uncertainty quantifications. To expedite the process-based models, developers performed different approaches to engage ML surrogates in the reaction step. Figure 4 shows the simulation structure that used the process-based model with the surrogate modeling procedure. Results showed a good agreement with predictions of outcomes from processbased and surrogate models. It indicates that the Machine Learning capabilities combined with the surrogates made from the process-based model work efficiently. The most important finding is identifying the relationship between the process-based and surrogate models. Figure 5 presents eight different scatter plots comparing the outputs of the process-based model with the predicted surrogate model performance for training (TR), validation (VA), and test sets (TE). The red line indicates that the 1:1 ratio between the process-based and surrogate models provides a visual means of their correlations. The training (TR) data obtained R2 values close to 100% as this is only training the outputs and response surrogate. For the validation, R2 values above 90% indicate good agreement with training. The test set results have shown similar correlations, averaging above 96% coefficient of determination. Thus, the results show excellent prediction performances and optimization. It can be noted that the improvement of approximation functions further can achieve greater accuracy.
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Fig. 5 Comparison of process-based and surrogate-based models
3.3 DL-Based Simulation of Contaminant Migration: Case Study Li et al. [11] modeled a study region as a two-dimensional inhomogeneous medium with irregular borders. Steady groundwater flow with hypothetical conservative contaminant that would not undergo biological or chemical transformations was considered. Contamination transport was simulated for ten years, with twenty simulation periods. The unknown variables are identified through numerical simulations. The contaminant was released during the six-month simulation period. MODFLOW and MT3DMS toolboxes were used to perform numerical calculations to model groundwater flow and contaminant transport. The simulation model was fed with GCSs’ information, and the corresponding contaminant concentrations were determined. To determine the GCSI, the optimization model was employed which was linked with the generated simulation model. Thousands of repetitive computations were necessary to solve the optimization model. The computation load can be avoided by a surrogate model developed more accurately. In sequence, five hundred groups of input variables were identified for the simulation model. The developed surrogate models were trained by four different methods with the input variables (400 groups) and concentrations at well locations as output variables. Li et al. [11] used a DL method with a long short-term memory (LSTM) network, which has great potential for characterizing the input–output conversion relationship of complex nonlinear numerical simulations to a surrogate model. Researchers used LSTM network, Radial Basis Function (RBF), Kriging, and Kernel extreme learning machines’ method. Several models were developed, including numerical simulation, surrogate, and nonlinear optimization models. The four surrogate models were compared and examined. The most accurate surrogate model was chosen and linked to the optimization model. Figures 6a, b show the study area and the locations of
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point contaminant sources as well as pumping and observation wells, respectively. Figure 7 shows the concentration distribution of contaminants in groundwater at different elapsed times simulated by numerical models. The accuracy of developed surrogate models was tested by: the coefficient of determination (R2 ), relative error (RE), and the root mean square error (RMSE). The surrogate model (LSTM, Kriging, RBF, and KELM) with the highest accuracy was selected and linked to the optimization model. A nonlinear optimization model was developed to capture the precise location and past release sources of groundwater
Fig. 6 a Details of study area, b the distribution of hydraulic conductivity in the study area
Fig. 7 Contaminant concentration distribution in groundwater at different elapsed time phases: a 360 days, b 720 days, c 1800 days, and d 3600 days
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contamination. The objective function, constraints, and the decision variables were the parts of the model. As reported by Guo et al. [12], a generic algorithm (GA) is employed to optimize the model. The accuracy of the LSTM surrogate model was found to be the best. The optimization model can be linked to the LSTM surrogate model to reduce about 99% of the computational time required. Variations of the contaminant concentrations in the six observation wells (O1 -O6 ) shown in Fig. 6a at different periods are presented in Fig. 8. It is determined that R2 values for the four models vary from 92.89 to 98.35%, the RMSE ranges from 88.14 to 182.75, and the RE ranges from 7.63 to 18.62%. When the network layers or sequence length exceeds a specific limit, the gradient may disappear during the training. It could result in a decline in surrogate model accuracy. The results suggest that LSTM can create the surrogate model. The variations in the trends of the observation wells can be attributed to their locations (refer to Fig. 6a) from the contaminant source, pumping well, and the transport of the contaminant. The monotonic decrement in the concentration levels in O1 -O3 was due to their close vicinity to pumping well. Similarly, the initial increment in the wells O4 -O6 was due to their location away from the pumping well. Since the contamination released from the point sources in small slugs, the initial concentration levels were less in observations wells O4 O6 . Later, with direction of the flow, the contaminant concentration increased as the contaminant plume migrates and then reduced after certain time period after the plume further migrates. It can also be noted that the hydraulic conductivity (refer to Fig. 6b) was high in the location of observation wells O4 -O6 .
Fig. 8 Variation in the contaminant concentration in observation wells at various time periods
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4 Concluding Remarks The emerging Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have potential to address several site remediation challenges, such as contamination mapping and remedy optimization, leading to cost-effective and efficient remedial strategies. These emerging technologies can speed up the decisionmaking process in a way similar to human thought, just at a faster and more precise pace. They enhance the effectiveness of the remediation strategy design, either by reducing its cost or increasing its input parameters’ reliability. Based on this study, the following conclusions can be drawn: • AI has been used in many different ways in site remediation. Some of these uses are to assist decision-makers by recommending the desired remediation alternatives. AI can also be used to optimize the pumping schedule for groundwater remediation. These applications are just a few examples where AI can supplement site remediation. From the given case study, it is understood that AI techniques can: identify optimum pumping schedule, minimize contaminant concentrations, and reduce treatment costs. The results of this study reinforce the idea that AI provides an assortment of applications in the environmental remediation process. • ML applications are also emerging to work best with groundwater remediation studies. With the help of surrogate modeling, this technique supports active learning to improve further training data. ML significantly improves training accuracy in further data analysis. ML also promotes better computational timing for complex problems and algorithms to gain a more in-depth process understanding and allow quicker model explorations. ML shows promising interaction with AI strategies in hopes of complete use without human communications. • DL can produce specific models better than both AI and ML. The more advanced key factor in Deep Learning is the application of neural networks. They imply that the technology will work like a human brain and can solve more complex problems than ML. The functionality and structure of a human brain applied to a computer program will result in more sophisticated technology. It proved to be a great emulator for groundwater transport models, making predictions and speeding up the process. From the given case study, it is determined that R2 values of the four models vary from 92.89 to 98.35%, the RMSE ranges from 88.14 to 182.75, and the RE ranges from 7.63 to 18.62% indicating the efficiency of the model. The limitations of DL include complexity in using 3D models and handling multiple parametric models. It is optimistic that Deep Learning can be expanded and be an essential technology for site remediation. Many studies use the surrogate-based remediation data for the analysis. However, it is recommended to use real field data for the accurate analysis. Surrogate-based data should only be used in cases of non-availability of raw data. Acknowledgements The first author is grateful for the financial support provided by the Science and Engineering Research Board (SERB), Govt. of India, through the SERB International Research
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Experience Fellowship (SIRE) (Award # SIR/2022/000374), which allowed performing this research at the University of Illinois Chicago (UIC), USA.
References 1. Sharma HD, Reddy KR (2004) Geoenvironmental engineering: site remediation, waste containment, and emerging waste management technologies. Wiley, Hoboken, NJ 2. Hamilton J (2012) Careers in environmental remediation. Office Occup Stat Employ Projections, US Bureau, Washington, DC 3. Russell S, Norvig P (2022) Artificial intelligence: a modern approach, 4th US ed 4. Zhang XD (2020) A matrix algebra approach to artificial intelligence, chap 6, pp 223–440. https://doi.org/10.1007/978-981-15-2770-8 5. Melhem HG, Nagaraja S (1996) Machine learning and its application to civil engineering systems. Civ Eng Syst 13(4):259–279. https://doi.org/10.1080/02630259608970203 6. Majumder P, Lu C (2021) A novel two-step approach for optimal groundwater remediation by coupling extreme learning machine with evolutionary hunting strategy based metaheuristics. J Contam Hydrol 243:103864. https://doi.org/10.1016/j.jconhyd.2021.103864 7. Ng A (2018) Machine learning yearning, deeplearning.ai. 8. Bengio Y, Courville A (2016) Deep learning (adaptive computation and machine learning), MIT Press, Cambridge (USA). ISBN 978-0262035613 9. Sadeghfam S, Hassanzadeh Y, Khatibi R (2019) Groundwater remediation through pumptreat-inject technology using optimum control by artificial intelligence (OCAI). Water Resour Manage 33:1123–1145. https://doi.org/10.1007/s11269-018-2171-6 10. Sprocati R, Rolle M (2021) Integrating process-based reactive transport modeling and machine learning for electrokinetic remediation of contaminated groundwater. Water Resour Rese 57:e2021WR029959. https://doi.org/10.1029/2021WR029959 11. Li J, Lu W, Luo J (2021) Groundwater contamination sources identification based on the longshort term memory network. J Hydrol 601:126670, ISSN 0022-1694. https://doi.org/10.1016/ j.jhydrol.2021.126670 12. Guo JY, Lu WX, Yang QC, Miao TS (2019) The application of 0–1 mixed integer nonlinear programming optimization model based on a surrogate model to identify the groundwater pollution source. J Contam Hydrol 220:18–25. https://doi.org/10.1016/j.jconhyd.2018.11.005
Effect of Jute Fiber on Engineering Properties of Soil Parvesh Kumar and Fayaz Ahmad Mir
Abstract Stabilization of soil by the addition of natural and synthetic fiber is considered as quite common exercise nowadays. The process of strengthening of plain soil helps in enhancing the various engineering properties of soil such as unconfined compressive strength of soil, shear parameters of soil, bearing capacity of soil. An attempt is made to increase engineering properties of soil sample with the addition of Jute fiber as an additive in this study. Jute fiber is added in soil sample in different percentages such as 0.25%, 0.50%, 0.75%, and 1%. Earlier, the unconfined compressive strength of unreinforced soil is 0.87 kg/cm2 . After adding Jute fiber from 0 to 1%, the unconfined compressive strength changes from 0.87 kg/cm2 to 1.16 kg/cm2 . The sub-grade properties of the soil sample with addition of Jute fiber change significantly. The California bearing ratio value changes from 3.941% to 8.029% under unsoaking condition, whereas the California bearing ratio value changes from 2.4% to 5.3% under soaking conditions. Keywords Jute fiber · Stabilization · Fiber length · Reinforcement
1 Introduction The increasing rise of urbanization and industrialization has raised serious concerns about soil improvement in the construction industry. Soil improvement refers to the process of employing various methods to enhance the soil properties. Buildings, roads, irrigation systems, and other structures all employ soil as a building material. Soil improvement is necessary, especially in those conditions when the strength properties of the soil are not so good. According to the necessity, which differs from P. Kumar Department of Civil Engineering, Lingaya’s Vidyapeeth, Faridabad, Haryana, India P. Kumar (B) · F. A. Mir Department of Civil Engineering, National Institute of Technology Srinagar, Srinagar, Jammu and Kashmir, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_34
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site to site, soil needs to be upgraded. The main goal of strengthening a soil sample is to enhance bearing capacity, decrease settlement, and reduce deformation in order to increase stability. [1, 13] illustrated the outcomes of insertion of Jute on sub-grade characteristics. Bairagi et al. [2] executed an investigation to examine the influence of adding Jute on the engineering properties of black cotton soil, and the results show that on the inclusion of Jute fiber in the soil sample from 0 to 5%, the UCS value and sub-grade value of the specimen increase. Dasgupta [3] carried out an experimental investigation to enhance the characteristics of soil by the addition of Jute and concluded that there is crucial variation in the California bearing ratio value on adding Jute fiber. Gray and Ohashi [5], Gray and Al-Refeai [4], Yetimoglu and Salbas [22] concluded that length of fiber based is an important parameter to improve strength of soil. Hasan and Rayyaan [6], Sivakumar et al. [20] carried out a study to determine the effect of fiber geometry on the properties of soil and found that there is a significant effect of the geometry of fiber on the soil properties. Hossain et al. [7], Kumar and Mir [14] performed an investigation on Jute-reinforced soil that was accessible locally. Jute fiber content in soil is varied from 0.3% to 1.2% on the interval of 0.3% of the dry weight of the soil. Based on the test results, the California bearing ratio value improves as Jute fiber length increases. Additionally, it is also found that increasing Jute fiber diameter resulted in substantial increases in the California bearing ratio value. [11, 12] carried out a study on the enhancement in California bearing ratio values on adding Jute fibers. The amount of Jute fiber in the dry weight of the soil is determined in increments of 1%, ranging from a fraction of 1.0%–5.0%. Without taking fiber diameters into account, the lengths of fiber were assumed to be 20, 40, 60, 80, and 100 mm. Mali and Singh [15], Singh [17] examine the effect of fibers on the strength of cohesive soil and found that as the fiber content in soil increases, the strength parameters of the soil increases. An experimental investigation is done on locally accessible soil reinforced with Jute fiber by Singh and Bagra [18, 19]. The findings indicate that adding Jute fiber raises the California bearing ratio value. Muni et al. [16], Tang et al. [21] illustrated a study to examine the influence of arecanut fiber on the strength parameters of the soil. The findings indicate that the shear characteristics and stiffness modulus improve as the arecanut fiber content added. In the present study, the characteristics of plain soil are improved with help of Jute. In this study, the Jute fiber is added as 0.25%, 0.50%, 0.75%, and 1% by the weight of the soil sample. The percentages of the amount of Jute fiber added to the soil are decided based on the previous experimental work carried by different researchers in past. The Jute fiber is mixed in the soil according to the weight of the soil sample. The Jute fiber is cut into small pieces having length 30 mm and diameter 4 mm as shown in Fig. 1. Although Jute is an organic material and it will decompose in the soil, therefore in this study the Jute is chopped into pieces, and further, these pieces are coated with bitumen in order to keep them safe from microbial attack and degradation. The pieces of the Jute fiber are dipped into the hot bitumen for 3–4 s, and then, these pieces are left for cooling for about 24 h. After the process of coating the bitumen on the Jute fiber, these are used for further testing process. The Jute fiber is selected due to its high tensile strength and better durability. It can
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Fig. 1 Jute fiber used for the reinforcement of soil
easily resist heat and rolling; therefore, this material is selected in the present study for the stabilization of the soil. Also, Jute is easily available, cheap, biodegradable and eco-friendly material and has no adverse effect on the environment. Improving the engineering properties of the soil with Jute fiber is a very common technique. Enhancing the soil characteristics with the addition of Jute fiber is very economical.
2 Materials Used 2.1 Soil The soil is taken from Pampore site, near Jammu–Srinagar highway. The soil is dugged from the depth of 2 m. After collecting the soil sample, different tests are conducted on the soil to characterize it. The various characteristics of the unreinforced soil sample are displayed in Table 1.
2.2 Jute Fiber as a Reinforcement Material Natural, artificial, or a combination of both materials is used to create geotextiles. Geotextiles made from natural materials can be made from Jute, coir, sisal, wood chips or shavings, and paper. Jute can be divided into three different categories based on the different fabric properties and forms: woven Jute, nonwoven Jute, and open weave Jute, also known as soil saver. The ribbon of the stem is used to remove the fibers. The Jute fiber is purchased from the neighborhood market. The most common form of these fibers is threaded. Figure 1 shows the picture of the Jute used for the reinforcement of soil.
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Property Specific gravity Liquid limit
Value 2.643 35.8%
Plastic limit
25.87%
Optimum moisture content (OMC)
16.51%
Maximum dry density (MDD) (gm/cc)
1.785
Unconfined compressive strength (UCS) (kg/ cm2 )
0.87
California bearing ratio (CBR) (unsoaking conditions)
3.9%
California bearing ratio (CBR) (soaking conditions)
2.40%
3 Methodology Adopted Soil is collected from Pampore site for this study. The soil is taken at depth of 2 m. After the collecting the soil, it is being pulverized in the laboratory for the initial tests. After the process of pulverization, the sample is placed in the oven for 24 h at 110 degree. The unconfined compressive strength of soil and sub-grade characteristics of soil are determined after adding Jute. After that the Jute is mixed in the soil from 0.25% to 1%. A testing setup is developed in the laboratory to perform the experimental tests. A loading frame of 10N capacity is used to test the samples. The base of the loading frame is circular so that the cylindrical sample of soil during UCS test and the mold during California bearing ratio can be easily placed on the platen. Figure 2 shows the testing setup to perform the experimental investigations. Fig. 2 Testing setup to perform the experimental investigation
Effect of Jute Fiber on Engineering Properties of Soil 1.2
0% Jute .25% Jute .50% Jute .75% Jute 1% Jute
1 Compressive Stress (kg/cm2)
Fig. 3 Stress–strain graph obtained from unconfined compressive test at different fiber contents
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0
5
10 Strain (%)
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4 Result and Discussion 4.1 Effect on Compressive Strength of Soil Soil taken from the site is taken to the laboratory; after the oven drying process, the soil sample passing from 425 µm sieve is collected. Then, the water is poured into the soil sample and soil specimen is casted in the cylindrical split mold of diameter 38 mm and length 76 mm. The weight of the soil is taken according to the highest dry density of unreinforced soil, and then, the water is added to soil according to maximum moisture value of plain soil [9]. After the compaction, the sample is extracted with the help of sample extractor. Then, it is kept on unconfined compressive loading frame and compressive load is applied to it till the sample fails. The same procedure is followed in case of reinforced soil. To determine the effect of Jute in plain soil on the UCS of soil, the Jute content is mixed with the soil sample. Figure 3 represents the graph obtained between stress and strain from unconfined compressive test at different fiber contents. Figure 4 represents the modification in the UCS value of the plain soil sample on adding Jute to it.
4.2 Variation in California Bearing Ratio Characteristics of Soil Under Unsoaked Condition Various tests are performed both in soaking as well as in unsoaking conditions to examine the effect of Jute fiber. Initially, the sub-grade characteristics of the unreinforced soil are determined under unsoaked conditions [10]. The addition of reinforcing material, i.e., Jute fiber in percentage changes from 0.25% to 1%. The weight of soil sample is taken according to the highest dry density of plain soil at that
414 1.4 Unconfined Compressive Strength (kg/cm^2)
Fig. 4 Modification in UCS value with inclusion of fiber content
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0
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0.5 0.75 Jute Fiber Content (%)
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percentage of Jute which is determined by light compaction tests performed earlier [8]. After that, water is added in the soil specimen according to the OMC value of soil at that particular percentage. Similarly, sample is prepared in same manner for other percentages of Jute fiber. Figure 5 represents the California bearing ratio graph of soil at various proportions of Jute fiber. Figure 6 shows the graph having variation in California bearing ratio value with Jute fiber. From the obtained graphs, it can be summarized that on adding Jute in the soil sample, the sub-grade properties of the soil increase. The value of California bearing ratio for plain soil is recorded as 3.941% under unsoaking conditions which is further increased to 8.029% with the addition of the Jute fiber. It is also observed that maximum rise in the California bearing ratio value is experienced when 1% of Jute is inserted to the specimen of plain soil. From the results, it is concluded that California bearing ratio value increases up to 103% when 1% of Jute is mixed to the soil. 350
Load Dail Reading (kg)
Fig. 5 California bearing ratio graph of soil at different proportions of Jute fiber
300
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.75% Jute 1.0% Jute
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7.5 10 12.5 Penetration in (mm)
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CBR Value (%)
7 6 5 4 3 2 1 0
0
0.25
0.5
0.75
1
1.25
Fiber Content (%) Fig. 6 Graph showing variation in California bearing ratio value with Jute fiber
4.3 Variation in California Bearing Ratio Characteristics of Soil Under Soaking Condition
Load Dail Reading (kg)
After determining California bearing ratio value of specimen in unsoaking conditions, California bearing ratio value in soaking condition is also determined. Firstly, California bearing ratio value of unreinforced sample in soaking conditions is determined. Then, the quantity of Jute fiber is varied in terms of percentage in the soil sample. The quantity of Jute varies from 0.25% to 1%. California bearing ratio tests are performed for unreinforced and reinforced soils under soaked conditions. Figure 7 shows the California bearing ratio graph of soil at different proportions of Jute fiber under soaked conditions. From the obtained graphs, it can be summarized that by adding Jute fiber in the soil sample, the sub-grade characteristics of soil enhances. California bearing ratio value of unreinforced soil sample is 2.408% under soaking conditions which is further 350 325 300 275 250 225 200 175 150 125 100 75 50 25 0
0% Jute .25% Jute .50% Jute .75% Jute 1%Jute
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7.5 10 12.5 Penetration in (mm)
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Fig. 7 California bearing ratio graph at different proportions of Jute in soaking conditions
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Fig. 8 Variation in California bearing ratio value at different Jute fiber contents
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5 4 3 2 1 0
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Fiber Content (%)
enhanced to 5.328%. From the results, it is also noticed that maximum rise in the California bearing ratio is recorded at 1% Jute insertion. On insertion of 1% Jute Fiber in plain specimen of soil, the noticed reading of the California bearing ratio increases up to 121%. Figure 8 shows the change in California bearing ratio value at varying fiber contents. From the above graph obtained in Fig. 8, it can be summarized that as the Jute content is added in the soil sample, the value of California bearing ratio will also increase. From the study, it has been observed that the maximum rise in California bearing ratio value is obtained on adding 1% of the Jute fiber content in the soil sample.
5 Conclusion Soil stabilization is commonly used technique which is performed to enhance the basic characteristics of weak soil. The work is done to examine the effect on properties of soil with the addition of Jute fiber into it. A laboratory study is conducted to examine the effect of Jute fiber on the soil. From the performed work, the under mentioned conclusion can be made. • The value of MDD decreases to 1.63 gm/cc on varying the Jute content from 0.25% to 1%. Initially, its value was 1.78gm/cc, whereas the OMC value increases from 16.51% to 21.51% on adding Jute from 0.25% to 1%. • The UCS value of unreinforced soil increases from 0.87 kg/cm2 to 1.16 kg/cm2 on inclusion of Jute from 0.25% to 1%. The maximal value of UCS is noticed as 1.16 kg/cm2 . • The value of California bearing ratio of unreinforced soil rises to 8.029% on adding Jute under unsoaked conditions, earlier the value was 3.941%. The maximal California bearing ratio value is noticed as 8.029%. • The value of California bearing ratio rises from 2.45% to 5.318% when Jute is mixed in soil from 0.25% to 1% under soaking conditions. The maximal California bearing ratio value is noticed as 5.318%.
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• The soil stabilization using Jute Fiber can be useful in various application parts of civil engineering as it will increase the bearing capacity of soil and decreases the settlement. The soil stabilization using Jute Fiber can be used for safe and economical construction of super structures. Acknowledgements The authors would like to thank NIT, Srinagar. The authors appreciate the efforts of staff of Geotechnical Engineering Lab.
References 1. Aggarwal P, Sharma B (2010) Application of jute fiber in the improvement of subgrade characteristics. Int Conf Adv Civ Eng pp 51–53 2. Bairagi H, Yadav RK, Jain R (2014) Effect of jute fibres on engineering properties of lime treated black cotton soil. Int J Eng Res Technol 3(2):1550–1552 3. Dasgupta T (2014) Soil improvement by using jute geo-textile and sand. Int J Sci Eng Technol 3(7):880–884 4. Gray DH, Al-Refeai T (1986) Behaviour of fabric versus fibre-reinforccd sand. J Geotech Eng 112(8):804–820 5. Gray DH, Ohashi H (1983) Mechanics of fiber reinforcement in sands. J Geotech Eng 109(3):335–353 6. Hasan R, Rayyaan R (2014) Effect of fibre geometry on the tensile properties of thermoset jute fibre composites. Int J Sci Res Public 4(10):1–5 7. Hossain MA, Hossain MS, Hasan MK (2015) Application of jute fiber for the improvement of subgrade characteristics. Am J Civ Eng 3(2):26–30 8. IS: 2720 (Part 7) (1980) Determination of water content-dry density relation using light compaction 9. IS: 2720 (Part 10) (1991) Determination of unconfined compressive strength 10. IS: 2720 (Part 16) (1979) Determination of CBR of soil 11. Kumar D, Nigam S, Nangia A, Tiwari S (2015) Improvement in CBR values of soil reinforced with jute fiber. Int J Eng Tech Res 3(5):290–294 12. Kumar P, Mir FA (2017) Improvement in subgrade characteristics of soil reinforced with jute fiber. Int J Innov Res Sci Eng Technol 6(2):2220–2224 13. Kumar P, Mir FA (2019) Use of jute fiber in improving geotechnical properties of soil. In: Geotechnics for transportation infrastructure, pp 487–494 14. Kumar P, Mir FA (2018) Improvement in Geotechnical Properties of soil Reinforced with Jute Fibe ISGTI, IIT Delhi, pp 694–698 15. Mali S, Singh B (2014) Strength behavior of cohesive soils reinforced with fibers. Int J Civ Eng Res 5(4):353–360 16. Muni T, Jeram Y,Padu K, Yachang O, Singh HP (2014) Strength and stiffness response of itanagar soil reinforced with arecanut fiber. Int J Innov Res Sci Eng Technol 3(10):16659–16667 17. Singh HP (2011) Strength characteristics of soil reinforced with geosynthetic. Int J Earth Sci Eng 4(6):969–971 18. Singh HP, Bagra M (2013) Improvement in CBR value of soil reinforced with jute fiber. Int J Innov Res Sci Eng Technol 2(8):3447–3452 19. Singh HP, Bagra M (2013) Strength and stiffness response of Itanagar soil reinforced with jute fiber. Int J Innov Res Sci Eng Technol 2(9):4358–4367 20. Sivakumar Babu GL, Vasudevan AK (2008) Strength and stiffness response of coir -reinforced tropical soil. J Mater Civ Eng 571–578
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21. Tang CS, Shi B, Gao W, Chen FJ, Cai YS (2007) Strength and mechanical behavior of short polypropylene fiber reinforced and cement stabilized clayey soil. Geotext Geomembr 25 (3):194–202 22. Yetimoglu T, Salbas O (2003) A study on shear strength of sands reinforced with randomly distributed discrete fibers. Geotext Geomembr 21(2):103–110
Influence of Calcite Veins on the Failure Mode and Mechanical Behaviour of Basalt Dhirendra Kumar and P. S. K. Murthy
Abstract The calcite veins in the basalt rocks are formed due to the crystal growth of calcite mineral by filling of natural cracks and fissures and affect the mechanical behaviour of rocks under compression significantly. The mechanical behaviour and propagation of cracks in rocks are not only depended on the angle of veins to the direction of load, but also on the thickness of veins and its bonding with parent rock. In the present study, basaltic rock with various thicknesses of calcite veins from Deccan Plateau was investigated for uniaxial compressive strength (UCS) and shear strength parameters under triaxial compression. In addition, average mineralogical composition of this rock was determined using powdered X-Ray Diffraction analysis. Significant effects of calcite veins on the failure mode and variability in mechanical behaviour of basaltic rock were discussed. The presence of calcite veins has caused drastic reduction in the strength of basalts due to propagation of crack through veins and along its interface with parent rock. Due to presence of calcitic veins, a larger lateral deformation was observed in uniaxial compression. In triaxial compression, effect was reduced with the increase of confinement. Overall, the mechanical behaviour is largely influenced by the orientation and thickness of calcite veins in basaltic rocks. Keyword Calcite veins · Mechanical behaviour · Failure mode · Basalt · Orientation of veins
1 Introduction The knowledge about strength and the crack propagation in compression is crucial, in assessment of mechanical behaviour of rock. In general, the natural cracks filled with crystals of secondary minerals such as calcite, quartz, formed as veins in the parent rock, resist the stresses jointly. If these veins were ignored in the assessment D. Kumar (B) · P. S. K. Murthy CSMRS, New Delhi 110016, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_35
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Fig. 1 X-Ray diffractogram and possible phase identifications of Basalt with calcite veins
of mechanical properties of rock, results, in the over estimation of the strength due to non-accounting of weak nature of veins. Sometimes, these veins are treated as joints, which misinterpret the analysis of rock mass [1]. Hence, the behaviour of veined intact rock is important in the understanding of the influence of veins on rock mass [2]. Researchers [1–3] revealed that the significant difference in geo-mechanical properties of veined rocks majorly depends on the orientation of veins, vein thickness, and vein density. The direction, persistence, and interconnectivity of spreading crack strongly influence by the existing veins [4]. With different elastic properties of vein cement and parent rock, local stresses get affected with the weakness planes [5]. In the present study, basaltic rock with various thicknesses of calcite veins from Deccan Plateau of Western Ghats of peninsular India was investigated for uniaxial compressive strength (UCS) and shear strength parameters under triaxial compression. In addition, average mineralogical composition of this rock was determined using powdered X-Ray Diffraction analysis. The orientation and thickness of calcite veins in the selected basaltic rocks (Fig. 1) were also measured and discussed in the relevant sections to delineate the influence of calcite veins on mechanical behaviour.
2 Experimental Work To analyse the effect of calcite veins, on the failure mode, and mechanical behaviour of basaltic rocks, the laboratory experiments were conducted by characterising the veins in the basaltic rocks. A total of eight specimens each were prepared and tested in uniaxial compression and triaxial compression. All the investigations were carried
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out by ISRM [6] suggested methodology. The average mineralogical composition of veined basalt rock was also determined using powdered X-Ray Diffraction analysis.
2.1 Vein Characterisation The characterisation of calcitic veins in the selected basaltic rocks was done, to decipher the influence of calcitic veins on UCS and shear strength. The veins of all selected basaltic specimens were characterised, based on the thickness and orientation of distinctive and elementary veins. Some veins crossed the specimen completely or merge into other veins. Table 1 shows the orientation and thickness of calcite veins in the selected basalts. Table 1 Strength values corresponding to vein characteristic parameters Specimen No. Vein angle (°) Vein thickness (mm) Axial stress (MPa) Confining pressure (MPa) Uniaxial compression BV1
30
2
11
–
BV2
45
2
29
–
BV3
50
5
19
–
BV4
85
1
59
–
BV5
85
1
63
–
BV6
88
3
114
–
BV7
90
10
56
–
BV8
90, 70
5, 3
45
–
5
41
Triaxial compression BV9
2
BV10
58
3
68
6
BV11
60
1
117
7
BV12
75
2
72
5 10
BV13
75
1
149
BV14
76
4
58
3
BV15
78
2
84
4
BV16
80
5
110
8
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2.2 Specimen Preparation and Test Procedures The uniaxial compression and triaxial compression test specimens were prepared as per the suggested methods of ISRM [6] from NX size (54.7 mm in diameter) calcite vein basalt rock cores obtained from Deccan Plateau in Western Ghats of Peninsular India. For the uniaxial compressive strength evaluation, the specimens (height/diameter = 2.5) are axially loaded—until failure—between the platens in a compression machine. The longitudinal and lateral strains of the specimen are measured with the help of two vertical and two circumferential LVDTs connected to the Data Acquisition System to record any change in strain. The stress versus strain data were utilised for analysis of behaviour of veined basalts. For the triaxial compression strength test, the specimens (height/diameter = 2.0) were tested in high pressure triaxial cell, where the sealed specimens using flexible polyurethane membrane were placed and applied, desired confining pressure. The axial load is continuously recorded at a strain rate of 0.2 mm/m.
3 Experimental Results Results of investigation for behavioural assessment are discussed in the relevant sections. Figure 2 shows the typical tested specimen photographs of veined basaltic rock in uniaxial compression.
3.1 Vein Characteristic Parameters The orientation and thickness of veins measured in selected basaltic rocks are tabulated in Table 1. The orientation was varied from 30° to 90° for specimens to be tested for uniaxial compression, and for triaxial compression test specimens, it was
Fig. 2 Tested samples under uniaxial compression test
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varied from 0° to 80°. Overall, the veins’ thickness in the specimens was varied from 1 to 10 mm. The propagation of crack along veins and at interface of vein to the parent rock was observed. As highlighted earlier, the basaltic rocks with calcite veins have jointly taken stresses under compression. The crack initiation takes place in calcitic veins because they are weaker than the parent basaltic rock. When veins are oriented between 30° and 50° to the applied load, the natural shearing along the veins is more pronounced.
3.2 Mineralogical Composition X-Ray Diffraction results of powdered specimen with possible phase identification(s) pattern showed good similarities between the sample and mineralogy database to AMCSD/COD reference database, Fig. 1. The major identified minerals in the selected veined basalts are Calcite (37%), Labradorite (20%), Augite (19.5%), Stellerite (18.2%), Magnetite (2.5%), Periclase (2.2%), and Ilmenite (0.6%). In general, basaltic rocks comprise quartz, feldspars, and plagioclase minerals. When these basalts are veined with calcite minerals, the rock becomes weak along these veins due to low hardness (Mohs’ hardness of 3) of calcite, which largely affect the behaviour of the basaltic rock. Uniaxial compression strength (UCS). The typical stress–strain curves of the veined basaltic rocks in uniaxial compression are shown in Fig. 3. It was observed that the thicker veined specimens were failed at higher strains than thinner veined basalts. Stress–strain curves of specimen reflect plastic deformation after the much smaller elastic deformation due to the development of crack along the veins. The large deformation (Fig. 3) indicates sudden shearing of calcite vein, with slight decrease of stress. The parent basaltic rock minerals have contributed further increase of strength in compression. The experimental data values of UCS show lower strength values of 11 MPa in the thinner calcite-veined basalt with orientation angle of 30°, whereas for thicker veined basalt of 90° orientation resulted in UCS of 56 MPa. It was inferred that orientation has played less role than the thickness of vein in these rocks. Overall, UCS was reduced with the increase of thickness of calcite veins in basalts. Shear strength parameters in triaxial compression. Table 1 shows the triaxial test results of veined basalts in confining pressures ranging from 2 MPa to 10 MPa. When calcite veins oriented perpendicular to the direction of axial loading, was depicted lower axial stress at failure due to higher thickness of vein. With the increase of confinement, the thickness has negligible effect on strength. Through the best fit Mohr’s strength envelope, cohesion was 5 MPa and the angle of internal friction was 50°.
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Fig. 3 Typical stress versus strain, in uniaxial compression
4 Discussion on Veins Influence The veins in a rock may cause high variability in mechanical behaviour, which is controlled by thickness of vein and its orientation within specimens. Orientation and thickness of the vein were measured along with mineralogy of the specimens to investigate the behaviour of rock.
4.1 Influence of Vein Orientation The vein orientation was significantly affect the failure modes and mechanical behaviour, Fig. 4a, b. The peak strength affected by foliations when oriented between 35° to 81° as the failure mostly occurs along them which act as planes of weakness [7]. In UCS test, the specimens failed through the dominant vein orientation. However, when veins are not critically oriented to the applied load direction, the parent rock material comes into effect, and the failure occurs at higher stresses through the parent rock. The large lateral deformation on shearing of calcite vein is depicted in Fig. 3. In triaxial strength test, if the vein material is weaker than the parent rock and vein is in critical orientation, then the veined rock is prone to break along vein. When veins are not oriented between 35° and 81°, the primary crack was along the vein, and secondary common cracks developed shear failure mode. Overall, the vein orientation in veined basalt rock is certainly liable for fracturing along the vein. For behaviour analysis of calcite-veined basalt rock, not only the
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Fig. 4 (a), (b) Showing variability in mechanical behaviour in UCS and triaxial tests
vein orientation study, but the mineralogy and parent rock strength, may be useful. In general, critically orientated well-developed and persistent foliation cause a large decrease in strength and elastic property of rock.
4.2 Influence of Vein Thickness In uniaxial compression strength, the variability in test result attributed to an important type of heterogeneity such as veins of varying thickness and orientation, which demonstrates the disseminated alteration. The thin calcite vein of specimen shows linear elastic deformation under uniaxial compression, whereas the thick calcite vein tends to perform as a structure along the interface and resist the compressive load along with the parent rock material, resulting drastic change in the strength of the specimens with increased plasticity. The vein thickness exhibited inverse relationship with stiffness and peak strength properties in this test. The uniaxial compression strength test results of the specimens depict that the variation in thickness of veins influence the failure and mechanical behaviour, significantly. In triaxial strength test, the vein structural effect of the rock diminished by the applied confining pressure, which results higher strength of specimen. It also observed, at higher confining pressure, some cracks developed in directions, other than the veins. The result shows that crack propagates through or along the vein interface.
4.3 Influence of Minerology In veined specimens, failure mode depends on different combinations of vein formation and mineral strength. The failure along the vein interface will occur, if cohesive bond between the vein material and parent rock minerals is weak. When the vein infilling material itself is weaker than parent rock mineral, the failure will occur through vein.
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In this study, the failure behaviours of specimen observed through test results advocate that the rock weakens by the critically oriented veins. But, the failure mode is affected by the relative strengths of the parent rock and vein mineralogy, thickness, and orientation.
5 Conclusions In the present paper, the influence of calcite veins on basaltic rocks from the Deccan Plateau of Western Ghat area of Peninsular India was discussed. The orientation and thickness evaluation of calcite vein highlight the understanding the vein effect on the failure behaviour and mechanical properties of the rocks through laboratory experiments. Based on the analysis of experimental observations, it is inferred that: • The presence of calcite veins in the basaltic rocks has exhibited lower strengths that is 11 MPa for orientation angle of 30o and 56 MPa for 90° orientation in compression, due to failure along weak calcitic veins. It is inferred that calcite being soft mineral has propagated initial crack in these basaltic rocks. • It was observed that the thicker veined specimens were failed at higher strains than thinner veined basalts. With the increase of thickness of veins, the transformation from elasticity to plasticity, and shearing of specimen at higher load was observed. • Due to the presence of calcitic veins, a larger lateral deformation (>5000 micron) was observed in uniaxial compression. In triaxial compression, effect was reduced with the increase of confinement. With the increase of confinement, the effect of veins’ thickness in basalts is diminished, in turn increase the shear strength. • Overall, the mechanical behaviour is largely influenced by the orientation and thickness of calcite veins in basaltic rocks. Acknowledgements The authors are grateful to Director, CSMRS, for granting permission to publish the work. Thanks to Rock Mechanics Laboratory co-workers for their help in the laboratory study of this research. Further thanks to Dr. Sameer Vyas from the Chemistry Department of Central Soil and Materials Research Station, New Delhi, for technical support with XRD laboratory analysis.
References 1. Matthew DC, Jennifer JD (2021) Mineralogical and sample selection implications for geo mechanical properties of intact heterogeneous and veined rocks from the Legacy skarn deposit. Eng Geol 285:106067 2. Alexandr T, John H (2017) Quantifying the effects of vein mineralogy, thickness, and orientation on the strength of intact veined rock. Eng Geol 226:199–207 3. Lee HP, Olson JE, Holder J, Gale JFW, Myers RD (2015) The interaction of propagating opening mode fractures with pre-existing discontinuities in shale. J Geophys Res Sol Ea 120(1):169–181
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4. Virgo S, Abe S, Urai JL (2013) Extension fracture propagation in rocks with veins: insight into the crack-seal process using discrete element method modeling. J Geophys Res Sol Ea 118(10):5236–5251. https://doi.org/10.1002/2013JB010540 5. Gudmundsson A, Simmenes TH, Larsen B, Philipp SL (2010) Effects of internal structure and local stresses on fracture propagation, deflection, and arrest in fault zones. J Struct Geol 32(11):1643–1655 6. Ulusay R, Hudson JA (2007) The blue book: the complete ISRM suggested methods for rock characterization. Testing and Monitoring 7. Jaeger JC, Cook NG (1979) Fundamentals of rock mechanics, third edn. Wiley (1979)
Optimising Structures for Earthquake Impact in Seismic Prone Zone Daljeet Pal Singh and Divya Srivastava
Abstract The inelastic response of structural components and systems is typically used in seismically active locations to dissipate the energy that an earthquake imparts to a structure. Response spectra are frequently used to assess how seismic waves affect structures built with civil engineering. As the effect of seismic waves cannot be controlled completely, some strategies can be adopted to prevent the structural failure and collapse. The installation of seismic dampers in place of structural parts is suggested as a method for reducing seismic damage to buildings and enhancing their seismic performance. These dampers function similarly to the hydraulic shock absorbers found in automobiles and the suspension in motorbikes, where the hydraulic fluids can absorb the majority of unexpected and sudden jerks. To adopt environment-friendly approach for controlling the effects of seismic waves, special dampers are designed on the software E-Tabs v18.0.2 as per the parameters of Taylor Devices Inc. and these dampers are applied at optimum location in particular zone which resists the seismic energy and control the effects of seismic waves. As a result, the dampers lessen the energy that may be used to shake the building. As a result, the building deforms less and the likelihood of damage is decreased. This research aims at a high-rise residential building which is seismically designed as per IS 1893:2016 Part-1 for a particular seismic prone zone on E-Tabs v18.0.2 Ultimate as per latest and modified IS codal provisions. The storey displacement was found very high in the seismic prone zone without damper consideration. After designing of special dampers and placing them into the building, structure improved and reduced the extent of maximum storey displacement to a minimised value and made the structure comparatively safe. Keywords Passive control system · Seismic response · Maximum storey displacement · Special damper
D. P. Singh (B) · D. Srivastava Department of Civil Engineering, Amity University Uttar Pradesh, Lucknow Campus, Lucknow, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_36
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1 Introduction The goal of passive control systems, which heavily rely on isolation and energy dissipation components, is to dissipate some of the input energy. These systems have historically been thought of as intelligent systems since they generate more damping forces as the structural reaction becomes more significant. In general, passive systems used in smart structures can be regarded as systems with “limited intelligence” because they are unable to adapt to the excitation and global structural reaction and only have a limited capacity for control. They are calibrated to protect structures against a specific dynamic loading, and in other situations involving different forms of dynamic loading, their effectiveness will be less than ideal. The local structural reaction is the only factor that controls the energy dissipation mechanism, which is wholly dependent on the relative movement of the structure. However, passive control devices are relatively easy to design and build, have an inherent stability, do not require any external energy to operate, or structural response measurements. When there is an earthquake, dampers can be fitted in a building’s structural frame to absorb the energy entering the structure from the shaking ground (Fig. 1). As a result, the building deforms less and is less likely to sustain damage. Dampers work to absorb a significant quantity of seismic energy, which greatly minimises the building’s vertical movement back and forth (Fig. 2). It shall greatly help to promote a safety for the mankind and an eco-friendly approach indeed. Thus, we can significantly limit the seismic energy entering a building by installing such additional devices that have large damping capacities. Fig. 1 Damper installed in a floor of a residential building. Source Google
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Fig. 2 Depiction of a building with and without a damper. Source Google
2 Literature Survey The dynamic properties of the Smart Restorable Sliding Base Isolation System (SRSBIS) are initially evaluated in terms of the force–displacement behaviour, effective period of vibration, and comparable damping in the study work of M. Abdolrahim Jalali et al. After that, thorough nonlinear time-history analyses are used to assess how well SRSBIS-equipped structures that were built using a direct displacement-based technique responded to earthquakes. The earthquake reaction of the spherical tank with seismic isolation is examined in another study by Zhi-Rong Yang et al. that is based on response spectrum theory. A laminated rubber bearing’s characteristics and calculation model are introduced. The dynamic behaviour and earthquake reaction of the seismic isolation spherical tanks are examined in order to calculate the dynamic magnification factor. In a study by D. Demetriou et al., the investigation of a proportional integral derivative’s efficacy is also referred to as a PID. Additionally, a controlled Variable Damping Semi-Active Tuned Mass Damper, or VDSTMD, was used to stimulate the corresponding multi-storey building by reducing the response of vibration from a specific earthquake. The structural behaviour of steel frames fitted with an Added Damping and Stiffness Damper system is the subject of an inquiry by M. Khazaei that is conducted in three distinct stories. This system’s substantial advantages, such as its resilience to the effects of heat and the environment, dependable and stable behaviour, and appropriate behaviour, have drawn the attention of researchers all over the world. In compared to frames that merely have bracing, the results reveal that shear stress
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in certain of the floors of frames with Added Damping and Stiffness Dampers is reduced. It shall notice more uniform displacements as the number of floors rises, as well as proper energy distribution in the frames with Added Damping and Stiffness Damper systems. In the study done by Tatiana Belash, oscillograms of rubbing surfaces under shear were produced through experimentation, and following their processing, diagrams of shear for slabs with varying levels of roughness under varied vertical loads were constructed. The values of the dry friction factor in dry friction dampers were determined based on the inquiry that was conducted, and they ranged between 0.6 and 0.8 depending on the slabs’ level of roughness and the type of bulky material. The absence of a limiting closure force and the presence of a microplastic deformation area distinguish various Shear diagrams of tested energy sinks from traditional Coulomb diagrams (pure plastic mechanism of resistance). The arrangement of dry friction dampers, installed both in the building’s above-ground structures and directly in the structures of seismic isolating foundations, is demonstrated by calculation and theoretical analysis to be a dependable method for earthquake proofing the building. In a study by Osman Akyürek et al., the seismic response of a six-storey reinforced concrete (RC) building was examined using combinations of masonry infill walls, passive Tuned Mass Dampers, and active Tuned Mass Dampers (ATMD). In a study, a brand-new kind of frame structure-specific passive seismic damper called the Bar-Fuse Damper (BFD) is introduced. [1] The hot-rolled Square Hollow Sections (SHSs), C-channels, plates, and bars are some of the common steel sections from which the Bar-Fuse Damper is made. The cylindrical friction damper (CFD), a novel type of frictional damper that is suggested for the investigation, is demonstrated in the research by Masoud Mirtaheri et al. The inner shaft and the outer cylinder are the two parts that make up this damper. The shaft will move inside the cylinder by overcoming friction when the proper axial loads are applied to both ends of the cylindrical friction damper. As a result, there is a significant loss of mechanical energy. The cylindrical friction damper differs from the other friction dampers in that it does not create friction between the various contact surfaces using a range of high-strength bolts. In contrast to other forms of frictional dampers, this helps to lower expenditures such as building costs, streamline design calculations, and boost reliability. Both experimental and computational methods are used to investigate the hysteretic behaviour of CFD. The findings demonstrate that the suggested damper has a significant capacity for absorbing energy, considerably enhancing the performance of structures subjected to seismic loads. Additionally, there is a clear correlation between the experimental and numerical data. In the study conducted by A. Ras et al., a twelve-storey steel building moment frame with diagonal Fluid Viscous Dampers that have linear force versus velocity behaviour is the subject of a 3D numerical analysis into the seismic reaction. Using the SAP 2000 programme, the nonlinear time-history analysis, which is determined using rapid nonlinear analysis, is taken into account. Various comparisons between unbraced, braced, and damped structures are shown in a tabulated and graphical format.
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Using the measurement information from the installed monitoring system, Liyu Xie et al. s’ research involved a thorough identification to rebuild the numerical model method for this damped structure equipped with and without broken oil dampers. Additionally, a damage process for the oil dampers was produced based on the findings from identification and simulation. The oil dampers’ limit states underwent extensive examination. The investigation of sharing adjusted mass dampers for reducing seismic response is carried out theoretically and numerically in the paper by Z. Guenidia et al. Tuned Mass Damper’s (TMD’s) effects might spread from one structure to another. As a result, a reduction can be achieved in both buildings, which is a cost-effective method of controlling two nearby buildings with a single shared device. A hybrid shared TMD that combines an MR damper and a TMD can be used to implement the sharing. However, compared to findings achieved using a traditional shared TMD, those acquired utilising a hybrid shared TMD are more significant. Sharing a TMD between two nearby structures effectively mitigates the pounding risk, greatly reducing the seismic gap. The efficiency of the hybrid shared TMD is always reached with respect to the earthquake prominent frequencies over a wide range of neighbouring building frequencies. This study by Tharwat A. Sakr demonstrates a cutting-edge method for utilising numerous Tuned Mass Dampers as partial floor loads at a constrained number of floors. This tactic gets rid of a number of issues brought on by the addition of large masses needed for reaction control while maintaining the original structure’s mass without any additional stresses. On the vibration response of structures to wind and earthquakes, the varied impacts of utilising partial loads of limited floors beginning at the top as Tuned Mass Dampers are determined. It is also determined what happens when the proposed method is used on structures with various heights and features. A study is conducted to show how the number of stories and the area of the floor that is used as Tuned Mass Dampers affect a building’s behaviour. The outcomes show how well the suggested control method works to improve the drift, acceleration, and force responses of buildings to wind and earthquakes. By altering the storey–mass ratios and the number of floors used as Tuned Mass Dampers, the varied responses of the structures to wind and earthquakes were carefully monitored. A new passive earthquake damper for frame structures called the Bar-Fuse Damper (BFD) is introduced in this study by Reza Aghlaraa et al. Common steel components including hot-rolled Square Hollow Sections (SHS), C-channels, plates, and bars are used to create the BFD. It is affordable, simple to install, and does not require any unique fabrication techniques to produce. The main advantage of the BFD is the use of easily replaceable round steel bars as energy absorber components. The replacement bars serve as sacrificed components in the proposed device to release energy through a flexural and tensile mechanism. Hamid Radmard et al. Rahmani’s research examines the best location and characteristics for the Tuned Mass Dampers (TMDs), which are used in tall structures to reduce vibrations during earthquakes. After optimisation, it was discovered that the TMD locations were linked to the stories with the highest modal displacements in
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the lower modes and the stories with the highest modal displacements in the modes that the earthquake excitations most strongly affected. It was also discovered that the optimal location of the TMDs is significantly influenced by the frequency content of the earthquake. In this study [2], Romeo Tomeo et al. used nonlinear dynamic models to examine the effects of soil–structure interaction (SSI) effects on the seismic performances of 2D reinforced concrete (RC) moment resisting frames (MRFs). Through the use of a parametric research, the objective was achieved by varying (1) the soil parameters, (2) the modelling approach for the SSI impacts, and (3) the seismic design level of the structures. In their study, B. Ganjavi et al. devised an optimisation technique for seismic design of elastic soil–structure systems using the uniform distribution of damage over the height of structures as the criterion [3]. On the ideal distribution pattern, the impacts of the fundamental period, the number of storeys, earthquake excitation, the flexibility of the soil, the building aspect ratio, the damping ratio, and the damping model are examined [3]. A new lateral load pattern for elastic soil–structure systems is proposed on the basis of 30,240 optimum load patterns derived from numerical simulations and nonlinear statistical regression studies. It depends on the structural slenderness ratio, the soil’s flexibility, and the fundamental period of the structure. A study by M. V. Requena-Garcia-Cruz et al. focused on calculating the SSI impacts in seismic vulnerability studies of RC buildings using two methods: the Beam on Nonlinear Winker method (BNWM) and direct soil modelling [4]. The purpose is to suggest a technique for practically accounting for the SSI effects and completely describing soil behaviour. The approach has been used on a Lisbon case study RC mid-rise building [4]. By doing the studies in an undrained environment, it was possible to characterise a clay-type soil that is frequently found in Lisbon. To accurately depict the behaviour of the complete system (soil+foundation+structure), 3D finite element approaches have been presented to mimic the complex soil nonlinear constitutive law. The primary goal of the current effort is to lessen seismic reaction by improving building construction and installing dampers in seismically active areas. The idea behind reducing the seismic response by optimising building structure is to promote eco-friendly approaches as the optimisation does not have negative impact onto the environment. The volume editors, usually the programme chairs, will be your main points of contact for the preparation of the volume.
3 Methodology In present work, the latest E-TABS Ultimate software version 18.0.2 has been used for designing the high-rise residential building (G+15 Storey) as per the latest IS codal provisions of IS 1893:2016 Part-1 provided for seismic zone 4. Specific highrise building model parameters and loads as per IS 875 are mentioned which are
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discussed in Tables 1 and 2, respectively. Fluid Viscous Damper FVD 500 with complete design parameter are also provided in Tables 3 and 4, respectively. Table 1 High-rise residential building model parameters
Table 2 Loads’ definitions
Table 3 Seismic parameters for zone 4
Table 4 Special damper (FVD) design parameters
Parameters
Data
Plan dimension
12 m X 12 m
Type of building
Regular
Storey height (each)
3m
Storey
G+15
Type of building
Residential
Type of soil
Medium (II)
Grade of concrete (beam)
M20
Grade of concrete (column)
M25
Grade of concrete (slab)
M20
Slab thickness
150 mm
Grade of rebar
HYSD 500
Load type
Load value (kN/m)
Dead load (main wall)
15
Dead load (partition wall)
7.5
Dead load (slab)
1
Live load (slab)
3
Parameters
Value
Seismic code
IS 1893:2016 (Part-1)
Seismic zone
4
Zone factor
0.24
Importance factor
1.2
Soil type
Type II (medium soil)
Percentage of imposed load
25
Damping
5%
Damper parameters
Value/detail
Damper model name
FVD 500
Weight
98 kg
Force
500 kN
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To analyse efficiency of dampers in reducing earthquake impact, the designing is being done for two different cases. In first case, analysis is being done without damper and in other case provided with damper.
4 Results The E-TABS Ultimate software version 18.0.2 was used to assess the storey displacement in high-rise buildings in seismically active areas equipped with dampers to lessen the energy available to shake the structure and to lessen building deformation. The outcome is also contrasted with a storey displacement in a comparable circumstance without the use of dampers. It was found that there is a high maximum storey displacement occurring in the vertical direction. The 3D view of high-rise building model without dampers and then provided with dampers is depicted in Figs. 3 and 4, respectively. Tables 5 and 6 correspondingly display the findings for the same high-rise building with and without a damper. Figure 5 clearly depicts that there is a progressive increase of storey displacement from bottom to top with a very high extent, whereas the increase of storey displacement with damper seems to be at a lower extent on proceeding from bottom to top on providing dampers as shown in Fig. 6. Comparative study showcased a great reduction in the maximum storey (Storey 15) displacement after the application of special dampers (Table 7). Graphical representation of comparative storey displacements with and without application of dampers has been evaluated in Fig. 7. Fig. 3 High-rise building model 3D view
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Fig. 4 Special damper (FVD 500)
Table 5 Maximum storey displacement without special damper
Storey
Elevation
Y-Direction
m
Mm
Storey 15
45
43.015
Storey 14
42
41.654
Storey 13
39
39.839
Storey 12
36
37.609
Storey 11
33
35.028
Storey 10
30
32.16
Storey 9
27
29.064
Storey 8
24
25.797
Storey 7
21
22.411
Storey 6
18
18.954
Storey 5
15
15.47
Storey 4
12
11.999
Storey 3
9
8.576
Storey 2
6
5.242
Storey 1
3
2.106
Base
0
0
Figures 8 and 9 are the model representation of effect of seismic loads to the G+15 high-rise residential building without providing dampers and with dampers, respectively, into which red areas denote high impact and the green areas with low seismic impact. On analysing both models, it was found that residential building installed with dampers indicate encouraging response.
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D. P. Singh and D. Srivastava
Storey
Elevation
Y-Direction
m
Mm
Storey 15
45
31.678
Storey 14
42
29.052
Storey 13
39
26.665
Storey 12
36
23.877
Storey 11
33
21.403
Storey 10
30
18.509
Storey 9
27
16.067
Storey 8
24
13.222
Storey 7
21
10.947
Storey 6
18
8.333
Storey 5
15
6.37
Storey 4
12
4.195
Storey 3
9
2.687
Storey 2
6
1.214
Storey 1
3
0.282
Base
0
0
5 Conclusions The conclusion drawn after the overall design and analysis of special dampers for high-rise building in seismic prone area is: i. The maximum storey displacement was found in top storey in the seismic prone zone with zone factor of 0.24 as per the codal provisions of IS 1893:2016 Part-1 in both the cases. ii. The value of the maximum displacement in the building stories was high after the analysis of the G + 15 building with all the necessary seismic parameters applied as per codal provisions of IS 1893:2016 (Part-1). This is meant that without installing dampers the building was displacing very much in vertical direction due to the earthquake energy and would also lead to a progressive collapse of the building. iii. After applying the Fluid Viscous Damper (FVD 500) designed as per the criteria for Taylor Devices’ dampers at the corners and at alternate middle storey of the building, it was found that there was a reduction of the maximum storey displacement in the building storeys and it will be a safe point for the structure during seismic strike. iv. Fluid Viscous Dampers help to absorb a high amount of seismic energy which in turn bring down the to and fro movement of the building in vertical direction to a great extent and made the structure comparatively safe.
Optimising Structures for Earthquake Impact in Seismic Prone Zone
Fig. 5 Graph of maximum storey displacement without special damper
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Fig. 6 Graph of maximum storey displacement with special damper Table 7 Findings from the analysis Zone
Model parameters
Maximum storey displacement (mm.)
4
High-rise G+15 building (without special damper) Storey 15
43.015
4
High-rise G+15 building (with special damper) Storey 15
31.678
Optimising Structures for Earthquake Impact in Seismic Prone Zone Fig. 7 Seismic zone 4 model without special damper
Fig. 8 Seismic zone 4 model with special damper
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Maximum Storey Displacement in Seismic Prone Area in India 50 45 40 35 30 25 20 15 10 5 0
Without Special Damper
With Special Damper
Fig. 9 Graphical representation of maximum storey displacement in high-rise building in seismic prone area
References 1. Aghlaraa R, Tahir MM (2018) A passive metallic damper with replaceable steel bar components for earthquake protection of structures. Engineering Structures, Elsevier 159(1):185–197 2. Tomeo R, Bilotta A, Pitilakis D, Nigro E. Soil-structure interaction effects on the seismic performances of reinforced concrete moment resisting frames. Procedia Engineering 3. Ganjavi B, Hao H (2012) An optimization technique for uniform damage distribution in inelastic shear buildings considering soil-structure interaction effects 4. Requena-Garcia-Cruz MV, Bento R, Durand-Neyra P, Morales-Esteban A (2022) Analysis of the soil structure-interaction effects on the seismic vulnerability of mid-rise RC buildings in Lisbon. Elsevier (SciDirect), Structures 5. Ras A, Boumechra N (2016) Seismic energy dissipation study of linear fluid viscous dampers in steel structure design. Alexandria Eng J, Elsevier 55(3):2821–2832 6. Criteria for earthquake resistant design of structure general provisions and buildings. Bureau of Indian Standards, IS 1893-2016 Part-1, New Delhi 7. E-Tabs Ultimate Version 18.0.2 (2019) CSI America 8. Demetriou D, Nikitas N, Tsavdaridis KD (2015) Am J Eng Appl Sci 8(4):620–632 9. Rahmani HR, Konke C (2019) Seismic control of tall buildings using distributed multiple tuned mass dampers. Adv Civ Eng 10. Xie L, Cao M, Funaki N, Tang H, Xue S (2015) Performance study of an eight-storey steel building equipped with oil dampers damaged during the 2011 Great East Japan Earthquake. J Asian Archit Build Eng 13(1):181–188 11. Khazaei M (2013) Investigation on Dynamics Nonlinear Analysis of Steel Frames with Steel Dampers. Procedia Engineering, Elsevier 54(1):401–412
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12. Mirtaheri M, Zandi AP, Samadi SS, Samani HR (2011) Numerical and experimental study of hysteretic behavior of cylindrical friction dampers. Eng Struct 33(1):3647–3656 13. Kartha RV, Ritzy R (2015) Tuned liquid damper to control earthquake response in a multistoried building frame. Int J Eng Res Appl 5(8):49–56 14. Damodarasamy SR, Kavitha S (2018) Basics of structural dynamics and aseismic design. PHI Learning Private Limited, Delhi 15. Sakr TA (2015) Vibration control of buildings by using partial floor loads as multiple tuned mass dampers. HBRC Journal, Elsevier 13(2):133–144 16. Belash T (2015) Dry friction dampers in quake-proof structures of buildings. Procedia Engineering, Elsevier 117(1):402–408 17. Guenidia Z, Abdeddaima M, Ounisa A, Shrimalib MK, Datta TK (2017) Control of adjacent buildings using shared tuned mass damper, Procedia Engineering, Elsevier 199(1):1568–1573 18. Ganjavi B, Hao H (2012) Optimum lateral load pattern for elastic seismic design of shear buildings incorporating soil-structure interaction effects. Earthq Eng Struct Dyn
Correlation Between Field and Laboratory Deformability Moduli of Himalayan Sandstones P. S. K. Murthy and D. V. Sarwade
Abstract The deformability properties of rock mass plays vital role in the design of civil engineering structures which are built in and on rock. Estimation of the deformability modulus through field tests is very expensive and challenging task. In general, for a massive or closely jointed rock mass, elastic modulus of rock material on small scale laboratory tests provides a preliminary assessment and judgement about modulus of deformation of rock mass (E m ). In this study, an attempt was made to correlate modulus of deformation of rock mass with elastic modulus of intact rock at low stress levels (< 5 MPa). For this, field and laboratory investigations were carried out on massive sandstone located at Siwalik and Lesser Himalayan regions. For laboratory study, the sandstone samples were collected from the boreholes at the same location and identical depth and assessed elastic moduli at same stress levels, at which field tests on rock mass have been carried out. The study demonstrates the reliable estimation of E m from laboratory elastic modulus (E), for massive or less jointed rock mass, when assessed at low stress levels. Further, this paper also highlights the scale effect in the estimation of modulus of deformation. Keywords Rock mass · Deformability · Laboratory study · Sandstone · Correlation · Scale effect
1 Introduction Knowledge of the deformation modulus of rock mass is essential in any rock engineering project that involves analysis of deformations in the design of tunnel lining to dam or high-rise building foundations. Different, direct, and indirect methods have been proposed for estimating the deformation modulus of rock mass. These vary from in situ tests [1], to empirical methods, using various rock mass classifications. Since the natural rock mass comprise different types of discontinuities, it P. S. K. Murthy (B) · D. V. Sarwade CSMRS, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_37
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is very challenging to precisely measure the modulus of deformation of rock mass using in situ tests. The accuracy and reliability of in situ tests depend on the quality of execution of test and reliability of the theoretical assumptions, with the actual rock mass conditions. Plate load, dilatometer, and flat jack tests are often used for assessing deformation modulus of rock mass in various rock engineering projects. These in situ tests, however, are expensive and time-consuming and imply different operational difficulties [2]. Hence, these tests are accomplished when more precise and reliable estimation of modulus of deformation is required. Inconsistency with the assumption of theory of elasticity in comparison with real rock mass conditions is a crucial source of error in analysis of results of in situ tests. Several researchers have indirectly estimated rock mass modulus by different rock classification indices such as RMR, Q, RMi, GSI, and RQD [2–9]. However, studies revealed that these indirect methods need to utilize the intact rock properties and (or) discontinuities, obtained through laboratory studies. Hence, in the equivalent continuum approach in which deformability of rock mass is estimated by deformation properties of intact rock and discontinuities in rock [10, 11]. The studies [8] using RocLab software depicted that rock mass parameters vary non-linearly in the order of 2–10% of intact rock parameters. Studies on results of laboratory and in situ experiments conducted in Karun dam, Iran, showed possible correlations among them which can be utilized for design of structures in nearby regions [6]. To compare the deformation modulus of rock mass and intact rock, one needs to consider the stress level at which both laboratory and in situ investigations have been conducted. As per ISRM [1], there are three methods of assessment for Young’s moduli under laboratory compression tests, namely Average modulus, Secant modulus, and Tangent modulus. Out of, researchers [12, 13] noted that Secant Young’s modulus, which not only contain elastic strain but covers the pore compression of rock, can be treated as best indication of modulus of deformability of intact rock. In the present study, an attempt was made to correlate modulus of deformation of rock mass with elastic modulus of intact rock at low stress levels (< 5 MPa). For this study, field and laboratory investigations were carried out on two variants of massive sandstone rock, namely Kathua sandstone and Kasauli sandstone, of Siwalik and Lesser Himalayan regions [14], respectively. Both variants of sandstone are of dark to grey coloured, medium to coarse grained massive rock in nature. The in situ tests for deformability modulus were carried out using uniaxial jacking tests. For laboratory study, the sandstone samples of 54 mm diameter cores were collected from the boreholes at the same location and at the same identical depth and assessed for Secant Young’s moduli at same stress levels, at which field tests on rock mass have been carried out. The effect of scale on deformability of rock mass is also discussed.
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2 Methodology To meet the objective, field and laboratory investigations were carried on Kathua sandstone and Kasauli sandstone rock mass located in Siwalik and Lesser Himalayan regions. All the investigations were carried out as per ISRM suggested methods [1] and relevant International Standards. The detailed experimental methodology is explained in relevant sections.
2.1 Deformability Modulus of Rock Mass in Uniaxial Jacking Test Uniaxial jacking tests were conducted as per relevant standards to determine the modulus of deformation of rock mass. This test involves the loading of two opposite sides of an exploration adit or drift by hydraulic jacks, and loading plates, and measuring the induced deformations at surface. Total ten tests were conducted on Kathua sandstone, and eight tests conducted on Kasauli sandstone. Each test is investigated in five cycles of loading and unloading and measuring the deformation by dial gauges at regular intervals. Setup of the assembly and a graph showing the deformation versus applied stress is as shown in Fig. 1. Since the deformations recorded in the first cycle may not be true representative due to initial packing of surface undulations, modulus values obtained from the first cycle may not be used for design purpose. The fifth cycle is generally considered for calculating deformability modulus of rock mass at the estimated peak stresses. The modulus of deformation is the ratio of peak stress to strain corresponding to elastic and inelastic strains (W d ). Table 1 shows the calculated values of modulus of deformability (E m ) with range in two variants of sandstone.
2.2 Young’s Modulus of Intact Rock in Uniaxial Compression Test To modulus of elasticity or Young’s modulus of intact rock, specimens for both sandstone variants (each 10 specimens, 54 mm diameter) were prepared as per ISRM suggested methodology in length/diameter ratio of 2.5 and subjected to uniaxial compression test. The axial and lateral strains are measured using electrical resistance strain gauges, through data acquisition system. The vertical and circumferential strain gauges, two each are affixed at the middle height of the specimen. The rock specimens are axially loaded—until failure—between the platens in a Universal Testing Machine. Firstly, specimens were loaded to half of anticipated uniaxial stress and then unloaded and reloaded until specimen failure in compression. This is so because the specimens exhibit certain permanent or irrecoverable strains at the initial
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Fig. 1 a Test assembly and b typical deformation versus applied stress, in uniaxial jack test
Table 1 Deformability modulus of rock mass and intact rock Rock variant
E m (GPa)
E tan @ 50%UCS (GPa)
E sec @ in situ stress (GPa)
Max. Min. Avg. Max. Min. Avg. Max. Min. Avg. Kathua Sandstone @ 3.5 MPa 0.81
2.52
1.66
6.3
12.5
8.33
0.86
2.2
1.45
0.27
1.73
0.80
13
24
16
4.4
1.2
2.4
Kasauli Sandstone @ 5 MPa
loading. While loading and unloading, strains were recorded and traced stress–strain plots to decipher the tangent modulus value at 50% of ultimate stress (Fig. 2). The calculated values of tangent modulus are as given in Table 1. To meet the purpose of study, Secant Young’s modulus was calculated from the slope of the line from origin to the peak stress level at which in situ tests have been carried out. For Kathua sandstone at 3.5 MPa and for Kasauli sandstone at 5 MPa stress level, Secant Young’s modulus (E sec ) was calculated and tabulated in Table 1. Since, E sec comprises initial compression of pore, to, strains to any peak stress (contains elastic and inelastic strains), this is regarded as deformability modulus of intact rock. In the subsequent sections, comparison between deformability modulus of rock mass and intact rock shall be discussed.
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Fig. 2 Typical stress versus strain plot in uniaxial compression test
3 Data Analysis 3.1 Comparison Between Deformability Modulus Rock Mass and Intact Rock The results of deformability modulus from in-situ uniaxial jacking tests (E m ) on massive sandstone variants, compared with estimated Secant modulus or deformability modulus of intact sandstones. Due to closing of cracks, the moduli values at peak in situ stresses are only considered for the study. However, the calculated Secant modulus values (Table 1) were compared initially with the tangent modulus to decipher any relation among them. When all the laboratory test data on massive sandstone samples combined, it is interpreted that E sec at in situ peak stress is varying 0.2 times of E tan (when calculated at 50% of uniaxial compressive strength). Figures 3 and 4 show the correlation between the deformability values of rock mass (E m ) and intact rocks (E sec ) for the two variants of sandstone. In both variants of sandstone, it is observed that Secant modulus values have shown good linear
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correlation with in situ deformability modulus (E m ) with coefficient of correlation of 0.89. However, the linear function parameters for assessment of E m for both variants of sandstone are quite different. Due to massive nature of both sandstone variants without any joints, the data from both regions were combined and plotted as shown in Fig. 5. The combined plot also has shown good correlation with the data (R2 = 0.90).
Fig. 3 Deformability modulus versus tangent modulus of Kathua sandstone
Fig. 4 Deformability modulus versus tangent modulus of Kasauli sandstone
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451
Fig. 5 Deformability modulus versus tangent modulus (combined)
In general, the tangent modulus is largely used for assessment in the design of structures. With the relation between E tan and E sec , the linear function is modified for prediction of E m as E m = 0.24(E tan ) − 1.272.
(1)
Palmstrom and Singh [2] proposed an indirect estimate of E m through laboratory data on massive rock having few or no joints using modulus ratio (MR) and uniaxial compressive strength of rock (σc) as E m = 0.5(MR/1000) ∗ σc
(2)
where modulus ratio, MR = E tan /σ c ; also the equation is corrected for scale effect using Barton suggested expression [15]. Assuming the rock blocks of more than 2 m, Eq. (2) is further modified as E m ~ 0.5 E tan . Without application of scale effect on rock, the E sec data show a good agreement with the indirect estimates of E m proposed by Eq. (2). Being good representative of initial pore compaction, E sec values calculated at peak in situ stress levels is accurate for prediction of modulus of deformability of rock mass (< 5 MPa). Hence, Eq. (1) provides a best estimate of E m through E tan based on laboratory studies on massive rocks in nearby Himalayan regions.
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4 Conclusions In the present study, an attempt was made to correlate modulus of deformation of rock mass with elastic modulus of intact rock at low stress levels (< 5 MPa). For this, field and laboratory investigations were carried out on massive sandstone variants located at Siwalik and Lesser Himalayan regions. Based on results, • A linear correlation is proposed between deformability modulus of rock mass with Secant modulus of elasticity of intact rock. The correlation has shown similar trend and in good agreement with the correlation proposed by other researchers through laboratory tested data. • The Secant modulus is nearly varying 0.2 times of tangent modulus of rock. • The correlation proposed in the present study utilized Secant modulus values for prediction of deformability modulus of rock mass, which is the best representative in elastic region of rock where initial pore compaction takes place. Hence, Secant modulus can be regarded as ‘deformability modulus of intact rock’. • Though this study, a site-specific correlation based on in situ and laboratory studies on the same location and tested at the same identical depth could be possible. However, the developed correlation is confined to massive nature of rocks only and can utilized for similar rocks in nearby regions. • The study also highlights the need to develop site-specific correlations for estimating deformability modulus of jointed rocks giving due weightage for rock mass indices. Acknowledgements We are thankful to the Director, CSMRS, for sharing expertise and granting permission to publish the present research. We acknowledge the work of our co-workers in CSMRS’s Rock Mechanics division, during in situ and laboratory investigations. The co-operation of project authorities in making possible the in situ tests and arrangement of rock cores is highly appreciated.
References 1. Ulusay R, Hudson JA (2007) The blue book: the complete ISRM suggested methods for rock characterization. In: Testing and monitoring 2. Palmström A, Singh R (2001) The deformation modulus of rock masses—comparisons between in situ tests and indirect estimates. Tunn Undergr Space Technol 16(2):115–131 3. Barton N (2002) Some new Q value correlations to assist in site characterization and tunnel design. Int J Rock Mech Min Sci 39:185–216 4. Bieniawski ZT (1974) Geomechanics classification of rock masses and its application in tunnelling. In: Proceedings of the third congress of the International Society for Rock Mechanics, Denver, Part A, pp 27–32 5. Birid KC (2014) Comparative study of rock mass deformation modulus using different approaches. In: ISRM international symposium—8th Asian Rock mechanics symposium. OnePetro
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6. Ghamgosar M, Fahimifar A, Rasouli V (2010). Estimation of rock mass deformation modulus from laboratory experiments in Karun dam. In: ISRM international symposium—EUROCK 2010. OnePetro 7. Kayabasi A, Gokceoglu C (2018) Deformation modulus of rock masses: an assessment of the existing empirical equations. Geotech Geol Eng 36:2683–2699 8. Kishor P, Murali Krishna A (2014) Estimation of rock mass parameters using intact rock parameters. Int J Innov Res Sci Eng Technol 3(4):117–124 9. Polemis JK, Silva FFCD, Lima-F FP (2021) Estimating the rock mass deformation modulus: a comparative study of empirical methods based on 48 rock mass scenarios. REM Int Eng J 74:39–49 10. Naiem MMAA (2013) Correlation of sandstone rock properties obtained from field and laboratory tests. Int J Civ Struct Eng 4(1):1–11 11. Zhang L (2017) Evaluation of rock mass deformability using empirical methods—a review. Underground Sp 2(1):1–15 12. Malkowski P, Ostrowski L (2017) The methodology for the Young’s modulus derivation for rocks and its value. In: ISRM European rock mechanics symposium—EUROCK 2017. OnePetro 13. Małkowski P, Ostrowski Ł, Brodny J (2018) Analysis of Young’s modulus for Carboniferous sedimentary rocks and its relationship with uniaxial compressive strength using different methods of modulus determination. J Sustain Min 17(3):145–157 14. Srikantia SV, Bhargava ON (1998) Geology of Himachal Pradesh. Geol Soc Ind 15. Barton N (1990) Scale effect or sampling bias? In: Proceedings of international workshop on scale effects in rock masses, Balkema, Rotterdam, pp 31–55
Study on the Effect of Bottom Ash on the California Bearing Ratio of Clay Soil Mohammed Faisal Noaman , M. A. Khan, and Kausar Ali
Abstract The ability and efficiency of the road pavements are most strongly influenced by the type of subgrade soil, which is usually clay, which is unstable. Clay soil has a very low California Bearing Ratio (CBR); hence, because of this, the road pavements need a thick layer of pavement and a lot of subbase material. This increase in pavement thickness has a big effect on the amount and cost of paving materials. Because clay soil must be used as a subgrade in various cases, many researchers and geotechnical institutes have worked to improve its CBR rate. The aims of many previous research studies have centered on improving the CBR value of clay soil by reinforcing it with geogrids or geofibers, both of which are exceedingly expensive. The present research aimed to determine whether bottom ash admixture may improve clay soil drainage, as well as the optimum bottom ash amount to use and the influence of soaking duration on CBR values. Through blended ten different proportions of bottom ash (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%), as well as two standard samples for comparison. The optimum moisture content for plain clay soil and plain bottom samples was determined. The results exhibited that bottom ash enhances the CBR value of clay soil till 25% bottom ash, where the CBR value is 9.16% at 25% of bottom ash content compared to 5.71% for pure clayey soil. The CBR value decreased as the bottom ash content increased from 30 to 50%. While the results of the test effect of duration soaking showed a significant decrease in CBR value after 48 h of soaking, extending the soaking period to 96 h did not show a significant reduction. Keywords Ground enhancement · California bearing ratio · Pavement construction · Subbase · Bottom
M. F. Noaman (B) · M. A. Khan · K. Ali Department of Civil Engineering, Z. H. College of Engineering and Technology, Aligarh Muslim University, Aligarh 202002, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_38
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1 Introduction Soil is a critical element in civil geotechnical applications, and design engineers value it highly due to its big influence on the efficiency and performance of infrastructure project during the operating period [1]. The scale of urban expansion has doubled horizontally in recent years. As a result of the dwindling of the building areas covered by stable soil with good bearing capacity, it has become necessary to build infrastructure facilities on weak and unstable soils. This situation puts the geotechnical engineers in front of the challenges of developing the capacity of this weak soil and strengthening it to become suitable and safe to build on [2–4]. One of these challenges is the construction of a highway network to meet the needs of the expansion wave and to help in the economic renaissance, whereas road projects in the areas under development need a high bearing capacity, compared to the road network in urban areas. A large proportion of this expansion is based on unstable clay soils, which have weak CBR values. However, if subbase and base granular materials are placed on top of the subgrade clay soil, when exposed to cyclical vehicle loads, the clay will fail as a foundation for pavements [5, 6]. The previous researches focused on enhancing CBR rate of clayey soil were by natural or synthetic fibers such as coir, sisal, husk fiber, geogrid, nylon fiber, and polyester fiber [7–11]. The main problem with clayey soil as a subgrade under highway pavements is a change in volumetrics due to confined pore-water pressure between clayey particles. The phenomenon cyclic swelling and compressibility of clay soil subbase produce displacements in structural layers of pavement, reducing pavement strength. Attempting to solve this problem by using fiber reinforcement results in an increase in the cost of reinforcing solutions and a lack of economic efficiency. Where that, the focus only on stiffness does not alleviate the problem; rather, it adds economic burdens [12–15]. On the other hand, utilizing granular drainage debris such as sand, fly ash, dust, lime, or bottom ash is the method that provides the least amount of resistance to the release of surplus water pressure and increases the rate of permeability [16]. The amount of fly ash and bottom ash produced by thermoelectric power plants has been steadily rising all over the world. As a result, vast quantities of fly ash and its byproducts have covered hundreds of kilometers of valuable land. Bottom ash is a byproduct of the burning of fossil fuels to produce electricity. It has become a big issue for the ecology needing for more sustainable solutions. It has been shown that the application of free lime treatment improves the ability of a wide variety of soil types, in addition to soil-fly ash blends; this phenomenon has been the focus of a considerable amount of study [17–20]. The findings of the laboratory tests showed that the behavior of pozzolanic in lime, dust, and rice husk ash caused a greatly enhanced CBR rate. The fly ash’s consistency affects the CBR increase [17, 21–23]. The optimum moisture content (OMC) for admixtures of clay and bottom ash, particularly at high percentages of rice husk ash, cement, bituminous fly ash, or lime, increased as the CBR values did. Furthermore, the average dry unit weight of clay soil decreased because of the addition of fly ash and lime [19, 24–26]. The purpose of this study was to investigate the impact that bottom ash, when used as a chemical addition, has on the
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rate at which water is discharged from clay soil. Bottom ash is a granular, coarse residue of coal combustion that cannot be burned again. Bottom ash is used extensively as an addition material in road building all over the globe as a result of the geotechnical features it has. When used in road construction as a pavement material, bottom ash that has been combined with site soil results in a reduction in both the cost of aggregate and the cost of maintenance. Several studies have found that using bottom ash in road building is highly cost-effective, with a suggested composition of 30%. According to the findings of earlier experimental research, a combination of bottom ash, fly ash, and cement might potentially be utilized as a material for the paving of roads. This is according to the findings of several environmental studies [21]. The use of roughly 15% high-calcium fly ash with 7 days of curing is advised for maximum performing, according to the results of [27]. Dixit et al. [28] found that using varying percentages of fly ash as an addition to enhance soil stability might boost the CBR rate and make it more appropriate for making highway pavements. Prasad and Kumar [29] their findings confirmed that increasing the fly ash percentage from 0 to 25% reduced CBR values in both the unsoaked and soaked circumstances. The findings showed that adding up to 5% fly ash to gravel soil had no effect on CBR values. The granular soil behaved like sandy silt soil with increased fly ash, resulting in lower CBR values. The principal goal of this research is to determine the optimum amount of bottom ash that should be added to clay soil in order to increase its CBR value, as well as to investigate the impact that various soaking durations have on CBR values.
2 Materials The basic materials tested in the current study are clay soil and bottom ash. This soil is generally clayey and inorganic. CL clay has low plasticity and is often lean, sandy, or silty. In the current study, class F (low Ca) bottom ash was utilized, and its geotechnical properties are listed below.
2.1 Clay Soil The clay soil for the current study was gathered from the AMU fort valley in Aligarh, Uttar Pradesh, India, at coordinates (27.9290977, 78.0612811). Table 1 shows the engineering properties of clay soil (Fig. 1).
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Table 1 Engineering properties of clay soil S. No.
Properties
Value
1
Specific gravity
2.70
2
Optimum moisture content
18%
3
Maximum dry density
1.6 gm/cm3
4
Liquid limit
40%
5
Plastic limit
23%
6
Plastic index
17%
7
Cohesion
36 kPa
8
Angle of internal friction
11°
9
Soil classification
CL
Fig. 1 a Plain clay soil as obtained from natural; b Plain clay soil after grinding in lab
2.2 Bottom Ash In this study, the bottom ash (BA) is imported from the local thermal power plant in Aligarh (Kasimpur). It was gathered in a steel container and separated using a 425 µ sieve (Table 2 and Fig. 2). Table 2 Engineering properties of bottom ash
S. No.
Properties
1
Specific gravity
2.03
2
Optimum moisture content
35%
3
Maximum dry density
1.56 gm/cm3
4
Liquid limit
45%
Value
5
Plastic limit
N/A
6
Plastic index
N/A
7
Cohesion
4 kPa
8
Angle of internal friction
35°
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Fig. 2 a Pure bottom ash; b bottom ash and clay soil
3 Methodology This investigation work was all conducted in compliance with Indian standard procedures. After drying for 24 h at 105 °C in an electric oven, chunks of clayey soil were mashed and sieved using a 425 µ sieve. Following that, various amounts of bottom ash were added to it in order to do all the property tests. Geotechnical properties of raw materials (clay-bottom ash) are tested, including specific gravity, particle size, maximum dry density, optimum moisture content, and Atterberg limits. Due to that, most of the previous studies focused on a small mixing percentage, and to a range not exceeding 25%, samples of this study were prepared in increments of 5% and with a range of up to 50%. Where the test samples were made up of varying percentages of bottom ash and clay soil: 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50%. The bottom ash and clay soil are entirely mixed in the appropriate proportions with the correct moisture content on a dry weight basis. A compaction test was conducted according to Indian Standard Code (IS) 2720-part 8 [30]. The results of the whole test are shown in the next sections (Fig. 3).
Fig. 3 Equipment and tools that are used in this investigation work
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4 Results and Discussion The main objective of this experiment is to evaluate the effective duration of soaking CBR samples and impact of bottom ash mixed with clay soil on CBR behavior. The parts that follow offer an in-depth explanation.
4.1 Impact of Duration Soaking on CBR Rates of Clay Soil Figure 4 illustrates the impact of soaking duration on the rate of CBR for two samples of pure clay soil and two samples of pure bottom ash as described. This is in order to understand the influence of the soaking duration on the CBR rate and to adopt the critical duration and apply it to all test samples. When a sample of clay soil and a sample of bottom ash were soaked for 48 h., the findings exhibited a large reduction in CBR rate for both samples. Where the rates of CBR were after 48 h. 5.73 and 8.04% compared with dry samples of 8.63 and 10.79% for clay soil and bottom ash, respectively. When the soaking duration of the soils was prolonged to 96 h., the CBR value decline was found to be quite small. The results revealed that for plain clay soil samples, 91% of the CBR value declines within 48 h of soaking, whereas for plain bottom ash samples, 92.6% of the CBR value decreases after 48 h. As a result, all samples included in this study were immersed for 48 h, identical to those obtained by Nini [31]. Plain Soil
Plain Bottom Ash
Value of CBR
12.00 10.00 8.00 6.00 4.00 2.00 0.00
Unsoaking
48 Hrs
96 Hrs
Plain Soil
8.63
5.73
5.43
Plain Bottom Ash
10.79
8.04
7.82
Duration of Soaking (Hour) Fig. 4 Effect of different duration soaking on CBR values
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4.2 Impact of Various Content of Bottom Ash on CBR Rate of Clay Soil The penetration values vs load value curves for all of the samples are shown in Fig. 5. According to (IS) 2720-16 [32], CBR testing was performed on mixtures of clay soil with bottom ash to evaluate the influence of bottom ash on the efficiency of the cohesive mixture in resisting penetration, thus increasing the efficiency of the pavements, reducing the actual thickness, and reducing the economic cost of the projects. Where the mixtures of clay soil and bottom ash offer outstanding results in terms of resistance. Where the CBR value of untreated clay soil is 5.73 and 5.5% at 2.5 and 5 mm depths, compared to pure bottom ash, which has a CBR value of 8.04 and 7.93% at 2.5 and 5 mm penetrations. However, as seen in Fig. 6, the addition of 25% bottom ash leads to the highest improvement in CBR value, with CBR values at 2.5 and 5 mm being 9.16 and 8.97%, in that order. Bottom ash may therefore be used to construct geotechnical pavement for highways, airports, and other constrictions. The increase in CBR value may be for the reason that bottom ash is chemically similar to fly ash, which has cement-like properties because of its high lime content and good pozzolanic effect. The same interpretation was given by [33].
Applied Load (kN)
2.5 2 1.5 1 0.5 0
0
2
4
6
8
penetration Value (mm)
10
12
Plain Clay Soil BCS+5%BA BCS+10%BA BCS+15%BA BCS+20%BA BCS+25%BA BCS+30%BA BCS+35%BA BCS+40%BA BCS+45%BA BCS+50%BA Plain Fly Ash
Fig. 5 Load penetration response of the clay soil that mixed with different of bottom ash content
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CBRV (%)
9 8 7 6 5 4
0
5
10
15
20
25
30
35
40
45
50
Bottom Ash Percentages (%) Fig. 6 The CBR value for clay soil with several content of bottom ash
5 Conclusions The California Bearing Ratio (CBR) experiments were performed in the lab, and the following findings were arrived: • Optimum duration for soaking CBR sample observation of 48 h was observed through the test, where decrease rate of CBR by 67% of rate of CBR for plain clay soil sample without soaking, while decrease rate of CBR by 75% of rate of CBR for plain bottom ash sample without soaking. • When extending the soaking duration of soil samples from 48 h. to 96 h, observed little decreases are 63 and 73% compared with non-soaked samples for pure clay soil and pure bottom ash, respectively. • The CBR value of clay soil increases with added bottom ash up to 25%, and the curve reaches its maximum value; beyond that, it starts to degrade and approach lower values. The pozzolanic activity of the bottom ash may be the reason for the increase in CBR that is correlated with its amount. • When the CBR value increased, the thickness of the pavement would decrease, which would save materials and costs.
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23. Biswas T, Sarkar D (2021) Stabilization of subgrade soil using nano-chemicals and fly ash. In: Lecture notes in civil engineering. https://doi.org/10.1007/978-981-33-6564-3_6 24. Elufowoju FE (2019) Investigation of the impact of selected additives on index properties of subgrade soils. Niger J Technol 38(2). https://doi.org/10.4314/njt.v38i2.3 25. Katare VD, Patil S, Mahajan D, Madurwar MV (2018) Pozzolanic properties of binary and ternary cementitious blends. https://doi.org/10.1061/9780784482032.050 26. Properties of GFRC mortars with different pozzolanic additives. In: Fibre reinforced cement and concrete (2021). https://doi.org/10.1201/9781482271225-17 27. Rahman IU et al (2021) Characterization of engineering properties of weak subgrade soils with different pozzolanic & cementitious additives. Case Stud Constr Mater 15. https://doi.org/10. 1016/j.cscm.2021.e00676 28. Dixit A, Nigam M, Mishra R (2020) Effect of fly ash on geotechnical properties of soil. Int J Eng Technol Manage Res 3(5):7–14. https://doi.org/10.29121/ijetmr.v3.i5.2016.62 29. Prasad R, Kumar D (2015) CBR and strength aspects of fly ash-granular soil mixtures. Int J Eng Res Gen Sci 3(4):943–953 30. IS 2720 (1983) Methods of test for soils: part 8 determination of water content-dry density relation using heavy compaction. BIS 31. Nini R (2019) Effect of soaking period of clay on its California bearing ratio valuec. In: World congress on civil, structural, and environmental engineering. https://doi.org/10.11159/icgre1 9.162 32. IS 2720(Part I-XVI) (1987) Method of test for soils, part 16: laboratory determination of CBR 33. Somnath Shil SKP (2015) Permeability and volume change behaviour of soil stabilized with fly ash. Int J Eng Res Technol (IJERT) 4(2):840–846. Available: https://www.ijert.org/ 34. Cabrera M, Rosales J, Ayuso J, Estaire J, Agrela F (2018) Feasibility of using olive biomass bottom ash in the sub-bases of roads and rural paths. Constr Build Mater 181. https://doi.org/ 10.1016/j.conbuildmat.2018.06.035 35. Zimar Z, Robert D, Zhou A, Giustozzi F, Setunge S, Kodikara J (2022) Application of coal fly ash in pavement subgrade stabilisation: a review. J Environ Manage 312. https://doi.org/10. 1016/j.jenvman.2022.114926
Rainfall Impact Force Versus Rise in PWP: A Study of Darjeeling Himalayan Landslide Singh Ankit, P. K. Kundu, and K. S. Rao
Abstract The Himalayas contributes to more than 70% of deadly landslides globally, with the majority of destructive landslides occurring in India due to the region’s high rainfall, prolonged monsoon, strong seismicity, youthful geology, and rough terrain. Landslides in the Himalayan region interrupt local people’s way of life and cause significant financial and human losses during the monsoon season. The goal of the current study is to determine the design rainfall intensity and its impact on slope stability. A thorough hydrological analysis of the area has been conducted for this, along with field monitoring. The effects of raindrop impact force and excess pore pressure development as a result of the impact have also been investigated, taking into account the lengthy monsoon and frequent high-intensity storms in the study area. To continuously track rainfall and pore water pressure, tipping bucket rain gauges and vibrating wire piezometers were installed. Equipment to measure raindrop impact force has been designed and manufactured to continually record the rainfall impact force. The water level in standpipes was measured using a digital water level indicator to track changes in groundwater levels. This study’s main goal is to measure the impact force of raindrops and how that impact affects the formation of pore water pressure on the Himalayan region’s slopes. Tindharia, a landslide site in the Darjeeling Himalayas of Eastern India that was caused by rainfall, was chosen for this (26°51' 14.55'' N, 88°20' 13.12'' E). Keywords Rainfall impact force · Landslide · Slope stability · Darjeeling Himalayas
S. Ankit (B) · P. K. Kundu · K. S. Rao Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_39
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1 Introduction Rainfall is the primary cause of 80% of landslides globally. When rainfall hits the ground surface, it primarily divides into two components: surface run-off and infiltration. Slope failures are brought on by infiltrated water entering the zone of unsaturation of the slope, which raises the pore water pressure and reduces matric suction [4, 8, 13, 14, 16, 18]. Hill slopes rarely have groundwater tables, with the exception of a few localised perched water tables. Hence, the overburdened materials are unsaturated. In such materials, the pore pressure is lower than the ambient pressure (matric suction). Due to this matric suction, such unsaturated soils have a higher shear strength than saturated soils. The matric suction decreases as rainwater seeps into the soil and eventually disappears when the soil is completely saturated. Pore pressure is positive below the water table, and the soil is typically thought of as saturated. According to Cheng et al. [2], when it rains heavily, the soil above the wetting front creates a perched water table and generates hydrostatic pressure. Numerous more researchers, including [3, 7, 15, 19], also had the similar findings. Various researchers have already looked into this topic [5–7, 11, 12, 19] and used field instruments to look into a variety of landslide-related topics. The majority of this research focused on measuring pore water pressure, which is primarily caused by seepage and an increase in the groundwater table as a result of rainfall. These experiments provided conclusive evidence that the perched water table formed after rainfall and that the depth to which it fell at the ground surface relied on the quantity and duration of the rains as well as the soil’s hydraulic conductivity. In other instances, a rise in the groundwater table was also noted. In the Himalayas, particularly the study area has a lengthy monsoon season with daily rains in monsoon (June–August) and frequent rains with an intensity, many a times up to 80 mm/h. The current study aims to investigate the following aspects of rainfall that have not yet been examined: (i) The raindrop impact force’s effect on increasing the destabilising force causing landslides. (ii) The creation of pore water pressure (PWP) brought on by raindrops hitting a saturated slope, which has the effect of weakening the soil’s shear strength.
2 Instrumentation and Measurement of Data Field measurements of rainfall intensity, groundwater table variation, produced pore water pressure, and raindrop impact force are taken for the raindrop impact study. Figure 1a depicts the position of the instrumentation works. There are no trees or other obstructions in the area. At the location, a tipping bucket rain gauge has been put in to measure rainfall hourly. The gauge has a wireless transmitter that continually broadcasts temperature (°C) and rainfall (in mm) during rainfall, which a wireless receiver then receives and records (Fig. 1b).
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Fig. 1 a Site locations at Tindharia landslide area, Darjeeling, b rain gauge, c water level indicator and measurement, d raindrop impact measuring equipment, and e instrumentation site and vibrating wire piezometer with data logger
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Two perforated PVC sandpipes were erected by the Japan International Cooperation Agency (JICA) as part of research carried out at the Tindhria landsliding site in 2016 on support of the Ministry of Road Transport and Highways (MoRTH), Government of India. The standpipes had an automatic data logger and were set up in boreholes that were 50 m deep. JICA’s record was gathered in order to conduct additional measurements and analysis. A water level indicator was used to measure the water levels during the current study (Fig. 1c). Equipment was created to constantly record the raindrop impact force in gm at the necessary frequency for the measurement of raindrop impact force. The apparatus consists of an Arduino board coupled to a load cell through an HX711 module of load cell amplifier. A precision 24-bit analogue-to-digital converter (ADC) called the HX711 is intended to interfere with a bridge sensor directly in industrial control applications and weighing scales. Analogue power for the ADC and the sensor is provided by an on-chip power-supply regulator, which eliminates external supply regulator requirement. The on-chip oscillator serves as the clock input, so no external component is needed. All HX711 controls are accomplished through the pins, and serial SDK and SCK pins are used for communication. A memory stick stores data at the chosen frequency. The load cell was mounted with a 7 cm × 5 cm plate on it for the raindrops to land on. The plate with the load cell was kept outside, while the entire system was kept within a watertight plastic box. Figure 1d displays the circuit diagram and the completed apparatus. A portable RST VW piezometer, which is a vibrating wire piezometer (VWP) (Fig. 1e), is employed for long-term, remote measurement of borehole pressure and piezometric levels. A data logging system is attached to the instrument to enable automated data collection from vibrating wire transducers. A frequency signal which is produced by the vibration of the wire near the coil is transferred to the read-out device/data logger (Fig. 1e). The reading is kept in Hz via the read-out or data logger. After applying calibration factors to the reading, pressure in engineering units is obtained. The piezometer was positioned 40 cm below the ground’s surface, and the VWP measurements were constantly recorded at 5-s intervals (the top saturated zone within the perched water table). In the absence of rain, water was poured at regular intervals to keep the piezometer tip saturated, which must always be supplied with water. In order to replicate the site conditions (1(e)) of the bare slope, free of any vegetation or grasses, the piezometer was set up in an area without any grasses.
3 Results and Discussions The study area, which is a part of the Darjeeling Himalayas hill region, experiences heavy monsoonal rainfall on a yearly average of about 3500 mm. During the months of June to August, it rains very frequently, nearly every day, causing massive slides. The slides typically only extend to a shallow depth and are contained in top overburden materials made up of gravel and stones embedded in the matrix of sand. To
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Fig. 2 Instrumentation results of groundwater table and rain gauge: a present monitoring and b earlier 2016 monitoring by JICA
analyse the associated failure mechanisms, instrumentation in the field was used to assess rainfall intensity, groundwater table (GWT), pore water pressure (PWP), and raindrop impact force (RIF) as a result of raindrop impact in order to get better understanding of the failure process. The fluctuation of GWT with rainfall intensity for the current monitoring session and the measurements previously recorded by JICA are shown in Fig. 2. The prior data was acquired over 121 days (08/09/2016–06/01/2017), while the current data was recorded over 101 days (12/07/2018–20/10/2018). The present period saw daily rainfall variation from 2 to 73 mm/day, with total cumulative rainfall of months of July and August 2018 was 766 mm. In borehole BH-AB-1 and BHAB-2, respectively, the groundwater table remained nearly constant at 32 and 45 m depths during the present monitoring session, and the similar is concluded from the analysis of data that the rainfall had hardly any effect on the variation of groundwater table. Analysing previously collected data also produced similar results that were substantially identical, with the water table in BH-AB-1 and BH-AB-2 remaining nearly constant at 30 and 45 m, respectively, with a small change in the water table seen in BH-AB-2 after a 200 mm/day heavy shower. On the slope surface, the maximum impact force generated by rainfall (F i(max) ) in fully saturated condition, as well as its effect on pore water pressure variation as measured by VWP, and rainfall impact force measurement device are plotted against rainfall intensity for each rainfall event in Fig. 3. The experimental findings on the occurrence of PWP caused by raindrop impact with the saturated ground surface are not well documented in the literature. The PWP should be equal to the impact pressure of raindrops considering the soil to be saturated with the development of perched water table during the rainfall. Furthermore, according to Pascal’s law, across the depth of the wetting front, the pressure should be the same i.e. throughout the entire saturated zone. For the impact pressure arising from a collision between water and a solid, [10] provided the following equation:
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Fig. 3 Monitoring results of raindrop impact force and VWP (from 07-08-18 to 25-08-18)
P = 4 × 10−6 V , 2
(1)
where P represents the pressure in kg/cm2 and V is the raindrop’s terminal velocity in cm/sec. The terminal velocity of a 4 mm diameter raindrop in experimental research by [17] was 9 m/s. Similarly, the pressure values of 256 and 324 kPa at terminal velocities of 8 and 9 m/s, respectively, are yielded by Honegger’s equation. These values are comparable to the findings from the field measurements. The size, concentration, and terminal velocity of the raindrops all affect how much destabilising force results from the impact force of the raindrops. When conducting their study on drop size distribution, [9] used actual measurement data from the JossWaldvogel disdrometer and performed drop size distribution. They concluded that rainfall intensity causes an increase in the number and size of the rain drops. Even with the highest measured force of 57.6 gm on a 35 cm2 area, the overall force from the current study is only 16.9 kg/m2 (i.e. 0.17 kN/m2 ), which is insignificant in contrast to the destabilising force required for a landslide. However, the measurements made in the field did not account for the cloudburst situations in which rainfall intensity can reach up to 1000 mm/h or greater, with the raindrops larger than 6 mm, and the terminal velocity exceeds 10 mm/s. To make any inferences, more research is required because the maximum rainfall intensity in the current study during the experimentation monitoring period was just 29 mm/h.
4 Conclusions Analysis of the data in this study shows that there is little to no impact of rainfall on GWT in the study area; hence, a rise in the water table is not likely to be the cause of slope collapse. Despite being a modest destabilising effect for slope collapse, the impact of raindrops on shear strength reduction via pore water pressure development
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is substantial. Additionally, the antecedent rainfall conditions have a huge impact on how the pore water pressure develops; in unsaturated soil, even a large downpour following a few days of dry spell did not cause the rise in PWP. However, in case of antecedent rainfall conditions with few spells of rain, a moderate rainfall of 10 mm/h gave rise to a high PWP. With the rainfall intensity of 10 mm/h, the highest recorded PWP is 330.77 kPa. It is also observed that raindrop impact force increased with increasing rainfall intensity, and the values lie in the range from 1.50 to 57.7 gm. This further increased PWP of the soil in the antecedent, saturated conditions.
References 1. Calvello M, Cascini L, Sorbino G (2008) A numerical procedure for predicting rainfallinduced movements of active landslides along pre-existing slip surfaces. Int J Numer Anal Meth Geomech 32(4):327–351 2. Cheng WJ, Xiao-Nan G, Shi-guo M (2014) Effects of pore-water pressure distribution on slope stability under rainfall infiltration. Electron J Geotech Eng 19:1677–1685 3. Cho SE (2009) Infiltration analysis to evaluate the surficial stability of two layered slopes considering rainfall characteristics. Eng Geol 105(1–2):32–43 4. Crosta GB, Frattini P (2001) Rainfall thresholds for triggering soil slips and debris flow. In: Proceedings of the 2nd EGS Plinius conference on Mediterranean storms: Publication CNR GNDCI, vol 2547, pp 463487 5. Dikshit A, Satyam DN (2018) Estimation of rainfall thresholds for landslide occurrences in Kalimpong, India. Innov Infrastruct Solut 3(1):24 6. Dikshit A, Satyam DN, Towhata I (2018) Early warning system using tilt sensors in Chibo, Kalimpong, Darjeeling Himalayas, India. Nat Hazards 94(2):727–741 7. Fannin RJ, Jaakkola J (1999) Hydrological response of hillslope soils above a debris-slide headscarp. Can Geotech J 36(6):1111–1122 8. Fourie AB (1996) Predicting rainfall-induced slope instability. In: Proceedings of the institution of civil engineers: geotechnical engineering, vol 119, no 4 9. Harikumar R, Kumar VS, Sampath S, Vinayak PVSSK (2007) Comparison of drop size distribution between stations in Eastern and Western coasts of India. J Indian Geophys Union 11(2):111–116 10. Honegger E (1927) Tests on erosion caused by jets. Brown Boveri Rev 14(4):95–104 11. Huang AB, Lee JT, Ho YT, Chiu YF, Tsai TL (2009) Field monitoring of pore-water pressure profile in a slope subjected to heavy rainfalls. In: Proceedings XVII international conference on soil mechanics and geotechnical engineering, pp 1931–1934 12. Johnson KA, Sitar N (1990) Hydrologic conditions leading to debris-flow initiation. Can Geotech J 27(6):789–801 13. Kim J, Jeong S, Park S, Sharma J (2004) Influence of rainfall-induced wetting on the stability of slopes in weathered soils. Eng Geol 75(3–4):251–262 14. Lade PV (2010) The mechanics of surficial failure in soil slopes. Eng Geol 114(1–2):57–64 15. Pradel D, Raad G (1993) Effect of permeability on surficial stability of homogeneous slopes. J Geotech Eng 119(2):315332 16. Rahardjo H, Lee TT, Leong EC, Rezaur RB (2005) Response of a residual soil slope to rainfall. Can Geotech J 42(2):340–351 17. Vilayvong K, Yasufuku N, Ishikura R (2016) Evaluation of rainfall erosivity and impact forces using strain gauges. Lowland Technol Int 17(4):207–217
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18. Yoshida Y, Kuwano J, Kuwano R (1991) Rain-induced slope failures caused by reduction in soil strength. Soils Found 31(4):187–193 19. Zhan TL, Ng CW, Fredlund DG (2007) Field study of rainfall infiltration into a grassed unsaturated expansive soil slope. Can Geotech J 44(4):392–408
Design and Cost Analysis of Headed Bars as Mechanical Anchorage System for Reinforced Concrete Beam-Column Joints Shubham Singhal , Ajay Chourasia , and Pallavi Rai
Abstract In reinforced concrete (RC) frames, anchorage system of conventional development length and standard 90º or 180º bend hooked bar anchor terminating at the joint, protruding into the face of the column, have many drawbacks such as reinforcement congestion, improper concreting and compaction, honeycombing, which ultimately leads to joint strength deterioration and joint damage during the earthquakes. Moreover, development length requires high amount of steel, which leads to depletion of natural resources, along with increased cost. This evolved need for development of alternate anchorage systems such as headed bars, which have the potential to eliminate the shortcomings of conventional anchorage without any compromise on economy. Headed bar is formed by welding or threading a steel anchor at the end of beam reinforcement bar. This paper presents design and cost analysis of headed bars which can serve as anchorage for RC beam-column joints. It bestows a cost-effective and construction-efficient alternative to anchorage system of conventional development length. Design specifications in the form of geometrical recommendations for headed bars are made based on pull-out tests. The paper further derives the equation of development length and demonstrates cost-effectiveness of headed bars through rigorous cost analysis and comparison with costing of anchorage system of conventional development length for different rebar diameters. Keywords Headed bars · RC beam-column joint · Development length · Mechanical anchorage · Pull-out tests · Cost analysis S. Singhal (B) Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida 201301, India e-mail: [email protected] A. Chourasia Structural Engineering Division, CSIR—Central Building Research Institute, Roorkee 247667, India P. Rai Amity School of Engineering and Technology, Amity University Uttar Pradesh, Lucknow 226010, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_40
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1 Introduction Beam-column junction forms a critical region as it attracts large seismic forces which lead to the induction of plastic hinge at the joint. Beam-column joint in the frame system shall ensure the degree of restraint in any direction. Flexural deformation of beam and column may result in stress concentration at beam and column edges, for which adequate provisions shall be incorporated to prevent the damage at the joint. Beam-column joints may be categorized as rigid, semi-rigid or hinged. Rigid joints are continuous joints that can adequately transfer the axial force, moment and shear, while semi-rigid joints do not possess full continuity and have comparatively lower yield moments. Hinged joints are incapable of resisting moments and can only sustain gravity loads. Some joints using mechanical anchorages may behave as semi-rigid joint system. Reinforced concrete (RC) structures are conventionally designed as moment resisting frames. Subsequently, during the seismic loading, plastic hinge develops near the toe of the RC column and at RC beam-column joint due to the presence of mechanical anchorage at the joint, which is often in the form of development length. The RC beam-column joint may be designed for plastic hinge occurring near the joint and to induce shear demand close to nominal shear of joint for conventional monolithic component. Apart from development length, various types of mechanical anchorage systems were designed and tested by the researchers worldwide to study their mechanism and behaviour under seismic loading [1–4]. Beam-column joints, one with reinforcement bars and another through bolting, were evaluated under cyclic loading. Both the anchorage systems underperformed and did not emulate monolithic behaviour owing to occurrence of rotation at joint [5]. Behaviour of RC beam-beam joint anchorage using U and L bent reinforcement bars positioned exterior to the column element was studied, where the test specimen delivered lower strength but higher ductility as compared to monolithic specimen [6]. Another beam-column joint anchorage using threaded reinforcement bar and tapered splices was tested under lateral cyclic load. It was concluded that the proposed system can be adopted for the regions of high seismicity [7]. A bolted moment joint anchorage system as shown in Fig. 1 in which 10 and 20 mm mild steel plates were fixed at beam end and column face was experimentally investigated by Pul and Sentürk ¸ [8]. Beam plate was made stiffened by other two small plates all along, and three high-strength bolts were used at both sides of the beam. Column plate was fastened to concrete through anchorage rods welded to the plate. The T-shaped beam (250 × 450 mm) and column (300 × 300 mm) were tested to non-varying axial load acting on the column and displacement controlled reversed cyclic load on end of beam and compared with identical conventional specimen. Higher moment and shear resisting capacity were observed. Hence, bolted moment joint anchorage system can be adopted for beam and column for buildings in the regions of high seismicity. Figure 2 shows a dry beam-column joint system using stiffener angle, steel tubes and HSFG bolting. Howbeit, this anchorage system has not been evaluated experimentally [9].
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Fig. 1 Bolted moment anchorage [8]
Fig. 2 Steel angle at beam-column joint [9]
A ductile moment resisting anchorage system was explored by Parastech et al. [10], where columns were casted continuously, leaving a free space at the beamcolumn junction. In the anchorage zone, beams having hollow U-shaped cross section where a longitudinal reinforcement bar is placed to support four diagonal stirrup rebars which protrude from the column are as shown in Fig. 3. The joint was then filled with cast-in situ concrete. The joint was subjected to cyclic loading and demonstrated superior flexural strength, energy dissipation and initial stiffness in comparison with the similar cast-in situ specimen. Flexural cracks were seen in joint, primarily focused in the zone of plastic hinge formation in the beam, which is in agreement with the weak beam-strong column principle in earthquake-resistant analysis and design. Beam to column connections may also be provided with steel inserts, bolting, anchorage bars, welding and other mechanical means [11]. Currently available alternate mechanical anchorage systems are difficult to implement and rarely used for cast-in situ beam-column joints. This paper provides design and cost analysis of
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Fig. 3 Ductile moment resisting anchorage system [10]
headed bars and its design specifications based on pull-out tests and derivation of development length. The only limitation of headed bars relates to that of attaching it to the beam rebar. The paper further presents cost analysis, demonstrating the cost-effectiveness of headed bars as compared to the development length system.
2 Headed Bars as Anchorage System for Beam-Column Joints The beam-column joint region is a critical zone in RC frame structures, which experience stresses during the seismic loading. The peak stresses so developed beyond the critical section at the either end of the member require a minimum embedment depth of reinforcement bars to develop its yield stress. This minimum embedment length of reinforcement is achieved by providing development length, which is extension of beam longitudinal rebars into the column and usually bent at 90º. Current trend of architectural design in structures which constrains the dimension of member hinders the proper provision of this development length. Longitudinal flexural reinforcing bar protruding into the column owing to inadequate space for development length reinforcing bar causes steel congestion problem, which leads to improper concreting and difficulty in compaction, consequently resulting in honey combing and inadequate structural performance of joint. Further to this, high amount of steel reinforcement in construction leads to cost overrun and depletion of natural resources. The potential solution could be headed bars, which are established by providing a steel anchor at the end of beam longitudinal rebar. This steel anchor may be attached through welding or threading. Headed bars are cost effective, have easy installation, facilitate time-saving fabrication, minimization of steel congestion and increase construction efficiency in joints, without deteriorating the structural performance. Figure 4 shows the conventional anchorage and headed bars in RC beam columns. Significant research on bond behaviour of headed bars has been carried out by Singhal et al. [12], Chourasia et al. [13], Hong and Park [14], Kang et al. [15], Kang and Mitra [16], Lee and Yu [17] and Chun et al. [18]. However, limited research has
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Fig. 4 Beam-column joints with a development length and b headed bars
been performed on length of head and its influence on the anchorage capacity. Some ACI codes are incorporated with the guidelines for provision of headed bar with certain restrictions on certain parameters such as embedment depth, concrete grade, grade of steel and clear spacing. However, there still lies ambiguity while deciding on embedment depth and head geometry. This paper provides geometrical recommendations for headed bars for their implementation in RC beam-column joints, through pull-out tests. The paper further demonstrates cost-effectiveness of headed bars through rigorous cost analysis and comparison with costing of conventional anchorage system of development length for different rebar diameters.
3 Pull-Out Tests 3.1 Experimental Methodology To draw geometrical recommendations for headed bars, tension pull-out experiments were performed on various types of headed bars embedded into the concrete. The concrete and reinforcement steel of 20 MPa and Fe 415 grade have been used in the study. A total of 45 different types of specimens with three different profile heads (plain, groove and ribbed) and five different lengths of head (11, 19, 27, 35 and 43 mm) were used in the study. Figure 5 demonstrates different headed bars used. The headed bars were embedded into the concrete cube of 300 mm at varying embedment depths of 6.25 φr , 8.33 φr and 10.42 φr (φr is rebar diameter). The free end of headed bar protruded out over a length of 150 mm to ensure proper gripping of bar to conduct the test in UTM of 100 tonnes capacity as portrayed in Fig. 6. The specimens were tested monotonically under tension load till the failure. Pull-out strength obtained from the test is referred as anchorage or bond capacity of headed bar.
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(b)
(c)
Fig. 5 Types of headed bars: a plain headed bars; b grooved headed bars and c ribbed headed bars Fig. 6 Experimental setup for pull-out tests
3.2 Results and Discussion Behaviour of Headed Bars under Pull-out Tests. Dowel bars showed complete pull-out failure mode with inferior anchorage capacity, while headed bars showed bar slippage and concrete failure with superior anchorage capacity. Among five different lengths of head, 27 mm head (head length = head diameter) was influential enough for bond stress resistance. All three types of headed bars were found to have similar behaviour on initial stage of loading, and at the ultimate loading point, the failure pattern differed for each specimen for each embedment depth. Failure pattern was almost similar for plain and grooved headed bar. Ribbed headed bar was found to give better performance with regard to the anchorage and failure pattern in comparison with plain and grooved headed bars. Figure 7 presents the bond or anchorage capacity of different headed bars tested under pull-out loading.
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80 60
6.25db
50
8.33db
40
10.42db
30 20 10 0
P11 P19 P27 P35 P43 G11 G19 G27 G35 G43 R11 R19 R27 R35 R43 WH
Bond Capacity (kN)
70
Specimen Type Fig. 7 Pull-out capacity of headed bars with varying embedment. p: plain, g: grooved, r: ribbed, 11,19, 27, 35, 43: length (mm)
Table 1 Design specifications for headed bars
Parameter
Recommendation
Area of head
> 5 times the rebar diameter
Bearing ratio
4
Minimum rebar diameter
12 mm
Diameter of head
≥ 2.25 times the rebar diameter
Ratio of length and diameter of head
1
Head profile
Ribbed
Yield strength of headed bar
500 MPa
Geometrical Recommendations for Headed Bars. Based on extensive pull-out tests and observations and results obtained thereof, following recommendations are made for application of headed bars in RC beam-column joints (Table 1).
4 Derivation of Development Length for Headed Bars in Beam-Column Joint Tension force acts on longitudinal rebar of RC beam, which is transferred to the beamcolumn joint region. The force must be resisted by the reinforcement configuration and detailing provided in the beam-column joint, which is conventionally in the form of L-shaped development length as per IS 456: 2000 [19]. It has its own limitations
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as discussed before in the paper. The development required for the headed bars (L d ) can be derived based on equating the tension force experienced by longitudinal bars of beam to the force acting in the joint region, based on design bond stress (τ bd ) of concrete. Tension force, T =
σsπ φ2r , 4
(1)
where σ s = stress in reinforcement at the design load section, which may be considered as 0.87 f y for extreme loading; φr = diameter of reinforcement bar; f y = yield stress in reinforcement bar. Force acting in the joint region F = τbd (L d × π φr ) + τbd (L h × π φh )
(2)
where L h = length of head anchor; φr = diameter of head anchor. Equating Eqs. (1) and (2), σsπ φ2r = τbd (L d × π φr ) + τbd (L h × π φh ). 4
(3)
Thus, development length required for headed bars Ld =
L h φh σs φr − 4τbd φr
(4)
Alternatively, development length for headed bars can also be computed from Eq. 5 [20]. ( Ld =
) f y ψt ψe √ φr 2.1 f c'
(5)
where f c ' = grade of concrete; ψ e and ψ t = modification factors in accordance with ACI 318-14 [20].
5 Cost Analysis Costing of implementation of headed bars in RC frame (beam-column joints) was evaluated and compared with the costing of traditional development length for rebars of different diameter. Costing of steel anchor is taken as per the rate provided by the manufacturer. Rate of steel work was taken to be |60/kg, including the charges of labour which is most prevalent in the construction. Embedment depth of rebar in
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Table 2 Cost analysis of headed bars Rebar dia (mm)
Anchor dia (mm)
12
24
27
20.50
36.50
38.40
16
32
36
32.50
64.36
91.02
Anchor length (mm)
Anchor costa (|)
Total costing Costing of development of anchorb lengthc (|) (|)
20
40
45
53.00
104.11
177.78
25
50
56
90.50
172.91
347.22
32
64
72
174.50
315.58
728.18
a
Fig. 8 Percent saving in headed bars with respect to rebar diameter
Percent Saving (%)
Cost as per manufacturer b Anchor cost + rebar cost, considering rate of |60/kg including labour charges. (rebar length embedded in beam considered as 300 mm) c Development length as per IS 456:2000, considering rate of |60/kg including labour charges
100 75 50 25 0
12
16
20
25
32
Rebar Diameter
to RC beam-column joint was considered to be 300 mm for the headed bars, while the embedment depth required for conventional system of development length is calculated in accordance with IS 456: 2000 [19]. Table 2 presents the analysis of cost and comparison of development length and headed bars various rebar diameters. It is obvious from the cost analysis that the headed bars are much more cost effective, with economy increasing with the increasing diameter of rebar (Fig. 8).
6 Conclusion The research provided design specifications and cost analysis of headed bars as a joint anchorage system for beam-column joint. The proposed headed bars were determined to be effective enough in comparison with dowel bars in terms of bond capacity and damage mode. Design specifications in the form of geometrical recommendations for headed bars are made based on the pull-out tests. The paper further derives the equation of development length and demonstrates cost-effectiveness of headed bars through rigorous cost analysis and comparison with costing of traditional anchorage
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method of development length for different rebar diameters. It can conveniently be summarized that the headed bars can facilitate a much better alternate to the prevalent development length for an effective joint anchorage system for connecting RC beam and column. Generalized recommendations and equations for the development length for optimized design of headed bars are expected to be of considerable worth to the engineers and structural designers involved in construction industry.
References 1. Singhal S, Chourasia A (2019) Seismic resistance of precast reinforced concrete shear wall: experimental and analytical study. In: Proceedings of 8th international engineering symposium, Kumamoto University, Kumamoto, Japan 2. Chourasia A, Kajale Y, Singhal S, Parashar J (2020) Seismic performance assessment of twostorey precast reinforced concrete building. Struct Concr 21(5):2011–2027 3. Singhal S, Chourasia A, Panigrahi SK, Kajale Y (2021) Seismic response of precast reinforced concrete wall subjected to cyclic in-plane and constant out-of-plane loading. Front Struct Civ Eng 15:1128–1143. https://doi.org/10.1007/s11709-021-0753-5 4. Singhal S, Chourasia A, Kajale Y (2022) Design of steel wire loop connection for precast reinforced concrete structural components. Scientia Iranica 5. Alcocer S, Carranza R, Perez-Navarrete D (2000) Behaviour of a precast concrete beam-column connection. In: 12th world conference on earthquake engineering, vol 1543, pp 1–8 6. Wahjudi DI, Suprobo P, Sugihardjo H (2014) Behavior of precast concrete beam-to-column connection with U-and L-bent bar anchorages placed outside the column panel-experimental study. Procedia Eng 95:122–131 7. French CW, Hafner M, Jayashankar V (1989) Connections between precast elements-failure within connection region. J Struct Eng 115(12):3171–3192 8. Pul S, Sentürk ¸ M (2017) A bolted moment connection model for precast column-beam joint. In: Proceedings of the 2nd world congress on civil, structural and environmental engineering, ICSENM 129 9. Aninthaneni PK, Dhakal RP (2014) Conceptual development: low loss precast concrete frame buildings with steel connections. In: NZSEE conference 10. Hossein P, Iman H, Reza R (2014) A new ductile moment-resisting connection for precast concrete frames in seismic regions: an experimental investigation. Eng Struct 70:144–157 11. Bournas DA, Negro P (2012) Seismic performance of mechanical connections in the SAFECAST precast building. In: 15th world conference on earthquake engineering, Lisbon, Portugal 12. Singhal S, Chourasia A, Kajale Y (2021) Cyclic behaviour of precast reinforced concrete beam-columns connected with headed bars. J Build Eng 42:103078 13. Chourasia A, Gupta S, Singhal S (2017) Investigation on headed bars as anchorage device in beam-column joint—a literature review. In: Proceedings of CISHR. National Institute of Technology Uttarakhand, Srinagar, pp 202–213 14. Hong S, Park SK (2012) Uniaxial bond stress-slip relationship of reinforcing bars in concrete. Adv Mater Sci Eng 2012:1–12 15. Kang THK, Ha SS, Choi DU (2010) Bar pullout tests and seismic tests of small-headed bars in beam-column joints. ACI Struct J 107(1):32–42 16. Kang THK, Mitra N (2012) Prediction of performance of exterior beam-column connections with headed bars subject to load reversal. Eng Struct 41:209–217 17. Lee HJ, Yu SY (2009) Cyclic response of exterior beam-column joints with different anchorage methods. ACI Struct J 106(3):329–339
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18. Chun SC, Choi CS, Jung HS (2017) Side-face blowout failure of large-diameter high-strength headed bars in beam-column joints. ACI Struct J 114(1):161–172 19. IS 456: 2000. Plain and reinforced concrete-code of practice. Bureau of Indian Standards, New Delhi 20. American Concrete Institute 318-14 (2014) Building code requirements for reinforced concrete. American Concrete Institute, Farmington Hills
Technoeconomic Assessment of Iron Filings Blocks Abiola Adebanjo , Kehinde Oyewole , Vicky Kumar , Siti Nooriza Abd Razak , Eden Emmanuel, Priyanka Singh , and Adedamola Adebisi
Abstract In this paper, an effort has been made to incorporate iron filings (IF), a waste from metal workshops, in the production of hollow masonry blocks. The fine aggregate component was partially replaced by 5, 10, 15, and 20% of IF. A mix ratio of 1:8 was used in the production of blocks of size 450 mm × 150 mm × 225 mm. The sorptivity, compressive strength (CS), and cost analysis of masonry blocks with iron filings were evaluated. The results showed that the iron filings used were well graded. The sorptivity of iron filings blocks (IFB) decreased as the percentage of iron filings increased from 0 to 20%. The highest compressive strengths were obtained at 5% addition of iron filings, ranging from 0.93 N/mm2 at 7 days to 2.10 N/mm2 at 28 days. The cost analysis revealed a 1.05% reduction in the unit price of the block with optimum CS at conventional pricing rates. Keywords Sorptivity · Compressive strength · Iron filings · Masonry blocks
A. Adebanjo (B) · A. Adebisi Department of Civil Engineering, Osun State University, Osogbo, Nigeria e-mail: [email protected] K. Oyewole Department of Chemical Engineering, Osun State University, Osogbo, Nigeria A. Adebanjo · V. Kumar · S. N. A. Razak Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia E. Emmanuel Department of Civil Engineering, RECTEM, Mowe, Nigeria P. Singh Department of Civil Engineering, Amity University, Noida, Uttar Pradesh, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_41
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1 Introduction Masonry blocks are one of the oldest construction materials. They have been widely adopted for use in both developed and commonwealth countries due to their ease of use, availability of material, relatively low cost, and ease of installation by unskilled workers [1]. In their paper, [2] stated that the production of blocks is becoming the backbone of infrastructure development in every country. In Nigeria, for example, the block-making industry is one of the largest sub-sectors of the construction industry. At the moment, numerous block industries in the country are attempting to meet the demands of the construction sector. However, no strict measures exist to determine the quality of the materials utilised, and thus, the quality of the blocks is created [3, 4]. According to [5], there are other prevailing issues surrounding the quality and availability of the constituent materials that make up the masonry units. Some of these are the use of fine aggregates with high clay content and the concerns about the effect of sand dredging on the sustainability of aquatic life. In addition to this, Sholanke et al. [4] reported that the recent increase in the cost of conventional materials used in the production of masonry units has also had a direct effect on the unit cost of blocks. Consequently, for sustainability and socio-economic development, there is a need to use alternative materials, particularly waste materials from industrial processes with desirable properties that can complement conventional materials such as sand in masonry production. The utilisation of waste of all kinds is fast becoming of interest to most researchers because it provides better alternatives to waste disposal and some of the challenges that come with the latter. Some of these challenges are the high cost of recycling, potential pollution, and loss of landmass [6]. Instead of dumping these materials in scarce landfills, reusing them in building construction as a complementary material can be a considerable option [7–10]. For instance, Davies and Olofinade used polyethylene terephthalate (PET) waste to partially replace sand in cement-based hollow masonry blocks. They reported that the density and compressive strength of blocks made with PET waste were well above the minimum requirements for blocks made from lightweight coarse aggregates [11]. In another effort by Robert et al., it was reported that when coconut husk was used to partially replace sand in sandcrete blocks, the blocks produced satisfied the condition for non-load bearing walls [12]. The following authors [13, 14] also concluded that 5% of crushed waste plastic and 10% of sawdust as a partial replacement for sand, the properties of the blocks compared favourably with those of the reference samples. Iron filings (IF), which are relatively fine particles produced locally in excessive quantities by steel workshops and factories, are a by-product that has yet to be used extensively in block production. If this waste is not disposed of properly, it has a devastating effect on the environment. Recent efforts to incorporate this new material into concrete have produced impressive results. For example, Alsaad et al. [15] replaced the sand with iron filings in concrete and reported improved compressive and tensile strengths. Also, Olawale et al. used IF in self-compacting concrete and the results compared favourably with those of conventional fine aggregate [16].
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The use of IF as a partial replacement for sand in masonry blocks seeks to address two major concerns raised earlier. The first is to determine its suitability as a complementary material for conventional fine aggregates in masonry block units, and the second is to find a cheaper way to get rid of it so that it does not pollute the environment as much as it could. This study, therefore, focused on the suitability of using IF as a partial replacement for fine aggregates in masonry block production. To accomplish this, the particle size of the various aggregates was assesed. Different mixes of masonry blocks were produced by replacing the sand content with IF. Thereafter, the sorptivity and compressive strength of the blocks were determined using their respective standards. Lastly, the cost analysis for incorporating IF into block units was evaluated.
2 Materials and Methods Portland Limestone Cement (PLC), fine aggregates (river sand and stone dust), and iron filings were the primary materials used in this study. BUA’s brand of Grade 42.5 PLC was used and conforms to the requirement of [17]. The fine aggregates were obtained from Osun State University Block Industry. IF were collected from metal workshops in Osogbo, which were deposited in large quantities; Fig. 1a–c shows the aggregates’ pictorial view. The PLC was used as a binding agent, while river sand and stone dust were used as fine aggregate in the mix for the control samples and their physical properties are as provided in Table 1. The IF was used to replace the fine aggregate component of the masonry mix at varying percentages of 5, 10, 15, and 20. A mix ratio of 1:8 (cement: fine aggregate) was used in the production of masonry blocks of size 450 mm × 150 mm × 225 mm. The blocks produced are as shown in Fig. 1d; the mix ratio adopted in this study was based on the findings from a pilot study by [18] which revealed that the majority of the block producers in the study area use mix ratios ranging from 1:8 to 1:16. The quantity of materials needed to produce 100 units of blocks is provided in Table 2. Particle size analysis of aggregates, sorptivity, and compressive strength of the blocks were determined using the methods specified by [12, 19–22] and are as shown in Fig. 1e–f. The economic benefits of incorporating IF in masonry blocks were also evaluated using standard material rates, as presented in Table 3. Although iron filings were obtained for free in metal workshops, the cost of sieving and transporting to the site was estimated at $2.22/ ton ($0.002/kg). A profit margin of 10% of the total cost of production was also assumed to arrive at a logical decision.
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Fig. 1 Experimental procedure a stone dust; b river sand; c iron filings fine aggregate; d iron filings blocks (0, 5, 10, 15, and 20%); e compressive strength test; f typical block at failure Table 1 Physical properties of aggregates Property
Sand
Stone dust
Iron filings
Standard
Specific gravity
1.4
1.8
1.6
2.40
Water absorption (%)
3.87
2.56
1.95
5.0
Bulk density (g/cm3 )
1.2
1.30
1.7
1.2–1.90
Table 2 Quantity of materials required for 100 units of block IF (%)
Cement (kg)
River sand (kg)
Stone dust (kg)
Iron filings (kg)
Water (kg)
0
250
1333.33
666.67
0.00
125
5
250
1266.67
633.33
100.00
125
10
250
1200.00
600.00
200.00
125
15
250
1133.33
566.67
300.00
125
20
250
1066.67
533.33
400.00
125
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Table 3 Standard material rates in Nigeria Item
Cement
River sand
Stone dust
Iron filings
Water
Labour/block
Amount ($/kg)
0.222
0.010
0.010
0.002
0.002
0.067
3 Results and Discussion 3.1 Particle Size Distribution of Aggregates The particle size distribution curve for the sand, iron filings, and stone dust used for the production of the masonry blocks is shown in Fig. 2. The coefficient of uniformity (Cu), which describes the gradient of the curve on a semi-logarithmic graph, usually ranges from ≤ 2 (poorly graded) to ≥ 5 (well graded). Based on this classification, river sand and iron filings all had values greater than 4.0, and as such, they are well graded, but this was not the case for the stone dust. The coefficient of curvature (Cc), which defines how densely packed the aggregates are, generally ranges from 1 to 3. The results showed that both the river sand and the stone dust were below the limit, but the stone dust was way above the limit. Also, results of the fine modulus (FM) showed that the stone dust was coarser than the other two materials, as the value of FM obtained exceeded the maximum of 3.25 specified by [5, 23]. According to Adekunle et al. [18], well-graded fine aggregates increase the bonding strength of sandcrete mix as the particles have approximately the same diameter, while poorly graded sand reduces the bonding strength of sandcrete mix as the diameter of the particles varies significantly. In their opinion, Omoregie and Alutu believe that the grading performance of the aggregates can also influence the compressive strength of blocks because finer materials with poorly graded curves will require more water to enhance the workability, thereby compromising the strength of the block [5].
Percentage Passing
120 100 80 River Sand iron Fillings
60 40 20 0 0.01
0.1
1
Sieve Opening (mm) Fig. 2 Particle size distribution curves for fine aggregates
10
Fig. 3 Sorptivity of iron filings blocks
A. Adebanjo et al.
Sorptivity (mm/Sec1/2)
490
6.00E-07 5.00E-07 4.00E-07
0%
3.00E-07
5%
2.00E-07
10%
1.00E-07
15%
0.00E+00 15
25
35
45
20%
Time (Sec1/2)
3.2 Sorptivity of Iron Filings Block The response of IFB to capillary rise and absorption rate over 30 min is represented in Fig. 3. Samples with IF showed a lower absorption rate than the control samples, especially in the early minutes of exposure to water. According to Robert et al., blocks with lower sorptivity values should be given consideration when they are intended to be used as walling units in buildings. The high sorptivity experienced by the control samples in this study can be attributed to the high water absorption of sand [12]. This observation is in line with [24] findings, where it was reported that sandcrete blocks have high sorptivity after long exposure to water. The blocks with greater percentages of IF (15 and 20%) absorb water at a much slower rate suggesting that these blocks could be useful in tropical humid environments where capillary suction of water from the surrounding environment is an issue. Findings from this study are an improvement on the results of [12], where it was reported that sawdust waste, when used in blocks, increased the pore spaces in the block, thereby increasing the sorptivity of the blocks. However, another major concern is the degradation of the blocks as a result of the rusting that may arise when the iron filings remain in the water for too long; nevertheless, this may be avoided by coating the iron filings with polymer before use.
3.3 Compressive Strength of Iron Filings Block The result of the compressive strength of the masonry blocks at different curing ages of 7, 14, and 28 days is presented in Fig. 4. For masonry block samples tested after 7 days of curing, the compressive strength ranged from 0.48 N/mm2 for 20% IF to 0.93 N/mm2 for 5% IF. As the curing age increases from 7 to 28 days, the compressive strength of the blocks increases by an average of 200% across the board, ranging from 1.07 N/mm2 for 20% IF to 2.10 N/mm2 for 5% IF.
Compressive Strength (N/mm2)
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3 2.5 2 7 DAYS
1.5
14 DAYS
1
28 DAYS
0.5 0
0
5
10
15
20
Iron filings content (%) Fig. 4 Compressive strength of IFB
The effect of iron filings on the blocks produced was positive at a 5% replacement value but decreased gradually as the percentage replacement increased to 20%. This observation is similar to that obtained by [11], where it was reported that at 5 and 10% of PET waste in sandcrete mix, the compressive strength compared relatively with the requirement of the Nigerian Building and Road Research Institute (NBRRI) [25] for hollow sandcrete blocks. However, the block with the optimal compressive strength in this study was 16% less than the minimum requirement of 2.5 N/mm2 specified by [26] for blocks with a mix ratio of 1:6 at 28 days of curing age. One possible explanation for this reduction in strength is the mix ratio (1:8) adopted in this study. Boob [27] studied the performance of sawdust in low-cost sandcrete blocks and obtained an optimum compressive strength of 4.5 N/mm2 using a mixing ratio of 1:6. Similarly, [14] investigated the potential of replacing sand with sawdust and obtained a 28-day compressive strength of about 5.3 N/mm2 with a mixing ratio of 1:3. When compared to earlier studies, it is evident that the mix ratio used in this study (1:8) had a negative influence on compressive strength. What is more worrisome is that many masonry block manufacturers in this part of the world employ weaker mix ratios ranging from 1:8 to 1:16 for their manufacturing.
3.4 Cost Analysis of Using Iron Filings in Masonry Block Units The cost analysis for making 100 units of blocks with 0, 5, 10, 15, and 20% of iron filings is provided in Table 4. According to the calculations, a unit block produced from a 1:8 mix will sell for about $0.93 at conventional material pricing. The results also demonstrated that at 5, 10, 15, and 20% of IF in the blocks, there was a price reduction of 1.05, 2.10, 3.15, and 4.20%, respectively. Findings from this study were slightly lower than the observations in [28], where it was reported that by replacing 16% of the sand content in the block with agricultural wastes, the overall cost of
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Table 4 Cost analysis for producing 100 units of blocks IF (%)
Cement
($)
($)
($)
($)
($)
($)
($)
($)
0
55.56
14.81
7.41
0.00
0.28
6.67
84.72
93.19
River sand
Stone dust
Iron filings
Water
Labour cost
Total cost of Profit production (1.10% of (TCP) TCP)
5
55.56
14.07
7.04
0.22
0.28
6.67
83.83
92.22
10
55.56
13.33
6.67
0.44
0.28
6.67
82.94
91.24
15
55.56
12.59
6.3
0.67
0.28
6.67
82.06
90.26
20
55.56
11.85
5.93
0.89
0.28
6.67
81.17
89.28
the block produced was reduced by roughly 10%. At 30–35% higher replacement values, the cost reduction was nearly one-third that of the control sample.
4 Conclusion This study has focused on the technoeconomic potential of using iron filings as a partial replacement for fine aggregates in masonry block units. The physical properties of iron filings and conventional aggregates were evaluated to determine their suitability as an aggregate in masonry block production. The sorptivity and compressive strength of IFB were also determined. Furthermore, the cost of incorporating this material in block production was investigated, and the study’s findings are summarised below: i. The particle size of iron filings compares favourably with those of conventional aggregates. ii. As the percentage replacement increases from 0 to 20%, the sorptivity reduced notably for all the percentages of IF. The presence of iron filings in the block reduced the rate at which the block absorbed water. iii. There was a reduction in the compressive strength as the content of IF increased. However, blocks with IF of 5 and 10% were relatively higher than the NBRRI minimum standard of 2.0 N/mm2 for non-load bearing walls. iv. The cost analysis of incorporating IF in block production revealed a 1.05 and 2.10% reduction in unit price for 5 and 10% of IFR, respectively. Acknowledgements The authors express their sincere appreciation to the staff of the Materials and Structures Laboratory of Osun State University. Also, we would like to extend our appreciation to Osun State University Block Industry and members of the Mechanical Workshop of Osun State University for their support during the experimental work.
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References 1. Yang X, Wu H, Zhang J, Wang H (2019) Shear behavior of hollow concrete block masonry with precast concrete anti-shear blocks. Adv Mater Sci Eng 2. Anosike MN, Oyebade AA (2012) Sandcrete blocks and quality management in Nigeria building industry. J Eng Project Prod Manage 2(1):37–46. https://doi.org/10.32738/jeppm. 201201.0005 3. Kamiyo OM (2020) Modelling of heat transfer through hollow blocks produced with ricehusk-ash blended cement. Arid Zone J Eng Technol Environ Azojete 16(3):501–508 4. Sholanke AB, Fagbenle OI, Aderonmu PA, Ajagbe AM (2015) Sandcrete block and brick production in Nigeria-prospects and challenges. IIARD Int J Environ Res 1(4) 5. Omoregie A, Alutu OE (2006) The influence of fine aggregate combinations on particle size distribution, grading parameters, and compressive strength of sandcrete blocks. Can J Civ Eng 33(10):1271–1278 6. Caijun S, Qian J (2000) High performance cementing materials from industrial slags—a review. J Resour Conserv Recycl 29:195–207 7. Ameri M, Ali B (2012) Experimental investigation of stone matrix asphalt mixture containing steel slag. Scientia Iranica A:19(5) 8. Azunna SU, Abd Aziz FN, Abu Bakar N, Mohd Nasir NA (2018) Mechanical properties of concrete with coconut shell as partial replacement of aggregates. IOP Conf Ser: Mater Sci Eng 431(3):7. https://doi.org/10.1088/1757-899X/431/3/032001 9. Mekki M, Abdelghani N, Zitouni S (2018) Effect of crushed glass aggregate on the physicomechanical properties of micro-concrete. Leban Sci J 19(2):210–228. https://doi.org/10.22453/ lsj-019.2.210228 10. Peng J, Huang L, Zhao Y, Ghen P, Zeng L, Zheng W (2013) Modeling of carbon dioxide measurement on cement plants. Adv Mater Resour 610–613:2120–2128 11. Davies IEE, Olofinnade OM (2021) Suitability of using post-consumer polyethylene terephthalate wastes in cement-based hollow sandcrete blocks. IOP Conf Ser: Mater Sci Eng 1036(1):012046 12. Robert UW, Etuk SE, Agbasi OE, Okorie US, Lashin A (2021) Hygrothermal properties of sandcrete blocks produced with raw and hydrothermally-treated sawdust as partial substitution materials for sand. J King Saud Univ Eng Sci 13. Akinyele JO, Toriola IO (2018) The effect of crushed plastics waste on the structural properties of sandcrete blocks. Afr J Sci Technol Innov Dev 10(6):709–713 14. Adebakin IH, Adeyemi AA, Adu JT, Ajayi FA, Lawal AA, Ogunrinola OB (2012) Uses of sawdust as admixture in production of low-cost and lightweight hollow sandcrete blocks. Am J Sci Indus Res 3(6):458–463 15. Alsaad AJ, Radhi MS, Taher MJ (2019) Eco-friendly utilizing of iron filings in production reactive powder concrete. IOP Conf Ser Mater Sci Eng 518(2). https://doi.org/10.1088/1757899X/518/2/022051 16. Olawale OS, Kareem M, Muritala T, Adebanjo A, Alabi O, Olawuyi O, Fadipe O (2021) Utilization of iron Filings as partial replacement for sand in self compacting concrete. Tanzania J Sci 47(3):906–916 17. British Standards BS EN197-1 (2000) Cement. Composition, specifications and conformity criteria for common cements 18. Adekunle MA, Babatunde FO, Kunle EO, Gideon OB, Ayodeji OO, Patience FT (2018) Assessment of Sandcrete blocks manufacturers’ compliance to minimum standard requirements by standard organisation of Nigeria in southwest, Nigeria International. J Appl Eng Res 13(6):4162–4172 19. British Standards BS EN 933-2 Tests for geometrical properties of aggregates. Determination of particle size distribution. Test sieves, nominal size of apertures 20. American Society for Testing and Materials ASTM C127 (2015) Standard test method for density, relative density (specific gravity), and absorption. ASTM Standard Book
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21. Taha MR, El-Dieb AS, Shrive NG (2001) Sorptivity: a reliable measurement for surface absorption of masonry brick units. Mater Struct 34(7):438–445 22. British Standards EN 772-1:2011 (2011) Methods of test for masonry units. Determination of compressive strength (+A1:2015) 23. American Society for Testing and Materials ASTM C33/C33M-13 (2018) Standard specification for concrete aggregates. ASTM Standard Book 24. Navaratnarajah SW, Kandage KK (2015) The scale effect on small-scale modelling of cement block masonry. Mater Struct. https://doi.org/10.1617/s11527-015-0696 25. Nigerian Building and Road Research Institute (NBRRI) (2006) NBRRI interlocking blockmaking machine. NBRRI Newsl 1(1):15–17 26. Nigerian Industrial Standard (2000) Standard for Sandcrete blocks. The Nigerian Industrial Standard Blocks. Standard Organisation of Nigeria, Lagos. 27. Boob TN (2014) Performance of sawdust in low-cost Sandcrete blocks. Am J Eng Res 3(4):197– 206 28. Sathiparan N, De Zoysa HTS (2018) The effects of using agricultural waste as partial substitute for sand in cement blocks. J Build Eng 19:216–227. https://doi.org/10.1016/j.jobe.2018.04.023
Performance Evaluation of Activated Sugarcane Bagasse for Abattoir Wastewater Treatment Ibrahim Mohammed Lawal, Shamsul Rahman Mohamed Kutty, Dalhatu Saleh, Vicky Kumar, Priyanka Singh, Abdullahi Haruna Birniwa, Sule Abubakar, and Ahmad Hussaini Jagaba
Abstract Wastewater from abattoir is known to be highly contaminated, which may cause harm to the environment and health if not handled carefully; many treatment approaches have been used to treat this wastewater. However, most of the approaches have its constraints, such as being expensive, ineffective or requires special skills; therefore, the needs arise to develop an inexpensive, effective, and eco-friendly way of treating this wastewater especially in developing economy. Sugarcane bagasse has been proposed due to its availability, in expensiveness, biodegradability, and effectiveness in removing contaminants; in order to determine its effectiveness, different dosages of activated sugarcane bagasse (ASCB) (25, 30, 35, 40, 45, and 50 g/L) and reaction time of 24, 48, 72, 96, and 120 h were studied. The results of the experiment showed a pH increase from acidic to alkaline medium after 24 h through 96 h; the optimum dosage, reaction time, and percentage removal of COD, TDS, EC, and colour were determined to be (25 g/l, 24 h, 51.92%), (25 g/l, 24 h, 21.3%), (30 g/l, 120 h, 68.6%), and (50 g/l, 120 h, 83.54%), respectively. These findings showed a significant success on the usage of this adsorbent in the removal of contaminants in the wastewater with its effectiveness increasing by increasing its dosage; therefore, I. M. Lawal (B) · S. Abubakar · A. H. Jagaba Department of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi, Nigeria e-mail: [email protected] I. M. Lawal Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, UK S. R. M. Kutty · V. Kumar · A. H. Jagaba Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia D. Saleh Department of Civil Engineering, Faculty of Engineering Technology, Nigerian Army University, PMB 1500, Biu, Borno State, Nigeria P. Singh Department of Civil Engineering, Faculty, Amity University Uttar Pradesh, Noida, India A. H. Birniwa Department of Chemistry, Sule Lamido University, PMB 048, Kafin-Hausa, Nigeria © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. K. Shukla et al. (eds.), Recent Developments in Geotechnics and Structural Engineering, Lecture Notes in Civil Engineering 338, https://doi.org/10.1007/978-981-99-1886-7_42
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ASCB can be used in place of another adsorbent for treating abattoir wastewater, being it cheap and effective. Recommendation was made on the study of increasing the dosages of ASCB and keeping the reaction time constant. Keywords Sugarcane bagasse · Abattoir · Wastewater · Adsorption · Chemical oxygen demand
1 Introduction Large concentrations of whole blood from the dead animals as well as suspended food particles from the stomach and intestine of the slaughtered animals are features of abattoir wastewater [1]. The main contaminants are organic loads from poop, faeces, grease, fat, lard, undigested food, blood, suspended matter, soluble proteins, excrement, manure, and colloidal particles [2]. Slaughterhouses and Meat Processing Plants are a significant global sector, and the nature of the wastewater they produce relies on the various methods used throughout the slaughtering process. Abattoir wastewater hence needs considerable treatment for a safe and sustainable discharge to the environment [3]. Environmental pollution caused by abattoir operations is well known to be a serious threat to public health; these activities put the local community and the workers at risk for both communicable and non-communicable diseases [4]. When abattoir wastewater is discharged to receiving water bodies untreated, infectious diseases such as TB, colibacillosis, salmonellosis, brucellosis, and helminths are discovered to be passed to humans since they are difficult to eradicate [1]. Abattoir waste has been discovered to pollute groundwater and provide a severe odour that is upsetting to those who live nearby [5]. Abattoir wastewater has been treated using a variety of techniques to make it suitable for environmental discharge or reuse in agriculture. Rendering and composting were the previous approaches used; in the former, integrated waste was treated using heat to break down the contaminants into usable products, while in the latter, organic waste was composted in the presence of air to produce compost, a nutrient-rich product used in agriculture. However, due to strict regulations and the need for additional space, these methods are now rarely used [6]. Pre-treatments, primary, secondary, and tertiary treatments—the traditional technique of treating abattoir wastewater—were shown to be successful in eliminating the wastewater’s solids content as well as the biochemical oxygen demand (BOD) and chemical oxygen demand (COD). However, it costs a lot of money and required expert knowledge [7]. Additionally, membrane technology has demonstrated exceptional performance by providing high efficiency for the removal of pollution, the recovery of water, and the manufacture of valuable products; yet, the cost of the membrane and its fragility are concerns when using this technique [8]. Therefore, it becomes necessary to look into techniques for treating abattoir wastewater that will be efficient, environmentally friendly, and affordable.
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Agricultural by-products from farms and agro-industries must also be appropriately disposed of or used to create other products. Since many agricultural products are used to treat wastewater, the effects of disposing of both the by-products and the wastewater are minimized. The treatment of sewage sludge with the augmentation of biogas production has been done using waste products from the agro-industry, such as olive mill waste, cheese whey, and crude glycerol [9]. Similar to this, rice husk, a low-value agricultural by-product was employed as a sorbent to eliminate some notable heavy metals from the drain holding sewage and agricultural wastewater in the El-Menofiya Governorate, Egypt [10]. A COD removal of 72, 74, and 73% was recorded for coconut shell-activated carbon, coconut shell fibre, and rice husk activated carbon, respectively. These inexpensive activated carbons were used for the remediation of various pollutants, including chemical oxygen demand (COD), heavy metals, anions, etc., from industrial wastewater [11]. Numerous studies on the use of agricultural by-products to remediate wastewater have been conducted in a manner similar to the ones indicated above. Sugarcane bagasse or popularly called “Bagasse” is one of the major agricultural waste products in the world (Fig. 1). It is the fibrous residue left over after sugarcane is crushed and its juice is extracted [12]. Bagasse has a wide range of applications in the fabrication of composite materials to enhance the performance of the parent materials because of their chemical composition and natural biodegradability [12]. Because of its widespread availability and potential to serve as an excellent substrate for microbial processes to produce value-added products, numerous attempts have been made to produce from bagasse substrate protein-enriched animal feed, enzymes, amino acids, organic acids, and substances with medicinal significance [13]. Sugarcane bagasse’s primary components, according to an analysis, are lignin, cellulose, hemicellulose, ash, and wax [14]. Due to its composition, it can be utilized as reinforcement, which enhances the materials’ mechanical qualities [12]. Due to its high biodegradability and solid-state fermentation, sugarcane bagasse has been used as an absorbent in treating wastewater. An inexpensive adsorbent with a surface area of 806.57 m2 /g is rich in organic functional groups and highly effective Fig. 1 Sugarcane bagasse waste
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at removing lead. Pb2+ has been created by combining sugarcane bagasse with sewage sludge [15]. Sugarcane bagasse was also used to create a powerful anion-exchange resin that decolourizes dye house effluent successfully, affordably, and safely [16]. Reactive dye that has been hydrolysed and with high affinity is bound to the resin made from bagasse [16]. Sugarcane bagasse and Sylhet sand were used in laboratory-scale artificial wetlands to treat wastewater from the textile industry. The results indicated stable removal performances for BOD and ammonia, which were 79 and 66%, respectively [17]. Bagasse has a very high polysaccharide content that, when combined with hemicellulose and lignin, can operate as an aggressive coagulant agent, removing suspended particles up to 95.9% of the time under ideal circumstances [18]. Through the development of mathematical models, the dosage of activated carbon made from sugarcane bagasse, pH, and reaction time was used as independent variables to determine the best BOD and COD removal. The best activated carbon dosage was found to be 0.915 g/L, pH 3.225, and a reaction time of 98.91 min for the highest BOD and COD removal efficiencies of 0.0225 and 0.023 mg/L min1, respectively [19]. Similar outcomes were achieved when COD, alkalinity, oil, and grease were removed from car wash wastewater using activated carbon generated from sugarcane bagasse, with respective removal success rates of 52.08, 59.09, and 40.64% [20]. Sugarcane bagasse is also used to lower the conductivity and total dissolved solids (TDS) of wastewater. In a study, it was feasible to lower conductivity and total dissolved solids by removing calcium ions from an aqueous solution using sugar cane bagasse that had been treated with carboxylic acids (TDS) [21]. Methylene blue (MB), the common dye, used in industries has been found to be effectively removed through the usage of chemically modified sugarcane bagasse, in an alkaline environment [22]. The use of sugarcane bagasse as a biosorbent in the treatment of textile wastewater contaminated with cancer-causing Congo red dye was discovered to cause the pH of the wastewater to rise from 4 to 10, and the highest adsorption occurred at 10, demonstrating that the best adsorption occurs in an alkaline medium [23]. It is clear from the foregoing that sugarcane bagasse can treat different streams of wastewater due to its biodegradability and chemical components, and it has been found to be efficient and reasonably priced due to its widespread availability. It will therefore be important to investigate how it can be used to treat wastewater from abattoirs, looking at its effect on COD, TDS, electrical conductivity, and changes in pH.
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2 Materials 2.1 Adsorbent Collection The sugarcane bagasse used was collected at the sugarcane market in Fadama, Bauchi State Nigeria, washed with a sufficient amount of water to remove mud and other impurities and was finally air dried.
2.2 Wastewater Collection Wastewater sample was collected as per standard method under the standard condition from Bauchi state meat factory, Bauchi State Nigeria. A preliminary test of the wastewater was then carried out by sieving to remove undigested foods (grasses), loose meat, grit and colloidal particles, hair, animal faeces, and suspended materials in the water after which the wastewater was then allowed to settle in a basin for sedimentation.
2.3 Sulphuric Acid 0.5% sulphuric acid, diluted with distilled water, was used in washing the sugarcane bagasse as a preparatory stage for the activation in other to remove microorganisms and other contaminants which may alter the expected result.
2.4 Distilled Water Distilled water was used throughout the research process when determining the COD content in the slaughterhouse wastewater, due to the dark colouration (oxblood), the amount of potassium permanganate consumption was high, and this will give an ineffective result. Therefore, 5% of the wastewater sample was complemented with 95% distilled water to make it up to 100% and a total of 100 ml. Distilled water was used in rinsing the pH meter in order to avoid errors.
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3 Experimental Methods 3.1 Adsorbent Development The material was treated by soaking it in 0.5% sulfuric acid for around 1000 g, and it was then dried for 24 h in an oven. The dried treated sugarcane bagasse was then subjected to thermal activation by being incinerated at a temperature of approximately 400 °C for one hour after the carbonized material had been rinsed with water to remove the free acid and dried at 105–110 °C for 24 h. After incineration, the product was then ground into tiny particles and sieved through a size 402-µm standard BS sieve. Finally, the prepared activated carbon from the sugarcane bagasse was stored in an airtight container until required.
3.2 pH/TDS/EC, Determination The pH, TDS, and EC were determined using the pH/EC/TDS meter MODEL HI 9813-5.
3.3 Batch Adsorption Study For the purpose of gathering the equilibrium data necessary for the design and operation of the wastewater/effluent treatment process, batch sorption studies were carried out in a temperature range of (24–27 °C). We used a number of 1 L containers for our equilibrium studies. The effluent was poured into each container. A known amount of adsorbent (25, 30, 35, 40, 45, and 500 g) was added into each container with the exception of one known as the blank solution/sample or control (effluent sample without adsorbents) with all well labelled. The containers were covered and stirred sporadically for the necessary lengths of time, which were 24, 48, 72, 96, and 120 h. On the basis of early studies, the contact time and other variables (such as the dosage of the adsorbent) were chosen. Filtration was used to separate the supernatant, and the target parameters were examined for each of the planned time periods.
3.4 Chemical Oxygen Demand (COD) Determination Using potassium permanganate as the oxidizing agent, the COD was determined using the titration method, the measurement was done as quickly as feasible
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after sample collection, and the glass boiling equipment was kept in a dust-free environment. The first stage is to determine the titration factor ( f ) of KMnO4 solution as follows: 1. 100 ml distilled water was heated after adding anti-bump granules and 5 ml sulfuric acid. 2. KMnO4 solution was added until weakly pink colour appears. 3. 20 ml oxalic acid was added from a pipette and then titrated again with KMnO4 until weakly pink. The KMnO4 consumption was noted. The factor( f ) = 20/x
(1)
The next stage was carried out with the sample as follows: 1. 100 ml of the sample was taken in an Erlenmeyer flask; 5 ml sulfuric acid added and was boiled for 5 min with cover. 2. While boiling, 20 ml of KMnO4 was added from a pipette. 3. The solution was then allowed to simmer for 10 min. 4. 20 ml oxalic acid was then added, and the mixture was heated until the colour completely disappears. A blank with 100 ml of dilution water is measured in parallel. COD (mg/L) =
(a − b) ∗ f ∗ 316 mg , V
(2)
where a = KMnO4 consumption by sample (ml) b = KMnO4 consumption by sample blank (ml) f = titration factor of the KMnO4 solution.
4 Results and Discussion 4.1 Result The results of the study (Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10) showed the effect of dosing activated sugarcane bagasse (ASCB) and reaction time in the removal of pollutants in the abattoir wastewater on TDS, COD, EC, and colour removal.
pH Value
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10 9.5 9 8.5 8 7.5 7 6.5 6 5.5 5
0g/L 25g/L 30g/L 35g/L 40g/L 45g/l 50g/l 24H
48H
72H Time (hr)
96H
120H
Fig. 2 Effect of pH on the adsorption of ASCB
EC (S/m)
2400
0g/L 25g/L
1900
30g/L 1400
35g/L 40g/L
900
45g/L
400 24H
48H
72H Time (hr)
96H
120H
50g/L
EC % removed
Fig. 3 Electrical conductivity against time
80 70 60 50 40 30 20 10 0
25g/l 30g/l 35g/l 40g/l 45g/l 50g/l 24H
48H
72H Time (hr)
96H
Fig. 4 Percentage removal of electrical conductivity against time
120H
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1200
TDS (ppm)
1000 0g/L
800
25g/L
600
30g/L
400
35g/L 50g/L
200 0 24H
48H
72H Time (hr)
96H
120H
TDS % removed
Fig. 5 Total dissolved solids concentration against time
50 45 40 35 30 25 20 15 10 5 0
25g/l 30g/l 35g/l 40g/l 45g/l 50g/l 24H
48H
72H
96H
120H
TIME (hr) Fig. 6 TDS % reduction against time
Colour (mg/l)
40000 35000
0g/l
30000
25g/l
25000
30g/l
20000
35g/l
15000
40g/l
10000
45g/l
5000
50g/l
0 24H
48H
72H
Time (hr) Fig. 7 Colour against time
96H
120H
Colour % removed
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90 80 70 60 50 40 30 20 10 0
25g/l 30g/l 35g/l 40g/l 45g/l 50g/l 24H
48H
72H
96H
120H
Time (hr) Fig. 8 Percentage reduction of colour against time
COD (mg/l)
7000 6000
0g/L
5000
25g/l
4000
30g/l
3000
35g/l
2000
40g/l
1000
45g/l 50g/l
0 24H
48H
72H
96H
120H
Time (hr) Fig. 9 COD concentration against time
COD % removed
60 50
25g/L
40
30g/L 35g/L
30
40g/L
20
45g/L
10
50g/L
0 24H
48H
72H
Time (hr) Fig. 10 Percentage reduction of COD
96H
120H
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4.2 Discussion The dynamics of the contaminants concentrations in the wastewater shown in Figs. 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10 indicate that the dosage and response time of ASCB have an impact on the physicochemical characteristics of the wastewater from the abattoir in a way that lowers their concentrations, hence lowering the organic loading of the wastewater by treating the wastewater. As seen in Fig. 2, the pH of the wastewater has increased due to the addition of ASCB from an acidic medium after 24 h to an alkaline environment during the 96 h with different dosages of ASCB, a sign that the ideal environment for the adsorption, as mentioned previously, will make the ASCB adsorption effective. When ASCB was added, it was seen that the electrical conductivity of the wastewater decreased (Fig. 3), with the best dosage and reaction time being 30 g/L of ASCB and 120 h, respectively, representing a 68.6% drop in electrical conductivity (Fig. 4). The ideal ASCB dosage and reaction time that produced the 43.3% reduction in TDS shown in Fig. 6 are 25 g/L and 24 h, respectively (Fig. 5). This demonstrates that the effect of ASCB in the reduction of TDS is immediate, and any further results obtained after 24 h may be incorrect due to bacterial activity in the wastewater stream. As seen in Fig. 7 above, the optimum dosage of ASCB that corresponded to the maximum reduction of colour is 50 g/L with a reaction time of 120 h, and the percentage reduction in colour as seen in Fig. 8 above is 83.54%. Chemical oxygen demand (COD) of the wastewater was seen to reduce after the addition of the adsorbent, with the optimum dosage and reaction time of 25 g/L and 24 h, respectively (Fig. 9), which corresponds to 51.92% reduction as seen in Fig. 10.
5 Conclusion According to the experimental findings, the adsorbent was able to display performance characteristics similar to those of commercial activated carbon. Low-cost adsorbents may be a potential solution to the removal of pollutants and other compounds from abattoir wastewater since the percentage removal of the various parameters examined increases with an increase in the mass of the adsorbent dosage. Accordingly, ASCB possesses comparable physicochemical characteristics that, based on the percentage of removal, are crucial for adsorption performance and can be used to effectively treat industrial wastewater. Therefore, it is recommended that additional adsorbent doses be used in future studies to boost adsorption capacity because doing so increases the adsorbent’s performance efficiency while maintaining a consistent reaction time.
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