Recent Trends in Transportation Infrastructure, Volume 1: Select Proceedings of TIPCE 2022 (Lecture Notes in Civil Engineering, 354) 981993141X, 9789819931415
This book presents the select proceedings of the 2nd International Conference on Transportation Infrastructure Projects:
145 83 13MB
English Pages 440 [417] Year 2023
Contents
About the Editors
Transportation Infrastructure: Materials and Construction
Impact of Mechanized Cold Mix Construction Method for Hilly Region Roads
1 Introduction
2 Location and Pre-construction Condition Assessment
3 Characterization of Material and Mixture Design at Laboratory
4 Test Section Construction
5 Discussion
6 Conclusion
References
Evaluation of the Effect of the Production Process in Quality Parameters of Polymer Modified Performance Grade Binders: A Case Study
1 Introduction
2 Material Characteristics
3 Production Methodology of PMB
3.1 Production Unit 1
3.2 Production Unit 2
4 Laboratory Setup
5 Results and Discussions
5.1 Softening Point
5.2 Rotational Viscosity by Brookfield Viscometer
5.3 Elastic Recovery
5.4 MSCR—Jnr Difference
5.5 MSCR—Jnr at 3.2 kPa.
6 Conclusion
References
Effect of Superplasticizer on Characteristics of Pervious Concrete
1 Introduction
2 Materials
2.1 Cement
2.2 Aggregates
2.3 Superplasticizer
3 Methodology and Sample Preparation
3.1 Methodology
3.2 Sample Preparation
4 Test Methods
4.1 Slump Test
4.2 Flexural Strength Test
4.3 Flexural Toughness Test
5 Results and Discussion
5.1 Slump
5.2 Density
5.3 Flexural Strength
5.4 Fracture Toughness
6 Conclusion
References
Analysis of Internal Pore Structure of Porous Asphalt Concrete Using X-ray Computed Tomography Images
1 Introduction
2 Test Procedure
3 Result and Discussion
3.1 Porosity
3.2 Void Size
3.3 Euler Characteristics
3.4 Percolation Number
3.5 Tortuosity
3.6 Number of Voids
4 Conclusion
References
Utilization of Recycled Concrete Dust and Lime as a Binary Blended Filler in Cold Bitumen Emulsion Mix
1 Introduction
2 Materials
3 Experimental Programs
3.1 Mix Design and Specimen Preparation
4 Results and Discussions
4.1 Mix Design of CBEM
4.2 Optimization of RCD Filler in CBEM
4.3 Marshal Stability and Marshal Quotient (MQ)
4.4 Indirect Tensile Strength (ITS) and Indirect Tensile Strength Ratio (ITSR)
5 Conclusions
References
Development of Shakedown Criteria for Prediction of Permanent Deformation Characteristics of Modified UGMs with THF Steel Slag
1 Introduction
2 Materials and Experimental Investigations
2.1 Materials
2.2 Laboratory Investigations
3 Experimental Results
4 Proposed Shakedown Criteria
5 Results and Discussions
5.1 Effect of Moisture Variation on Permanent Deformation of UGMs
5.2 Effect of Stress Variation on Permanent Deformation of UGMs
6 Conclusion
References
Industrial and Agro-Based Wastes as Alternative Binders in Roller Compacted Concrete Pavements: A Comprehensive Review
1 Introduction
2 Fresh Properties
2.1 Optimum Moisture Content
2.2 Maximum Dry Density
2.3 Vebe Time
3 Mechanical Properties
3.1 Compressive Strength
3.2 Flexural Strength
3.3 Split Tensile Strength
4 Durability Properties
4.1 Water absorption
4.2 Water Permeability
4.3 Freeze–Thaw (F-T)
5 Summary and Conclusions
References
Utilization of Industrial and Agricultural Wastes to Enhance the Properties of Concrete–A Review
1 Introduction
2 Waste Classification
2.1 Industrial Wastes
2.2 Agricultural Wastes
3 Conclusions
References
Study on Utilizing Reclaimed Asphalt Pavement in Bituminous Concrete Wearing Course with PMB 70-10 V as Binder Using Hot In-Plant Recycling Process
1 Introduction
2 Materials and Recycling Method
3 Methodology
3.1 Mix Design
4 Results and Discussion
5 Pilot Project and Challenges Faced
5.1 Pavement Condition of Pilot Project
6 Conclusions
References
Successful Utilization of High Amount of Reclaimed Asphalt Pavement Material in Bituminous Pavements: Indian Case Study
1 Introduction
1.1 General
1.2 Objective and Scope
2 Field Investigation
2.1 Background
3 Laboratory Investigation
3.1 Physical Properties of RAP and Fresh Binders
3.2 Binder Extraction
3.3 Blending Process of RAP and Aggregates
3.4 Mix Design Procedure
3.5 Rejuvenator
3.6 Mix Preparation
4 Results
4.1 Marshall Test Results
4.2 Moisture Resistance of RAP-Modified Mixes
4.3 Recommended Job Mix Formula
5 Observations and Recommendations
References
Suitability of Rejuvenator Addition Method for Hot Mix Asphalt Recycling
1 Introduction
2 Objective
3 Materials and Methods
4 Results and Discussion
4.1 Comparison of Volumetric Properties Between Rej RAP and SB Method
4.2 Comparison of Asphalt Mix Properties Between Rejuvenated RAP and Soft Blend Method
4.3 Statistical Analysis of Results
5 Summary and Conclusion
References
Assessment of Optimum Rejuvenator Dosage for Maximizing the Use of Reclaimed Asphalt Pavement (RAP) in Hot Mix Recycling
1 Introduction
2 Objective of the Study
3 Materials Used
4 Experimental Details
5 Results and Discussion
5.1 Effect of Rejuvenator on Physical Properties
5.2 Effect of Rejuvenator on Rheological Properties
5.3 Optimum Rejuvenator Dosage
5.4 Validation of Optimum Rejuvenator Dosage
6 Conclusions
References
Study on Estimation of Optimum Dosage of Warm Mix Additives for Production of Asphalt Mixtures
1 Introduction and Background
2 Material Selection
3 Experimental Setup
4 Results
4.1 Discussion on Production Temperatures
4.2 Discussion on Coating Ability
4.3 Discussion on Compactability
4.4 Selection of Optimum WMA Additive Dosage
5 Conclusions
References
The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt Binder
1 Introduction
1.1 Research Significance
2 Material and Methods
2.1 Materials
2.2 Methods
2.3 Asphaltene Extraction
2.4 Formulation of Aging Indices (AI)
3 Results and Discussion
3.1 Rheological Test Results
4 Conclusions
References
Application of FDR Technology for Upgradation of a National Highway
1 Introduction
1.1 Appraisal of the Project Road
2 NH 4 Rehabilitation Program
2.1 Laboratory Evaluation
2.2 Construction
3 Field Validation
4 Conclusion
References
Investigating Mechanical and Hydraulic Properties of Porous Concrete Pavements
1 Introduction and Background
2 Materials and Methods
2.1 Materials Used
2.2 Methodology
2.3 Mix Design
3 Results and Discussions
3.1 Total Void Ratio
3.2 Density
3.3 Compressive Strength
4 Conclusions
References
Development of High Friction Bituminous Surface Course for Aircraft Movement
1 Introduction
1.1 Background
1.2 Objectives and Scope of the Study
2 Field Investigations
2.1 Background
2.2 Measurement of Friction on Trial Section
3 Laboratory Investigations
3.1 General
3.2 Marshall Mix Design
3.3 Moisture Resistance
4 General and Specific Recommendations
5 Limitation and Future Scope
References
Sustainability of Asphalt Rubber-Gap Pavements: A Comparative Environmental Impact Analysis
1 Introduction
2 Literature Review
3 GHG Emission Determination
4 Pavement Design: IRC 37:2018
5 Life Cycle Assessment
6 Conclusions and Future Scope
References
Design and Analysis of Flexible Pavement Using Brick Aggregate Using Finite Element Method
1 Introduction
2 Study Objective
3 Analysis of Experimental Results
3.1 Vinyl Acrylic Copolymer
3.2 Soil
3.3 Overburnt Brick Aggregate
3.4 Modified Proctor Test
3.5 California Bearing Ratio and Resilient Modulus
4 Features of Finite Element Model
4.1 Material Characterization
4.2 Element Types and Mesh Size
4.3 Techniques for Modeling Interactions
4.4 Boundary Conditions
4.5 Loading Condition
5 Results
6 Conclusions
References
Utilization of Lime Stabilized Pond Ash and Sand Mix Using Nanomaterials for the Subbase Course of Industrial Pavements
1 Introduction
2 Literature Review
3 Materials
3.1 Pond Ash
3.2 Sand
3.3 Lime
3.4 Nanomaterial
4 Experimental Studies
5 Result and Discussions
5.1 Compaction Behaviour and CBR Values
5.2 Triaxial Strength Test
5.3 Unconfined Compressive Strength Test and Hydraulic Conductivity
5.4 Slake Durability Test
5.5 Light Falling Weight Deflectometer Test
5.6 Final Analysis and Foundation Design
6 Conclusions
References
Investigation and Rehabilitation of Bituminous Pavement Using Sustainable Construction Technique: A Case Study
1 Introduction
2 Study Objective and Scope
3 Field Investigation and Laboratory Analysis
3.1 Test Pit and Core Extraction
3.2 Traffic Count
3.3 BBD Analysis
3.4 Laboratory Investigation of Extracted Material
4 Result and Discussion
4.1 Pavement Condition Assessment
4.2 Overlay Design
4.3 Design of Pavement for Reconstruction
5 Conclusion
References
Field Evaluation of Thin Bituminous Surface Mixes
1 Introduction
2 Material Specification and Physical Properties
3 Laboratory Evaluation of Density, ITS, and TSR
4 Construction of Test Sections
5 Field Evaluation of Test Sections
5.1 Progression of Permeability
5.2 Progression of Texture Depth
5.3 Progression of Roughness
5.4 Progression of Rebound Deflection
6 Performance Prediction of Test Section
6.1 Evaluation of Effective Pavement Modulus
6.2 Evaluation of Effective Structural Number
6.3 Evaluation of Predicted Pavement Life
7 Comparison of Performance and Construction Cost
8 Conclusion
References
Lessons Learnt from a Premature Failure of Stone Matrix Asphalt (SMA) on a High-Volume Indian Highway
1 Introduction
2 Project Description and Visual Condition
3 Detailed Investigation Plan
3.1 Laboratory Testing of Field Samples
3.2 Additional Laboratory Studies
4 Test Results
4.1 Findings from Desktop Study
4.2 Results of Field Samples
4.3 Effect of Mineral Fillers Properties on SMA mixes
5 Findings
6 Recommendations
References
Effect of Nominal Maximum Aggregate Size and Bitumen Content on Frictional Properties of Different Bituminous Surface Courses
1 Introduction
2 Materials Selection
2.1 Aggregate
2.2 Bitumen
3 Methodology
3.1 Evaluation of Frictional Characteristics
4 Results and Discussion
4.1 Frictional Performance Under Surface-Dry Condition
4.2 Frictional Performance Under Varying Water Depth
5 Conclusions
References
Dynamic Complex Modulus and Rutting Characteristics of Reclaimed Asphalt Pavement (RAP) Mixes
1 Introduction
1.1 Background and Objectives
2 Witczak E Predictive Equation Model
3 Simulation Using KENLAYER
4 Materials
4.1 Reclaimed Material
4.2 Virgin Aggregates and Bitumen
5 Methodology
6 Results and Discussions
6.1 Dynamic Properties of RAP-HMA Mixes
6.2 Performance of RAP-HMA Mixes Using KENLAYER Simulations
6.3 Performance of RAP-HMA Mixes
7 Conclusion
References
SMART and Intelligent Transportation
Geometry Data Extraction of Existing Horizontal Alignment: A Global Review Report and Methodological Example
1 Introduction
2 Literature Review
2.1 GPS
2.2 GIS Maps
2.3 AutoCAD Digital Map
2.4 Satellite Imagery
2.5 Vision Technology
2.6 LiDAR
2.7 IMU
3 Methodology Based on GIS and AutoCAD Civil 3D ©
3.1 Validation
4 Results and Discussion
5 Conclusion
References
Development of Incident Management System for Efficient Usage of Transportation Infrastructure
1 Introduction
2 Literature Review
2.1 Ant Colony Optimization Algorithms
2.2 Blackboard Architecture
2.3 Incident Management
3 Study Area and Data Collection
4 Methodology
4.1 Start of Ant Algorithm
4.2 Ant’s Route Generation
4.3 Link Pheromone Intensity Updating
4.4 Setting Value of Global Minimum Route Length
4.5 Check for End Conditions
5 Results and Demonstration of the Program Developed
6 Conclusions
Annexure-Survey Questionnaire
References
Connected Autonomous Vehicles (CAV) Testbed at IIT Hyderabad
1 Introduction
2 Review of Existing Testbeds
3 IIT Hyderabad CAV Testbed Facility
3.1 Testbed Features for Connected and Autonomous Vehicles
3.2 Facilities for Drones and UAVs
3.3 Other Facilities
3.4 Use Case Scenarios
4 Challenges Encountered During Testbed Development
5 Conclusion
References
Community and Social Well-Being and Safety
Measuring Impacts of Delhi-Meerut Expressway on Land Cover and Land Use
1 Introduction
2 Study Area
3 Study Approach
3.1 Preliminary Analysis
3.2 Spatial Analysis
4 Data Collection and Database
5 Data Analysis and Results
6 Conclusion
References
Comparison of Vehicular Emissions from BS-III and BS-VI Motorized Two-Wheelers
1 Introduction
2 Methodology
3 Result and Discussion
4 Conclusion
References
Road Safety Inspection of NH-205A: A Case Study
1 Introduction
2 Study Area
3 Methodology
3.1 Collection of Accident Data
3.2 Traffic Surveys on the Study Stretch
4 Results and Discussions
5 Recommendations
References
Analysis and Prediction of Hit-and-Run Road Accidents
1 Introduction
2 Literature Review
3 Study Area and Objective
4 Methodology
5 Statistical Analysis
5.1 Descriptive Analysis
5.2 Chi-Square Test
5.3 Binomial Logistic Regression Model
6 Findings and Conclusion
References
Study of Single-Vehicle Traffic Crashes
1 Introduction
2 Literature Review
3 Data Description and Study Area
3.1 Study Area and Scope
3.2 Data Collection and Analysis
3.3 Crash Data
4 Method
4.1 Model Development
5 Result and Discussion
5.1 Impact of Number of Lanes
5.2 Impact of Road Segment Length
5.3 Impact of Traffic Flow
5.4 Impact of Access Density
References
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Lecture Notes in Civil Engineering
Rajat Rastogi G. Bharath Dharamveer Singh Editors
Recent Trends in Transportation Infrastructure, Volume 1 Select Proceedings of TIPCE 2022
Lecture Notes in Civil Engineering Volume 354
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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Rajat Rastogi · G. Bharath · Dharamveer Singh Editors
Recent Trends in Transportation Infrastructure, Volume 1 Select Proceedings of TIPCE 2022
Editors Rajat Rastogi Department of Civil Engineering Indian Institute of Technology Roorkee Roorkee, Uttarakhand, India
G. Bharath CSIR-Central Road Research Institute New Delhi, India
Dharamveer Singh Department of Civil Engineering Indian Institute of Technology Bombay Mumbai, Maharashtra, India
ISSN 2366-2557 ISSN 2366-2565 (electronic) Lecture Notes in Civil Engineering ISBN 978-981-99-3141-5 ISBN 978-981-99-3142-2 (eBook) https://doi.org/10.1007/978-981-99-3142-2 © 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
Transportation Infrastructure: Materials and Construction Impact of Mechanized Cold Mix Construction Method for Hilly Region Roads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nipun Beniwal, Siksha Swaroopa Kar, G. Bharath, Amit Kumar, Krishan Saini, and M. N. Nagabhushana Evaluation of the Effect of the Production Process in Quality Parameters of Polymer Modified Performance Grade Binders: A Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arivuselvan Thillaivendhan, Vipul Jain, Arpan Ghosh, Kamlesh Gupta, R. Lakshmi Narayanan, and Amarjeet Tiwari Effect of Superplasticizer on Characteristics of Pervious Concrete . . . . . Shuddhashil Ghosh and Priyansh Singh
3
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Analysis of Internal Pore Structure of Porous Asphalt Concrete Using X-ray Computed Tomography Images . . . . . . . . . . . . . . . . . . . . . . . . . A. Jegan Bharath Kumar, R. Ganeshvijay, P. Murshida, and R. Rajasekar
39
Utilization of Recycled Concrete Dust and Lime as a Binary Blended Filler in Cold Bitumen Emulsion Mix . . . . . . . . . . . . . . . . . . . . . . . Deepak Prasad, Sanjeev Kumar Suman, and Bhupendra Singh
51
Development of Shakedown Criteria for Prediction of Permanent Deformation Characteristics of Modified UGMs with THF Steel Slag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashish Mishra and Sunny Deol Guzzarlapudi Industrial and Agro-Based Wastes as Alternative Binders in Roller Compacted Concrete Pavements: A Comprehensive Review . . . . . . . . . . . M. Selvam, Solomon Debbarma, and Surender Singh
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Contents
Utilization of Industrial and Agricultural Wastes to Enhance the Properties of Concrete–A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sameer Malhotra, Abhishek Kanoungo, and Ajay Goyal
91
Study on Utilizing Reclaimed Asphalt Pavement in Bituminous Concrete Wearing Course with PMB 70-10 V as Binder Using Hot In-Plant Recycling Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Niranjan Geddada, Arpan Ghosh, and Kamlesh Gupta Successful Utilization of High Amount of Reclaimed Asphalt Pavement Material in Bituminous Pavements: Indian Case Study . . . . . . 115 G. Bharath, Ambika Behl, Siksha Kar, and Satish Chandra Suitability of Rejuvenator Addition Method for Hot Mix Asphalt Recycling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Ankit Sharma, Gondaimei Ransinchung Rongmei Naga, and Praveen Kumar Assessment of Optimum Rejuvenator Dosage for Maximizing the Use of Reclaimed Asphalt Pavement (RAP) in Hot Mix Recycling . . . 137 Prakhar Aeron, Praveen Aggarwal, and Nikhil Saboo Study on Estimation of Optimum Dosage of Warm Mix Additives for Production of Asphalt Mixtures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Mayank Sukhija, Nikhil Saboo, and Agnivesh Pani The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt Binder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Dabbiru Sairam, Shobhit Jain, Anush K. Chandrappa, and Umesh C. Sahoo Application of FDR Technology for Upgradation of a National Highway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Ambika Behl, G. Bharath, and Amit Kumar Investigating Mechanical and Hydraulic Properties of Porous Concrete Pavements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Deepti Avirneni, Abhishek Kumar Bondada Ch., and Semanth Reddy Bommu Development of High Friction Bituminous Surface Course for Aircraft Movement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Manoj Shukla, G. Bharath, and Satish Chandra Sustainability of Asphalt Rubber-Gap Pavements: A Comparative Environmental Impact Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Karunakar Koyyuru, K. M. Arun Sagar, and Veena Venudharan
Contents
vii
Design and Analysis of Flexible Pavement Using Brick Aggregate Using Finite Element Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Ashish Kumar Singh, Khumber Debarma, and Partha Pratim Sarkar Utilization of Lime Stabilized Pond Ash and Sand Mix Using Nanomaterials for the Subbase Course of Industrial Pavements . . . . . . . . 243 Abhishek Roy, Aditya Shankar Ghosh, and Tapas Kumar Roy Investigation and Rehabilitation of Bituminous Pavement Using Sustainable Construction Technique: A Case Study . . . . . . . . . . . . . . . . . . . 259 Manoj Kumar Shukla, Sikseha Swaroopa Kar, Satish Pandey, and Shankh Das Field Evaluation of Thin Bituminous Surface Mixes . . . . . . . . . . . . . . . . . . 269 Jithin Kurian Andrews, Vishnu Radhakrishnan, and Reebu Zachariah Koshy Lessons Learnt from a Premature Failure of Stone Matrix Asphalt (SMA) on a High-Volume Indian Highway . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 Purbayan Ghosh Mondal, Anil Kumar Baditha, Dharamdas Ahriwar, Rajib Chattaraj, and Kranthi Kumar Kuna Effect of Nominal Maximum Aggregate Size and Bitumen Content on Frictional Properties of Different Bituminous Surface Courses . . . . . . 295 Rajan Choudhary, Rajneesh Kumar, Ankush Kumar, Santanu Pathak, and Abhinay Kumar Dynamic Complex Modulus and Rutting Characteristics of Reclaimed Asphalt Pavement (RAP) Mixes . . . . . . . . . . . . . . . . . . . . . . . . 311 U. Salini and Soorya Ann Koshy SMART and Intelligent Transportation Geometry Data Extraction of Existing Horizontal Alignment: A Global Review Report and Methodological Example . . . . . . . . . . . . . . . . 325 Mohd Atif and Gourab Sil Development of Incident Management System for Efficient Usage of Transportation Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 Gurmesh Sihag, Praveen Kumar, and Manoranjan Parida Connected Autonomous Vehicles (CAV) Testbed at IIT Hyderabad . . . . . 353 Digvijay S. Pawar, Ankit Singh, and Rajalakshmi Pachamuthu Community and Social Well-Being and Safety Measuring Impacts of Delhi-Meerut Expressway on Land Cover and Land Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369 Aayush Keshri, Aditya Manish Pitale, and Shubhajit Sadhukhan
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Contents
Comparison of Vehicular Emissions from BS-III and BS-VI Motorized Two-Wheelers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Ankit Kumar Singh and Abhisek Mudgal Road Safety Inspection of NH-205A: A Case Study . . . . . . . . . . . . . . . . . . . 393 Ankur Sharma, Har Amrit Singh Sandhu, Sovina Sood, and Rajan Dabral Analysis and Prediction of Hit-and-Run Road Accidents . . . . . . . . . . . . . . 407 Divya Solanki and Pankaj Prajapati Study of Single-Vehicle Traffic Crashes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421 Janak R. Suthar and Pankaj Prajapati
About the Editors
Dr. Rajat Rastogi is currently a Professor at the Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee. He obtained his Ph.D. from the Indian Institute of Technology Bombay, Mumbai, in 2002. His major area of research interests includes transport policy analysis, road safety, travel behavior modeling, sustainable transport planning, integration of transportation modes, etc. Dr. G. Bharath is currently a Senior Scientist from CSIR-Central Road Research Institute, New Delhi. He obtained his Ph.D. from the Indian Institute of Technology Kharagpur, Kharagpur, in 2016. His major interest areas are pavement material characterization, analysis and design of flexible & rigid pavements, sustainable road construction technologies and pavement failure investigations. Dr. Dharamveer Singh is currently an Associate Professor at the Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai. He obtained his Ph.D. from the University of Oklahoma, Norman, USA, in 2011. His major interest areas are Asphalt mix design and performance evaluation, design of cement concrete and bituminous pavement, design of innovative pavements, performance and quality of concrete roads, recycled asphalt mixes—design and performance, rheological evaluation of bitumen and additives, stabilization, and cold recycling, Superpave binder characterization, etc.
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Transportation Infrastructure: Materials and Construction
Impact of Mechanized Cold Mix Construction Method for Hilly Region Roads Nipun Beniwal, Siksha Swaroopa Kar, G. Bharath, Amit Kumar, Krishan Saini, and M. N. Nagabhushana
Abstract India’s mountainous and hilly regions have limited road connectivity, which severely impedes economic growth. For Himalayan border nations to meet their strategic goals, a robust and durable road network is crucial. However, environmentally fragile hilly regions might not be suitable for typical road construction techniques like hot mix asphalt. The narrow and tough site location creates difficulties in the transportation of materials and construction equipment. Also, space is not available for hot mix plants set up in hilly regions. Construction of hilly roads is generally conducted using a manual method, which leads to poor construction quality. To alleviate the issue, a machine is fabricated which can be used for cold mix production and laying. In the present paper, the effectiveness of the machine is evaluated through actual field trial conditions. Results show that the variability of the bituminous mix is reduced by using the mechanized method compared to manual methods. Keywords Mechanized laying · Cold mix · Bitumen emulsion
1 Introduction More than 48 million people reside in hilly areas and depend on the Indian Himalayan Region (IHR) for their food and energy [1, 2]. Along with this, nearly 1.2 billion people depend on its downstream river basins for the production of food and energy [1, 2]. Due to extremely challenging terrain, extreme weather conditions and events, dispersed habitations, underdeveloped infrastructure, etc., the IHR has been dealing with a number of issues for its development [2]. In addition, the northeastern states N. Beniwal · S. S. Kar (B) · G. Bharath · A. Kumar · K. Saini · M. N. Nagabhushana CSIR-Central Road Research Institute, Mathura Road, New Delhi 110025, India e-mail: [email protected] G. Bharath e-mail: [email protected]
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_1
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N. Beniwal et al.
of IHR have inadequate connectivity, both with the rest of India and among their individual states. As a result, the cost of delivering public services in the Himalayas is significantly higher than in other regions of the nation. This is mostly because of the terrain’s difficulty to access, the distances involved, and the remoteness of the area. Hence, an adequate and long-lasting road network is very much necessary in Himalayan areas for the overall development of the region as well as fulfilling defense needs. In places with considerable rainfall, building asphalt roads with ordinary paving grade bitumen is undesirable because seasonal rain affects mix production and laying [3]. At high altitudes or snow-bound areas as the temperature remains very low during most part of the year limiting the laying of hot mix. On the contrary, there is no need to heat the aggregate and bitumen by using bitumen emulsion as a binder for the paving of the bituminous top layer. Use of bitumen emulsion results in a reduction in emissions and also energy consumption. This technology will ease the construction and maintenance of existing road networks. In addition, transportation of material and construction equipment in hilly areas is a major issue, considering the site terrain at IHR. Hill sites in remote areas only offer a little amount of space for plant installation. The absence of large, traditional construction, and operating equipment is typically a major concern with high altitude sites. Hence, manual processes and techniques to construct roads in hilly areas are followed which leads to the poor construction quality and is time-consuming construction exercise [4, 5]. The performance of pavement depends majorly on construction methodology along with construction materials [4–7]. In general practice, a hot mix plant is used to produce bituminous cold mix using bitumen emulsion and then transported and paved using a construction paver [8, 9]. Bowers and Powell suggest the quality of emulsified mix produced from a hot mix plant shows better performance compared to the manual production of mix [10]. The literature says the emulsified mix has a complex behavior, the quantity of material dosages (emulsion, water, and cement) has a major impact on the performance of cold mix [8, 11]. In the Himalayan region, the desired speed of construction of the road is not achieved and the conventional mechanized method is inappropriate and capitalintensive [1, 2]. Plant setup for the construction of roads is difficult due to nonavailability of adequate places in hilly regions [3]. Hence, it is very much essential to develop cold bituminous mix technique and also a low-cost compact mixer and paver for construction. For mechanized laying of cold bituminous layer, the mixer and paver have been fabricated and the effectiveness of the fabricated machine has been analyzed in the present study.
2 Location and Pre-construction Condition Assessment A stretch of 1 km road from Jhimar to Bhitakot Motor Marg, Almora Uttarakhand in the Himalayan Region has been selected for the study (Fig. 1). The yearly maximum and minimum temperature are measured 57 to −2 °C, respectively. The maximum
Impact of Mechanized Cold Mix Construction Method for Hilly Region …
5
rainfall and snowfall is 252 and 187 mm, respectively. During the laying of the section, the average ambient air temperature was 12 °C. The minimum air temperature during laying is measured to be 7 °C. Around 300 commercial vehicles will be plying on the current road as reported by the Uttarakhand Rural Development Authority in 2020. Traffic intensity for 10 years of design life is estimated to be 1.1msa. The soil material and aggregate have been collected from the site and tested in the laboratory. The laboratory analysis of soil is presented in Table 1. The crust composition as per IRC SP 72 is estimated to be 300 mm (Granular Subbase of 150 mm, Wet Bound Maccadam (WBM) Grade II and Grade III of 75 m each). Over the WBM layer, a bituminous premix carpet layer of thickness of 20 mm is to be laid to get the riding quality of the pavement.
Fig. 1 a View of site before laying of premix carpet. b Collection soil and gravel from the existing pavement
Table 1 Laboratory test results of Subgrade soil samples collected from site
Parameter
Values
Gravel, %
1.43
Sand, %
29.1
Silt and Clay, %
67.9
FMC, %
10.4
LL, %
27.4
PL, %
15.1
PI
13
MDD, gm/cc
1.812
OMC
10.1
Soaked CBR, %
5.5
Soil type
CL
Note LL, liquid limit; PL, plastic limit; PI, plasticity index; MDD, maximum dry density; OMC, optimum moisture content; FMC, field moisture content
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3 Characterization of Material and Mixture Design at Laboratory The aggregate and bitumen emulsion from the site was collected to the laboratory to evaluate the material properties as per IS standards. Optimized emulsion quantity is determined through the mixture design for SDBC (semi-dense bituminous concrete) layer construction. RS1 emulsion is used for the tack coating, and MS grade emulsion is used for the SDBC mix preparation. The emulsion and aggregate properties are presented in Tables 2 and 3, respectively. The adopted gradation of aggregates is given in Table 4 for the field laying. The estimated amount of binder was determined using Eq. (1), based on the gradation of the aggregate. Samples were prepared using gyratory compactor at 100 gyrations to control voids. P = [(0.05 × A) + (0.1 × B) + (0.5 × C)]
(1)
where P = Required emulsion quantity in percentage A = Aggregate percentage retained on 2.36 mm sieve B = Aggregate percentage passing the 2.36 mm sieve and retained on the 75 µ sieve C = Aggregate percentage passing on 75 µ sieve Table 2 Test results of emulsion sample Properties of bitumen emulsion
RS1
MS
Test results
Requirement as Test per results IS:8887-2004
Requirement as per IS:8887-2004
Residue on 600 µm IS sieve (% mass), max
0.00
0.05
0.00
0.05
Viscosity by Saybolt furol viscometer, seconds, at 25 °C
34.24
–
96.5
–
Viscosity by Saybolt Furol Viscometer, 23.29 seconds, at 50 °C
20–100
74.44
50–130
Storage stability after 24 h, %, max
1.75
2
1.67
2
Particle charge
Positive Positive
Positive Positive
61.20
65.13
Tests on residue (a) Residue by evaporation, % Min
60
65
(b) Penetration, 25 °C/100gm per 5 s
87
80–150
92.50
60–150
(c) Ductility, 27 °C/cm, Min
80
50
82
50
Impact of Mechanized Cold Mix Construction Method for Hilly Region …
7
Table 3 Test results of aggregate Test
Result
Specification limit
Method of test
Grain size analysis
4%
Max 5% passing 0.075 mm sieve
IS:2386 Part I
Combined flakiness and elongation index
33.40%
Max 35%
IS:2386 Part I
Los Angeles abrasion value
21.01%
Max 35%
IS:2386 Part IV
Aggregate impact value
17.77%
Max 27%
IS:2386 Part IV
Specific gravity 10 mm aggregates
2.65
–
IS:2386 Part III
Specific gravity of 6 mm aggregates
2.675
–
IS:2386 Part III
Specific gravity of fine aggregates
2.87
–
IS:2386 Part III
Water absorption of 10 mm aggregates
0.37%
Max 2%
IS:2386 Part III
Water absorption of 6 mm 0.38% aggregates
Max 2%
IS:2386 Part III
Water absorption of fine aggregates
Max 2%
IS:2386 Part III
Table 4 Adopted aggregate gradation
1.15%
Sieve size, mm
% Passing Obtained gradation
19
Required gradation as per IRC SP 100 Lower limit
Upper limit
100
100
100
13.2
95
100
90
9.5
80
90
70
4.75
43
51
35
2.36
31.5
39
24
1.18
22.5
30
15
0.3
14
19
9
5
8
3
0.075
Using trial emulsion content, coating test was carried out for the aggregate used in this study, which was pre-wetted with water. Coating test was also carried over a range of water content (1–4% by weight of aggregate). The bitumen emulsion is then added and mixed for 1 min until the uniform coating is obtained. New batches were prepared with an addition of an increment of 1% water by weight of dry aggregate. Emulsion coating over the aggregate depends on the aggregate moisture content. The optimized moisture quantity is determined to maximize the coating of emulsion over aggregate.
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N. Beniwal et al.
Trial test samples were prepared at laboratory with increasing emulsion contents at an optimized moisture/water content. The maximum stability and bulk density of mix is found out to be at 9% and 2% emulsion and water content, respectively.
4 Test Section Construction 500 m stretch is constructed using conventional manual process. Conventional manual process involves production of cold mix using concrete mixer, transportation material through trolley, and laying by the labors (Fig. 2a–c). The fabricated machine is used for production of cold mix using inbuilt pug mill and paving through the inbuilt paver (Fig. 3). 500 m stretch adjacent to the manual laying section is laid using the fabricated machine.
Fig. 2 View of conventional manual laying process. a production of mix, b transportation, c Laying
Impact of Mechanized Cold Mix Construction Method for Hilly Region …
9
Fig. 3 View of mechanized laying system
5 Discussion The bitumen emulsion mixed material was collected from both the concrete mix and mechanized machine at different batches of mixing and checked the gradation at the laboratory through extraction. The gradation of mix from concrete mixer and mechanized mixer is presented in Fig. 4. Results show the large variability in gradation using the concrete mixer, whereas the variability is less in case of mechanized mixer. Fig. 4 Gradation of extracted material of site mix
10 Table 5 Comparison of mechanized and conventional process
N. Beniwal et al.
Parameters
Conventional process
Mechanized process
Total No. of Labors involved
15
7
Total stretch made in a day
200 m
1200 m
Fuel consumption per day
8L
6L
The variability is also observed visually. The thickness of laid surface using mechanized mixer is 20 mm ± 1 mm, whereas with manual laying thickness varies by 17–22 mm. The total stretch that can be constructed with the conventional process comes out to be 100–150 m per day which includes both the layers of Premix carpet and Seal Coat with all the necessary coatings of tack coat, wherever required. While on the other hand, this stretch can be constructed up to a total length of 1–1.5 km per day. This can help in fast-paced construction and will be more economical to use, especially where the work is needed to be completed urgently without compromising the quality of the construction. Fuel consumption by only the rotating conventional mixer is 8L per day. It excludes the fuel utilized by the 8tonne compacting roller and dumper truck that is used for transportation of aggregates to the site. The mechanized mixer fuel consumption is 6L per 5 h of working. The detail comparison of other benefits using mechanized process is presented in Table 5.
6 Conclusion The present paper shows an overview of current practices used for cold mix construction and its implication for project execution and quality of work. Conventional road construction time and cost data were acquired from site engineers, construction contractors, site labors from multiple construction projects through questionnaires. Data during actual paving of roads using both mechanical and conventional methods was collected and evaluated. Results show that with the mechanized process of laying the rate of construction is six times faster compared to the manual construction method. The mechanized construction method results in saving fuel consumption. The bituminous mixes (both manual mixing and mechanized mixer) were collected from the site. Manpower requirement is also minimized by using mechanized process of construction. A significant amount of variation in terms of aggregate gradation was found in the manual mixing method compared to the laboratory mix design. The mechanized process can be used effectively for hilly region road construction with better quality and time-saving.
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References 1. Singh JS (2006) Sustainable development of the Indian Himalayan region: Linking ecological and economic concerns. Curr Sci 784–788 2. Nandy SN, Dhyani PP, Samal PK (2006) Resource information database of the Indian Himalaya. Almora: Environmental Information System on Himalayan Ecology, GP Institute of Himalayan Environment and Development 3. Pundhir NKS, Nunda PK (2006) Development of bitumen emulsion based cold mix technology for construction of roads under different climatic conditions of India 4. Plantulli A (1981) Progress in the laying of flexible paving maintenance equipment. Publication of, Svenska Vaegfoereningen Foerlags AB 5. Chen Y (2019) Quality problems and preventive measures for municipal road and bridge construction. J Arch Res Dev 3(2) 6. Yap JBH, Chow IN, Shavarebi K (2019) Criticality of construction industry problems in developing countries: Analyzing Malaysian projects. J Manag Eng 35(5):04019020 7. Hasan A, Baroudi B, Elmualim A, Rameezdeen R (2018) Factors affecting construction productivity: a 30 year systematic review. Eng Constr Arch Manag 8. Braži¯unas J, Sivileviˇcius H (2010) The bitumen batching system’s modernization and its effective analysis at the asphalt mixing plant. Transport 25(3):325–335 9. Sivileviˇcius H, Šukeviˇcius Š (2009) Manufacturing technologies and dynamics of hot-mix asphalt mixture production. J Civ Eng Manag 15(2):169–179 10. Bowers BF, Powell RZ (2021) Use of a hot-mix asphalt plant to produce a cold central plant recycled mix: production method and performance. Transp Res Rec 2675(11):451–459 11. Day D, Lancaster IM, McKay D (2019) Emulsion cold mix asphalt in the UK: a decade of site and laboratory experience. J Traffic Transp Eng (English Edition) 6(4):359–365
Evaluation of the Effect of the Production Process in Quality Parameters of Polymer Modified Performance Grade Binders: A Case Study Arivuselvan Thillaivendhan , Vipul Jain, Arpan Ghosh, Kamlesh Gupta, R. Lakshmi Narayanan, and Amarjeet Tiwari
Abstract In India, most of the agencies started to use Polymer Modified Bitumen (PMB) as a binder in the bituminous layer due to its higher performance, India’s climatic conditions, and the increment in traffic loads. The variability in quality parameters of polymer-modified performance grade binder of a particular grade has been observed even if the key parameters like source and grade of base binder, and source and dosage of polymer are kept constant. The study’s primary aim is to compare the variability in quality parameters of the PMB produced at two different production units and find the permissible range of quality test results in the modified bitumen while following a standard production methodology and standard laboratory set-up. Detailed statistical analysis was undertaken for 200 batches of PMB samples. Result of the study indicates the importance of automation in production plants as well as quality control equipment. Production unit 1 (PU 1) with more automation showed lesser variability consistently across all quality parameters of the PMB as compared to production unit 2 (PU 2) which had more manual processes in the production. Also, the laboratory set-up in terms of availability of automated equipment, temperature control, and skilled technician, of PU 1 was better as compared to PU 2 which played a key factor in the variability of quality parameters. The study’s key takeaway is to highlight the importance of creating an environment of quality consciousness to produce performance grade binders for long-lasting pavements. Keywords Polymer modified bitumen · Production methods of PMB · Laboratory standards · Quality analysis of produced PMB A. Thillaivendhan (B) · V. Jain · A. Ghosh · K. Gupta · R. Lakshmi Narayanan · A. Tiwari V R TECHNICHE Consultants Private Limited, Noida 201305, India e-mail: [email protected] V. Jain e-mail: [email protected] A. Ghosh e-mail: [email protected] K. Gupta e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_2
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1 Introduction Bituminous binders are widely used for road paving applications. The bitumen’s chemical composition significantly affects its viscoelastic properties and, hence, its performance as a paving material [2]. In both paving and industrial applications, the bitumen should be resistant to climate and more demanding traffic loads, for which reason rheological properties play a key role in different aspects. But most of the available conventional bitumen would not provide all the needed characteristics together. Moreover, in some applications, the performance of base bitumen may not be satisfactory considering the required engineering properties because it is brittle in a cold environment and softens readily in a warm environment. In addition, as the traffic speed and load have dramatically increased, unexpected overloading has notably shortened the life of asphalt pavements, increasing its costs of maintenance and risks to users [3]. Hence, to enhance the performance properties of base bitumen, a variety of additives have been introduced and some have been used successfully for many applications. Modifiers and additives have been used to boost bitumen performance. The most common modifying agents are polymers. Bitumen is modified by polymers and often proves to be the most cost-effective alternative to conventional bitumen because they improve targeted aspects of the performance of roads, and the polymers employed to modify bitumens are readily available at a reasonable cost. Polymer modified bitumen (PMB) is one of the specially designed and engineered bitumen grades that are used in making pavement, roads for heavy-duty traffic, and home roofing solutions to withstand extreme weather conditions. PMB is a normal bitumen with the added polymer, which gives it extra strength, high cohesiveness, and resistance to fatigue, stripping, and deformations [6]. This paper takes into consideration the observations carried out during the production of over 19,000 tons of performance grade polymer modified binder at two different production units for the periodic maintenance of four National Highway projects. The study’s primary aim is to compare the variability in quality parameters of the modified binder produced at two different production units. The paper explains in detail the various steps of the production methodology and quality control process which are key to achieving lesser variability in the final product. A lesser variability would ensure consistent operations of the Hot Mix Plant (HMP) in terms of the binder’s heating requirements and the bituminous mix’s production. It would also ensure consistency in laying and compaction, achieving the required performance parameters. It is to be noted that the current Indian standards give the minimum or maximum specified limits for a different grade of polymer-modified bitumen, wherein there are no ranges specified for each of the quality parameters. However, in countries outside India, the modified binder has few specifications wherein ranges in quality parameters have been specified for key rheological parameters. The study also focuses to find the permissible range of quality test results in the modified bitumen while following a standard production methodology and standard laboratory set-up to perform the quality tests.
Evaluation of the Effect of the Production Process in Quality Parameters …
15
Table 1 Quality test results of VG 30 Quality parameter
Softening point (°C)
Penetration (1/100) mm
Ductility (cm) at 25 °C
Absolute viscosity at 60 °C (Poises)
Kinematic viscosity at 135 °C (cSt)
Obtained results
51.17
47
100
3463.69
506.175
2 Material Characteristics The base binder which is used in this study is VG (Viscosity Grade) 30 from an Indian refinery. As described earlier, the source of the base binder is common for both production units. The basic quality tests performed in the base binder are the softening point, penetration, viscosity, and ductility. The quality test results are studied and certified as per the specification given by IS 73: 2013 (Paving Bitumen—Specification 4th Revision). The test results of the base binder, i.e., VG 30 are shown in Table 1. This study’s typical grade of polymer (modifier) is SBS (Styrene Butadiene Styrene) elastomeric. It is a clear linear block copolymer based on styrene and butadiene with bound styrene of 30% mass. It is supplied from Europe in the form of porous pellets dusted with talc. The cross-linking agent which is used in PMB production is elemental sulfur. The elemental sulfur is used to cross-link the polymer molecules via a double bond of butadiene and to couple a polymer and bitumen through sulfide and/or polysulfide bonds. It leads to the formation of a stable polymer network in bitumen and reduces the possibility of separation between the bitumen and polymer.
3 Production Methodology of PMB 3.1 Production Unit 1 It is a single-pass production methodology system. In this production unit, we have an advanced option to feed bitumen, polymer, and cross-linking agents in automatic with the proper control system. The flowmeter has been placed between each storage tank to control the quantity of material passing in weight-based also it helps to maintain the required quantity of material automatic as per batch recipe. The detailed production methodology is described below. The base binder (VG 30) is heated to 170–180 °C in the bitumen storage tank (B). Bags of pre-weighed polymer and cross-linking agent are counted and placed in proximity to their respective dosing hopper by the product specification and batch size.
16
A. Thillaivendhan et al. A: Base binder unloading point B: Base binder storage tank C: Pre-mixing tank D: Polymer feeding point E: Additive feeding point F: Shear mill G: Curing tank for PMB H: PMB (Final product) loading
Fig. 1 PU 1—Process of production methodology
The base binder is pumped from its storage tanks to the pre-mixing tank (C), where the weighing and mixing take place. In parallel, the polymer and additive are added to the pre-mixing tank with the required proportion. The addition of all three ingredients takes place at the same time and it is a continuous process. Then, the mixture of all three ingredients enters the shear mill, where the polymer granules are sheared and ground with the base binder. Then, the material is transferred into the curing tank and agitated to form a homogeneous mixture. The produced PMB needs to be stored for periods of 8–12 h to dissolve the polymer granulation into the base binder in a curing tank. Then, the final product is taken for quality testing to proceed with loading and dispatch to the site. The production process is shown in Fig. 1.
3.2 Production Unit 2 It is a multiple-pass production methodology system. In this production unit, we do not have an option to feed polymer, and cross-linking agents which are automatic, and these ingredients are added in manually with the help of labor. Also, the material passing quantities are taken place volume-based (not weight-based), due to the nonavailability of the flow meter. The production process is shown in Fig. 2.
G E
A
B
C
F
D
Fig. 2 PU 2—Process of production methodology
H
A: Base binder unloading point B: Base binder storage tank C: Reaction kettle D: Shear mill E: Polymer feeding point F: Dilution Tank for PMB G: Additive feeding point H: PMB (Final product) loading point
Evaluation of the Effect of the Production Process in Quality Parameters …
17
The base binder (VG30) is heated in the storage tank (B) by a bitumen heater to about 180 °C and then pumped through pipes heated by hot thermic oil to the reaction kettle (C) of the plant. The polymer is loaded into the reaction kettle from its loading hopper, once the required quantity of base binder passed. The dosage of the polymer is regulated by weight and is usually 8–12% of the total mass. After that, both components are mixed by an agitator inside of the reaction kettle (C), to prepare them for feeding to a shear mill (D), which is placed outside the reaction kettle. A shear mill (D) breaks up polymer granules and mixes them with bitumen. Then, the concentrated PMB is transferred to a dilution tank (F). Fresh bitumen is added to make dilution to the specified PMB properties and agitated to form a homogenous mixture. Generally, it should be stored for at least 8–12 h to fully dissolve the polymer granulate mixed in it, this time depends on the temperature and intensity of mixing. After that, the additive is added to the dilution tank (F). The dosage of additives is controlled by humans, while the plant manually maintains the values required by the formulation. A detailed comparison of the two production units is shown in Table 2. Table 2 Comparison of two production units Description of comparison Materials used in the PMB production
Plant level
Manpower
Transportation
Parameters
Production unit 1
Production unit 2
Base binder
Durapave VG30
Durapave VG30
Polymer
SBS
SBS
Additive
Sulfur (Pellets)
Sulfur (Powder)
Plant type
Continuous plant (Automatic)
Batch plant (Manual)
Pass (No. of passes)
Single pass
Multiple pass
Flow meter
Available
Not available
Quantity calculation
Weight-based
Volume based
Polymer dosing
Automatic
Manual
Fuel oil filter
Available
Not available
Additive dosing
Automatic
Manual
Plant operator (Production In-charge)
Two shift (Two persons in each shift)
Two shift (One person in each shift)
Lab staff
Two shift (Two persons in each shift)
Two shift (One person in each shift)
Segregation of trucks
Yes
No
Dedicated Yes transport facility
No
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A. Thillaivendhan et al.
4 Laboratory Setup In PU 1, all the testing equipments are available to perform the quality tests on a base and modified binders. Here, most of the equipment is automatic so we can reduce manual error. Also, the laboratory set-up is made with a proper temperature control system and skilled technicians to perform quality tests. These factors are helped to reduce the variability of quality parameters. Whereas in PU 2 a few of the testing equipment is not available and all the basic testing equipment is manual and of its oldest version. The details are shown in Table 3. Table 3 Details about the availability of laboratory equipment S. No
Characteristics Test equipment
Production unit 1
Production unit 2
Availability Remarks of equipment
Availability of equipment
Remarks
1
Softening point Ring and ball apparatus
Available
Automatic
Available
Manual
2
Elastic recovery
Ductility testing machine
Available
Automatic
Available
Manual
3
Flash point
Cleveland flash point tester
Available
Semi-automatic
Not Available
4
Viscosity
Rotational viscometer
Available
–
Available
–
5
FRAASS breaking point
FRAASS breaking point tester
Available
–
Not available
–
6
DSR
Rheometer
Available
–
Available
–
7
PAV
Presser vessel
Available
–
–
Vacuum oven
Available
–
Not available
Air compressor
Available
–
8
Penetration
Penetrometer
Available
–
Available
–
9
Absolute viscosity
Viscosity bath
Available
–
Available
–
Vacuum regulator
Available
–
Available
–
Tube
Available
–
Available
–
10
Kinematic viscosity
Viscosity bath
Available
–
–
Tube
Available
–
Not available
11
RTFO
Oven
Available
–
Available
–
12
TFO
Oven
Available
–
Available
–
Evaluation of the Effect of the Production Process in Quality Parameters …
19
Table 4 Statistical parameter for Softening Point test results Softening Min point (°C)
Max
Average Range Standard Variance Median Mode Specified deviation limit (Min)
PU 1
65.45 70.60 67
PU 2
66
78
69.31
5.15 12
0.844
0.712
66.96
67.08 65
2.437
5.939
68.68
67
65
5 Results and Discussions In the study, there are 200 batches of PMB samples that have been analyzed. For each batch of PMB sample, softening point, rotational viscosity, elastic recovery, and MSCR (Jnr difference and Jnr at 3.2 kPa) tests are carried out. The statistical parameter and normal distribution curve have been detailed for each test result to show the variability ranges in the obtained test results.
5.1 Softening Point The average softening point (SP) of a produced PMB from a PU 1 is 67 °C against the target specification of 65 °C (Min) with a minimum SP of 65.45 °C and a maximum of 70.60 °C. In PU 2, the average SP is 69.31 °C with a minimum SP of 66 °C and a maximum of 78 °C. The detailed statistical parameter for both the production unit’s test results is shown in Table 4. The normal distribution curves have been plotted with the statistical parameter and it is shown in Fig. 3. The bell-shaped curve obtained from the PU 1 test results is narrow, whereas in PU 2 it is flat. It is due to the wide ranges, i.e., 12 °C in the SP test results. It is also observed that 82% of tested samples lie in the range of 66–68 °C of SP from PU 1, whereas in PU 2 it is 41%. It clearly explains that the production unit could produce a modified bitumen with a permissible range in the softening point of 2 °C when operating with standard production methodology and standard laboratory set-up to perform the quality tests. The range has been shifted to 66–71.3 °C of SP in PU 2 for lying 82% of tested samples.
5.2 Rotational Viscosity by Brookfield Viscometer The average Rotational Viscosity (RV) of a produced PMB from a PU 1 is 0.86 Pa.S with a standard deviation of 0.059 and a variance of 0.0035. Whereas, in PU 2 the average RV is 0.91 Pa.S. The detailed statistical parameter of the RV test results for both the production units is shown in Table 5. The normal distribution curves have been plotted with the statistical parameter, shown in Fig. 4. The bell-shaped curve
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A. Thillaivendhan et al.
Fig. 3 Quality test results of softening point test for PU 1 and PU 2
Table 5 Statistical parameter for rotational viscosity test results Rotational Min Viscosity (Pa.S)
Max Average Range Standard Variance Median Mode Specified deviation limit (Max)
PU 1
0.76 1.14
0.86
0.38
0.059
0.0035
0.85
0.81
1.2
PU 2
0.6
0.91
0.58
0.144
0.0206
0.87
0.86
1.2
1.18
obtained from the PU 1 test results is narrow, whereas in PU 2 it is flat. It is due to a higher value of standard deviation and variance from the PU 2 PMB samples. It is also observed that 89% of tested samples lie in the range of 0.8–1.0 Pa.S RV from PU 1, whereas in PU 2 it is 48%. It clearly explains the production unit could produce a modified bitumen with a permissible range in the RV of 0.2 Pa.S, whereas in PU 2 the range has been shifted to 0.6–1.13 Pa.S of RV for lying 89% of tested samples.
5.3 Elastic Recovery The Elastic Recovery (ER) range of a produced PMB from a PU 1 is 5, i.e., 72–77% with a standard deviation of 0.943. Whereas in PU 2 the range is 13, i.e., 72–88% with a standard deviation of 2.386 and a variance of 5.693. The detailed statistical parameter of the ER test results for both the production units is shown in Table 6. The
Evaluation of the Effect of the Production Process in Quality Parameters …
21
Fig. 4 Quality test results of viscosity test for PU 1 and PU 2
normal distribution curves have been plotted with the statistical parameter. The bellshaped curve follows the same pattern as SP and RV results. It is also observed that 88% of tested samples lie in the range of 73–75% of ER from PU 1, whereas in PU 2 it is 26%. It clearly shows the production unit could produce a modified bitumen with a permissible range of 2% in ER when it is following standard production methodology and standard laboratory set-up to perform the quality tests. The range has been shifted to 72–80% of ER in PU 2 for lying 88% of tested samples. It is shown in Fig. 5. Table 6 Statistical parameter for Elastic Recovery test results Elastic recovery (%)
Min
Max
Average
PU 1
72
77
73.78
PU 2
72
88
76.93
Range
Standard deviation
Variance
Median
Mode
Specified limit (Min)
5
0.943
0.889
74
74
70
13
2.386
5.693
76.6
75
70
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A. Thillaivendhan et al.
Fig. 5 Quality test results of elastic recovery for PU 1 and PU 2
5.4 MSCR—Jnr Difference The average Jnr difference of a produced PMB from a PU 1 is 45.89% against the target specification of 75% (Max) with a minimum result of 36.42% and a maximum of 42.98%. Whereas, in PU 2 the average Jnr difference is 54.62%. The detailed statistical parameter for both the production unit’s test results is shown in Table 7. The normal distribution curves have been plotted with the statistical parameter. It is shown in Fig. 6. The bell-shaped curve obtained from the PU 1 test results is narrow, whereas in PU 2 it is a flat shape. It is also observed that 92% of tested samples lie in the range of 40–55% of Jnr difference from PU 1, whereas in PU 2 it is 30%. Table 7 Statistical parameter for MSCR (Jnr Difference) test results Jnr Min difference (%)
Max
Average Range Standard Variance Median Mode Specified deviation limit (Max)
PU 1
3642 61.95 45.89
25.53
4.384
19.217
45.79
46.5
PU 2
4298 63.54 54.62
20.56
6.730
45.294
57.36
57.39 75
75
Evaluation of the Effect of the Production Process in Quality Parameters …
23
Fig. 6 Quality test results of Jnr difference for PU 1 and PU 2
5.5 MSCR—Jnr at 3.2 kPa. The range of Jnr at 3.2 kPa of a produced PMB from a PU 1 is 0.38, i.e., 0.6–0.98 (1/kPa) with a standard deviation of 0.093. Whereas in PU 2 the Jnr range is 0.44, i.e., 0.34–0.79 (1/kPa) with a standard deviation of 0.1875. The detailed statistical parameter of the test results for both the production units is shown in Table 8. The normal distribution curves have been plotted with the statistical parameter. The test results also explained that 84% of tested samples lie in the range of 0.65–0.9 1/kPa of Jnr from PU 1, whereas in PU 2 it is 50%. The details are expressed in Fig. 7. Table 8 Statistical parameter for MSCR (Jnr at 3.2 kPa) test results Jnr at 3.2 Min (1 kPa)
Max Average Range Standard Variance Median Mode Specified deviation limit (Max)
PU 1
0.6
PU 2
0.34 0.79
0.98
0.8
0.38
0.0939
0.0088
0.82
0.88
1
0.58
0.44
0.1875
0.0352
0.61
0.79
1
Fig. 7 Quality test results of Jnr at 3.2 kPa for PU 1 and PU 2
24
A. Thillaivendhan et al.
6 Conclusion The variability in the quality test results has been minimized in PU 1, where the controllable factors like automated feeding of ingredients, placement of flowmeter, standard laboratory setup to reduce manual error, and skilled manpower are in control along with uncontrollable factors like sufficient manpower, periodic maintenance of production plant, calibration of laboratory equipment’s in time, segregation of trucks, etc., in the production level. It leads to defining the permissible range in the quality test results in the produced modified bitumen, instead of following the maximum and minimum specified limits as per our Indian codes [8]. Whereas in PU 2, the permissible ranges have been increased consistently in all the quality parameters concerning PU 1. It is shown in Table 9. It is due to large variability in each quality test result. It is due to most of the controllable factors becoming uncontrollable in PU 2. A lesser variability would ensure consistent operations of the Hot Mix Plant (HMP) in terms of the binder’s heating requirements and the bituminous mix’s production. It would also ensure consistency in laying and compaction, achieving the required performance parameters. Recommendations The following points/techniques will reduce the variability in the properties in a manual production process of modified bitumen. . Flowmeter—It is mandatory to be present in each pipeline before the storage tank to assure the quantity of materials passed into the storage tank. . Dedicated Storage Tanks—With a different grade of base binder (VG 30 and VG 10) and modified bitumen. . Maintenance of Plant—Routine maintenance of the plant should be done at regular intervals for machinery parts, particularly in the shear mill. Table 9 Comparison of quality parameter’s ranges For PU 1 and PU 2 S.no
Test parameter
% of samples lie in the ranges
PU1
PU2
1
Softening point (°C)
82
2
5.3
3.3
2
Rotational viscosity (Pa.S)
89
0.2
0.53
0.33
3
Elastic recovery (%)
88
2
8
6
4
Jnr Diff (%)
93
15
22
7
5
Jnr at 3.2 (1 kPa) 84
Ranges in each parameter
0.25
0.45
The difference in the ranges from PU1 and 2
0.2
Evaluation of the Effect of the Production Process in Quality Parameters …
25
. Calibration of Laboratory Equipment—Regular calibration needs to be done for all the laboratory equipment. . Laboratory Equipment—Placing automated laboratory equipment is mandatory to reduce manual errors in the testing. . Segregation of Trucks—The trucks should be properly segregated with different grades of the binder to avoid quality issues. . Manpower—Sufficient skilled manpower should be present in the production and laboratory teams. . All activities should be monitored closely. . Overheating of materials should be avoided.
References 1. McNally T (2011) Introduction to polymer modified bitumen. Woodhead Publishing Limited 2. Perez Lepe A, Martinez Boza FJ, Gallegos C, Gonzalez MME, Santamaria A (2003) Influence of the processing conditions on the rheological behavior of polymer modified bitumen. Fuel 82:1339–1348 3. Bulatovic VO, Rek V, Markovic (2012) Review polymer modified bitumen. Mater Res Innov 16 4. Rosssai CO, Spadafora A, Teltayev B, Gonzalez, Izmailova G, Amerbayev Y, Bortolotti V (2015) Polymer modified bitumen—Rheological properties and structural characteristics. Colloids Surf A Phys Chem Eng Asp 5. Zhu J, Birgisson B, Kringo N (2014) Polymer modification of bitumen—advances and challenges. Eur Polym J 54:18–38 6. Polymer Modified Bitumen | modified bitumen | modified asphalt (rahabitumen.com) 7. IS 73: 2013 Indian Standard Paving Bitumen—Specifications (Fourth Revision) 8. IS 15462:2019 Indian Standard Polymer Modified Bitumen (PMB)—Specification (First Revision) 9. ASTM D6373—15 Standard Specification for Performance Graded Asphalt Binder
Effect of Superplasticizer on Characteristics of Pervious Concrete Shuddhashil Ghosh and Priyansh Singh
Abstract Pervious concrete is a promising ecological methodology. It is open graded in nature as it has zero to minimal fine aggregate, making it stiff and difficult to work with. Due to the open-graded matrix, this concrete has a high void ratio and has emerged as a sustainable solution to reduce surface runoffs. This paper investigated pervious concrete behavior with a water-cement ratio between 0.25 and 0.3 and a superplasticizer dosage of 0–2%. Various mix proportions were prepared, keeping a constant air void and aggregate cement ratio. Mechanical properties of fresh and hardened concrete such as slump, density, flexural strength, and fracture toughness were measured. Corresponding graphs of mechanical properties with water-cement ratio and superplasticizer % variations are obtained. The results show that with increasing the dosage of SP, the properties of PC get improved. Keywords Pervious concrete · Superplasticizer · Flexure
1 Introduction Pervious concrete (PC) has been used in the United States and Japan for more than 30 years [1]. It has a lot of pores, and the cement paste is equally spread throughout the matrix. Pervious concrete can allow the passage of rainwater and stormwater into aquifers via interconnected voids. It is made of cement, coarse aggregate, little to no amount of fine aggregate, and water [1]. Pervious concrete has a porosity of 11–35% [2, 3]. This causes pervious concrete to have considerable permeability resulting in superior drainage properties and high noise absorption; however, it negatively affects the concrete’s strength. Compressive strength can range from 3.5 to 28 MPa, and flexural strength from 1 to 3.8 MPa, with a density between 1600 and 2000 kg/ m3 [2]. As a result, it can be used as an environmentally friendly paving material for applications such as walkways, sidewalks, light traffic roads, shoulders, and parking lots [4]. S. Ghosh · P. Singh (B) Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_3
27
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S. Ghosh and P. Singh
Workability refers to various properties, including mixing, finishing, and compatibility. The current strategy for achieving workability is based on trial–error due to a lack of scientific procedures [5]. Previous research correlated paste flowability [6] and cement paste spread [7] to workability. The lubricating action of the paste provides workability in Portland Cement Pervious Concrete (PCPC). As a result, as the matrix hardens, the paste develops strength, transferred to the aggregate via bonding. The bonding and contact load transmission between the paste-coated aggregates maintains the matrix’s overall stability. As a result, cement paste plays an integral part in PCPC’s fresh and hardened qualities [6]. Workability can be increased by either increasing the w/c ratio or by using a superplasticizer (SP). Research shows that increasing w/c in the range of 0.25–0.35 led to increased compressive strength due to decreased porosity [8]. Previous studies have found that using SP can lead to a significant increase in the mechanical properties of PC [9]. Adding SP can also increase setting time, which is beneficial in PC construction as the cement paste thickness is smaller, leading to a decrease in setting time compared to conventional concrete [10]. Pervious concrete pavements are vulnerable to flexural strains and fatigue due to vehicular loads, and these elements have not been thoroughly investigated [11]. The effects of SP and water/cement (w/c) on the workability, density, flexural strength, and fracture toughness of pervious concrete were investigated in this research. For this study workability of PC is taken as the acceptable slump value [12].
2 Materials 2.1 Cement Ordinary Portland cement (OPC) of M53 grade conforming to IS 269:2015 [13] was used as the binder. The chemical composition and physical properties are presented in Tables 1 and 2, respectively.
2.2 Aggregates For this research, locally procured crushed granite stones, which passed through a 10 mm sieve and retained in a 6.3 mm sieve, were used as coarse aggregate. The properties of aggregates are listed in Table 3.
Effect of Superplasticizer on Characteristics of Pervious Concrete Table 1 Chemical composition of cement
Table 2 Physical properties of cement
Table 3 Aggregate properties
29
Particulars
Test results
Limits (IS 269:2015)
LSF (lime saturation factor)
0.93
0.80–1.02
Alumina modulus
1.05
Min 0.66
The insoluble residue (%)
1.57
Max 4.0
Magnesia (%)
1.02
Max 6.0
Sulphuric anhydride (%)
2.62
Max 3.5
Loss in ignition (%)
2.52
Max 4.0
Tricalcium aluminate
5.29
–
Chloride (%)
0.027
Max 0.1
Physical properties
Measured values
Test method
Limits (IS 269:2015)
Soundness (mm)
1
IS 4031 (Part III) [14]
10 mm (max)
Standard consistency (%)
33.2
IS 4031 (Part IV) [15]
–
Initial setting time (minutes)
42
IS 4031 (Part V) [16]
30 min (max)
Final setting time (minutes)
190
Compressive strength (MPa)
–
3 days
27.3
27 MPa (min)
7 days
37.1
37 MPa (min)
600 min (max) IS 4031 (Part VI) [17]
–
Specific gravity 3.15
IS 4031 (Part XI) [18]
Parameters
Test results
IS code
Limits
Dry rodded density (kg/m3 )
1546.5
IS 2386 (Part III) [19]
–
–
Absorption (%)
1.42
IS 2386 (Part III) [19]
0.1–2% [20]
Specific gravity
2.924
IS 2386 (Part III) [19]
2.5–3 [21]
IS 2386 (Part IV) [22]
Max 35% [23]
Los Angeles abrasion (%)
15.4
30 Table 4 Superplasticizer properties
S. Ghosh and P. Singh
Description
Results
Material
Super plasticizer-SNS
Color
Water white
Specific gravity
1.35 ± 2
Solid content
40 ± 2
PH
7–7.5
Solubility
Water
Mixing ratio
300–500 gms per Cement Bag
2.3 Superplasticizer An SNS superplasticizer was used in this research, the properties of which are listed in Table 4.
3 Methodology and Sample Preparation 3.1 Methodology Aggregate gradation was chosen based on the literature review. Aggregates tests were done as per IS codes to determine the different properties of aggregates. Based on previous studies, w/c, air voids %, and aggregate cement ratio were selected. Slump tests were conducted on different w/c with varying SP dosages. When the slump value ranged from 20 to 60 mm, the mix was a workable mixture. Six beams were cast for each mixture, three for flexural strength determination and three for fatigue toughness. Dry densities were also determined for the casted beams. The research outline is described in Fig. 1.
Fig. 1 Research outline
Effect of Superplasticizer on Characteristics of Pervious Concrete
31
3.2 Sample Preparation The cement aggregate ratio used in PC by different researchers varied between 0.08 and 0.25, while the air voids varied between 15 and 35% [5, 24]. In this study, PC was made with a fixed cement/aggregate ratio of 0.2 and an air void of 20% to get good strength and permeability. The absolute volume approach was used to construct the mix proportions, assuming the aggregates were saturated surface-dried (SSD). Hand mixing was used to prepare fresh mixtures. The amounts of water and aggregates were modified according to SP content to preserve the planned mix proportioning. The procedure consisted of mixing dry aggregates and a small amount of water equivalent to absorption % for 1 min to bring the aggregates to saturated surface dry (SSD) condition. Then cement was added to and mixed for another minute for uniform mixing. Then the mixture was divided into two trays mixing for ease. The remaining water, mixed with SP, was added to the dry cement and aggregate mixture in both trays and mixed for 3 min. The SP range varied from 0 to 2%. The mixture composition is given in Table 5. The mixture was first tested for the slump test. After determining the slump, the mixture was mixed again for 30 s, and beams were cast. The beams were cast in 2 layers. Both the layers were compacted using a 2.5 kg proctor hammer. After compaction, the excess mixture was trimmed off using a trowel to give a smooth, level finish. Table 5 Mix proportions used for sample preparation Mix ID
Mix proportioning Cement
Aggregate
Water
SP (%)
w/c
25–0
1756
8657
564
0
0.25
25–5
1754
8643
563
0.5
0.25
25–10
1751
8629
562
1
0.25
25–15
1748
8615
561
1.5
0.25
25–20
1745
8601
560
2
0.25
275–0
1737
8563
601
0
0.275
275–5
1734
8549
600
0.5
0.275
275–10
1732
8536
599
1
0.275
275–15
1729
8522
598
1.5
0.275
275–20
1726
8508
597
2
0.275
30–0
1719
8471
638
0
0.3
32
S. Ghosh and P. Singh
Fig. 2 a slump height measurement and b zero slump
4 Test Methods 4.1 Slump Test The conventional slump cylinder was used to determine the slump of the freshly prepared concrete (Fig. 2) [25]. The mix was poured into the cylinder, and a trowel was used to level the top. After slowly lifting the cylinder, the height difference between the top of the cylinder and the middle of collapsed material was measured. During the testing, the room temperature was 24 ± 2 °C.
4.2 Flexural Strength Test Three-point bending test was conducted on a servo-controlled Universal Testing Machine (UTM) (Fig. 3). A constant strain rate of 0.1 mm/min was applied to measure the mid-span deflection of the specimen. The tests were performed until failure occurred. An LVDT sensor on the steel frame measured the deflection in the specimen’s center.
4.3 Flexural Toughness Test The beams were subjected to a three-point bending test under a 0.1 mm/min constant strain rate. The fracture toughness KIC is calculated using Eq. (1) [26]:
Effect of Superplasticizer on Characteristics of Pervious Concrete
33
Fig. 3 Setup of the beam samples
KIC =
[ ( )1 ( a )3 ( a )5 ( a ) 17 ( a )9 ] PL a 2 2 2 2 2 − 4.6 + 21.8 − 37.6 + 38.7 × 2.9 B H 3/2 H H H H H
(1) where L, H, B, and a refer to the beam specimen’s length, height, width, and notch while P represents the maximum load. In this work, a notch depth of 20 mm is taken.
5 Results and Discussion 5.1 Slump The changes in a slump are shown in Fig. 4. When the w/c ratio was 0.25, the slump was 0 cm, which increased to 15 mm and 55 mm when w/c was 0.275 and 0.3, respectively. The moisture state of aggregates has a significant effect on the slump when no SP is added. As w/c increases, the cement content decreases, making the cement paste thinner and less viscous, allowing for more lubrication for the aggregates. Since the cement paste is thin, the chances of segregation increase; hence increasing slump with just the addition of water is not advisable. Adding SP with a constant W/C ratio improved the workability of concrete. The trendline equations of w/c of 0.25 and 0.275 are y = 24x + 12 and y = 20.4x − 0.4. The increased slope indicates that SP is slightly less effective in an increasing slump when low w/c is used.
34
Fig. 5 Density variation with different w/c and SP dosage
Slump Height (mm)
w/c = 0.25
w/c = 0.275
80
w/c = 0.3 y = 24x + 12 R² = 0.9796
60 40
y = 20.4x - 0.4 R² = 0.9927
20 0 0
0.5
w/c = 0.25
Density (kg/m3)
Fig. 4 Slump variation with different w/c and SP dosage
S. Ghosh and P. Singh
2120 2100 2080 2060 2040 2020 2000
1
1.5
SP %
w/c = 0.275
2
2.5
w/c = 0.3
y = 42x + 2017 R² = 0.9932 y = 40x + 1981.3 R² = 0.9494
0
0.5
1
1.5
2
2.5
SP%
5.2 Density The density variations are shown in Fig. 5. The dispersion effect is the key method SP promotes particle packing density. Particles that have been de-agglomerated are more readily and tightly packed [27], and as mentioned earlier, the effect of SP increases with higher w/c. It can be noted that the packing density of pastes increases with an increase in the w/c ratio along with an increase in SP%. It can also be seen that while w/c = 0.3 gives the highest density, there is a higher chance of segregation of cement paste. Previous research has shown that density can be used as an indicator of strength [28]. The trendline slope for w/c = 0.25 is lower than w/ = 0.275, indicating that SP is more effective in increasing compressive strength with a higher w/c ratio. This can be due to increased paste volume filling up the pores.
5.3 Flexural Strength The flexural strength variation can be seen in Fig. 6. The rate of strength increases for both w/c of 0.25 and 0.275 is nearly the same, as the difference between the
Fig. 6 Flexural strength variation with different w/c and SP dosage
Flexural Strength (MPa)
Effect of Superplasticizer on Characteristics of Pervious Concrete
w/c = 0.25
35
w/c = 0.275
1.60
w/c = 0.3
y = 0.204x + 0.9534 R² = 0.905
1.40 1.20
y = 0.2053x + 0.8184 R² = 0.9628
1.00 0.80 0
0.5
1
1.5
2
2.5
SP %
trendline slopes is 0.6%. Also, the flexural strength for 0.3 w/c is the lowest. This can be attributed to the thin paste between the aggregates, leading to weaker bonding.
5.4 Fracture Toughness Variation of fracture toughness is shown in Fig. 7. Toughness values show a similar trend as flexural strength with an increase in SP% and w/c. This indicated that increasing w/c within a specific range and SP could increase PC’s resistance to cracking and its propagation. As the trendline slope for w/c = 0.25 is more than that of 0.275, SP is more effective in resisting crack propagation with lower w/c, which can be due to more viscous paste. w/c = 0.25
KIC (MPa m1/2)
Fig. 7 Fracture toughness variation different w/c and SP dosage
w/c = 0.275
w/c = 0.3
0.14 y = 0.0236x + 0.0817 R² = 0.9423
0.12 0.10
y = 0.0329x + 0.048 R² = 0.9922
0.08 0.06 0
0.5
1
1.5
SP %
2
2.5
36
S. Ghosh and P. Singh
6 Conclusion Workability affects the mechanical properties of pervious concrete and can be changed by either changing the w/c ratio or adding a superplasticizer. Variation in a slump, density, and mechanical properties of pervious concrete was investigated for different w/c ratios and SP doses. Based on the experimental results, the following conclusions can be drawn. . PC’s workability increased by both increasing the w/c ratio and with the addition of superplasticizers. . Increasing the workability with increasing w/c resulted in increased density while negatively affecting the mechanical properties. . Changing workability with SP increased the mechanical strength due to denser paste between aggregate particles. . The rate of strength gain with increasing SP dose was more for w/c of 0.275 as the rate of increase of density was higher than with w/c = 0.25. . The study’s optimum SP and w/c content were 2% and 0.275, respectively.
References 1. Huang B, Wu H, Shu X, Burdette EG (2010) Laboratory evaluation of permeability and strength of polymer-modified pervious concrete. Constr Build Mater 24:818–823. https://doi.org/10. 1016/j.conbuildmat.2009.10.025 2. Tennis P, Leming M, Akers D (2004) Pervious concrete pavements 3. Putman BJ, Neptune AI (2011) Comparison of test specimen preparation techniques for pervious concrete pavements. Constr Build Mater 25:3480–3485. https://doi.org/10.1016/j. conbuildmat.2011.03.039 4. Gesoˇglu M, Güneyisi E, Khoshnaw G, Ipek S (2014) Investigating properties of pervious concretes containing waste tire rubbers. Constr Build Mater 63:206–213. https://doi.org/10. 1016/j.conbuildmat.2014.04.046 5. ACI (2010) Report on Pervious Concrete, ACI 522R-10 6. Chindaprasirt P, Hatanaka S, Chareerat T, Mishima N, Yuasa Y (2008) Cement paste characteristics and porous concrete properties. Constr Build Mater 22:894–901. https://doi.org/10. 1016/j.conbuildmat.2006.12.007 7. Obla K, Lobo C, Hong R, Kim H (2015) Optimising concrete mixtures for performance and sustainability 59 8. Sonebi M, Bassuoni MT (2013) Investigating the effect of mixture design parameters on pervious concrete by statistical modelling. Constr Build Mater 38:147–154. https://doi.org/ 10.1016/j.conbuildmat.2012.07.044 9. Yang J, Jiang G (2003) Experimental study on properties of pervious concrete pavement materials. Cem Concr Res 33:381–386. https://doi.org/10.1016/S0008-8846(02)00966-3 10. Mohammed BS, Liew MS, Alaloul WS, Khed VC, Hoong CY, Adamu M (2018) Properties of nano-silica modified pervious concrete. Case Stud Constr Mater 8:409–422. https://doi.org/ 10.1016/j.cscm.2018.03.009 11. Chandrappa AK, Biligiri KP (2017) Flexural-fatigue characteristics of pervious concrete: statistical distributions and model development. Constr Build Mater 153:1–15. https://doi.org/10. 1016/j.conbuildmat.2017.07.081
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12. Indian Roads Congress (2017) IRC-15: Standard Specifications and Code of Practice for Construction of Concrete Roads 13. IS 269:2015:IS 269 (2015) Ordinary portland cement – specification (Sixth Revision). Bur Indian Stand 14. IS 4031—Part III (1988) Methods of physical tests for hydraulic cement: determination of soundness. Bur. Indian Stand. New Delhi. Reaffirmed in 2005 15. IS 4031 (1988) Part IV: Methods of physical tests for hydraulic cement. Part IV—Determination of consistency of standard cement paste. Bur Indian Stand. New Delhi. Reaffirmed in 2005 16. IS 4031 (1988) Part V: Methods of physical tests for hydraulic cement. Part V—Determination of initial and final setting times. Bur Indian Stand. New Delhi. Reaffirmed in 2005 17. IS 4031 (2005) Part VI: Methods Of Physical Tests For Hydraulic Cement Part 6 Determination Of Compressive Strength Of Hydraulic Cement Other Than Masonry Cement (First Revision). Bur Indian Stand. Delhi. 1–3 18. IS 4031 (1988) Part XI: 1988Methods of physical tests for hydraulic cement. Bur Indian Stand 1–6 19. IS 2386 (1963) Part III: Method of Test for aggregate for concrete. Part III- Specific gravity, density, voids, absorption and bulking. Bur. Indian Stand. New Delhi. (Reaffirmed 2002) 20. Pavement materials: Aggregates, https://www.civil.iitb.ac.in/tvm/1100_LnTse/404_lnTse/ plain/plain.html, last accessed 28 June 2022 21. Indian Railway Institute of Civil Engineering: Specific Gravity of Aggregates. Gov. India Minist. Railw. 18(1) (2016) 22. IS :2386 (2016) (Part IV ): Methods of test for Aggregates for Concrete, part 4 : Mechanical properties. Bur. Indian Stand. New Delhi. 1–37 23. MoRTH (2013) Specifications for Road Bridge Works 5th Revision. Indian Roads Congr. behalf Govet. India, Minist. Road Transp. Highw. 1, 1–883 24. Chandrappa AK, Biligiri KP (2016) Pervious concrete as a sustainable pavement materialResearch findings and future prospects: A state-of-the-art review. Constr Build Mater 111:262– 274. https://doi.org/10.1016/j.conbuildmat.2016.02.054 25. IS 1199 (1959) Methods of sampling and analysis of concrete. Bur Indian Stand 1–49 26. Chen Y, Wang K, Wang X, Zhou W (2013) Strength, fracture and fatigue of pervious concrete. Constr Build Mater 42:97–104. https://doi.org/10.1016/j.conbuildmat.2013.01.006 27. Kwan AKH, Wong HHC (2008) Effects of packing density, excess water and solid surface area on flowability of cement paste. Adv Cem Res 20:1–11. https://doi.org/10.1680/adcr.2008. 20.1.1 28. Ibrahim A, Mahmoud E, Yamin M, Patibandla VC (2014) Experimental study on Portland cement pervious concrete mechanical and hydrological properties. Constr Build Mater 50:524– 529. https://doi.org/10.1016/j.conbuildmat.2013.09.022
Analysis of Internal Pore Structure of Porous Asphalt Concrete Using X-ray Computed Tomography Images A. Jegan Bharath Kumar, R. Ganeshvijay, P. Murshida, and R. Rajasekar
Abstract In most paving applications in Kerala, dense-graded mixes are used for roadway and parking lot surface, which is impermeable, and rainwater flows over the pavement surface and drains along the side of the roads. A porous asphalt (PA) pavement is a kind of Hot Mix Asphalt (HMA) that contains interconnecting air gaps. This research aims to examine the internal pore structure of the porous asphalt concrete specimen through laboratory experiments and post-processing of X-ray computed tomography (CT) images. The study is also intended to determine the anisotropy of pore characteristics in the horizontal and vertical direction with the absence and presence of clogging material (collected from the sides of the urban roads). Scanned images have been processed to analyze the various parameters such as void area ratio (porosity), size of the voids, percolation number, and tortuosity. Results show that the porous asphalt concrete has an anisotropic pore structure and the obtained porosity value through image analysis matches reasonably with laboratory test results. The porosity in the vertical slices, which facilitates the horizontal flow, is more significant than in the horizontal slices, which facilitate the vertical flow. Moreover, the porosity is reduced by 6.92% in horizontal slices and 1.91% in vertical slices due to the presence of clogging materials. Keywords X-ray CT · Clogging material · Porosity · Percolation number · Tortuosity
A. Jegan Bharath Kumar (B) · P. Murshida KSCSTE-National Transportation Planning and Research Centre (NATPAC), Thiruvananthapuram, Kerala, India e-mail: [email protected] R. Ganeshvijay National Institute of Technology, Tiruchirappalli, Tamil Nadu, India R. Rajasekar College of Engineering, Guindy, Anna University, Chennai, Tamil Nadu, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_4
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1 Introduction Porous Asphalt Mix (PAM) is a kind of Hot Mix Asphalt (HMA) mixture with interconnected air voids, also named as permeable friction course mix or open grade friction courses. As a result of the open grade aggregate gradation, OGFC provides improved surface drainage during rainfall [1]. The rainwater will vertically flow down from the surface. Then it flows horizontally through interconnected air voids and subsequently comes out of the pavement through the edge of the pavement [2]. PAM has higher hydraulic conductivity or permeability than Dense Graded Hot Mix Asphalt (DGHMA) due to its high air void content. The performance life or effectiveness of PMAs will be determined primarily by permeability. The permeability of PFCs is mainly governed by the adequate void space available for drainage [3]. The reduction in the effective air voids content occurs mainly due to the clogging of voids [4, 5], and it is usually evaluated using permeameter in the laboratory and field. The micro-pore structure analysis of the mix reveals the effect of clogging material in the voids and the permeability in the horizontal and vertical directions [6]. A Computed Tomography (CT) scan is a medical imaging technique used in radiology to get a detailed image of the body. CT scanning and subsequent image processing techniques have been widely used to analyze the microstructure characteristics of many homogeneous and heterogeneous specimens, such as concrete and soil [7] specimen. Since, the technology has been widely used to analyze the microstructure characteristics of asphalt mixtures, especially the distribution of air voids [8–11]. The horizontal direction of the PAM exhibited more interconnectivity and pore density than the vertical direction. In addition, the size of the pores was more consistent in the horizontal direction compared to the vertical direction [12]. In porous asphalt mixes, the moisture flow may be separated into horizontal and vertical flows. In particular, the horizontal flow rate is much greater than the vertical flow rate [13]. It is considered that the differential in horizontal and vertical permeability is intimately tied to the distribution and properties of the interconnected pores within the asphalt mixture [12]. However, the number of pores, interconnectivity, and size of pores in the horizontal and vertical orientations in the absence and presence of clogging material have not been examined in the literature. This study aims to analyze the internal pore structure of the porous asphalt concrete specimen by X-ray CT. It is also intended to determine the anisotropy in the pore characteristics in horizontal and vertical directions. Moreover, this study is designed to compare the pore characteristics with the absence and presence of the clogging material.
Analysis of Internal Pore Structure of Porous Asphalt Concrete Using …
41
2 Test Procedure The desired air voids content in the hot mix asphalt is in the range of 3–5%, whereas in the porous asphalt specimens, the targeted air voids content is 18% or greater. This study has been conducted with an aggregate gradation (Fig. 1) selected as per ASTM D7064 [14], which would satisfy the requirements of the porous asphalt mix’s (PAM’s) properties (stone-to-stone contact, voids in coarse aggregate (VCA)) and STYRELF 70 range polymer modified bitumen (PMB) has been used as binder. The optimum binder of the porous asphalt mix has been conducted with a series of experiments such as air voids (using bulk specific gravity, and maximum specific gravity), drain down test, and abrasion test (aged and un-aged abrasion tests) as per IRC 129-2019 [15] and ASTM D7064 [14]. Marshall specimen have been prepared with varying asphalt content ranging from 4.5% to 6% with every 0.5% increment with 50 blows compaction levels on each face of the sample. The OBC value for this mix is obtained as 5%, which satisfies the requirements as per IRC: 129-2019 and ASTM D7064. The maximum and bulk specific gravity is determined in the un-compacted and compacted states, respectively. The determination of the permeability characteristics of the designed PAM is conducted using the falling head method. The clogging behaviour of the PAM mix is conducted by permeability test after spreading eight grams (1 mg/mm2 ) of clogging material above the horizontal surface and allow the water to flow through the pores. The clogging materials are collected from the nearby sides of urban roads and four cycles of clogging. The images were scanned under dry conditions in the absence and presence of clogging material (termed as raw specimen and clogged specimen respectively). Using the X-ray source, the CT images were taken by placing the specimen in both horizontal and vertical directions to obtain the images of horizontal and vertical slices, maintaining the uniform spacing of 0.625 mm between the slices along with the depth of the specimen. This parameter can also be termed as Voxel depth.
Percentage Passing (%)
120 100
Upper Limit G Lower Limit
80 60 40 20 0 0.01
0.10
1.00 Sieve Size (mm)
Fig. 1 Adopted aggregate gradation
10.00
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Fig. 2 Selected ROI of the binary image
The X-ray CT images are analyzed by following the below mentioned procedures. Step1: Selecting the required images and specifying the Region of Interest (ROI is a cropped image area want to filter or operate). The size of ROI was selected to remove the irregularities in the casted samples. Step2: Making the image Binary. Step3: Void area ratio (Porosity), Size of voids. Step4: Euler characteristics (Percolation Number). Step5: Tortuosity. The ROI selected for analyzing horizontal slices is of 90 mm (Fig. 2) diameter, and for analyzing the vertical slices; it was set as 70 mm × 70 mm.
3 Result and Discussion 3.1 Porosity The micro-porosity was calculated as the volume of micro-pores per unit volume of the ROI. In the image processing software, after converting the images into binary format and having specified the ROI, the porosity was determined. It was calculated as the percentage of the area of air voids in the total area of ROI. This is further specified in terms of volume units by multiplying it with the voxel depth (spacing between successive slices). This porosity was determined by software for all the slices individually, and the mean porosity was found. The mean porosity was 18.97% in the horizontal slices and 19.89% in the vertical slices in the raw specimen. From Fig. 3a, the maximum porosity in the horizontal slices is limited to 22%, whereas it goes beyond 24% in the vertical slices. It is clearly observed that the porosity in the vertical slices, which allows fluid flow in the
Analysis of Internal Pore Structure of Porous Asphalt Concrete Using … Horizontal Slices Vertical Slices
70 60 50 40 30 20
Specimen Thickness (mm)
80
80
Specimen Thickness (mm)
43 Horizontal Slices Vertical Slices
70 60 50 40 30 20 10
10
0
0 8
13
18
23
Porosity (%)
(a)
28
33
8
13
18
23
28
33
Porosity (%)
(b)
Fig. 3 Distribution of porosity along the depth of the a raw specimen and b clogged specimen
horizontal direction, is greater than the porosity in the horizontal slices, which allows fluid flow in the vertical direction. The mean porosity of horizontal and vertical slices is 19.43% which matches reasonably with the laboratory results (19.83%). In the specimen with clogging material, the mean porosity was 12.05% in the horizontal slices, which is 6.92% less than that in the raw specimen. And it was 17.98% in the vertical slices, which is 1.91% less than in the raw specimen. It is clear that, due to the effect of clogging, there is a significant reduction in porosity in the horizontal slices but the reduction is less in the vertical slices. From Fig. 3b, the maximum porosity in horizontal slices is reduced to 16%, but it is still 22% in the vertical slices. Hence it can say that the fluid flow in the horizontal direction will be less affected by the clogging material when compared to the flow in the vertical direction. It can also notice that the porosity in the vertical slices is greater than 18% and satisfies the requirement of porous asphalt concrete. In contrast, the porosity in the horizontal slices does not do so. The reduction in porosity is commensurate to the depth of percolation of the clogging material. While comparing the Fig. 3a and b, the findings reveal that the clogging materials are percolated throughout the depth of the specimen. Whereas maximum number of clogged materials are obstructed in the upper depth of 0–10 mm of the specimen.
3.2 Void Size Void size is determined as the average void diameter. It was calculated using the thickness algorithm within the image processing software. In a particular slice, each void is converted into equivalent circles, and the diameter of such circles is used to calculate the mean diameter of voids. Similarly, the overall mean diameter of voids
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and the standard deviation and maximum diameter is determined for all the slices. As shown in Fig. 4, the variation in size of voids (from small to big) is described by varying colours (from blue to yellow). From Fig. 5a and b, it is observed that the size of voids in the vertical slices is significantly greater than that in the horizontal slices, in both raw specimens and specimens with clogging material. The mean diameter of voids in the vertical slices is reduced by 11.4% due to the effect of clogging material. And there are no significant changes (reduced 1.7%) in the size of voids in the vertical slices.
Fig. 4 Voids converted into equivalent circles
Vertical Slices Horizontal Slices
0.771
Std Dev.
0.669
2.111
Mean
0.662
1.870
Mean
1.806
6.531
Maximum
Vertical Slices Horizontal Slices
0.786
Std Dev.
1.775
5.665
Maximum
3.951
4.229 0
2
4
6
Diametre (mm)
(a)
8
0
2
4
Diametre (mm)
(b)
Fig. 5 Size of equivalent circles in the a raw specimen and b clogged specimen
6
8
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45
3.3 Euler Characteristics The connectivity of pore network is commonly expressed based on the Euler number (χ). χ is a function of the number of isolated air voids (N), the number of redundant connections in the air paths or genus (C), and the number of completely enclosed cavities (H). When the Euler number is negative, it is an indication that the air voids are percolated. χ = N −C + H
(1)
χ value for, Raw specimen’s Horizontal slices = −594. Raw specimen’s Vertical slices = −554. Clogged specimen’s Horizontal slices = +198. Clogged specimen’s Vertical slices = −538. From the observed Euler characteristics, we can see that there is no connection of voids in the horizontal slices due to clogging material. The vertical slices still show connectivity even after occurrence of clogging material.
3.4 Percolation Number The percolation of air voids was defined as the relationship between the volume of biggest air void (Vb) and the total volume of air voids in the ROI. This parameter was called as Percolation Number (PN). When this value approaches 1, it means that all the air voids are connected. From Fig. 6, it is clear that due to the clogging materials, hence, based on percolation number also, it is possible to state that the voids in the vertical slices, which facilitate horizontal flow, are less affected by the clogging material when compared to the voids in the horizontal slices, which facilitates the vertical flow. 1.4
Percolation Number
Fig. 6 Percolation number of the specimens
Before Clogging After Clogging
1.2 1
0.973
0.897
0.986 0.976
0.8 0.6 0.4 0.2 0 Horizontal Slices
Vertical Slices
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The percolation number in the vertical slices are more than the horizontal slices. Consequently, flow rates in the horizontal directions are higher, compared to vertical flow rates. Considering the voids size analysis, the void size in the vertical slices found to be substantial, causing anisotropy in the water flow in the porous mixtures. The high flow rate in the horizontal direction produces turbulent state flow, and as a consequence, the influence of clogging material on the porosity of vertical slices is less than that of horizontal slices.
3.5 Tortuosity The macro-pores tortuosity was calculated as the ratio of the total macro-pore length to the total shortest distance between the ends of all macro-pores in the ROI. The macro-pore length was determined using the software, with no pruning of the dead ends. Tortuosity is an indication of the curvature of air voids. For example, Tortuosity of 1.2 indicates that, from a point ‘m’ to another point ‘n’ in the specimen, any fluid has to flow 20% more distance than the shortest distance between ‘m’ and ‘n’ due to the curvature of voids. Air voids are seldom straight lines. Greater tortuosity indicates greater curvature of air voids and the fluid needs to flow more distance. From Fig. 7a and b, it is observed that the curvature of voids is more in the vertical slices and the same trend follows for the clogged specimen as well (Fig. 7c and d). The mean Tortuosity (Fig. 8) is increased in the vertical and horizontal slices, which indicates that the clogging material would significantly change not only the volume of pores but also the curvature of pores.
3.6 Number of Voids By comparing the ranges of x-axes of Fig. 7(a, b) and (c, d), it is able to observe that the skeleton number in Fig. 7(c, d) is more. This indicates that there could be a greater number of voids in the clogged specimen than in the raw specimen. This comparison indicates the necessity of analyzing the number of voids as well. The output of porosity analysis which contains the details of number of voids in each slice by default has been used for this analysis. The shape of ROI of horizontal slices is circular, whereas it is rectangular for vertical slices. Since the shape and area of ROI of horizontal and vertical slices are different, it is appropriate to analyze the number of voids ‘per unit area’ rather than the total number of voids. From Fig. 9, it is observed that the number of voids in the clogged specimen is greater than that in the raw specimen. By comparing this observation with the void size distribution (Fig. 5), it has been noted that the clogging materials splits the voids in the vertical slices, due to which the number of voids got increased (Fig. 9) and the mean size of voids got decreased (Fig. 5). The same trend does hold true for
1.5
1.5
1.4
1.4
1.3
1.3
Tortuosity
Tortuosity
Analysis of Internal Pore Structure of Porous Asphalt Concrete Using …
1.2
1.2
1.1
1.1
1
1 0.9
0.9 0
20
40
0
60
10
(a)
1.7
1.7
1.6
1.6
Tortuosity
1.8
1.5 1.4 1.3
50
1.4 1.3 1.2
1.1
1.1
1
1
0.9
0.9 100
40
1.5
1.2
50
30
(b)
1.8
0
20
Skeliton No
Skeliton No
Tortuosity
47
150
0
200
60
120
180
240
Skeliton No
Skeliton No
(c)
(d)
Fig. 7 Distribution of tortuosity in a horizontal and b vertical slices-raw specimen, and c horizontal and d vertical slices-clogged specimen 1.09
Fig. 8 Mean tortuosity
Tortuosity
1.08 1.07 1.06
1.051
1.05 1.04 1.03
1.078
Before Clogging After Clogging
1.037 1.024
1.02 1.01 1 0.99 Horizontal Slices
Vertical Slices
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No. of Voids/sq.cm
Fig. 9 Number of voids per unit area (sq.cm)
2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
Before Clogging After Clogging 1.364 1.25
Horizontal Slices
1.617 1.385
Vertical Slices
horizontal slices. After clogging, this increased number of voids caused to produce a greater number of tortuosity values than the raw specimen. It has also been noted that the vertical slices have more voids than the horizontal slices before and after clogging.
4 Conclusion In this experimental investigation, image analysis technique has been applied to analyses the X-ray CT scanned images of Porous Asphalt Concrete specimen with the absence and presence of clogging material. Several parameters have been determined using image processing software and the observations are described as follows: . Porosity of the specimen in the vertical slices is significantly greater than that in the horizontal slices, which holds true after the occurrence of clogging materials. . Porosity was reduced by 6.92% in horizontal slices and 1.91% in the vertical slices, after the presence of clogging materials. . Size of voids in the vertical slices is significantly more than that in the horizontal slices, in both raw specimen and the specimen with clogging material. . Based on the Euler number and PN, connectivity of air voids in the horizontal direction was affected by the clogging materials, whereas the vertical slices still had the connectivity in pores even after the presence of clogging material. . The Tortuosity was also found to be more in the vertical slices than the horizontal ones in both raw and clogged conditions. And some fluctuations in the Tortuosity have been observed in the specimen due to the clogging material. . The number of voids per unit area has been greater in the vertical slices when compared to the horizontal slices. It has been seen that the number of voids got increased in the clogged specimen. The reason could be the clogging material intruding into the voids and splitting them From the observations, it has been clear that the Porous Asphalt Concrete has an anisotropic pore structure. The porosity in the vertical slices which facilitates in the horizontal flow is greater than the horizontal slice which facilitates the vertical flow.
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And the pore structure of the vertical slices was less affected by the occurrence of clogging material when compared to the horizontal slices.
References 1. Prithivi SK (2022) Design, construction, and maintenance of open-graded asphalt friction courses. Information Series 115, National Asphalt Pavement Association (2002) 2. Hao F, Chaohui W, Gong Xin Y, Qian C, Luqing L (2021) Design optimization and performance evaluation of the graded friction course with small particle size aggregate. Adv Civ Eng (2021) 3. Abouful M, Garcia A (2017) Factors affecting hydraulic conductivity of asphalt mixture. Nottingham Transportation Engineering Centre (NTEC), University of Nottingham, UK 4. Suresha SN, Varghese G, Ravi Shankar AU (2010) Laboratory and theoretical evaluation of clogging behaviour of porous friction course mixes. Int J Pavement Eng 11(1):61–70 5. Coleri E, Kayhanian M, Harvey JT, Yang K, Boone JM (2013) Clogging evaluation of open graded friction course pavements tested under rainfall and heavy vehicle simulators. J Environ Manag 129:164–172 6. Kutay ME, Aydilek AH, Masad E, Harman T (2007) Computational and experimental evaluation of hydraulic conductivity anisotropy in hot-mix asphalt. Int J Pavement Eng 8(1):29–43 7. Juliana M, Thyagaraj T (2018) Quantification of desiccation cracks using X-ray computed tomography for tracing shrinkage path of compacted expansive soil. Department of Civil Engineering, IIT Madras, India 8. Masad E, Omari AA, Chen H-C (2007) Computations of permeability tensor coefficients and anisotropy of asphalt concrete based on microstructure simulation of fluid flow. Comput Mater Sci 449–459 9. Alvarez AE, Carvajal JS, Reyes OJ, Estakhri C, Walubita LF (2012) Image analysis of the internal structure of warm mix asphalt (WMA) mixtures. TRB 2012 Annual meeting, University of Magdalena, Colombia 10. Huining X, Yiqiu T, Xingao Y (2016) X-ray computed tomography in hydraulics of asphalt mixture. Harbin University of Technology, China 11. Chen J, Yao C, Wang H, Ding Y, Xu T (2018) Expansion and contraction of clogged open graded friction course exposed to freeze-thaw cycles and degradation of mechanical performance. Constr Build Mater 167–177 12. Chen J, Wang J, Wang H, Xie P, Guo L (2020) Analysis of pore characteristics and flow pattern of open-graded asphalt mixture in different directions. J Mater Civ Eng 32(9) 13. Huining X, Yao X, Wang D, Tan Y () Investigation of anisotropic flow in asphalt mixtures using the X-ray image technique. Pore Structure Effect. Harbin University of Technology, China (2017) 14. ASTM D7064 (2013) Standard practice for open graded friction courses 15. IRC:129 (2019) Specification for open-graded friction course
Utilization of Recycled Concrete Dust and Lime as a Binary Blended Filler in Cold Bitumen Emulsion Mix Deepak Prasad, Sanjeev Kumar Suman, and Bhupendra Singh
Abstract The cold bitumen emulsion mix (CBEM) offers environmental benefits and cost-effectiveness compared to previous approaches due to the nearly complete elimination of the heating process and convenience of use. However, its poor early strength must be addressed to increase its use. On the other hand, natural aggregate resource depletion and the generation of construction and demolition (C&D) waste are becoming serious global issues. In order to solve these issues, the present study used recycled concrete dust (RCD), which originated from C&D waste, as a filler in CBEM. In the study, conventional stone dust (SD) filler is replaced by RCD in a proportion of 1–5% of the weight of total aggregates and optimized based on the ITS test. Lime was then blended with an optimized RCD in CBEM. For analysis, Marshal stability, Marshal quotient, indirect tensile strength (ITS), and indirect tensile strength ratio (ITSR) tests were used. The results obtained from these tests were compared with the control CBEM sample, and it was found that the inclusion of RCD and lime by 3% and 2%, respectively, of total aggregate weight as a binary blended filler improved the properties of CBEM and met the requirement for medium traffic volume. Keywords Cold bitumen emulsion mix · Recycled concrete · Lime · Indirect tensile strength
D. Prasad (B) · S. K. Suman Department of Civil Engineering, National Institute of Technology, Patna, India e-mail: [email protected] S. K. Suman e-mail: [email protected] B. Singh Civil and Infrastructure Engineering, Indian Institute of Technology, Jodhpur, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_5
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1 Introduction A traditional asphalt pavement consumes mainly asphalt binder and aggregates. The road construction industry strives to select the most efficient materials when constructing pavement. A sustainable road construction can be achieved by using suitable materials. In order to construct sustainable pavement, cold bitumen emulsion mixes (CBEM) are made with bitumen emulsion as a binder. As they do not use heat in their mixing and compaction process, they are both cost-effective as well as environmentally friendly. They are, however, limited in their application due to their lower early strength. It needs to be cured in order to achieve the strength needed. The water in bitumen emulsion and the water needed for pre-wetting the aggregates may get encapsulated in the mix. This encapsulated water in CBEM is mainly responsible for having low strength. Several researchers are working on different techniques to modify the strength of CBEM, such as using a time–temperature regime for curing, and using cementitious and pozzolanic materials as filler. The main focus of researchers is to either remove or utilize the CBEM’s encapsulated water. The removal of water may be done by applying time–temperature regime for curing purpose [1]. However, finalizing the time–temperature regime for obtaining the required strength was found uncertain. Even some researchers indicated that the full curing of CBEM is not possible. Thus, it needed some other technique so that the CBEM can gain the required strength in short time interval. The use of cement as filler in CBEM which utilizes the encapsulated water for hydration and act as a secondary binder material [2]. Some researchers have used other materials than cement, i.e. flyash [3] and lime [4] as a filler in CBEM and indicated that their pozzolanic and cementing behaviour gave comparable or improved performance compared to conventional mix. Thus, from the previous studies, it may be concluded that using cementitious and pozzolanic materials as fillers enhances CBEM performance in early stage. On the other hand, scarcity of construction materials and disposal of construction and demolition (C&D) waste are serious problems for every construction sectors worldwide. Every country’s socioeconomic development necessitates excessive construction materials, and extreme mining depletes nonrenewable resources and harms the environment. Thus, there is need of secondary source of construction materials, which can fulfil their requirement in different construction sectors. Recycled concrete aggregates (RCA) originating from C&D waste are found as a secondary source for different sectors i.e. cement concrete [5], unbound pavement [6] bituminous concrete pavement [7, 8], etc. However, this usage is lacking in countries such as India and China. The most of the studies have used RCA as a coarse aggregate in bituminous mix. One of the main drawback of using RCA as coarse aggregate is their loosely attached mortar on surface, which hinders the direct contact of binder with virgin aggregate, and easily get separated on applying load [8]. Thus, fine fraction of RCA, termed as recycled concrete dust (RCD) may be utilized in bituminous mix. A number of studies have used RCD as a filler in bituminous mixes and found comparable results in terms of resilient modulus [9].
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53
The use of RCA in CBEM is very limited, some studies even used coarse RCA in CBEM [10]. A variety of RCA sizes must be considered in utilization. In this study, RCD was used as a filler in CBEM. In the study, conventional stone dust (SD) filler was replaced by RCD in a proportion of 1–5% of the weight of total aggregates and optimized based on the ITS test. For further modification lime was used with optimum RCD as a binary blended filler in CBEM. Objective of this study is to analyze the effect of RCD and lime, as fillers, on the strength and moisture susceptibility of CBEM.
2 Materials In this present study single sourced aggregates from local quarry of Bihar, India, were used. Aggregates were originated from basaltic type of rock. Basaltic stone dust, RCD and lime were used as filler in CBEM. These fillers were finer than 0.075 mm in size. Cationic slow setting (CSS-2) emulsion having residual bitumen content of 58.3% was used as binder for mix preparation. Potable water was used for the purpose of enhancing the workability of the mix before the application of binder. It provides a wet aggregate surface to the binder. All the required properties of materials used in this study are enlisted in Table 1.
3 Experimental Programs The experimental plan of this study is shown in Fig. 1. The inferiority of CBEM is mainly due to the less adhesiveness and cohesiveness of bitumen emulsion. Thus, for analyzing CBEM, there is need of an appropriate parameter, which directly indicates the binding properties of CBEM. The tensile property of mix may be considered for the same [21]. In this study the determination of design parameters and optimization of RCD in CBEM were done by conducting ITS test.
3.1 Mix Design and Specimen Preparation Dense graded bituminous concrete, grading-1 (BC-1) as per MoRTH [11], was used as the aggregate gradation in the study for the preparation of CBEM (see Fig. 2). For the design of CBEM, marshal mix design, guidelines given by MS-14 [22] was adopted. In this study, the marshal stability was replaced with indirect tensile strength test for determining various design parameters. This study used 50 blows at each end of their Marshal sample for compaction, confirming the Marshal method criteria for medium traffic volume [23]. CBEM prepared with stone dust as filler material was considered as control mix (unmodified mix). The modification of the
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Table 1 Properties of materials used Materials
Properties
Values
Standard used
Coarse aggregates
Impact value (%)
13.05
IS 2386 (Part IV) [12]
L. A. abrasion value (%)
17.14
IS 2386 (Part IV) [12]
Water absorption (%)
0.69
IS 2386 (Part III) [13]
Specific gravity
2.71
IS 2386 (Part III) [13]
Combined flakiness and elongation 20.45
IS 2386 (Part I) [14]
Water absorption (%)
0.98
IS 2386 (Part III) [13]
Specific gravity
2.68
IS 2386 (Part III) [13]
Fillers stone dust RCD Lime Specific gravity
2.68 2.45 2.38
IS2720 (Part III) [15] IS2720 (Part III) [15] IS2720 (Part III) [15]
Residue on 600 mic (%)
0.045
IS 8887 [16]
Viscosityat 25 °C, Saybolt furol viscometer (seconds)
49
IS 3117 [17]
Storage stability (%)
17.14
IS 8887 [16]
Particle charge
(+)ve
IS 8887 [16]
Test on residue Specific gravity Penetration at 25 °C Ductility at 27 °C
1.01 78.5 74
IS 1202 [18] IS 1203 [19] IS1208 [20]
–
–
–
Fine aggregates
Binder Bitumen emulsion (CSS-2)
Water
CBEM was done by partially replacing the stone dust with RCA by 1, 2, 3, 4, and 5% by weight of total aggregates. For further modification 2% lime was added in CBEM containing optimized RCD. A lime modified CBEM was also prepared by replacing stone dust with 2% lime and compared. In this study, total four type of mix were prepared and abbreviated as M0, ML, M-X, and M-XL for Control CBEM, lime modified CBEM, CBEM containing X% RCD filler (RCD modified CBEM), and CBEM containing X% RCD and 2% lime as filler (Lime-RCD modified CBEM), respectively. The effect RCD and lime as fillers in CBEM was analyzed by determining the marshal stability, marshal quotient, indirect tensile strength, and indirect tensile strength ratio as per ASTM D6927, ASTM D6931, and AASHTO T283 respectively.
Utilization of Recycled Concrete Dust and Lime as a Binary Blended … Coarse & fine aggregates
55
Bitumen emulsion (CSS)
Fillers (SD, RCA, Lime)
Conventional test
• . . .
Mix design and their categorization Control CBEM (unmodified) Lime modified CBEM (replacement of SD with hydrated lime by 2 % by weight of total aggregate) RCD Modified CBEM (replacement of SD with RCD from 1-5% by weight of total aggregates) RCD-lime Modified CBEM (replacement of SD with optimized RCD and 2 % hydrated lime)
Optimization of RCD filler in CBEM
. . .
Experimental study Marshal stability Marshal quotient (MQ) Indirect tensile strength (ITS) & Indirect tensile strength ratio (ITSR)
Conclusion & recommendation
Fig. 1 Experimental flow chart of study 100
Fig. 2 Gradation of aggregates
Upper limit
% Passing
90 80
Lower limit
70
Adopted
60 50 40 30 20 10 0 26.5
19
13.2
9.5
4.75
2.36
1.18
0.06
0.03
0.015 0.075
Sieve sizes (mm)
4 Results and Discussions 4.1 Mix Design of CBEM For CBEM mix design four parameters i.e., initial residual bitumen content (IRBC), optimum premixed water content (OPWC), optimum total liquid content at compaction (OTLC), and optimum residual bitumen content (ORBC) were calculated as per MS-14 [22]. The IRBC, OPWC, OTLC, and ORBC were found to be
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D. Prasad et al.
6.6%, 2.5%, 6.86%, and 6.1% respectively. These all parameters were kept constant for all type of mix to develop a better understanding of isolate effect of each filler in CBEM.
4.2 Optimization of RCD Filler in CBEM The variation of ITS result with different proportions of RCD in CBEM is shown in Fig. 3. The ITS value of control CBEM was found to be 205 kPa. Replacing stone dust filler with RCD, efficiently modify the CBEM. Up to 3% RCD, the ITS value was found increasing, followed by decreasing trend. The CBEM containing 3% RCD filler increased the ITS value by 30% compared to those of control CBEM. The main credit for the increasing trend of ITS result on increasing RCD filler in CBEM goes to their lower specific gravity than stone dust. This study replaced stone dust with RCD filler based on weight percentage. At the same weight, the RCD filler attains a higher volume than stone dust, resulting in higher adsorption to the binder [26]. After a 3% dose of RCD filler in CBEM, the balling action of the bitumen emulsion comes into play due to the highly increased filler content. This action was intensified with a further increase of RCD in CBEM. It complicated the mixing and compaction process, leading to the improper coating of bitumen emulsion on aggregates, causing a decreasing trend of ITS results. XRD test was performed on stone dust and RCD filler to know their mineral compositions (see Fig. 4). From Fig. 4, it was found that stone dust mainly contains amphibole, anorthite, albite, and quartz, and RCD fillers mainly contain calcite, albite, and quartz. The presence of highly proportion of albite, anorthite, and quartz negatively affect the bituminous mix due to their poor adhesive property to the bitumen, where calcite can form a strong bond with bitumen in presence of water, and improve the bituminous mix [27]. However, the albite can form strong bond with bitumen in dry condition, but it quickly gets break in the presence of water [27]. Due to presence of water in CBEM over a period, albite mineral present in SD, may not be 300
ITS (kPa)
Fig. 3 Optimization of RCD in CBEM
250
200
150 M0
M1
M2
M3
M4
M5
Utilization of Recycled Concrete Dust and Lime as a Binary Blended …
57
Fig. 4 XRD of (a) Stone dust, (b) RCD
able to form a strong bond with bitumen, and results a lower value of ITS of control CBEM. The incorporation of RCD filler increased the calcite mineral in the mix and improved the adhesive property with bitumen. However, the excessive incorporation of RCD in CBEM increased the quartz and albite in the mix and decreased the ITS value. Thus, the increasing ITS trend on up to 3% incorporation of RCD in CBEM might be due to the lower specific gravity of RCD compared to SD and the presence of calcite mineral in RCD filler. The decreasing trend of ITS result after higher incorporation of RCD (greater than 3%) in CBEM might be due to balling effect or the presence of quartz and albite minerals in RCD filler.
4.3 Marshal Stability and Marshal Quotient (MQ) Figure 5 shows the variation in marshal stability and marshal quotient values of different mixes. The minimum required value of marshal stability for medium traffic is 5.338 kN as per MS-2 [23]. Where the marshal quotient (MQ) values of 2 and 5 kN/mm were considered as the required minimum and maximum values as per MoRTH [11]. The control mix (M0) was unable to achieve the required marshal stability and marshal quotient values in early stage. The control mix had a 5.01 kN marshal stability value, which was improved by almost 12% by incorporating 3% RCD filler in CBEM. However, M3 barely achieved the minimum required value of marshal stability. Where, in case of MQ, a slight increment was found in the case of RCD modified CBEM compared to control CBEM. This improvement is credited to the lower specific gravity and calcite mineral of RCD, which increases the stiffness and improve the adhesive property in the mix, respectively. When lime was added to the mix, the RCD-lime modified CBEM enhanced its stability and MQ value by more than 60% and 120%, respectively, when compared
D. Prasad et al. 6
10
5 kN/mm (Max)
8
MQ (kN/mm)
Marshal stability (kN)
58
6 4 2 0 M0
M3
ML
4
2 kN/mm (Min)
2
0
M3L
M0
M3
(a)
ML
M3L
(b)
Fig. 5 Variation of a Marshal stability and b Marshal quotient values of different mix Fig. 6 XRD of lime Intensity (counts)
8000
8
7
5- Calcite (CaCO3) 6- Portlandite (Ca(OH)2) 7- Calcium Oxide (CaO) 8- Dolomite (CaMg(CO3)2)
7000 6000 6
5000 4000 3000
5
7 5
2000
6
8
1000 0
6
0
10
20
30
40
50
5
60
70
2θ
to the control mix, and met the requirements. However, it gave a very slightly higher value than the lime-modified CBEM. The XRD of lime is shown in Fig. 6. It was found that lime mainly contains calcium oxide (CaO), portlandite (Ca(OH)2 ), and dolomite (CaMg(CO3 )2 ). The hydration of CaO in the presence of water in the mix form Ca(OH)2 and it get carbonated with atmospheric CO2 and gained cementing property in the mix [28]. These hydration and carbonation improved the marshal stability and marshal quotient of CBEM with the incorporation of lime in the mix. As the lime utilized moisture from the mix, albite present in RCD filler plays an important role in improving the marshal stability of RCD-lime modified CBEM by making a strong bond with bitumen in a dry state.
4.4 Indirect Tensile Strength (ITS) and Indirect Tensile Strength Ratio (ITSR) Figure 7 shows the variation of indirect tensile strength (ITS) and indirect tensile strength ratio (ITSR) of different mixes. The ITS and ITSR results were found to have a similar trend to marshal stability and MQ value, however the ITSR value
500
100
400
80
ITSR (%)
ITS (kPa)
Utilization of Recycled Concrete Dust and Lime as a Binary Blended …
300 200 100
59
80 % (Min)
60 40 20
0 M0
M3
ML
M3L
(a)
0
M0
M3
ML
M3L
(b)
Fig. 7 a ITS, and b ITSR of different mix
of RCD-lime modified CBEM was found lower than lime modified. The ITS value of control CBEM was found to be 205 kPa. Incorporating 3% RCD improved the ITS value by around 30% of the control mix. This improvement was mainly due to the presence of calcite in the RCD filler, which improved the adhesive property of bitumen to the aggregates. On incorporating lime into the mix, the RCD- lime modified CBEM was found to have improved ITS value by around 110% of control CBEM and about 60% of RCD modified CBEM. As already mentioned, CBEM contains some extent of moisture in the early stage. Thus, only calcite, present in RCD filler, was found to make a strong bond with bitumen in the RCD modified CBEM, while albite and quartz were found to make weak bonds in this mix during the early stages. As the moisture decreased due to the hydration process with the addition of lime, the albite presents in the RCD filler made a strong bond in the RCD-lime modified CBEM. In case of moisture susceptibility, the use of RCD and lime significantly improved the ITSR value by above 120% compared to those of control mix, but it barely achieved the minimum required value. The interaction between lime and bitumen plays an important role in improving the adhesion between siliceous particle and bitumen in presence of water. The bitumen is comprised of both cationic and anionic surfactants, in which only cationic surfactant make strong bond with silica atom present in the mineral like quartz and albite. The remaining one i.e., anionic surfactant rests in free state, and it is easily replaced with water. On incorporating lime in the mix, hydrated lime contact with aggregates, the calcium ions get penetrated on the aggregate surface and form water insoluble salt by making bond with anionic surfactant of bitumen. The bare achievement of the minimum required ITSR of RCDlime modified CBEM is mainly due to their moist conditioning, which reduces the adhesion of bitumen to the albite minerals present in SD and RCD.
60
D. Prasad et al.
5 Conclusions Present study examined the influence of RCD filler in CBEM. The conventional filler (SD) was replaced by RCD from 1 to 5%. ITS was used to optimized the RCD filler. For further modification of CBEM, lime was used. Marshal stability, Marshal quotient, ITS, and ITSR were evaluated. Following conclusions were made: . The incorporation of RCD fillers into CBEM first increased the ITS value, reaching the highest ITS value at 3% incorporation, but then it declined. Thus, 3% RCD filler is the optimal dosage in CBEM. . Incorporating RCD filler into the CBEM improved marshal stability, marshal quotient, ITS, and ITSR values compared to the control CBEM. Nevertheless, the RCD modified CBEM barely met the limit during early stage. . Using 2% lime and 3% RCD as a binary blended filler in CBEM further improved marshal stability, marshal quotient, ITS and ITSR values versus a control CBEM and met the required limit for medium traffic. The current study was conducted only for early stages. It can be extended further by using curing. Once the curing process is applied, the control and RCD modified CBEM may meet the specified limit.
References 1. Prasad D, Suman SK (2023) Impact of curing on the volumetric and mechanical properties of cold bitumen emulsion mix. Eng Res Express 5(2):025037 2. Al Nageim H, Al-Busaltan SF, Atherton W, Sharples G (2012) A comparative study for improving the mechanical properties of cold bituminous emulsion mixtures with cement and waste materials. Constr Build Mater 36:743–748. https://doi.org/10.1016/j.conbuildmat.2012. 06.032 3. Prasad D (2022) Utilization of fly ash as a filler in cold bituminous emulsion mix. 3:491–501. https://doi.org/10.1201/9781003222910-51 4. Jain S, Singh B, Saboo N (2022) Use of lime as filler in cold mix asphalt. Lect Notes Civ Eng 172:775–785. https://doi.org/10.1007/978-981-16-4396-5_68 5. Prasad D, Pandey A, Kumar B (2021) Sustainable production of recycled concrete aggregates by lime treatment and mechanical abrasion for M40 grade concrete. Constr Build Mater 268:121119 6. Poon CS, Chan D (2006) Feasible use of recycled concrete aggregates and crushed clay brick as unbound road sub-base. Constr Build Mater 20:578–585. https://doi.org/10.1016/j.conbui ldmat.2005.01.045 7. Singh B, Prasad D, Kant RR (2021) Effect of lime filler on RCA incorporated bituminous mixture. Clean Eng Technol 4:100166 8. Prasad D, Singh B, Suman SK (2022) Utilization of recycled concrete aggregate in bituminous mixtures: a comprehensive review. Constr Build Mater 326:126859. https://doi.org/10.1016/J. CONBUILDMAT.2022.126859 9. Rochlani M, Falla GC, Wellner F, et al (2020) Feasibility study of waste ceramic powder as a filler alternative for asphalt mastics using the DSR. Road Mater Pavement Des 1–13. https:// doi.org/10.1080/14680629.2020.1778508
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10. Jain S, Singh B (2021) Use of recycled concrete aggregate in cold bituminous emulsion mix. In: Green and Intelligent Technologies for Sustainable and Smart Asphalt Pavements: Proceedings of the 5th International Symposium on Frontiers of Road and Airport Engineering. CRC Press, Delft, Netherlands (IFRAE), p 320 11. MORT&H (2013) Specification of Road and Bridge Work (Fifth Revision). New Delhi, India 12. IS 2386 (Part IV) (1963) Indian Standard Method of Test for Aggregates for Concrete, Part IV : Mechanical Properties. New Delhi, India 13. IS 2386 (Part III) (1963) Methods of test for aggregates for concrete, Part 3: Specific gravity, density, voids, absorption and bulking. New Delhi, India 14. IS 2386 (Part I) (1963) Methods of Test for Aggregates for Concrete, Part I: Particle Size and Shape. New Delhi, India 15. IS 2720 (Part-III) (1980) Specific Gravity of Soil as per IS: 2720 Part-3 (1980) with Procedure, Lab Report, Formula. New Delhi, India 16. IS 8887 (2004) Bitumen Emulsion for Roads (Cationic Type). New Delhi 17. IS 3117 (2004) Bitumen Emulsion for Roads and Allied Applications (Anionic Type)Specification. New Delhi, India 18. IS 1202 (1978) Indian Standard Method for Testing Tar and Bitumen: Determination of Specific gravity. New Delhi, India 19. IS 1203 (1978) Indian Standard Method for Testing Tar and Bituminous Materials : Determination of Penetration. New Delhi, India 20. IS 1208 (1978) Indian Standard Method for Testing Tar and Bituminous Materials : Determination of Ductility. New Delhi, India 21. Dulaimi A, Al Nageim H, Ruddock F, Seton L (2017) High performance cold asphalt concrete mixture for binder course using alkali-activated binary blended cementitious filler. Constr Build Mater 141:160–170 22. MS-14 (1997) Asphalt Cold Mix Manual. Laxington, USA 23. MS-2 (2014) Asphalt Mix Design Methods (7th Edition). Laxington, USA 24. ASTM D6931 (2012) Standard Test Method for Indirect Tensile (IDT) Strength of Bituminous Mixtures. Washington DC 25. AASHTO T 283 (2014) Standard Method of Test for Resistance of Compacted Asphalt Mixtures to Moisture-Induced Damage. Washington, D.C 26. Chen M, Lin J, Wu S (2011) Potential of recycled fine aggregates powder as filler in asphalt mixture. Constr Build Mater 25:3909–3914. https://doi.org/10.1016/J.CONBUILDMAT.2011. 04.022 27. Zhang J, Apeagyei AK, Airey GD, Grenfell JRA (2015) Influence of aggregate mineralogical composition on water resistance of aggregate-bitumen adhesion. Int J Adhes Adhes 62:45–54. https://doi.org/10.1016/J.IJADHADH.2015.06.012 28. Singh B, Jain S (2021) Effect of lime and cement fillers on moisture susceptibility of cold mix asphalt. Road Mater Pavement Des 1–17. https://doi.org/10.1080/14680629.2021.1976254
Development of Shakedown Criteria for Prediction of Permanent Deformation Characteristics of Modified UGMs with THF Steel Slag Ashish Mishra
and Sunny Deol Guzzarlapudi
Abstract The characterization and prediction of plastic deformation behavior of Unbound Granular Materials (UGMs) are important under transient vehicular loads. UGMs majorly contribute to load distribution from surface layer to subgrade. Hence, it is necessary to use materials that can withstand the load repetitions without incremental collapse. The main factors that affect the permanent deformation behavior of UGMs are material characteristics such as gradation, density, aggregate type, shape, texture, angularity, and moisture content. Further, stress related factors such as deviator and induced cell pressure, number of cycles, loading frequency, and load duration are considered. Repeated Load Triaxial (RLT) tests have been performed on the selected materials to assess the deformation characteristics for its feasibility as UGM in pavement base and subbase layers. Since the existing shakedown criteria are not applicable for locally available materials such as Twin-Hearth Furnace (THF) Steel slag aggregate and conventional aggregate, therefore, in this Study, conventional aggregates are replaced with THF steel slag, and its permanent deformation properties are characterized with the help of RLT test. The new shakedown boundaries are defined based on the nature of the curve developed between plastic deformation (PD) and the number of loading cycles. The locally tested UGMs were assigned Range A, B, and C based on the curve angle between PD and the logarithmic number of load cycles. The selected materials can be assigned as Range A when PD < 1.5%, Range B when 1.5% < PD < 3%, and Range C when PD > 3% based on the curve slope. Keywords Shakedown theory · Unbound granular materials · Repeated load triaxial test
A. Mishra · S. D. Guzzarlapudi (B) Department of Civil Engineering, National Institute of Technology, Raipur, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_6
63
64
A. Mishra and S. D. Guzzarlapudi
1 Introduction The plastic deformation commonly termed as permanent deformation accumulating progressively with vehicular transient load repetition results in rutting distress in the pavement [1]. In the current scenario, developing countries like India primarily focused on utilizing non-conventional bound granular materials (BGMs) or unbound granular materials (UGMs) due to steep shortfall of traditional UGMs. Under the flagship program of innovative technology scheme by Government of India numerous categories of roads were being constructed by using non-conventional BGMs and UGMs. Often, low volume roads experience rutting failure due to the aggregation of permanent deformation in both bound and unbound layers [2]. The inflation of plastic strain in unbound aggregate base and subbase layers depends on load related factors and material properties [3]. It is the primary distress in the flexible pavement for UGMs; therefore, understanding the plastic deformation behavior of UGMs helps in accurately estimating and predicting the performance of an unbound base and sub base layer [4]. Numerous researchers agreed that plastic deformation (PD) of UGMs is an irrecoverable strain that may lead to rutting in flexible pavements [5]. Currently, the permanent deformation characteristics of UGMs is being in the laboratory with the help of the Repeated Load Triaxial Test (RLTT) [6]. The Shakedown concept is applied to predict the plastic deformation of UGMs. The mechanical characterization of UGMs is more critical and will help to know their strength and stiffness characteristics. The UGMs used as base, and sub-base material had some resilient response with the application of maximum load level, and that must be known so that material cannot reach a plastic deformation state. Werkmeister et al. [7] found in his research that a critical threshold stress level occurs between the stable and unstable conditions in the pavements, and it is represented as shakedown limit. Therefore, it is necessary to understand the critical stress level of UGMs this helps in selecting material for the base and sub-base layer and reducing the thickness of pavement as per material load-carrying capacity. Therefore, it is easy to understand the reason for various battles between the multiple stakeholders in pavement construction over the value of this parameter. Its wrong estimation leads to errors that result in over-designed or under-designed layer thicknesses. Sharp [8] initially applied the shakedown theory in pavement design. Werkmeister et al. [7] had defined Shakedown limits, and three different permanent deformation ranges have been categorized as Range A: plastic shakedown (the response of material is only plastic for a limited number of load repetitions, further after post compaction the material depicts resilient form), Range B: Creep shakedown (the permanent strain rate level decreases to a lower limit and then achieves nearly a steady level during the primary stage), and Range C: incremental collapse (the permanent strain rate decreases slowly, and further, the accumulation of permanent strain does not end). The generic representation of shakedown concept based on permanent deformation characteristics is shown in Fig. 1. Gu et al. [5] found that the existing shakedown criteria may be unsuitable for the locally available UGMs of Texas and developed new shakedown criteria for
Development of Shakedown Criteria for Prediction of Permanent …
65
Fig. 1 Concept of shakedown theory
flexible base materials in Texas. Chen et al. [9] developed new shakedown criteria for reinforced samples and updated Werkmeister et al. [7] criteria and found suitable for the samples with geogrids. Qian et al. [10] also developed new method that is developed based on an effective cyclic stress ratio since the existing criteria is for non-cohesive materials (Aggregates or sand) only. A new shakedown criteria was developed by [11] for UGMs of Victoria, Australia, the material characterization was done on the basis of curve slope angle between PD and logarithmic number of load cycles such as (0° < Range A < 22.5°, 22.5° < Range B < 45°, 45° < Range C < 90°). Thus, based on the previous literature studies the shakedown criteria is for limited number of load repetitions and for specific type of material. The existing shakedown criteria was developed based on the PD measurement at single stage stress level. Limited studies were reported on developing shake down criteria upon considering multi stage stress levels [11]. THF steel slag is locally available and can partially replace the conventional aggregates. Therefore, new shakedown criteria is needed to characterize such nonconventional sustainable materials to be used in base and sub-base layers that can withstand the load repetitions without exceeding the elastic limit of the material. In this Study, the shakedown limit has been decided based on a limited number of load repetitions applied on conventional stone aggregates and Twin Hearth Furnace (THF) steel slag in distinct combinations proposed to use in granular layers. The shakedown limits of Werkmeister’s [7] and Gu [12] criteria need to be reassessed for the proposed materials based on the multi-stage stresses in RLT tests, as shown in Table 1.
66
A. Mishra and S. D. Guzzarlapudi
Table 1 Shakedown range boundaries Shakedown criteria
Ranges
Boundaries of the shakedown ranges
Werkmeister et al. [7]
A
P D 5000 − P D 3000 < 4.5 × 10−5
B
4.5 × 10−5 < P D 5000 − P D 3000 < 4.5 × 10−4
C
P D 5000 − P D 3000 > 4.0 × 10−4
A
P D 5000 − P D 3000 < 6.0 × 10−5
B
6.0 × 10−5 < P D 5000 − P D 3000 < 6.0 × 10−4
C
P D 5000 − P D 3000 > 6.0 × 10−4
Gu et al. [12]
P D 5000 and P D 3000 are the accumulated PDs at the 5000th and 3000th load cycle.
2 Materials and Experimental Investigations 2.1 Materials The Twin Hearth Furnace (THF) steel slag as UGMs used in this Study was collected from Bhilai steel Plant (BSP) Chhattisgarh dump site. The conventional natural stone aggregate used was collected from local quarry. The Study comprises of combination of Conventional natural stone aggregate and THF steel slag aggregate as given in Table 2. The physical properties of the selected material combinations were tested and the corresponding results are depicted in Table 3. The particle size distribution of material combination is given in Fig. 2. Table 2 Material combinations for the study S.no
UGMs mix type
Combination
Code
1
Conventional aggregates (100%)
Good quality
CA1
Poor quality
CA2
THF Steel slag (100%)
Vesicular without pocket steel slag
SS1
Vesicular with pockets steel slag
SS2
50% good quality aggregates + 50% Vesicular without pocket steel slag
CA1SS1
50% good quality aggregates + 50% Vesicular with pocket steel slag
CA1SS2
50% poor quality aggregates + 50% Vesicular without pocket steel slag
CA2SS1
50% poor quality aggregates + 50% Vesicular with pocket steel slag
CA2SS2
2 3
4
50% Conventional aggregate: 50% THF Steel slag
50% Conventional aggregate: 50% THF Steel slag
Development of Shakedown Criteria for Prediction of Permanent …
67
Table 3 Physical properties of study UGMs CA1
CA2
SS1 SS2
CA1SS1 CA1SS2 CA2SS1 CA2SS2
Compaction (modified) 2.28 *MDD (g/cc)
2.11
2.56 2.25
2.41
2.28
2.37
2.25
*OMC (%)
8.40
9.60
9.60 10.80 9.00
9.80
9.20
10.30
Liquid limit (%)
22.4
23.2
29.7 33.4
28.3
30.4
34.2
35.8
Plasticity Index
3
2
–
–
–
–
–
–
D10 (mm)
0.2
0.9
0.2
1
0.2
0.12
0.12
0.16
D30 (mm)
1.6
3.5
2
2.8
0.8
0.9
0.6
0.45
D50 (mm)
5.1
14
8
11
2
4
2.8
1.5
D60 (mm)
8
17
16
16
3
12
3
2.5
Fines (< 0.075 mm) %
4.6
0
0.4
0.6
0.65
0.34
0.43
0.54
Coefficient of Uniformity (Cu )
15.83 40.00 67.8 55.17 22.50
15.00
12.77
15.62
Coefficient of curvature (Cc )
11.22 1.60
0.09 5.60
3.40
1.06
3.47
0.50
Indian soil classification system
GW
GW GP
GW
GP
GW
GP
Physical Properties
GP
Cumulative Percentage passing (%)
Note * MDD: Maximum dry density, OMC: Optimum moisture content 100 90 80 70 60 50 40 30 20 10 0 0.01 SS1 CA2SS1
0.1
1 IS Sieve size (mm) SS2 CA2SS2
CA1SS1 CA1
10
100 CA1SS2 CA2
Fig. 2 Particle size distribution of the study materials
2.2 Laboratory Investigations Detailed laboratory investigations were performed for the selected study materials. The permanent deformation of the UGMs is investigated by RLTT as per the guidelines suggested by AASHTO T 307–99. The testing procedure consists of distinct repeated deviator stress (σd ) levels & constant confining pressure (σ3 ) levels, as shown in Table 5. The test programme followed AG-PT/T053. The specimen was
68 Table 4 RLTT (PD) test sequence
A. Mishra and S. D. Guzzarlapudi
Material
Moisture content (%) OMC
Table 5 Deviator Stress and confining pressure levels for RLTT (PD) Test
Dry density (gm/cc)
(OMC + 2)
MDD
CA1
8.40
10.40
2.28
CA2
9.60
11.60
2.11
SS1
9.60
11.60
2.56
SS2
10.80
12.80
2.25
CA1SS1
9.00
11.00
2.41
CA1SS2
9.80
11.80
2.28
CA2SS1
9.20
11.20
2.37
CA2SS2
10.30
12.30
2.25
Stages
σ3 (kPa)
σd (kPa)
Number of cycles
1
50
350
10,000
2
50
450
10,000
3
50
550
10,000
cylindrical with a diameter of 100 mm and a height of 200 mm. The number of samples prepared was three for each combination with varying moisture content, as shown in Table 4.
3 Experimental Results The RLTT results for the study materials were discussed, which portrays the Permanent deformation behavior of Conventional aggregates and THF steel slag. The presence of sufficient moisture content in UGMs is very important to achieve a maximum density, as water plays a key role and acts as a lubricant in the unbound materials that enables to roll or slide on each other during the process of compaction in order to achieve MDD. Therefore, the Study concentrates on the UGMs behavior under moisture content variation, and it is tested at OMC and above OMC, as shown in Table 4. The Study does not include the variation below OMC because, in the field, it is difficult to compact UGMs below OMC, which results in workability issues and requires more effort to achieve MDD. Table 6 shows the permanent deformation characteristics of UGMs at different moisture content and at different load cycles. The permenant deformation is increasing with moisture content on wet of optimum side. As shown in Table 6, CA1SS1 has a PD of 2.54, 3.66 at 9% & 11% moisture content corresponding to 30,000 load cycles, respectively. Similarly, CA2SS1 has a PD of 6.09, 7.03 at 9.2 & 11.2% moisture content corresponding to 30,000 load cycles, respectively. The increase in moisture content increases permanent deformation; this
Development of Shakedown Criteria for Prediction of Permanent …
69
is majorly due to fines that increase the plasticity. The fines are susceptible to moisture content, and due to increase in surface area results in more moisture consumption and an increase in permanent deformation. This behavior is consistent with the earlier studies conducted by [13, 14]. The stress level is a critical factor that influences the PD behavior of UGMs. In this Study, the deviator stress levels considered is given in Table 5. The effect of stress variation is seen in the permanent deformation behavior of UGMs at different load cycles, as shown in Fig. 3, For example, SS1 had PD values of 0.95, 1.43, & 2.04% under deviator stresses of 350, 450, & 550 kPa, respectively, and this behavior is seen in previous studies as [15, 16]. Therefore, at each load, repetition generates small deformation, which accumulates and results in permanent deformation. As shown in Fig. 4 SS1 had an increase in PD of 0.95−2.04% when deviator stress was increased from 350 to 550 kPa, respectively. Table 6 Permanent deformation of UGMs at different moisture content at varying loads OMC (%)
UGM
OMC +2 (%)
Plastic deformation at OMC%
Plastic deformation at OMC + 2 (%)
10,000 load cycles
10,000 load cycles
20,000 load cycles
30,000 load cycles
20,000 load cycles
30,000 load cycles
CA1
8.4
10.4
0.85
1.23
1.51
1.35
1.88
1.97
CA2
8.6
10.6
4.34
6.78
–
5.67
7.45
–
SS1
9.6
11.6
0.95
1.43
2.04
1.23
1.98
3.32
SS2
9.8
11.8
2.89
4.88
–
3.56
5.64
–
CA1SS1
9
11
1.14
1.86
2.54
2.12
2.55
3.66
CA1SS2
9.6
11.6
1.35
2.2
2.92
2.87
3.56
3.56
CA2SS1
9.2
11.2
2.29
3.41
6.09
3.67
4.14
7.23
CA2SS2
9.3
11.3
3.66
6.01
–
4.88
6.98
–
CA2, SS2, CA2SS2 sample had failed before 30,000 load cycles
Permanent Deformation (%)
*
8 7 6 5 4 3 2 1 0
At 20,000 cycles
At 10,000 cycles
300
350
400
At 30,000 cycles
450
500
550
Deviator Stress σd (kPa) CA1
CA2
SS1
SS2
CA1SS1
CA1SS2
CA2SS1
CA2SS2
Fig. 3 Effect of varying deviator stress levels on PD of UGMs at MDD & OMC
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A. Mishra and S. D. Guzzarlapudi
Cumulative Permanent Deformation (%)
70 10 9 8 7 6 5 4 3 2 1 0
σd = 350 kPa
σd = 550 kPa
σd = 450 kPa Fail
0
5
10
15
Fail
20
Fail
25
30
Number of load cycles (N) (x 103) CA1
CA2
SS1
SS2
CA1SS1
CA1SS2
CA2SS1
CA2SS2
Fig. 4 Effect of varying number of load cycles on PD of Study UGMs
4 Proposed Shakedown Criteria The new shakedown criteria and limits are proposed based on plastic deformation characteristics. The boundaries are defined based on the nature of the curve between plastic deformation (PD) and the number of loading cycles. Further, these new shakedown criteria were compared with the criterion of [5, 7, 11]. The locally tested UGMs were assigned as Range A, Range B, and Range C based on the curve angle obtained between PD vs. the Logarithmic number of load cycles. Table 6 shows the nature of permanent deformation characteristics of different UGMs at different deviator stress level and load cycles. Figure 5 shows the PD curve for studied UGMs at 350 kPa deviator stress and at 10,000 load cycles, such as CA2 and CA2SS2 had a Range C curve which indicates a total collapse in comparison to rest of UGMs which shows Range A & Range B curve at OMC. Table 8 shows the comparison between different shakedown criteria with the proposed criteria at 10,000 load cycles. The UGMs showing PD behavior of Range A & Range B can be used for pavement design, but UGM showing PD curve similar to Range C should be neglected. The slope of the curve between PD and logarithmic number of load cycles is the principle behind new shakedown criteria. The inflection point is the point of the curve where the beginning of the failure process is identified. As shown in Fig. 6 the shakedown boundaries are defined based on slope angle subtended by the PD curve with the horizontal. Thus, as shown in Table 9, shakedown ranges can be defined as per slope angle, such as Range A as angle < 20°, Range B as angle between 20–40°, and Range C as angle 40° < Range C < 90°. As shown in Table 7, the material characteristics are changes as per increase in deviator stress and load cycles. The UGMs are tested at 350 kPa deviator stress at 10,000 load cycles results in CA2 and CASS2 are in Range C, SS2 and CASS1 are in Range B, and CA1, CA1SS1, and CA1SS2 are in Range A. The increase in deviator stress to 450 kPa at 20,000 load cycles results in CA2 and CA2SS1 UGMs reach to incremental collapse i.e., Range C. The increase in deviator
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Permanent deformation (%)
stress to 550 kPa at 30,000 load cycles UGMs such as CA1 is in Range A and SS1, CA1SS1 and CA1SS2 are in Range B, which means it is acceptable as base and sub-base material in pavement design. 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0
Range C
Range B Range A 0
2000
4000
6000
8000
10000
Number of loading cycles CA2 SS1
CA2SS2 SS2
CA1 CA2SS1
CA1SS1 CA2SS2
Permanent deformation (%)
Fig. 5 Different permanent deformation curves at OMC corresponding to 350 kPa deviator stress for different study materials
5 4
Range C
3
Range B
2 1
Range A 0 1000
3000
5000
7000
9000
Number of loading cycles
Fig. 6 Representing different failure patterns for UGMs to obtain new shakedown criteria
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Table 7 Proposed shakedown criteria for Study UGMs at different stress level and Load cycles, respectively Study material
Moisture content/ density
CA1
OMC/ MDD
CA2
Proposed shakedown criterion At 350 kPa deviator stress (10,000 load cycles)
At 450 kPa deviator stress (20,000 load cycles)
At 550 kPa deviator stress (30,000 load cycles)
A
A
A
C
C
C
SS1
A
A
B
SS2
B
C
C
CA1SS1
A
B
B
CA1SS2
A
B
B
CA2SS1
B
C
C
CA2SS2
C
C
C
5 Results and Discussions 5.1 Effect of Moisture Variation on Permanent Deformation of UGMs The mean percentage increase in the permanent deformation of CA1 and CA2 UGMs at OMC and OMC + 2% for 350 kPa, 450 kPa, and 550 kPa deviatoric stress by applying 10,000, 20,000, and 30,000 load cycles is 44.73, 31.36, and 30.46%, respectively. Similarly, for SS1 and SS2, the mean percentage increase in permanent deformation is 26.32, 27.01, and 62.75%. Whereas, for CA1SS1 and CA1SS2, the mean percentage increase in permanent deformation is 99.28, 49.46, and 33%. For CA2SS1 and CA2SS2, the mean percentage increase in permanent deformation is 46.80, 18.77, and 18.72%. This variation indicates the susceptibility of permanent deformations of UGMs with increased moisture content levels. These variations in the Permanent deformation levels are primarily due to the presence of fines and thereby increase in the surface area. Similar behavior has been observed in the earlier studies conducted [13, 14]. The comparison of variations in the Permanent deformation among conventional UGMs (CA1 and CA2) and Non-Conventional UGMs (SS1 and SS2) depicts a high mean percentage increase in the permanent deformation levels compared to SS1 and SS2 UGMs in initial stress levels. Whereas in final stress level SS1and SS2 depicts a high mean percentage increase in the permanent deformation levels compared to CA1 and CA2. The mix UGMs (CA1SS1 and CA1SS2) depicts a high mean percentage increase in Permanent Deformation levels compared to conventional UGMs (CA1 and CA2) at initial and final stress levels. Similarly, CA2SS1 and CA2SS2 have a high mean percentage increase in Permanent Deformation levels compared to CA1 and CA2 at initial stress levels, whereas, at final stress levels, CA1 and CA2 have a
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Table 8 Comparison of shakedown criteria of study UGMs Study material
Moisture content Variation
Werkmeister et al. (3000–5000) load cycles
Gu et al. (3000–5000) load cycles
Alnedawi et al. (10,000) load cycles
Proposed Criterion (10,000) load cycles
CA1
OMC + 2%
C
C
A
A
OMC/ MDD
B
B
A
A
OMC + 2%
C
C
C
C
OMC/ MDD
C
C
C
C
OMC + 2%
C
C
B
A
OMC/ MDD
B
B
A
A
OMC + 2%
C
C
C
C
OMC/ MDD
C
C
B
B
OMC + 2%
C
C
B
A
OMC/ MDD
C
C
B
A
OMC + 2%
C
C
B
B
OMC/ MDD
C
C
B
A
OMC + 2%
C
C
B
C
OMC/ MDD
C
C
C
B
OMC + 2%
C
C
C
C
OMC/ MDD
C
C
C
C
CA2
SS1
SS2
CA1SS1
CA1SS2
CA2SS1
CA2SS2
Table 9 New boundaries for shakedown ranges
Range
Range deformation angle (°) From
To
A
0°
20°
B
20°
40°
C
40°
90°
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high mean percentage increase in PD as compared to CA2SS1 and CA2SS2. The Mix UGMs (CA1SS1 and CA1SS2) have a high mean percentage increase in permanent deformation compared to SS1 and SS2 at initial stress levels, whereas, at final stress levels, the SS1 and SS2 have high mean percentage increase than CA1SS1 and CA1SS2. The UGMs mix combination (CA2SS1 and CA2SS2) has a high mean percentage increase in PD compared to SS1 and SS2 at initial stress levels, but at final stress levels, results seem different PD is high for SS1 and SS2. These variations in the Permanent deformation levels are primarily due to the water absorption and volume of permeable voids showing higher values with the replacement of CA1 and CA2 with SS2. The replacement of Conventional aggregates with SS2 further increases the water absorption and volume of permeable voids, which may be due to the higher water absorption and porous structure of SS2 UGM (Palankar et al. [17], Pathak et al. [18]). CA1SS1 has depicted less susceptibility to moisture content with low variation in the permanent deformation; this may be due to the superior mechanical properties of SS1. Whereas CA2SS1 depicted moderate sensitivity to moisture content, this may be due to the poor quality of natural aggregates with high water absorption capacity. CA1SS2 depicted moderate to high moisture sensitivity; this may be because SS2 consists of vesicular nature, a rough and porous surface. CA2SS2 depicted high moisture sensitivity due to poor quality natural aggregates and vesicular steel slags with pockets on its surface. However, it has more permanent deformation and fails at minimum load repetitions. CA1 and SS1 are low to moderate sensitivity to moisture content because of superior mechanical properties, whereas CA2 and SS2 are moderate to highly sensitive to moisture content because they consist of poor-quality aggregates and slag that have a porous and rough surface.
5.2 Effect of Stress Variation on Permanent Deformation of UGMs The mean percentage increase in the permanent deformation of Conventional (CA1 & CA2) UGMs at OMC for 350 kPa to 450 kPa and 450 kPa to 550 kPa deviatoric stress is 50.46 and 22.76%, respectively. Similarly, in SS1 and SS2, the mean percentage increase in permanent deformation is 59.69 and 42.66%. Whereas CA1SS1 and CA1SS2 have a mean percentage increase in PD is 63.06 and 34.64%. For CA2SS1 and CA2SS2, the mean percentage increase in permanent deformation is 56.66 and 78.59%. These variations in the Permanent deformation levels are due to the accumulation of plastic strain, which increases with each load repetition. Similar behavior has been observed in the earlier studies conducted [13, 14]. The comparison of variations in the Permanent deformation amount of conventional UGMs (CA1 and CA2) and Non-Conventional UGMs (SS1 and SS2) depicts that SS1 and SS2 have a high mean percentage increase in Permanent deformation as compared to CA1 and CA2 at both initial and final stress levels. Similarly, CA1SS1
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and CA1SS2 have a high mean percentage increase in PD concerning CA1 and CA2 at both initial and final stress levels. CA2SS1 and CA2SS2 also depict higher mean permanent deformation than CA1 and CA2 at initial and final stress levels. CA1SS1 and CA1SS2 have a high mean percentage increase in Permanent deformation in the initial stress level compared to SS1 and SS2, but in the final stress level, SS1 and SS2 have higher variation than CA1SS1 and CA1SS2. SS1 and SS2 UGMs have a high mean Percentage variation of PD compared to CA2SS1 and CA2SS2 at the initial stress level, but in the final stress level, CA2SS1 and CA2SS2 have higher variation in PD compared to SS1 and SS2. CA1SS1 has depicted less susceptibility to stress variation with low variation in the permanent deformation; this may be due to the superior mechanical properties of SS1 and CA1 consisting of well-graded natural aggregates with the better interlocking property. In comparison, CA2SS1 has moderate permanent deformation at stress level variation because it consists of poor-quality natural aggregates and vesicular steel slags without pockets at the surface. CA1SS2 has low to average mean percentage variation in permanent deformation. This may be because it consists of suitable quality aggregates, which have better strength, and SS2 consists of vesicular nature, a rough and porous surface (Palankar et al. [17], Pathak et al. [18]). Whereas, CA2SS2 depicted high variation in permanent deformation at stress level variation due to poor quality natural aggregates and vesicular steel slags with pockets on its surface, it has more permanent deformation and fails at minimum load repetitions. CA1 and SS1 UGMs are less susceptible to stress variation because of superior mechanical properties, whereas CA2 and SS2 are moderate to highly sensitive to stress variation because they consist of poor-quality aggregates and slag with a porous and rough surface.
6 Conclusion The new shakedown criteria have been defined by considering conventional aggregates and THF steel slag aggregates as UGMs used in base and sub-base layers. The basic properties and RLT tests were performed on selected UGMs. RLT tests were conducted over distinct samples with varying densities and moisture content at different stress conditions. The laboratory test results depicted plastic deformation behavior at controlled conditions by several factors. Since the existing shakedown criteria are not applicable for locally available materials such as THF Steel slag aggregate, conventional aggregate, and multi-stage RLT tests, new shakedown criteria and limits are proposed based on plastic deformation characteristics. The limits are defined based on the nature of the curve between plastic deformation (PD) and the number of loading cycles. Further, these new shakedown criteria were comparable with the criterion reported in the literature. The UGMs were tested at OMC at 350 kPa deviatoric stress, were designated as Range A, B, and C based on the curve angle obtained between PD vs. the Logarithmic number of load cycles. Thus, the
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selected UGMs can be designated under Range A when PD < 1.5%, Range B when 1.5% < PD < 3%, and Range C when PD > 3% based on the curve slope. Thus, new shakedown criteria have many advantages to existing criteria. This will help categorize material quality and works as a quick material assessment tool based on the PD curve. The PD level of selected UGM mixes that fall in Range A & Range B is found suitable, whereas UGM mixes in range C, may depict plastic strain and subsequently generate incremental collapse. This Study also enables us to understand the rutting behavior likely to experience in the granular layers during the pavement’s service life.
References 1. Uzan J (2004) Permanent deformation in flexible pavements. J Transp Eng 130(1):6–13. https:/ /doi.org/10.1061/(ASCE)0733-947X(2004)130:1(6) 2. Pérez I, Medina L, Gallego J (2010) Plastic deformation behaviour of pavement granular materials under low traffic loading. Granular Matter 12(1):57–68. https://doi.org/10.1007/s10 035-009-0154-2 3. Xiao Y, Tutumluer E, Mishra D (2015) Performance evaluations of unbound aggregate permanent deformation models for various aggregate physical properties. Transp Res Rec: J Transp Res Board 2525(1):20–30. https://doi.org/10.3141/2525-03 4. Epps J et al (2014) Development of a specification for flexible base construction. Final Rep. No. FHWA/TX-13/0-6621, College Station 5. Gu F, Zhang Y, Luo X, Sahin H, Lytton RL (2017) Characterization and prediction of permanent deformation properties of unbound granular materials for Pavement ME Design. Constr Build Mater 155:584–592. https://doi.org/10.1016/j.conbuildmat.2017.08.116 6. Lekarp F (1999) Resilient and permanent deformation behavior of unbound aggregates under repeated loading 7. Werkmeister S, Dawson AR, Wellner F (2001) Permanent deformation behavior of granular materials and the shakedown concept. Transp Res Rec 1757:75–81. https://doi.org/10.3141/ 1757-09 8. Sharp RW (1985) Pavement Design Based Upon Shakedown Analysis. Institution of Engineers, Australia, Civil Engineering Transactions, CE 27(4):411–418 9. Chen Q, Abu-Farsakh M, Voyiadjis GZ et al (2012) Shakedown analysis of geogrid reinforced granular base material. J Mater Civ Eng 25(3):337–346 10. Qian JG, Wang YG, Yin ZY et al (2016) Experimental identification of plastic shakedown behavior of saturated clay subjected to traffic loading with principal stress rotation. Eng Geol 214:29–42 11. Alnedawi A, Nepal KP, Al-Ameri R (2019) New shakedown criterion and permanent deformation properties of unbound granular materials. J Mod Transp 27(2):108–119. https://doi.org/ 10.1007/s40534-019-0185-2 12. Gu F, Zhang Y, Droddy CV, Luo R, Lytton RL (2016) Development of a new mechanistic empirical rutting model for unbound granular material. J Mater Civ Eng 28(8):04016051. https://doi.org/10.1061/(asce)mt.1943-5533.0001555 13. Barksdale RD (1972) laboratory evaluation of rutting in base course materials Presented at In: 3rd International conference on the structural design of asphalt pavements, Grosvenor house Park Lane, London 14. Rahman MS, Erlingsson S (2015) Predicting permanent deformation behaviour of unbound granular materials. Int J Pavement Eng 16(7):587–601. https://doi.org/10.1080/10298436. 2014.943209
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15. Garg N, Thompson M (1997) Triaxial characterization of Minesota road research project granular materials. Transport Research Record Journal Transport Research board 1577:27–36 16. Li L, Saboundjian S, Liu J et al (2013) Permanent deformation behavior of alaskan granular base materials. ISCORD 2013:428–435 17. Palankar N, Ravi Shankar AU, Mithun BM (2017) Investigations on Alkali-Activated Slag/ Fly Ash Concrete with steel slag coarse aggregate for pavement structures. Int J Pavement Eng 18(6):500–512 18. Pathak S, Choudhary R, Kumar A, Kumar Shukla S (2020) Evaluation of benefits of opengraded friction courses with basic oxygen furnace steel-slag aggregates for hilly and highrainfall regions in India. J Mater Civ Eng 32(12):04020356 19. AG-PT/T053 (2007) Austroads repeated load triaxial test method: determination of permanent deformation and resilient deformation characteristics of unbound granular materials under drained conditions. Austroads, pp 1–29
Industrial and Agro-Based Wastes as Alternative Binders in Roller Compacted Concrete Pavements: A Comprehensive Review M. Selvam, Solomon Debbarma, and Surender Singh
Abstract Incorporating alternative binders from industrial and agricultural wastes, in blended cement-based materials can lower cement consumption and reduce the carbon footprint. In addition, its inclusion can provide a filler effect, promote secondary hydration, and reduce the heat of hydration, thus, improving the strength and durability of cement concrete mixes. This paper provides a critical overview of the use of alternative binders, or commonly named supplementary cementitious materials (SCMs), in roller-compacted concrete pavement (RCCP) mixes. The major conclusions are (i) inclusions of SCMs can lead to higher water demand to achieve maximum compactness, (ii) the maximum dry density of RCCP mixes made with alternative binders is comparatively lower than that without alternative binders, (iii) the use of fly ash, granulated ground blast furnace slag, and rice husk ash can improve the mechanical and durability properties of RCCP at longer curing ages, and (iv) it is recommended to utilize silica fume to improve the strength and durability of RCCP mixes. This study concludes that the use of alternative binders can improve some properties of the RCCP mixture but depends on varying optimal replacement levels, curing age, and oxide composition of the SCMs utilized. Keywords Roller-compacted concrete pavements · Supplementary cementitious materials · Review · Mineral admixture
M. Selvam (B) Research Scholar, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600036, India e-mail: [email protected] S. Debbarma Indian Institute of Technology Bombay, Mumbai 400076, India e-mail: [email protected] S. Singh Indian Institute of Technology Madras, Chennai 600036, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_7
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1 Introduction Cement is a widely used binding material in the construction industry due to its cohesive and adhesive properties. The Portland cement demand for the construction of pavements and buildings is anticipated to reach 550–600 million tons per annum in 2025 [1]. Consequently, the increased cement production to meet the aforestated demand will increase the carbon footprint, global warming, and exploitation of natural resources. During the hydration process of Portland cement, the cement grains react with water to produce two primary hydration products: calcium silicate hydrate (C–S–H) and calcium hydroxide (CH), presented in Eq. (1). The former (C–S–H) imparts strength to the concrete, while the latter (CH) induces the porosity near ITZ (Interfacial transition zone) due to the wall effect. To mitigate this detrimental effect of CH, researchers took an alternative approach by effectively utilizing industry and agro-based wastes as alternative binders in blended cement-based materials [2]. The role of reactive silica/alumina present in alternative binders is crucial since it reacts with CH to produce secondary C–S–H or calcium aluminate silicate hydrate (C–A– S–H) phases depending on the intake of silica or alumina (see Eq. 2). These phases further refine the pores, thereby densifying the microstructure and improving the ITZ characteristics, leading to better strength and durability. The primary role of SCMs is to provide secondary hydration products, filler effect, reduce the total heat of hydration, and improve concrete properties [3]. However, the reactivity of SCMs depends upon the fineness, the amorphous content, and the chemical, and solution composition [2]. Silicates (C3 S and C2 S) + H → C − S − H + CH
(1)
CH + Reactive silica or alumina + H → C − S − H or C − A − S − H (2) For roller-compacted concrete pavement (RCCP) mixes, the most commonly available alternative binders/supplementary cementitious materials (SCMs) such as silica fume (SF), fly ash (FA), ground granulated blast furnace slag (GGBFS), rice husk ash (RHA), and sugarcane bagasse ash (SBGA) have been broadly utilized [4–10]. However, the comprehensive analysis and effect of the inclusion of alternative binders on the fresh, mechanical, and durability properties of RCCP have not been studied till now. Hence, this review paper seeks to address the alternate binders’ influence as a partial replacement to cement to produce sustainable RCCP mixes.
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2 Fresh Properties 2.1 Optimum Moisture Content From existing studies, it was observed that the inclusion of the considered alternative binders may increase the Optimum Moisture Content (OMC) of RCCP mixes up to 43% [5–7]. For instance, the inclusion of FA at varying proportions of 20, 40, and 60% increased the OMC by 4.4, 22.2, and 33.2%, respectively [7]. The increase in OMC may be attributed to the higher fineness of FA (4040 cm2 /g) compared to that of Portland cement (3880 cm2 /g) used in the authors’ study [7]. Likewise, due to the higher specific surface area of SF particles (>15,000 cm2 /kg), the inclusion of 5–10% of SF as a partial replacement to cement was also found to increase the OMC value by about 0.3–23% [8–10]. An increase in the OMC value in the range of 3.7 and 19.7% could also be expected with the utilization of 3 and 5% of RHA particles, respectively [4]. The use of SBGA entails the highest increase in the OMC by about 33% and 43% when utilized in the proportion of 10 and 15%, respectively [6]. Due to the hygroscopic nature of SBGA particles, SBGA mixes require more water to attain maximum compactness and thus increase the OMC values. The inclusion of 20, 40, and 60% of GGBFS particles has also been reported to increase the OMC by approximately 1, 4.2, and 11.4%. This increase in the OMC may be attributed to the non-reactivity of slag particles during the early concrete ages [5].
2.2 Maximum Dry Density The inclusion of alternative binders has been reported to reduce the Maximum Dry Density (MDD) of RCCP mixes. For instance, the inclusion of high-volume FA in proportions of 20, 40, and 60% was reported to lower MDD by about 1.2, 4.6, and 6.8% [7]. Likewise, Fakhri and Saberik [9] also observed that the inclusion of 10% of SF particles could lower MDD by about 2.9%. Meanwhile, the highest reduction rate (about 4–11%) in the MDD of RCCP mixes was noted when RHA and SBGA particles were utilized in the proportion of 5–15% [4, 6]. This was primarily due to the hygroscopic nature of the RHA and SBGA particles, as a result of which the fresh mixes entail more water to achieve maximum compactness. The inclusion of 20– 60% of GGBFS particles has also been reported to reduce MDD by about 0.6–1.4% [5]. The reduction in the MDD of RCCP mixes due to the inclusion of alternative binders is primarily due to the lower specific gravities of these alternative binders compared to cement. Irrespective of the type and replacement level of alternative binders utilized, the reduction rate in the MDD was found to be marginal (less than 11%). Hence, the use of alternative binders as a partial replacement to cement is expected not to cause much significant variation in the fresh properties of the RCCP mixes.
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2.3 Vebe Time As far as the RCCP mixture consistency is concerned, it has been observed that the inclusion of 10% of SF particles increased the Vebe time from 80 to 88 seconds [10]. This indicates the possibility of workability-related issues with the addition of SF particles. To mitigate this problem, the use of water-reducing admixtures can improve the workability and compactability of SF-based RCCP mixes [10]. To summarize the effect of alternative binders on the fresh properties of RCCP mixes, the factors influencing the fresh properties are shown in Table 1.
3 Mechanical Properties 3.1 Compressive Strength The incorporation of alternative binders has a positive effect on the strength of RCCP mixes. For example, Vahedifard et al. [10] demonstrated that the use of 10% of SF particles could improve compressive strength by about 20%. At the same replacement rate, Fakhri and Saberik [9] also reported an improvement of about 28%. This is mainly due to the formation of secondary C–S–H phase and a good degree of pore refinement provided by the SF particles during the pozzolanic reaction, thus, improving the compressive strength. The inclusion of GGBFS was also reported to show a marginal improvement of about 0.1−4.5% at 10–60% replacement levels [11, 12]. This improvement in the compressive strength is mainly due to the cement hydration, pozzolanic reactivity of slag, and the hydraulic reaction of slag [13]. For instance, at 40% of GGBFS replacement level, the hydration of cement provides sufficient calcium hydroxide required for slag reaction. As a result, this leads to mineral crystallization, and the micro-pores are filled by the slag, thus, leading to improved concrete strength [5]. In the case of RHA-RCCP mixes, Modarres and Hosseini [4] reported a reduction in the compressive strength mainly due to the absence of free CaO in the RHA particles. Moreover, curing time plays an important role in the compressive strength development of RHA-RCCP mixes. At 28 days of moist curing, the CH available for the pozzolanic reaction is low, which impedes the pozzolanic reactivity and subsequently reduces the concrete strength by about 10%. But at 90 days of moist curing, the concentration of CH increases as a consequence of hydration progression, leading to the formation of secondary C–S–H phase, which then contributes to improving the strength by about 5%. But this behavior may not be prominent at higher RHA replacement levels (greater than or equal to 5%). For instance, at 5% of RHA dosage, the amount of CH produced during the hydration reaction is insufficient to activate all available pozzolan particles [4]. As a result, the excess RHA particles remain inactive and act as a filler. The use of 10–15%
Trend in OMC relative to control mix Increase Increase Increase
Difference in Vebe time relative to control mix (%) × × × Decrease Decrease Decrease
Trend in MDD relative to control mix × × ×
Trend in Vebe time relative to control mix
0.95 4.3 11.4
0.6 0.75 1.3
× × × Increase Increase Increase
3.7 19.7
4 8
× × Increase Increase
0.35
2.9
×
20 23
5 3
× ×
Increase Increase
Increase
Decrease Decrease
Decrease
Decrease Decrease
Decrease Decrease Decrease
× ×
×
× ×
× × ×
0.23
× 10
Increase
×
Increase
33 43
10 11
×
Increase Increase
Decrease Decrease
× ×
Remarks: Inclusion of SBGA entails more water to achieve maximum compactness owing to its hygroscopic nature and the use of RAP
10 15
Remarks: Use of silica fume tends to make the mix drier in nature and may cause workability issues on-site
10
Remarks: Higher variation reported due to the utilization of Reclaimed asphalt pavement (RAP) aggregates
5 10
Remarks: Lower specific gravity of SF leads to a reduction in the MDD
10
Remarks: Higher specific surface area of RHA particles increases the OMC
3 5
Remarks: Slag does not react with other phases during early concrete ages
20 40 60
Remarks: Higher fineness of FA particles leads to increased OMC, while the lower specific gravity of FA leads to reduced MDD
Note × indicates data are not disclosed
SBGA
SF
RHA
GGBFS
4.4 22.3 33.2
20 40 60
FA
1.2 4.6 6.9
Difference in Difference in OMC relative to MDD relative control mix (%) to control mix (%)
Replacement level (%)
SCM type
Table 1 Influence of alternate binders on the fresh properties of RCCP mixes
Debbarma et al. [6]
Vahedifard et al. [10]
Debbarma et al. [8]
Fakhri and Saberik [9]
Modarres and Hosseini [4]
Aghaeipour and Madhkhan [5]
Mardani-Aghabaglou and Ramyar [7]
References
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of SBGA particles has also been reported to reduce the compressive strength by about 12–20%; however, this was mainly attributed to the use of asphalt-coated RAP aggregates, which hindered the ITZ densification by the secondary C–S–H phase [6, 8]. Meanwhile, the use of FA particles shows a positive effect up to a certain replacement level, beyond which deterioration of the concrete strength may be expected. For instance, Ati¸s et al. [14] reported that the use of 15% of FA could improve the 28-day compressive strength by about 14.7%. But at higher dosages (30 and 45%), compressive strength reduction of 19 and 47% was observed. This was mainly attributed to the increased water-to-cementitious ratio as the amount of FA increased. The primary reason for the lower strength reduction may be due to the higher free CaO content in the FA particles [7]. Nevertheless, the use of FA contributes to better strength development at longer curing days due to its slow reactivity. In fact, at 90 days of curing age, FA-inclusive roller-compacted concrete pavement mixes could produce concrete with a significantly higher compressive strength (>50%) as compared to the control mix [15]. Hence, the use of 15% of FA particles as cement replacement could produce concrete with a comparable or even higher compressive strength than that of the RCCP made with cement only at 28 days. The inclusion of 30% of FA may also develop a comparable compressive strength to that counterpart control RCCP mix.
3.2 Flexural Strength Similar to compressive strength results, the inclusion of 10% of SF particles was also reported to improve flexural strength by about 20% [9]. Besides, the use of 1 and 2% of nano-silica (NS) has been found to significantly improve flexural strength by 60 and 16% [16]. This improvement is mainly due to the ITZ densification and pore refinement provided by the fine SF particles during the pozzolanic reaction. However, the addition of higher dosages (greater than or equal to 15%) of SF particles may lower the flexural strength, mainly caused by the excess and finer SF fractions [17]. Meanwhile, the inclusion of 20–60% of FA particles has been reported to reduce flexural strength by about 5–39% at 28 days of curing age [7]. This may be mainly attributed to the slow reactivity of FA particles which contributed very little to the strength development at shorter curing days. The use of GGBFS has been reported to reduce the flexural strength at shorter curing ages (3 days) but later improved the flexural strength due to the pozzolanic activity of the GGBFS particles. Rao et al. [12] demonstrated that the inclusion of 10–60% of GGBFS could improve flexural strength by about 4–16 and 5–14% at 28 and 90 days of curing age. The maximum improvement in flexural strength was observed at 40% of the GGBFS replacement level, with an improvement of about 16% and 14% at 28 and 90 days. Contrarily, the inclusion of 3% of RHA was found to improve flexural strength only at longer curing ages (120 days) but reduced the same at shorter curing ages (7 and 28 days) [4]. This was mainly attributed to the deficiency in CH required to activate the pozzolanic
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compounds of RHA containing very low CaO. Besides, at higher RHA dosages (5%), the deficiency in the CH phase becomes higher, and hence, excess RHA particles remain inactive, resulting in flexural strength reduction [4]. Likewise, the use of 10– 15% of SBGA also reduces the flexural strength by approximately 9–16%, mainly due to the increased w/c ratio and higher porosity induced by the hygroscopic SBGA particles [6].
3.3 Split Tensile Strength The incorporation of alternative binders has exhibited a mixed behavior in the split tensile strength of RCCP mixes. For instance, an improvement of about 5% was reported at 9% of the SF replacement level, and this was mainly attributed to the higher concentration of secondary C–S–H phase produced and the higher fineness of SF particles [18]. Contrarily, the inclusion of FA particles showed both increasing and decreasing trends in the split tensile strength of RCCP mixes. For instance, Ati¸s et al. [14] demonstrated an improvement of about 22% was noticed till 15% of FA replacement level, beyond which the split tensile strength starts to drop drastically. Meanwhile, Mardani-Aghabaglou and Ramyar [7] reported that the split tensile strength reduces irrespective of the FA replacement level. On the other hand, the use of 10–15% of SBGA can cause a significant split tensile strength reduction of about 32–39%, mainly due to the hygroscopic nature of SBGA particles and the use of RAP aggregates [8]. In the case of GGBFS-RCCP mixes, curing time plays a significant role in strength development. At shorter curing ages (3–7 days), a reduction in the split tensile strength was observed primarily due to the slow reactivity of GGBFS particles [11]. But at prolonged curing ages (>28 days), a significant improvement of about 50% was positively observed at 50% of GGBFS replacement level [11]. A summary presenting the range in the 28-day strength of RCCP mixes containing SCMs is shown in Table 2.
4 Durability Properties 4.1 Water absorption The inclusion of alternative binders lowered the water absorption due to the microstructure’s pore-filling ability and densification. For instance, the inclusion of GGBFS reduced water absorption owing to its non-reactive nature. Also, as the replacement of GGBFS increases, the water absorption is found to decrease linearly. The highest water reduction was observed to be 45% at a higher replacement level [5]. Similarly, the incorporation of SF and FA in RAP-RCCP mixes showed a positive effect of reduction in water absorption due to the filler effect and production of
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Table 2 Summary of alternative binders incorporated RCCP strength at 28-days of curing age SCM type
SCM Major Cement replacement oxides in content level (%) SCM (kg/m3 )
SF
10
SiO2 = 85%
264
Range in compressive strength (MPa)
Range in flexural strength (MPa)
Range References in split tensile strength (MPa)
52
6.5
×
Fakhri and Saberik [9]
×
Vahedifard et al. [10]
Remarks: Significant improvement in the concrete strength 10
SiO2 = 85%
215
30
×
Remarks: Improvement observed despite low-cementitious content 5–10
SiO2 = 90%
350
23–25
4.9–5.1
2.8–3.0
Debbarma et al. [17]
Remarks: Insignificant improvement observed due to the use of RAP aggregates NS
1–2
SiO2 = 92%
268
57–80
6.5–8.8
5–6
Mohammed and Adamu [16]
3.5–4.0
Mardani-Aghabaglou and Ramyar [7]
×
Rezaei et al. [19]
Remarks: High pozzolanic reactivity of nano-silica leads to significant strength enhancement FA
20–60
SiO2 = 100–200 32–39 49.7% CaO = 10.8% Al2 O3 = 17%
4.2–4.7
Remarks: Use of FA did not improve the strength properties 20–60
SiO2 = 118–236 17–35 62.8% CaO = 3.43% Al2 O3 = 24%
4.2–6.1
Remarks: No improvement in concrete strength was observed 15–45
SiO2 = 18.5% CaO = 51.3%
110–170 12–26
2.1–3.2
1.2–2.5
Rao et al. [20]
Remarks: Improvement observed till 15% replacement level only GGBFS 10–60
SiO2 = 115–265 43–45 34% CaO = 33% Al2 O3 = 16%
7.0–7.9
3.5–4.8
Rao et al. [11]
(continued)
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Table 2 (continued) SCM type
SCM Major Cement replacement oxides in content level (%) SCM (kg/m3 )
Range in compressive strength (MPa)
Range in flexural strength (MPa)
Range References in split tensile strength (MPa)
Remarks: Improvement due to the pozzolanic activity of GGBS RHA
3–5
SiO2 = 87%
183–224 29–37
8.5–11
×
Modarres and Hosseini [4]
Remarks: High flexural strength due to the center-point flexural beam loading SBGA
10–15
SiO2 = 66%
297–315 16–26
3.2–3.7
1.7–2.2
Debbarma et al. [6, 8]
Remarks: Decrease in concrete strength was observed due to the use of RAP aggregates Note × indicates data are not disclosed
extra CSH gel on account of pozzolanic reactivity [17]. On the other hand, the water absorption capacity was found to be increased in the SBGA inclusive RAP-RCCP mixtures owing to the hygroscopic nature [17]. Despite this, no major studies are available for other SCMs; therefore, more research studies are required to understand its effect on the water absorption of RCCP mixtures.
4.2 Water Permeability Water permeability is used to measure the resistance offered by concrete against water flow under pressure. It can be determined either by measuring flow rate or by measuring penetration depth after splitting. The effect of GGBFS on water permeability is determined at different replacement levels of about 20–60%[5]. The results depict that lower penetration depth could be obtained at 40% replacement; however, the penetration depth is increased at higher replacement [5]. The differential behavior at the higher replacement of GGBFS is manifested due to the lower cement content, which causes the inadequate supply of portlandite. As a result, incomplete formation of crystal growth would form. In such cases, more pores and larger cracks could be formed, which paves the way for the permeability of water [5]. Similarly, the influence of permeation of fly ash-inclusive RCCP mixtures is evaluated using the German water permeation test. In this study, three mixes were developed: higher fly ash with lower low cement, moderate fly ash with moderate cement, and low fly ash with higher cement [18]. Above all, the moderate fly ash of 60–70% with moderate cement content showed better performance with less permeation to water [18]. However, only a handful of studies are available on the water permeability characteristics; therefore, more studies on the alternate binders are required to evaluate their performance and durability in water logging/prone areas.
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4.3 Freeze–Thaw (F-T) Vahedifard et al. [10] investigated the effects of SF on the F-T durability of RCCP mixes made with low-cement. The authors observed that the addition of 10% of SF particles could withstand 300 F-T cycles without any significant deterioration. For mixtures containing no SF particles, increasing the cementitious content from 12% (235 kg/m3 ) to 15% (275 kg/m3 ) exhibited about 3.1% increase in the relative dynamic modulus of elasticity (DME) and about 9.8% decrease in the mass after F-T cycles. In contrast, the same behavior was not observed when SF was incorporated in the proportion of 10%. For instance, very little mass loss was observed at 12% cementitious content, while a significant change in mass loss of about 32% was observed for the mixes containing 15% cementitious content. Shen et al. [21] also investigated the combined effect of 5% of SF and 35% of FA on the frost resistance of RCCP mixes after 100 F-T cycles at 90 days. They concluded that the surface of the SF concrete suffered considerable spalling, even with the aggregate exposed. However, this phenomenon is probably due to the presence of FA particles in high amounts, which deteriorated the pore structure and led to a decrease in the F-T resistance. Nevertheless, they observed that the addition of SF was found to be beneficial in terms of F-T durability, according to the relative DME and the mass-loss rate.
5 Summary and Conclusions There seems to be a significant potential for alternative binders in RCCP applications to maximize the economic and environmental benefits. Significant savings can be achieved by converting these waste materials into useful resources by producing new concrete. The literature shows that utilizing SCMs would surely affect the fresh and hardened properties of RCCP. The mixes made with these SCMs would require extra water to achieve maximum compaction due to their higher specific surface area than OPC. Also, due to their lower density, the achieved maximum density of RCCP mixes would be lesser than conventional RCCP mixes. Further, the use of SF particles as a replacement for cement could improve the strength and durability of RCCP. The use of FA, GGBFS, and RHA could also improve the RCCP properties; however, its benefit may be observed at prolonged curing ages only due to its slow reactivity. But limited studies on the use of SCMs in RCCP encourage more research to be carried out to understand the behavior of SCMs in the microstructure of RCCP mixtures. Moreover, validation of these studies should be carried out via laboratory as well as field studies. Acknowledgements The first author would like to thank the Ministry of Education, Government of India, for providing the PMRF scholarship. The first and third authors wish to acknowledge the financial support received from the Indian Institute of Technology Madras, Chennai, under the project: Technologies for Low carbon & Lean Construction (TLC2 - SB20210809CEMHRD008100).
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References 1. https://www.ibef.org/industry/cement-india.aspx. 2. Lothenbach B, Scrivener K, Hooton RD (2011) Supplementary cementitious materials. Cem Concr Res 41:1244–1256 3. Juenger MCG, Siddique R (2015) Recent advances in understanding the role of supplementary cementitious materials in concrete. Cem Concr Res 78:71–80 4. Modarres A, Hosseini Z (2014) Mechanical properties of roller compacted concrete containing rice husk ash with original and recycled asphalt pavement material. Mater Des 64:227–236 5. Aghaeipour A, Madhkhan M (2017) Effect of ground granulated blast furnace slag (GGBFS) on RCCP durability. Constr Build Mater 141:533–541 6. Debbarma S, Ransinchung GD, Singh S, Sahdeo SK (2020) Utilization of industrial and agricultural wastes for productions of sustainable roller compacted concrete pavement mixes containing reclaimed asphalt pavement aggregates. Resour Conserv Recycl 152:104504 7. Mardani-Aghabaglou A, Ramyar K (2013) Mechanical properties of high-volume fly ash roller compacted concrete designed by maximum density method. Constr Build Mater 38:356–364 8. Debbarma S, Ransinchung GDRN, Singh S (2019) Suitability of various supplementary cementitious admixtures for RAP inclusive RCCP mixes. Int J Pavement Eng: 1–14 9. Fakhri M, Saberik F (2016) The effect of waste rubber particles and silica fume on the mechanical properties of Roller Compacted Concrete Pavement. J Clean Prod 129:521–530 10. Vahedifard F, Nili M, Meehan CL (2010) Assessing the effects of supplementary cementitious materials on the performance of low-cement roller compacted concrete pavement. Constr Build Mater 24:2528–2535 11. Rao SK, Sravana P, Rao TC (2016) Abrasion resistance and mechanical properties of Roller Compacted Concrete with GGBS. Constr Build Mater 114:925–933 12. Rao SK, Sravana P, Rao TC (2016) Investigating the effect of M-sand on abrasion resistance of Roller Compacted Concrete containing GGBS. Constr Build Mater 122:191–201 13. Feng X, Garboczi EJ, Bentz DP, Stutzman PE, Mason TO (2004) Estimation of the degree of hydration of blended cement pastes by a scanning electron microscope point-counting procedure. Cem Concr Res 34:1787–1793 14. Ati¸s CD, Sevim UK, Özcan F, Bilim C, Karahan O, Tanrikulu AH, Ek¸si A (2004) Strength properties of roller compacted concrete containing a non-standard high calcium fly ash. Mater Lett 58:1446–1450 15. Cao C, Sun W, Qin H (2000) Analysis on strength and fly ash effect of roller-compacted concrete with high volume fly ash. Cem Concr Res 30:71–75 16. Mohammed BS, Adamu M (2018) Mechanical performance of roller compacted concrete pavement containing crumb rubber and nano silica. Constr Build Mater 159:234–251 17. Debbarma S, Ransinchung G, Singh S (2020) Improving the Properties of RAP-RCCP mixes by incorporating supplementary cementitious materials as part addition of portland cement. J Mater Civ Eng 32:04020229 18. Yerramala A, Ganesh Babu K (2011) Transport properties of high volume fly ash roller compacted concrete. Cem Concr Compos 33:1057–1062 19. Rezaei MR, Abdi Kordani A, Zarei M (2020) Experimental investigation of the effect of Micro Silica on roller compacted concrete pavement made of recycled asphalt pavement materials. Int J Pavement Eng:1–15 20. Rao SK, Sravana P, Rao TC (2016) Investigating the effect of M-sand on abrasion resistance of Fly Ash Roller Compacted Concrete (FRCC). Constr Build Mater 118:352–363 21. Shen L, Li Q, Ge W, Xu S (2020) The mechanical property and frost resistance of roller compacted concrete by mixing silica fume and limestone powder : Experimental study. Constr Build Mater 239:117882
Utilization of Industrial and Agricultural Wastes to Enhance the Properties of Concrete–A Review Sameer Malhotra, Abhishek Kanoungo, and Ajay Goyal
Abstract About 11.2 billion tons of solid waste that is dumped every year in landfills and releases toxic chemicals in the soil, water, and air. It further pollutes more than 280 billion tons of groundwater. In addition to it, more than 14 million tons of plastic end up in the ocean every year. There lie vast opportunities for researchers and challenges to lessen this harmful impact. Detailed investigations are always in pursuit of finding and utilizing these wastes for some useful applications. The construction and cement industries are owing to their environmental impact. At the same time, these industries have the huge potential of utilizing waste for better applications. This study describes that industrial and agricultural wastes such as fly ash, slag, glass, crumb rubber, textile waste, plastic fibers, ceramic, rice husk, coconut fiber, and sugar bagasse are effective and suitable alternatives as a partial replacement for cement and aggregates in concrete. Industrial and agricultural waste materials enhance several properties of concrete i.e., durability, workability, strength, fire resistance, toughness, insulation, etc. All the properties are examined by different tests such as compressive test, flexural test, split tensile test, carbonation test, slump test, X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). Some of the industrial by-products and agricultural wastes act as pozzolans as documented in various literature. This study is to identify the minor or major gaps in the current knowledge on the utilization of industrial and agricultural wastes. Keywords Solid waste · Environmental impact · Waste management · Industrial and agricultural wastes · Cementitious materials · Admixtures · By-Products
S. Malhotra · A. Kanoungo (B) · A. Goyal Department of Civil Engineering, Chitkara School of Engineering and Technology, Chitkara University, Himachal Pradesh, India e-mail: [email protected] S. Malhotra e-mail: [email protected] A. Goyal e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_8
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1 Introduction Siddique [1] Solid wastes are increasing at a much faster rate now a days due to increase in population. Solid wastes of around 277.1 million tons are being produced in India. Thermal Power Plants, Iron & Steel Mills, Non-ferrous Industries, and Cement Industries generates huge amount of solid waste [2]. Agriculture sector also produces large quantities of agricultural residues (sawdust, leaf litter, forest waste, and crop residues, animal husbandry, fertilizers). Due to non-decomposition of matters, problem of solid disposal is being occurred [3]. Landfilling and burning solid trash with the help of furnaces are the two major different routine methods to reduce solid waste from earth. Meanwhile, due to increasing costs of operating landfills with scarcity of landfills, the disposal of industrial by-products is becoming an increasing concern. Safiuddin [4] The quantities of natural resources on earth are limited and there is excess quantity of waste being generated. Construction industries are the largest user of natural resources and are releasing huge amount of waste. The most widely used human-made material is concrete. After water, concrete is the second most-consumed substance on earth. Around 22–27 billion tons of concrete is being produced globally every year [5]. The concrete industries emit 8–9% of anthropogenic greenhouse gases annually [6]. At present, from the sustainability point of view, sand and cement are the two problematic components. The third largest contributor of CO2 emission is Portland Cement Production. These days the annual global production of cement is 4.1 billion tons [7]. Similarly, use of regular sand is increasing because of huge utilization of mortar and concrete. Many researchers have tried to generate new construction materials out of various industrial and agricultural waste materials. To investigate the feasibility of solid wastes as potential substitute for traditional materials like cement and sand, the study of many different researches has been taken into consideration from last few years.
2 Waste Classification To sort the process of solid waste utilization, discussion being done on solid wastes like industrial and agricultural wastes.
2.1 Industrial Wastes The targeted wastes that are produced from industries are fly ash, steel slag, blast furnace slag, sewage sludge, rubber waste, ceramic waste, textile waste, and plastic fiber waste. Depending upon their physical, chemical, and mineralogical composition
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along with the mechanical and durability properties these materials can be used in concrete (Tables 1, 2, 3, 4, 5, 6, and 7).
2.2 Agricultural Wastes All the unwanted waste produced during agricultural activities are listed under agricultural wastes. Some of the targeted agricultural wastes are rice husk, coconut fiber, and sugar bagasse. These materials can be used in concrete on the basis of their physical and mineralogical composition along with durability and mechanical properties (Tables 8, 9, and 10). Table 1 Fly ash Author
Methodology adopted
Results
Yermala et al. [8]
Fly ash replaced OPC 53 grade cement by 5−25%, curing was done for 28, 90 and 180 days
Compressive Strength (C.S.) at 5%, 10% and 15% observed higher but lesser at 20% and 25%. Similar results evaluated for split tensile strength
Solanki et al. [9]
Cement replaced partially by 0, 10, 20 and 30% of fly ash and hypo sludge in M20 grade concrete, tests were conducted after 28 days
Highest Flexural Strength (F.S.) increased by 11.08% was observed at 20% fly ash replacement for 28 days curing. The strength was observed lesser for 10% and 30% replacement
Madhavan et al. [10]
Varying percentages of fly ash by 10, 20 and 30% and steel fiber by 0.5, 1 and 1.5%. Beams were casted to get the results. The strength was evaluated at 7 and 28 days
Highest F.S. gained when 10% of fly ash was replaced along with 1% steel fiber. The increase in flexural strength was shown by 3.70 N/mm2, 5.89 N/ mm2 and 6.35 N/mm2
Hygrive et al. [11]
Different concrete was designed of M20, M25, M30 and M40 grades, fly ash replaced cement by 30, 40 and 50%, and curing was done for 7 and 28 days
Highest C.S. for M20 grade gained after 7 and 28 days by replacing 30% fly ash whereas M35 grade showed highest F.S. after 28 days for 30% fly ash replacement
Saboo et al. [12]
Replacing cement with fly ash between The porosity decreased by 10% after the ranges from 5 to 15%. The strengths adding 2% of metakaolin. ANCOVA were examined after 28 days evaluated that porosity effect was dominated by adding fly ash
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Table 2 Slag Author
Methodology adopted
Results
Singh et al. [13]
Fine aggregates were partly replaced with blast furnace slag by 0, 10, 25 and 40% in a control Self Compacting Concrete (SCC). All the results were examined for 365 days
Scanning Electron Microscopy (SEM) and XRay Diffraction (XRD) evaluated that blast furnace slag showed better strength and durability than control mix
Mohan et al. [14]
The silica fume and ground granulated blast furnace slag (GGBFS) were replaced by 0, 5, 10 and 15% individually. The strengths were checked at 7, 28, 56 and 90 days
The effective change occurred in C.S. and F.S. by replacing 10% of silica fume than other mixes. The GGBFS was added to reduce the ecological issue of waste disposal
Solvador RP et al. [15]
Blast furnace slag replaced cement. Age of concrete at which various results were observed are 24 h, 28 days and 91 days
At 30% substitution of slag, the consumption of Alite and formation of Portlandite were 7–15% lower until 24 h of slag employment
Guo et al. [16] The steel slag was incorporated in concrete by 0, Steel slag replacement up to 20% improved the 10, 20, 30 and 40% by replacing fine aggregates performance of Steel slag sand concrete to monotonic and impact compression. Slight effect on Poisson’s Ratio also observed Tangadagi et al. [17]
Steel slag replaced at different percentages from 0 to 50% with an increment of 10%. The experiment work was done on M30 grade concrete. Age of concrete was 28 days
Reduced the workability but enhanced the strength up to 30% steel slag replacement and thereafter decreased drastically
Table 3 Glass Author
Methodology adopted
Results
Du et al. [18]
Glass powder replaced cement up to 60%. Curing was done for 28 days. With the help of XRD and TGA that it was observed that glass powder formed C-S–H after reacted with CH
Highest strength at 15% and 30% replacement. Water penetration depth, chloride diffusion and migration coefficients reduced by 77, 91 and 92% respectively at 60% replacement
Letelier et al. [19]
Glass powder used during the study with a maximum size of 38 µm act as a filler. Tests were conducted up to 90 days age of concrete
Up to 20% of glass powder and 30% of fine recycled concrete aggregates incorporation in concrete reduced the CO2 emission by up to 19%
Lu et al. [20]
Waste Glass Cullet (WGC) was incorporating as fine aggregates and Recycled Concrete Aggregates (RCA) as coarse aggregates by varying percentage up to 100% with blended value 2.36-5 mm and 5-10 mm respectively
Thermal conductivity reduced to 0.63W/mk, density was 932 kg/m3 and C.S. decreased by 23 and 31% respectively for WGC and RCA. Silica fumes by 10% enhanced the strength by 23.5 and 59.5%
Bostanci et al. [21]
Replacement of marble dust by 5 and 10% of cement (MD 5 & MD10) and recycled glass as sand replacement by 20% (RGS 20) for 45 MPa grade concrete
C.S. reduced by 7% and 15% for MD 5 and MD 10 respectively. RGS 20 reduced the strength by 10% at all ages. Lower permeability by 15.2% and 14.1% in MD 5 and MD 10
Wang et al. Concrete mix incorporated with 0.60 and 2.54 cm [22] glass fiber by 0.5, 1.0 and 1.5%. Higher temperature strength analysis up to 1000ºC. Curing was done up to 28 days
Early strength reduced for 0.60 short fibers added by 0.5% of cement and 2.54 cm of long fiber by 0.5–1.0%. F.S. reduced by 1.9−8.5% with 1.0–1.5% short fiber and strength was enhanced by 3.1% to 11.9% with long fiber
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Table 4 Crumb rubber Author
Methodology adopted
Chylik et al. [23]
Fine and coarse crumb rubber in concrete by Decrease in workability, C.S. and permeability with 0 to 100% replacement. Tests were performed increase in crumb rubber percentage. The results on 7, 28 and 45 days age of concrete were analyzed for 40, 80 and 120 kg/m3
Bisht et al. [24]
Replacement of crumb rubber from fine aggregates in varied percentages by 0, 4, 4.5, 5 and 5.5%. Curing was done for 28 days
The workability, C.S. and F.S. decreased with increment in crumb rubber. For non-structural elements only up to 4% of replacement was examined
Kaewunruen et al. [25]
Micro scale crumb rubber replaced fine aggregates at varying ratios up to 10% along with the silica fume replacement up to 10%. 28 days age of concrete were considered for testing
Decrease in C.S. but split tensile strength increased and F.S. was examined with optimal rubber particles. Damping properties and electrical resistivity improved up to 100% & 47%. Respectively
Elaal et al. [26]
Incorporation of pre-treated crumb rubber particles using thermal treatment at 200 ºC in concrete. The tests were performed at 7 and 28 days concrete
Promising enhancement majorly in C.S. by 93, 60 and 47% by 10, 20 and 40% of rubber replacement. The highest crumb rubber concrete recovery was observed by 92.7%
Eisa et al. [27] Incorporation of crumb rubber of size 2 mm and 3 mm by 5, 10, 15 and 20% with 1% of steel fiber and for 28 days curing was done
Results
C.S. enhanced by 11–34%, modulus of elasticity and split tensile strength also affected up to 20% replacement of crumb rubber
Table 5 Textile waste Author
Methodology adopted
Results
Hosseini et al. [28]
Polypropylene carpet fiber waste of 20 mm length by 0.25−1.25% with Ordinary Portland Cement (OPC) and 20% replacement of Palm Oil Fuel Ash (POFA) as supplementary cementing material
19.6 and 12.4% of tensile Strength increased and F.S. increased by 19.5 and 14.1% for OPC and POFA respectively at 90 days
Pichardo et al. [29]
This study examined the use of recovered cotton fiber in polyester concrete
40% improvement in the C.S. and 7% in the F.S
Karpagam et al. [30]
Textile cut pieces of 1 cm × 1 cm were incorporated in different percentages such as 10, 20, 30 and 40% in M20 grade concrete. Cracks were observed at 120 h
C.S., F.S. and tensile strength increased by 20, 18 and 20% for 20% textile fiber replacement. No cracks and honey combing were shown at 250ºC temperature
Sadrolodabaee et al. [31]
Textile waste fiber as short random fiber by 6−10% by weight or non-woven fabrics in 3−7 laminate layers as internal reinforced material. The curing was done for 28 days
Reinforced with six layers of non-woven fabrics with F.S. of 15.5 MPa and toughness of 9.7 kJ/m2 were proved to be optimal composite
Kumar et al. [32]
Textile sludge replaced cement by varying percentages of 2.5, 5, 7.5, 10, 15 and 20%. Alumina nanoparticles were added by 3%. At 7 and 28 days, the tests were performed
C.S. increased by 5.1, 2.7 and 1.7% for 2.5, 5 and 7.5% at 7 days, split tensile strength increased by 4.3, 2.9 and 0.81% for 2.5, 5 and 7.5%
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Table 6 Plastic fibres Author
Methodology adopted
Results
Khalid et al. [33]
Two different synthetic fibers, polyethylene terephthalate and wire fibers in a concrete matrix. High fiber activated the failure resistance mechanisms
Incorporating ring shaped plastic fiber with a width of 10 mm showed great results with the increment of 32.3% for the first crack load in concrete
Tuladhar et al.
Comparison of recycled Polypropylene (PP) fibers with virgin Polypropylene (PP) fibers and Steel Reinforcing Mesh (SRM) for life cycle assessment
99 and 91% less water and fossil fuels than SRM respectively whereas 28% and 78% of less water and fossil fuels were consumed by Recycled PP fibers than virgin PP fibers. Also, 50% less CO2 and 65% less PO4 were produced by recycled PP fibers
Hussaini et al. [34]
Plastic fibers added in varying percentages of 0.5, 1, 1.5 and 2% with HP-570 super-plasticizer, age of concrete was 28 days
C.S., tensile strength and F.S. were increased by 13.2, 117.4 and 207.5% respectively for 2% replacement of plastic fiber
Awoyera et al. [35]
Replacement of fine aggregates in ratios of 50 and 100% with 1.5 and 2.5% of plastic fibers (Polyethylene Terephthalate, PET), the curing was done up to 28 days
Highest C.S. obtained at 100% replacement of ceramic waste and addition of 2.5% plastic fiber, tensile strength increased by 45% with 100% ceramic waste and 2.5% plastic fiber addition
Anandan et al. [36]
Plastic fibers added homogenously and Fibers in tension zone showed higher F.S. of 5.26 N/mm2. confined fibers in tension only. The Absolute toughness was higher by 132% in tension zone fibers were added in varying ratio range confined plastic fiber concretes from 0–0.15%. The testes were done after 28 days
Table 7 Ceramic waste Author
Methodology adopted
Results
Kannan et al. [37]
Ceramic Waste Powder (CWP) replaced cement in varying percentages ranging from 10 to 40%. Testes were done after 28 and 90 days
CWP lowered the C.S. at early ages. The slump values were reduced except for 20 and 30% replacement. Electrical resistivity also increased with increase in CWP percentage
Siddique et al. [38]
Bone china ceramic waste replaced as fine aggregates by varying percentage of range 20 to 100% in concrete. Curing was done for 28 days
2.1% water loss and 7% fresh air content at 100% replacement respectively and the C.S. showed slightly higher values by 60, 80 and 100% replacement at 28 days
Dieb et al. [39]
CWP replaced cement at different replacement levels ranging from 10 to 40% in concrete matrix, different grades (i.e., 25, 50, 75 MPa). Strength was observed up to 90 days
Workability enhanced with 10% to 20% of CWP. Enhanced C.S. was observed at 10% replacement, the durability was enhanced at 40% replacement
Song et al. [40]
CWP replaced cement by 10% and 20%. Also, Artificial Neural Network (ANN) and Decision Tree (DT) were applied to identify the C.S. All the results were examined for 28 days
ANN showed better accuracy then DT with Liner Co-efficient Correlation value (R2) of 0.67. The high performance of an ANN model was also proved by K-fold cross validation method
Barreto et al. [41]
Clay ceramic waste (CCW) replaced as pozzolana constituent with 10 and 20% weight replacement by Ordinary Portland cement (OPC). Addition of ceramic generated C-S–H gel with CH. The age of concrete was 14 and 28 days
At 10% replacement, strength enhancement of 27.2 MPa at 14 days and 31.42 MPa at 28 days for 25 MPa grade strength. Similarly, at 20% replacement the strength of 24.5 MPa and 27.82 MPa at 14 and 28 days respectively
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Table 8 Rice husk Author
Methodology adopted
Results
Siddique et al. [42]
RHA replaced cement partially with 0−20%. During concrete making Bacterium Bacillus Aerius was mixed in water. Age of concrete was up to 56 days
Bacteria in RHA enhanced the C.S. at all ages. Best results with 10% RHA with C.S. of 36.1 MPa at 28 days. With bacteria 40.0 MPa
Umbasabor et al. Addition of Rice Husk Ash (RHA) by 5, 10 and [43] 15%. Specimens were exposed in muffle electric furnace for 2 h with temperature ranging from 100 to 700ºC. The different ages of concrete were 7, 28, 30, 60, 90, 120, 150 and 200 days
Concrete with 5% RHA performed better in fire than others. The range of Pozzolanic concrete and control concrete fire resistance was observed by 60−96% for 200−400 ºC, 41−55% for 500 ºC and 13−26% for 600−700 ºC
Gautam et al. [44]
RHA replaced OPC cement at 2.5% interval started from 5 to 15% on M40 grade with compaction factor 0.80 and w/c ratio of 0.40. The strengths were observed for 7 and 28 days
C.S. and split tensile strength examined maximum with 42.45 MPa and 3.2 MPa at 7.5% replacement. The cost analysis evaluated the saving of 4.417% INR price
Praveenkumar et al. [45]
Two different samples were prepared with 3% nano- RHA and 20% fly ash respectively. The various ages of concrete were 7, 28 and 56 days
Low chloride penetration rate hence, low corrosion rate, fly ash-based concrete showed greater depth during carbonation test than nano- RHA concrete, surface ph value and crushed ph value showed basic nature
Table 9 Coconut fibre Author
Methodology adopted
Results
Khan et al. [46]
15% of silica fume by mass of cement was added. With length of 5 cm and content of 2% coconut fibers were added. Super plasticizer added by 0, 0.5, 1 and 1.5%. The comparison was done between medium strength concrete (MSC) and medium strength coconut fiber reinforced concrete (MSCFRC). The curing was done for 28 days
The C.S. of MSCFRC’s with varying percentages improved by 1.1, 3.6, 1.5 and 9.4% respectively than that of MSC. The workability of MSCFRC reduced than that of MSC
Kumar et al. [47]
Coconut fiber added at 5% and coconut fiber ash at 15%. Conventional water was replaced by sea water. The strengths were evaluated for 7 and 28 days
The C.S., F.S. and split rigidity with coconut filaments at 1.5, 2.5 and 5.0% was seen to incremented at 7 and 28 days
Ahmad et al. [48]
Silica fume was added 10% and super plasticizer 1% to coconut fiber reinforced high strength concrete (CFR-HSC). The coconut fiber with 25 mm, 50 mm and 75 mm of varying percentages by 0.5, 1, 1.5 and 2% were incorporated. All the results examined for 28 days
The overall best results were observed for 50 mm long coconut fiber with 1% content by cement mass. The slump value and density decreased with increase in coconut fiber
Abbas et al. [49]
Coconut fiber with RHA, fly ash and GGBFS were used. The varying The C.S., 5.13 and 5.6% with percentages of coconut fiber were 0.1, 0.2, 0.3, 0.4, 0.5 and 0.6%. o.2% fiber incorporation and The ages of concrete were 7 and 28 days F.S. and split tensile strength were increased by 0.42 and 0.7% at 0.2% fiber after 28 days
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Table 10 Sugar bagasse Author
Methodology adopted
Results
Mangi et al. Sugarcane Bagasse Ash (SCBA) replaced 0, 5 [50] and 10% of cement by using M15 and M20 grade concrete from normal strength concrete (NSC). Cylindrical specimen was used. The various parameters were observed at 7, 14 and 28 days
SCBA at 5% replacement increased the C.S. by 12% of M20 grade as comparative to NSC. SCBA also improved the slump value and hence, workability increased
Jagadesh et al. [51]
SCBA replaced OPC up to 30% in two different forms named Original SCBA (O-SCBA) and Processed SCBA (P-SCBA). The properties were observed for 7 and 28 days
Density of P-SCBA increased to 0.78, 1.04 and 1.21% at fresh, 7 days and 28 days respectively than O-SCBA. The C.S. enhanced up to 28% for 10% replacement for P-SCBA and Modulus of Rupture enhanced at same percentage of 10% replacement
Mello et al. [52]
SCBA and Metakaolin (MK) replaced cement by 30–50%. Initial curing was done at room temperature and then exposed to 200, 400, 600 and 800ºC. The ages of concrete were 3, 7 and 28 days
SCC was less sensitive with up to 40% at high temperatures and declared less cracks and lower strength losses as compared to the normal room temperature
Neto et al. [53]
The SCBA was added by 5, 10 and 15%. The curing was done up to 28 days
SCBA concrete exhibited higher carbonation rate up to 69%. Lifetime increased up to 97.3% due to decrease in the chloride diffusion coefficients. By adding 5% SCBA the formation of C-S–H was occurred
3 Conclusions A comprehensive review is presented with a wide range of industrial and agricultural waste products. Influence of these materials as cementitious material and aggregates has also been discussed. Based on the review, the following conclusions are drawn: i. To mitigate greenhouse gas emissions i.e., CO2 emissions, the alternative protective action is frequent utilization of industrial and agricultural waste. ii. The employment of industrial and agricultural waste materials in concrete controls the dissipation of natural resources. iii. The mechanical properties have got enhanced at lower replacement levels and got reduced at higher replacement levels. iv. The compressive strength is influenced when fly ash and rice husk are used up to 30 and 10% as a replacement for cement; respectively. v. The ceramic waste shows maximum replacement percentages up to 100% of aggregates from concrete matrix. vi. The industrial and agricultural waste brings into play to generate sustainable ecological composite materials. vii. Use of crumb rubber decreases the workability of concrete due to excess voids. viii. Fly ash and rice husk are widely being used to produce concrete whereas several materials need more research processes to develop their demand in concrete production.
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Study on Utilizing Reclaimed Asphalt Pavement in Bituminous Concrete Wearing Course with PMB 70-10 V as Binder Using Hot In-Plant Recycling Process Niranjan Geddada , Arpan Ghosh, and Kamlesh Gupta
Abstract India has the second-largest road network in the world of about 62.16 lakh km. Reclaimed Asphalt Pavement (RAP) is produced in huge amounts after milling the aged or high severity distress bituminous pavement. RAP can be used again in Bituminous Concrete (BC) layer construction, saving bitumen, aggregates, and landfill space. Resources are scarce in some regions of our country where the reclaimed asphalt pavement usage will be cost-effective and environmentally friendly leading to sustainable development by conserving natural resources. This paper describes the study of volumetric and mechanical properties of RAP blended Bituminous Concrete mix with PMB 70-10 V as a virgin binder. In this study, 25% of RAP is added to virgin Aggregates in proportion to the weight of aggregates in the BC mix. PMB 70-10 V is used as a virgin binder, and RAP BC Mix is designed following MS-2 Asphalt Mix Design Method. The results show that RAP Bituminous Concrete mix with PMB 70-10 V binder at 5.6% optimum binder content (OBC) and 5.8% have exhibited Volumetric and Marshall properties similar to conventional Bituminous Concrete mix with PMB 70-10 V binder at 5.4% OBC. Also, the overall cost of BC mix materials, production, transportation, and laying is reduced by 8.77% relative to conventional BC mix cost. This study also describes the challenges faced during RAP BC mix production using the Hot In-Plant recycling process and execution in a pilot project in the southern region of India. Keywords Reclaimed asphalt pavement · Bituminous concrete · Hot in-plant recycling · Wearing course · Optimum binder content
N. Geddada (B) · A. Ghosh · K. Gupta V R Techniche Consultants Private Limited, Noida 201305, India e-mail: [email protected] A. Ghosh e-mail: [email protected] K. Gupta e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_9
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1 Introduction India has the second-largest road network in the world of about 62.16 lakh km. This comprises National Highways, Expressways, State Highways, Major District Roads, Other District Roads, and Village Roads wherein the majority of the roads comprise of Bituminous Pavement [1]. Reclaimed Asphalt Pavement is aged pavement material obtained after milling the aged or high severity distress bituminous pavement which is to be utilized over or otherwise eventually sent to landfills. In the pavement construction sector, using RAP in hot bituminous mixtures can minimize the utilization of natural resources and reduce damage to nature. In times of scarce crude oil resources, recycling and reusing RAP in new pavement constructions on the one hand, and the development of more sustainable and renewable alternatives to bitumen, on the other hand, are becoming increasingly important. Materials are the most expensive component in pavement construction, wherein about 70% of the cost is alone spent on materials to produce BC Mix [2]. Therefore, using RAP in the surface layers of flexible pavements, replacing a portion of the binder and aggregate is the most cost-effective method of bituminous pavement construction. As per Ministry of Road Transport and Highways (MoRTH) guidelines [3] and Indian Roads Congress (IRC), the utilization of RAP is allowed in Bituminous Macadam and Dense Bituminous Macadam and also limited to 30 percent (%) using Hot In-Plant Recycling (HIP) process [4]. Despite the advantages it has, RAP usage in pavement wearing courses is still restricted in India whereas RAP is allowed in wearing courses like BC in other countries like the US [5] and Canada [6]. We carried out this study to understand the BC RAP Mix properties and remove the barrier of using RAP in BC wearing courses.
2 Materials and Recycling Method Milled material from traceable sources can have very consistent properties and may not require further processing. In some cases, it may be desirable to screen or fractionate traceable source RAP to remove oversize particles to use the material in new asphalt concretes [5]. The RAP from a single layer has homogenous properties (aggregate type and grading curve, bitumen content, and bitumen characteristics) [7]. The mill speed at the job site should be controlled and kept uniform to promote consistency in the resulting RAP. These millings are very consistent and can be used in new mixes without further screening or crushing, saving processing costs [5]. For this study, the RAP material was obtained from the existing National Highway section in the southern part of India which was subjected to fatigue, aging, and weathering for 10 years. RAP was extracted from the existing bituminous concrete pavement consisting of a 40 mm BC layer and a 110 mm Dense bituminous macadam
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Fig. 1 Milling of existing pavement using Wirtgen W130 and stockpiling
(DBM) layer. The top 50 mm of pavement surface is milled in small-sized chunks using Wirtgen W130 Milling Machine at a uniform speed as shown in Fig. 1. Virgin aggregates have been collected from one of the aggregate sources available in the southern part of India. Modified bituminous binder of PMB 70–10 V Grade is used in this study where V represents the Very Heavy Service Condition which means Traffic levels of 10–30 million ESALs or Slow-moving traffic/Standard traffic (< 20 km/h) [8] and procured from one of the manufacturing plants in the southern part of India. The Hot In-Plant recycling process is used in the pilot project. This process involves producing and laying hot mix materials, not only virgin aggregates and binder but with a combination of reclaimed stockpiled aggregates already coated with binder and additional virgin aggregate and fresh binder to meet the requirements of the design [4].
3 Methodology In this study, the collected RAP sample was screened using a sieve arrangement such that aggregate greater than 19 mm in size was rejected since the Nominal Maximum Aggregate Size (NMAS) for bituminous concrete of grade II was 13.2 mm. The basic quality control testing of RAP materials involves the determination of RAP binder content, RAP aggregates gradation, and RAP aggregates testing. Additional tests such as RAP binder properties testing are only recommended for mixtures with RAP contents exceeding 25% [9]. To determine the percentage of the binder content present in the RAP material, bitumen extraction was done following IRC: SP 11–1988 (Appendix -5), “Method of test for binder content for paving mixtures by centrifuge” [10]. After extraction, the binder content and gradation of RAP Aggregate Material are determined and are represented in Table 1. In RAP Aggregate gradation, the percent passing 9.5 mm is exceeding the upper limit range specified as per MoRTH(2013) but after blending the RAP aggregate with Virgin aggregate the final gradation results are passing the specification limits specified in the MoRTH(2013) as mentioned in Table 4.
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Table 1 RAP binder content and gradation (After centrifuge extraction) Description
RAP
Binder content (%)
4.86
MoRTH 2013 Specification limits for BC
I.S. Sieve (mm)
Percent passing
Lower limit
Upper limit
19.00
100.00
100
100
13.20
94.75
90
100
9.50
88.54
70
88
4.75
65.90
53
71
2.36
48.95
42
58
1.18
41.21
34
48
0.600
33.39
26
38
0.300
22.67
18
28
0.150
15.57
12
20
0.075
7.95
4
10
The various tests were conducted on the extracted RAP aggregate samples and virgin aggregate samples, and the results are represented in Table 2. Also, various tests were conducted on the PMB 70-10 V Virgin binder samples and the results are represented in Table 3. Table 2 Properties of aggregates Test property
IS code
RAP aggregate
Virgin aggregate
MoRTH 2013 specifications
Aggregate impact value, % IS 2386 (Part IV)
21.42
17.8
24 Max
Combined flakiness and elongation index, %
IS 2386 (Part I)
31.36
19.5
35 Max
Specific gravity
IS 2386 (Part II)
2.562
2.69
2.5–3.0
Water absorption value, %
IS 2386 (Part III)
1.2
0.43
2.0 Max
Stripping value, %
IS 6241
96
98
95 Min
Polished stone value
BS 812–114
65
60.2
55 Min
Soundness, %
IS 2386 (Part V)
3.6
0.5
12.0 Max
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Table 3 Properties of bitumen (PMB 70-10 V) Test property
Code
Result
Requirements as per IS 15462:2019
Softening point (Ring and ball), °C, Min
IS 1205–1978
67
65
Elastic recovery @15 °C, Percent, Min
IS 15462:2019
78
70
Viscosity at 150 °C, Pa.s
ASTMD 4402
0.75
1.2
Complex modulus (G*) divided by sin delta (G*/sin(δ)) as Min 1.0 kPa
IS 15462:2019
2.717
1
Phase angle (δ) degree, Max
IS 15462:2019
68.9
75
Separation, Difference in softening point (Ring and Ball), °C, Max
IS 15462:2019
0.8
3
Flash point, °C, Min
IS 15462:2019
269
230
Loss in mass, percent, Max
IS 15462:2019
0.35
1
Complex modulus divided by sin delta (G*/ sin(δ)) as Min 2.2 kPa
IS 15462:2019
4.88
2.2
(a) MSCR, Jnr 3.2 at 70 °C, kPa, Max (b) MSCR, Jnr diff at 70 °C, Percent, Max
IS 15462:2019
0.79 57.39
1 75
IS 15462:2019
3465
6000
Tests on original binder
Tests on rolling thin film oven (RTFO) residue
Tests on pressure aging vessel (PAV) residue Complex modulus multiplied by sin delta (G*sin(δ)) as Max 6000 kPa
3.1 Mix Design In this study, Hot In-Plant Recycling (HIP) process is particularly focused on. As per IRC and MoRTH, 30% or less RAP is to be blended with virgin aggregate for the HIP recycling process [4]. As per MS-2 Asphalt Mix Design Method if RAP content exceeds > 25%, a more comprehensive mix design process is needed i.e., Blend charts need to be developed using the binder recovered from the RAP and virgin binder to determine the percentage of RAP that provides the desired binder and mix properties [11]. Hence in this study, 25% of RAP is added to virgin aggregates in proportion to the weight of aggregates in the BC mix. As per MS-2 Asphalt Mix Design Method, the standard recommendation is to select virgin binder one grade softer than would normally be selected and does not require tests on recovered RAP Binder. The simplification work when RAP having 4–6% asphalt binder content is used in an asphalt
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Table 4 Aggregates blending for RAP blended BC grade II Blending proportion IS.sieve (mm)
20.33% (18 mm)
10.16% (10 mm)
45.73% (4.5 mm)
23.78% (RAP aggregate)
100.00% blending result
MoRTH specification limits
19.00
22.36
10.16
43.70
23.78
100.0
100
13.20
20.12
10.16
43.70
22.53
96.5
90–100
9.50
8.06
10.16
43.70
21.05
83.0
70–88
4.75
0.09
2.96
43.70
15.67
62.4
53–71
2.36
0.03
0.11
39.40
11.64
51.2
42–58
1.18
0.00
0.04
33.25
9.80
43.1
34–48
0.600
0.00
0.00
26.07
7.94
34.0
26–38
0.300
0.00
0.00
16.23
5.39
21.6
18–28
0.150
0.00
0.00
8.91
3.70
12.6
12–20
0.075
0.00
0.00
2.28
1.89
4.2
04–10
mixture with a design asphalt binder content of approximately the same values (4– 6%), then the RAP percentage in the mixture is effectively the same as the RAP binder percentage. In this study, the RAP binder percentage is 4.86, design asphalt binder content percent is 4–6, and the selection of one grade softer is suitable for the RAP blended BC Mix design. PMB 70-10 V is used as a virgin binder, and RAP BC Mix is designed following MS-2 Asphalt Mix Design Method. Blending is done with a combination of RAP aggregates and virgin aggregates, and the results are represented in Table 4.
4 Results and Discussion The Marshall sample molds of RAP blended BC Mix (RAP binder plus virgin binder) and conventional BC Mix (Virgin binder) were cast with the various binder content proportions of 5.00, 5.20, 5.40, 5.6, and 5.8%, respectively. The Volumetric and Marshall properties of the RAP blended BC Mix are in close range to that of the conventional BC mix summarized in Table 5. From the results, the optimum binder content for BC conventional mix is 5.4% (Virgin binder) whereas 5.6% (RAP binder plus virgin binder) for RAP blended BC Mix. At Optimum binder contents, both the mixtures fulfill the minimum stability, Flow Value and satisfy the air voids, VMA, and VFB requirements respectively. From the graphs shown in Fig. 2, with an increase in binder content for both mixes the Bulk density increased, %Air voids decreased, %VMA decreased, %VFB increased, and flow increased which are following a general trend as given in MS-2 Asphalt Mix Design Methods [11]. Whereas stability decreased until 5.4% binder content and then increased which is a different trend but fulfilling the minimum stability criteria as per MoRTH (2013) for all binder contents.
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Table 5 Marshall test results for BC conventional and 25% RAP blended BC mix BC
BC RAP
BC
BC RAP
BC OBC
BC RAP
BC
BC RAP OBC
BC
BC RAP
%Virgin binder
5
3.846 5.2
4.048 5.4
4.251 5.6
4.453 5.8
4.655
% RAP binder
0
1.154 0
1.152 0
1.149 0
1.147 0
1.145
Bulk density, gm/cc
2.434
2.388 2.430
2.399 2.443
2.410 2.444
2.422 2.449
2.428
% Air voids
5.48
7.33
6.07
5.04
4.42
4.11
4.78
3.79
3.17
1.73
%VMA
13.86 14.73
14.19 14.51
14.16 14.3
14.06 14.06
14.06 14.03
% VFB
60.5
50.19
66.3
58.18
73.22 64.74
77.45 68.56
87.73 70.72
22.1
19.4
21.7
21.0
21.2
20.79 21.7
20.1
22.8
1.6
3.2
2.2
3.5
2.6
3.4
4.1
3.2
Stability, 21.8 KN Flow, mm
2.8
2.9
The volumetric property data curves for both mixes have a constant offset, which indicates that BC mix volumetric properties are similar in RAP blended BC mix at additional virgin binder content of 0.2− 0.4%. Also, %VMA is similar in both mixes at 5.60 and 5.80% binder content. At 5.4% binder content the RAP blended BC Mix has exhibited a high percent of Air Voids and a low percent of Voids filled with bitumen with respect to BC conventional mix. RAP binder which is aged and highly viscous has less adhesion relative to the virgin binder which is in agreement with Ying, Y. et al. study that with aging asphalt binder the adhesion force increases initially and then decreases with aging time [12]. The RAP blended BC mix has exhibited a requirement of 0.2–0.4% more binder to coat the aggregates and to fill in the voids of the Mix as that of the conventional mix. At 5.6% OBC, all the Marshall properties of the RAP blended BC Mix are satisfied, and the Marshall stability value is in close range to that of the conventional BC mix.
5 Pilot Project and Challenges Faced The pilot project is being executed in the southern part of India as an initiative for the innovative practices on Indian Roads. We produced the BC RAP Mix using the Hot-In-Plant recycling process. We had laid 3 km of the section using 25% RAP in the bituminous concrete wearing course. Also, by using RAP in the BC layer, the Cost spent on the Virgin binder, and virgin aggregated is reduced by 18.41% with
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Fig. 2 Marshall test results of RAP blended BC mix and conventional BC mix
respect to BC conventional Mix. The Cost spent on materials for 1 km of the section is mentioned in Table 6. Whereas the overall materials, production, transportation, and laying cost is reduced by 8.77% with respect to BC conventional Mix. The Cost spent on overall materials, Production, and laying for 1 km of the section is mentioned in Table 7. The percent cost saved on materials is high whereas the percent cost saved is relatively low when production, transportation, and laying cost is considered because the Hot Mix Plant (HMP) output capacity (Tons Per Hour (TPH)) is being reduced
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due to an increase in the dry and wet mix cycle time for obtaining homogeneous blended BC RAP production. The following are the challenges faced and steps taken to overcome challenges during production and laying at the site. 1. A separate bin with a screen arrangement is set up for RAP feeding such that oversize material is rejected, as shown in Fig. 3. 2. The RAP material cannot be incorporated as virgin aggregates in HMP because excessive blue smoke will be produced if the recycled material comes into contact with the burner flame due to the combustion of the aged binder [13]. Hence Cold RAP is directly fed into the pug mill where the hot virgin aggregates heat the RAP material by conduction. So, to maintain the final mix temperature of 170–180 ˚C, the virgin aggregates were super-heated to a temperature of 200–210 ˚C. 3. In the HMP mix cycle time, the dry mix time is increased by 10 s and the wet-mix time by 15 s to allow the RAP to mix homogeneously with the virgin aggregates and virgin binder properly. However, the HMP production output capacity is reduced from 160 to 100 TPH. Table 6 The material cost of both mixes for 1 km laid length Carriageway type
Thickness (mm)
Width (m)
Quantity laid (MT)
BC Cost (|)
BC RAP cost (|)
Cost saved (|)
Cost saved (%)
4 Lane divided
30
8.75
740
26,10,727
21,30,153
4,80,574
18.41
Table 7 Overall materials, production, transportation, and laying cost of both mixes for 1 km laid length Carriageway type
Thickness (mm)
Width (m)
Quantity laid (MT)
BC cost (|)
BC RAP cost (|)
Cost saved (|)
Cost saved (%)
4 Lane divided
30
8.75
740
37,94,077
34,61,422
3,32,655
8.77
Fig. 3 RAP loading bin screen arrangement and loading RAP in the bin
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Fig. 4 RAP blended BC mix temperature loaded in the truck at HMP
4. The RAP blended BC Mix received at the HMP achieved a temperature of 200 ˚C sometimes due to overheating of aggregates as shown in Fig. 4. when the bitumen is overheated the bitumen will be less viscous and hence makes sufficient coating of the aggregate and the filling the excess voids in the mix and the rheological properties of the bitumen also changes due to which durability of the mix decreases [14]. So, the burning temperature in the rotary dryer is controlled without any fluctuations of more than 210 ˚C, and further, the laying and compaction temperature at the site is regularly checked and controlled for proper execution.
5.1 Pavement Condition of Pilot Project In general, pavements are subjected to various kinds of loading and different environmental conditions, over time that manifest various distresses and affect the pavement performance. These distresses include rutting, fatigue cracking, temperature cracking, transverse cracking, and age-related block cracking. Under a set of loading and environmental conditions the performance of the flexible pavements is a function of properties of asphalt concrete mixture, volumetric properties (air voids, VMA, specific gravity, and asphalt content), and mechanistic properties of HMA mixture, and underlying base and subbase and roadbed materials. The temperature also has detrimental effects on the performance of the pavement; if the temperature is too high it causes rutting and low temperature will cause thermal cracking [15]. We carried out the visual pavement condition survey to understand whether any distress occurred in the pavement during the construction stage in November 2021 and recently after 5 months of subjecting the pavement to traffic and different environmental conditions in April 2022. The Pavement condition of the RAP blended BC
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Fig. 5 RAP blended BC layer construction at the site in November 2021
Fig. 6 RAP blended BC layer surface condition in April 2022
layer was good during the construction stage as represented in Fig. 5. Also, distresses were not observed in RAP blended BC layer after 5 months as represented in Fig. 6.
6 Conclusions 1. At respective Optimum Binder Contents (OBC), both the Mixtures satisfied the Air Voids, VMA, and VFB requirements and also fulfilled the minimum stability and Flow Value. 2. OBC for BC conventional mix is 5.4% whereas OBC is 5.6% for RAP blended BC Mix because variability was observed in volumetric properties, i.e., air voids and VFB. This shows that the RAP binder, which is aged and highly viscous has less adhesion relative to the virgin binder; hence the RAP blended BC mix has exhibited a requirement of 0.2−0.4% more binder to coat the aggregates and to fill in the voids of Mix as that of the conventional mix. 3. RAP blended BC mix Marshall stability value (21.7kN) is in close range to that of conventional BC mix Marshall stability value (21.0kN) at respective OBC which indicates that RAP Hot-In-plant recycling is a recommendable process for the BC wearing course.
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4. Using the RAP blended BC Mix, the material cost spent on the virgin binder and virgin aggregated is reduced by 18.41% whereas overall materials, production, and laying cost is reduced by 8.77% with respect to BC conventional. 5. Pavement condition was good and distresses were not observed after the pavement was subjected to traffic load and environmental conditions for 5 months.
References 1. Bharatmala Annual Report 2020–2021: Government of India, Ministry of Road Transport & Highways New Delhi 2. Anil Kumar Y, Syed Aqeel A (2019) a critical review of characterization and performance evaluation of reclaimed asphalt pavement (rap) in road construction. Int J Civ Eng Technol (IJCIET) 10 (01): 1379–1389 3. Ministry Of Road Transport & Highways, Specifications for Road and Bridge Works (Fifth Revision) 4. IRC:120–2015: Recommended practice for recycling of bituminous pavements 5. Reclaimed Asphalt Pavement in Asphalt Mixtures: State of the Practice. No. FHWA-HRT-11– 021. Federal Highway Administration: McLean, VA, USA 6. Ontario provincial standard specification, OPSS.MUNI 1151 7. Van Den Kerkhof E (2012) Warm waste asphalt recycling in Belgium-30 years of experience and full confidence in the future. In: Proceedings of the 5th Eurasphalt & Eurobitume Congress. Instambul, Turkey 8. IS 15462–2019: Polymer Modified Bitumen (PMB) Specification (First Revision) 9. Newcomb DE, Brown ER, Epps JA (2007) Designing HMA mixtures with high rap content: a practical guide; quality improvement series 124; NAPA: Lanham. MD, USA 10. IRC: SP 11–1988: Handbook of quality control for construction of roads and runways 11. MS-2 Asphalt Mix Design Methods.7th edn. Asphalt Institute 12. Ying Y, Xingyi Z, Long C (2020) Relationship among cohesion, adhesion, and bond strength: From multi-scale investigation of asphalt-based composites subjected to laboratory-simulated aging. Mater & Des 185. Article 108272 13. Kandhal PS, Mallick RB (1997) Pavement recycling guidelines for state and local governments. No. FHWA-SA-98–042. National Center for Asphalt Technology, Auburn, AL, USA 14. Samir B, Gautam Bir Singh T (2019) The study of effects of the overheated bitumen on the binder content and the marshall properties of the asphalt concrete, vol 2 issue 3. HBRP Publication 15. Mohammad JK, Nagaraju P (2020) Flexible pavement performance in relation to in situ mechanistic and volumetric properties using LTPP data, vol 2013. Hindawi Publishing Corporation ISRN Civil Engineering. Article ID 97 16. IS 2386–1963: Methods of test for aggregates for concrete 17. IS 6241–1971: Method of test for determination of stripping value of road aggregates 18. ASTM D 4402: Standard test method for viscosity determination of asphalt at elevated temperatures using a rotational viscometer
Successful Utilization of High Amount of Reclaimed Asphalt Pavement Material in Bituminous Pavements: Indian Case Study G. Bharath, Ambika Behl, Siksha Kar, and Satish Chandra
Abstract Reclaimed Asphalt Pavement (RAP) Material can be recycled into a fresh bituminous mixture by heating and mixing with fresh aggregates and binder. Since the RAP bitumen undergoes aging during the service life, it cannot be used directly without modification with softer virgin bitumen and/or rejuvenators to avoid premature cracking in pavements. The amount of RAP that can be included in bituminous mixtures is limited because the mixtures with high RAP content will have increased susceptibility to cracking due to aged RAP bitumen. Therefore, the rejuvenators can be used to soften the RAP bitumen. A case study demonstrates an increase in the percentage of RAP material (around 80%) in a bituminous mixture treated with a rejuvenator and characterizes the mixture’s quality. The main objective of this study is to provide a RAP mix design using hot in-place recycling technology for renewal treatment/preventive maintenance work of existing pavement of the Ranchi ring road project in the state of Jharkhand. In the laboratory, two rejuvenators (Tall oils and Paraffinic Oils) were evaluated to check its efficacy when blended with the RAP binder. In addition, the influence of rejuvenators was evaluated on extracted binders and mixtures conducted in various tests, such as softening point, penetration, and rheological properties at various dosages of rejuvenators. The Marshall method of mix design was adopted in this study for the mix design of HMA with 80% RAP content. In the field (Ranchi outer ring road), around 80% RAP material was successfully used in the surface layer (50 mm Bituminous Concrete layer) using a hot in-place recycling method. Required quantities of fresh aggregate, virgin binder, and rejuvenators are added to the RAP material milled from the pavement. Then, RAP, fresh aggregate, virgin binder, and rejuvenator are mixed well and compacted to the required thickness. Results showed that bituminous mix containing 80% RAP with tall oil rejuvenator fulfilled desired properties of surface layer mix.
G. Bharath (B) · A. Behl · S. Kar Central Road Research Institute, Delhi, India e-mail: [email protected] S. Chandra Indian Institute of Technology, Roorkee, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_10
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Keywords Recycled asphalt pavement · Binder extraction · RAP gradation · RAP blending · Marshall stability
1 Introduction 1.1 General The rise in construction activity has caused an increase in material demand, which has allowed for the depletion of natural resources such as stone aggregates. This has prompted those concerned to look into alternative methods, like reusing waste from existing road pavements. Milling distressed pavements and reusing them completely or partly is an accepted procedure now to conserve fresh aggregates. Road building agencies are increasingly exploring ways to re-employ such materials and are being allowed and encouraged by the national standard methods like IRC to do so. Reclaimed asphalt pavements materials are derived by the process of milling or excavation. These materials are crushed and screened to the designed size to meet the respective gradation requirements [1]. Incorporating RAP materials with virgin aggregates is one of the environmentally friendly and economical alternatives [2]. In addition, usage of high content RAP can result in 50–60% cost reduction in the preparation of bituminous mixes [3]. Previous studies indicate that high binder stiffness, variability, inconsistency of resources, and inadequate blending between recycled and virgin material are some prominent reasons for incorporating a low percentage of RAP [4, 5]. According to the FHWA survey, many state transport agencies allow using RAP for up to 30%. However, the majority incorporated only 10–20% of RAP in mix design [6]. A certain additional performance test is required in conventional mix design procedure while including more than 20% of RAP [7]. However, RAP material is aged and stiffer material which leads to brittle and fatigue failure of pavement [8, 9, 10, 11]. A solution to this literature suggests that using softer virgin bitumen, a high amount of conventional bitumen, or the addition of rejuvenating agents can be some of the ways to compensate for the negative effect of RAP in the mix [12]. Rejuvenators for HIR (hot in-place recycled) mixtures are typically hydrocarbons that are intended to help in restoring chemical and rheological properties of RAP binder to a consistency level appropriate for construction purposes [13, 14]. These are used for pavement preservation by penetrating the pavement by improving the maltene to asphaltene ratio of the aged binder [13]. Rejuvenator enhances the binder flexibility, which mitigates low temperature cracking and improves the fatigue performance of pavement [15, 16]. It provides adequate extra binder to coat the RAP and added aggregate, as well as to meet the mix design standards. The rejuvenator used in HIPR should be easily dispersed in the recycled mix and consistent with the aged asphalt binder to prevent separation like syneresis or paraffin exudation from the
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binder. RAP mixes rejuvenated with tall and paraffin oil show similar resistance for rutting and fatigue parameters compared to virgin mix [19, 20]. The paper industry generates tall oil as a byproduct. They are used widely in hot mix-manufacturing as emulsifiers, anti-striping agents, and warm mix additives. It was observed that tall oil improves the fatigue life of RAP mixtures. Tall oil is preferred for the analysis because it is observed that, to achieve similar physical properties to the virgin mix, rap mixes rejuvenated with paraffin oil require a high dosage of it when compared to rejuvenation with fatty acids and tall oil. Also, the mix rejuvenated by paraffin oil shows minor fatigue performance. It increases the aging susceptibility of samples due to increased loss of volatile fractions. It can be inferred that paraffin oil is not compatible with RAP and is not able to rebalance the chemical compositions of RAP due to its straight-chain aliphatic molecular structure.
1.2 Objective and Scope The objective of the project is to provide RAP mix design hot in-place recycling technology for renewal treatment/preventive maintenance work of existing pavement of Ranchi ring road project in the state of Jharkhand. To meet the above-stated objective, the scope of work included the following activities: • Reclamation and evaluation of aggregate and binder properties of mix samples obtained from the field. • Blend formulations of combined RAP and new aggregates to achieve desired gradation and preparation of viscosity and blending chart to decide the required dosage of rejuvenator and new binger grading. • New/fresh aggregate gradation, estimation of fresh aggregate, and fresh binder required for the recycled mix. • Trial mix design using Marshall method and selection of the section of job mix formula.
2 Field Investigation 2.1 Background The pavement section of Ranchi ring road, a six-lane carriageway in the state of Jharkhand, India, is selected for the collection of recycled material for laboratory testing. Field cores obtained from the site are shown in Fig. 1. The RAP obtained is eight years older, having VG 30 bitumen. The material evaluation aims to prepare samples, evaluate, and determine the significant properties of asphalt to achieve an optimized blend of materials to satisfy the ultimate mix requirement. The task entails sampling and evaluating aged mix (RAP mix), rejuvenator or recycling agent, virgin aggregates, and bitumen.
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Fig. 1 Field cores received from the sit
3 Laboratory Investigation 3.1 Physical Properties of RAP and Fresh Binders A total of 140 field cores were received from the site shown in Fig. 1. The cores were taken in a staggered manner covering all the lanes and were sorted by section/ chainage. The cores were selected from the outer wheel path of the pavement. Bulk density measurements were carried out for all the cores. The core samples received from the site were marked as Sects. 3, 4, 5, and 6. The average bulk density of field cores was found to be 2.4gm/cc.
3.2 Binder Extraction From each section and different lanes, about 4–5 core samples were taken for aggregate gradation, and 4–5 samples were taken for RAP bitumen recovery. To determine the grading of the existing aggregates, mechanical sieve analysis (conforming to IS:2386(part-I)) was performed on the aggregates recovered from the reclaimed bituminous pavement. Gradation of the reclaimed asphalt pavement (RAP) material for BC-II grading was done as per MoRTH [18] Section 500 standards.
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Fig. 2 Bitumen extraction using the Abson recovery method
Table 1 Physical properties of binders
Parameter
Penetration @ 25 °C
Viscosity @ 60 °C
Softening point
0.1 mm
Poise
°C
RAP
15
9000
75
VG 10
89
1000
48
Bitumen was extracted from the core samples using a Bitumen extractor. The bitumen recovery process was performed using distillation and Abson recovery methods as per ASTM D 2172 and ASTM D 1856, respectively. The recovery process is shown in Fig. 2. The average binder content in RAP was determined to be 4.5% by total RAP weight. Properties of the binder extracted from the RAP and virgin binder VG 10 are given in Table 1.
3.3 Blending Process of RAP and Aggregates Aggregate materials available for gradation were 20 mm, 10 mm, dust, lime, and extracted RAP material. Different proportions of the remaining three sizes of aggregates required to achieve the target gradation specified by the Ministry of Road Transport and Highways (2013) for the BC-II mix are selected from the blending exercise. RAP processing alters its aggregate gradation, and the number of fines produced severely limits the quantity of RAP added to the asphalt mixture. From the blending exercise, it was found that around 80% of reclaimed aggregates can blend with fresh aggregates from the target gradation consideration. Figure 3 shows the aggregate gradation.
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Fig. 3 Aggregate blending chart for BC-II
3.4 Mix Design Procedure After determining the relative aggregate proportions, a trial demand for the total binder was computed. The new asphalt binder grade was then chosen to recover the aged bitumen properties and recommend a final binder that fulfils the performance requirements while achieving the asphalt demand. After this, the optimum bitumen content was determined by the Marshall Method of mix design and MORTH (2013) [18] specifications for the BC-2 grading mix. The empirical formula shown in Eq. (1) determines the approximate asphalt demand of the combined aggregates which given by Asphalt Institute Manual MS-20. P = 0.035a + 0.045b + K c + F
(1)
According to the selected aggregate gradation, the total approximate asphalt demand of P 5.567% was obtained. The following Eq. (2) helps to calculate the amount (in percentage) of new asphalt required (Pnb) for the recycled mixture trials. It results in 2.01% new asphalt being added to the trial mixes. While the quantity of new asphalt to be added (R) was found to be 36.1 using Eq. (3). Pnb
1002 − r Psb Pb (100 − r )Psb − = 100(100 − Psb ) 100 − Psb
(2)
100Pnb Pb
(3)
R=
3.5 Rejuvenator In this study, two types of rejuvenator, Sylvaroad RP1000 (RA 1) and Savsol Rejuvenating oil (RA 2), were used. The rejuvenator blending process was performed
Successful Utilization of High Amount of Reclaimed Asphalt Pavement … Table 2 Critical temperatures for different rejuvenator dosages
121
Binder type
The critical temperature, °C Rejuvenator dosage
RA –1
RAP binder
0%
99
RA – 2
3%
95
94.5
5%
90.7
92
7%
87
90.3
Fresh binder
VG 10
63
Target binder
VG 40
81
on the binder heated at 130 ◦ C for 30 min. The additives were introduced into the hot bitumen at 100 to 135 ◦ C. To homogenize and remove any bubbles, the prepared blends should be continuously stirred for 30 s after every 5 min interval for the next 10 min. The treated sample is then ready for evaluation. Two different rejuvenators (RA 1 and RA 2) were mixed separately with reclaimed binder at 3%, 5%, and 7%. The reclaimed binder mixed with different dosages of RA 1 and RA 2 was tested using the procedures in AASHTO M 320 to determine the critical temperatures where the specification criteria are precisely met. Temperature-Frequency Sweep test was performed in DSR (Dynamic Shear Rheometer) from a temperature of 60−110 °C to determine the critical temperature where the G*/sinδ value exactly meets 2.20 kPa shown in Table 2. RTFO (rolling thin film oven) aging was performed on the reclaimed binder before carrying out the DSR test. RTFO aging of the recovered binder is done so that any residual solvent left from the recovery procedure would be removed. The critical temperature values obtained were used to prepare the blending charts. VG 10 is used as a fresh binder in the mix design. RAP pavement binder ratio (RPBR) is shown on X-axis. Critical temperatures of the RAP binder with different RA dosages are shown on a right vertical axis. The critical temperature of the fresh binder is shown on a left vertical axis. VG 40 is considered a target binder. From Fig. 4, for RA-1 (5% by weight of RAP Binder), RPBR is 64.9 (0.649), and for RA-2 (7% by weight of RAP Binder), RPBR is 65.9 (0.659). That is, by using a lower dosage of RA-1 rejuvenator, we can achieve similar RPBR. Therefore, in further study, the RA-1 type of rejuvenator was used for the preparation of bituminous mixes and testing.
3.6 Mix Preparation Trial specimens were prepared as per Marshall Method. Proportions of fresh asphalt binder (Pnb ), RAP percent (Psm ), and new/additional Aggregate percent (Pns ) were estimated as per the following equations. The proportions worked out for different total binder contents of 4.0% to 6.0% are given in Table 3.
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Fig. 4 Asphalt blending chart for RA 1 and RA 2
Table 3 Estimation of proportions of different components for RAP mix-BC-2 Pb
Pnb
Psm
Pns
RAP (gm)
New aggregate (gm)
4
0.38
80.42
19.2
1005.2
240.0
4.8
1250
4.5
0.9
80.00
19.1
1000.0
238.8
11.3
1250
5
1.42
79.58
19
994.8
237.5
17.7
1250
5.5
1.94
79.16
18.9
989.5
236.3
24.2
1250
6
2.46
78.74
18.8
984.3
235.0
30.7
1250
Pnb =
New bitumen (gm)
Total Mix (gm)
(100 − r )Psb (1002 − r Psb )Pb − 100(100 − Psb ) 100 − Psb
(4)
100(100 − r ) (100 − r )Pb − 100 − Psb 100 − Psb
(5)
Psm =
Pns = r −
r Pb 100
(6)
The mixing protocol was based on the most recent standard (MS-2 [17]) and laboratory mixing experiences. The mixing method consists of several stages. Stage I is to dry and heat the virgin aggregates above the mixing temperature (150-155C) by a certain amount. Even though actual mixing temperatures differ, a good thumb rule is to raise the temperature of virgin aggregates by 0.5 °C for each percentage of RAP mix. Thus, for a mix with 80% RAP, the mixing temperature of the virgin aggregate should be raised by 40 °C. Dry and warm the RAP material at a temperature of 120 °C to 130 °C for 2 h is stage II. Following to this, in stage III, the virgin binder is heated at the mixing temperature (150–155°C). In stage IV, RAP material, rejuvenator, and virgin aggregated are mixed with a hot virgin binder to get a homogeneous asphalt
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Table 4 Marshall test results for BC-2 grading Property
Binder content (%) 4
4.5
5
5.5
6
Gmb
2.387
2.439
2.468
2.474
2.468
Gmm
2.634
2.613
2.591
2.577
2.55
Air voids (%)
9.36
6.64
4.77
3.99
3.23
Gse
2.82
2.82
2.82
2.82
2.82
Gsb
2.771
2.771
2.771
2.771
2.771
Pba
0.64
0.64
0.64
0.64
0.64
Pbe
3.36
3.86
4.36
4.86
5.36
VMA
17.29
15.94
15.39
15.63
16.29
VFB
45.84
58.34
69.04
74.44
80.16
Stability (kN)
15.13
17.86
19.16
22.36
14.59
3.99
3.63
3.29
3.61
3.87
Flow (mm)
mix and achieve a complete coating on the aggregate. Once the batching and mixing process is complete, the mix design procedure is unchanged by the addition of RAP.
4 Results 4.1 Marshall Test Results Marshall Test results for BC-2 are given in Table 4. It can be observed that mix air voids of 4% was obtained at a binder content between 4.5 and 5%. VMA increased with the addition of RAP.
4.2 Moisture Resistance of RAP-Modified Mixes In the laboratory, mixes were compacted to 7% air voids using a Marshall compactor. The Indirect tensile strength test was performed on cylindrical specimens of 100 mm in diameter and 63.5 mm in height. Moisture conditioning of the specimens was done in accordance with AASHTO T 283 (2006). The samples were placed in a vacuum container saturated for 5–10 min at 67 kPa (AASHTO T 283, 2006). After reaching a saturation level of 55 to 80%, the samples were placed in a hot water bath preserved at 60 ± 0.5 °C for 24 ± 1 h. Following that, the samples were maintained at 25 ± 0.5 °C for 2 h using a water bath. The ITS values of conditioned and unconditioned specimens and the corresponding Tensile Strength Ratio (TSR) values are given in Table 5. As observed,
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Table 5 The moisture resistance of RAP mixes Mix type
ITS (kPa) unconditioned
ITS (kPa) conditioned
TSR %
Specified value min %
Without lime
782
580
74
80
With lime (1%)
910
850
93
RAP mixes without lime did not offer any resistance to moisture damager (74%), and the inclusion of 1% lime improved the same resulting in a TSR value of 93% while the minimum requirement is 80%.
4.3 Recommended Job Mix Formula Job mix formula with a maximum RAP amount of 80% was recommended for the rehabilitation of distressed pavement for construction. The Marshall properties obtained at optimum binder content and other details of the Job Mix Formula are given in Table 6. It can be noticed that Marshall’s stability is significantly higher than the requirements, and at the same time, the mix has sufficient Marshall flow properties. The optimum total binder content obtained corresponding to a median air void content of 4% is 5.5% by weight of the total mix. Properties of the bituminous mix at O.B.C are given in Table 6. The corresponding fresh bitumen content of VG10 was 1.94%. As mentioned earlier, rejuvenator dosages, as shown in Table 7, were recommended to reduce the stiffness of the materials. Since 80% RAP shall be used in the construction, VG 10 binder dosage is relatively lower so that a blend of fresh binder and rejuvenated RAP binder can act as a binding material. Figure 5 shows the successful implementation of hot in-place recycled pavement stretch with 80% OF RAP material. Table 6 Mix design details of RAP
Parameter
BC−II
Specification
Bulk density, g/cc
2475
−
Voids in compacted mix %
4.1
3−5%
Voids filled with bitumen %
74.44
65−75%
Voids in mineral aggregates %
15.5
14% min
Marshall Stability kN
19.5
9 kN
Flow value, mm
3.5
2−4 mm
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Table 7 Proportional details of the proposed mix design Material
Percentage, %
RAP material
79.16
Fresh aggregates (10 mm + dust)
18.90
10 mm aggregates
4.70
Dust
13.20
Lime
1
Fresh bitumen
1.9
Rejuvenator
5% weight of RAP binder (RA 1) or 7% weight of RAP binder (RA 2)
Fig. 5 RAP reclamation process on the field
5 Observations and Recommendations Extensive laboratory tests were carried out to arrive at the above-given job mix formula for HPR mix design. Care shall be taken while implementing the given JMF (Table 7) on-site. • 80% RAP with RA-1 type of rejuvenator was recommended for the field implementation on the surface layer and constructed successfully for the first time in India. • Fresh bitumen to be used should be VG 10 grade having absolute viscosity (60°C) in the range of 900−1100cP. • 1% lime shall be added to have better moisture resistance in the mix. • The rejuvenator to be used should be as per ASTM D 4552:2016 and capable of modifying the characteristics of the aged asphalt binder to the desirable level.
References 1. Hassan R (2009) Feasibility of using high RAP contents in hot mix asphalt. In: Proceedings of the 13th International flexible pavements conference 2. Ma Y, Polaczyk P, Park H, Jiang X, Hu W, Huang B (2020) Performance evaluation of temperature effect on hot in-place recycling asphalt mixtures. J Clean Prod 277:124093
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3. Moniri A, Ziari H, Aliha MRM, Saghafi Y (2021) Laboratory study of the effect of oil-based recycling agents on high RAP asphalt mixtures. Int J Pavement Eng 22(11):1423–1434 4. Kaseer F, Bajaj A, Martin AE, Arámbula-Mercado E, Hajj E (2019) Strategies for producing asphalt mixtures with high RAP content. J Mater Civ Eng 31(11):05019002 5. Mallick RB, O’Sullivan KA, Tao M, Frank R (2010) Why not use rejuvenator for 100% RAP recycling? (No. 10–1838) 6. Copeland A (2011) Reclaimed asphalt pavement in asphalt mixtures: State of the practice (No. FHWA-HRT-11–021). United States. Federal Highway Administration. Office of Research, Development, and Technology 7. Moghaddam TB, Baaj H (2016) The use of rejuvenating agents in production of recycled hot mix asphalt: A systematic review Constr. Build Mater 114:805–816 8. Izaks R, Haritonovs V, Klasa I, Zaumanis MJPE (2015) Hot mix asphalt with high RAP content. Procedia Eng 114:676–684 9. Veeraragavan RK (2016) An investigation of the performance of hot mix asphalt (HMA) binder course materials with high percentage of reclaimed asphalt pavement (RAP) and rejuvenators. Worcester, MA: Worcester Polytechnic Institute 10. Zaumanis M, Mallick RB, Frank R (2014) 100% recycled hot mix asphalt: A review and analysis. Resour Conserv Recycl 92:230–245 11. Zhang Y, Bahia HU (2021) Effects of recycling agents (RAs) on rutting resistance and moisture susceptibility of mixtures with high RAP/RAS content. Constr Build Mater 270:121369 12. Ziari H, Moniri A, Bahri P, Saghafi Y (2019) The effect of rejuvenators on the aging resistance of recycled asphalt mixtures. Constr Build Mater 224:89–98 13. Hajj EY, Sebaaly PE, Shrestha R (2009) Laboratory evaluation of mixes containing recycled asphalt pavement (RAP). Road Mat Pavement Des 10(3):495–517 14. Brownridge J (2010) The role of an asphalt rejuvenator in pavement preservation: use and need for asphalt rejuvenation. In: Compendium of papers from the first international conference on pavement preservation. Newport Beach CA, USA, pp 351–364 15. Hussein ZH, Yaacob H, Idham MK, Abdulrahman S, Choy LJ, Jaya RP (2020) Rejuvenation of hot mix asphalt incorporating high RAP content: issues to consider. In: IOP Conference Series: Earth and Environmental Science, vol 498, no 1. IOP Publishing, p 012009 16. Mogawer WS, Booshehrian A, Vahidi S, Austerman AJ (2013) Evaluating the effect of rejuvenators on the degree of blending and performance of high RAP, RAS, and RAP/RAS mixtures. Road Mater Pavement Des 14(sup2):193–213 17. Shen J, Amirkhanian S, Lee SJ (2005) The effects of rejuvenating agents on recycled aged CRM binders. Int J Pavement Eng 6(4):273–279 18. MS-2 (2015) Manual series no-2-asphalt mix design methods, 7th edn. Asphalt Institute, USA 19. MoRTH (2013) Specifications for road works and bridges, Ministry of Road Transport and Highways, 5th edn. New Delhi, India 20. Guduru G, Kumara C, Gottumukkala B, Kuna KK (2021) Effectiveness of different categories of rejuvenators in recycled asphalt mixtures. J Transp Eng, Part B: Pavements 147(2):04021006 21. Zaumanis M, Mallick RB, Poulikakos L, Frank R (2014) Influence of six rejuvenators on the performance properties of reclaimed asphalt pavement (RAP) binder and 100% recycled asphalt mixtures. Constr Build Mater 71:538–550
Suitability of Rejuvenator Addition Method for Hot Mix Asphalt Recycling Ankit Sharma, Gondaimei Ransinchung Rongmei Naga, and Praveen Kumar
Abstract In India, recycling of the reclaimed asphalt pavement (RAP) material has increased noticeably during the last decade. Several issues like active RAP binder in the RAP material are yet to be resolved. Moreover, the method of rejuvenator addition in the hot recycled mix is an open topic to debate. In the hot in-place and hot in-plant recycling processes, a rejuvenator is added to the RAP material. Also, some hot inplant units/batch plants add a rejuvenator in the bitumen tank, which (soft binder) is later mixed with RAP and virgin aggregates in the pug mill mixer. In the present study, the suitability of the rejuvenator addition method has been evaluated through an experimental study. The two mixing methods were analyzed. In the first method (soft binder), the rejuvenator was blended with the base binder and mixed with the virgin aggregates and the RAP material. In the second method (rejuvenated RAP), the rejuvenator was directly added to the warm RAP material and conditioned. Then, the rejuvenated RAP was mixed with the base binder and the virgin aggregates. The experimental campaign includes indirect tensile strength (ITS), Marshall stability (MS), tensile strength ratio (TSR), Marshall quotient (MQ), and an analysis of the volumetric parameters, viz., percent air voids (Va, %), voids in mineral aggregates (VMA), etc. The results indicated that the MS, ITS, and TSR have improved by shifting to the rejuvenated RAP method from the soft blend method. As statistically proved, it can be concluded that the rejuvenated RAP method is better than the soft binder method. Keywords Reclaimed asphalt pavement · Rejuvenator · Mixing method · Rejuvenated mix · Soft binder
A. Sharma (B) · G. R. Rongmei Naga · P. Kumar Civil Engineering Department, IIT Roorkee, Roorkee, India e-mail: [email protected] A. Sharma Civil Engineering Department, Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), Jaipur, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_11
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1 Introduction Recycling flexible pavement is a general practice in many developed countries. The hot mix asphalt recycling technology has gained sufficient acknowledgment and adaptation in India in the past decade. Indian Roads Congress (IRC) 120 (2015) [1] specified up to 30% RAP incorporation in the asphalt base course of the flexible pavement structure. However, several challenges arise, especially with high RAP content in the recycled asphalt pavement. Some of the challenges are as follows: modification in the mixing plant, moisture content of RAP material, percent aggregate coating of the final mix, the longevity of the recycled mix, etc. The standard modification in a batch mix plant is the provision of a separate conveyor belt to transport the RAP material to the pugmill mixer [5]. Moreover, a separate drum dryer should be provided for drying the RAP material. The drying of RAP material improves the economy of mix plant operation. The moist RAP material requires extra energy (or fuel) to maintain the mixing temperature in the mixer. Also, moist RAP can produce excessive smoke and pitting action in the mixer during the mixing process with virgin materials. Previous studies indicate that the rejuvenator addition location is of utmost importance concerning the quality of the resultant mix [2]. A plethora of studies investigated that the blending between rejuvenator, RAP binder, and virgin binder is not homogenous. Hence, to achieve better blending or more RAP binder activation, sufficient time is required for the diffusion of rejuvenator into the RAP aggregate’s aged binder coating [2–4]. The practical means to increase the retention time of rejuvenator over the RAP aggregate surface or how diffusion of rejuvenator can be improved have received far less attention. The present study aims to bridge the knowledge gap by comparing the two most widely used methods of rejuvenator addition in a batch mix plant. The first method is the rejuvenated RAP method (Rej RAP), where a rejuvenator is added to the dried (warm) RAP material, followed by mixing rejuvenator and dried RAP for 40 s. The second widely used method is the addition of a rejuvenator in a bitumen tank. The soft blend is used to mix with the dried RAP material to produce the final recycled mix. This method is named as soft binder (SB) method. According to the author’s practical experience, SB method is a convenient approach for the contractor. Because the Rej RAP method requires separate mixing and storage unit for Rej RAP material, before its addition to the pugmill mixer. The extra unit imposes extra cost and hence is avoided. In the present study, an attempt is made to investigate the efficiency of the rejuvenator addition method, which can activate more aged RAP binder and provide better strength of compacted recycled asphalt mix. Figure 1 indicates the methods of rejuvenator addition in a batch mix plant. Figure 1a indicates that the rejuvenator is pumped to the RAP drier, where the rejuvenator is added and mixed with dried RAP material and stored in a storage tank for the timely supply of the weighed quantity of rejuvenated RAP material in the mixer (pugmill). Similar to a conventional batch mix plant, the virgin aggregates, and bitumen are added to the pugmill. As shown in Fig. 1b, in the SB method, the rejuvenator is preblended with the base binder to prepare a soft blend that is supplied
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Fig. 1 Batch mix plant with (a) rejuvenator added over dried RAP material and (b) rejuvenator added in a base binder [5]
to the mixer. In both methods, dried RAP material was directly added to the pugmill mixer and not added through the screens and hot bins. The reason is the sticky dried RAP material which can chock the screens if added in high content (>30%) [6].
2 Objective To examine the suitability of rejuvenator addition location in an asphalt batch mix plant.
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3 Materials and Methods The RAP material was procured from Rajpath road, Delhi. The gradation of milled RAP material was found similar to Bituminous Concrete (BC) Grade-2 gradation of technical specification Ministry of Road Transport and Highways (MoRTH) [7]. The base binder (60/70 Pen grade) and three propriety rejuvenators (A, B, and C) were procured from Shell India Markets Pvt. Ltd. The High Performance Grade temperature criterion was used to determine the optimum rejuvenator content. The rejuvenator A, B, and C dosages are 12%, 6.5%, and 22%, respectively. The properties of the materials are provided in Tables 1 and 2. All samples were prepared by adding 40% RAP by weight of the total binder in the mix. The asphalt mixes were compacted using a Marshall compactor at 4% and 7% air voids for Marshall stability (MS) and indirect tensile strength (ITS) tests. The testing campaign includes two parameters, viz. volumetric and strength parameters. The volumetric parameters include air voids (Va, %), voids in mineral aggregates (VMA, %), and voids filled with bitumen (VFB, %). The strength parameters include MS, flow value (FV), ITS, and tensile strength ratio (TSR). A comparative study was carried out to determine the change in the values of the parameters between Rej RAP and SB method compacted recycled mixes. The conditioning time for Rej RAP method was 60 min at 100 °C. For the SB method, the mixing time was 40 s, and the mixing and compaction temperature was 160 °C and 150 °C, respectively. The results were statistically analyzed using a two-way analysis of variance (ANOVA) test (Fig. 2). Table 1 Properties of base (60/70) and RAP recovered binder S. No.
Properties
60/70 binder
RAP binder
1
Penetration
64
5
2
Softening point (°C)
49
91
3
Absolute viscosity (P)
2400
NA
4
ZSV (P)
4154
5,467,000
5
Complex viscosity (P)
4050
2,650,000
6
Flash point (°C)
230
290
7
True high PG (°C)
72
124
8
Rotational viscosity at 135 °C (Pa·s)
0.381
NA
9
Specific gravity
1.01
1.04
Table 2 Properties of rejuvenators S. No.
Property
A
B
1
Gs, 25 °C
0.86
0.95
2
ZSV, 60 °C (P)
0.70
0.74
C 0.99 16.5
Specification ASTM D 70 ASTM D7175
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Fig. 2 (a) Procured RAP material, (b) addition of rejuvenator on RAP material, (c) rejuvenated RAP material, and (d) blending of rejuvenator with a base binder to make a soft blend
4 Results and Discussion 4.1 Comparison of Volumetric Properties Between Rej RAP and SB Method As shown in Fig. 1, the volumetric properties of Recycled Hot Mix Asphalt (RHMA) and control mix (made with 60/70 binder only) are presented. As shown in Fig. 3a, irrespective of rejuvenator type and their dosages in the recycled mix, the Va of the rejuvenated RAP mix was lower than the soft blend method. The reduction in Va can be attributed to the diffusion of rejuvenator into an aged binder and making it available for the mixing process. The target Va was found between 2 and 3%, which indicates that either bitumen content or the number of Marshall hammer blows needs to be lowered to achieve the target Va of 4%. However, some agencies allow even 3% Va to allow more bitumen in the mixes [8]. The extent of variability from average results, i.e., coefficient of variation, COV was reduced by 7.8% when the Rej RAP method was adopted compared to the soft blend method. It can be concluded that the Rej RAP method activated the aged binder and reduced the air voids compared to the SB method. For SB method, the soft binder merely coated the RAP aggregates surface. Compared to the Rej RAP
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method, the SB method lacked activation of the aged binder coating. As shown in Fig. 3b, for both methods, the VMA was found in agreement with the standard specification of asphalt mixes [8]. Irrespective of rejuvenator type, the VMA of Rej RAP compacted specimens was less than the VMA of SB method specimens. Albeit of the same JMF and design method, the lower VMA in Rej RAP samples indicates the availability of a relatively more effective binder than in the SB method. VFB is an important criterion for accepting or rejecting marginally accepted mixes based on VMA. Previous literature indicates that the range of VFB ranges between 70 and 85% [5, 9, 10]. As shown in Fig. 3c, the VFB was found more in Rej RAP samples than in the SB samples. The results indicate that available bitumen increased when rejuvenated RAP was used instead of only dried RAP. It can be concluded that all three rejuvenators have activated the RAP binder coating over RAP aggregates.
4.2 Comparison of Asphalt Mix Properties Between Rejuvenated RAP and Soft Blend Method See Fig. 4. The MS can be defined as the peak failure load when the compacted asphalt mix is subjected to a 50.8 mm/min loading rate. According to the study conducted by Metcalf [11], the Marshall test is a confined test where the confining stresses are attributed to the curved-shaped heads of Marshall breaking mold. Moreover, the failure shear plane is similar to a direct compression test. The results indicate that the MS of Rej RAP mixes is more than the SB mixes. It can be attributed to the increased adhesion between recycled binder and the aggregates. Irrespective of rejuvenator type, there is an increase in MS of samples for the Rej RAP asphalt mix method. The FV is an indirect measure of internal friction of compacted asphalt mix. The previous study indicates a fairly good correlation between FV and the actually measured angle of internal friction of the asphalt mix [11]. It can be interpreted that the frictional resistance of Rej RAP samples is more than in the samples of the SB method. The increase in friction can be attributed to the improved adhesion between RAP aggregates and bitumen for the Rej RAP method. The ITS indicates the tensile strength of the compacted asphalt mix specimen. It was observed that cylindrical specimens compacted by the Rej RAP method showed better tensile strength than those compacted with the SB method. The adhesion between aggregates and bitumen was found more in the Rej RAP mixing method. It can be concluded that a better bond might be established between RAP material, virgin aggregates, and base binder when the rejuvenator was mixed with dried RAP and left for some time to diffuse the rejuvenator into the aged binder coating. It is possible that a softer blend merely coats the RAP material and doesn’t diffuse into the aged binder coating. The TSR was found to be more for the Rej RAP method, indicating that the moisture resistance of rejuvenated RAP compacted asphalt mix is better than the SB compacted asphalt mixes except for the Rej C sample. The present study aims to differentiate
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Fig. 3 Comparison of volumetric properties viz. (a) air voids, (b) voids in mineral aggregates, and (c) voids filled with bitumen, for Rej RAP and SB compacted asphalt mixes
the method of rejuvenator addition, and hence the effect of rejuvenator type is out of the scope. Marshall Stability alone is not a sufficient criterion to indicate the strength of compacted asphalt mix. The load-carrying capacity of an asphalt mix is a function of both stability and the flow value [11]. Marshall quotient is a measure of stiffness. The results indicate that the average MQ of SB method compacted asphalt mix was lower than the Rej RAP method’s MQ. Improved ITS and TSR indicate that Rej RAP samples are more intact than SB samples. It can be concluded that samples produced by the Rej RAP method can provide more stiffness than those produced by the SB method.
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Fig. 4 Comparison of mix properties viz. (a) MS, (b) flow value, (c) ITS, (d) tensile strength ratio, and (e) Marshall quotient for rejuvenated RAP and softer blend mixes
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Fig. 4 (continued)
Table 3 Rejuvenator addition location ANOVA check
If p < 10%, the effect is significant (S); else, not significant (NS) S. No.
Properties
p, %
S or NS
1
Marshall stability
0.5
S
2
Flow value
0.2
S
3
ITS dry
35.8
4
ITS wet
0.3
5
TSR, %
110.7
NS S NS
6
Va , %
7.6
S
7
Vb , %
7.6
S
8
VMA, %
7.6
S
9
VFB, %
10.0
S
4.3 Statistical Analysis of Results As shown in Table 3, for a 10% significance level, the results of two-way ANOVA indicate that significant changes have been observed in the properties of the compacted mix by changing the rejuvenator addition method. All parameters have shown significant changes except ITS dry and TSR.
5 Summary and Conclusion By changing the mixing method from SB to Rej RAP, noticeable changes were observed in the performance and volumetric parameters of the compacted recycled asphalt mixes. The VMA was decreased by 1.2% (average of three rejuvenators). The decrease in VMA was attributed to a 0.2% increase in effective bitumen (Vbe ) and a 7.4% decrease in Va . Similarly, VFB increased by 1.3%. The results indicated
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that although the quantity of materials is the same in both mixing methods, the rejuvenator on RAP material activated the aged binder, which increased the VFB and decreased Va , leading to an ultimate decrease in VMA. It was observed that on average, the MS, ITSdry , ITSwet , and TSR were increased by 24%, 12.6%, 23.2%, and 10.7%, respectively. The increase in MS indicates that Rej RAP material provided better adhesive strength than SB method when deformed at a constant strain rate of 50.8 mm/min. The resistance against tearing due to tensile stress was found to improve when the rejuvenator was added with dried warm RAP material instead of adding to the base binder. The resistance against moisture damage was also improved by adopting the Rej RAP method. It can be concluded that the Rej RAP method is a better method than the SB method. Irrespective of the property measured, the extent of variability from the average value (COV) was found less in the Rej RAP method than in the SB method.
References 1. IRC: 120 (2015) Recommended practice for recycling of bituminous pavements, p 72 2. Zaumanis M, Cavalli MC, Poulikakos LD (2020) Effect of rejuvenator addition location in plant on mechanical and chemical properties of RAP binder. Int J Pavement Eng 21:507–515. https://doi.org/10.1080/10298436.2018.1492133 3. Lo Presti D, Jiménez del Barco Carrión A, Airey G, Hajj E (2016) Towards 100% recycling of reclaimed asphalt in road surface courses: binder design methodology and case studies. J Clean Prod 131:43–51. https://doi.org/10.1016/j.jclepro.2016.05.093 4. Kriz P, Grant DL, Veloza BA, Gale MJ, Blahey AG, Brownie JH, Shirts RD, Maccarrone S (2014) Blending and diffusion of reclaimed asphalt pavement and virgin asphalt binders. Road Mater Pavement Des 15:78–112. https://doi.org/10.1080/14680629.2014.927411 5. West RC, Copeland A (2015) High RAP asphalt pavements Japan practice—lessons learned. Lanham, MD. https://www.asphaltpavement.org/PDFs/EngineeringPubs/IS139_High_RAP_ Asphalt_Pavements_Japan_Practice-lr.pdf 6. Mashru D (2015) Use of recycled asphalt pavement in asphalt plants—different approaches and pros and cons. NBM&CW, p 1. https://www.nbmcw.com/equipment-machinery/construct ion-equipments/road-construction-equipment/use-of-recycled-asphalt-pavement-in-asphaltplants-different-approaches-and-pros-and-cons.html. Accessed 17 Feb 2022 7. MORTH (2015) Specifications for road and bridge works. MORTH, p 906 8. Asphalt Institute (2014) MS-2 asphalt mix design methods, pp 1–197. https://bookstore.asphal tinstitute.org/catalog/book/ms-2-asphalt-mix-design-methods 9. Kamada O (2018) The recycling technology of asphalt pavement in Japan. Pavement Preservation Recycl. Summit. https://www.youtube.com/watch?v=msC9xO7s68E. Accessed 1 Apr 2020 10. Monden T (2014) Quality of RAP mixture in Japan, p 36. https://onedrive.live.com/?aut hkey=%21AHqoB-Rhp7ja3WU&cid=10043A6CE6CDF378&id=10043A6CE6CDF378% 218763&parId=10043A6CE6CDF378%2121280&o=OneUp 11. Metcalf CT (1959) Use of Marshall stability test in asphalt paving mix design, pp 12–22. http:/ /onlinepubs.trb.org/Onlinepubs/hrbbulletin/234/234-002.pdf
Assessment of Optimum Rejuvenator Dosage for Maximizing the Use of Reclaimed Asphalt Pavement (RAP) in Hot Mix Recycling Prakhar Aeron, Praveen Aggarwal, and Nikhil Saboo
Abstract In this study tall oil (TO) and waste engine oil (WEO) were used at two different dosages (5 and 10% by weight of RAP binder) to rejuvenate reclaimed asphalt pavement (RAP) binders obtained from two different sources. 50 and 100% RAP dosages were used with and without a VG30 binder. The optimum rejuvenator dosage for all the prepared blends were assessed using VG30 as the target binder. It was found that TO provides higher degree of rejuvenation in comparison to WEO, irrespective of the RAP source. In comparison to the physical tests such as penetration, softening point, absolute viscosity (using a capillary viscometer), and rotational viscosity (using a rotational viscometer), true high-performance grade (PG) temperature was found to be more appropriate for assessing the optimum rejuvenator dosage. The rate of change in stiffness with increase in rejuvenator dosage was not found to be linear for all the blends. Irrespective of RAP source, relationship between rejuvenator dosage and degree reduction in true PG temperature was obtained for TO and WEO blends having 50 and 100% RAP binder. Keywords Reclaimed asphalt pavement (RAP) · Rejuvenator · Tall oil · Waste engine oil · Hot recycling
P. Aeron (B) Civil Engineering Department, Indian Institute of Technology, Bombay, India e-mail: [email protected] P. Aggarwal Civil Engineering Department, National Institute of Technology, Kurukshetra, India e-mail: [email protected] N. Saboo Civil Engineering Department, Indian Institute of Technology, Roorkee, India e-mail: [email protected] URL: https://scholar.google.co.in/cita-tions?user=4ybtNM0AAAAJ&hl=en © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_12
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1 Introduction Incorporating a high amount of recycled asphalt pavement (RAP) into asphalt layers can pose the risk of premature fatigue cracking [1]. This is attributed to the presence of a highly oxidized asphalt binder. In order to restore the properties of the aged asphalt binder, a wide variety of recycling agents are utilized in hot mix recycling. In general, the use of recycling agents in RAP are warranted at a higher RAP dosage, typically greater than 30%. Recycling agents can be broadly divided into two categories: softeners and rejuvenators [2]. While both types of recycling agents work toward reducing the stiffness of the RAP binder, rejuvenators are targeted toward restoring the balance between the chemical constituents (asphaltenes and maltenes) [3]. This study concerns the use of rejuvenators for restoring the properties of the RAP binder. Various types of rejuvenators have been studied in the literature, which typically can be categorized as petroleum-based and/or bio-based. Researchers have been continuously working towards optimizing the dosage of rejuvenators for achieving desired short-term and long-term performance in high RAP asphalt mixtures [4]. The present study is one such effort in this direction. Due to the lack of studies on the subject, the present guidelines (in Indian specifications) on the use of RAP in asphalt layers remain very conservative [5]. Higher dosages of RAP are only allowed in unbound pavement layers, directly letting the potential binder properties of RAP go in vain. Therefore, research, such as the inclusion of rejuvenators for maximizing the RAP dosage in hot mix asphalt (HMA), can help in updating the available guidelines. This is not straightforward. For example, rejuvenated RAP binder may be a binary (RAP binder + Rejuvenator) or a ternary (RAP binder + Virgin binder + Rejuvenator), for 100% RAP and 10%. To compare various blends, the viscosity values were predicted at 160 and 180 °C using the standard Arrhenius model [6]. This is discussed in the results and discussion section. Additionally, the high-temperature PG grade was evaluated using an Anton Paar MCR 302 dynamic shear rheometer (DSR) using a parallel plate geometry. 25 mm spindle with a 1 mm gap was during the experiments. In addition to the hightemperature PG, the true fail temperature, denoted as, ‘true high PG temperature’ in this study, was also recorded.
5 Results and Discussion 5.1 Effect of Rejuvenator on Physical Properties Figure 1 presents the consistency test(s) results obtained for different asphalt binders and blends used in the present study. In general, it was found that the stiffness of the RAP binder blends reduced after the addition of rejuvenators. The penetration of recovered RAP binder from both the sources (PASA and SAMU) were found to be 1 dmm, while the virgin binder, VG30, had a penetration value of 37.7 dmm. Addition of both the rejuvenators increased the penetration values of RAP binder blends, to different degrees. In PASA, both TO and WEO had approximately similar level of effect on the penetration values. On the other hand, at similar dosage of rejuvenator, use of TO led to higher increase in the penetration values (as compared to WEO) in RAP blends produced from SAMU. This indicates that the degree of effect of rejuvenator on the physical property of RAP binder blends is a function of the source of RAP. As the target was to produce a rejuvenated blend with properties equivalent to the control binder (VG30), it was found that S50-T10 had the closest penetration values to VG30, followed by P50-T10. Softening point results indicated that, PASA is stiffer than SAMU, and the effect of TO is more pronounced than the effect of WEO, at similar percentage of rejuvenators. In agreement to penetration test results, S50-T10 was found to have the closest match with VG30.
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Fig. 1 Physical properties of binder a penetration, b softening point, c absolute viscosity, d rotational viscosity
The absolute viscosity values measured at 60 °C are shown in Fig. 1c. No conclusive results could be drawn from this test. During the laboratory investigation it was found that stiffer binder (such as RAP binder and their blends) showed negligible movement (or excessive delay in flow) inside the capillary tube under the applied pressure. This may be attributed to the higher stiffness and lower applied
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pressure. Few additional iterations were done by varying the tube types. However, ambiguous and inconclusive results were obtained. This study recommends that capillary viscometers shouldn’t be used for assessing the viscosity of stiff binder blends. In order to measure the high temperature consistency of the binders, rotational viscometer was used whose results are presented in Fig. 1d. This test was also chosen as better temperature control can be achieved during measurement and the results will not be confounded due to the inherent stiffness of RAP binders and their blends. As mentioned previously, for different blends, different set of temperatures were chosen to achieve the target minimum torque. Arrhenius model, as given below, was used to model the relationship between viscosity and temperature and predict the viscosity at 160 and 180 °C. Few random validations were done and the measured values were found in good agreement with the predicted results. 1 1 η = Aexp B − T1 T2
(1)
On an average, irrespective of the binder type, the viscosity at 160 °C was 1.6–2.3 times the viscosity at 180 °C. At both the temperatures, S50W10 was found to show closest match with the control binder VG30. In general, it was found that at similar rejuvenator dosage blends prepared with WEO had lower rotational viscosity in comparison to TO blends. This is not in agreement to other physical properties results, where TO lead to higher reduction in the degree of stiffness at similar rejuvenator dosage. This may be attributed to temperature susceptibility of the rejuvenators. At higher temperatures, loss in properties of TO may be higher in comparison to WEO. More studies are further required in this direction.
5.2 Effect of Rejuvenator on Rheological Properties Figure 2 presents the true high PG temperature obtained for different blends using an MCR 302 (Anon Paar) dynamic shear rheometer (DSR). 25 mm spindle with 1 mm plate gap was used during the measurement. True high PG indicates the exact fail temperature beyond which the value of G*/sinδ becomes less than 1 kPa. Advantages of using DSR measurement for RAP binders and its blends, in comparison to other tests as discussed above, are better temperature control and higher repeatability. Additionally, the parameters measured using DSR is a fundamental measure of the material behavior unlike the empirical tests such as penetration and softening point. It was found that 100% RAP blends with 5% TO yields approximately similar true high PG temperature to that of 50% RAP blends with 10% WEO, irrespective of RAP source. This indicate that at similar rejuvenator percentage, TO has higher rejuvenation capability than WEO. S50T10 was found to have closest match with VG30 followed by S50W10. The effect of rejuvenator was also found to be a function of RAP source. For example, in PASA 10% TO blends produced higher degree of
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Fig. 2 True high PG temperature of different binders
reduction in stiffness in comparison to SAMU, where the extent of reduction in true high PG temperature was a function of percentage of RAP binder.
5.3 Optimum Rejuvenator Dosage Optimum rejuvenator dosage is defined as the percentage of rejuvenator required for a given RAP binder blend to achieve the properties of the control binder VG30. As the results were obtained only at two rejuvenator dosage, i.e. 5 and 10%, linear interpolation was used for predicting the optimum rejuvenator dosage. As discussed above, 5 different types of tests were conducted in this study. However, based on the laboratory observations and test results, it was found that true high PG temperature measured using the DSR has better repeatability and accurate temperature control during the experimentation. Additionally, optimum dosage evaluated using other experiments showed ambiguous results. Therefore, true high PG temperature of RAP blends was used for forecasting the optimum dosage of the rejuvenator corresponding to the result obtained for VG 30 (72.2 °C). Table 5 shows the obtained results.
5.4 Validation of Optimum Rejuvenator Dosage In the previous section, the optimum dosages were calculated only based on 2 data points. It is, therefore, necessary to validate if the obtained results match with the actual value of rejuvenator(s) at which the true high PG of rejuvenated blends and VG 30 are equal. In this direction, additional blends at varying rejuvenator dosages were prepared and the true high PG temperature was measured. Actual dosages at
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Table 5 Optimum rejuvenator dosage Source
Rejuvenator type
RAP %
Optimum rejuvenator dosage (%)
PASA
TO
50
24
100
35
50
20
100
27
50
14
100
22
50
21
100
36
WEO SAMU
TO WEO
Fig. 3 Comparison between the actual and predicted dosage of optimum rejuvenator
which the true high PG is equal to 72.2 °C were assessed. The comparison between actual and predicted results is shown in Fig. 3. It was observed that for P100-W (100% PASA with WEO) the predicted value is not in agreement with the actual value. Other predicted values were found to be in close agreement with the actual measured value. During laboratory validation, it was observed that the rate of reduction in stiffness with an increase in WEO dosage was higher in the lower dosage range of WEO (up to 15%). Beyond this, the rate of reduction in true PG temperature was relatively slow. Similar results were seen in the case of P50W, as shown in the Fig. 3. However, in SAMU, WEO showed linear trends with good agreement between actual and measured values. This indicates that the use of linear interpolation should be carefully executed for the prediction of optimum rejuvenator dosage. This may be rejuvenator and RAP source-specific. In order to assess the effect of variables such as RAP source, RAP dosage, and rejuvenator type on the dosage of rejuvenator, the variation of rejuvenator dosage with change in true high PG was plotted. The change in true high PG was calculated by subtracting the true high PG temperature of the RAP binder (with/without VG30) from the true high PG temperature of the respective rejuvenated blend. The results from TO and WEO blends are shown in Fig. 4. As can be seen (Fig. 4a, c), for both the type of rejuvenator, the relationship between rejuvenator dosage and change in true high PG is nearly independent of
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Fig. 4 Relationship between % rejuvenator and change in true high PG a TO blends from PASA and SAMU, b combined TO blends, c WEO blends from PASA and SAMU, d combined WEO blends
the type of RAP source. Blends with a similar percentage of RAP are in close proximity with each other, irrespective of the source of RAP. The combined relationship is shown in Fig. 4b, d where it can be seen that an appreciable (R2 > 0.8) linear correlation exists. These graphs will therefore facilitate approximate determination of rejuvenator dosage (of TO and WEO) for reduction of stiffness of the base binder (RAP binder, with or without a virgin binder) by any given value in terms of true high PG temperature.
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6 Conclusions Based on the laboratory study and analysis, the following conclusions were drawn: 1. The extent of reduction in stiffness by a rejuvenator is a function of the source of the RAP binder 2. Effect of TO is more pronounced than WEO, at similar dosage of rejuvenator. 100% RAP blends with 5% TO yields approximately similar true high PG temperature to that of 50% RAP blends with 10% WEO. 3. Capillary viscometers shouldn’t be used for characterization of stiff blends such as RAP binders. 4. Based on the overall test results it is found that S50T10 show the closest match with the corresponding properties of VG30. 5. Comparing different tests conducted in this study, true high PG temperature is found to be more suitable for studying the effect of rejuvenator in hot mix recycling. 6. Except for P100-W10, optimum rejuvenator dosage calculated using linear interpolation is found to give satisfactory match with the actual values. 7. The relationship between rejuvenator dosage and change in true high PG temperature is independent of RAP the source.
References 1. Zaumanis M, Mallick RB (2015) Review of very high-content reclaimed asphalt use in plantproduced pavements: state of the art. Int J Pavement Eng 16:39–55. https://doi.org/10.1080/102 98436.2014.893331 2. Environmental biotechnology and safe—recycling agent asphalt (n.d.) 3. Zahoor M, Nizamuddin S, Madapusi S, Giustozzi F (2021) Sustainable asphalt rejuvenation using waste cooking oil: a comprehensive review. J Clean Prod 278:123304. https://doi.org/10. 1016/j.jclepro.2020.123304 4. Kaseer F, Martin AE, Arámbula-Mercado E (2019) Use of recycling agents in asphalt mixtures with high recycled materials contents in the United States: a literature review. Constr Build Mater 211:974–987. https://doi.org/10.1016/j.conbuildmat.2019.03.286 5. Lo Presti D, Jiménez Del Barco Carrión A, Airey G, Hajj E (2016) Towards 100% recycling of reclaimed asphalt in road surface courses: binder design methodology and case studies. J Clean Prod 131:43–51. https://doi.org/10.1016/j.jclepro.2016.05.093 6. Yang L, Zhou D, Kang Y (2020) Rheological properties of graphene modified asphalt binders. Nanomaterials 10:1–13. https://doi.org/10.3390/nano10112197
Study on Estimation of Optimum Dosage of Warm Mix Additives for Production of Asphalt Mixtures Mayank Sukhija, Nikhil Saboo, and Agnivesh Pani
Abstract Use of warm mix asphalt (WMA) technologies is among the sustainable construction techniques that allow the production of asphalt mixtures at reduced heating temperatures, relative to conventional hot mix asphalt (HMA). The primary focus of the present study was to optimize the dosage of five different WMA additives. One base asphalt binder and two aggregate sources were used for the preparation of HMA and WMA mixtures. The mixing and compaction temperatures of WMA mixtures were determined using a novel workability-based approach. Further, coating and compaction ability checks were applied to verify the obtained mixing and compaction temperatures, respectively. Results revealed that the incorporation of WMA additives in asphalt mixtures lowered the production temperatures, irrespective of the WMA technology, dosage, and aggregate source. Validation checks indicated that all the WMA mixtures attained similar to better aggregate coating and consistent packing density as compared to conventional HMA mixtures, despite being produced at reduced production temperatures. It was found that the optimum dosage of WMA additives is a function of aggregate source and WMA technology. It is expected that WMA mixtures prepared at the optimum dosage, determined through the proposed approach, may provide equivalent properties as HMA. Keywords Warm mix asphalt · Hot mix asphalt · Workability · Production temperatures · Coating · Compaction ability
M. Sukhija (B) · A. Pani IIT (BHU), Varanasi, India e-mail: [email protected] A. Pani e-mail: [email protected] N. Saboo IIT Roorkee, Roorkee, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_13
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1 Introduction and Background Hot mix asphalt (HMA) technology is majorly adopted to construct asphalt pavements worldwide. HMA is prepared, spread, and compacted at high heating temperatures (above 150 °C) [1]. Working with mixtures involving such high temperatures negatively affects the environment [2]. This concern has prompted researchers to explore other sustainable technologies that can reduce the energy requirement during the construction of asphalt pavements. In this direction, warm mix asphalt (WMA) technology has been found as an alternative with the goal of reducing environmental pollution and facilitating sustainable pavement construction [3]. WMA technology facilitates the construction of asphalt mixtures at lower heating temperatures than HMA. Even though the mixing and compaction temperatures of WMA mixtures are reduced, the performance remains the same or even better than conventional HMA mixtures [4]. In addition, WMA technology facilitates improved social, and economic benefits, including reduced energy consumption and corresponding greenhouse gas (GHG) emissions, creation of an improved working environment for the workers while working in the field, and wide paving window [5–8]. Following the evolvement of WMA technologies, different WMA additives have been developed and are being used for pavement construction. The existing WMA additives can be divided into three broad categories depending on their working mechanism. These are organic, chemical, and foaming-based technologies [3, 9]. Needless to say, the working mechanism of these technologies may be different, but the primary aim is to reduce the production temperatures of asphalt mixtures. However, the reduction in production temperatures is primarily a function of WMA technology and their respective dosages [10]. In practice, the reduction in production temperatures of WMA mixtures inevitably varies due to the difference in the aggregate source. For a particular construction with fixed aggregate type and WMA technology, selecting/optimizing the appropriate dosage of WMA additive is critical for asphalt industrialists. Multiple studies [11–13] have indicated the importance of WMA additive dosage and its effect on the quality of the asphalt mixtures. It is desirable to select the dosage that not only reduces the production temperature, but also provides similar/better performance compared to conventional HMA. However, not many studies are available on optimizing the dosage of WMA additives for the preparation of asphalt mixtures incorporating different aggregate types. The present study intends to optimize the dosage of five different WMA additives based on their production temperatures determined through workability-based approach. Initially, all the WMA mixtures prepared at varying dosages with different aggregate types were tested to determine the production temperatures. Further, coating and compaction ability checks were applied to verify the obtained production temperatures. These checks act as vital parameters to determine the optimum dosage of WMA additives, as they account for the variability caused by the change in aggregate source.
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2 Material Selection A commonly used viscosity-graded (VG) base asphalt binder, VG30, was taken in the present study. Two different aggregate sources (granite and dolomite) were incorporated to assess the effect of aggregate mineralogy on the optimum dosage of WMA additives. Table 1 shows the physical properties of the asphalt binder and aggregates used in this experimental work. Five different WMA additives, characterized under different WMA technologies, were used for preparing the asphalt mixtures. The range of dosages for each WMA additive was taken based on the recommendations of the manufacturer. The details of the WMA additives and their dosages are reported in Table 2. Table 1 Physical characteristics of asphalt binders and aggregates Asphalt binder
Aggregates
Tests
Method
VG30
Requirements [14]
Tests
Method
G
D
Requirements [15]
PV at 25 °C, 0.1 mm
IS 1203
65
45 Min
F&E, %
IS 2386 (Part I)
20.0
24.0
35
V at 60 °C, Pa·s
IS 1206 (Part 2)
280
240–360
LAV, %
IS 2386 (Part IV)
21.0
19.0
30
SP, °C
IS 1205
50
47 Min
AIV, %
IS 2386 (Part IV)
18.5
23.0
24
Note PV, V, and SP in asphalt binder tests refer to penetration value, viscosity, and softening point, respectively. F&E, LAV, and AIV in aggregates testing denote combined flakiness and elongation index, Los-Angeles abrasion value, and aggregate impact value, respectively G and D denote granite and dolomite aggregate, respectively
Table 2 Details of WMA additives [16–20] WMA technology
Additive
Composition
Recommended dosage(s)
Organic additives
Sasobit (S)
Aliphatic synthetic paraffin wax produced from the Fischer–Tropsch method
(1, 2, 3)% w/b
Sasobit Redux (SR)
Aliphatic synthetic paraffin wax prepared using Fischer–Tropsch process
(0.7, 1.35, 2)% w/b
Cecabase (C)
Bio-sourced cationic surface-active agent
(0.2, 0.35, 0.5) w/b
Rediset (R)
Cationic-based surfactant
(0.4, 0.5, 0.6)% w/b
Aspha-Min (AM)
A foaming process with the use of synthetic (0.3)% w/m zeolite
Chemical agents
Foaming technologies
Note w/b and w/m denote by weight of the asphalt binder, and by weight of the asphalt mixture, respectively
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For preparing the organic and chemical-based WMA binders, VG30 was initially heated and stirred appropriately. The recommended dosage(s) of WMA additives were subsequently incorporated into the already heated base asphalt binder (VG30 here). A mechanical stirrer, operated at 500 rpm, was used to prepare WMA binders. Mixing was done for 30 min at a temperature of 130–140 °C. On the other hand, foaming-based additive (i.e., Aspha-min), was incorporated during the mixing of materials (asphalt binder and aggregates) within the power-driven asphalt mixer.
3 Experimental Setup In the present study, the production temperatures were initially determined for different HMA and WMA mixtures. Generally, mixing and compaction temperatures were evaluated with the use of the traditional viscosity-based method [21]. This method, commonly called as equi-viscous (EQ) method, has been continuously debated in past studies [22, 23], especially in the case of WMA mixtures. For WMA, there are different technologies (such as chemical and foaming agents) that do not alter the viscosity of asphalt binder. In addition, it was reviewed that the mechanism behind the reduction in production temperature for WMA is a function of friction between the coated aggregates rather than the viscosity of asphalt binder [24]. The interfacial friction is expected to indirectly influence the workability of asphalt mixtures [25]. From this perspective, the production temperatures of WMA mixtures, incorporating both aggregate sources, were forecasted using a novel workability approach, as proposed in a previous study [10]. Initially, there was a need to set one reference point for finding the mixing and compaction temperatures. The EQ method is well known to provide reliable results for conventional viscositygraded asphalt binder (VG30 in the present study) [26–28]. Hence, the temperatures corresponding to VG30 were taken as a reference. The workability of conventional HMA mixture (prepared with VG30), at the equi-viscous temperatures (mixing and compaction), was used to estimate the production temperatures for WMA mixtures. The detailed procedure for assessing the workability and corresponding production temperatures can be found elsewhere [10]. The obtained production temperatures were further validated using coating ability (for mixing temperature) and compactability (for compaction temperature) checks performed on each WMA mixture. The coating ability was assessed using a new experimental setup (as shown in Fig. 1a) developed in the laboratory, while the compactability characteristic was examined using an impact compactor (as shown in Fig. 1b) with 75 blows of compaction on each side of the specimen. Easy-touse Android software was installed to find the coating of asphalt binder on the aggregates (Fig. 1c) for the validation of mixing temperature. On the other hand, the comparison of air-void in the compacted asphalt mixture (Fig. 1d) was selected as the parameter for the validation of compaction temperature. All the checks were performed by taking conventional HMA as a reference mix. The results obtained
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Fig. 1 a Coating setup, b impact compactor, c loose asphalt mixture for coating, and d compacted asphalt mixtures
from the comprehensive testing program were further used to optimize the dosage of WMA additives for both aggregate sources. Bituminous concrete (grading II), based on the Ministry of Road Transport and Highways (MoRTH), India [15], was produced in the laboratory. The designed aggregate gradation for both the aggregate source is shown in Fig. 2 and the (OBC) of the conventional HMA mixtures was evaluated. The optimum binder content (OBC) was estimated to be 5.8% and 5.6% for granite, and dolomite-inclusive asphalt mixtures, respectively. In this experimental work, the OBC of HMA and WMA mixtures were kept the same owing to the minor impact of WMA additives on the OBC and mix volumetrics [3, 4].
4 Results 4.1 Discussion on Production Temperatures Table 3 presents the average values of production temperatures and the value of individual temperature reduction with the adoption of WMA mixtures, relative to HMA mixtures. Based on EQ method, the mixing and compaction temperatures for chemical-based WMA additives either did not change with the variation in the dosage or provided marginal temperature reduction. On the contrary, the production temperatures obtained using the workability approach showed that the WMA technology lowers the production temperature, irrespective of WMA type, dosages, and aggregate source. Also, the extent of reduction in production temperature increased with the increase in dosage for all the WMA technologies. Interestingly, aggregate source
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Cummulative percent passing, %
100 90
Lower limit Upper limit Granite Dolomite
80 70 60 50 40 30 20 10 0 0.01
0.1
1
10
100
Sieve size, mm Fig. 2 Designed aggregate gradation for both the aggregate source
was found to affect the production temperature of WMA. However, no specific trend in the ranking of WMA mixtures was observed with the change in aggregate source, as shown in the last row of Table 3. For example: SR (2% w/b) showed higher reduction in mixing temperature with granite aggregates, whereas, in case of dolomite aggregates, the highest reduction was attained with the addition of AM (0.3% w/m). On the other hand, independent of the aggregate source, the addition of C (0.5% w/ b) indicated maximum reduction in compaction temperatures. However, lowering of production temperature beyond a critical limit may adversely affect the engineering characteristics, such as aggregate coating, densification of asphalt mixture, and eventually the mechanical performance. Therefore, the dosage should be optimized by satisfying/keeping in view the basic characteristics of asphalt mixtures, which are highly dependent on the production temperatures.
4.2 Discussion on Coating Ability As stated, the reliability of the predicted mixing temperatures of asphalt mixtures was assessed using the coating ability check. Initially, aggregate coating was judged based on the coating index (CI). CI is the absolute difference within the values of colors attained in uncoated and coated aggregates. The in-depth details regarding the evaluation of aggregate coating can be found elsewhere [10]. Since two aggregate sources were used, there was a need to normalize CI of WMA mixtures with respect to the CI of conventional HMA mixture. This new normalized parameter was defined as the “Normalized Coating Index (CIN ).” To assess the influence of WMA additives over the aggregate coating, the value of CIN for HMA mixtures, irrespective of the
156
R0.5
–
Ranking
16
18
14
10
16
9
4
22
19
15
17
9
7
–
SR > R > S > C > AM
147
145
149
152
146
153
158
141
144
148
146
153
156
163
28
28
25
14
37
20
11
35
27
21
19
10
5
–
C > SR > AM > R > S
119
120
122
133
111
128
136
113
120
126
128
137
143
148
RMT
24
20
17
14
22
18
15
23
19
14
20
15
12
–
AM > SR > C > S > R
139
143
146
148
141
144
148
139
143
149
142
148
150
163
MT
RCT
Dolomite CT
MT
RMT
Granite CT
RCT
25
17
14
11
25
18
15
24
19
12
19
16
10
–
C > AM > SR > S > R
123
130
133
136
122
129
133
124
129
136
128
132
137
148
Note EQMT and EQCT refer to equi-viscous mixing and compaction temperatures, respectively. MT, CT, RMT, and RCT indicate mixing temperature, compaction temperature, reduction in mixing temperature, and reduction in compaction temperatures, respectively
–
138
–
152
–
R0.6
AM
143
144
145
156
158
C0.5
145
146
R0.4
158
C0.35
136
149
158
SR2
145
140
158
153
SR0.7
SR1.35
C0.2
140
153
S3
143
142
157
155
148
S1
163
VG30
EQCT
S2
EQMT
Mixtures
Table 3 Production temperatures of different asphalt mixtures
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Granite
Dolomite
1.20
CIN
1.00 0.80 0.60 0.40 0.20 0.00
Mixture Type Fig. 3 Effect of WMA technology on aggregate coating
aggregate type, was taken as unity. Generally, a higher value of CIN is desirable for better aggregate coating. Figure 3 shows the CIN for all the asphalt mixtures prepared at their mixing temperatures, determined with the use of workability approach. An increase in mixing temperature generally results in a better coating of asphalt binder over the aggregates. Interestingly, the application of WMA additives, irrespective of the aggregate source, imparted the same/improved CIN , despite being produced at lower mixing temperatures. It was observed that the change in CIN is a function of aggregate source, WMA technology, and their respective dosages. The variation in CIN did not indicate any definite trend with the change in aggregate source. Chemical-based WMA mixtures lead to higher improvement in CIN , followed by organic and foaming-based WMA mixtures. The variation in coating with the change in WMA additive can be attributed to the change in their working mechanism. It was evident that the increase in dosage of any WMA additive resulted in better aggregate coating. The value of CIN for all the WMA mixtures was found to pass the critical threshold limit of 10% variability, defined based on the CIN of conventional HMA mixtures, irrespective of the aggregate source.
4.3 Discussion on Compactability The air-void in asphalt mixtures is a critical factor that controls the quality of compacted asphalt mixtures. Therefore, the value of air-voids, for both HMA and WMA mixtures, was determined to verify the compaction temperature. As per the MoRTH guidelines [15], the value of air-voids in a compacted asphalt mixture should range from 3 to 5%. Figure 4 presents the value of air-voids determined for all the asphalt mixtures compacted at their compaction temperatures, obtained using the
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Granite
Dolomite
157
Specified air-voids ~ 3% - 5%
Air-voids, %
5 4 3 2 1 0
Mixture Type Fig. 4 Effect of WMA technology on packing density of asphalt mixtures
novel workability-based approach. It was found that HMA and WMA mixtures, irrespective of the aggregate source, satisfied the requirement of air-voids specified by MoRTH [15]. The value of air-voids was found to be the function of WMA technology, its dosage, and aggregate source. However, no definite trend was observed with the variation in any of these variables.
4.4 Selection of Optimum WMA Additive Dosage The dosage of WMA additives was optimized based on the results of coating and compactability checks. These checks were preferred because they consider the variability which occurs due to the change in aggregate source and are directly dependent on the mixing and compaction temperatures of asphalt mixtures. Initially, it was anticipated to select the optimum dosage based on the coating ability check; however, in the present study, all the WMA mixtures indicated higher CIN value than conventional HMA mixtures, even at their minimum dosage. Thus, it was comprehended that the difference in air-void could be an appropriate technique to find the optimal dosage of WMA additives. The optimum dosage was selected based on the criteria that the air-voids of the WMA mixtures are the same or under 10% variability as that of conventional HMA mixtures. Table 4 shows the optimum dosage determined for each WMA additive. It was found that the optimum dosage varied with the change in aggregate type and WMA technology. The optimum dosage for Aspha-min was directly selected as 0.3% w/m because only a single dosage was recommended by the manufacturer. It is expected that the use of optimum WMA additive dosage would produce a WMA with similar performance as conventional HMA.
158 Table 4 Optimum dosage of warm mix additives
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WMA additives
Dosage depending on aggregate type Granite
Dolomite
Sasobit (S)
3% w/b
2% w/b
Sasobit Redux (SR)
1.35% w/b
1.35% w/b
Cecabase (C)
0.5% w/b
0.2% w/b
Rediset (R)
0.4% w/b
0.6% w/b
Aspha-min (AM)
0.3% w/m
0.3% w/m
Note w/b and w/m denote by weight of the asphalt binder, and by weight of the asphalt mixture, respectively
5 Conclusions The key findings of the present research work are as follows: 1. The results confirmed the inaptness of the conventional equi-viscous method to estimate the mixing and compaction temperatures of WMA mixtures; rather, it provides appropriate production temperatures for HMA mixtures (prepared with conventional VG binders). 2. Workability analysis shows that the incorporation of WMA additives significantly lowers the mixing and compaction temperatures. The extent of reduction in temperature is a function of aggregate source, WMA technology, and their respective dosage. 3. The coating check shows that all the WMA mixtures exhibit the same or even better coating, irrespective of the aggregate type, even at reduced mixing temperatures. In particular, chemical additives yield a higher coating than organic and foaming-based additives for both granite and dolomite aggregates. 4. All the WMA mixtures, irrespective of the aggregate source, exhibit consistent air-voids as conventional HMA mixtures, despite being compacted at lower temperatures. However, no definite trend was seen with the variation in WMA additive dosage. 5. Optimum dosage of WMA additives varies with the change in aggregate source. The variation is highly reliant on WMA type. For example: the optimum dosage of SR (1.35% w/b) remains the same, irrespective of the aggregate source, whereas 0.5% C is suitable for granite-based asphalt mixtures and 0.2% C is the optimal dosage for dolomite-based asphalt mixtures.
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The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt Binder Dabbiru Sairam, Shobhit Jain, Anush K. Chandrappa, and Umesh C. Sahoo
Abstract Aging causes the asphalt to stiffen and become brittle, which leads to a potential for premature fatigue and thermal cracking. This paper assesses the potential of using Waste Cooking Oil (WCO) as an effective anti-aging material in a base binder. The objective is to restore the behavior of the aged binder to the control/base binder through WCO modification performed prior to aging. The response of the WCO-modified binder against Short-term aging is investigated by performing the penetration test, softening point test, viscosity test, and rheological test using DSR. To determine the optimum rate of addition of WCO at which the grading of shortterm aged binder will be the same as that of unaged one, aging indices have been developed and calculated for different binders. Based on the results of the physical and rheological testing on the modified samples in both aged and unaged conditions, it was found that the addition of WCO to the base binder significantly reduced the aging as compared to that of the base binder. An optimum WCO dosage of 5% by weight of the binder has been found for VG30 while the optimum WCO dosage for the anti-aging effect was found to lie between 3 and 5% by weight of the binder for PG64-10. Keywords Anti-aging agent · Waste cooking oil (WCO) · Short-term aging (STA)
D. Sairam · S. Jain (B) · A. K. Chandrappa · U. C. Sahoo School of Infrastructure, IIT Bhubaneswar, Bhubaneswar, Odisha 752050, India e-mail: [email protected] D. Sairam e-mail: [email protected] A. K. Chandrappa e-mail: [email protected] U. C. Sahoo e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_14
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1 Introduction Aging of asphalt is defined as the hardening of binder caused due to changes in its chemical composition during the construction process and over the period of its service life. This causes an alteration in the properties of asphalt. Aging can be divided into two phases: Short-term aging (STA) and Long-term aging (LOT). STA is the initial stage aging, which occurs during the production of the asphalt mixtures at mixing and compaction temperature. Production at higher temperatures results in the loss of volatile components and oily components from the binder. As a result, the exposed thin layer of the mixture on the surface of the aggregate hardens and alters the properties of asphalt like viscosity and stiffness. This occurs at a very fast rate due to high temperatures. LOT is the second aging that occurs during the service life of the pavement where the binder is exposed to environmental conditions such as moisture and temperature. The rate of hardening depends on the surrounding environment and the present air void content [1]. Rejuvenators have been used as anti-aging agents by many researchers. Basically, rejuvenators are used to restore the original properties (same as the virgin binder) of oxidized binder. Rejuvenators reinstate the asphaltenes-to-maltenes (A/M) ratio to its previous state (virgin binder) [2, 3]. The rejuvenator should be capable to improve the susceptibility of aged binder against the temperature and susceptibility. Few studies have evaluated the modification effect of waste cooking oil (WCO). However, the WCO is being utilized as a rejuvenator majorly [1, 4–7]. WCO is one of them, which is getting popularity in the pavement industry. The WCO can be collected from restaurants, food processing plants, domestic disposables, and recycling stations. India produces roughly 2.18 million tonnes (222 crore litres) of WCO per year [8]. WCO needs a cost-effective and eco-friendly disposal strategy such as waste oil recycling as a way to reduce pollution caused by unauthorized dumping [9]. A major contribution to the massive quantity of WCO produced by households and restaurants is the rise in food consumption as well as the quick enormous rise in the human population [10]. WCO increases the oily components in asphalt binder, resulting in higher maltene proportion in the binder. After STA, these additional oily components evaporate and the aged modified binder shows the same properties as the unaged binder without WCO. The ultimate goal of the study is to find the optimum amount of WCO to modify the binder. There are many studies which evaluated the performance of binders with WCO, but very limited studies are there which showed the anti-aging potential of WCO [11]. The penetration value and ductility of the binder increase, while the softening point decreases with the addition of WCO at various dosages [12–14]. The variation in viscosity at different temperatures with changing WCO content was studied by Mahrez et al. [15]. According to the study, the viscosity of the RTFO-aged binder was reduced by half when a WCO dosage of 6% by weight was used. The review of different studies indicated that aged binders of grade PG 60/70, 50/ 60, 30/40, and 40/50 required WCO dosages of 1%, 1%, 3%, and 3% by weight to rejuvenate their complex shear modulus (G*), respectively. However, 1, 3, 4, and 5%
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WCO by weight were required to revive the phase angle of virgin binder of PG 80/100 [13, 16, 17]. Further, the rutting parameter (G*/sinδ) is dependent on the quality of the WCO being used, which further varies with the free fatty acid content in WCO as determined by its acid value [18]. Azahar et al. [4] studied the effect of the addition of unmodified and transesterified WCO in binder samples. The results confirmed that the transesterified (chemical modification) WCO-rejuvenated binder has higher fatigue and rutting resistances as compared to the unmodified WCO-rejuvenated binder. Hence, it is evident that with the increase in WCO dosage in the asphalt binder prior to aging, the percentage of recovery and the ability to resist permanent deformation decrease for the aged binders owing to the decrease in complex shear modulus (G*) [19]. This results in the reduction of the rutting resistance parameter, which is governed by G*/sin(δ). All the studies showed the rheological and physical properties of binders modified with WCO. The anti-aging properties of asphalt with WCO and the effect of modification on the rheological and chemical properties of binders were investigated in the study.
1.1 Research Significance In previous research, WCO was used as a rejuvenator with asphalt binder and RAP binder not as an anti-aging additive. In some studies, it was concluded that WCO can be used as anti-aging agent, but the optimal WCO dose was not assessed. This paper includes the efficacy of the WCO modification to industry-relevant binders like VG30 and PG64-10 as an anti-aging agent, and it also correlates the variations of rheological properties with chemical properties so as to gain a deeper understanding of the properties of asphalt binder with WCO. Meanwhile, aging index forms a simpler parameter to understand the performance of the asphalt binder with respect to the desired product. Thereby, the industry could reap benefits from its usage and also reduce the environmental impact of such non-renewable material.
2 Material and Methods The materials and experimental methods adopted are briefly described in this section.
2.1 Materials Viscosity-graded 30 (VG30) and PMB 64-10 (Polymer modified bitumen) binders were used in this study. The WCO was collected free of cost. The sample of WCO
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is collected in huge chunks from the public hostel, IIT Bhubaneswar. The quality of the WCO sample taken is assessed from an acid value test based on ASTM D5555. The acid value was determined as 4.2%.
2.2 Methods The control binders were first modified with the 3 and 5% (by weight) WCO to get a modified binder. Firstly, the binder was heated to a uniform temperature of 130 °C to obtain the pouring state of a binder. The binder was modified with WCO at various percentages by weight of the total binder. A mechanical stirrer was used to blend the materials with a speed of 1000 rpm for 60 min at 160 °C [20]. These parameters are chosen to maintain fluidity and to ensure homogenous mixing. The modified binder is then short-term aged to demonstrate the effects of STA. STA is simulated in a laboratory using Rolling Thin Film Oven (RTFO) according to ASTM D2872. The following tests were performed on the binders.
2.2.1
Oscillation Test
Rheological properties of an asphalt binder are determined using a Dynamic Shear Rheometer (DSR) at intermediate and high temperatures as per AASHTO T-315. The complex shear modulus (G*) (resistance to deformation) and the phase angle (phase gap between the applied and resultant parameter) of the specimen are calculated using DSR. Essentially, two types of tests were run on oscillation, and they are explained here. i. Strain sweep: This test is basically performed to find the linear viscoelastic region (LVER) of the binder. The temperature is varied from 45 to 65 °C. ii. Frequency sweep: In this test, the values of G* and δ are determined in two conditions, (a) sample size 1 mm with 25 mm plate geometry for a temperature higher than 45, and (b) sample size 2 mm with 8 mm plate geometry for the temperature lower than 45, at a constant shear strain of 0.1% [21]. The frequency is varied from 0.1 to 20 Hz. This data is used in the plotting of master curves. Rutting resistance is evaluated at high temperatures by the parameter, G*/sin(δ). The greater the value of G*/sin(δ), the higher is the resistance to rutting. Therefore, for better rutting performance, G* needs to be higher and δ needs to be lower.
2.2.2
Master Curves
Master curves for asphalt binders are plotted from the data obtained from a frequency sweep. Master curves are used to predict data corresponding to extreme frequencies and temperatures (both high and low) which need to be interpolated from the
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data obtained from testing. In order to do this for temperature, a standard reference temperature must be selected. The data from all other temperatures are to be shifted to this reference temperature with the help of a shift factor as shown in Eq. 1 until a smooth curve is obtained. Christensen-Anderson-Marasteanu (CAM) model has been selected to plot master curves, which is shown in Eq. 2. As part of the paper’s analysis, T ref is set at 35 °C. The shift factor is formulated as Eq. 2: log a(T ) =
−C1 ∗ (T − Tref ) C2 + T − Tref
(1)
where T is the test temperature (°C). T ref is the reference temperature set at 35 °C. C 1 and C 2 are material constants. ∗
G (ω) = G g ∗ 1 +
ωc ωr
K − mK (2)
where G*(ω) shows the shear modulus at a particular frequency. Gg shows the glass modulus which is assumed as 1 GPa. ωr represents the reduced frequency. ωc represents the cross-over frequency. m, K are the shape parameters which collectively form the rheological index.
2.3 Asphaltene Extraction n-Heptane is utilized as the solvent to extract the asphaltenes in accordance with the ASTM D6560. In this process, 100 ml of n-heptane and 1 g of asphalt sample are blended until the binder sample is completely dissolved. The blend is then heated under reflux for approximately an hour. As a result, asphaltenes, waxy compounds, and inorganic elements precipitate are then accumulated on the filter paper. The waxy compounds are subsequently extracted from the filtrate using hot heptane in an extractor. Hot toluene is used to dissolve asphaltene once the waxy compounds have been eliminated, and, as a consequence, inorganic elements are separated. Following the evaporation of the extraction solvent, asphaltenes are weighed. Asphaltene content is the ratio of the weight of asphaltenes extracted to the weight of the sample taken initially.
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2.4 Formulation of Aging Indices (AI) By comparing orders of numerical magnitude related to any of the asphalt binder properties for two subsequent aging situations, such as viscosity, rutting resistance, and asphaltene/maltene ratio, AI can be calculated which quantifies the aging. According to Kumbargeri and Biligiri [20], AI is calculated as shown in Eq. 3: AI =
Asphaltene content of STA binder Asphaltene content iof unaged binder
(3)
3 Results and Discussion 3.1 Rheological Test Results DSR was performed to find the rheological properties of the different binders.
3.1.1
Oscillation Tests and Master Curve Results
Temperatures between 45 and 65 °C were selected for the evaluation of hightemperature behavior of unaged, short-term (STA) aged and WCO-modified (5% by weight) unaged bitumen binder samples. Results are calculated at varying strains (0.1–15% at a frequency of 1.59 Hz) and frequencies (0.1–20 Hz at a strain of 0.1%). Based on the values obtained from the frequency sweep tests, master curves are plotted comparing the STA aged and unaged binders using the ChristensenAnderson-Marasteanu model (CAM) for optimization. The graphs showing the comparison of the master curves between the binder sample are given in the following Figs. 1 and 2. From the figures given below, it could be concluded that the complex shear modulus increased with STA aging of the unaged bitumen.
Frequency Sweep The frequency sweep was performed at 25–65 °C using a 25 mm parallel plate geometry and 1 mm gap (for temperatures higher than 45 °C) and 8 mm parallel plate geometry and 2 mm gap (for temperatures lower than 45 °C) at various frequencies (20–0.1 Hz). All binders were tested, and rutting parameter (G*/sinδ) and complex shear modulus (G*) were calculated. From the graphs shown below (Figs. 1 and 2), it can be observed that the shear modulus and the rutting resistance increased with an increase in the frequency for both binder cases. Additionally, it was observed that the asphalt binder develops elastic characteristics as a result of the shorter loading
The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt … 25000
Unaged PG64-10
Aged PG64+5%
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Aged PG64+3%
G*/sin , Pa
20000 15000 10000 5000 0 0
5
10
15
20
25
Frequency (Hz)
Fig. 1 Rutting parameters of PG64-10 samples at 65 °C 25000 Unaged VG30
Aged VG30+5%
Aged VG30+3%
G*/sin , Pa
20000 15000 10000 5000 0 0
5
10
15
20
25
Frequency (Hz)
Fig. 2 Rutting parameters of VG30 samples at 65 °C
intervals, and the value of the rutting parameter rises as well, suggesting enhanced higher temperature binder performance when loading frequency rises. The performance of the modified sample of aged VG30 (Aged + 5%) is found to be similar to that control binder (unaged VG30) while also lying within the range of 3–5% by weight of modification, while, on the other hand, the performance of the modified sample of PG64-10 was also found to be in the range of 3–5% of modification. For VG30, the results of complex shear modulus, and rutting resistance of the short-term aged binder modified with 5% WCO were found to be similar as compared to the control binder (unaged VG30). Also, the high-temperature performance of both the modified sample and control binder sample were similar as indicated by the frequency sweep graphs. This indicates that the optimum WCO content for depicting anti-aging properties in VG30 was achieved at 5% of the oil by weight of the asphalt binder. The high-temperature performance of both modified samples and control binder samples were lying in the range as indicated by the frequency sweep graphs. It is key to note that the degree of aging is higher in the virgin binder (VG30) as compared to the polymer-modified one (PG64-10).
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Unaged PG64
Unaged PG64+5%
Aged PG64+3%
Aged PG64+5%
10000000
G* (Pa)
1000000 100000 10000 1000 100 10 0.0001
0.001
0.01
0.1
1
10
100
1000
Reduced Frequency (Hz)
Fig. 3 Master curves of all PG64-10 binders at a reference temperature of 35 °C
This may be explained by the fact that the WCO addition recovered the asphaltene/ maltene ratio of the binders by raising the asphalt binder’s oxidizable content. This initially raises the maltene content in unaged conditions and when the oxidative aging occurs, the asphaltene would slightly be raised in comparison to this maltene and thereby, the control binder properties are maintained.
Master Curves For all the samples of VG30 and PG64-10, master curves are shown in Figs. 3 and 4 given below and the corresponding parameters are given in Tables 1 and 2 for PG64-10 and Tables 3 and 4 for VG30, respectively. The modified samples of VG30 and PG64-10 both displayed lower G* values than the corresponding unaged binder samples. Nevertheless, the 5% modified sample of aged VG30 produced findings that were comparable to those of the control binder, indicating the significant antiaging potential of WCO. On the other hand, the optimum WCO modification dose for PG64-10 was found to lie in the range of 3–5% by weight. In Fig. 3, it can be observed that at high temperatures (indicated by the lower frequency readings of the CAM models), the aged PG64-10 modified with 3% WCO showed properties similar to that of the control binders (unaged PG64-10).
Aging Index Based on the rutting resistance (G*/sin(δ)) measured at 1.59 Hz from the frequency sweep data, the aging index is formulated as the ratio of the rutting resistance of the aged sample to that of the control binder sample. The indices of the aged to unaged and aged-modified to unaged are compared to show the performance of the additive as an anti-aging modifier.
The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt … 1E+09
Unaged VG30 Aged VG30+5%
100000000
169
Unaged VG30+5% Aged VG30+3%
10000000
G*(Pa)
1000000 100000 10000 1000 100 10 0.0001
0.001
0.01
0.1
1
10
100
1000
Reduced freq (Hz) Fig. 4 Master curves of all VG30 samples at reference temperature of 35 °C
Table 1 CAM model fitting constants for PG64-10 samples Characteristic
Binder type
C1
C2
ωc (rad/s)
m
K
Complex shear modulus
Unaged PG64-10
16.00
143.00
77546.5
0.795
0.2625
Unaged PG64-10 + 5%
16.00
150.00
76057.88
0.873
0.173
Aged PG64-10 + 3% 16.00
144.00
65883.89
0.805
0.42
Aged PG64-10 + 5% 17.00
179.45
65858.63
0.86
0.2022
Table 2 Shift factors [log a(t)] for PG64-10 samples Binder type
25 °C
35 °C
45 °C
55 °C
65 °C
Unaged PG64-10
1.203
0
−1.04
−1.96
−2.69
Unaged PG64-10 + 5%
1.20
0
−1.047
−1.966
−2.69
Aged PG64-10 + 3%
1.203
0
−1.044
−1.96
−2.7
Aged PG64-10 + 5%
1.203
0
−1.044
−1.96
−2.7
Table 3 CAM model fitting for VG30 samples Characteristic
Binder type
C1
C2
ωc (rad/s)
m
K
Complex shear modulus (G*)
Unaged VG30
17.43
180.00
202.909
1.22
0.187
Unaged VG30 + 5%
18.00
180.00
900.03
1.09
0.173
Aged VG30 + 3%
18
189.00
900.00
1.09
0.155
Aged VG30 + 5%
17.43
180.00
148.55
1.61
0.127
Figures 5 and 6 depict the comparison of the aging indices of different binder samples and their variation from the threshold value of the control binder. This
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Table 4 Shift factors [log a(t)] for VG30 samples Binder type
25 °C
35 °C
45 °C
55 °C
65 °C
Unaged PG64-10
1.02
0
−0.91
−1.73
−2.40
Unaged PG64-10 + 5%
1.006
0
−0.904
−1.72
−2.39
Aged PG64-10 + 3%
1.02
0
−0.91
−1.73
−2.40
Aged PG64-10 + 5%
1.02
0
−0.914
−1.74
−2.45
Aging Index (G*/sin )
2.0
Indices of samples
Threshold for control binder
1.5 1.0 0.5 0.0 Aged PG64
Aged PG64+5%
Aged PG64+3%
PG64-10 binder
Aging Index (G*/sin )
Fig. 5 Aging indices of the PG64-10 samples in comparison with the threshold set by the control binder
3.0
Indices of samples
Threshold for control binder
2.5 2.0 1.5 1.0 0.5 0.0 Aged VG30
Aged VG30+5%
Aged VG30+3%
VG 30 Binder Fig. 6 Aging indices (rutting parameter) of the VG30 samples in comparison with the threshold set by control binder
threshold value indicates the control binder conditions. Therefore, if the AI is closer to this threshold, the properties would be similar to that of the control binder. Figures 7 and 8 depict the comparison of the aging indices of the PG64-10 and VG30, respectively. These indices are formulated using the asphaltene/maltene ratio of the binder samples, and it was found from the used asphaltene extraction technique.
Aging Index (A/M ratio)
The Potential of Waste Cooking Oil as an Anti-aging Additive in Asphalt … Indices of samples
2.0
171
Threshold for control binder
1.5 1.0 0.5 0.0 Aged PG64
Aged PG64+5%
Aged PG64+3%
PG64-10 binder
Aging Index (A/M ratio)
Fig. 7 Aging indices of the PG64-10 binder samples in comparison with the threshold set by control binder Indices of samples
5.0
Threshold for control binder
4.0 3.0 2.0 1.0 0.0 Aged VG30
Aged VG30+5%
Aged VG30+3%
VG30 Binder Fig. 8 Aging indices (A/M ratio) of the VG30 samples in comparison with the threshold set by control binder
From the above graphs, it is evident that the aged VG30 binder modified with 5% by weight of WCO (AI = 0.97 and 1.07 resp.) showed properties similar to that of the control binder. On the other hand, the optimum WCO for the binder modification of PG64-10 was found to lie between 3% (AI = 1.33 and 1.27 resp.) and 5% (AI = 0.67 and 0.83 resp.) by weight. Figures 9 and 10 indicate that the results obtained from the aging indices are promising which is supported by an R-square value of 0.99. This indicates that the indices from both the rheological as well chemical properties are well correlated and demonstrate the influence of bitumen composition on the rheological properties.
3.1.2
Durability Test
Durability tests are employed to indicate the effective workability of the asphalt binder when mixed with aggregates for laying purposes. This is estimated based on the stripping test conducted as per IS 6241 (1971). The following tables discuss the
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Correlation of AI
AI based on G*/sin
2.0 1.5
R² = 0.9993
1.0 0.5 0.0 0
0.5
1
1.5
2
AI based on A/M ratio Fig. 9 Correlation of aging indices of PG64-10
Correlation of AI
AI based on G*/sin
3.0 2.5
R² = 0.9927
2.0 1.5 1.0 0.5 0.0 0
1
2
3
4
5
AI based on A/M ratio Fig. 10 Correlation of the aging indices of VG30
percentage of aggregates that are strongly coated, moderately coated, and unwell coated respectively as shown in Fig. 11. Figure 12 shows the percentage of binder coating on aggregates depending on various binder types. In the case of PG64-10, the addition of WCO lowered the coating ability of the binder as compared to the unaged binder. This is due to the interaction of the oil components of the binder which form a non-adhesive layer over the aggregate, thereby reducing the coating ability of the binder. In the case of VG30, the addition of WCO lowered the coating ability of the modified binder when compared with unmodified unaged binder but as much as in the case of PG64-10. This could be attributed to the polymer modification and its influence over the adhesive properties of the binder under the influence of WCO.
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Fig. 11 Degree of coating on aggregates as indicated by strong, moderate, and unwell coating, respectively
Fig. 12 Percentage binder coating on aggregate
4 Conclusions The performance of WCO as an anti-aging additive in asphalt binders was determined in this study. For this purpose, WCO percentages of 3 and 5% by weight were utilized in unaged binders (VG30 and PG64-10). The WCO-based modification of bitumen was done followed by short-term aging. For assessment, rheological and chemical tests were performed on unaged, aged, and modified conditions in order to do a comparative study. • The application of WCO in asphalt binder resulted in the reduction of the shear modulus and thereby the rutting capacity of the short-term aged binder. It softened the binder initially so that when the aging sets in, the degree of hardening is lowered as compared to an unmodified sample. High-temperature performance of the binders (Aged VG30 modified with 5% WCO) as indicated from the master
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curves (G* at low reduced frequency readings) was found to be similar to that of their respective control binders. MSCR tests were conducted at two standard stress levels for all the samples. It was observed that the recovery for aged PG6410 with WCO modification was not as high as that of the control binder due to the nature of the polymer modification. On the other hand, WCO-modified-aged VG30 samples (3% and 5%) were found to have a better recovery than the control binder by 25% and 10%, respectively. • Stripping test was performed to test the durability of the binders against the damage taken in terms of coating loss. There was a little drop in the coating ability of the modified binders in comparison to the control binders and hence anti-stripping additive may be required along with the WCO considering the durability issues. • Aging Indices were formulated based on the ratio of the rutting parameters (G*/ sin(δ)) and also on the basis of the asphaltene/maltene ratio for both the binder types. Hence, the optimum WCO content for binder modification was achieved at 5% by weight for VG30 while it lay in the region of 3–5% by weight of WCO for PG64-10. • Further research could include the effect of WCO on the long-term aging of the asphalt binders because although it was found in PG64-10 that at 5% dosage, the binder underperformed as compared to the control binder, with long-term aging the properties could further improve. As a result, a novel approach to deliver the anti-aging rejuvenator such as WCO to the layers of the asphalt pavement as and when required during the course of service life needs to be developed. This would then negate the initial underperformance of the asphalt binder and would provide the scope for improved performance during the service life.
References 1. Ahmed RB, Hossain K (2020) Waste cooking oil as an asphalt rejuvenator: a state-of-the-art review. Constr Build Mater. https://doi.org/10.1016/j.conbuildmat.2019.116985 2. Garcia A, Schlangen E, Van De Ven M (2011) Properties of capsules containing rejuvenators for their use in asphalt concrete. Fuel 90(2):583–591 3. Jain S, Chandrappa AK (2023) A laboratory investigation on benefits of WCO utilisation in asphalt with high recycled asphalt content: emphasis on rejuvenation and aging. Int J Pavement Eng 24. https://doi.org/10.1080/10298436.2023.2172577 4. Azahar WNAW, Bujang M, Jaya RP, Hainin MR, Ngadi N, Mohamad M (2016) Chemical identification of waste cooking oil as additive in bitumen. Key Eng Mater 700:207–215. https:/ /doi.org/10.4028/www.scientific.net/KEM.700.207 5. Mamun A, Al-Abdul H (2020) Comparative laboratory evaluation of waste cooking oil rejuvenated asphalt concrete mixtures for high contents of reclaimed asphalt pavement. Int J Pavement Eng 21(11):1297–1308 6. Sheinbaum C, Balam M, Robles G (2015) Biodiesel from waste cooking oil in Mexico City. Waste Manage Res 33(8):730–739 7. Zhu, Dong B, Wang W, Zhao G, Guo P, Ma Q (2019) Effect of waste engine oil and waste cooking oil on performance improvement of aged asphalt. Appl Sci.https://doi.org/10.3390/ app9091767
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8. Biodiesel made from used cooking oil rolled out in India, 2021. TIMEDRIVE 2021 9. Kazmierowski T, Marks P, Lee S (1999) Ten-year performance review of in situ hot-mix recycling in Ontario. Transp Res Rec 1684:194–202 10. Singhahandhu A, Tezuka T (2010) The waste-to-energy framework for integrated multi-waste utilization: waste cooking oil, waste lubricating oil, and waste plastics. Energy 35(6):2544– 2551 11. Jain S, Dabbiru S, Chandrappa AK (2023) Effects of waste cooking oil on the antiageing ability of bitumen. Adv Civ Eng Hindawi 2023. https://doi.org/10.1155/2023/5155407 12. Asli H, Ahmadinia E, Zargar M (2012) Investigation on physical properties of waste cooking oil—rejuvenated bitumen binder. Constr Build Mater 37:398–405 13. Rasman M, Hassan NA, Hainin MR, Putra Jaya R, Haryati Y, Shukry NAM, Abdullah ME, Kamaruddin NHM (2018) Engineering properties of bitumen modified with bio-oil. In: MATEC web of conferences. EDP Sciences. https://doi.org/10.1051/matecconf/201825002003 14. Zargar M, Ahmadinia E, Asli H, Karim MR (2012) Investigation of the possibility of using waste cooking oil as a rejuvenating agent for aged bitumen. J Hazard Mater 233–234:254–258. https://doi.org/10.1016/j.jhazmat.2012.06.021 15. Mahrez A, Karim MR, Ibrahim MR, Katman HY (2009) Prospects of using waste cooking oil as rejuvenating agent in bituminous binder. Proc East Asia Soc Transp Stud 7:1751–1766 16. Asli H, Karim MR (2011) Implementation of waste cooking oil as RAP rejuvenator. J East Asia Soc Transp Stud 9:1336–1350. https://doi.org/10.11175/easts.9.1336 17. El-Shorbagy AM, El-Badawy SM, Gabr AR (2019) Investigation of waste oils as rejuvenators of aged bitumen for sustainable pavement. Constr Build Mater 220:220–237. https://doi.org/ 10.1016/j.conbuildmat.2019.05.180 18. Zhang D, Chen M, Wu S, Liu J, Amirkhanian S (2017) Analysis of the relationships between waste cooking oil qualities and rejuvenated asphalt properties. Materials (Basel) 10. https:// doi.org/10.3390/ma10050508 19. Jain S, Chandrappa AK (2022) Rheological and chemical investigation on asphalt binder incorporating high recycled asphalt with waste cooking oil as rejuvenator. Innov Infrastruct Solut. https://doi.org/10.1007/s41062-022-00871-3 20. Kumbargeri YS, Biligiri KP (2016) A novel approach to understanding asphalt binder aging behavior using asphaltene proportion as a performance indicator 21. Moreno Navarro F, Sol-Sanchez M, Garcia-Trave G, Rubio-Gamez MC (2018) Fatigue cracking in asphalt mixtures: the effects of ageing and temperature. Road Mater Pavement Des 19:561– 570. https://doi.org/10.1080/14680629.2018.1418717
Application of FDR Technology for Upgradation of a National Highway Ambika Behl, G. Bharath, and Amit Kumar
Abstract Highway construction is one of the industries that uses the most natural resources. The use of recycled materials can lead to significant reductions in mining and the consumption of virgin materials, energy conservation, and landfill space. Innovations such as recycling and pavement stabilization shall be implemented on Indian roads to reduce fuel and aggregate consumption. This paper presents the case study of the adoption of full-depth reclamation (FDR) technology for the rehabilitation and widening of the national highway in Andaman. The work site is in a remote place, and transportation of aggregates to the site is a very expensive proposition. Mining of these raw materials is not allowed in areas near the construction site since it has an adverse effect on the forest environment. To overcome all these challenges, alternate pavement construction methods were explored, and the adoption of stabilization technology for rehabilitation and up-gradation of some parts of Andaman Trunk Road (ATR) was carried out by using FDR. The design planned the in situ stabilization of the existing crust with cement. Keywords Full-depth reclamation · Stabilization · Cement stabilized pavement · Pavement recycling
1 Introduction Pavement recycling can be performed in three ways: cold mix recycling, hot mix recycling, and full-depth reclamation process [1]. If pavement failure is restricted to the upper layer only and the pavement is in suitable bearing condition, hot recycling can be a good solution. If the pavement has structural flaws and is severely damaged A. Behl (B) · G. Bharath · A. Kumar Central Road Research Institute, Delhi, India e-mail: [email protected] G. Bharath e-mail: [email protected]
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_15
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such as fatigue along the wheel path, rutting, and reflected cracking, it is suggested to adopt a full-depth reclamation method. If the situation falls somewhere in between, cold recycling can be useful [2, 3]. Full-depth reclamation (FDR) is a pavement restoration technology that comprises recovering the existing asphalt pavement as well as the underlying foundation into a new base layer [4]. The entire thickness of the asphalt, as well as a portion of the aggregates below it, is utilized to construct a stabilized base course in FDR [5]. The depth of reclamation is affected by the current pavement thickness, soil properties, and on traffic conditions. In general, reclamation depth varies between 100 and 300 mm [6–8]. Full-depth reclamation reduces the pavement construction cost by 25– 50% when compared with conventional pavement cost [9, 10]. There are numerous advantages of full-depth reclamation, including increased bearing capacity, increased durability, structural strength, and stability of pavement, hence leading to a long pavement service life [1]. In comparison to approaches that require aggregates to be trucked to the site, a full-depth reclamation process reuses the in-place aggregates and hence less amount of virgin aggregates is required. When compared to removeand-replace construction methods, FDR is time-saving and economical by reducing hauling and labour costs [11]. The reclamation process is defined in five primary phases including in-place Pulverization and mixing of the present asphalt layer with base and subgrade material. Several additives and water are blended with obtained pulverized pavement on which required gradation and compaction are performed to achieve the desired level. This process is followed by the application of the surface course [10, 12]. FDR’s key advantage is the ability to reuse reclaimed asphalt pavement (RAP) and in-place aggregates. The reuse of RAP material particularly in the base layer of pavement provides useful materials for road maintenance and rehabilitation process. This act is an environmentally friendly and quick solution. The inclusion of an appropriate stabilizer to the RAP and soil mixture increases its strength and stiffness hence permitting it to be used in the base course [13]. Portland cement, calcium chloride, hydrated lime, and coal fly ash are among the chemical stabilizers utilized. For bituminous stabilization, asphalt emulsions and foaming asphalt are utilized [14, 15]. The use of cement in FDR provides several technological, economic, and environmental benefits [1]. It results in pavements that are more durable, less erosive, water-resistant, and can withstand stress due to high traffic loads. Full-depth reclamation with cement has been used mostly on low-traffic intensity roads [7, 16]. The slab-like characteristics of cement stabilized base layer mitigate the subgrade failure, pothole formation, and road roughness of pavement. This also leads to reduced design pavement thickness [4]. The literature suggests that raising the percentage of cement in the mix prepared with RAP and aggregates shows an increase in unconfined compressive strength value [6, 17–22].
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It is important to calculate the optimum stabilizer content of cement on the basis of strength and durability of the treated slab in the laboratory to avoid the formation of shrinkage cracks [6, 17, 21]. Prior to the cement stabilization process stabilization, the in-place material should be checked for sulphate concentration because the chemical reaction of minerals leads to the swelling action of the layers. Therefore, sulphate content below 3000 ppm is acceptable for soil stabilized with cement [17, 21].
1.1 Appraisal of the Project Road The major highway in Andaman and Nicobar Islands is NH 4. The Andaman Trunk Road (ATR) connects the capital city of Port Blair to Diglipur and is 230.7 km long. This highway is undergoing extensive renovations currently. The pavement to be upgraded was badly damaged and had a 25–30 mm asphalt layer over WMM. Figure 1 shows the pavement condition before rehabilitation. The vast Andaman and Nicobar group of islands is separated from mainland India by sea. Owing to limited resources, environmental constraints, and obvious compulsion, the islands depend on mainland India for almost everything; most of the construction raw material also need to be shipped from the mainland to the Port Blair ports. Transportation of aggregates to the site would have been a very expensive proposition, so an alternate road construction method was explored.
Fig. 1 Pavement condition before rehabilitation
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2 NH 4 Rehabilitation Program 2.1 Laboratory Evaluation In order to give optimum pavement design for rehabilitation and widening of the NH 4 section, a detailed site visit was made. Visual inspection was carried out to assess the distress in the existing pavement. The existing pavement materials from different layers of the pavement were pulverized and transported to Central Road Research Institute (CRRI) laboratory for evaluation to find the suitability of full-depth reclamation and reusing that material in constructing new pavement. Materials used in cement stabilized aggregate base comprise basically three components, aggregates, cement, and water. Gradation of aggregates, density, index properties, and strength are all factors to consider when designing a mix, while gradation is the most important. The particle size distribution with the highest density is generally sought after. Gradation for cement-bound materials as per MoRTH specifications (5th Revision) is adopted. The physical requirements for materials and cement treatment in the base course are specified in MoRTH specifications, Grading I Clause 401.2.2. (5th Revision). Table 1 shows the gradation of the existing material and proportioning for cement treated base (CTB) mix. All the soil samples were tested, and PI was found to be 5. The aggregate materials are used in a given proportion as shown in Table 1 to cast cubes for the compressive strength test. The cubes are cast at a pre-determined reference density of 2.21 g/cc and optimum moisture content (OMC) 6.50%. For preparing compressive strength test samples, cubical moulds of 15 cm (internal) size were used, and the mix was compacted using vibratory compaction. CTB mix was designed; 7-day laboratory unconfined compressive strength (UCS) of more than 4.5 MPa is required for use in the base course. The average observed 7 days UCS value was found 4.75 MPa and the average observed 28 days UCS value was 7.19 MPa. 5% cement was used, cement is generally effective for low plasticity materials, the percentage passing through 425 µm sieve should not exceed 25%, and uniformity coefficient should be greater than 10. Soil having PI greater than 30, or organic content higher than 2%, or carbonate concentration more than 0.2% is generally unsuitable for cement stabilization. The pavement design is carried out for design traffic of 20 MSA and stabilized subgrade of CBR 8%. The pavement design was as per Table 2.
2.2 Construction Project evaluation was the first step in the construction process. A necessary comprehensive site investigation was conducted in order to check and qualify the quality and quantity of reclaimed material that will be processed for the recycling procedure. The biggest advantage of using the in situ stabilization method is that there is no need for the excavation of old or existing soil, the disposal, and the return of the new ground.
0
0
39
24
15
5
3
1
19
9.5
4.75
0.6
0.3
0.075
0
0
0
0
63
93
37.5
100
0%
40 mm
1
1
1
1
7
69
100
100
0%
20 mm
Fresh materials
100
70%
Existing material
53
Sieve size (mm)
Proportioning and gradation of individual aggregate
0
0
0
1
86
100
100
100
10%
10 mm
4
7
12
100
100
100
100
100
15%
Stone dust
95
100
100
100
100
100
100
100
5%
Cement
Table 1 Aggregate proportioning for existing granular layer material with fresh aggregates
6
8
10
31
46
57
95
100
Gradation of blended mix
0
5
8
25
35
45
95
100
Lower limit
10
40
65
100
100
100
100
100
Upper limit
Specified limits as per MoRTH 2013 Vth revision
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Table 2 Pavement design Design traffic
20 msa
Bituminous concrete (BC)
40 mm
Crack relief layer/SAMI Stabilized base with FDR material
330 mm
Subgrade (effective 8% CBR)
500 mm
The materials used in a sub-base/base should be satisfactorily well-graded to achieve a well-closed surface texture, and their grading should fall within the range shown in the table below. Fresh aggregate/dust was spread over the existing road surface as per the design mix requirement; Fig. 2 shows the aggregates spread on the surface. The stabilizing additive was also spread on the surface as shown in Fig. 3. WR 240 recycling machine/ stabilizer was used with a water tanker for pulverizing the existing pavement surface, and in situ mixing of stabilizing additive was carried out. The top 30 cm was pulverized (Fig. 4). Preliminary compaction is done with the help of a padfoot roller (Fig. 5), and final compaction is done with a steel drum compactor (Fig. 6) followed by PTR for final finishing. Then curing process follows before the BC overlay. Curing should be done for minimum of 7 days with water spraying 2–3 times a day. Figure 7 shows the surface after compaction; the mix was laid and compacted in a single train. Additives like Cement (OPC 43) are added to increase or attain the required strength.
Fig. 2 Spreading of aggregate
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Fig. 3 Spreading of cement
Fig. 4 In situ stabilization in progress
3 Field Validation After 6 months of construction, the cores were taken from the section for validation of the strength/UCS values of the CTB layer. The locations for the cores were chosen in such a way that they should cover the entire area and representative stabilized samples. These collected cores were carefully packaged and delivered to the laboratory for evaluation of unconfined compressive strength (UCS).
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Fig. 5 Preliminary compaction
Fig. 6 Final compaction
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Fig. 7 Finished CTB surface
A condition survey of all the roads was carried out manually to identify any cracks on the pavement surface. No cracks were observed in all the study roads. All the sections were constructed with a crack relief layer (SAMI) to avoid the reflective cracks due to cement stabilization. The collected cores were properly sliced to a cylindrical shape of the required length to get a uniform surface for the unconfined compressive strength (UCS) test. The UCS test results are shown in Table 3.
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Table 3 UCS value of field cores Sample No.
Chainage
UCS, MPa
1
243–560
7.79
2
241–775
6.49
3
242–980
5.19
4
230–460
7.79
5
231–520
7.15
6
230–830
9.61
7
166–990
8.71
8
174–370
6.79
4 Conclusion The FDR process with stabilization resulted in reduced construction time, virgin aggregate consumption, material transportation, and various other environmental advantages. Changer software was used to calculate the reduction in emissions of CO2 equivalent and material savings. For a project of 45 km (2 lanes) approximately 2140 tonne of equivalent CO2 is saved by adopting FDR technology which means less pollution. The aggregate savings were approximately 2.5 lakh tonnes.
References 1. Ghanizadeh AR, Rahrovan M, Bafghi KB (2018) The effect of cement and reclaimed asphalt pavement on the mechanical properties of stabilized base via full-depth reclamation. Constr Build Mater 161:165–174 2. Dai S, Skok E, Westover T, Labuz J, Lukanen E (2008) Pavement rehabilitation selection 3. Stroup-Gardiner M (2011) Recycling and reclamation of asphalt pavements using in-place methods. No. Project 20-05 (Topic 40-13) 4. Reeder GD, Harrington DS, Ayers ME, Adaska W (2017) Guide to full-depth reclamation (FDR) with cement. No. SR1006P 5. Morian DA, Solaimanian M, Scheetz B, Jahangirnejad S (2012) Developing standards and specifications for full depth pavement reclamation. No. FHWA-PA-2012-004-090107, Dept. of Transportation, Pennsylvania 6. Bang S, Lein W, Comes B, Nehl L, Anderson J, Kraft P, deStigter M, Leibrock C, Roberts L, Sebaaly PE, Johnston D (2011) Quality base material produced using full depth reclamation on existing asphalt pavement structure–task 4: development of FDR mix design guide. No. FHWA-HIF-12-015, Federal Highway Administration, Office of Pavement Technology, United States 7. Godenzoni C, Graziani A, Bocci E, Bocci M (2018) The evolution of the mechanical behaviour of cold recycled mixtures stabilised with cement and bitumen: field and laboratory study. Road Mater Pavement Des 19(4):856–877 8. Gonzalo-Orden H, Linares-Unamunzaga A, Pérez-Acebo H, Díaz-Minguela J (2019) Advances in the study of the behavior of full-depth reclamation (FDR) with cement. Appl Sci 9(15):3055 9. Guthrie WS, Brown AV, Eggett DL (2007) Cement stabilization of aggregate base material blended with reclaimed asphalt pavement. Transp Res Rec 2026(1):47–53
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10. Pappas J (2012) Environmental considerations of in-place recycling. In: Virginia pavement recycling conference. Virginia Tech Transportation Institute, Virginia 11. Luhr DR, Adaska WS, Halsted GE (2007) Guide to full-depth reclamation (FDR) with cement 12. Mallick RB, Bonner DS, Bradbury RL, Andrews JO, Kandhal PS, Kearney EJ (2002) Evaluation of performance of full-depth reclamation mixes. Transp Res Rec 1809(1):199–208 13. Puppala AJ, Hoyos LR, Potturi AK (2011) Resilient moduli response of moderately cementtreated reclaimed asphalt pavement aggregates. J Mater Civ Eng 23(7):990–998 14. Kearney EJ, Huffman JE (1999) Full-depth reclamation process. Transp Res Rec 1684(1):203– 209 15. Maccarrone S, Holleran G, Leonard DJ, Hey S (1994) Pavement recycling using foamed bitumen. In: 17th ARRB conference, Gold Coast, Queensland, proceedings, vol 17, part 3, 15–19 Aug 1994 16. Jones D, Louw S, Wu R (2016) Full-depth reclamation: cost-effective rehabilitation strategy for low-volume roads. Transp Res Rec 2591(1):1–10 17. Batioja DD (2011) Evaluation of cement stabilization of a road base material in conjunction with full-depth reclamation in Huaquillas, Ecuador. Brigham Young University 18. Maher MH, Gucunski N, Papp WJ (1997) Recycled asphalt pavement as a base and sub-base material. ASTM Spec Tech Publ 1275:42–53 19. Miller HJ, Guthrie WS, Crane RA, Smith B (2006) Evaluation of cement-stabilized full-depthrecycled base materials for frost and early traffic conditions 20. Suebsuk J, Horpibulsuk S, Suksan A, Suksiripattanapong C, Phoo-ngernkham T, Arulrajah A (2019) Strength prediction of cement-stabilised reclaimed asphalt pavement and lateritic soil blends. Int J Pavement Eng 20(3):332–338 21. Taha R, Al-Harthy A, Al-Shamsi K, Al-Zubeidi M (2002) Cement stabilization of reclaimed asphalt pavement aggregate for road bases and subbases. J Mater Civ Eng 14(3):239–245 22. Dixon PA, Guthrie WS, Eggett DL (2012) Factors affecting strength of road base stabilized with cement slurry or dry cement in conjunction with full-depth reclamation. Transp Res Rec 2310(1):113–120
Investigating Mechanical and Hydraulic Properties of Porous Concrete Pavements Deepti Avirneni, Abhishek Kumar Bondada Ch., and Semanth Reddy Bommu
Abstract Porous concrete pavements are gaining research importance as they are instrumental in addressing two major environmental challenges: recharging groundwater and reducing stormwater runoff. In developing countries like India where demand for paved roads is increasing multifold, porous concrete pavements might prove a good alternative over conventional pavements owing to the above-said advantages. However, their use is limited to sidewalks and low-volume roads as they exhibit low strength and are less durable. Strength improvement of porous concrete is the need of the hour. Most of the studies on porous concrete focused on permeability and hydraulic properties. However, strength improvement is not well addressed. Using small quantities of fine aggregates, graded course aggregates would substantially improve the strength of porous concrete. Also, fibers are said to greatly enhance the strength of porous concrete paving the way for their use in high-volume roads. The present study focuses on investigating the compressive strength and its improvements of porous concrete pavements using plastic and steel fibers. Compressive strength tests were performed for the designed mixes. Also, total air void tests were conducted to measure the possible groundwater recharge. Keywords Porous concrete · Strength · Permeability · Air voids
D. Avirneni (B) · A. K. Bondada Ch. · S. R. Bommu Mahindra University, Hyderabad, India e-mail: [email protected] A. K. Bondada Ch. e-mail: [email protected] S. R. Bommu e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_16
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1 Introduction and Background India has the second largest road network (over 6,215,797 km) in the world after the United States, out of which 70% were paved as of 2020 [1]. However, there is a huge demand for road infrastructure owing to the exponential increase in motor vehicle registrations in the country. It is clearly evident from the annual budget of the year 2022 (over 1100 billion INR allocated to roads) that the Government of India is putting its consistent efforts to build new expressways and economic corridors [2]. It is accepted that the improved road network enhances the socio-economic development of the country. However, it also adds a huge amount of carbon footprint, consumes a lot of resources, and creates an urban heat island. The rapid growth of the urban population has not only created huge demand for pavements but also has forced negative changes in the landscape. Also, it created serious problems pertaining to stormwater drainage in most of the Indian metropolitans. Moreover, paved surfaces do not infiltrate stormwater and thereby pose a problem of flooding. In this regard, the construction of porous concrete pavements can provide a two-fold advantage in terms of rainwater harvesting and rainwater drainage. Porous concrete (PC) also known as pervious concrete is concrete with limited/no fines with high void content that allows water to pass through and reduces stormwater runoff/flooding and facilitates groundwater recharge. It contains a large fraction of interconnected voids, which can be achieved by using gap graded aggregates and with little or no fines. It is therefore often referred to as no fines concrete. PC pavement is considered as a green infrastructure solution which can replace the conventional gray infrastructure, especially for low-volume roads, parking lots, side streets, etc. [3]. Many studies were reported in the literature with the main objective of using them in low-traffic situations in order to mitigate the environmental issues pertaining to stormwater management and rainwater harvesting. Other potential benefits of PC pavements as reported in the literature are mitigating heat island effect, sound absorption, pollutant removal from stormwater, etc. [4]. The porous concrete contains single-sized/gap graded aggregates with an optimum quantity of cement enough to coat the aggregates and bind them together. Its porosity typically varies between 15 and 25% with a prescribed minimum of 15% (NRMCA). In order to maintain sufficient void content in the porous concrete, aggregates of size 19–9.5 mm are generally used by many researchers [5]. However, several other studies aiming at strength improvement have used coarse aggregates of size 9.5– 2.36 mm also [6]. The mechanical properties like strength and durability of pervious concrete are very important as they directly affect the design thickness of the pavement. In the recent past, many researchers have estimated different properties for various types of porous concrete. The studies indicate that porous concrete exhibits low compressive strength owing to the presence of low/no fines. Also, the type, shape, and gradation of aggregates significantly influence the compressive strength of porous concrete. The addition of admixtures, especially water reducers may improve workability with a low water-cement ratio and increases strength as well. Also, both steel and plastic fibers
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were known to improve the strength and durability of concrete. Fibers with different aspect ratios (ratio of length to diameter) varying from 20 to 100, and different cross-sections were used by some researchers in their study. Indicative changes in different physical properties, especially crack resistance, and also impact, fatigue, and durability of concrete can be witnessed by the addition of a certain percentage of steel fibers [7]. Although porous concrete pavements exhibit promising benefits to the built and natural environments, there are certain issues that threaten their long-term effectiveness. One of the important factors is the clogging of porous concrete pavements due to sediments in stormwater, or particles originating from traffic. Hence, porous concrete requires due maintenance to upkeep the advantages live throughout its design life. Overall, past studies proved that the use of porous concrete is limited to lowvolume roads such as local streets, parking lots, and footpaths. However, their use in high-volume roads is not much popular owing to their low strength and durability. Hence, this study aims at producing porous concrete with reasonably good strength, so that it can be used in urban streets and highways in the near future.
2 Materials and Methods 2.1 Materials Used The materials used in this project are cement, fine aggregate, coarse aggregates, steel fibers, plastic fibers, and water. The details of the materials are given below. Portland Cement Ordinary Portland cement of 53 grade was used for this study conforming to the requirements of IS-8112. The properties of the cement are shown in Table 1. Aggregates Coarse Aggregates Crushed angular aggregates passing 20 mm and retained on 16 mm and passing 12.5 mm and retained on 10 mm sieve were used in this study. The properties of coarse aggregates were presented in Table 2. Table 1 Properties of cement
S. no.
Property
Value
1
Fineness
390 m2 /Kg
2
Initial setting time
60 min
3
Final setting time
530 min
4
Sp. gravity
2.92 g/cc
192 Table 2 Properties of coarse aggregates
D. Avirneni et al.
S. no.
Property
Value
1
Impact value
16%
2
Crushing value
35%
3
Los Angeles abrasion value
30%
4
Sp. gravity
2.54
Fine Aggregates River sand passing through 1.18 mm sieve and retained on 600 µm sieve was used. The specific gravity of sand was found to be 2.62. Fibers Steel fibers Steel fibers with length 5 mm and diameter 0.1 mm were used in this study. The density of the steel fibers is 7860 kg/m3 . Fibers used in the study are shown in Fig. 1. Plastic fibers The polyethylene terephthalate (PET) fibers formed by mechanical cutting of PET bottles were used in the study. The bottlenecks and the bottom of the bottles were discarded. The length of the fibers is ensured to be in the range of 40–60 mm and the width of the fibers ranged from 2 to 3 mm. The density of plastic fibers is 1380 kg/ m3 . Fibers used in the study are shown in Fig. 1.
Fig. 1 Plastic and steel fibers used in the study
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Table 3 Proposed mixes S. no.
Mix name
Mix composition
1
M1
Single-sized aggregates (16–20 mm)
2
M2
Single-sized aggregates (16–20 mm) + 5% fine aggregates (600 µm to 1.18 mm)
3
M3
50% (16–20 mm) + 50% 10–12.5 mm) + 5% fine aggregates (600 µm to 1.18 mm)
4
M4
Single-sized aggregates (16–20 mm) + 5% fine aggregates (600 µm to 1.18 mm) + 1% Plastic fibers by volume of concrete
5
M5
Single-sized aggregates (16–20 mm) + 5% fine aggregates (600 µm to 1.18 mm) + 1% steel fibers by volume of concrete
2.2 Methodology Overall, five mixes as shown in Table 3 were proposed in this study, and all the mixes were tested for compressive strength after 3, 7, and 28 days of curing. Further, after 28 days air void content was measured for all the mixes. Mix M1 is the base mix which had single-sized aggregate and no fine aggregate. Other mixes M2 to M5 have 5% fine aggregate. M3 had 2 sizes of aggregates along with fine aggregates. The details of the mixes were shown in Table 3.
2.3 Mix Design The concrete mix design proposed by IRC 44-2017 for pervious concrete pavements was used. The following are the steps involved in mix design: (1) The grade of concrete designed is M20. (2) OPC 53 grade cement was used for all the designs. (3) The specific gravity of cement is 3.15 and the specific gravity of coarse aggregate is 2.7. (4) The water absorption of the coarse aggregate is 0.5%. (5) Design strength was calculated using the following formula: f , ck = f ck + 1.65S where f’ck is the target mean compressive strength at 28 days, fck is the characteristic compressive strength at 28 days, and S is the standard deviation of compressive strength. From Table 1 of IRC 44, The standard deviation S = 2.5 N/mm2 f , ck = 24.13 N/mm2
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(6) The water-cement ratio for all the mixes was set at 0.36. (7) From Table 2 of IRC 44-2017 for a design strength of 24 MPa, the void content will be 15%. (8) The paste volume is the summation of cement volume and water volume. (9) Let Vp be the paste volume, Vp = Cement Volume + Water Volume Vp =
w c × 1000 + kg/m3 3.15 1000
where c is the weight of the cement. (10) From IRC 44-2017, for a well-compacted concrete the paste volume Vp will be 18%. Hence, c can be calculated from the above equation. c = 266.6 kg/m3 . (11) Volume of aggregate = [1 − (paste volume + void content)] = 67% of the total concrete volume. (12) Mass of coarse aggregate = 1809 kg/m3 In some mixes, 5% fine aggregate was used in the total aggregate content in order to enhance the strength of porous concrete. The quantities of raw materials used in the present study for different mixes were shown in Table 4. Table 4 Mix proportions S. no.
Mix name
Mix compositions (Kg/m3 ) Water
Cement
Coarse aggregate
Fine aggregate
Fibers
1
M1
141
393
1500
0
0
2
M2
141
393
1500
76
0
3
M3
141
393
750+750
76
0
4
M4
141
393
1500
76
13.8
5
M5
141
393
1500
76
78
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3 Results and Discussions 3.1 Total Void Ratio Total void content is defined as the total percentage of voids present in the volume of the specimen. To calculate the volume of voids, the cube specimen is made air-tight by using polyethene sheets and tape. Later, water is filled in the specimen from the top until all the air voids are filled with water. The volume of voids is the volume of water that is filled in the voids. The total void content of hardened porous concrete cubes was determined using Eq. (1): Pv(%) =
Vw × 100 Vs
(1)
Pv Void content. Vs Volume of the sample. Vw Volume of voids. Figure 2 shows the void ratio of different mixes. Error bars indicate the standard deviation of three samples. It is observed that the aggregate gradation exhibited a significant effect on the total void ratio. The total void ratio decreased for graded aggregates. Mix without fine aggregates has more voids in comparison with the mix with fine aggregates. It was observed that most of the porous concrete had a total void ratio ranging from 8 to 16% regardless of aggregate size. 20
Voids Ratio (%)
16 12 8 4 0 Composition Single sized 5% Fine Graded aggregates aggregates aggregates Mix
M1
Fig. 2 Voids content of different mixes
M2
M3
1% Plastic fibers
1% Steel fibers
M4
M5
196 Table 5 Density of the mixes
D. Avirneni et al.
Mix
Weight (Kg)
Volume (m3 )
Density (Kg/m3 )
M1
7.01
0.003375
2077.037
M2
7.65
0.003375
2266.667
M3
7.99
0.003375
2367.407
M4
7.79
0.003375
2308.148
M5
7.88
0.003375
2334.815
3.2 Density Density of porous concrete is calculated as the ratio of the weight of the cube (Kg) to the volume of the cube (m3 ). Density for various mixes is calculated and reported in Table 5. Mix M3 has the highest density and least void content. It is evident that using two different size aggregates increased particle packing and thereby density.
3.3 Compressive Strength Compressive strength of different mixes was determined in accordance with IS:5161959. Cubes of size 15 cm × 15 cm were cast (Fig. 3) and tested after curing for 3, 7, and 28 days. Three cube specimens for each mix were cast and mean value is reported. The 28-day compressive strength results were shown in Table 6. The compressive strength of mix M3 is observed to be the highest of all the mixes. It is observed that the higher the void content, the lower the compressive strength. Compressive strength increases as the average size of aggregates decreases, however void content decreases. Fibers, both steel and plastic, have significantly increased
Fig. 3 Porous concrete cubes
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Table 6 Compressive strength of different mixes (MPa) Mix
Mix composition
M1
Single sized aggregates
3 days
7 days
3.24
5.76
28 days 12.45
M2
5% Fine aggregates
9.34
16.35
24.16
M3
Graded aggregates
15.43
26.45
33.87
M4
1% plastic fibers
12.23
20.82
29.01
M5
1% steel fibers
16.01
25.34
30.93
the compressive strength of porous concrete. Though the base mix was designed as an M20 mix, the improvements in the gradation and inclusion of fibers have brought to the maximum compressive strength of 33 MPa. Strength development rate with respect to different curing periods for different mixes was shown in Fig. 4. All mixes gained around 30% of strength at 3 days and 60% of strength at 7 days in comparison with 28 days of curing. Gradation of aggregates and inclusion of fibers have not much changed the rate of strength gain. Error bars indicate the standard deviation of three samples. Figure 5 shows the relation between void content and compressive strength. Compressive strength increases as void content is increased in general for all the mixes. However, it is interesting to note that both compressive strength and void content of the mix with steel fibers are higher in comparison with mixes with plastic fibers. This might be possible because the width of plastic fibers is considerably high in comparison with steel fibers. Hence, plastic fibers clog the voids and reduce the void content.
Compressive Strength (Mpa)
40 35 30 25 20 15 10 5 0 0
5
10
15
20
25
30
Curing Period (days) M1
M2
M3
M4
Fig. 4 Compressive strength for different mixes at different curing periods
M5
D. Avirneni et al.
Compressive Strength (Mpa)
198
40 33.87(M3)
35
30.93(M5)
30 24.16 (M2)
29.01(M4)
25 20 15
12.45(M1)
10 8
9
10
11
12
13
14
15
16
Void Ratio (%) Fig. 5 Relation between compressive strength and voids ratio for different mixes
However, a balance between strength and void content should be arrived at in choosing a particular mix. Based on the requirement of particular site conditions like terrain, rainfall in that area, and traffic, one should carefully select the mix to achieve the required properties of porous concrete.
4 Conclusions Based on the experimental results obtained in the study, the following conclusions have been made: • Addition of 5% fine aggregate increased the strength of porous concrete 2 times in comparison with the base mix which had single-sized aggregates. • Using graded aggregates has increased strength threefold by achieving 8% void content. • Addition of both steel and plastic fibers increased the compressive strength up to 150%. • Compressive strength increased as the void content decreased in all cases except the case with plastic fibers. • Density increased as void content decreased for all the mixes. • Rate of strength gain with the period of curing was similar to all mixes. It can be concluded from the study that the strength of porous concrete can be improved by the inclusion of fibers, or by improving particle packing. Hence, porous concrete can be used in urban streets which would address the problems of groundwater and flooding.
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References 1. Ministry of Road Transport and Highways, Government of India.: Annual report (2020–21) 2. Union budget, National portal of India, https://www.india.gov.in/spotlight/union-budget-fy2022-2023. Accessed 11 Apr 2022 3. Xie N, Akin M, Shi X (2019) Permeable concrete pavements: a review of environmental benefits and durability. J Clean Prod 210:1605–1621 4. Chandrappa AK, Biligiri KP (2016) Pervious concrete as a sustainable pavement material— research findings and future prospects: a state-of-the-art review. Constr Build Mater 111:262– 274 5. Neithalath N, Sumanasooriya MS, Deo O (2010) Characterizing pore volume, sizes, and connectivity in pervious concretes for permeability prediction. Mater Charact 61(8):802–813 6. ACI 522R-2010, Report on Pervious Concrete, American Concrete Institute (2010) 7. Tang CW, Cheng CK, Ean LW (2022) Mix design and engineering properties of fiber-reinforced pervious concrete using light weight aggregates. Appl Sci 12(524):1–21
Development of High Friction Bituminous Surface Course for Aircraft Movement Manoj Shukla, G. Bharath, and Satish Chandra
Abstract Runway skid resistance is the most important parameter in deciding the safety levels and is responsible for traffic accidents, especially in wet conditions. Tirepavement interaction, which influences skid resistance, is one of the principal safety factors for asphalt pavements which is directly connected to surface texture characteristics. There is currently no established protocol for the choice and utilization of aggregate gradation to achieve desired frictional performance. The present research was taken up with the objective of developing specifications for Asphalt Concrete surfacing to ensure and further improve the friction coefficient. It was achieved by modifying the gradation of the mix to produce high friction coefficient. A surface course with friction between tire and the pavement not less than 0.74 was targeted in the study. The Laboratory investigations revealed that the mix produced with modified gradation has sufficient strength as estimated through Retained Marshall Stability. The mix was also found less susceptible to moisture-induced damage, as verified through Tensile Strength Ratio analysis. Trial sections of Asphaltic Concrete (AC) were laid at two airports in order to check the runway friction coefficient with modified aggregate gradations. Three trial sections were laid on two airport runways, and runway friction values were measured using the Airport Surface Friction Tester (ASFT). Friction values were also measured on the existing runway (before laying of the trial sections). The friction values in trial sections were in the range 0.78–0.83 which are greater than the targeted value of 0.74. The laboratory and field trials by the modified gradation exhibited that all the stipulated norms are met while enhancing the friction considerably. Keywords Skid resistance · Airport surface friction tester · Asphalt concrete surfacing
M. Shukla (B) · G. Bharath Central Road Research Institute, Delhi, India e-mail: [email protected] S. Chandra Indian Institute of Technology, Roorkee, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_17
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1 Introduction 1.1 Background Runway skid resistance is the most important parameter in deciding the safety levels and is responsible for traffic accidents, especially in wet conditions. Hoerner and Smith (2002) claim that the majority of accidents that occur in wet weather are caused by uncontrolled skidding resulting from inadequate surface friction [1]. Studies show that a 0.1 increase in average friction can result in a 13% decrease in the frequency of wet accidents [2, 3]. Thus, skid resistance is one of the most important functional performance parameters of a pavement. Several studies have shown that in wet weather, runway skid resistance decreases significantly [4–8]. Therefore, friction must be high enough to enable directional control of aircraft during landing and effective braking along the length of the runway. According to the technical specification, the friction must be at least 0.63 after construction of the runway [9]. Perhaps, a thin film of water on the road can cause hydroplaning in high-speed vehicles. In addition, other factors like tread wear, tire groove, and pavement texture have been taken into account in skid resistance formulae developed through research methods [10, 11]. Currently, runway grooves are intended to enhance skid resistance and decrease the likelihood of hydroplaning throughout aircraft landing and takeoff [12–14]. Wet-pavement friction, as per statistical data analysis, is also vital to highway traffic collisions [15]. Thus, it is important to find the frictional properties of the runway surface. Tire-pavement interaction is a crucial safety consideration for asphalt pavements, which is connected to surface texture and has a significant influence on skid resistance and surface drainage. According to Srirangam (2014), adequate macrotexture can improve ride comfort and safety in wet conditions by providing better skid resistance [16]. The characteristics of the aggregates of the wearing course in the surface layer determine the skid resistance [17, 18]. When the tire deforms around the coarse aggregates, macrotexture induces energy dissipation (hysteresis) and generates a retarding force [19]. Coarse aggregate bonded to the asphalt surface with angular fines provides a beneficial micro texture [20]. The size, shape, and gradation of coarse aggregate in the asphalt mixture, as well as the construction practices, all influence macrotexture [21]. Kanafi (2015) conducted a 9-month study to investigate the relationship between friction and texture (macro and micro) of asphalt pavements and used statistical and fractal variables to correlate surface texture with friction [5]. While most studies aim at extending pavement life, there is no transparent standard for the selection and utilization of aggregate gradation to ensure preferred frictional efficiency. To achieve the intended surface characteristics, a suitable surface mix for AC pavement must be selected.
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The coefficient of friction is defined as the ratio of the tangential force required for maintaining uniform relative motion between the two surfaces in contact (tire and pavement surface) to the perpendicular force trying to hold them in contact. Satisfactory runway friction properties are required for three major purposes (ICAO-2002): deceleration of the airplane following landing or an aborted take-off; sustaining directional stability during the ground roll on take-off or landing, particularly in cross-wind, asymmetric engine power, or technical malfunctions; and wheel spin-up at touchdown.
1.2 Objectives and Scope of the Study The major objective of the present study was to develop specifications for Asphalt Concrete surfacing to ensure and further enhance the friction coefficient for aircraft movement. The scope of work included the following activities: . Review of AAI’s surfacing mix specifications through laboratory evaluation . Carry out desirable modifications in grading to obtain volumetric properties of design requirements/specifications . Evaluation of performance and determination of friction coefficient on laid sections on different runways . Performance-based recommendations to achieve design objective friction level for a new surface. The activities involved are represented by a flowchart shown in Fig. 1.
Fig. 1 Flowchart for research methodology
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2 Field Investigations 2.1 Background Field visits to two different airports, Bhopal and Imphal, were made to undertake field observations, review laboratory processes, and verification of ingredient material. During the project, aggregate gradation for Bhopal airport was modified in two different trials keeping within the gradation envelope of AAI specifications. It was decided to follow the gradation for Dense Asphaltic Concrete (DAC) layer which is almost similar to the FAA gradation and used in all AAI works. Specifications provided by AAI and FAA for aggregate gradations are given in Table 1. The AAI and FAA aggregate gradation plots are shown in Fig. 2. According to research studies, increases in the proportion of coarse aggregate in asphalt mixture will result in higher surface friction [22]. Therefore, in the study, it was intended to modify the AAI gradations by altering the coarser percent of aggregate gradations. A proper iterative exercise was required to set the gradation to achieve the objective, without losing the mix parameters including density-void requirements. The trail gradations are adopted based on AAI gradations and verified to be within the FAA-specified gradation limits. The aggregate gradations finally used for trial sections (referred to as modified aggregate gradation in this paper) are given in Table 2. To check the runway friction coefficient for modified aggregate gradations, two trial sections, 300 m each in length, were laid in Bhopal. Similarly, one trial section was laid in Imphal airport for a length of 200 m. VG-30 viscosity grade bitumen was used in the DAC layer for three test sections. The physical properties of the binder and aggregates used in the study are given in Tables 3 and 4, respectively. The details of the target aggregate gradations selected for the test sections are given in Table 2. Trial gradations, AAI and FAA aggregate gradations, are compared in Fig. 3. Table 1 Aggregate Gradation for DAC layer
Sieve size (mm)
AAI (2011)
FAA (2017)
Passing (%) 19
100.00
100
13.2
90–100
79–99
9.5
70–88
68–88
4.75
53–71
48–68
2.36
42–58
33–53
1.18
34–48
20–40
0.6
26–38
14–30
0.3
18–28
9–21
0.15
12–20
6–16
0.075
4–10
3–6
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Fig. 2 Aggregate gradation for DAC layer Table 2 Target aggregate gradation selected for the test section Sieve size (mm)
Bhopal Trial-1
Imphal Trial-2
Trial-1
100
100
Percentage passing 19
100
13.2
94.7
97.2
93.2
9.5
76.0
87.4
82.4
4.75
52.3
70.7
57.9
2.36
42.7
48.4
43.3
1.18
30.9
32.4
32.0
0.6
23.0
24.1
24.1
0.3
18.3
19.1
19.0
0.15
9.4
9.8
12.4
0.075
5.4
5.7
4.0
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Table 3 Runway surface friction test results using ASFT Location/test stretch
Friction coefficient Test stretch 1
Test stretch 2
Existing surface
Bhopal
0.79
0.83
0.66
Imphal
0.78
–
0.63
Table 4 Physical properties of aggregates Properties
Bhopal
Imphal
Specified value
Aggregate impact value (%)
15
17
24% (max)
Combined flaky and elongation index (%)
42
24
35% (max)
Water absorption (%)
0.9
1.2
2% (max)
Fig. 3 Trial aggregate gradation
The bituminous mixes were produced in a drum mix plant. In Bhopal, four sieves (10 mm, 6 mm, 4 mm, and dust) were placed in the screening chamber, whereas in Imphal, only three sieves (16 mm, 10 mm, and dust) were placed in the screening chamber. Aggregate blending was performed to determine the proportions of various
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Fig. 4 Construction of trial section on Bhopal runway, a brooming, b aggregate stockpiling, c drum mix plant, and d finished surface
aggregate sizes to be used. Construction stages of the DAC layer in Bhopal and Imphal are shown in Figs. 4 and 5, respectively.
2.2 Measurement of Friction on Trial Section Current friction-measuring equipment in use at airports around the world employs a variety of principles and differs in basic functional and technical characteristics. In this study, Airport Surface Friction Tester (ASFT) was used to measure the friction coefficient. The ASFT is a vehicle that employs a fifth wheel in the trunk, designed as per ASTM E1551, which measures the friction coefficient. Figure 6 shows the configuration of the ASFT. It comes with a self-watering system and a tank equipped in the vehicle’s rear seat area. The coefficient of friction is continuously recorded in the computer. In both runways (Bhopal and Imphal), the type of aircraft operated is A-321/B737800 whose Landing/Take-off speed is around 140–160 mph. However, as per FAA specifications, ASFT friction values are specified for 95 km/h speed. For the trial sections in Bhopal and Imphal, runway friction values were measured using ASFT at a speed of 95 km/h. Friction values were also measured on the existing runway before laying the trial sections. Three repetitions of ASFT tests were conducted on each stretch and the average friction of the three repetitions was taken as the friction coefficient of the stretch. The test results of ASFT are shown in Table 3. The field
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Fig. 5 Construction of trial section on Imphal runway, a aggregate stockpiling, b drum mix plant, c tack coat application, and d finished surface
Fig. 6 Airport surface friction tester (ASFT)
photograph during testing in Bhopal is shown in Fig. 7. From the friction test results, it was found that friction coefficients are significantly improved through the selected gradations in both Bhopal and Imphal. A friction value of 0.74 was targeted in the study for newly laid sections when measured by ASFT at the test speed of 95 km/h (ICAO-2002). In all laid test sections, friction values are greater than 0.74.
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Fig. 7 ASFT in progress at Bhopal
3 Laboratory Investigations 3.1 General The laboratory investigations were carried out primarily for assessing the volumetric parameters of DAC used for trial sections (Bhopal and Imphal). Evaluation of the quality of materials collected included mechanical and engineering characteristics. To evaluate the different characteristics of runway materials used, a number of relevant tests on aggregates, bitumen, and bituminous mixes were carried out. Loose mixes were collected from the truck immediately after loading from the mixing plant. The physical properties of the aggregates and binders used are given in Tables 4 and 5, respectively. Before compacting, the mixes were loosened by heating to a temperature of 155–160 °C. The mixes were compacted at a temperature of 135 °C which is the average compaction temperature considered for compacting the DAC layer in the field. The compaction temperatures of the binders determined in the laboratory based on equi-viscous conditions (MS-2, 2015) were 135–140 °C for the VG30 binder. Marshall Properties (Job mix formulae) for all three mixes are given in Table 6. The bulk density of compacted samples was measured using the ‘Core Lok’ facility and loose mix density was evaluated using ‘Rice Apparatus’. Table 5 Physical properties of binders used in the test sections
Property evaluated
VG30 Bhopal
Imphal
Penetration @ 25 °C, 100 g, 5 s, 0.1 mm
61
64
Softening point, °C
53
51
Specific gravity
1.03
1.04
Absolute viscosity @ 60 °C (poise)
2907
3025
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Table 6 Marshall Properties for mixes collected from field S. no.
1
Parameter
Property Specified value as per AAI specifications
Trial 1 Trial 2 Trial 1
Bhopal
Imphal
No. of compaction blows on each side of Marshall specimen
75
75
12 (min)
75
75
2
Marshall stability (kN)
15
15
13
3
Bitumen content (by weight of mix) –
5.6
5.6
5.7
4
Bulk density (g/cc)
–
2.49
2.44
2.37
5
Marshall flow (mm)
2.0–4.0
6
Marshall quotient (ratio of stability/ 2.0–5.0 flow)
3.2
3.5
3.5
3.86
4.2
3.7
7
Percent voids in mix (%)
3–5
4.69
4.7
4.4
8
Percent voids in mineral aggregates (%)
12–14
12.9
13.7
13.7
9
Percentage voids in mineral aggregates filled with bitumen (%)
65–75
70
66
68
10
Retained Marshall stability on immersion test
Not less than 75%
84
86
81
11
Tensile strength ratio
Not less than 80%
90
92
84
12
Laboratory friction (using British pendulum tester)
NA
106 (dry) 87 (wet)
107 (dry) 89 (wet)
–
3.2 Marshall Mix Design The Mix design was done for the DAC as per the Marshall method. Marshall Specimens were prepared by taking desired proportions of aggregates along with varying quantities of bitumen. For all sections, the specimens were prepared with 4.0, 4.5, 5.0, 5.5, and 6.0% bitumen content (by weight of Total mix). The average results of the Marshall tests (Job mix formula) conducted on a number of specimens prepared with different mixes (two from Bhopal and one from Imphal) are tabulated in Table 7.
3.3 Moisture Resistance In the laboratory, mixes were compacted to 75 blows with a Marshall Compactor. Indirect tensile strength (ITS) tests were performed on cylindrical specimens measuring 100 mm in diameter and 63.5 mm in height. The specimens were moistureconditioned in accordance with AASHTO T 283 (2006). The samples were placed in a vacuum container saturated for 5–10 min at 67 kPa. After reaching a saturation
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Table 7 Marshall Properties for laboratory mixes S. no.
1
Parameter
Property Specified value as per AAI specifications
Trial-1
Bhopal Trial-2
Trial-1
Imphal
No. of compaction blows on each side of Marshall specimen
75
75
75
75
12 (min)
2
Marshall stability (kN)
16
14
12.5
3
Bitumen content (by weight of mix) –
5.5
5.8
5.8
4
Bulk Density (g/cc)
–
2.480
2.439
2.365
5
Marshall flow (mm)
2.0–4.0
3.5
3.1
3.3
6
Marshall quotient (ratio of stability/ 2.0–5.0 flow)
4.6
4.5
3.4
7
Percent voids in mix (%)
4
4
4
8
Percent voids in mineral aggregates 12–14 (%)
3–5
13.4
13.9
13.8
9
Percentage voids in mineral aggregates filled with bitumen (%)
65 to 75
70
72
71
10
Retained Marshall stability on immersion test
Not less than 75%
85
82
79
11
Tensile strength ratio
Not less than 80%
88
91
82
level of 55–80%, the samples were placed in a hot water bath preserved at 60 ± 0.5 °C for 24 ± 1 h. Following that, the samples were maintained at 25 ± 0.5 °C for 2 h using a water bath. The Tensile Strength Ratio (TSR) values are given in Table 7.
4 General and Specific Recommendations Runway surface friction coefficient resulting in the skid resistance is the primary parameter in deciding the safety levels and is responsible for traffic accidents, especially in mud-on-surface and wet conditions. The texture of the surfacing, as imparted by the size and gradation of aggregates used, is the pivoting feature in deciding the friction offered/generated. Thus, it is obvious that while maintaining the strength and integrity of the surfacing, the required friction coefficient is also achieved while constructing the surface layer. A proper iterative exercise is required to set the gradation to achieve the objective, without losing the mix parameters including densityvoid requirements. It, therefore, becomes imminent that the recommended gradation band/envelop is kept intact and only readjustment/re-tuning is done to get a relatively open texture. It must be also ensured that aggregate structure is well achieved and maintained during construction and traffic operations. By a careful balancing consideration, the desired results can be achieved to a greater extent.
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Table 8 Study-based recommended aggregate gradation for DAC layer Sieve size (mm)
Percent passing Lab study*
FAA (2017)
19
100
100
13.2
95–100
79–99
9.5
78–82
68–88
4.75
52–58
48–68
2.36
42–45
33–53
1.18
30–32
20–40
0.6
23–25
14–30
0.3
18–20
9–21
0.15
10–12
6–16
0.075
5–6
3–6
In the present cases of Bhopal and Imphal runways, the laboratory and field trials have helped identify the gradation changes required to fulfill the objectives of enhancing friction coefficient while meeting the FAA standards. The laboratory and field trials by the modified gradation have exhibited that all the stipulated norms are met while enhancing the friction considerably. Based on the study, the gradation of aggregates as given in Table 8 is recommended for the surface layer of the runway. Though the suggested gradings are narrow-ranged, it is based on various trials at two airport sites viz., Imphal and Bhopal. However, a tolerance of a total amount of 5% on certain sieves is permitted. As the grading is suggestive of best results, it may be tried to be as close, however, it always should be within FAA grading and also near the midpoints, to the extent possible.
5 Limitation and Future Scope The aggregate gradation recommendations of the study are based on an investigation of limited trial sections. Further investigation on a large number of trial sections and also study performance characteristics of the asphalt mixture is recommended for future scope.
Development of High Friction Bituminous Surface Course for Aircraft …
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References 1. Hoerner TE, Smith KD (2002) High performance concrete pavement: pavement texturing and tyre-pavement noise. Federal Highway Administration, USA, Report No. FHWA-DTFH6101-P-00290 2. Kennedy CK, Young AE, Butler IC (1990) Measurement of skidding resistance and surface texture and the use of results in the United Kingdom. Surf Charact Roadways Int Res Technol Am Soc Test Mater Philadelphia, ASTM STP 1031:87–102 3. Hosking JR (1987) Relationship between skidding resistance and accident frequency: estimates based on seasonal variation. Transport and Road Research Laboratory (TRRL), Department of Transport, Crowthorne, U. K., Report No. RR 76 4. Flintsch GW, de Leon ´ E, McGhee KK, AI-Qadi IL (2003) Pavement surface macrotexture measurement and applications. Transport Res Rec 1860:168–77 5. Mahboob Kanafi M, Kuosmanen A, Pellinen TK, Tuononen AJ (2015) Macro-and micro texture evolution of road pavements and correlation with friction. Int J Pavement Eng 16:168–179 6. Kane M, Artamendi I, Scarpas T (2013) Long-term skid resistance of asphalt surfacings: correlation between Wehner-Schulze friction values and the mineralogical composition of the aggregates. Wear 303:235–243 7. Kogbara RB, Masad EA, Kassem E, Scarpas A, Anupam K (2016) A state-of-the-art review of parameters influencing measurement and modeling of skid resistance of asphalt pavements. Construct Build Mater 114:602–617 8. Vaiana R, Capiluppi GF, Gallelli V, Iuele T, Minani V (2012) Pavement surface performances evolution: an experimental application. Proc Soc Behav Sci 53:1149–1160 9. Widyatmoko I, Fergusson C, Wood J (2015) Friction characteristics of airfield asphalt concrete in service. Proc Inst Civil Eng Transp 168(2):132–138. Thomas Telford Ltd 10. Gallaway BM, Schiller RE, Rose JG (1971) The effects of rainfall intensity, pavement cross slope, surface texture, and drainage length on pavement water depths 11. Anderson DA, Huebner R, Reed JR, Warner J, Henry JJ (1998) Improved surface drainage of pavements 12. Horne WB, Tanner JA (1969) Joint NASA-British ministry of technology skid correlation study-results from American vehicles 13. Chou C-P, Chu H-J, Chen A-C (2020) Advanced runway groove identification. Measurement 152:107272 14. Lee M-H, Chou C-P, Li K-H (2009) Automatic measurement of runway grooving construction for pavement skid evaluation. Autom Constr 18(6):856–863 15. Ivan JN, Ravishanker N, Jackson E, Aronov B, Guo S (2012) A statistical analysis of the effect of wet-pavement friction on highway traffic safety. J Transport Saf Secur 4:116–136 16. Srirangam S, Anupam K, Scarpas A, Kasbergen C, Kane M (2014) Safety aspects of wet asphalt pavement surfaces through field and numerical modeling investigations. Transp Res Rec J Transp Res Board 37–51 17. Forster SW (1989) Pavement microtexture and its relation to skid resistance. J Transp Res Board Washington DC Transportation Research Record, No 1215, 151–164 18. Corley-Lay JB (1998) Friction and surface texture characterization of 14 pavement test sections in Greenville, North Carolina. Transp Res Record, 1639, Washington DC 155–161 19. Goodman SN, Hassan Y, El Halim AOA (2006) Preliminary estimation of asphalt pavement frictional properties from superpave gyratory specimens and mix parameters. In: CD-ROM Proceedings, 85th Annual meeting of transportation research board, Washington DC
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20. Balmer GG, Hegmon RR (1980) Recent developments in pavement texture research. J Transp Res Board Washington DC 788, 28–33 21. Noyce DA, Bahia HU, Yambo JM, Kim G (2005) Incorporating road safety into pavement management: maximizing asphalt pavement surface friction for road safety improvements. Midwest Regional University Transportation Center Traffic Operations and Safety (TOPS) Laboratory, Draft Literature Review and State Surveys 22. Khasawneh MA, Alsheyab MA (2020) Effect of nominal maximum aggregate size and aggregate gradation on the surface frictional properties of hot mix asphalt mixtures. Constr Build Mater 244:118355
Sustainability of Asphalt Rubber-Gap Pavements: A Comparative Environmental Impact Analysis Karunakar Koyyuru, K. M. Arun Sagar , and Veena Venudharan
Abstract The main objective of the study was to conduct a LCA of Asphalt RubberGap graded (AR-Gap) pavements and compare the environmental impacts of ARGap pavements with the conventional pavement. The scope of the study included the determination of Greenhouse Gas (GHG) emissions during the various stages of pavement construction, including raw material production, mixing, transportation, placing, and compaction. For this study, AR-Gap and conventional pavements are designed as per IRC:37-2018 guidelines using IITPAVE for three subgrade and three traffic conditions, totalling nine design combinations. The material quantities were calculated for all design combinations and respective GHG emissions were determined. The comparative analysis of the GHG emissions from AR-Gap and conventional pavements showcased that AR-Gap pavements produced lower level of emissions in comparison with the conventional pavement. Overall, it is anticipated that this study will provide a background on the life cycle analysis of AR-Gap pavements and their GHG emissions during the various stages of pavement construction. It is envisioned that this research study will set a strong venue for advancing the current state of the art pertaining to AR-Gap pavements and consideration of the same as a sustainable pavement alternative to conventional asphalt concrete pavements. Keywords Crumb rubber · Gap gradation · AR-gap mixture · Life cycle assessment · Greenhouse gases
K. Koyyuru · K. M. Arun Sagar · V. Venudharan (B) Indian Institute of Technology, Palakkad, Kerala 678623, India e-mail: [email protected] K. Koyyuru e-mail: [email protected] K. M. Arun Sagar e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_18
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1 Introduction Asphalt Rubber Gap graded (AR-Gap) mixture is a superior performing asphalt pavement mixture that is prepared as a blend of asphalt binder and rubber along with gap graded aggregate gradation. There is a wealth of literature that illustrates the superior performance of AR-Gap mixtures toward various pavement distresses including moisture damage, rutting, fracture, and fatigue cracking [1, 2]. The inclusion of crumb rubber in asphalt not only provides efficient use of scrap tires that helps keep the environment green but also improved the viscoelastic characteristics of the binder and thus aids in (a) reduction in reflective cracking in asphalt overlays, (b) reduction in maintenance costs, (c) resistance to fatigue cracking and rutting, (d) increased pavement life, and (e) decreased tire/pavement interaction noise levels [1]. Further, the gap-aggregate gradation in AR-Gap mixtures has successfully showcased an improved resistance toward pavement distresses in comparison with the conventional dense-aggregate gradation [3–5]. Though vast literature presents the enhanced performance of AR-Gap mixtures, there are studies that showcase demerits of AR-Gap mixtures including (i) increased cost of construction, (ii) higher construction temperatures, and (iii) difficulty in construction [6]. Therefore, it is deemed important to understand the environmental impact of AR-Gap mixtures as a pavement layer and to compare the overall benefit of utilizing AR-Gap pavements in place of conventional pavements. In this direction, life cycle assessment (LCA) on AR-Gap pavements is essential to understand the environmental impacts of AR-Gap pavements during its life cycle from procurement of raw materials to disposal/recycle stage. Note that the LCA method is developed to evaluate a product’s environmental impact across its full life cycle. The method’s purpose is to determine the environmental repercussions of the whole production chain. One of our society’s major issues in construction is sustainable infrastructure. The transportation network, particularly the pavement network, is critical for its long-term development. The pavement network is essential for transporting people and goods from one place to another safely and efficiently. An increase in traffic demand and adverse climatic conditions calls for superior performing pavements. Statistics shows that India ranks third in annual CO2 emission in the world in the year 2016 [7], which became about 3363.59 MtCO2 e in the year 2019 [8]. Further, it is noteworthy that pavement construction and maintenance also contribute significantly to massive energy consumption and greenhouse gas (GHG) emissions [9]. The enormity of these sustainability issues is expanding due to the growing number of pavement constructions globally and the massive increase in vehicle use. Pavement engineers must find a way to reduce environmental damage and greenhouse gas emissions and arrive at sustainable pavement engineering. Some persistent effort has been made to lessen the environmental consequences and greenhouse gas emissions from pavement networks, such as using a binder that blends crumb rubber from tire waste with asphalt without harming performance, Recycled Materials Components (RMCs) from industrial waste, can help
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reduce in greenhouse gas emissions also be cost-effective and using of Reclaimed Asphalt Pavements (RAP) and Recycled Concrete Aggregate (RCA). The LCA was created to evaluate the impact of a product’s GHG emissions on the environment throughout the course of its life cycle. This study aims to determine the total greenhouse gas emissions and environmental implications of asphalt rubber gap graded pavement (AR-Gap pavement), as well as to compare the greenhouse gas emissions to the results of conventional asphalt pavement, thereby identifying the pavement that creates less environmental impact during the construction stage. This aids decision-makers in industry, government, and other organizations to build a system or define a strategy by identifying the points in a life cycle where environmental performance can be enhanced. The primary objective of this study was to understand a life cycle assessment of AR-Gap pavements and compare the outcomes of the AR-Gap pavement with the conventional asphalt pavement. The scope of the study included (i) identifying the quantity of CO2 emissions from each step from raw material procurement to service toward traffic for AR-Gap and conventional pavements, (ii) designing of AR-Gap pavements for various subgrade and traffic conditions, (iii) determining the CO2 emissions for the designed pavements, (iv) comparing the CO2 emissions from AR-Gap pavements with the conventional pavements and evaluate the environmental impact due to the use of AR-Gap mixtures in pavement construction.
2 Literature Review Marianela Espinoza et al. estimated the carbon footprint of hot mix asphalt pavement as the focus of this project (HMA). The study considered the stages of production and building. The HMA layers’ production and construction stages resulted in a carbon footprint of 65.781 kg CO2 eq per lane kilometer. In this study, the production stage produced around 98 percent of the total GHGs, while the construction stage produced only 2% of the total GHGs. Aggregate production had about 6% of total GHGs, equivalent to the contribution of transportation (close to 6 percent) [10]. Ali Azhar Butt et al. determined that asphalt manufacture is a very energy-intensive operation. An investigative study to see if they have the potential to reduce energy consumption by lowering mixing temperatures was recommended. To reduce excessive energy use and fuel combustion emissions, it is preferable to have the quarry site, asphalt production plant, and building site all within a short distance of each other. It’s also a good idea to consume electricity that’s been generated efficiently [11]. Martina Irene Giani et al. calculated the environmental benefits of using recovered asphalt pavement and strategies for lowering production temperatures in the plant and reconstructing the pavement after it has been used for its whole life. All life cycle stages have been studied from the extraction of virgin materials through the end of life. This study’s findings demonstrate that the extraction and manufacture of virgin materials have higher life cycle consequences (up to 40% CO2 equivalent), owing to
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the presence of asphalt. During the manufacturing process, this crude oil derivative has a lot of negative consequences [12]. Irene Bartolozzi et al. studied AR hot mixes with improved structural and functional performance to reduce environmental impact significantly. This benefit is quantified by the findings of the investigation provided in this study. The environmental benefits of employing AR solutions instead of typical hot mixes for pavement repair are projected to be roughly one-third (33%) of total energy consumption and fewer greenhouse gas emissions. AR solutions outperform the original solution in terms of structural and functional performance. They may be able to handle more traffic than anticipated and have a longer estimated lifespan [13]. Saud A. Alfayez et al. added that crumb rubber to the asphalt binder can improve various binder qualities by lowering the asphalt binder’s temperature and susceptibility. Crumb rubber can improve pavement resistance to rutting and permanent deformation, minimize fatigue cracking, improve durability, reduce tire solid waste, and promote pavement sustainability by lowering energy consumption and natural resource consumption, as well as lowering maintenance and repair costs [14]. Paravita Sri Wulandari et al. Crumb rubber-modified asphalt used less asphalt than regular asphalt. The void ratio of the mixture will grow when the asphalt content is reduced, increasing the permeability of the mixture. The addition of crumb rubber to the asphalt resulted in a decrease in flow and improved stability [15].
3 GHG Emission Determination The first step in the direction of the research study was to determine the GHG emissions during the various activities during pavement construction. The different activities that come under pavement construction which result in GHG emissions include (a) Concrete mix production, (b) Plant and machinery for production, (c) Concrete mix transportation from plant to site, and (d) Asphalt concrete layer compaction. Therefore, in order to accomplish the life cycle assessment of AR-Gap pavements and to compare the results with conventional asphalt concrete pavements, GHG emissions from raw materials and mix production, transportation, and compaction were determined from previous literature. This research entails gathering information on GHG emissions from raw materials for each process, from extraction to production, placing, and compaction. All GHG emission calculations are based on a one-kilometer-long, 3.5-m-wide pavement section. The total CO2 equivalent is the unit used to indicate GHG emissions. Asphalt, a crude oil derivative, aggregates, crushed rock from a quarry, and crumb rubber from used tire waste are the primary elements in asphalt pavement and AR-gap pavement. The details of emissions during the production of these raw materials are shown in Table 1. Further, the GHG emissions from the remaining activities during pavement construction were determined and presented in [16].
Sustainability of Asphalt Rubber-Gap Pavements: A Comparative … Table 1 GHG emission details [17–19]
Sl. no.
Activities
219
Total CO2 eq/kg
Asphalt production 1
Crude oil extraction
0.313296
2
Refinery
0.025623
3
Heating
0.021000
4
Asphalt storage
0.009304
5
Transport
0.234883
6
Electricity
0.035998
Total
0.640104
Aggregate production 1
Fragmentation
0.000110
2
Loading and hauling
0.000194
3
Crushing
0.002630
4
Screening
0.000350
5
Storage
0.000681
Total
0.003965
Crumb rubber 1
Collecting
0.000076600
2
Transportation
0.000360000
3
Chopping/shredding
0.000919000
4
Screening
0.000000112
5
Devulcanization
0.000756000
6
Refining
0.000000571
7
Storage
0.000291000
8
Electricity
0.000681000
Total
0.003084283
4 Pavement Design: IRC 37:2018 The next step was to design the flexible pavement with an AR-Gap mixture and conventional asphalt concrete in order to carry out the life cycle assessment exercise. The pavement design was done in accordance with IRC:37-2018 [20] using IITPAVE software [21]. The pavement was designed for three traffic levels, namely 50, 100, and 150 msa, and three subgrade conditions with CBR 2, 5, and 10%. For the design calculations, the following design parameters were considered: . Subgrade: CBR 2, 5, and 10%. . Granular subbase (GSB) layer: Grading 1 as per Table 400-1 of MoRTH 2013 [22].
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. Wet mx macadam (WMM) layer: Grading as per Table 400-13 of MoRTH 2013 [22]. . Dense graded bituminous macadam (DBM) layer: VG30 bitumen and grading 2 as per Table 500-10 of MoRTH 2013 [22]. . Surface layer: bituminous concrete of grading 2 as per Table 500-17 of MoRTH 2013 was considered for asphalt pavement with a resilient modulus of 3000 MPa [22]. . Whereas a gap gradation along with crump rubber was used for AR-Gap graded pavement with a resilient modulus of 4500 MPa. For the various traffic and subgrade combinations, pavements were designed with AR-Gap and conventional dense-graded mix as surface courses with granular subbase. Thicknesses were determined using the trial and error approach, maintaining the critical strain slightly above the estimated strain from the IITPAVE software output by giving the inputs of Elastic modulus and Poisson’s ratio of the different layers of the pavement section. The layer thicknesses of the designed pavements are presented in Figs. 1 and 2. The figure shows that the pavement structures with AR-Gap mixture as surface course resulted in lesser thickness in comparison with the pavement structure with conventional asphalt concrete for all traffic and subgrade combinations. The reduction in overall thickness ranged from 3 to 10% with the substitution of conventional asphalt concrete with AR-Gap mixtures. This reduction in the overall pavement thickness will result in reduced material requirements, which will positively influence the life cycle analysis as explained in the below section.
Fig. 1 Dense-graded asphalt concrete pavement thicknesses
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Fig. 2 AR-Gap pavement thicknesses
5 Life Cycle Assessment The GHG emissions in terms of carbon dioxide equivalent (CO2 eq) were considered for analysis in the LCA tool. Therefore, the GHG emissions at different stages of pavement construction including Production, Plant and Machineries (P&M), Transportation, and Compaction were evaluated for all aforementioned pavement structures in order to assess the impact of these pavement structures on the environment. The cradle-to-gate assessment is carried out in this study. The quantity of the materials for each pavement layer was calculated as a pavement section of 3.5 m width and 1 km length. Table 2 presents the total GHG emissions from the construction of all eighteen pavement structures. From the table, it can be observed that the GHG emissions from the AR-Gap pavement construction are lesser in comparison with the conventional asphalt pavement. An overall reduction of approximately 10% in GHG emissions was observed with AR-Gap mix inclusion in the pavement structure. Further, it is interesting to note that since the material required for AR-Gap pavement is less in all cases, the GHG emissions from production are significantly reduced. In addition, the inclusion of crumb rubber resulted in lower asphalt requirements in the case of AR-Gap pavements which also resulted in lower GHG emissions from AR-Gap production. Similarly, with the reduction layer thicknesses and subsequent reduction in material requirements, the GHG emissions from the remaining activities of pavement construction were less for AR-Gap pavements in comparison with conventional dense-graded asphalt concrete pavement. Figure 3 presents the percent change in GHG emissions from conventional asphalt concrete pavement and AR-Gap pavement.
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Table 2 GHG emissions for various pavement structures CBR %
Traffic msa
Production (CO2 eq)
P&M (CO2 eq)
Compaction (CO2 eq)
Transportation (CO2 eq)
Total emissions (CO2 eq)
AR-Gap pavement 2
5
10
50
58,280.53
42,636.07
3064.35
36,960
140,940.967
100
64,032.87
52,822.27
3611.72
38,676
159,142.877
150
70,566.20
57,629.34
3704.09
44,286
176,185.641
50
47,522.23
39,289.29
2257.99
24,816
113,885.525
100
52,220.69
49,426.08
2712.99
26,400
130,759.770
150
55,387.69
54,729.59
3069.99
27,984
141,171.280
50
42,347.45
36,337.14
1808.62
20,064
100,557.222
100
47,677.55
48,119.85
2620.62
21,648
120,066.029
150
50,481.09
53,318.87
2620.62
22,936
129,256.589
3519.35
37,290
152,391.949
Dense-graded asphalt concrete pavement 2
5
10
50
64,384.08
47,198.50
100
70,991.05
60,198.15
3611.72
39,864
174,664.935
150
72,444.86
60,616.14
3611.72
41,382
178,054.734
50
53,480.53
44,063.55
2712.99
26,004
126,261.086
100
59,178.87
56,801.96
3069.99
27,588
146,638.829
150
60,775.44
60,961.01
3069.99
27,786
152,592.451
50
45,432.19
38,337.03
1808.62
20,064
106,641.848
100
54,635.72
55,495.73
2620.62
22,836
135,588.087
150
56,232.29
59,654.79
2620.62
23,100
141,607.710
Fig. 3 Percentage change in GHG emissions
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It can be observed from Fig. 3 that among the designed pavements, the GHG emissions increased with an increase in traffic and a reduction in subgrade strength. Further, the pavement for 2% CBR and traffic of 150 MSA resulted in maximum emissions, and the pavement for 10% CBR and traffic of 50 MSA scenario resulted in minimum emissions. The maximum reduction in GHG emissions with AR-Gap inclusion was observed for a subgrade-traffic combination of 10% CBR and 100 MSA with a magnitude of 13%. Overall, it was concluded that AR-Gap pavements would not only provide superior performing long-life pavements but also help in reducing GHG emissions, resulting in a sustainable alternative in place of conventional densegraded asphalt concrete pavement.
6 Conclusions and Future Scope The objective of this study was to understand a life cycle assessment of AR-Gap pavements and compare the outcomes of the AR-gap pavement with the conventional asphalt pavement. The conclusions drawn from the study are as follows: . Based on the pavement design carried out as per IRC 37:2018, it can be concluded that the AR-Gap pavement requires lesser layer thicknesses in comparison with the conventional pavement for all subgrade-traffic combinations. An overall thickness reduction of nearly 3–10% was observed with the inclusion AR-Gap mixture as a surface layer. . The GHG emissions for both pavement types increased with a decrease in subgrade strength and with an increase in traffic. . The GHG emissions from all activities under consideration, namely production; plant and machinery; transportation; and compaction, were lower for AR-Gap pavements. This trend can be attributed to the reduced thickness of the AR-Gap pavement structures in comparison to the conventional pavement. . In the case of all subgrade-traffic combinations considered in the study, the ARGap pavements showcased lower GHG emissions in comparison with the conventional pavement. The reduction in GHG emissions was observed to be higher for pavements designed to accommodate higher traffic. The study shows that AR-Gap graded pavements create less impact toward the environment during various stages of construction when compared to conventional bituminous pavement. The AR-Gap graded pavements use less materials, fuel, and energy consumption and release less GHG emissions than the latter. The fact that the incorporation of waste tires in pavement construction reduces the additional burden toward waste disposal. Also, the dominant pavement has the ability to cater to more traffic than conventional ones.
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The future scope of the study includes the following: (i) LCA of AR-Gap pavements incorporating its service life should be considered for a better understanding of the mix’s superiority in being a sustainable pavement alternative, (ii) Life cycle cost analysis should be performed in order to identify the economic impact of AR-Gap pavements, and (iii) LCA of AR-Gap pavements should be carried out under various climatic conditions. Overall, it is anticipated that this study will provide a background on the life cycle analysis of AR-Gap pavements and their GHG emissions during the various stages of pavement construction. It is envisioned that this research study will set a strong venue for advancing the current state of the art pertaining to AR-Gap pavements and consideration of the same as a sustainable pavement alternative to conventional asphalt concrete pavements.
References 1. Venudharan V, Biligiri KP, Sousa JB, Way GB (2017) Asphalt-rubber gap-graded mixture design practices: a state-of-the-art research review and future perspective. Road Mater Pavement Des 18(3):730–752 2. Venudharan V, Biligiri KP (2019) A novel design toolkit to assess asphalt-rubber gap-graded mixture performance: target properties and parametric relationships. Constr Build Mater 219:69–80 3. Venudharan V, Biligiri KP (2020) Conceptualization of three-stage fatigue failure in asphaltrubber gap-graded mixtures using dynamic semi-circular bending test. Transp Res Rec 2674(7):44–55 4. Venudharan V, Biligiri KP (2020) Rutting performance of asphalt-rubber gap-graded mixtures: evaluation through statistical and reliability approaches. Road Mater Pavement Des 21(sup1):S2–S18 5. Venudharan V, Biligiri KP (2019) Investigation of cracking performance of asphalt-rubber gap-graded mixtures: statistical overview on materials’ interface. J Test Eval 47(5):3336–3354 6. Kaloush KE (2014) Asphalt rubber: performance tests and pavement design issues. Constr Build Mater 67:258–264 7. Sreedhar S, Jichkar P, Biligiri KP (2016) Investigation of carbon footprints of highway construction materials in India. Transp Res Proc 17:291–300 8. Climate Watch (2019) Climate watch historical country greenhouse gas emissions data. World Resources Institute. https://www.climatewatchdata.org/ghg-emissions?end_year=2019&start_ year=1990. Accessed 07 July 2022 9. Zhongming Z, Linong L, Xiaona Y, Wangqiang Z, Wei L (2020) Decarbonising urban mobility with land use and transport policies. OECD Library 10. Espinoza M, Noelia C, Rebekah Y, Ozer H, Aguiar-Moya JP, Baldi A, Loría-Salazar LG, AlQadi IL (2019) Carbon footprint estimation in road construction: La Abundancia-Florencia case study. Sustainability 8(11):2276 11. Butt AA. Life cycle assessment of asphalt pavements, SBN 978-91-85539-96-3 12. Giani MI, Dotelli G, Brandini N, Zampori L (2015) Comparative life cycle assessment of asphalt pavements using reclaimed asphalt. Resour Conserv Recycl 104:224–238 13. Bartolozzi I, Rizzi F, Borghini A, Frey M (2013) Life cycle assessment of a rubberized asphalt road in Lamia, Greece. Fresenius Environ Bull 22(7):2104–2110 14. Alfayez SA, Suleiman AR, Nehdi ML. Recycling tire rubber in asphalt pavements. Sustainability 12:09076
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15. Wulandri PS, Tjandra D (2017) Use of crumb rubber as an additive in the asphalt concrete mixture. Proc Eng 171:1384–1389 16. Karunakar K (2021) Life cycle assessment of AR-gap pavement. B.Tech Project Report, IIT Palakkad 17. Blaauw S, Maina J, Grobler L (2020) Life cycle inventory of bitumen in South Africa. Traffic Eng 2:100019 18. Korre A, Durucan A (2009) Life cycle assessment of aggregates. Waste Resources Action Programme EVA 025 19. Bressi S, Santos J, Oreškovi´c M, Losa M (2019) A comparative environmental impact analysis of asphaltt mixtures comtaining crumb rubber and reclaimed asphalt pavement using life cycle assessment. Int J Pavement Eng 22 20. IRC 37 (2018) Guidelines for the design of flexible pavements. Indian Roads Congress, New Delhi 21. IITPAVE Software, IIT Kharaghpur 22. Ministry of Road Transport & Highways (MORTH) (2013) Specification for road and bridge works, 5th edn. Indian Roads Congress, New Delhi
Design and Analysis of Flexible Pavement Using Brick Aggregate Using Finite Element Method Ashish Kumar Singh, Khumber Debarma, and Partha Pratim Sarkar
Abstract There is a severe scarcity of stone aggregates in India’s north-eastern region. Therefore, to minimize the overall thickness of the pavement and to reduce the consumption of stone aggregate, stabilization of the subbase and subgrade may be carried out. In this study, commercially available Vinyl Acrylic Copolymer (K31APS) was used as a soil stabilizer with different percentages of Portland cement (0, 1, 2, and 3%) to assess the utilization of soil, available locally, along with overburnt brick aggregates (OBBA) in subgrade and subbase layers. Modified Proctor test and CBR test were carried out at different proportions of soil and brick aggregates and resilient modulus values were calculated. Laboratory results show that Vinyl acrylic copolymer (K31-APS) enhances the strength of the blended mix nearly by 200%. This study also includes the development of a 3-D FEM for flexible pavements using ABAQUS. The 3-D brick element (C3D8R) in the ABAQUS program was used to simulate various 3-D models, and surface deformation, horizontal tensile strain, and vertical compressive strain corresponding to stabilized and unstabilized layers were obtained. Keywords Overburnt brick aggregate (OBBA) · Vinyl acrylic copolymer (K31-APS) · ABAQUS
A. K. Singh (B) · K. Debarma · P. P. Sarkar Department of Civil Engineering, National Institute of Technology, Agartala 799046, India e-mail: [email protected] K. Debarma e-mail: [email protected] P. P. Sarkar e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_19
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1 Introduction Pavement structures are designed to support and distribute loads caused by vehicle loading to the subgrade soil safely. The distribution of stresses imposed on the pavement surface by traffic loading and their reduction at subgrade is the primary structural function of a granular subbase layer. Otherwise, large amounts of permanent deformation caused by overstressing loose granular material may accumulate, resulting in unsustainable levels of resilient pavement deflections under moving or static wheel loads. In India’s north-eastern regions, locally produced, low-quality natural aggregates may lack the strength and hardness to bear loads, causing them to distort excessively. Stabilizing subgrade soil and subbase allows these regions to rely less on importing expensive high-quality aggregate by utilizing local resources. Polymer emulsions have been used for soil stabilization since the late 1960s [1]. Polymer emulsions/ dispersion/latexes are made up of very small polymer particles (0.05–5 μm in diameter) and are mainly made through emulsion polymerization dispersed in water [2]. Polymer dispersion/emulsions/latexes are copolymer structures made up of two or many distinct monomers, with total solid particles ranging from 40 to 50% by mass [2]. Due to their cheaper costs, ease of handling, modification in the compositions, and environmental benefits, polymer emulsions are increasingly replacing traditional soil stabilizers in soil stabilization [3]. To further improve the engineering properties of natural soils, Cement is commonly added to the polymer. Micro crack propagation is reduced in the polymercement matrix, which is common in soils stabilized with cement [4]. The polymercement matrix significantly improves the tensile and flexural strength, as well as fracture toughness, of the stabilized soils [4]. Using polymer latexes/emulsion with cement is often economical, as both are than bitumen [5]. Three-dimensional FE analysis tools are nowadays accounted as the finest cheaperapproach to provide solutions to certain fundamental questions about the performance of the pavement. Duncan [6] used the FEM for the first time to analyze flexible pavements. Later, many software-based analyses using this finite element method were prepared. ABAQUS is a commercial finite element modeling application. The ABAQUS is an engineering analysis software program developed to model the physical reaction of structures and solid bodies to loads, contact, impact, temperature, and other environmental variables all over the world [7]. In depth study of several software associated with pavement analysis, by Chen [8] concludes that results from ABAQUS were analogous to those obtained from other software. Using 3-D dynamic analysis in ABAQUS, Zaghloul and White [9] simulated the pavement deflections for flexible pavements under FWD loads. Results demonstrate that their model could simulate truckloads and accurate deformation predictions could be made. Hence, several pavement issues that the more basic multi-layer elastic theory was unable to explain have been successfully simulated using Finite Element (FE) techniques. This study investigated the 3-D FEM of flexible pavement using the ABAQUS program in which assembly of different layers (asphalt, base, subbase, and subgrade
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layer), interaction between these layers, static analysis step, loading, and appropriate boundary conditions were determined. Finally, stress, strain, and surface deformation were calculated for each model.
2 Study Objective The major objective of this study is (a) To find the feasibility of the strength of subgrade and subbase layers using Vinyl Acrylic Copolymer, Portland cement, and locally available overburnt brick aggregate (OBBA) and (b) To find the surface deformation, horizontal tensile strain, and vertical compressive strain, at the bottom of the surface layer and the top of the subgrade layer respectively, in different 3-D flexible pavement models created using finite element software ABAQUS.
3 Analysis of Experimental Results 3.1 Vinyl Acrylic Copolymer In this study, we have used a polymer-based stabilizer K31-APS (Vinyl Acrylic Copolymer). K31-APS is a stabilizer used for soil stabilization, subbase stabilization, erosion control, and dust control. It consists primarily of Polyethylene glycol octyl phenyl ether and Polyethylene glycol octyl phenoxy ether. K31-APS is actually tiny polymer particles which are suspended in water (emulsified). The leftover polymer particles combine to form a continuous layer of polymer surrounding the soil or aggregates when the water evaporates during the curing process. It is a blue-white color liquid having pH in the range of 4.0–6.0. The density of K31-APS is generally in the range of 1.066–1.090 gm/cm3 . In this research, a mixing ratio of 01:06 was adopted, i.e. 1 part of K31 APS and 6 parts of water corresponding to the OMC of blended mixes.
3.2 Soil Important properties of some of the locally available soil are shown in Table 1.
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Table 1 Soil properties
Serial no.
Properties
1
Specific gravity, G
Value 2.63
2
Maximum dry density, MDD (gm/cm3 )
1.94
3
Optimum moisture content, OMC (%)
13.4
4
Liquid limit, LL (%)
21.06
5
Plastic limit, PL (%)
12.79
6
Plasticity index, IP (%)
8.27
3.3 Overburnt Brick Aggregate The overburnt brick aggregates tested in this study were collected from a local brick manufacturer. Due to a lack of control over the production process, these overburnt bricks are a type of waste brick that is formed accidentally during the fabrication of good-quality red bricks. The use of such bricks in a soil aggregate mix is investigated in this study. The aggregate gradation was determined according to MORD 2014 table no. 400.2-B [10], as shown in Table 2. The qualities of the OBBA used in this study were evaluated using a set of standard tests. The test results are listed in Table 3. Table 2 Gradation of OBBA Sieve size Percent by mass passing is sieve grading designation (nominal size) Subbase Course Specification limit (MORD 2014, table no. 400.2-B) Selected gradation of OBBA 40 mm
100
100
20 mm
80–100
95
10 mm
55–80
70
4.75 mm
40–60
47
2.36 mm
30–50
35
600 μm
15–30
22
75 μm
5–15
10
Table 3 Properties of OBBA Types of tests
Values of OBBA (%)
Required values as per MORD 2014 specification
Aggregate impact value (IS:2386 Part IV)
45.43
Less than 30%
Flakiness index (IS:2386 Part I)
42.45
Less than 25%
Water absorption
10.97
Less than 10%
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The values obtained after testing overburnt brick aggregates, which are readily available in Tripura, fall short of the MORD criteria. It should be noted that the criteria are based on the results of natural stone aggregates with substantially higher strengths than these OBBA. The difficulty however lies in utilizing these aggregates as part of a subbase course while maintaining the appropriate strength as specified in the MORD 2014 [10] specification.
3.4 Modified Proctor Test The overburnt aggregate utilized in this study was sieved into various sizes and then reconstituted to achieve the desired gradation. The influence of stabilizer, OBBA, and Portland cement content on the MDD and OMC of various soil aggregate blended mixes was investigated as per IS-2720 (Part 8) [11]. Table 4 presents the findings. As shown in Table 4, with the increase in OBBA percentage, MDD decreases and OMC increases at the same time.
3.5 California Bearing Ratio and Resilient Modulus Blended Soil-aggregate mixes were examined to assess the effects of OBBA, Vinyl Acrylic Copolymer, and Portland cement on the mixture strength. The samples were compacted and kept in soaked condition for 96 h as per IS 2720 (Part 16) [12]. The modulus of elasticity of unbound pavement materials is generally described in terms of the modulus of resilience (MRS ). In pavement systems, MRS is a direct indicator of stiffness for unbound materials and is calculated as the ratio of applied cyclic stress to recoverable (elastic) strain after many cycles of repetitive loading. Around the world, many correlations between MR and other soil parameters are used [13]. To analyze the stiffness of the sample in this study, the resilient modulus has been calculated using Eq. (1) as per IRC 37 2018 [14]. The California bearing ratio values and corresponding modulus of resilience values henceforth are shown in Table 4. M R S = 17.6 ∗ (C B R)0.64 f or C B R > 5 % where MRS Modulus of resilience of subgrade soil (in MPa). CBR California bearing ratio of subgrade soil (%).
(1)
100
100
100
100
50
25
25
25
25
0
A-0
A-1
A-2
A-3
A-4
B-0
B-1
B-2
B-3
B-4
C-0
C-1
C-2
C-3
C-4
D-0
D-1
D-2
D-3
D-4
E-0
SG-1
SG-2
SB-1
SB-2
SB-3
SG-3
SB-4
SB-5
SB-6
SB-7
SB-8
SB-9
SB-10
SB-11
SB-12
SB-13
SB-14
SB-15
SB-16
SB-17
SB-18
25
50
50
50
50
75
75
75
75
75
100
Soil (%)
Sample No.
Model name
100
75
75
75
75
75
50
50
50
50
50
25
25
25
25
25
0
0
0
0
0
OBBA (%)
0
3
2
1
0
0
3
2
1
0
0
3
2
1
0
0
3
2
1
0
0
Portland cement (%)
Table 4 MDD, OMC, California bearing ratio, and resilient modulus
00:00
01:06
01:06
01:06
01:06
00:00
01:06
01:06
01:06
01:06
00:00
01:06
01:06
01:06
01:06
0
01:06
01:06
01:06
01:06
0
K 31
1.56
1.72
1.73
1.74
1.75
1.75
1.78
1.8
1.81
1.82
1.82
1.85
1.86
1.87
1.91
1.91
1.89
1.9
1.94
1.94
1.94
MDD (g/cm3 )
11.2
12
11.6
11.2
11
11
12.2
11.8
11.4
11.1
11.1
12.5
11.7
11.5
10.1
10.1
14.7
14
14
13.4
13.4
OMC (%)
68.1
203.1
200.98
177.67
106.54
64.17
132.12
108.96
103.97
66.74
23.9
75.1
73.55
56.75
24.06
16.04
50.4
40.86
24.51
13.17
6.8
CBR (%)
262.26
527.77
524.24
484.47
349.24
252.47
400.80
354.29
343.82
258.89
134.18
279.20
275.50
233.37
134.75
103.95
216.31
189.12
136.36
91.63
60.02
MRS (MPa)
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4 Features of Finite Element Model In this study, as per IRC:SP-72-2015 [15], for a traffic volume of 1.5 msa to 2 msa and subgrade CBR value of 5–6, four layers of pavement were considered: surface, base, subbase, and subgrade. The layers of the pavement are represented as volumes (3-D model), as shown in Fig. 1. The thickness of the asphalt layer is 50 mm, the base layer is 225 mm thick, subbase layer is 200 mm thick, and subgrade is 300 mm thick. Model dimensions (5000 × 4000 × 775 mm) were chosen to minimize errors of edge effect while keeping element sizes within permissible limits.
4.1 Material Characterization Table 5 summarizes the properties of the materials used in this study. These properties pertain to the program’s input specifications. The modulus of elasticity (E), Poisson’s ratio (v), and density are the three parameters which are being used. Since Poisson’s ratio has a negligible effect on pavement’s responses [16], choosing a fair value rather than determining it from an actual laboratory test is common.
4.2 Element Types and Mesh Size In ABAQUS, all of the model’s components have been modeled using eight-node continuum 3-D brick element (C3D8R) with lower order numerical integration.
Fig. 1 Geometry of 3-D model of the Pavement layers by ABAQUS program
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Layers
Model name Resilient modulus, MRS (MPa)
Poisson’s ratio (ν)
Asphalt layer
Reference
700
0.35
Base layer
Reference
168
0.35
Subbase layer Subbase layer
Reference
168
0.35
SB-1
136.36
0.25
SB-2
189.12
0.25
SB-3
216.31
0.25
SB-4
134.75
0.35
SB-5
233.37
0.25
SB-6
275.5
0.25
SB-7
279.2
0.25
SB-8
134.18
0.35
SB-9
258.89
0.35
SB-10
343.82
0.25
SB-11
354.29
0.25
SB-12
400.8
0.25
SB-13
252.47
0.35
SB-14
349.24
0.35
SB-15
484.47
0.25
SB-16
524.24
0.25
SB-17
527.77
0.25
SB-18
262.26
0.35
Reference
55
0.35
SG-1 SG-2 SG-3
60.02 91.63 103.95
0.35 0.35 0.35
Subgrade layer
*Reference (IRC:SP-72-2015 pavement catalogue), Subbase (SB), Subgrade (SG)
This element can represent large deformation, geometric nonlinearities, and material nonlinearities. At each node, the solid element (C3D8R) has 3 degrees of freedom: changes in the dimensions x, y, and z. The solid element (C3D8R) is a first-order (linear) element with no rotational degrees of freedom. To maintain the continuity of nodes between successive levels, all layers are simulated with the same geometry. The stresses and displacement gradients are stronger around the wheel loads, henceforth more elements are used. Meshes based on hexahedrons with eight nodes are chosen, and the mesh size is optimized to achieve a compromise between calculation speed and stability.
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Fig. 2 Finite element mesh of the model assembly
To identify the appropriate mesh size, a series of FEA with reducing element size is performed. At the interface between layers, where stress and strain gradients are larger, fine mesh is created near the loading zone along the path of the wheel. In the vertical and horizontal directions, a moderately coarse mesh is employed in the areas far away from the loading zone. The nodes and elements used in the mesh are 98,391 and 57,132 in number, respectively. The model has a total of 205,749 variables. The mesh size and element types are shown in Fig. 2.
4.3 Techniques for Modeling Interactions The Interaction module allows limiting the degrees of freedom between model regions. One can combine two regions via interaction. The use of ABAQUS to generate contact interaction between model parts necessitates the definition of interaction surfaces. ABAQUS/Standard offers a number of different contact compositions. The contact discretization, tracking technique, and designation of “master” as well as “slave” roles to the contact surfaces are all used in each formulation. The pavement layers interacting with one another are modeled by assigning the contact surfaces as “master” and “slave”. Tie contact was given because interaction qualities between two adjacent layers were considered to be perfectly bonded.
4.4 Boundary Conditions In finite element analysis boundary conditions have a significant impact on pavement responses since they directly affect model accuracy [17]. To imitate real-world boundary conditions, the boundary conditions were chosen. The subgrade’s bottom
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surface is considered as fixed. This means, at the subgrade bottom, nodes cannot move in horizontal or vertical directions, and the boundary nodes along the pavement edges were restricted in the horizontal direction, but could move vertically.
4.5 Loading Condition Pavement modeling and simulation need the determination of tire contact area and stress. According to Hadi [18], tire is more of a rectangular shape than circular, with two semicircles and a rectangle making up the entire area of the tire. In this study, a standard axle load of 80 KN is considered with dual wheels on both sides. For a single axle load, each tire carries a 20 KN load with a 0.56 MPa uniform tire pressure [14]. For evaluation of stress, strain, and deformation and for easy computations, the tire’s contact area is calculated using axle load assuming that the rigid single tire is a rectangle having dimensions 228 mm × 157 mm.
5 Results In total, 22 different pavement models were studied with different subbase and subgrade material properties. Surface deformation, vertical compressive strain, and horizontal tensile strain, at the top of the subgrade layer and at the bottom of the surface layer respectively were evaluated utilizing the ABAQUS model. The surface deformation of the reference model is shown in Fig. 3 in ABAQUS. Figures 4, 5, and 6 show surface deformation, vertical compressive strain at the subgrade’s top, and horizontal tensile strain at the base of the surface layer for different subbase models, respectively. Figures 7, 8, and 9 show the same for different subgrade models, respectively. As shown in Fig. 4, obtained surface deformation value corresponding to the reference model was 0.5221 mm which got decreased up to 0.4652 mm corresponding to the SB-17 model. Similarly, the value of compressive strain in the vertical direction at the top of the subgrade decreased from 0.0004579 (reference model) to 0.0003703 (SB-17 model) as the percentage of OBBA, Portland cement, and K31-APS increased in the subbase layer (Fig. 5), whereas the tensile strain in the horizontal direction at the base of the surface layer increased from 0.0004396 to 0.0004562 corresponding to the reference and SB-17 model, respectively (Fig. 6). As shown in Figs. 7, 8, and 9, the surface deformation value decreased from 0.5221 mm to 0.4905 mm, vertical compressive strain got reduced from 0.0004579 to 0.0003047, whereas the horizontal tensile strain increased from 0.0004396 to 0.0004486 corresponding to reference and SG-3 model, respectively.
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Fig. 3 Surface deformation of reference model
Fig. 4 Surface deformation of different subbase models
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Fig. 5 Vertical compressive Strain at the top of Subgrade Layer of different subbase models
Fig. 6 Horizontal Tensile strain at the base of the Surface Layer of different
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Fig. 7 Surface deformation of different subgrade models
Fig. 8 Vertical Compressive Strain at the top of the Subgrade Layers of different Subgrade models
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Fig. 9 Horizontal Tensile strain at the base of the Surface Layer of different Subgrade models
6 Conclusions This research is carried out to determine the effect of Overburnt Brick Aggregate, Vinyl Acrylic Copolymer, and Portland cement on the strength of the subbase and subgrade layer. Based on the experimental and analytical results, the following conclusions are summarized: 1. Adding Portland cement decreases MDD, whereas OMC of the blended mix increases. 2. Vinyl acrylic copolymer (K31-APS) enhances the strength of the blended mix nearly by 200%. 3. Blended mix of 75% soil and 25% OBBA when used as a subgrade material shows a reduction of 6.05% in surface deformation and 33.46% in vertical compressive strain at the top of the subgrade compared to the conventional layer of subgrade. 4. The highest reduction in surface deformation of 10.9% and vertical compressive strain at the subgrade’s top of 19.13% was observed corresponding to the blended mix of 25% soil and 75% OBBA stabilized with K31-APS and 3% Portland cement when used as a subbase material than conventional subbase layer. 5. It was observed that when soil-aggregate mix was used as the subbase and subgrade material with a high percentage of OBBA and Portland cement content, vertical compressive strain at the top of the subgrade as well as deformation at the surface decrease, whereas horizontal tensile strain at the base of surface layer increases. 6. Therefore, the modified locally available material layer when properly compacted and strengthened should be capable of carrying rural traffic. Furthermore, under the same conditions of low-volume traffic, the cost is predicted to be lower than with a standard flexible pavement layer. However, more research into the abovementioned material compositions is needed to better understand the material’s behavior under various adverse loading as well as climate conditions.
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Acknowledgements The authors gratefully acknowledge the Govt. of India, Department of Science & Technology for financial support through the project “Mitigating the scarcity of stone aggregates in pavement construction using locally available materials & stabilization”, Grant No: SP/YO/555/2018(C).
References 1. Fungaroli AA, Prager SR (1969) Evaluation of some acrylic polymers as soil stabilizers. Ind Eng Chem Prod Res Dev 8(4):450–453 2. Ohama Y (1998) Polymer-based admixtures. Cement Concr Compos 20(2–3):189–212 3. Siddiqi RA (1978) Cost, effectiveness and utility of polymer soil stabilizers. Oklahoma State University 4. Walters DG (1988) Latex hydraulic cement additives. No 1204 5. Rodway B (2001) Polymer stabilisation of clayey gravels. In: 20th ARRB conference 6. Duncan JM, Monismith CL, Wilson EL (1968) Finite element analysis of pavements. Highway Res Rec 228(18–33):157 7. Hibbitt D, Karlsson B, Sorensen EP (2009) ABAQUS user’s manual, version 6.9. Hibbitt, Karlson, Sorensen Inc, Rhode Island 8. Chen DH, Zaman M, Laguros J, Soltani A (1995) Assessment of computer programs for analysis of flexible pavement structure. Transp Res Rec 1482(137):123–133 9. Zaghloul SM, White T (1993) Use of a three-dimensional, dynamic finite element program for analysis of flexible pavement. Transp Res Record (1388) 10. MORD: Specification for Rural Roads (2014) 11. IS: 2720 (Part 8) (1983) Determination of water content-dry density relation using heavy compaction 12. IS: 2720 (Part 16) “Laboratory Determination of CBR.” (1987) 13. Maslehuddin M et al (2003) Comparison of properties of steel slag and crushed limestone aggregate concretes. Constr Build Mater 17(2):105–112 14. IRC: 37 (2018) Guidelines for the design of flexible pavements 15. IRC: SP-72 (2015) Guidelines for the design of flexible pavements for low volume roads 16. Huang YH (193) Pavement analysis and design 17. Bayat A, Knight MA (2010) Investigation of flexible pavement structural response for the Centre for Pavement and Transportation Technology (CPATT) test road. No 10-3646 18. Hadi MNS, Bodhinayake BC (2003) Non-linear finite element analysis of flexible pavements. Adv Eng Soft 34(11–12):657–662
Utilization of Lime Stabilized Pond Ash and Sand Mix Using Nanomaterials for the Subbase Course of Industrial Pavements Abhishek Roy, Aditya Shankar Ghosh, and Tapas Kumar Roy
Abstract This paper investigates the strength and durability characteristics of nanomaterial stabilized sand–pond ash–lime mix. This experimental program determined the physical properties and chemical composition of the reagents like sand, lime, pond ash, and nanomaterials (Terrasil and Zycobond). Various geotechnical tests like modified CBR, UCS, Triaxial strength test, and slake durability test are conducted on the nanomaterial stabilized samples in various dosages (Terrasil:Zycobond:Water = 1:1:150; 1:1:200; 1:1:250, 1:1:300, 1:1:350, 1:1:400). The results obtained showed that adding nanomaterial solution in the ratio of 1:1:300 provided CBR of 79%, UCS of 1.96Mpa, along with cohesion of 40.02 kg/cm2 and an angle of internal friction of 53°. The slake durability measured by Gamble’s slake durability classification classified the material to be of high to very high durability. The elastic modulus of the optimum mix has been determined using a Light Falling Weight Deflectometer, and subsequently, the safe pavement depth is analysed using KENPAVE. Therefore, this study shows how nanotechnology can be used as a light in the dark for modifying the geotechnical properties of non-conventional granular materials like pond ash. Keywords Pond ash · Nanomaterial · CBR · UCS · LFWD · KENPAVE
A. Roy (B) · A. S. Ghosh · T. K. Roy Department of Civil Engineering, Indian Institute of Engineering Science and Technology, Shibpur, India e-mail: [email protected] A. S. Ghosh e-mail: [email protected] T. K. Roy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_20
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1 Introduction Industrial or High Volume Roads (HVR) provide connectivity to industrial and commercial business locations, thereby escalating the overall nation’s economic growth. HVR contributes over 30% of the country’s total road network [1, 2]. However, researchers have expressed deep concern regarding its subbase failure and lack of durability [2, 3]. MoRTH has constructed 12,205 km of NH in FY 2020– 21 [4]. Extensive conventional construction materials must be used with the target of 11,000 km of roadway to be constructed in FY 2021-22. However, emphasis is laid on the effective utilization of Non-Conventional Granular Materials (NCGM) like Pond Ash (PA) for pavement foundation construction [5] due to the scarcity of conventional materials in large quantities. 235.46 million tonnes of Coal Combustion Ash (CCA) has been generated by India from 2019 to 2021. Only 78.69% has been utilized, of which 9% is used for road construction [6, 7]. The remaining ash is disposed of on 65,000 acres of land, resulting in the underutilization of valuable land, pollution, and human health hazards in the surrounding areas [7, 8]. Effective utilization of this stored industrial waste is the need of the hour. Researchers have obtained ways of partially substituting the Conventional Granular Material (CGM) with NCGM and stabilizing it with Nanomaterials (NM) to put it to effective use for pavement foundation construction [9, 10]. NM has one or more internal structure dimensions of less than 100 nm [11]. Researchers discovered that incorporating NM into granular soils increases their UCS [12, 13]. 3% NM and 5% lime effectively improve the soil bearing capacity and make it efficient for subbase material in road construction [9]. The literature review shows that adding NM as a stabilizer is an excellent alternative to be used in compacted subbase in HVR.
2 Literature Review The investigators obtained relevant results for utilizing PA as an alternate foundation layer material owing to its pozzolanic properties imparting high bearing strength [6, 12, 14]. They have also found its effective use as a road embankment material owing to its cohesiveness [2]. However, researchers also concluded that untreated PA used in construction showed issues like low compacted density, lack of cohesion, and durability along with subsequent erodibility [15]. Furthermore, PA treated with cement and lime could provide weathering action insulation, but it lost strength and efficiency over time due to moisture ingression [13, 15, 16]. Working on this aspect, the investigators have found improved resistance to the permanent deformation of pavement subbase using PA on utilizing the NM, which consists of a Si–O–Si bond [17]. This not only resists the percolation of water inside the subbase but also improves the
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interparticle binding, improving rutting resistance, fatigue resistance, and permanent deformation [15, 17]. Therefore, nanotechnology can be used as a guiding light that can be applied as a perfect engineering solution for stabilizing PA substituted mix that can be utilized in pavement subbase construction [3, 18]. With reference to the shortcomings mentioned above, this paper determines the physical and chemical properties of PA and NM. It further determines the optimum concentration of NM in the Sand–Pond ash–Lime (SPL) mix to determine its durability. Finally, the material design has been validated by KENPAVE.
3 Materials The materials used for this study have been explained in detail as follows.
3.1 Pond Ash The PA samples were collected from KTPS, Ash pond No. 4, using a scoop. Dry state sampling was carried out conforming IS: 6491-1972. The physical properties of the collected PA sample are shown in Table 1. The PA sample composition was analysed by volumetric titration conforming to IS: 3812 (Part 1)-2013, and the results are tabulated in Table 2.
3.2 Sand Dense natural sand, free from any adherent deleterious substance coating and durable that represents Grading-V that conforms to the requirements of IS: 2116-1980, clause 401.2.1 has been used as CGM for this study. Table 1 Physical properties of pond ash
Physical properties
Values
Specific gravity (Gs )
2.103
Coefficient of uniformity (Cu )
1.306
Coefficient of curvature (Cc ) Maximum dry density (MDD)
0.867 (KN/m3 )
11.8
Optimum moisture content (OMC) (%)
27.86
Liquid limit and plastic limit
Non-plastic
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3.3 Lime Hydrated lime that is chemically pure and in accordance with IS: 1514-1990 was purchased (Tables 3 and 4).
3.4 Nanomaterial The NM’s include Terrasil (NanoT ) and Zycobond (NanoZ ), procured from Zydex Industries, India. Both the NM’s have particle sizes of 95 nm. NanoZ with NanoT imparts higher subbase soil strength and flexibility, enabling dimensionally stable non-deforming bases. NanoT is a heat-stable, transparent, and water-soluble liquid [13]. It is a 100% organo-silane reactive soil modifier that chemically transforms water-absorbing OH groups to water-resistant alkyl groups creating a permanently water-repellent soil surface layer [17] as represented by Fig. 1. Researchers obtained NanoT as a mixture of ethylene glycol, benzyl alcohol, and hydroxyalkyl-alkoxyalkyl [19]. The physical properties of NanoT are shown in Table 5, and its chemical components are represented in Table 6. NanoZ is a UV, heat-stable organosilane cross-linkable soil modifier that chemically binds soil particles into a flexible cross-linked network. It reacts with soil producing an 80–90 nm flexible layer that improves fatigue resistance in stabilized soils [17]. Upon hydrolysis, the inoperative R(alkyl) group, as well as the trialkoxy Table 2 Chemical composition of pond ash
Table 3 Physical properties of hydrated lime
Chemical composition
Values (%)
Silica (SiO2 )
78.02
Alumina (Al2 O3 )
1.08
Magnesium oxide (MgO)
1.4
Iron oxide (Fe2 O3 )
12.7
Calcium oxide (CaO)
2.5
Loss on ignition (LoI)
1
Others (TiO2 , MnO, Na2 O, SO3 , K2 O, P2 O5 )
3.3
Physical properties
Lime sample
Form
Fine dry powder
Colour
White
Specific gravity
2.3
pH (at room temperature)
12.93
Fineness
(m2 /kg)
657
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Constituents
Percentage composition (%)
Calcium oxide (CaO)
71.00
Silica (SiO2 )
4.00
Magnesium oxide (MgO)
2.50
Alumina (Al2 O3 )
0.50
Iron (II) oxide (Fe2 O3 )
0.40
Sulphur trioxide (SO2 )
0.30
Fig. 1 Molecular structure of NanoT forming water-repelling surface on reaction with soil [17] Table 5 Physical properties of NanoT [17]
Physical properties
Specifications
Physical state
Liquid
Colour
Dark brown
Odor
Slightly sweet
pH
5% solution in water neutral or slightly acidic
Melting point
−5 °C
Freezing point
Below −5 °C
Boiling point
Approx. >200 °C
Flash point
>75 °C closed cup
Viscosity
100–800 CPS at 30 °C
Explosive properties
Not explosive
Oxidizing properties
Not oxidizing
Density
1.110 ± 0.01 g/ml at 30 °C
Water solubility
Miscible with water
248 Table 6 The concentration of chemical components in NanoT
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Chemical component
Concentration (%)
Alkoxy-alkyl silyl compounds
90–95
Ethylene glycol
5–10
Fig. 2 Hydrolysis reaction chemistry of NanoZ [17]
Table 7 Physical properties of nanoZ [17]
Physical properties
Specifications
Physical state
Dispersible liquid
Colour
Translucent
Odour
Faint odour
pH
Approx. 5.0–5.6
Melting point
0 °C
Boiling point
100° C
Flash point
90 °C
Viscosity
< 200CPS at 30 °C
Density
1–1.02 g/ml
Water solubility
Partly soluble at 15 °C
Flammability
Non-flammable
Self-igniting temperature
Non-self-igniting
Miscibility with water
Miscible
group of NanoZ , forms silanol (Si–OH) groups which in turn form siloxane (=Si– O–Si = ) upon reacting with siliceous substrates [3]. Figure 2 shows the molecular hydrophobicity of the long alkyl chain in the organic group (Tables 7 and 8).
4 Experimental Studies The chemical characterization of PA and lime was carried out according to IS: 1727– 1967. Prior to the test, unblended optimum SPL mix (SPL0:0:0 = 71% Sand: 25% PA: 4% lime) was mixed with various dosages of NM (NanoT :NanoZ :Water = 1:1:150;
Utilization of Lime Stabilized Pond Ash and Sand Mix Using … Table 8 Chemical composition of NanoZ [17]
Chemical composition
249
Percentage by weight (%)
Oxygen
46.7%
Silicon
27%
Aluminium
8.1%
Calcium
6.7%
Iron
5%
Carbon
3%
Magnesium
1.4%
Others
2.1%
Component
Concentration (%)
Acetic acid
0.2–1
Acrylic co-polymer
34–36
Water
62–65
1:1:200; 1:1:250, 1:1:300, 1:1:350, 1:1:400) as per the OMC and subsequently termed as SPL1:1:150 , SPL1:1:200 , SPL1:1:250 , SPL1:1:300 , SPL1:1:350, and SPL1:1:400 respectively in this study. This was followed by a Modified Compaction test as per IS: 2720 (Part-16)-1987. The samples were then compacted to their OMC to measure the hydraulic conductivity according to IS: 2720 (Part 17)-1987. The c and φ values of the OMC compacted blended samples were obtained by Consolidated Undrained (CU) Triaxial test conforming to IS: 2720 (Part-11)-1993 without measuring the pore water pressure. The strength is evaluated in terms of UCS conforming to IS: 2720 (Part-10)-1987. Also, 4-day soaked CBR test as per IS: 2720 (Part-16)-1987 was performed using modified compaction test results and compared with the MORD and MoRTH [1, 20]. Before conducting the CBR, 7 days of curing was done. 7, 14, and 28 days of curing of the samples was done before the UCS, followed by 7 days of air drying. Finally, the optimum NM stabilized SPL mix was put to slake durability test in accordance with IS: 10,050-1981. The measurement of the surface deflection modulus for the stabilized SPL was collected using DYNATEST LWDMOD, and analysed using 3031 LWD 5.1. The data obtained was used to verify the safe pavement foundation depth using KENPAVE (Table 9 and Fig. 3).
250 Table 9 Description of the samples used for laboratory experiment
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Description of SPL0:0:0
NM dosage (NanoT :NanoZ :Water)
Termed as
71% Sand + 25% PA + 4% Lime
1:1:150
SPL1:1:150
71% Sand + 25% PA + 4% Lime
1:1:200
SPL1:1:200
71% Sand + 25% PA + 4% Lime
1:1:250
SPL1:1:250
71% Sand + 25% PA + 4% Lime
1:1:300
SPL1:1:300
71% Sand + 25% PA + 4% Lime
1:1:350
SPL1:1:350
71% Sand + 25% PA + 4% Lime
1:1:400
SPL1:1:400
5 Result and Discussions 5.1 Compaction Behaviour and CBR Values The findings of the CBR tests demonstrate that the soil samples have shown bearing resistance improvement. Table 10 reveals that the NM used in various dosages improves the bonding of the SPL mix due to its dilution resulting in the penetration of NM at the molecular level and filling the voids of the mix [3, 9]. The nanomaterial was used in the CBR test at the OMC. The generated siloxane bond like the primary valence bond is naturally found in soils. It is sturdy, stable, and resists water, preventing the units of structures from expanding. This primarily results in soil densification and corresponding bearing strength increment [10, 21]. Therefore, the dramatic rise in CBR values is explained. The soaked CBR value for the optimum SPL1:1:300 mix is 79.00%.
5.2 Triaxial Strength Test The efficacy of NM in improving the strength of SPL mixes was investigated using triaxial tests on SPL specimens that had been cured for 7 days. The c and φ values of NM stabilized SPL mixes were tested under CU Triaxial compression conditions without measuring the pore water pressure. The findings showed that increasing the NM dosage content enhanced the cohesion and angle of internal friction of the optimum mix (SPL1:1:300 ) by 41.32% and 20.32%, respectively, compared to the controlled mix. The pozzolanic reaction, which creates the CSH gel, is the dominant mechanism for strength enhancement in this study. It primarily functions as a binder
Recommendations
Unconfined compressive strength test IS 2720(part 10)-1991
Falling Light Weight Deflectometer Test ASTM: E2835- 11
Triaxial strength Test IS 2720(part 11)-1993
Design of Pavement Cross-Section using KENPAVE
Optimum mix
Modified California Bearing Ratio Test IS 2720(part 16)-1987
Fig. 3 Flowchart of the experimental investigations
Slake durability test IS 10050- 1981
Modified Compaction test IS 2720(part 8)- 1983
SPL mix (Sand:PA:Lime=71%:25%:4%) mixed with different dosages of nano-material (NanoT:NanoZ: Water= 1:1:150, 1:1:200, 1:1:250, 1:1:250, 1:1:300, 1:1:400)
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gel that improves soil cohesiveness rather than friction angle. The drop in the production of CSH gel is principally responsible for the lowering trend in the cohesiveness and friction angle of the treated specimens with more than the optimum dosage [18]. This decrease can be ascribed to the development of lumpy nanosilica fragments and a probable decrease in the number of nanoparticles available for the process [15]. Table 11 shows that the c and φ values increase with an increase in the NM dilution with SPL mix, showing the maximum values of c = 40.02 kg/cm2 and φ = 53°.
5.3 Unconfined Compressive Strength Test and Hydraulic Conductivity Compared to the controlled mix (SPL0:0:0 ), the UCS of NM stabilized mixtures significantly improved with a more extended curing period [13]. The remarkable strength increase of NM stabilized SPL mixes was attributed exclusively to the pozzolanic reaction due to the lime addition [7]. Sand, pond ash, and lime react with NM solution. The lime contains calcium ions that react with aluminium oxide and silicon oxide present in the pond ash, leading to the production of cementitious gels, namely Calcium Silicate Hydrate (C S H) and Calcium AluminoSilicate Hydrate (C A S H) binding the PA particles. The reason for the prolonged reaction is the
Table 10 Modified compaction and soaked CBR values
Table 11 Cohesion and Friction angle values by Triaxial test
Description
OMC (%)
MDD (gm/cc)
Soaked CBR (%)
SPL0:0:0
21.732
2.4758
32.85
SPL1:1:150
21.732
2.4758
59.12
SPL1:1:200
21.732
2.4758
65.20
SPL1:1:250
21.732
2.4758
68.22
SPL1:1:300
21.732
2.4758
79.00
SPL1:1:350
21.732
2.4758
73.00
SPL1:1:400
21.732
2.4758
66.52
Description
Cohesion (c) (kg/cm2 )
Friction Angle (φ°)
SPL0:0:0
28.32
44
SPL1:1:150
34.58
48
SPL1:1:200
37.85
50
SPL1:1:250
38.34
51
SPL1:1:300
40.02
53
SPL1:1:350
32.18
47
SPL1:1:400
30.09
46
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Table 12 UCS values of the samples Description
UCS values of the samples after curing the samples (MPa) 7 days
14 days
28 days
SPL0:0:0
0.546
0.754
0.824
SPL1:1:150
0.958
1.150
1.600
SPL1:1:200
1.094
1.268
1.738
SPL1:1:250
1.226
1.404
1.818
SPL1:1:300
1.308
1.558
1.966
SPL1:1:350
1.068
1.226
1.708
SPL1:1:400
0.968
1.194
1.668
Permeability
No permeability value is obtained using 24 h falling head permeability test conforming to IS: 2720 (part 17)-1986
lime content in the pond ash being very minimal (2.5%). Hence, the gel formation gradually increases over the curing period [12]. The test result shown in Table 12 of the optimum NM stabilized SPL mix in the duration of 7–14 days of curing increased from 1.308 MPa to 1.558 MPa, finally reaching the value of 1.966 MPa for 28 days of curing. Also, the UCS of the SPL mixes reached its peak when the NM dosage was increased by up to 1:1:300, whereas the UCS decreased when the additive was increased further. The reduction of the UCS values after optimum dosage can be attributed to the high specific surface area of nanosilica. IRC SP 20(IRC 2002) specifies, for use in subbase layer, the minimum laboratory UCS of the fly ash–lime mixture after 28 days’ curing should be 1.5 MPa. A nonfunctional organic R (alkyl) group and trialkoxy groups make up the substance known as NanoT [17] which produces silanol (Si–OH) groups on hydration. These reactive silanols produce siloxane linkages [19]. The NanoT , when combined with PA, lime, and their chemical reactions with the water flow path, act as a filler for porous soil and lower the soil’s hydraulic conductivity. The treated surface gains molecular-level hydrophobicity from the organic group’s lengthy alkyl chain resulting in the impermeability of the SPL mixes, and enhancing the strength of the mix [3, 17].
5.4 Slake Durability Test The Slake durability test was carried out for the optimum NM stabilized SPL mix (SPL1:1:300 ). 7, 14, and 28 days of curing were performed. The SDI values, Id1 , and Id2, shown in Table 13, use Gamble’s slake durability classification [7, 22, 23]. The test also showed an increase in the curing period from 7 to 14 days, and up to 28 days SDI value increases, as in Table 14. It shows Id2 of the sample varies from 98% to 99%, which is of high durability to very high durability.
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Table 13 Gamble’s slake durability classification [24] Sl. no.
SDI 1st cycle (Id1 )
Remarks of durability
SDI 2nd cycle (Id2 )
Remarks of durability
1
>99
Very high durability
>99
Very high durability
2
>98–99
High durability
>98–99
High durability
3
>95–98
Medium–high durability
>95–98
Medium–high durability
4
>85–95
Medium durability
>85–95
Medium durability
5
>60–85
Low durability
>60–85
Low durability
6
60
60
>60
0.7
1.0
0.5 4.1
4.0
3.0 0.672
0.678 0.454
9 months
>60
>60
>60
0.7
1.2
0.5 4.1
4.0
3.0 0.714
0.714 0.480
1 year
>60
>60
>60
1.0
1.2
0.6 4.4
4.4
3.0 0.718
0.772 0.500
5.1 Progression of Permeability Grease ring test is one of the simple methods to compare the field permeability of different surface mixes [7]. In the present study, a ring of 80 mm diameter and 25 mm height was made using thick application of grease, such that the water does not escape through the walls of the ring. The ring is then filled with water up to a height of 20 mm, and the time to drain off through the surface is recorded using a timer. During the initial period of evaluation, the water disappeared quickly from the surface, especially in case of OGPC and MSS. But later, as the pavement surface densified, the inter-connected voids reduced and subsequently the field permeability decreased. When the time taken to drain off was more than 1 h, the surface was considered to be impervious. It was inferred that the BC surface become impervious at the end of 3 months, while it took nearly 6 months for the OGPC and MSS surface to become impervious. However, this duration would depend up on several factors such as the type of gradation, traffic intensity, and environmental factors favoring the densification of mixes. This understanding of the mix behavior is significantly important while scheduling the construction of the surface layer. Due to the inferior specification of the seal coat surface, which is unable to seal the voids in the OGPC surface initially itself, water will penetrate to lower layers, especially if construction activity of bituminous mix is planned immediately prior to monsoon. Hence, with the present specification of OGPC and seal coat, it is recommended to plan construction activities sufficiently prior to monsoon, such that the pavement becomes impervious before the next monsoon season.
5.2 Progression of Texture Depth Evaluation of texture depth using sand patching test can provide reliable estimates of the bleeding/surface polishing occurring during initial densification of the surface mix and loss of fine aggregates occurring during initial stages of raveling. During the initial service period, it is expected that the texture depth would gradually decrease
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due to surface polishing/bleeding of bitumen, which subsequently fills the voids on the surface. But later when the pavement starts to deteriorate, fine aggregates will start to get separated from the surface, resulting in a gradual increase of texture depth. In the present study, 100 cm3 of fine aggregates passing 2.36 mm sieve and retained on 0.075 mm sieve was used for the sand patching test. The fine aggregates were spread to a circular shape, such that no further sand remained on the surface. The diameter of the circle along multiple orientations was noted, and the average diameter was used for calculating the area of the circle. The texture depth was then calculated as the ratio of the total volume of sand to the area of the circle on the surface. From Table 4, it can be inferred that the rate of reduction in texture depth was much faster on BC surface due to faster densification, and this can be correlated to its resistance to moisture infiltration. Although there was slight increase in texture depth after the monsoon, due to loss of fine aggregate, the rate of increase was comparatively lower on the BC surface. It was concluded that the BC surface mix was able to hold the aggregate particles intact and they were capable of resisting moisture induced damages.
5.3 Progression of Roughness Currently the LVR in India is designed based on the guidelines of IRC SP 72 [5], which follow AASHTO [1] design principles, in which roughness expressed in terms of Present Serviceability Index (PSI) is considered for the terminal design criteria. In the present study, surface roughness measured in terms of International Roughness Index (IRI), using MERLIN apparatus, was used to compare the riding quality offered by the different surface mixes. IRI of the test sections were reported based on the average of three values, estimated based on the MERLIN roughness index obtained corresponding to 200 revolutions. MERLIN roughness index was converted to IRI using Eq. 1, where “D” represents MERLIN roughness index in mm. From Table 4, it can be inferred that the roughness observed on the BC surface was much lower than that on the OGPC and MSS surfaces, due to its ability of being compacted to a smooth surface. This is primarily due to the NMAS of the BC mix, which was less than half the layer thickness, and the dense aggregate gradation in comparison with the other two open-graded mixes. IRI = 0.593 + 0.0471D
(1)
5.4 Progression of Rebound Deflection Structural evaluation of the test sections was performed in terms of the rebound deflection measured under the standard loading conditions, outlined in IRC 81 [4],
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for strengthening of flexible pavements using BBD. The test was carried out on thin bituminous surfaces and hence the effect of temperature was neglected for the analysis. However, since the test was carried out during different seasons of the year, moisture correction was applied to the observed deflection data. Moisture correction factors outlined in IRC 81 [4] for sandy/gravelly subgrade with annual rainfall of more than 1300 mm were used in the present study, for the correction of actual observed data. The corrected surface deflection values are summarized in Table 4. It was observed that the surface deflection of the pavement initially decreases up to 6 months and thereafter it slowly starts to progress. Reddy and Veeraragavan [10] referred to this time period during which the pavement deflection reduces after construction as “stabilization period.” In the present study, stabilization period of the three test sections was found to occur after 6 months of construction, and the corresponding values are highlighted in Table 4. The deflection corresponding to this stabilization period is referred to as “initial deflection” in the present study. The stabilization period for different combinations of pavements can vary depending upon several factors such as the secondary compaction, characteristics of the layers under traffic loading, thickness of the layers, and traffic loading rate. This minimum deflection value achieved at the end of the stabilization period can be considered a characteristic measure of pavement strength, and hence this value is used in the present study for evaluating effective pavement modulus, as recommended in AASHTO [1]. It should be noted that the initial deflection value of pavement with BC surface was significantly lower than the other two surfaces.
6 Performance Prediction of Test Section Performance of a pavement ideally needs to be compared in terms of the wheel load repetitions that the pavement has endured before reaching the terminal criteria. Since this process may take several years to complete, researchers often use prediction methods to evaluate the predicted life of the pavement. An understanding of the structural number of the pavement can also provide a reliable estimate of the life of the pavement. AASHTO [1] has provided a simple method to estimate the effective structural number of the pavement, as a function of the effective modulus of the pavement. Since LVR in India is presently designed based on the concepts of structural number, an effort was made in the present study, to estimate the life of pavement, based on the effective structural number of the pavement.
6.1 Evaluation of Effective Pavement Modulus The determination of the effective structural number of the pavement starts with the determination of effective pavement modulus, which can be calculated based on the initial deflection observed during the deflection study conducted using BBD.
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Table 5 Predicted performance of the test sections Type of mix
Surface deflection (mm)
Effective modulus (ksi)
Pavement thickness (inches)
Effective structural number
Predicted life (msa)
OGPC
0.672
67,860
12.8
2.35
0.55
MSS
0.678
66,410
12.8
2.33
0.52
BC
0.454
182,990
13.2
3.37
5.41
In the present study, equivalent surface deflection was the equivalency criteria used for determining the effective modulus of pavement. The analysis was done using IITPAVE software, which is a linear elastic layer program, developed for the analysis of flexible pavements. The loading condition used for the analysis was 0.56 MPa type pressure and 40 kN wheel load, similar to that of the load applied during the BBD test. The actual cross section of the test sections consists of a thin bituminous surface layer, base layer, and granular sub-base layer above the subgrade. For the purpose of analysis, the three layers above the subgrade were modeled as a single layer in IITPAVE software, and the moduli values were iterated until the calculated surface deflection matched with the observed deflection under BBD loading. Subgrade was assigned with a modulus of 61 MPa, which corresponds to 7% CBR, and Poisson’s ratio was assumed as 0.35. The effective modulus values for the three test sections are summarized in Table 5.
6.2 Evaluation of Effective Structural Number Since the actual method for the determination of the structural number of a pavement is time consuming, AASHTO [1] has provided a simplified equation for determining effective structural number of pavement, as a function of effective pavement modulus and thickness of the pavement above subgrade (Eq. 2). SNeff = 0.0045 ∗ D ∗ EP( 3 ) 1
(2)
In Eq. 2, “SNeff” represents the effective structural number of the pavement, “D” represents the thickness of the pavement in inches, and “EP” represents the effective modulus of pavement layers above subgrade in psi. The effective structural number corresponding to the three test sections is summarized in Table 5.
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6.3 Evaluation of Predicted Pavement Life AASHTO [1] has provided a nomograph for estimating the structural number corresponding to a given wheel load repetition and an equation (Eq. 3) for estimating the number of wheel load repetitions corresponding to pavement with a known structural number and subgrade condition. ( ( ΔPSI )) log 4.5−1.5 ) ( log10 (W18 ) = Zr ∗ So + 9.36 ∗ log10 (SN + 1) − 0.20 + 1094 0.40 + (SN+1) 5.19 + 2.32 ∗ log10 (Mr ) − 8.07
(3)
In Eq. 3, ΔPSI is adopted as 2 since the expected drop in PSI for LVR was specified as 2 in IRC SP 72 [5]. “W18 ” represents standard 18-kip wheel load repetitions, “Zr ” represents standard normal deviate and “So” represents standard deviation. “SN” represents structural number of the pavement and “Mr ” represents effective road bed modulus in psi. The recommended value of Zr corresponding to a reliability of 50% is zero. The predicted life of the three test sections, evaluated using the effective structural number is summarized in Table 5.
7 Comparison of Performance and Construction Cost The overall implication of using the three surface mixes within the scope of this study was compared in terms of the construction cost and expected design life of the pavement. Presently, the estimates for the construction of LVR in the state of Kerala, India, are done based on the estimate data given in PRICE software, and hence the same information was used in the present study, for calculating the material cost and other expenses corresponding to OGPC, seal coat, MSS, and BC (Table 6). It should be noted that the OGPC layer is accompanied by the application of 6 mm seal coat and hence the total cost of OGPC surface should be considered as the sum of OGPC and seal coat layer. A comparison of the construction cost and predicted life of the 3 surface mixes is illustrated in Fig. 2. Table 6 Construction cost of surface mixes (Rupees), per square meter Type of mix
Thickness (mm)
OGPC
20
30
6
10
Seal Coat
Machinery and Labor
Bitumen
Aggregate
Overhead (10%)
Profit (10%)
Total (Rupees)
61
36
13
14
154
28
12
5
6
61
MSS
20
30
76
36
14
16
172
BC
30
30
128
56
21
24
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300
Predicted Life (in msa)
Construction Cost (in Rs.)
6
250
5
200
4
150
3
100
2
50
1
0
Predicted life (msa)
Construction cost per sq. m. ( Rupees)
280
0 OGPC
MSS
BC
Type of surface mix Fig. 2 Comparison of predicted life and construction cost
From Fig. 2, it can be inferred that when a field engineer prefers to use MSS over OGPC, the construction cost is reduced by 20%, without any significant reduction in expected pavement life. Hence it would be ideal to prefer MSS over OGPC, for pavements with low or medium traffic condition. But when it comes to the selection of surface course for pavements with high traffic condition, it would be necessary to think about a pavement combination that can ensure improved performance within the limited budget. The current guidelines in India do not permit to use of BC directly over a granular base layer, considering the difficulty to compact a dense bituminous mix, without a stiff bituminous binder course. However, experience gained in the construction of the test section presented in the study has motivated several field engineers to construct BC surfacing over a compacted WMM layer. Several other LVR sections have also been constructed in the state of Kerala, following this study, especially in Rebuild Kerala Initiative projects in LVR. It can also be inferred that, even though the construction of BC surfacing is 20% more than OGPC, it can ensure significantly improved performance (estimated pavement life), when compared with OGPC or MSS. Pavements with BC surface can endure traffic of 5.4 msa, while the pavement with OGPC and MSS can only endure 0.5 msa, before reaching the terminal condition.
8 Conclusion In the present study, a comprehensive analysis of the behavior of the three surface course mixes, such as the OGPC, MSS, and BC was done, with consideration to its laboratory and field performance. Considering the need to shift toward more durable pavement structures, it is necessary to develop new construction practices, which can offer pavements with improved performance. This understanding is more important in the case of LVR, since a major share of the total road network belongs
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to the category of LVR and the present construction practices in India fails to meet the design life of the pavement. From the present study, it was concluded that it is possible to construct a thin layer of BC directly above the granular layer, and the field application of 30 mm thick BC layer can significantly improve the performance of LVR, without any appreciable change in construction cost. The difference in thickness of OGPC and BC layer is also one of the reasons for the improved performance of pavements with BC surfacing. However, it requires long-term field performance studies to understand more about the material and make them a part of the new revisions of IRC specifications. Acknowledgements Authors wish to acknowledge the Alappuzha Division of Local Self Government Department, Government of Kerala, for providing the necessary financial support for constructing the test sections, and the Science and Engineering Research Board (SERB) for providing the financial support for conducting the performance evaluation of the test sections
References 1. AASHTO (1993) Guide for design of pavement structures, American association of state highways and transportation officials 2. ASTM D 6931 (2017) Standard test method for indirect tensile strength of asphalt mixtures, ASTM international 3. Choudhary R, Singh SK, Kumar A, Porwal SS (2016) Permeability characteristics of bituminous premix carpet and mix seal surfacing. J Indian Road Congr 658:383–392 4. IRC: 81 (1997) Guidelines for strengthening of flexible road pavements using Benkelman beam deflection technique (first revision), Indian road congress: New Delhi 5. IRC: SP 72 (2015) Guidelines for the design of flexible pavements for low volume rural roads (first revision), Indian Road Congress: New Delhi 6. IRC: 37 (2018) Guidelines for the design of flexible pavements (fourth revision), Indian road congress: New Delhi 7. Kandhal PS, Veeraragavan A (2016) Review of practices for improving ride quality and periodical renewal of bituminous pavements in India. J Indian Roads Congr 77–3 8. Ministry of Road Transport & Highways (MoRTH) (2013) Specification for road and bridge works, fifth revision, Indian road congress: New Delhi 9. Ministry of Rural Development (MoRD) (2014) Specification for rural roads, first revision, Indian road congress: New Delhi 10. Reddy BB, Veeraragavan A (1997) Structural performance of in-service flexible pavements. J Transp Eng 123:156–167
Lessons Learnt from a Premature Failure of Stone Matrix Asphalt (SMA) on a High-Volume Indian Highway Purbayan Ghosh Mondal, Anil Kumar Baditha, Dharamdas Ahriwar, Rajib Chattaraj, and Kranthi Kumar Kuna
Abstract This paper discusses the lessons learnt from a premature pavement failure investigation of an Stone Matrix Asphalt (SMA) surface course laid to rehabilitate one of the most heavily laden National Highways in India. A detailed laboratory investigation was carried out to evaluate the causes of the failure. In addition to testing the samples from the field, the study also verified the applicability of an acid–base titration method to quantify the lime content in the field asphalt mixes. Considering the higher proportion of mineral filler in SMA mixes, a laboratory investigation was conducted as a part of this study to examine the influence of filler fractional voids on the properties of the SMA mixes. Along with the causes of the failure, the paper also emphasizes the pitfalls associated with the SMA construction. The paper also highlights the implications of these pitfalls and lessons learnt during the implementation of the project. One of the aims of the paper is to recommend best practices based on the lessons learnt, specifically etiquettes that are specific for SMA construction and that are not well established. Results of the additional laboratory studies as a part of the investigation showed that the filler fraction voids influenced the mix workability and the bitumen demand. Lime filler with high fractional voids resulted in mixes with lower workability and higher bitumen demand. The findings emphasize the importance of quality control tests for lime filler when used in SMA mixes. Keywords Stone matrix asphalt · Failure investigation · Fractional voids
P. G. Mondal (B) · A. K. Baditha · D. Ahriwar · K. K. Kuna Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India e-mail: [email protected] K. K. Kuna e-mail: [email protected] R. Chattaraj Public Works Department, Government of West Bengal, Kolkata, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_23
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1 Introduction SMA, otherwise known as Stone Matrix Asphalt, is a gap-graded hot mix asphalt designed to achieve direct stone-to-stone contact. Due to the superior resistance against rutting which has been a major failure phenomenon on Indian Highways, the tentative mix specifications of SMA have been introduced in 2008 in IRC: SP:792008 [1]. Since then, there have been a few research initiatives including field studies [2]. Its implementation in India has gained momentum since the introduction of the provision to use SMA as a surface course for highways in the latest pavement design guidelines (IRC:37-2018). However, producers of these mixes have faced several challenges in the successful deployment of the mix. This is particularly true for relatively small or new road construction firms as they have been wedded to the production of dense-graded mixes that have been the norm for the past few decades. In this context, the objective of the present paper is to emphasize the common pitfalls associated with the SMA construction through a case study. An attempt has also been made to present recommendations so that such pitfalls can be avoided on other highway projects.
2 Project Description and Visual Condition Main quarries of road aggregates and natural sand in West Bengal are located by the side of the National Highway (NH) which is predominantly featured by heavily loaded single, tandem, and multi-axle trucks which carry aggregates. The original composition of the pavement is of very high and heterogeneous in character with asphalt layer thickness varying from 140 to 300 mm whereas granular base thickness varied from 280 mm to more than 400 mm at some locations. The axle load survey data and traffic data analysis indicated that the pavement is severely overloaded for the existing pavement composition. The vehicles with a vehicle damage factor of more than 40 operate on the road stretch continuously. Axle loads as high as 28 tons were found in the axle survey data. Figure 1a presents an example of an overloaded truck plying on the NH. Due to excessive overloading, the distresses such as potholes, raveling, and alligator cracking were observed on a significant length of the stretch. The general condition of the said stretch in 2017 can be seen in Fig. 1b. The managing road agency has planned to rehabilitate this stretch in early 2018. The rehabilitation of the pavement works involved 100 mm milling of the existing asphalt layer and inlaying 40 mm SMA surface course over 60 mm new Dense Bituminous Macadam (DBM) binder/base course. The inlay/overlay pavement design was based on IRC:37-2012 [3] and IRC:115-2014 for design traffic of 146 msa (5 years design life). The mix design of SMA (13 mm nominal size) was carried out as per IRC: SP:79-2008 and the bitumen used was PMB 40 meeting the requirements of IRC SP 53-2010. Table 1 presents the gradation limits recommended in IRC: SP:79-2008 and the design grading achieved by the blending exercise. To achieve the
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Fig. 1 a An overloaded truck carrying aggregates from a nearby quarry (left); b general condition of the pavement in 2017 before rehabilitation
desired levels of the filler (75-micron passing) in the mix, 8% of hydrated lime was recommended. As required by the SMA specifications, voids in the coarse aggregate fraction of the compacted SMA mix (VCAMIX ) were found to be 32.5% which is less than the voids in the coarse aggregate fraction determined by dry-rodded test (VCADRC = 45.5%). The rehabilitation works were implemented in early 2019. However, premature distresses were observed on parts of this pavement within 2 to 3 months after construction, i.e., immediately after monsoon. In May 2019, a visual condition survey was carried out to identify the typical condition of the pavement. The visual survey indicated that a significant length of the section was severely damaged. The major distress that identified was shoving along the wheel path, accompanied by rutting. Typical shoving and rutting failure of the stretch is shown in Fig. 2a. Table 1 Gradation requirements for SMA mix and design gradation as per Job Mix Formula (JMF) for the project
I.S. sieve size (mm)
Percent passing Requirements as per Table Design gradation 3 of IRC: SP:79-2008 Desired range
Midpoint
100
100
100.0
13.2
90–100
95
95.2
9.5
50–75
62.5
54.0
4.75
20–28
24
26.4
2.36
16–24
20
21.5
1.18
13–21
17
18.4
0.6
12–18
15
14.5
0.3
10–20
15
12.5
8–12
10
8.8
19
0.075
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Fig. 2 a Typical photo of severely shoved and rutted pavement; b Absence of stone-to-stone contact in the SMA surface course
A trial pit was excavated to assess the overall condition of the pavement layers and to check whether the rutting is limited to the surface course of the pavement. From the trail pits, it was noted that the pavement cross section consists of 40 mm of newly laid SMA, 60 mm of newly laid DBM on the top of around 200 mm of old bituminous layer on WMM, GSB, and subgrade. The thickness details of the pavement layers are in line with the design recommendations. It was noted from the pavement cross section that the rutting is mostly limited to the surface course, i.e., the SMA layer. Attempts were made to extract cylindrical cores from the pavement areas that were severely shoved and rutted. The cores did not come intact while only the SMA layer came out indicating de-bonding of the layer from DBM below at these locations. Visual examination of the cores taken adjacent to the failed pavement areas indicated lack of stone-to-stone contact in the surface layer which is the main characteristic of the rut-resistant SMA mix. It was noted that on the pavement sections where only DBM is laid and SMA is yet to be laid, the pavement surface looked to be in a reasonably good condition with very minor distresses which are common when DBM is opened for traffic for fairly long periods. Based on the observations from the visual survey, a detailed laboratory investigation was planned to analyze the causes of the failure.
3 Detailed Investigation Plan For the detailed investigation, firstly, a desktop study that involved reviewing the construction logs including the density recordings and the method statements of the materials used in the SMA, etc. was carried out. A detailed laboratory investigation of the samples and materials collected from the field was carried out. To assess the in situ density of SMA, a number of full-depth cores from the locations proximal to the failed pavement surfaces were collected. To assess the compliance of the laid SMA
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mix with IRC: SP-79 requirements, slabs reclaimed from the failed locations were collected. Further, other materials such as bitumen, aggregates, cellulose fiber, and lime that are used in the SMA production were collected for the detailed laboratory investigation.
3.1 Laboratory Testing of Field Samples To determine the bitumen content of the SMA slabs, the bitumen from the slabs was first extracted using trichloroethylene in a centrifuge extractor as per ASTM D2172. Then the bitumen was recovered from the solvent using rotary evaporator as per ASTM D5404-12. Gradation of the aggregates extracted from the SMA slabs and the bitumen content were then determined. Eight samples were considered for gradation analysis and bitumen content determination. The results were calibrated based on the results obtained from the mixes with a known quantity of constituents. Measurement of bulk density (Gmb ) of the trimmed SMA cores was carried out on paraffin-coated specimens as per AASHTO T 275. Theoretical maximum specific gravity (Gmm ) of three loosened mixes was determined as per ASTM D2041. The PMB 40 bitumen used in the SMA production was tested for physical properties to verify its compliance with relevant standards (IRC: SP:53-2010). Softening point test was also carried out on the bitumen that was extracted from the reclaimed SMA mix. To investigate the extent of moisture damage in the SMA mix, a moisture sensitivity test was carried out as per AASTHO T283 on Marshall samples with 7% air voids prepared from the asphalt slabs from the field. For the preparation of the Marshall samples, the asphalt slabs were placed in an oven at 100 °C for 1 hour to loosen the mix and then mixed and compacted at 160 ºC and 150 ºC, respectively. Trails were carried out to determine the number of Marshall blows required to achieve 7% air voids. To quantify the amount of lime in the reclaimed SMA mixes, an acid–base titration test method proposed by Mouillet et al. [4] was conducted. The test involves hydrochloric acid titration of a suspension of the filler extracted from asphalt mix. The test derives the hydrated lime purity (% Ca(OH)2 ) from existing lime characterization methods (IS: 1514/EN 459-2). To validate and calibrate this method of quantification of hydrated lime, the test was carried out on fillers extracted from the asphalt mixes produced in the laboratory with known amounts of hydrated lime. Titration test was conducted on filler extracted from the SMA samples prepared with 0, 2, 4, 6, and 8.8% (corresponds to approx. 0, 23, 45, 68, and 100% lime replacement) of lime replacing equal quantities of mineral filler (75-micron passing) of target grading. Adopting the calibration factors from the validation tests, the lime quantity of the reclaimed SMA mixes was determined.
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3.2 Additional Laboratory Studies To understand the effect of properties of lime, particularly the fractional voids, on the properties of SMA mixes such as workability and Optimum Bitumen Content (OBC), studies were carried out on three lime types one of which is the lime used in the SMA produced for the surface course of the pavement under investigation. To study the effect of lime quantity and resulting fractional voids of filler on OBC, Marshall mix design as per MS-2 (Asphalt Institute Manual Series-2, 7th edition) was carried out on the aggregate fraction with the above-mentioned proportions (i.e., 0, 23, 45, 68, and 100%) of filler replacement with lime. The coarse aggregates used in the study satisfied the physical requirements specified in Table 1 of IRC: SP:79-2008. Similarly, the filler material satisfied the grading requirements specified in Table 1 of IRC: SP:79-2008. For brevity of the paper, the results are not presented in the paper. 13 mm NMAS was considered for these studies and the target gradation was the same as in Table 1. The samples were prepared by applying a compaction effort of 50 blows on each side as recommended in IRC: SP:79-2008. The bitumen content was chosen based on the mix requirements specified in Table 1 of IRC: SP:79-2008. The penetration (at 25 ºC), softening point, and Kinematic viscosity (at 150 ºC) of the PMB 40 bitumen (as per IRC: SP:53) used are 45 dmm, 61 ºC, and 408 cSt, respectively. The number of gyrations to 92% Gmm in the Superpave Gyratory Compactor (SGC) was used as an indicator for workability. Workability was measured on SMA mixtures produced by replacing the 0, 23, 45, 68, and 100% of mineral filler proportion, and compacting to 96% Gmm . The bitumen content was kept constant at 6% of mix weight. The same mixes were used for the calibration of the lime quantification approach discussed in the earlier section. Fractional voids of filler with different proportions of lime are determined as per EN 1097-4. The method involves measurement of voids in a unit volume of lime compacted to standard compaction effort of 100 blows with a 350 gm hammer of 25 mm diameter on 10 gm of lime.
4 Test Results 4.1 Findings from Desktop Study From the review of the construction log details, it was noted that the Gmm was consistently around 2.630. This value is moderately higher than the Gmm of 2.560 obtained from the mix design with the same aggregates and design bitumen content of 6%. Gmm value decreases with the bitumen content and an average value of 2.630 corresponds to a bitumen content of around 5%. Air voids were calculated based on the Gmb values of the cores collected during the construction for quality control purposes. The average air void values from nine samples were 9.43% which is more than the desired. The statistical analysis (hypothesis testing with H0 : µ = 6 and HA :
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µ > 6) on the air voids data resulting in a p-value of 0.01 suggests that the SMA layer was not compacted to the requirements of IRC SP:79 and MoRTH. According to these specifications, the SMA layer is to be compacted to more than 94% of Gmm , i.e., not more than 6% air voids are allowed in the compacted SMA layer. The high air voids must have allowed water to percolate into the mix that resulted in the weakening of the adhesive bond between aggregate and bitumen and the cohesive bond within the mix. Furthermore, most of the trucks are excessively overloaded. The axle load survey results indicate that this particular stretch carries the trucks whose Vehicle Damage Factor (VDF) is as high as 45, which is alarmingly high.
4.2 Results of Field Samples The mean and standard deviation of the air voids derived from the Gmb and Gmm measurements on 11 field cores were found to be 7.3 and 2.4, respectively. The statistical analysis (hypothesis testing with H0: µ = 6 and HA: µ > 6) of this data resulted in a p-value of 0.04 suggesting that the SMA layer was not compacted to the requirements of IRC:SP:79 and MoRTH. This finding is in line with the desktop study. The test results on the SMA slabs indicate that much of the test data were outside the permissible JMF tolerances. For example, only three samples out of eight tested samples were found to have bitumen content within the 6.0% ± 0.3. All other samples did not meet the lower bitumen content tolerance. The average bitumen content in the SMA layer was found to be 4.9% (by weight of mix) with a standard deviation of 0.52%. The statistical analysis also suggested that the bitumen content in the SMA in field slabs is less than the JMF bitumen content of 6% (p-value = 0). Softening point test was also carried out on the bitumen that was extracted from the reclaimed SMA mix. The average softening point was found to be 65.5 °C which was about 4.5 ºC more than the JMF softening point. Experience indicates that the softening point temperature of modified bitumen usually increases by around 5˚C due to oxidation during mixing, laying, and compaction of the bitumen. To verify if the lime added to mixes is fully recovered during the extraction and recovery processes, as stated earlier, acid–base titration tests were carried out on the filler (75-micron passing material) recovered from SMA mixes produced with known filler composition (0, 23, 45, 68, and 100%). The test results in terms of Ca(OH)2 concentration are presented in Fig. 3. The test results are compared with theoretical Ca(OH)2 concentration based on the quantity and quality (purity) of lime added to the SMA mix from which the filler was recovered. The purity of the lime added in these mixes in terms of Ca(OH)2 was 95.5%. As can be noted from the figure, the titration test results at all the lime concentrations are marginally below the line of equality indicating that the test indicated slightly lower lime content in the filler, between 5 and 20% lower than the theoretical values, with percentage difference decreasing with increase in concentration. Thus, the tests on filler solution from mixes with 2,
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Fig. 3 Titration test results on the filler recovered from SMA mixes with known quantities of lime
4, 6, and 8.8% of lime indicated the presence of 1.7, 3.6, 5.7, and 8.3% of lime. The results suggest that the test is able to quantify the lime present in the filler. There is a good correlation between the theoretical values and the test values and the linear regression derived between these two was used to predict the lime content in the field mixes. Aggregate gradations for SMA layers for all the eight mixes are also shown in Fig. 4. The Fig. 4 indicates that no sample mix has gradation within limits specified in IRC: SP:79. As can be seen from the figure, the sieve sizes 9.5, 4.75, and 2.36 mm in most cases were found to be outside the recommended limits. Furthermore, the filler content was outside the permissible JMF tolerances (8.8 ± 1.5). Table 2 presents the results on the fillers extracted from the three randomly selected field cores. As can be noted from the table that in all three mixes the lime content is around 2% which is lower than the JMF lime content. The combined results in Fig. 4 and Table 2 suggest that gradation is much finer than the JMF. The average TSR of the SMA mixes was found to be 43% confirming the moisture damage in the mix as the TSR requirement as per IRC SP-79 (2008) is a minimum of 80%.
4.3 Effect of Mineral Fillers Properties on SMA mixes Table 3 presents the results of the workability tests on the SMA mixes with three lime types (A, B, and C) with different fractional voids. Lime B is the one used to develop the JMF, Lime C is the lime used in the SMA construction. Lime A is included in the study to evaluate the effect of fractional voids on the SMA properties. The fractional
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Fig. 4 Sieve analysis results on extracted aggregates from reclaimed SMA mix Table 2 Results of the lime quantification tests on the mixes from the field Mix no.
Filler content in the mixture (%)
Mix 3 6.3
Ca(OH)2 content % in fillera
Lime content % in Lime content in the fillerb mixture (%)
28.1
30.1
1.9
Mix 4 3.8
50.3
53.9
2.0
Mix 8 4.9
36.4
39.0
1.9
a
Values using the calibration linear regression from Fig. 3 Value obtained after correcting for the purity of lime obtained from field which is 93.3% in terms of Ca(OH)2 b
Table 3 Workability and OBC for SMA mixes with varying lime content Lime content in Lime content in Lime A the mixture (%) the filler (%) (fractional voids = 0.59)
Lime B (fractional Lime C (fractional voids = 0.43) voids = 0.32)
N@ 92%Gmm
OBC (%)
N@ 92%Gmm
OBC (%)
N@ 92%Gmm
OBC (%)
0.0
0.0
44
6.4
44
6.4
44
6.4
2.0
22.7
48
6.4
41
5.8
42
Na
4.0
45.5
50
7.5
44
6.2
42
Na
6.0
68.2
53
8
46
6.5
39
6
8.8
100.0
55
Na
50
Na
35
Na
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Fig. 5 Relation of filler fractional voids with the bitumen requirement for SMA mixes
void of the filler used in the study is 0.39. As can be noted from the table, in general, the workability indicator, i.e., number of gyrations to 92% Gmm increased with the addition of lime content for Lime A and Lime B which have fractional voids of 0.49 and 0.53, respectively. For mixes with Lime C which is having relatively lower fractional voids (0.32), the workability decreased with an increase in lime content. Table 3 also presents the OBC obtained for the mixes with different lime contents thus different filler fractional voids. The filler fractional voids are plotted against the mix OBC in Fig. 5. The figure suggests a strong positive correlation between OBC and filler fractional voids, indicating that mixes with filler of higher fractional voids may require relatively more bitumen.
5 Findings Based on the desktop study, field investigation, and detailed laboratory studies, it may be concluded that the distress can be attributed to a combination of causes rather than a single cause. The field densities suggest that the SMA layer was not compacted to the desired densities. The high air voids must have resulted in the weakening of the adhesive bond between aggregate and bitumen and the cohesive bond within the mix. The weakened mix due to moisture damage, as confirmed by the TSR tests, might have caused rutting in the mix. The high air void content might have allowed excessive water to infiltrate into the SMA layer resulting in the weakening of the interface between SMA and DBM. Failure of the interface results in the SMA layer acting as a separate layer which compromises the structural integrity of the pavement causing cracking of the layer initially and then shoving of the cracked material because of the heavy-laden trucks. High air void content and lack of stone-to-stone contact might have also contributed to the rutting of the mix. Furthermore, most of the trucks are excessively overloaded. The resulting high stresses could have accelerated and exaggerated the failure of the SMA layer.
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The laboratory studies indicate that filler (both mineral filler and lime) factional voids influence workability and bitumen requirement in the mix. The absence of quality control tests to this property in the existing specifications might have also caused the failure of the SMA.
6 Recommendations Based on the outcome of the detailed investigation, the recommendations were made considering the lessons learnt from the project. The recommendations are in addition to the widely accepted SMA-related best practices such as handing the cellulose fiber, etc. and general etiquette involved in the construction of dense-grade asphalt layers. Being a gap-grade mix, SMA draws their resistance against rutting from stoneto-stone contact. Thus, the importance of closely controlling the gradation is most important for the performance of SMA, particularly for the material passing the 4.75 and 0.075 mm sieves. The investigation of the present study and similar failures elsewhere in the country suggest that the SMA mixes are unapologetic with regard to the aggregate gradation non-compliance. As the coarse aggregate proportion is 70–80% of the total blend, more emphasis shall be given to handling the coarse aggregate at the crushers and production plant. Vertical shift impact crushers are preferred and if necessary, multiple cold bins can be used for coarse aggregates. SMA mixes usually require approximately 10% passing the 0.075-mm sieve. This means the SMA mixes typically require the addition of at least 5% commercial mineral fillers such as lime. The present study indicated that qualitative characteristics of these additives such as fractional voids significantly influence the mix performance. Therefore, the source of these lime fillers must be carefully selected. Further research is necessary to establish the quality requirements of the secondary fillers used in SMA considering their effect on the SMA mix design and performance. SMA mixes are generally cool quicker compared to the dense-grade mixes, and therefore the rollers should be operated immediately behind the paver. Another important field consideration with respect to compaction is that the rolldown of SMA mixtures is considerably less compared to dense-grade mixes due to the virtue of the gradation, therefore, lower lift thickness shall be provided compared to dense-graded mixes. The tandem roller shall be used in a high-frequency and low-amplitude mode. Excessive vibration of the roller breaks the coarse aggregate and forces the mastic to the surface of the mat. Further, unlike in the dense-graded mixes, pneumatic tired rollers shall not be used on SMA as these tires pick up the mastic causing surface defects.
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References 1. IRC:SP:79 (2008) Tentative specifications for stone matrix asphalt, Indian roads congress 2. Kamaraj C, Jain PK, Sharma BM, Gangopadhyay S (2013) Design, constrcution and performance of Stone Matrix Asphalt (SMA)-Field test section. Highw Res J, 12–25 3. IRC 37 (2012) Tentative guidelines for the design of flexible pavements, Indian roads congress 4. Mouillet V, Séjourné D, Delmotte V, Ritter HJ, Lesueur D (2014) Method of quantification of hydrated lime in asphalt mixtures. Constr Build Mater. https://doi.org/10.1016/j.conbuildmat. 2014.06.063
Effect of Nominal Maximum Aggregate Size and Bitumen Content on Frictional Properties of Different Bituminous Surface Courses Rajan Choudhary, Rajneesh Kumar, Ankush Kumar, Santanu Pathak, and Abhinay Kumar
Abstract Skid resistance, a measure of the force produced when a vehicle tire is prevented from sliding along the road surface, is a salient functional requirement of a pavement surface. Skid resistance is influenced by several factors, such as road surface texture, aggregate characteristics, aggregate gradation, binder content, surface temperature, and environmental conditions (presence of water film). This study investigated the frictional characteristics of three different asphalt surface courses, which included bituminous concrete (BC), open-graded friction course (OGFC), and stone matrix asphalt (SMA). The different factors considered during skid resistance measurement are: dry and wet surface conditions, varying nominal maximum aggregate size (NMAS—BC: 19.0 mm and 13.2 mm; OGFC: 19.0 mm and 12.5 mm; SMA: 13.2 mm and 9.5 mm), and variable binder content/percentage (for BC—5.5, 6.0, and 6.5%; for OGFC: 6.0, 6.5, and 7.0%; for SMA: 6.0, 6.5, and 7.0%). The British pendulum and sand patch test methods were used to evaluate the frictional/skid resistance and surface texture properties of these mixtures, respectively. OGFC mixtures showed better frictional characteristics compared to BC and SMA mixes. Texture depth played an important role in the development of friction, especially during the presence of water over the mix surface. Furthermore, the presence of a water film had a detrimental impact on frictional efficiency, i.e., higher R. Choudhary (B) · R. Kumar · A. Kumar · S. Pathak Department of Civil Engineering, Indian Institute of Technology Guwahati (IIT Guwahati), Assam, India e-mail: [email protected] A. Kumar e-mail: [email protected] S. Pathak e-mail: [email protected] A. Kumar Department of Civil Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India e-mail: [email protected]
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_24
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water depth resulted in lower frictional resistance. Surface texture for different types of asphalt mixes (BC, SMA, and OGFC) had a fairly good correlation with skid resistance under both dry and wet conditions. Keywords Bituminous concrete · Open-graded friction course · Stone matrix asphalt · Skid resistance · British pendulum tester · Sand patch method
1 Introduction Road traffic injuries are one of the major concerns in developing countries, including India leading to the rise in the number of deaths, disabilities, and hospitalization. The rate of vehicle crashes is influenced by several factors, including driver behavior, vehicle condition, environmental effects, highway geometrics, and pavement surface condition. The friction of a pavement/road surface is an important element influencing safe vehicle movement. Pavement friction is a force acting opposite to the direction of vehicular motion that restricts the movement of a vehicle tire relative to the pavement surface [1]. The friction force developed at the contact zone between tire and pavement is also explained as skid resistance. Lack of friction can cause skidding/ slippage of vehicles. Skidding becomes more prominent under wet weather conditions when a thin layer of water serves as a lubricant over the road surface and reduces the friction between the tire and the pavement [2]. A road should have adequate skid resistance for the safe movement of vehicles, especially at higher speeds. A low skidresistant surface is prone to accidents, particularly under wet weather conditions, and thus imposes a threat to human life and loss of economic assets. Construction of a road surface with adequate skid resistance and timely maintenance for retaining the minimum skid resistance is of utmost importance for the safe and efficient movement of vehicles. In the development and maintenance of roads, the friction characteristics of different surface/wearing courses play a crucial role. In India, more than 90% of the roads are flexible in nature [3]. Flexible pavements have a wearing/surface course that have a either dense-graded, gap-graded, or an open-graded aggregate gradation. Aggregate type/gradation, asphalt film thickness (determined in terms of percentage binder content), the surface texture of the road surface, environmental surroundings (presence of water film), and vehicle conditions are key factors that influence the frictional properties of a road surface. Bituminous concrete (BC) is a dense-graded bituminous mixture commonly used as a wearing course for highways in India. It consists of a well-graded blend of aggregates achieved through proportioning of coarse and fine aggregates, and filler, which are then homogeneously mixed and coated with a thin film of bituminous binder. Stone matrix asphalt (SMA), preferred for heavy duty pavement, is a bituminous mixture having a gap-graded aggregate gradation, comprising predominantly of coarse aggregates that enhance rutting resistance by good stone-to-stone contact/ interaction, while a typically higher binder content (5.5–7.0 percent by mixture
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weight) attributes stability and adhesion by raising the thickness of asphalt film around the aggregate particles [4]. Stabilizers, typically fibers, are incorporated in SMA mixtures to aid the reduction of binder draindown. Open-graded friction course (OGFC) is a special type of wearing course, with predominantly uniformly graded aggregates, mainly used to minimize hydroplaning and enhance skid resistance. The uniform aggregate skeleton of OGFC provides a surface course with high porosity that enables surface water to flow laterally through the mixture to the day-lighted edge of the pavement. Coarse aggregate skeleton with high air void content in OGFC creates a surface course with relatively higher permeability, capable of quick drainage/ removal of surface water. Aggregate properties such as geological origin (igneous, sedimentary, and metamorphic), size (coarse and fine, NMAS), gradation, shape (angular and rounded), texture (rough and smooth), and resistance to polishing action by vehicle wheels have a direct influence on skid resistance [5]. Out of all the above-mentioned properties, gradation, shape, and texture of the coarse aggregate are found to significantly influence the skid resistance of a pavement surface. The surface texture of the paving surface also contributes significantly to the skid resistance of the pavement. The overall asperities (micro-texture and macro-texture) of the pavement top layer have the significant influences on skid resistance. Micro-texture refers to the surface irregularities of individual aggregates and is primarily responsible for the adhesion portion of the frictional force, while macro-texture indicates the degree of differences and channels between the aggregate particles in the pavement layer and mainly depends on the aggregate structure/gradation. Micro-texture is observed to provide low-speed pavement surface friction, while macro-texture is primarily liable for high-speed pavement surface friction. Skid resistance changes over time as an action of the tire and environmental factors like temperature and weather conditions. Surface skid resistance is negatively influenced by the temperature. The mechanism involved in the loss of skid resistance due to temperature variations is mainly attributed to hysteresis loss of the vehicle tire. Higher temperatures result in a variation in the skid resistance. Skid resistance is also observed to vary significantly with the season. Long dry weather periods result in the accumulation of fine aggregate particles/debris that is polished off the road surface, resulting in extensive loss of micro-texture and macro-texture. This accumulation of fine aggregate particles, along with other contaminants such as oil and grease, leads to a significant loss in skid resistance. Although heavy precipitation increases pavement macro-texture by clearing drainage channels between aggregates, it also adversely affects frictional resistance when water films form on the pavement surface. The main aim of this study is to evaluate the friction characteristics of three asphalt surface courses, including bituminous concrete (BC), open-graded friction courses (OGFC), and stone matrix asphalt (SMA). This study investigated the influence of nominal maximum aggregate size (NMAS) and percentage binder content (%BC) on the frictional characteristics of the selected surface courses under both wet and dry conditions.
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Table 1 Physical characteristics of aggregates Physical property
Test methods
Results
Combined elongation and flakiness index (%)
IS: 2386 Part 1
16.8
Water absorption (%)
IS: 2386 Part 3
Los Angeles abrasion (%)
IS: 2386 Part 4
22.6
Aggregate crushing (%)
IS: 2386 Part 4
21.7
0.65
2 Materials Selection 2.1 Aggregate Aggregates for this study were obtained from a local stone quarry and were tested for physical requirements as per the guidelines of the Ministry of Road Transport and Highways (MoRTH) [6] and the ASTM D7064 [7] specifications. The selected aggregates met the specified MoRTH and IRC requirements and were suitable for the fabrication of BC, SMA, and OGFC mixes. The physical characteristics of aggregates used in the study are shown in Table 1.
2.2 Bitumen A polymer-modified bitumen conforming to grade 40 (PMB 40) was selected for this study. The bitumen was tested for requirements as per IS 15462 [8]. The test results obtained are presented in Table 2. Table 2 Physical properties of PMB binder
Property
Result
Requirement
Softening point, °C
71.0
Min. 60
Penetration at 25 °C, 0.1 mm
42
30–50
Elastic recovery at 15 °C, %
76
Min. 70
Viscosity at 150 °C, Poise
7.8
3–9
Flash point, °C
>220
Min. 220
Separation test, °C
1.9
Max. 3
Tests on Rolling Thin Film Oven (RTFO) residue Increase in softening point, °C
2.8
Max. 5
Loss in weight, %
0.2
Max. 1
Elastic recovery at 25 °C, %
74.5
Min. 50
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3 Methodology Three wearing course mix types (BC, SMA, and OGFC), each with two different NMAS (BC: 19.0 mm and 13.2 mm; SMA: 13.2 mm and 9.5 mm; OGFC: 19.0 mm and 12.5 mm) were selected for this study. Cylindrical bituminous mix specimens of 150 mm diameter and 50 mm height corresponding to all mix types were prepared using a superpave gyratory compactor. Three replicates of each mix type were fabricated at each of the variable bitumen contents (BC: 5.5, 6.0, and 6.5%; SMA: 6.0, 6.5, and 7.0%; OGFC: 6.0, 6.5, and 7.0%). For the preparation of OGFC and SMA mixes, organic cellulose fibers (0.3% by weight of mix) were also mixed to lessen the potential for binder draindown. The BC and SMA mixes were prepared at an air void content of 4 ± 0.2%, while the OGFC mixes were prepared at 20 ± 1% target air voids at both NMAS. As per the manufacturer’s recommendations, the mixing and compaction temperatures of 170 °C and 160 °C, respectively, were used to prepare the three different mix types. The experimental variables are listed in Table 3, and Figs. 1, 2, and 3 illustrate the aggregate gradations of the three different mix types corresponding to the selected NMAS. One replicate of each wearing course corresponding to its respective NMAS and %BC is also illustrated in Fig. 4.
3.1 Evaluation of Frictional Characteristics British Pendulum Tester: The British pendulum tester (BPT) illustrated in Fig. 5 is the most commonly applied laboratory and field test equipment to ascertain the frictional characteristics of a pavement by assessing the resistance between the rubber slider attached at the end of the pendulum arm and the pavement surface. The BPT measures the skid resistance corresponding to a speed of about 10 kmph in accordance with ASTM E303 [9] specifications. A styrene butadiene copolymer (SBR) rubber block of dimension 76 mm (length) × 25.4 mm (width) × 6.35 mm (thickness) is attached to the pendulum arm and is allowed to slide for a distance of about 12.4– 12.7 cm over the pavement surface to record the resistance offered by it. The friction measurement is shown by a needle on an inscribed gauge, is expressed in British pendulum number (BPN), and is provided as the mean of five measurements. Wetting protocol: Variation of skid resistance owing to the occurrence of a water film over the wearing course was also examined in this study. For this, a water film Table 3 Experimental variables used in this study
Sl. no.
Mix type
NMAS
%BC
1
BC
19.0 and 13.2 mm
5.5, 6.0, and 6.5%
2
OGFC
19.0 and 12.5 mm
6.0, 6.5, and 7.0%
3
SMA
13.2 and 9.5 mm
6.0, 6.5, and 7.0%
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Fig. 1 Aggregate gradation used for BC mixes corresponding to NMAS 19.0 and 13.2 mm
Fig. 2 Aggregate gradation used for SMA mixes corresponding to NMAS 13.2 and 9.5 mm
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Fig. 3 Aggregate gradation used for OGFC mixes corresponding to NMAS 19.0 and 12.5 mm
Fig. 4 Wearing course specimens for evaluation of frictional characteristics
of 1 mm thickness was attained through regular increments of 0.1 mm. The mean theoretical water level was computed as the ratio of sprayed volume of water to the wetted area. The following computations were used to determine the quantity of water to be sprayed over the top of the 150 mm cylindrical mix sample. Volume of required amount of water = π/4 × d 2 × h
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Fig. 5 British pendulum tester used in this study
= π/4 × 152 × 0.01 = 1.77 cm3 where “d” = diameter of the asphalt mix specimen in “cm” and “h” = desired theoretical water depth in “cm”. Thus, 1.77 cm3 of water was uniformly sprayed onto the top of the specimen to obtain the mean theoretical water level of 0.1 mm. This recurring procedure was continued with subsequent 0.1 mm thick water film increments till a total of 1 mm theoretical water depth was achieved. To prevent water from flowing from the test area, a sealant was applied along the edge and bottom of the test specimen. British pendulum test was then conducted over the test specimens to record the BPN values for every 0.1 mm increment in the water film thickness. Mean texture depth evaluation: The texture of the pavement surface is one of the factors that contribute to the manifestation of skid resistance. The skid resistance is affected by two texture levels: micro-texture and macro-texture. Micro-texture refers to wavelengths less than 0.5 mm, and macro-texture refers to wavelengths between 0.5 and 50 mm [10]. Micro-texture is caused by aggregate mineralogy and the roughness of the aggregate particles, whereas macro-texture is caused by asphalt mix characteristics and construction methodology. The mean texture depth (MTD), defined as the average depth of the pavement surface macro-texture, is the most often used measure to quantify macro-texture [11]. The MTD of the bituminous mixtures was evaluated in accordance with ASTM E965 [12] specifications. After the evaluation of frictional characteristics under both dry and wet surface conditions, the specimens were dried completely using a CoreDry® apparatus. The volumetric sand patch technique provided in ASTM E965 was then used to establish the MTD of the samples. It entailed distributing a specified amount of sand (180 to 250-micron sizes) in the shape of a circle on a thoroughly dry and clean test surface using a spreading
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instrument. The spreading continued until the surface voids were flushed with the highest aggregate points. After that, the area covered with sand was measured, and the mean depth between the top of the surface aggregate particles and the bottom of the pavement surface voids was computed as the ratio of the volume of sand to the area of the sand patch, as shown in Eq. 1. MTD =
4V π D2
(1)
where MTD = mean texture depth (mm), V = sand volume (mm3 ), and D = average diameter of the area covered by the material (mm).
4 Results and Discussion 4.1 Frictional Performance Under Surface-Dry Condition The variation of British pendulum number (BPN) for all mix combinations under surface-dry conditions is presented in Figs. 6, 7, and 8. The results of BPN values indicated that the OGFC mix provided the highest frictional resistance, followed by SMA and BC mixtures. BPN values indicate the frictional resistance offered to correspond to a vehicle speed of 10 kmph. BPN values are governed by the microtexture of the asphalt mixture. Micro-texture is an aggregate surface asperity and is higher for coarser aggregate. As the fraction of coarse aggregate is higher for OGFC mixtures compared to SMA and BC mixtures, it is thus expected that OGFC mixtures have a higher micro-texture and correspondingly higher BPN value than the other two mix types/wearing course types. BPN values were found to decrease with a reduction in the NMAS for a given mix type. BPN values were also found to decrease with an increase in the percentage binder content irrespective of the NMAS due to an increase in the asphalt film thickness, which smoothens the surface of the aggregates, thereby reducing its microtexture and subsequently increasing the potential for skidding. These results are also agreeing with the results obtained in other studies where the effect of binder content on frictional properties was reported [11, 12].
4.2 Frictional Performance Under Varying Water Depth The presence of water film over the road surface results in a phenomenon commonly termed hydroplaning or aquaplaning. It is the phenomenon in which a vehicle moving at high speed tends to lose contact with the road surface and appears to drive over a thin film of surface water, thereby resulting in a significant drop in the skid resistance
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Fig. 6 Variation of BPN values for BC mixtures under dry surface conditions
Fig. 7 Variation of BPN values for SMA mixtures under dry surface conditions
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Fig. 8 Variation of BPN values for OGFC mixtures under dry surface conditions
and enhancing the potential for road accidents. In this study, water film thickness over the different wearing courses varied from a depth of 0.1–1.0 mm at an increment of 0.1 mm. The variation of the BPN values with water film thickness for the different mix types is shown in Figs. 9, 10, and 11. It can be observed that for all wearing course mix types used, there was a gradual reduction in the BPN values with an increment in the thickness of water film over the surface. The presence of water film reduces the adhesion component of skid resistance. However, this decrease in the BPN values with an increase in the thickness of water film is not identical for all the three wearing course mix types evaluated. OGFC mixtures showed the least decrease in BPN values, followed by SMA and BC mixtures, considering the BPN values at 0 and 1 mm water depths. This observation can be ascribed to the changes in the surface texture of the wearing courses. OGFC mixtures consist of a large fraction of coarse aggregate, which results in a higher mean texture depth value compared to the other two wearing courses (shown in Figs. 12, 13, and 14). The higher texture depth enhances the breaking of the water film present over the mix surface and is thus able to retain skid-resistant properties to a greater extent. MTD for different types of asphalt mixes (BC, SMA, and OGFC) had a fairly good correlation with dry and wet BPN, demonstrating the effect of pavement surface texture on the skid resistance under both dry and wet conditions (shown in Table 4). Also, for all the mixtures, a drop in the BPN values with water film thickness was reported to escalate with an increment in the percentage binder content (or asphalt film thickness). However, no significant difference in the variation of BPN values with water film thickness was observed for varying NMAS.
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Fig. 9 Variation of BPN values for BC mixtures under wet surface conditions
Fig. 10 Variation of BPN values for SMA mixtures under wet surface conditions
5 Conclusions In terms of road safety, skid resistance, which is a measure of the frictional force produced between a vehicle tire and road surface, is an essential property of a pavement surface. This study attempted a laboratory-scale evaluation of the frictional
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Fig. 11 Variation of BPN values for OGFC mixtures under wet surface conditions
Fig. 12 Variation of MTD values for BC mixtures
properties of bituminous concrete (BC), stone matrix asphalt (SMA), and opengraded friction course (OGFC) bituminous wearing course mixes. The major findings and conclusions of the study are summarized as follows: 1. The variation in the values of British pendulum number (BPN) for the different wearing courses showed that the OGFC surface provided the best frictional resistance, followed by SMA and BC mixes.
308
Fig. 13 Variation of MTD values for SMA mixtures
Fig. 14 Variation of MTD values for OGFC mixtures
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Effect of Nominal Maximum Aggregate Size and Bitumen Content … Table 4 Correlation matrix of MTD with dry and wet BPN
309
Dry BPN
Wet BPN
MTD
Dry BPN
1
–
–
Wet BPN
0.89
1
–
MTD
0.79
0.82
1
2. For all the wearing courses, BPN values were found to decrease with an increase in the percentage binder content due to an expected increase in the asphalt film thickness, which smoothens the surface of the aggregates and thereby reduce its frictional/skid resistance. 3. BPN values increased with an increase in the nominal maximum aggregate size (NMAS). 4. The frictional resistance of BC, SMA, and OGFC mixtures decreased with an increase in the water film thickness. The frictional efficiency of OGFC mixtures in wet conditions was found to be quite better than SMA and BC mixtures. 5. The texture depths of OGFC mixtures were also higher than those of BC and SMA mixtures. 6. MTD for different types of asphalt mixes (BC, SMA, and OGFC) had a fairly good correlation with dry and wet BPN, demonstrating the effect of pavement surface texture on the skid resistance under both dry and wet conditions. Finally, it can be concluded that OGFC mixes exhibited better frictional and textural characteristics compared to conventional dense-graded BC and gap-graded SMA mixtures. OGFC mixes could serve as a safer wearing course option on highway sections that demand higher skid resistance and also for areas with heavy rainfall where safety is a major concern.
References 1. Hall JW, Smith KL, Titus-Glover L, Wambold JC, Yager TJ, Rado Z (2009) Guide for pavement friction. Final report for NCHRP project. National cooperative highway research program, Washington DC, USA 2. Pattanaik ML, Choudhary R, Kumar B (2017) Evaluation of frictional pavement resistance as a function of aggregate physical properties. J Transp Eng Part B: Pavements 143(2):04017003 3. IRC:SP:100 (2014) Use of cold mix technology in construction and maintenance of roads using bitumen emulsion. Indian roads congress, New Delhi, India 4. Brown ER, Cooley LA (1999) Designing stone matrix asphalt mixtures for rut-resistant pavements. National cooperative highway research program. Transportation research board, national research council, Washington DC, USA 5. Ludema KC, Gujrati BD (1973) An analysis of the literature on tire-road skid resistance (No. Rpt. No STP-541) 6. MoRTH (2013) Specification for road and bridge works. Ministry of road transport and highways, 5th ed, Indian roads congress, New Delhi, India 7. ASTM D7064 (2013) Standard practice for open-graded friction course (OGFC) mix design. ASTM international, West Conshohocken, PA
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8. IS 15462 (2004) Polymer and rubber modified bitumen–specification. Bureau of Indian standards, New Delhi, India 9. ASTM E303 (2018) Standard test method for measuring surface frictional properties using the British pendulum tester. ASTM international, West Conshohocken, PA 10. PIARC Technical Committee on Surface Characteristics C.1 (1995) International PIARC experiment to compare and harmonize texture and skid resistance measurements–research report 11. Kogbara RB, Masad EA, Kassem E, Scarpas AT, Anupam K (2016) A state-of-the-art review of parameters influencing measurement and modelling of skid resistance of asphalt pavements. Constr Build Mater 114:602–617 12. ASTM E965 (2019) Standard test method for measuring pavement macrotexture depth using a volumetric technique. ASTM international, West Conshohocken, PA
Dynamic Complex Modulus and Rutting Characteristics of Reclaimed Asphalt Pavement (RAP) Mixes U. Salini and Soorya Ann Koshy
Abstract Reusing pavement materials after reclaiming ensures the conservation of natural resources and becomes an ideal solution to the increasing need for road construction materials. Recycled asphalt or Reclaimed Asphalt Pavement (RAP) is a valid alternative as it decreases the use of virgin aggregates and bitumen in Hot Mix Asphalt (HMA) mixes. The Mechanistic-Empirical Pavement Design Guide emphasizes the modulus/stiffness-based approach for assessing the flexible pavement’s fatigue and rutting criteria. An attempt to estimate the number of load repetitions for the failure of mixes by rutting (msa) using the Dynamic Complex Modulus (E) obtained from the Witczak E Predictive model has been made in this paper. RAP extracted from a Bituminous Concrete (BC) surface was used in the preparation of RAP-HMA mixes, and these mixes were prepared with Natural Rubber-Modified Bitumen (NRMB) and VG 30 as binders. The E-value of RAP-HMA mixes was found when different percentages of RAP (0, 5, 10, 15, 20, and 30%) were added to the virgin aggregates. An increase in the E-value was observed with the increase in RAP in HMA mixes. The mixes prepared with NRMB gave greater E-values, ranging from 3408.2 to 3691.2 MPa, compared to the mixes prepared with VG 30, ranging from 3309.6 to 3412.09 MPa. With an increase in RAP percentages for mixes with both NRMB and VG 30, the number of load repetitions for failure by rutting also increased. Keywords Reclaimed asphalt pavement (RAP) · Natural rubber-modified bitumen (NRMB) · Dynamic modulus · Witczak predictive model
U. Salini (B) KSCSTE – National Transportation Planning and Research Centre, Thiruvananthapuram, India e-mail: [email protected] S. A. Koshy Rajiv Gandhi Institute of Technology Kottayam, Pampady, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_25
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1 Introduction The road construction industry identified the potential struggle it will face in future due to the lack of availability of construction materials, so the focus has now shifted from conventional construction techniques to sustainable construction practices. Reclaimed Asphalt Pavement (RAP) is one such practice where the milled-out aggregates and binder from the existing pavement are reused in the production of new HMA mixes, thereby leading to the preservation of the natural resources. The concept of reclaiming materials from the existing pavement and reusing them was practiced way back in 1915. This technique has substantiated roots now and is widely adopted in the paving industry all over the world. One of the significant design parameters in the Mechanistic-Empirical Pavement Design Guide (MEPDG) is the force–deformation characteristics of a viscoelastic material, expressed in terms of stiffness. Dynamic complex modulus is the measure of the stiffness of a viscoelastic material computed from the responses of the pavement, including strain, deflection, and stress. The complex modulus is an intricate quantity, whose real part signifies the elastic stiffness while the internal damping of the materials is represented by the imaginary part. The absolute value of the complex modulus is identified as the dynamic complex. It is proposed by the Mechanistic-Empirical Pavement Design Guide (MEPDG) as a significant material characterization property and is a crucial input parameter that connects material attributes to field fatigue cracking and rutting performance. In the present study, the dynamic modulus of the RAP-HMA mix was predicted using the Witczak E predictive model. The influence of the HMA surface E-value on the strains in the underlying pavement layers was simulated using KENLAYER software. The computed vertical strain over the subgrade was used to evaluate the number of load repetitions for failure by rutting in million standard axles for the RAP-HMA mix using the 90% reliability equation in IRC: 37-2018 [13].
1.1 Background and Objectives Taylor [23] showed that the success of recycling technology depends entirely on effective laboratory control. The life of recycled bituminous surfacing is observed to be longer than the surfacing prepared from entirely new materials. The serviceability of pavement layers with recycled mixes produced by the central plant was found to be similar to that of pavements with conventional virgin mixes [9]. Around 12 to 55% savings in cost was obtained using recycled materials in bituminous mixes when compared to virgin bituminous mixes [3]. With the use of softer grade bitumen along with a rejuvenator, bituminous mixes containing recycled materials were found to perform better than conventional virgin bituminous mixes [24]. Also, the use of stiffer
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grade bitumen along with the lower percentage of recycled materials in foamed bituminous mixes was found to improve moisture susceptibility and permanent deformation [20]. It was found that it would be possible to produce mixes with a high percentage of recycled materials that would serve as a surface, binder, and base layer by regulating the homogeneousness of recycled material and employing bitumen with the appropriate rheological qualities [8, 14, 16]. Sullivan [22] and Christensen [9] identified that rehabilitation projects of old asphalt pavements produce a significant amount of RAP. Bituminous pavements are milled out for resurfacing, removed fully for reconstruction due to severe distresses or dug out to obtain access to underground utilities. RAP characterization before its use is important as the removed pavement material collected from a source will not be the same as from another source. The amount of RAP in the mix affects the performance of the mix especially if RAP content is high as it can lead to undesirable stiffening of the mix. The blending of the existing aged bitumen in the RAP with the virgin binder increases the stiffness of the resulting mix thereby producing an efficient and successful RAP mixture. But extreme stiffness of the binder can lead to a brittle mix prone to cracking and the workability decreases. The excess stiffening of the binder can be prevented by the use of binder of softer grade than the RAP binder. Experimental investigations on RAP mixes show that at RAP contents below 15%, its effect on the properties of the mix is insignificant [13, 15]. AASHTO M 323-10 [1], the guidelines for choosing a binder for RAP mixtures were developed on the idea that the virgin and RAP binder would blend fully, however in reality, the blending ranges between none to complete blending. Bonaquist [7] and Copeland [10] employed mix properties like dynamic modulus to determine the blended binder properties and compared them with the binder properties measured. According to Witczak [26], the dynamic modulus is a crucial parameter used in evaluating the rutting and fatigue cracking distress prediction in the MEPDG. For a material exposed to sinusoidal loading, dynamic modulus is defined in AASHTO TP 79, 2010 [3] as the absolute value of complex modulus taken as the ratio of the peak-to-peak stress to the peak-to-peak strain [21, 24]. AASHTO TP 62 [4] provides the guidelines for measuring Dynamic modulus in the laboratory. The new Witczak model [25] demonstrated superior prediction to other models such as the old Witczak model [26] and the Hirsch model [9], according to a statistical analysis carried out to compare the three prediction methods by Bari and Witczak [8]. The major study objectives are (a) to compute the dynamic modulus of RAPHMA mixes employing Witczak E predictive equation (b) to evaluate the stress– strain response of RAP-HMA mixes using the software KENLAYER, especially the vertical compressive strain over the subgrade and (c) to estimate the number of load repetitions that the pavement can withstand before failure by rutting from the 90 percent reliability equation specified in IRC: 37-2018 [13]. Two virgin binders have been used in this study, NRMB and VG 30, for the preparation of the RAP-HMA mix. The performance of the mixes was also verified in the laboratory by conducting Indirect Tensile Strength (ITS) test, moisture susceptibility test, and wheel rut test. The tensile strength of the bituminous mixtures was determined by carrying out
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the indirect tensile strength test (ITS) as per ASTM D 6931-12 [5] on dry and wet samples. Tensile strength ratio (TSR), which shows the moisture susceptibility of the mix was found in accordance with AASHTO T 283 [2]. It is the ratio of ITS of water conditioned specimen (which is soaked in water for 24 h at 25 ºC) to that of the unconditioned specimen.
2 Witczak E Predictive Equation Model Mathew W. Witczak in 1972 developed an empirical model for predicting mixture stiffness for various temperature ranges, loading rate, aging, etc., from the mix design and material properties. The sigmoidal function utilized for defining the relationship between loading rate and dynamic modulus is the basis of this model. The Witczak predictive equation, projected in AASHTO 2002 Design Guide, and the Hirsch model are the most commonly used for envisaging the dynamic modulus of different bituminous mixtures. The Witczak predictive equation model is given in Eq. (1). LogE = −0.261 + 0.008225X 200 − 0.00000101(X 200 )2 + 0.00196X 4 − 0.03157Va [ − 0.415
]
1.87 + 0.002808X 4 + 0.0000404X 38
−0.0001786(X 38 )2 + 0.016X 34 Vbeff + Vbeff + Va 1 + e(0.716log f −0.7425logμ)
(1)
where E is the mixture dynamic modulus, in 105 psi, log (µ) is obtained from the penetration–viscosity relation by Mirza and Walczak [16] as log (μ) = 10.5012 − 2.2501 log (P) + 0.00389 log (P)2 where P is the penetration for 100 g binder under 5 s of loading expressed in 0.1 mm; μ is the viscosity in Poise; f is the frequency of load in Hz; V beff is the percentage effective bitumen content, by volume; V a is the percentage air voids in the mix, by volume; X 200 is the percentage passing No. 200 sieve, by total aggregate weight; X 4 is the percentage retained on No. 4 sieve, by total aggregate weight (cumulative); X 38 is the percentage retained on 3/8-in. sieve, by total aggregate weight (cumulative); and X 34 is the percentage retained on 3/4-in. sieve, by total aggregate weight (cumulative).
3 Simulation Using KENLAYER KENPAVE is a simulating software from which stresses and strains at given thickness of the pavement can be obtained. In the present study, KENLAYER was used to determine the vertical strain that causes rutting under the center of a dual tire
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assembly. Load group was considered as dual wheel assembly, with contact pressure as 560 kPa and contact radius as 10.66 cm. The number of load repetitions for failure by rutting in million standard axles (msa) for the HMA mixes with RAP is obtained from the 90% reliability equation given in IRC: 37-2018, which is given in Eq. (2). The critical vertical strain corresponds to the strain over the subgrade layer directly under the middle of the dual wheel assembly, that is, in the present study, strain at 56 cm depth is the critical vertical strain. N = 1.41 × 10−08 × [1/εv ]4.5337
(2)
where N is the number of cumulative standard axles and εv is the vertical strain in the subgrade.
4 Materials To prepare a RAP-HMA mix the RAP collected from national highway in Thiruvananthapuram, virgin aggregates from quarry in Thiruvananthapuram and bitumen from Bharat Petroleum Corporation Limited, Kochi was used.
4.1 Reclaimed Material Reclamation of materials from pavement surface can be done by the methods like milling, ripping, or breaking of exiting pavement layer. A two lane National Highway (NH-47) at Karakkamandapam in Trivandrum District, Kerala was to be upgraded to four lanes from Karamana to Kaliyikkavila for a length of 5.5 km. The RAP was milled out from this road stretch with the help of a backhoe and care was taken to scarify only the surface layer. As per the PWD, Kerala records the pavement surface constituted bituminous concrete mix with NRMB as binder and was laid 6 years before widening project. The gradation of the extracted RAP falls within the gradation limits specified in Ministry of Road Transport and Highways (MoRTH) [19] for BC mix, as shown in Fig. 1. The bitumen was extracted from RAP using centrifugal extractor following ASTM D 2172-11 guidelines and the binder content was estimated to be 5.03%. The gradation of the reclaimed material is shown along with the BC gradation in Fig. 1.
4.2 Virgin Aggregates and Bitumen Crushed angular granite stone aggregates of varying sizes obtained from a local stone quarry with crusher unit, Blue Star Industries, Thiruvananthapuram district was used
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100 90 Percentage passing
80 70 60
RAP GRADATION BC Upper range BC Lower range BC mid range
50 40 30 20 10 0 0
2
4
6
8 10 12 Sieve size (mm)
14
16
18
20
Fig. 1 RAP and BC gradation
Table 1 Properties of asphalt binder VG 30 and NRMB 70 Property
VG 30 Result
Specification
Softening point (R and B) (ºC)
54
Min 47
59
Min 55
IS:1205-1978
Ductility at 27 °C (cm)
90
Min 75
>100
Min 50
IS:1208-1978
NRMB 70 Result
Standard code Specification
Specific gravity
1.01
Min0.99
1.012
Min 0.99
IS:1202-1978
Penetration at 25 °C,5secs,1/ 10 mm
64
50–70
68
50–89
IS:1203-1978
3000 ± 600
5
2–6
IS:1206 part II
Viscosity at 150 2895 °C (Poise)
as virgin aggregate for the preparation of RAP-HMA mix. Viscosity-Grade bitumen (VG 30) and NRMB 70 from Bharat Petroleum Corporation Limited, Kochi were the virgin binders added for the preparation of the mix. The properties of the asphalt binders are given in Table1.
5 Methodology In order to estimate the dynamic modulus and rutting characteristics of RAP-HMA mix, firstly, the material characteristics and the proportion of materials to form a perfect blend of RAP and virgin material were determined. As the RAP was scarified
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from a BC surface, the binder content in RAP was found by extracting the binder using centrifuge extractor. Also the aggregate gradation of the RAP after bitumen extraction was found out by conducting sieve analysis. The RAP was combined with virgin aggregate at percentages of 0, 5, 10, 20, and 30%. By trial-and-error method, the RAP and virgin aggregates were mixed to obtain the BC-II gradation. Dynamic complex modulus of the mixes was estimated from the Witczak’s E-predictive model. The number of load repetitions for failure by rutting was found from the empirical equation in IRC-37:2018 for which the vertical compressive strain above the subgrade was obtained from KENLAYER simulations. Also in addition to the determination of dynamic modulus and rut characteristics, the performance of these HMA-RAP mixes was assessed from the indirect tensile strength, TSR, and rut depth. Rutting characteristics of RAP mixtures were evaluated using a Hamburg wheel tracking device (HWTD).
6 Results and Discussions 6.1 Dynamic Properties of RAP-HMA Mixes The properties of RAP-HMA mixes which are utilized for computation of dynamic modulus and the dynamic modulus obtained from Witczak predictive equation model are shown in Table 2. In this study, the dynamic modulus of the virgin BC-II mixes when prepared with VG 30 and NRMB is found to be 3310 MPa and 3408 MPa, respectively, as shown in Fig. 4. It can be seen that the addition of RAP led to an increase in E-value in case of both the binders. This is because the RAP tends to make the mixture stiffer. The mixes prepared with NRMB have higher E-value compared to the mixes prepared with VG 30. At RAP percentage of 30, the mix prepared with NRMB has the highest E-value of 3691 MPa. Thus, the mixes with NRMB have higher resistance to rut deformation under traffic loading. Thus, modified binders perform better when added along the hardened binder of RAP compared to unmodified binders.
6.2 Performance of RAP-HMA Mixes Using KENLAYER Simulations The number of load repetitions for failure by rutting in msa for the RAP-HMA mixes evaluated based on 90% reliability is given in Table 3. The critical vertical strain corresponds to the strain on the top of the subgrade layer directly under the center of the dual wheel assembly, that is, for the present study, the strain at 56 cm depth is taken as the critical vertical strain. The number (no.) of load repetitions for failure by rutting and the corresponding critical vertical strain are shown in Fig. 2.
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Table 2 Dynamic complex modulus at different RAP–Virgin aggregate percentages Binder
RAP and V (%)
Gmb
Va
P200
P4
P38
Vbeff
µ
E (MPa)
NRMB
RAP0% + 100%V
2.351
4.2
7
38
22
6.021
2.46
3408
RAP 5% + 95%V
2.35
3.9
6.83
37.78
21.15
6.133
2.46
3425
RAP10% + 90%V
2.352
3.859
6.65
38.02
20.76
6.083
2.46
3444
RAP15% + 85%V
2.39
3.892
6.9
38.2
21.16
5.276
2.46
3564
RAP20% + 80%V
2.393
4.08
6.3
37.93
21.04
4.799
2.46
3591
RAP30% + 70%V
2.432
3.99
7
37.4
21.13
4.458
2.46
3691
RAP0% + 100%V
2.366
4
7
38
22
5.754
2.46
3310
RAP 5% + 95%V
2.364
4.1
6.83
37.78
21.15
5.63
2.79
3340
RAP10% + 90%V
2.366
4.06
6.65
38.02
20.76
5.622
2.79
3344
RAP15% + 85%V
2.362
4.1
6.9
38.2
21.16
5.651
2.79
3354
RAP20% + 80%V
2.386
3.93
6.3
37.93
21.04
5.314
2.79
3398
RAP30% + 70%V
2.504
4.35
7
37.4
21.13
5.054
2.79
3412
VG 30
(%)
From the performance evaluation KENLAYER, it is observed that an increase in the RAP content led to a rise in the number of load repetitions for the failure by rutting. The comparison of VG 30 and NRMB mixes showed that for BC grade-II mix with 30% RAP with NRMB as the binder is more resistant to rutting. Table 3 Critical vertical strain for different percentages of RAP Binder
RAP and virgin (V) E aggregate percentage (MPa)
NRMB RAP 0% + 100%V RAP 5% + 95%V
VG 30
Critical vertical strain (in No. of load repetitions for the order of 10^-4) failure by rutting (msa)
3408.2 1.575
2452.50
3425.2 1.574
2459.57
RAP 10% + 90%V
3443.5 1.574
2459.57
RAP 15% + 85%V
3563.6 1.569
2495.30
RAP 20% + 80%V
3590.5 1.568
2502.53
RAP 30% + 70%V
3691.2 1.564
2531.68
RAP 0% + 100%V
3309.6 1.579
2424.45
RAP 5% + 95%V
3339.9 1.578
2431.43
RAP 10% + 90%V
3343.7 1.578
2431.43
RAP 15% + 85%V
3353.7 1.577
2438.43
RAP 20% + 80%V
3397.7 1.575
2452.50
RAP 30% + 70%V
3412.0 1.575
2452.50
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Fig. 2 E (MPa) and number of load repetitions to failure by rutting of RAP-HMA mix
6.3 Performance of RAP-HMA Mixes The inclusion of RAP resulted in the rise in ITS up to 20% RAP and thereafter a slight decrease in ITS was observed as can be seen in Fig. 3. Rut depth decreased for both NRMB and VG 30 binders. Compared to the mixes with VG 30, the mixes with NRMB demonstrated greater resilience to rutting. The TSR and rutting resistance for all the HMA-RAP mixes are as indicated in Figs. 4 and 5, respectively. From the test results, it is also visible that a rise in dosage of RAP has led to an increased rutting resistance of the mix e to rutting owing to the presence of aged and stiffer binder in the RAP. Even though the mixes fulfilled the minimum criteria for TSR of 80%, it is visible that the rise in RAP content has increased the vulnerability of the mix to moisture and can be further rectified by the use of anti-stripping agents [20].
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VG 30
2500
NRMB
ITS (kPa)
2000 1500 1000 500 0 0
5
10 15 RAP(%)
20
30
20
30
TSR (%)
Fig. 3 ITS of RAP-HMA mixes VG 30
100 90 80 70 60 50 40 30 20 10 0 0
Fig. 4 TSR of RAP-HMA mixes
5
NRMB
10 15 RAP(%)
Dynamic Complex Modulus and Rutting Characteristics of Reclaimed …
3.5
VG30
321
NRMB
Rut Depth, mm
3 2.5 2 1.5 1 0.5 0 0
5
10
15
20
30
RAP (%) Fig. 5 Rut depth of RAP-HMA mixes
7 Conclusion The ITS and rutting behavior of HMA-RAP mixes was assessed by conducting laboratory studies. The mixes were prepared using NRMB and VG 30 binders at different percentages of RAP (0, 5, 10, 15, 20, and 30%). The major objectives of the study were to determine the dynamic modulus using Witczak E predictive equation for selected RAP-HMA mixes and to evaluate their stress–strain response using KENLAYER software. Following were the conclusions drawn from the study. . The dynamic modulus (E)-value improved on addition of RAP in HMA mixes. The mixes prepared with NRMB have higher E-value compared to the mixes prepared with VG 30. . The increased dosage of RAP in the mix lead to a rise in the number of load repetitions for the failure by rutting.
References 1. AASHTO M 323 (2013) Standard specification for Superpave volumetric mix design, standard specifications for transportation materials and methods of sampling and testing, 30th ed, AASHTO, Washington DC, USA 2. AASHTO T-283 (2021) Standard method of test for resistance of compacted bituminous mixture to moisture induced damage, AASHTO, Washington DC, USA 3. AASHTO: TP-79 (2010) Determining the dynamic modulus and flow number for hot mix asphalt (HMA) using the asphalt mixture performance tester (AMPT). American association of state highway and transportation officials, Washington DC, USA
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4. AASHTO TP 62 (2007) Standard method of test for determining dynamic modulus of hot-mix asphalt (HMA). American association of state highway and transportation officials, Washington DC, USA 5. ASTM D 6931-12 (2012) Standard test method for indirect tensile (IDT) strength of bituminous mixtures, American society for testing and materials, West Conshohocken, Pennysylvania, USA 6. Bari J, Witczak MW (2006) Development of a new revised version of the Witczak E* predictive model for hot mix asphalt mixtures (with discussion). J Assoc Asph Paving Technol, 75 7. Bonaquist R (2007) Can I run more RAP?. Hot mix asphalt technology, 11–13, National asphalt pavement association, Landham, MD 8. Celauro C, Bernardo C, Gabriele B (2010) Production of innovative, recycled and highperformance asphalt for road pavements. Resour Conserv Recycl 54:337–347 9. Christensen DW, Bonaquist R (2015) Improved Hirsch model for estimating the modulus of hot-mix asphalt. Road Mater Pavement Des 16(sup2):254–274 10. Copeland A, D’Angelo J, Dongre R, Belagutti S, Sholar G (2010) Field evaluation of a high reclaimed asphalt pavement/warm mix asphalt project in Florida: a case study. Transp Res Rec 2179(1):93–101 11. Xiao F, Amirkhanian SN, Juang CH (2007) Rutting resistance of rubberized asphalt concrete pavements containing reclaimed asphalt pavement mixtures. J Mater Civ Eng 19:475–483 12. Epps JA, Little DN, O’Neal RJ, Gallaway BM (1978) Mixture properties of recycled central plant materials. Recycl Bitum Pavements ASTM STP 662:68–103 13. IRC:37-2018, Guidelines for the design of flexible pavements 14. Kupolati WK (2009) Characterization of bitumen extracted from used asphalt pavement. Eur J Sci Res 25:226–233 15. Li X, Marasteanu MO, Williams RC, Clyne TR (2008) Effect of reclaimed asphalt pavement (proportion and type) and binder grade on asphalt mixtures. J Transp Res Board, no 2051, 90–97 (2008) 16. Mirza MW, Witczak MW (1995) Development of a global aging system for short and long term aging of asphalt cements. J Assoc Asph Paving Technol 17. Mc-Bee WC, Sullivan TA, Saylak D (1978) Recycling old asphaltic pavements with sulfur. Recycl Bitum Pavements ASTMSTP 662:123–141 18. McDaniel RS, Soleymani H, Shah A (2002) Use of reclaimed asphalt pavement (RAP) under Superpave specifications: a regional pooled fund study (report no. FHWA/IN/JTRP-2002/6). IDoT, p 69 19. MORTH (2013) Specifications for road and bridge works (fifth revision), Ministry of road transport & highways, India 20. Ping HG, Wing-Gun W (2008) Effects of moisture on strength and permanent deformation of foamed asphalt mix incorporating RECYCLED materials. Constr Build Mater 22:30–40 21. Singh DV, Zaman M, Commuri S (2011) Comparison of hierarchical levels of MEPDG for predicting dynamic modulus of asphalt mix. In: Proceeding of 13th international conference of international association for computer methods and advances in computational mechanics, Melbourne, Australia May 9–11 22. Sullivan J (1996) Pavement recycling executive summary and report (report no. FHWA-SA95-060). Federal highway administration, Washington, DC 23. Taylor NH (1978) Life expectancy of recycled asphalt paving. Recycl Bitum Pavements ASTM STP 662:3–15 24. Widyatmoko I (2008) Mechanistic-empirical mixture design for hot mix asphalt pavement recycling. Constr Build Mater 22(2):77–87 25. Witczak MW (2007) Specification criteria for simple performance tests for rutting. Transp Res Board 580 26. Witczak M, Fonseca O (1996) Revised predictive model for dynamic (complex) modulus of asphalt mixtures. Transp Res Board 1540:15–23
SMART and Intelligent Transportation
Geometry Data Extraction of Existing Horizontal Alignment: A Global Review Report and Methodological Example Mohd Atif
and Gourab Sil
Abstract Roadways are the most popular mode of transportation. However, practitioners, policymakers, enforcement authorities, and researchers do not always hold complete and reliable records of road geometry data (i.e., plan & profile drawings). This study reviewed the existing literature on the extraction of road geometry data. Existing methods are efficient for extracting geometric features of horizontal alignment based on the availability of recourses and applicability. The selection of a suitable methodology depends on various constraints like cost, time, availability of technology, and skilled workforce. Based on the reviewed literature, a cost-effective methodology based on GIS and AutoCAD Civil 3D © is proposed for low- and middle-income countries like India for recreating geometric features of existing horizontal alignments. A 3 km road section was taken inside the IIT Indore campus. Road width, tangent length, curve radius, curve length, and deflection angle were calculated for 17 curves along the road section. Calculated values were validated with the actual values obtained from the field survey method. Statistical analysis has confirmed that the proposed methodology is in good agreement with the actual values. This methodology would be a cost-effective and efficient alternative for extracting road geometry data and evaluating road performance. Keywords Road geometry · Data extraction · Horizontal alignment · GIS
1 Introduction Roadways are the most popular mode of transportation. It is paramount that the operational efficiency, mobility, comfort, safety, and convenience for the motorist of road infrastructure should be ensured according to the guidelines as practicable [1]. For this purpose, the geometry of the roadways is one of the primary influencing factors. However, practitioners, policymakers, enforcement authorities, and researchers do M. Atif (B) · G. Sil Department of Civil Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh 453552, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_26
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not always hold complete and reliable records of road geometry data (i.e., plan & profile drawings) [2, 3]. This problem is prevalent for the roadways constructed in past decades when computerized drawings and the technologies to store them efficiently were unavailable. Furthermore, even if the plan & profile drawings are available, it is not always an easy task to arrange those drawings. Sometimes, certain differences could be found between the as-built road and the plan & profile drawings for several reasons, such as land acquisition, political or social factors, and inaccuracies in construction operations. These practical issues are not rare in the case of low- and middle-income countries like India. The objective of the present study is to . Prepare a review report on the available methods for road geometry data extraction. . Formulate and validate a cost-effective methodology for extracting the geometric features of existing horizontal alignments. The present paper will provide critically reviewed literature explaining the advantages and disadvantages of the available methods. Furthermore, a cost-effective methodology based on the reviewed literature could be beneficial for evaluating the performance (viz., operational efficiency, mobility, comfort, safety, and convenience for the motorist) of any existing roadways.
2 Literature Review Previous studies on road geometry extraction undertaken around the world are presented in Table 1. Various sources such as global positioning system (GPS), geographic information system (GIS) map, AutoCAD digital map, satellite imagery, vision technology, light detection and ranging (LiDAR), and inertial measurement unit (IMU) have been used to extract road geometry data [3]. The instruments used, the length of the road taken, the type of geometric features extracted, and the achieved accuracy are also presented.
2.1 GPS GPS receiver integrated with a surveying vehicle acquires geographical positioning data (latitude and longitude) of the road. Ai and Tsai correctly detected all 25 tested curves (including spiral curves) with GPS and reliably calculated the radii [4]. Gradient was determined in addition to horizontal alignment features with a 0.4% maximum deviation by collecting heading, pitch, and roll data of the survey vehicle [5, 6]. Differential GPS could be used for high precision and accuracy. Roh et al. [7] used a GPS/GLONASS combination to obtain high-precision road geometry positioning data and found it consistent with traditional design drawings. Imran et al. [8] employed a combined GPS-GIS technique for a 25 km section of the twolane rural highway of easter, Ontario. The positional data collected by the GPS was
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Table 1 Previous studies on road geometry extraction Source
Literature
Instruments
Road length (km)
Geometric features
Accuracy (%)
GPS
[4–8]
GPS receiver, Inertial Navigation System (INS), survey vehicle/ mobile mapping system
90
GIS maps
[9–11]
GIS roadway maps and GIS applications
>10
Horizontal curve (length, radius, deflection angle)
>95
AutoCAD digital maps
[12]
Digital Maps
10
Horizontal curve (simple, reverse) radius, deflection angle, spiral length
>95
LiDAR
[3, 18, 19]
Laser scanning system on a survey vehicle/ mobile mapping system
90
Vision technology
[16]
Survey vehicle with cameras
–
Curve radius
>99
IMU
[21, 22]
IMU sensor with survey vehicle/ mobile mapping system
95
analyzed in the ArcView extension. Their methodology has produced quick, accurate (error of less than 5%), and relatively low-cost horizontal alignment of a road.
2.2 GIS Maps GIS maps are low-cost data collection methods that provide complete road network data [9]. ArcGIS is a widely used GIS application for working with maps. ArcGIS
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has tools such as curve calculator and curve extension for curve geometry calculations (curve radius, curve length, and deflection angle). Such tools are ineffective because they need manual tangent detection and calculations. The New Hampshire Department of Transportation developed an improved curve finder tool for curve data extraction [10]. The algorithm of curve finder was based on finding bearing angles between the consecutive vertices of the GIS roadway centerline. A curve is found when the bearing angle exceeds the threshold value. A tangent is found when the bearing angle falls short of the threshold value. Results showed 96.7% accuracy in curve detection for more than 10 km of road section [9]. Moreover, 100% curve detection rates were achieved on low-volume country roads [11]. Rasdorf et al. [10] conducted a comparative study on curve calculator, curve finder, and curve extension. Curvature extension was found to be an excellent fit for individual curve analysis. The curve calculator produced satisfactory results for individual curves with an error of approximately 1% when 8 GIS points existed and less than 0.1% when 25 GIS points existed. Curve finder was found as the best application for network analysis.
2.3 AutoCAD Digital Map A digital map is a cost-effective and time-saving data source for obtaining horizontal alignment geometry [12]. The procedure involved digitizing the road edge line or centerline in the AutoCAD environment and identifying the critical points of curves, i.e., point of curvature (PC) and point of tangent (PT). PC and PT points of the curves were identified using bearing angle measurements. The curve radius, length, and deflection angle were calculated using curve geometry equations.
2.4 Satellite Imagery Satellite imagery can be used for road geometry extraction with automatic and semiautomatic techniques. Zhao and Shibasaki [13] used the semiautomatic approach based on remote sensing software to generate the road mask image containing road pixels. The edges were extracted using straight lines, while long lines with slight direction changes were considered road seeds. As the operator provided the starting point, the following location was chosen by comparing a template to the road mask picture and road seeds. Reverse horizontal curves were extracted by Easa et al. [14] and spiraled horizontal curves were extracted by Dong et al. [15] using IKONOS 1-m spatial imagery. They converted satellite images from color to grayscale and identified the road edges based on changes in brightness level using a Canny edge detector. This method was found accurate in establishing horizontal curves.
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2.5 Vision Technology Roads can be detected using vision technology based on image capture. Tsai et al. [16] developed an algorithm based on vision technology to obtain horizontal curvature data from roadway images. Their methodology was composed of four steps. (1) Extraction of curve edges using image processing technique; (2) mapping edge positions from the image domain to the real-world domain; (3) calibration of camera parameters to eliminate the effects of capturing angles on image quality; (4) measurements of horizontal curves. The results depicted accurate radii for curves (radii < 66 m) with errors of less than 1%.
2.6 LiDAR Mobile mapping systems generally contain LiDAR for capturing road networks with high productivity. Horizontal alignment elements such as straight roads, circular curves, and spirals were extracted based on LiDAR data [17]. The point cloud data within the left and right edges of the pavement were used to model left and right pavement lane markings and the centroid of the detected pavement markings provided by the road centerline. Luo and Li [3] combined IMU and 3D LiDAR systems to extract ramp geometry automatically. The average errors for curve detection and curve radius measurement were 5.89% and 1.99%, respectively, with significance pvalues of 0.621 and 0.989 for longitudinal and cross-slope measurement. Gargoum et al. [18] used LiDAR data to extract the curve radius, length, curve center coordinates, and deflection angle of two 4 km sections of a two-lane highway with an average error of less than 3%. To validate LiDAR data on a large scale, Shalkamy et al. [19] examined 242 km of highways in Alberta, Canada. Road centerline data was extracted to evaluate horizontal curve geometry. The method was found reliable, with 96–100% accuracy.
2.7 IMU Longitudinal road profiles can be measured using an IMU sensor integrated with a surveying vehicle [20]. Ishikawa et al. [21] used D-GPS/DR navigation and GPSGyro/IMU approaches for vehicle localization. Positioning and posture estimation were highly accurate, with 0.073 root mean square (RMS) error for heading, 0.064 RMS error for pitch, and 0.116 RMS error for roll. Luo et al. [22] proposed an automatic curve extraction method based on IMU and 3D profiling data on a 4.35 km road section. The IMU sensor measured the speed and lateral acceleration of the vehicle. Superelevation was measured and calibrated using profile data. The change in heading angle was used to identify the horizontal curve, and the curve radius
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was determined using the kinematic, geometry, and lateral acceleration methods. All three approaches produced good accuracy in radius calculations. However, the results of the kinematic method were close to the actual radius values. The discussed literature has shown different methods for road geometry extraction. However, very few articles have covered all the relevant information. The present paper tried to cover existing methods that would provide a holistic overview of the extraction of road geometry features. The above-discussed methods have their benefits and drawbacks. GPS is one of the techniques for collecting 2D road data points. The GPS receiver integrates with INS and mobile mapping systems containing cameras, scanners, and other sensors [4, 6]. GPS technique has been widely used for the extraction of tangents, horizontal curves, vertical curves, and gradients. The error in calculating geometry features is generally less than 10%. However, a more extensive road network data collection requires substantial efforts and costs. GIS maps are low-cost data collection methods compared to GPS surveys capable of providing comprehensive road network data [9]. GIS roadway maps detect curves with more than 95% accuracy, providing curve geometry features such as length, radius, and deflection angle. AutoCAD digital maps are also low-cost data collection sources that are not updated frequently; thus, they may be outdated. Satellite imagery is one of the inexpensive sources of road geometry data. The quality of the satellite image utilized determines the accuracy of the data. For higher accuracy, high-resolution satellite images are preferred. This technique is capable of extracting simple as well as reverse horizontal curves. High-rise buildings obscure some areas of the roads in GIS maps and satellite images, resulting in incomplete road data. In addition, both approaches only provide 2D horizontal alignment data [3]. Vision-based technology is another efficient way; however, the efficiency of this method depends on the camera, its placement, and calibration. Furthermore, road gradient and cross-slope could influence the camera parameter calibration [3]. This technique has certain limitations and could be further improved to extract geometric features such as curve length, deflection angle of curve, tangent length, and transition length. The actual scene of the road alignment can be measured using LiDAR, which has a high potential for measuring discrete and spatial data. LiDAR sensor has enormous advantages in road data surveying, such as accuracy, time-saving, and high productivity. LiDAR data management, on the other hand, is more complex than other methods because it involves extensive data. As a result, data processing takes a longer time [2]. Furthermore, the instrumentation cost involved in data collection is enormous. The above-discussed methods can be used to extract the horizontal alignment of the road. A surveying vehicle with an IMU sensor can measure road gradient and superelevation. Thus, the IMU sensor can be used to determine road profile data. All the discussed methods can be effective for road geometry extraction based on the availability of resourses and applicability. However, selecting a suitable methodology depends on various constraints like cost, time, availability of technology, and skilled workforce. The primary concern lies in their execution cost. It is highly challenging for low- and middle-income countries like India to execute a methodology that involves substantial cost. GIS maps and satellite imagery are cost-effective methods that can be used to counter this problem. Therefore, a methodology based
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on GIS and AutoCAD Civil 3D is presented to extract the geometric features of an existing horizontal alignment. The proposed methodology can be judiciously selected for geometric data extraction by the practitioners and researchers as per their needs.
3 Methodology Based on GIS and AutoCAD Civil 3D © The geometric features of horizontal alignment, such as road width, tangent length, curve radius, curve length, and deflection angle of curve, were calculated using GIS and AutoCAD Civil 3D ©. The complete methodology of the study is presented in Fig. 1. A 3 km road section inside the IIT Indore campus was selected for the study (Fig. 2). The first site (S1) is a two-lane section of 2 km containing 11 curves. The second site (S2) is a four-lane section of 1 km containing 6 curves. The centerline of the road section was digitized in the google earth pro application using the add path tool. Initially, road width was measured with a ruler tool. Road centerline geocoordinates (latitude and longitude) were obtained and converted into vector format using a global mapper application. AutoCAD Civil 3D © application was used to extract the horizontal alignment of the road section. The geocoordinates of the road centerline in vector format were imported in AutoCAD Civil 3D ©. Imported points were utilized for creating horizontal alignment using create best fit alignment tool. This tool makes the best fit alignment based on the geometry points inserted. The edges of the road were further created using create offset alignment tool. Fig. 1 Methodology framework
Road section
Digitization of road centerline in Google Earth pro Extraction of road centerline geocordinates (Latitude and Longitude) Conversion of road centerline data into vector format in Global Mapper
Importing data in AutoCAD Civil 3D
Recreation of horizontal alignment in AutoCAD Civil 3D
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Fig. 2 Road section
3.1 Validation Field Survey Method The horizontal alignment features calculated using GIS and AutoCAD Civil 3D © were compared to actual values obtained from the field survey method. The road section inside the IIT Indore campus was selected to execute the field survey method effectively. The radius of the curve was calculated in the field based on the chord offset method (Fig. 3) using Eq. (1) [23]. In this method, a chord at or within the limiting points (PC and PT) of a curve is measured. The mid ordinate is measured from the midpoint of the chord to the centreline of the road. PC and PT points were identified by marking the centreline of the curves into various intervals varying from 1 to 3 m. The theodolite was set on the tangent part of the road to fix the line of sight. The first point found with a significant deflection in the line of sight of theodolite was taken as a limiting point (PC or PT) of the curve. The chord length (C) was measured by fixing the theodolite at one of the limiting points (PC or PT) and sighting the other where one surveyor was standing with a leveling staff. The mid ordinate (M), tangent length, and road width were measured with theodolite and leveling staff or tape. Curve length was calculated by counting the marked intervals. R=
4M 2 + C 2 8M
(1)
where R is curve radius in meter, M is mid ordinate in meter, and C is chord length in meter.
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Fig. 3 Chord offset method
4 Results and Discussion Horizontal alignment features calculated with the proposed method and field survey method are presented in Table 2. The variations in calculated and actual values of road width, tangent length, curve radius, curve length, and deflection angle are plotted in Fig. 4. An average error of less than 8% was found for the geometric features. Such errors could be due to inaccuracy in the digitization of the road centerline in Google earth pro. The variation of error along the range of geometric feature values was studied. The variation of error with curve radius shows that the error is random for curves with radii less than 50 m. The plot indicates that after 50 m, the error is likely to decrease with the increase in the magnitude of the curve radius (Fig. 5). Higher accuracy and efficiency can be achieved with advanced digitization methods of road centerline and higher radii (R > 50 m) curves. Single-factor ANOVA was used to determine the statistical significance difference between the calculated and actual values. ANOVA was tested against a 5% significance level for the following hypothesis: H0 = calculated and actual values of horizontal alignment features are same H1 = calculated and actual values of horizontal alignment features are different ANOVA results validated the above findings. Road width (F (1,32) = 0.01, p = 0.91), tangent length (F (1,28) = 0.03, p = 0.86), curve radius (F (1,32) = 0.00, p = 0.99), curve length (F (1,32) = 0.00, p = 0.97), and deflection angles of curve (F (1,32) = 0.00, p = 0.99) were found with no statistically significant difference with the proposed and field survey methods.
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Table 2 Geometric features of horizontal alignment Location
Road width (m)
Tangent length (m)
Curve radius (m)
Curve length (m)
Deflection angle (degree)
A
A
B
A
A
A
B
B
B
B
S1-C1
7
7
248
220
29
28
44
43
90
87
S1-C2
7
7
29
34
16
14
19
20
77
81
S1-C3
7
7
178
166
17
16
10
11
39
36
S1-C4
7
8
169
158
20
18
23
20
66
63
S1-C5
7
7
43
45
18
17
6
6
19
20
S1-C6
7
7
77
75
23
22
9
11
25
26
S1-C7
7
7
52
57
13
15
11
10
36
39
S1-C8
7
7
407
390
32
30
50
44
90
85
S1-C9
7
7
242
226
29
30
46
49
89
91
S1-C10
7
7
126
115
18
16
14
12
41
43
S1-C11
7
7
_
_
18
18
11
13
35
38
S2-C1
14
14
59
55
82
86
74
73
52
52
S2-C2
14
15
72
70
110
114
36
35
18
17
S2-C3
14
14
135
134
247
244
6
6
3
4
S2-C4
15
14
150
149
151
155
6
6
2
3
S2-C5
15
15
73
74
214
212
22
23
6
6
S2-C6
14
15
_
_
91
88
29
28
18
18
where A is the proposed method, B is the field survey method, and S-C represents the combination of site and curve
Fig. 4 Error calculations for geometric features
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Error (%)
10 8 6 4 2 0 0
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100 150 Curve radius (m)
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Fig. 5 Variation of error with curve radius
5 Conclusion The present paper reviews the existing literature for the extraction of road geometry data. GPS, IMU, and LIDAR efficiently extract horizontal and vertical alignment features but could be expensive for network data extraction as the data collection system relies on a survey vehicle [3, 5–8, 18, 19, 21, 22]. Vision technology has substantial potential in accuracy but needs further improvement to extract geometric features [16]. The economic sources are GIS maps, AutoCAD digital maps, and satellite imagery [9–12, 14, 15]. They can be used for extracting horizontal alignment features. In simple words, GPS, GIS maps, AutoCAD digital maps, satellite imagery, vision technology, LiDAR, and IMU methods can be effective for road geometry data extraction based on the availability of resourses and applicability. The selection of a suitable methodology depends on various constraints like cost, time, availability of technology, and skilled workforce. For low- and middle-income countries like India, it is feasible to adopt a cost-effective methodology as an alternative for the estimation of roadway geometric features. Therefore, a cost-effective methodology based on GIS and AutoCAD Civil 3D © was applied and validated on a 3 km road section of the IIT Indore campus. This methodology was suitable for extracting road width, tangent length, curve radius, curve length, and deflection angle of curve for the two-lane and four-lane roads. The obtained results are promising and consistent with the previous studies [3–5, 7, 8, 18, 19]. The proposed methodology would be a good fit for highways as the error depends on the magnitude of the geometric feature. This study focused on the low-cost methodology for extracting horizontal alignment geometric features. The validation process is executed on two-lane and four-lane roads of the IIT Indore campus. Therefore, future studies could explore highways with significant geometric variations to get robust validation. Furthermore, an efficient methodology by optimizing the error for both horizontal and vertical alignment features of road highways could provide holistic applicability to the data extraction process. Practitioners can use the proposed method or select another method from the
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review report to extract the existing alignment geometric data. The extracted geometry would be used as influencing (i.e., independent) input parameters to evaluate the roadway performance, like consistency, vehicle stability, single-vehicle safety, etc., for geometric effects of the existing roadway alignment. Acknowledgements The authors would like to thank the Department of Civil Engineering, Indian Institute of Technology Indore, for their support. The financial support from the Science and Engineering Research Board (SERB) under the project: Analysis and Modelling of Drivers’ Perception and Performance of Operational Measures for Geometric Design Consistency and Safety Evaluation of High-Speed Roadways (SRG/2021/002117) is acknowledged. The authors would also like to thank Mr. Arvind Mehta, Mr. Akshay Jangam, Mr. Mohd Amin Khan, Mr. Shudhashil Ghosh, and Mr. Vinay Sharma for their support in data collection.
References 1. AASHTO: A policy on geometric design of highways and streets. AASHTO, Washington, DC (2011) 2. Marinelli G, Bassani M, Piras M, Lingua AM (2017) Mobile mapping systems and spatial data collection strategies assessment in the identification of horizontal alignment of highways. Transp Res Part C Emerg Technol 79:257–273. https://doi.org/10.1016/J.TRC.2017.03.020 3. Luo W, Li L (2018) Automatic geometry measurement for curved ramps using inertial measurement unit and 3D LiDAR system. Autom Constr 94:214–232. https://doi.org/10.1016/J.AUT CON.2018.07.004 4. Ai C, Tsai Y (2015) Automatic horizontal curve identification and measurement method using GPS data. J Transp Eng 141(2):04014078. https://doi.org/10.1061/(ASCE)TE.1943-5436.000 0740 5. Awuah-Baffour R, Sarasua W, Dixon KK, Bachman W, Guensler R (1997) Global positioning system with an attitude: method for collecting roadway grade and superelevation data. Transp Res Rec 1592(1):144–150. https://doi.org/10.3141/1592-17 6. Di Mascio P, Di Vito M, Loprencipe G, Ragnoli A (2012) Procedure to determine the geometry of road alignment using GPS data. Procedia Soc Behav Sci 53:1202–1215. https://doi.org/10. 1016/J.SBSPRO.2012.09.969 7. Roh T-H, Seo D-J, Lee J-C (2003) An accuracy analysis for horizontal alignment of road by the kinematic GPS/GLONASS combination. KSCE J Civ Eng 7(1):73–79. https://doi.org/10. 1007/BF02841990 8. Imran M, Hassan Y, Patterson D (2006) GPS–GIS-based procedure for tracking vehicle path on horizontal alignments. Comput-Aided Civ Infrastruct Eng 21:383–394. https://doi.org/10. 1111/J.1467-8667.2006.00444.X 9. Li Z, Chitturi M, Bill A, Noyce D (2012) Automated identification and extraction of horizontal curve information from geographic information system roadway maps. Transp Res Rec 2291(1):80–92. https://doi.org/10.3141/2291-10 10. Rasdorf W, Findley DJ, Charles, Zegeer V, Sundstrom CA, Hummer JE, Asce F (2012) Evaluation of GIS applications for horizontal curve data collection. J Comput Civ Eng 26(2):191–203.https://doi.org/10.1061/(ASCE)CP.1943-5487 11. Li Z, Chitturi Mv, Bill AR, Zheng D, Noyce DA (2015) Automated extraction of horizontal curve information for low-volume roads. Transp Res Rec 2472(1):172–184. https://doi.org/10. 3141/2472-20 12. Hashim IH, Bird RN (2005) Operating speed behaviour models for single rural carriagewayscase study of north East of England. In: Proceedings of the 37th annual conference, universities’ transport study group. Newcastle University
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13. Zhao H, Kumagai J, Nakagawa M, Shibasaki R (2002) Semi-automatic road extraction from high-resolution satellite image. In: International archives of the photogrammetry, remote sensing and spatial information sciences—ISPRS archives 14. Easa SM, Dong H, Li J (2007) Use of satellite imagery for establishing road horizontal alignments. J Sur Eng 133:29–35. https://doi.org/10.1061/(ASCE)0733-9453(2007)133:1(29) 15. Dong H, Easa SM, Li J (2007) Approximate extraction of spiralled horizontal curves from satellite imagery. J Surv Eng 133:36–40. https://doi.org/10.1061/(ASCE)0733-9453(2007)133: 1(36) 16. Tsai YJ, Wu J, Wang Z, Hu Z (2010) Horizontal roadway curvature computation algorithm using vision technology. Comput-Aided Civ Infrastruct Eng 25:78–88. https://doi.org/10.1111/ j.1467-8667.2009.00622.x 17. Holgado-Barco A, González-Aguilera D, Arias-Sanchez P, Martinez-Sanchez J (2015) Semiautomatic extraction of road horizontal alignment from a mobile LiDAR system. Comput-Aided Civ Infrastruct Eng 30:217–228. https://doi.org/10.1111/MICE.12087 18. Gargoum S, El-Basyouny K, Sabbagh J (2018) Automated extraction of horizontal curve attributes using LiDAR data. Transp Res Rec 2672(42):98–106. https://doi.org/10.1177/036 1198118758685 19. Shalkamy A, Karsten L, Gargoum S, El-Basyouny K (2020) A framework to detect horizontal curves and assess their geometric properties from remotely sensed point clouds. Int J Remote Sens 41(21):8328–8351. https://doi.org/10.1080/01431161.2020.1771792 20. Gim J, Ahn C (2018) IMU-based virtual road profile sensor for vehicle localization. Sensors 18(10):3344. https://doi.org/10.3390/S18103344 21. Ishikawa K, Amano Y, Hashizume T, Takiguchi JI (2007) A study of precise road feature localization using mobile mapping system. In: IEEE/ASME international conference on advanced intelligent mechatronics, AIM. https://doi.org/10.1109/AIM.2007.4412541 22. Luo W, Li L, Wang KCP (2016) Automated pavement horizontal curve measurement methods based on inertial measurement unit and 3D profiling data. J Traffic Transp Eng (English Edition) 3:137–145. https://doi.org/10.1016/J.JTTE.2016.03.004 23. Findley DJ, Foyle RS (2009) Procedure for identification and investigation of horizontal curves with insufficient superelevation rates
Development of Incident Management System for Efficient Usage of Transportation Infrastructure Gurmesh Sihag, Praveen Kumar, and Manoranjan Parida
Abstract Various agencies are investing a tremendous amount of budget in improving roadway conditions; however, congestion problems are not solved. For the highway congestion challenges, merely expanding the capacity of the roadway segment is not an efficient solution because highway congestion is not just a problem of reoccurring “rush hour” delays in urban areas. Non-recurring type congestion, triggered by incidents like accidents, disabled vehicles, severe weather, work zones, special events, and other temporary interruptions to the highway transportation system, also has a significant share. Hence, there is a need to develop Traffic Incident Management systems to control these non-recurring congestions to use available transportation infrastructure efficiently. In the present study, the incident management system is developed to manage the incidents on Madhya Marg (Chandigarh) employing Ant System Algorithm and Blackboard Architecture. Travel time data required for the development of the incident management system is obtained by conducting a speed and delay study by the floating method. The journey time is classified into peak/off-peak/normal flow time based on the results of the traffic volume study. The current study develops a diversion equation also to anticipate the traffic diverted if route diversion information is available. Keywords Incident management system · Ant system algorithm · Blackboard architecture
G. Sihag · P. Kumar (B) Indian Institute of Technology Roorkee, Roorkee, Uttrakhand 247667, India e-mail: [email protected] M. Parida CSIR-Central Road Research Institute (CRRI), New Delhi 110025, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_27
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1 Introduction Many countries consider traffic incidents to be a high-priority problem because incidents can have negative consequences such as the increased likelihood of secondary crashes, increasing fuel consumption and air pollution, and increasing traffic congestion levels. According to the studies conducted worldwide, secondary incidents account for roughly one-quarter of all incidents. Because of the serious consequences of incidents, there is a need to improve traffic incident management effectiveness. Traffic incident management is defined as the use of available resources to mitigate the effects of traffic incidents and reduce the duration of the incident. Improving the efficiency of the TIM process requires an understanding of various activities involved in the process. Incident management is a complex activity comprising many activities ranging from incident detection to various clearance operations and emergency services [1]. It involves different agencies like Police, Fire Brigade, etc. Hence, Manual coordination of varying personnel involved in incident management is not possible. So, the need for a computer program (Software) arises [2]. The present study develops an incident management system in the form of a computer program by using C# programing language and Microsoft Visual Studio software. The program uses Ant System Algorithm [3] to find the shortest route under both incident and no incident conditions. Under the incident condition, the link having the incident is removed, or the impedance on the link is increased based on the type of incident. The program is developed based on the Blackboard architecture. Deployment of this program is expected to reduce the response time by providing the shortest route to reach the incident site and recovery time by providing an alternate route to the users.
2 Literature Review 2.1 Ant Colony Optimization Algorithms At present, the Dijkstra algorithm, Floyd algorithm, and A* algorithm are most commonly used to solve shortest path problems in transportation planning. Although each method has its own advantages and adaptability, Ant colony optimization algorithms’ unique advantages in solving many complex optimization problems have attracted the attention of researchers working in the field of transportation planning to solve the shortest path problem. Ant colony optimization (ACO) is a relatively new technique for approximate optimization. In the early 1990s, Marco Dorigo and colleagues [4] developed the first ACO algorithms. These algorithms are inspired by the observations of the foraging behavior of real ants.
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Ants have the ability to deposit a material known as pheromone on the surface as they travel to and from the sources of food. Ants searching for food perceive the presence of pheromone and take the path on which the concentration of pheromone is higher. By following this mechanism, Ants transport food from the source to their nest remarkably effectively. Deneubourg and colleagues [5] used a binary bridge experiment to study the pheromone laying and following behavior of the ants. In this experiment, the Food source was connected to ants’ nests by two bridges of equal length. At starting, individual ants chose one of the bridges randomly. However, after a while, more ants started following one of the bridges because of the more pheromone deposited on that bridge and the tendency of the ants to follow the path of higher pheromone concentration. Finally, all ants of the colony chose the same bridge. Goss and colleagues [6] also carried out a similar experiment, but they used two bridges of unequal length. In this experiment, the bridge’s initial choice fluctuations were significantly reduced as compared to Deneubourg’s experiment. In this case, ants choosing the shorter bridge reached the food earlier than the ants choosing the long bridge and, while returning, chose the shorter bridge. It was because of the higher pheromone concentration on that bridge. The use of the shorter bridge further increased the pheromone concentration on it. As a result, in this experiment, all ants quickly converged to the shorter bridge. Various studies have shown that ants’ indirect communication via pheromone trails (called stigmergy) allows them to find the shortest paths between their nest and sources of food. Various ant colony optimization algorithms are available in the literature [7, 8], e.g., Ant System., Maximum-minimum Ant System, Ant Colony System, Elitist Ant System, etc. Ant System Algorithm was the first ant colony optimization algorithm proposed in the literature. In this algorithm, the probability of kth Ant following the link i-j (pk ij ) is given by Eq. (1).
pikj =
⎧ ⎪ ⎪ ⎪ ⎨
β
τiαj .ηi j , i f j ∈ allowedk Σ β τilα .ηil
l ∈ allowedk ⎪ ⎪ ⎪ ⎩ 0 other wise
(1)
where τij is the pheromone concentration on the link (i, j); ηij is the inverse of the length of link (i, j); allowedk is the list of links that the kth Ant has not yet visited; and α and β are the parameters which govern the relative importance of the pheromone concentration and the heuristic information ηij . The pheromone updating rule for τij is as follows: τi j ← (1 − ρ).τi j +
m Σ k=1
Δτikj
(2)
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where ρ is the rate of evaporation, m is the total number of ants, and Δτij k is the amount of pheromone laid per unit length on edge (i, j) by the kth Ant and is calculated by using Eq. (3): ⎧ ⎨ Q , i f ant k used edge (i, j ) in its tour Δτikj = L k ⎩ 0 other wise
(3)
where Lk is the kth Ant’s tour length and Q is a constant. In the literature, Ant colony optimization algorithms have proven to be effective in realizing dynamic traffic routing also [9, 10]. So, in the present study, the ant colony optimization algorithm is used to solve the shortest route optimization problem.
2.2 Blackboard Architecture The blackboard architecture tries to emulate a team of problem solvers (experts) to solve a problem by gathering around a blackboard. The blackboard, in this case, corresponds to a shared memory that facilitates communication and cooperation among the group members. The group members are experts or sources of knowledge that contribute to the incremental development of a solution. Here blackboard is used to hold the solution state and computational data produced and required by the knowledge sources. There are three essential components of blackboard architecture: Knowledge sources, blackboard data structure, and Control Unit [11]. The control unit is used to make runtime decisions about which knowledge sources to execute next for the optimal problem solution.
2.3 Incident Management Incident management is defined as a coordinated, planned, and systematic use of technical, human, mechanical, and institutional resources to reduce incidents’ impact and duration [12]. Incident management increases the safety of incident responders, crash victims, and motorists. The use of these resources also improves highway mobility, operating efficiency, and safety by systematically bringing down the time required to detect and verify incident occurrences. Incident management is achieved by setting an appropriate response and clearing the incident safely while controlling the affected flow until the flow becomes normal. Or in other words, Incident management is the synchronization of activities undertaken by various agencies to bring traffic flow to normal condition after an incident has occurred.
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Fig. 1 Timeline of a typical incident management process
Incident management involves a recognizable series of activities undertaken by persons from various response organizations and agencies [13]. Different constituents of incident duration and the timeline of a general incident management process are illustrated in Fig. 1.
3 Study Area and Data Collection Madhya Marg in Chandigarh is selected as the study area for the current study. Chandigarh’s traffic and transportation problems are growing overnight because of the marginal increase in road infrastructure and the rapid increase in the use of motorized vehicles. Madhya Marg connecting Panchkula at one end to PGI on the other end is counted among the important roads of Chandigarh and provides access to many educational institutes, shopping centers, and offices. It also offers direct and the shortest link between the towns of Kalka, Pinjore, Chandimandir Cantonment, Panchkula in Haryana, Baddi, Parwanoo, Shimla, etc. in the state of Himachal Pradesh, Anandpur Sahib, Kharar, Mullanpur, etc. in Punjab. Hence, traffic across the tri-city further worsens the traffic congestion problem on Madhya Marg. So, the present study attempts to mitigate the traffic congestion problem on Madhya Marg by managing the traffic effectively with the help of an incident management system. Traffic volume count was done to classify the time of the day into peak/offpeak/normal flow time and develop the speed-flow relationship for the study area. Classified traffic volume count was done in two shifts of 5 h each from 7:00 to 12:00 and 16:00 to 21:00, with 15 min of counting and 15 min of break. Traffic volume count was also done from 3 to 4 am to determine the wee-hour traffic flow.
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Travel time data required for the development of the incident management system was collected by conducting the speed and delay study by the floating car method. The main reason behind selecting the floating car method was to ensure that the travel time measured was free from the delay caused due to incidents. Five test runs were performed in each traffic flow condition (peak flow, normal flow, and wee-hours to consider the temporal variation of travel time in analyzing the road network). A stated preference type survey was also conducted as a part of the current study to develop the diversion equation to anticipate the traffic diverted if route diversion information is available. Respondents of the survey were chosen from the users of the Madhya Marg meticulously to ensure that the sample is a true representation of the population in terms of gender, age, education level, occupation, etc.
4 Methodology In the present study, an incident management system is developed in the form of a computer program. The computer program was made using the C# programing language and Microsoft Visual Studio software. In the present study, various personnel involved in incident management are grouped into three categories: Road users, Response Team, and traffic management team. Road users can find the shortest route under the prevailing traffic conditions and can see the location and type of incident that occurred on the Madhya Marg. These services offered to the road users are termed as open services, as these are open to everyone and do not require any login to the program. The response team involves the agencies involved in the clearance process of the incident. It includes crane service providers, towing service providers, local police, etc., as well as emergency services like firefighting, emergency medical services, etc. Response team members can send and view the messages to the noticeboard visible to all response team members as well as traffic management team members. The traffic management team is the central control group in this program and includes all the persons who are involved in planning the strategies for traffic management. So, the members of the traffic management team are given additional power to add/remove the incident on the road network and edit the ant colony optimization algorithm used to find the shortest route. The services offered to the response team and traffic management teams are termed as reserved services as access to these services is limited to the members of the teams only and require login to the computer program. In the incident management system developed in the current study, response team members act as knowledge sources, the notice board visible to all personnel involved in the incident management act as a blackboard data structure, and traffic management team members act as the control unit. Figure 2 shows the flow chart of various steps involved in the ant system algorithm used to find the shortest route for managing the incidents in the current study.
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Fig. 2 Flow chart for ant system algorithm used
4.1 Start of Ant Algorithm At the starting, a pheromone of the amount equal to the initial pheromone intensity (τ0 ) is distributed to all the links of the network. All the ants (i.e., equal to the total no. of ants, m) are positioned on the origin node (i.e., starting node). Also, the variable global minimum route length (LGlobalMini ) is set to a larger value, say, 1.0 × 1010 .
4.2 Ant’s Route Generation In this step, the probability of movement of all ants positioned at the origin node (say, node r) to the next valid node (say node s) is calculated. This probability of movement of ants from node r to node s is given by Eq. (4) [8, 14] and is dependent on the length of the link r-s and the pheromone concentration on link r-s
pk(r,s)
⎧ [τ (r, s)]β .[η(r, s)]β ⎪ ⎪ , i f s ∈ Jk (r ) ⎨ Σ [τ (r, u)]β .[η(r, u)]β = u∈J (r ) k ⎪ ⎪ ⎩ 0 other wise
(4)
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where τ (r, s) is the pheromone concentration on the link (r, s), and for the first iteration, it will have a value equal to τ0 ; η (r, s) is known as the impedance function, and the value of η (r, s) is the multiplicative inverse of the length of the link r-s, i.e., η (r, s) = 1//length of the link (r, s); Jk (r) defines the list of nodes which are connected with the node r and are yet not visited by ant k, and β is a constant. From Eq. (4), it can be noted that the probability of movement of Ant to the node having a larger link length connection with node r will be less than that of the node having a smaller link length connection with node r. The probability of ant “k” moving from node r to nodes that are not connected to node r will be zero. So, each Ant will have a new location and a new Jk (r) list. This process of finding probabilities of movement and transferring ants to the new node is iterated until the conditions listed below are met: • All of the ants have arrived at the destination node. • Some ants have arrived at the destination node while the rest ants are dead ants. Dead ants are the ants that have not arrived at their destination node and whose Jk (r) list is the null set, i.e., they don’t have any valid node for their transfer. The iteration process is terminated when all ants other than the dead ants have arrived at the destination node because dead ants have no further solution for their route.
4.3 Link Pheromone Intensity Updating When all ants reach the destination or some ants reach the destination, and others are dead ants, then one iteration of the ant system algorithm is completed. In the next step, pheromone concentration on the network links is updated according to Eq. (5) [15]. τi j ← (1 − ρ).τi j +
m Σ
Δτikj
(5)
k=1
where ⎧ ⎨ Q , i f edge(i, j ) belongs to the r oute o f the best ant k k Δτi j = L k ⎩ 0 other wise
(6)
where ρ is the rate of pheromone evaporation, (1-ρ) denotes the fraction of pheromone concentration that remained on the link, and it has a value less than 1; Lk is the route length or trip length of the Ant following the shortest route; Q is a constant with a value greater than 1.
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Ant following the shortest route is also known as the best Ant in the terminology of ant colony optimization algorithms. There may be more than one best Ant if there are ants having equal minimum route lengths. In the first iteration, the best Ant’s total route length is always less than the value of the variable global minimum route length (LGlobalMini ). From Eqs. (5) and (6), it is clear that all the links of the network will lose a fraction of the pheromone concentration after every iteration because of the evaporation, but all the links used in best Ant’s route will have additional pheromone concentration equal to Q/Lk .
4.4 Setting Value of Global Minimum Route Length The best Ants’ trip length or route length (Lk ) is compared to the minimum route length (LGlobalMini ), and if the value of the best Ant’s route length (Lk ) is less than the value of the variable minimum route length (LGlobalMini ), then the value of the variable (LGlobalMini ) is set equal to the route length of the best Ant. ( L Global Mini =
L k , i f L k < L Global Mini L Global Mini other wise
(7)
4.5 Check for End Conditions After updating the pheromone concentration, the procedure from the Ants’ route generation step is repeated with the updated link pheromone concentration values. This iteration process is continued till one of the following conditions is met: • All of the ants take the same path from the origin node to the destination node. • Or the specified number of iterations has been reached. If the end conditions are met, the route chosen by all ants or the maximum number of ants will be the shortest route between the origin and destination nodes. Figure 3 shows the flow chart of the overall functioning of the program developed. The performance of ACO algorithms is sensitive to the changes in parameters. Hence, all the six parameters (Number of Ants, Number of iterations, Beta, Rho, Q, and Initial Pheromone) of the ACO algorithm used in the present study were calibrated for the network considered in the study. Also, a provision to edit the parameters is added to the computer program developed in the study in case recalibration is required due to changes in network characteristics.
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Fig. 3 Flow chart of the overall functioning of the program
5 Results and Demonstration of the Program Developed Figure 4 shows the variation in traffic volume with the time of the day. From Fig. 4, it can be observed that the study area has a morning peak hour from 9:00 to 10:00 (possibly due to the work trips as Madhya marg provides access to the offices and educational institutes), while the evening peak hour is from 17:00 to 18:00 (possibly due to return work trips and recreational trips as Madhya Marg proves access to the shopping centers). So, based on the results of the traffic volume study, journey time can be classified into peak flow time if journey time is from 9:00 to 10:00 or 17:00 to 18:00 and off-peak time if journey time is from 23:00 to 05:00. If journey time is other than above mentioned time, it can be classified as normal flow time. Traffic volume count was also done from 3:00 am to 4:00 am to know the wee-hours flow, which was found to be 435 pcu per hour. To obtain the travel time data required to develop the incident management system speed and delay study was conducted by the floating car method. Test runs were made during peak hours, normal flow time, and off-peak hours obtained from the traffic volume study. Speed-flow data obtained from the speed and delay study were also used to develop a relationship between speed and volume which can be used to find travel time on the network if traffic volume is input to the program. The speed-flow relationship was obtained by performing regression analysis and is shown in Eq. (8). R2 coefficient for the equation developed was 0.773.
PCU/15 Minutes
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800 689 700 602 544 516 600 484.5 463.5 445.5 424 416.5 500 408 408 394 376.5 369.5388 400 315.5 307.5 265 300 199.5184 200 100 0
Time of the Day Fig. 4 Variation of traffic volume with the time of the day
q = 70.92 × Vs − 0.86 × Vs2
(8)
A diversion equation was also developed by conducting a stated preference type of survey on various users of the Madhya Marg to know beforehand how much traffic will be diverted to the alternate route if the Variable Message Sign (VMS) shows the route diversion message is installed. Respondents for the survey were chosen meticulously to ensure that the sample is a true representation of the population in terms of gender, age, education level, occupation, etc. The diversion equation was developed by performing regression analysis on the survey data and taking % diversion (Percentage of the respondents taking alternate route) as an independent variable and time and distance saved as the dependent variable. This diversion equation developed is shown in Eq. (9). R2 coefficient of the equation developed was 0.725. Note in Eq. (9), travel time saved is in minutes and distance saved is in km. Diver sion (%) = 8.04 × T ime Saved−10.876 × Distance Saved + 43.205 (9) Figure 5 shows the snapshot of the home window, traffic management team member window, and shortest route-finding window with input data as well as the result page. From Fig. 5, it can be noted that the shortest route result page shows the input data and corresponding shortest route as well as the shortest route length. The shortest route-finding window of the program requires input in 3 steps. Step 1 requires Origin and Destination input. Step 2 asks for the impedance to be used in finding the shortest route. Either distance or time can be used as impedance. If the distance is chosen as the impedance, then there is no input data for step 3, but if the impedance selected is time, then either traffic volume (For Finding Shortest Route by the incident management team) at the time of the journey or the time of journey (For finding shortest route by Road users) is to be input as Step 3.
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Fig. 5 Snapshot of the program developed
6 Conclusions The present study develops an incident management system for Madhya Marg in Chandigarh by using blackboard architecture and an ant system algorithm. Data required to develop the incident management system was obtained by conducting the traffic volume study and speed and delay in the study area. Morning and evening peaks were found from 9:00 to 10:00 and 17:00 to 18:00. The incident management system was developed in the form of a computer program using Microsoft visual studio and c# programming language. The program developed is geographically transferable by just changing the road network data. In the Incident management system developed in the current study, various agencies involved in the incident management can communicate through a single platform using blackboard architecture. In this program, incidents on the network can be added by only authorized persons, while the location of these added incidents can be seen by all agency personnel involved in managing the incidents. The program provides the shortest route based on either distance or time by using the Ant System Algorithm and provides the feature of editing parameters of the Ant System Algorithm as per the requirement. The program developed in the current study has the limitation that it cannot detect the incidents automatically. In the future, a model can be developed and incorporated into the program, which will automatically detect the incident based on the detection of abnormality in the traffic flow pattern.
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Annexure-Survey Questionnaire
References 1. Ram Kumar PE (2000) Incident management using intelligent transport system. University of Roorkee, Roorkee 2. Kumar P, Jain SS, Kumar Rama PE (2002) Computer software for incident management. Highway Res Bull (HRB) 66:173–188 3. Kumar P, Mishra S (2013) Artificial swarm intelligence for attaining the objectives of intelligent transport systems. Int J Eng Res Technol (IJERT) 6:75–78 4. Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B Cybern 26:29–41 5. Deneubourg JL, Aron S, Goss S, Pasteels JM (1990) The self-organizing exploratory pattern of the argentine ant. J Insect Behav 3 6. Goss S, Aron S, Deneubourg JL (1989) Self-organized shortcuts in the argentine ant. Naturwissenschaften 76:579–581
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7. Kumar P, Mishra S (2015) Application of swarm intelligence in road network design—a review. Indian Highways 43:13–23 8. Suman S (2011) Web GIS-based advanced public transport system using MapServer and ant algorithm. Indian Institute of Technology Roorkee, Roorkee 9. Cong Z, Schutter BD, Babuška R (2013) Ant colony routing algorithm for freeway networks. Transp Res C 37:1–19 10. Jabbarpour MR, Noor RM, Khokhar RH (2015) Green vehicle traffic routing system using ant-based algorithm. J Netw Comput Appl 58:294–302 11. Kumar P, Sihag G, Mishra S (2018) Development of incident management system using ant system algorithm and blackboard architecture. Indian Highways 46:39–47 12. Farradyne P (2000) Traffic incident management handbook. US Department of Transportation, Washington DC 13. Owens N, Armstrong A, Sullivan P, Mitchell C, Newton D, Brewster R, Trego T (2010) Traffic incident management handbook. Federal Highway Administration, Washington DC 14. Suman S, Kumar P (2014) Ant colony optimization algorithms for vehicle routing, route planning, and scheduling. Highway Res J 7:55–65 15. Kumar P, Suman S, Mishra S (2014) Shortest route finding by ant system algorithm in web geographical information system-based advanced traveler information system. J Eng 10:563– 573
Connected Autonomous Vehicles (CAV) Testbed at IIT Hyderabad Digvijay S. Pawar, Ankit Singh, and Rajalakshmi Pachamuthu
Abstract The future holds a surprise for all of mankind, depending on how we strive to move towards a more sustainable and safer road environment. The inclusion of connected and autonomous vehicles (CAVs) into the traffic streams of many developed countries has led to higher levels of road safety and driver satisfaction. India, with a booming vehicle ownership rate and heterogenous traffic system, needs to give the connected autonomous vehicles inclusion a serious thought to help make roads safer and efficient. This paper aims to describe the development of CAV testbed at Indian Institute of Technology Hyderabad (IITH) and the challenges faced in planned controllable environment setting for the developing world traffic. The testbed facility provides a well-developed infrastructure to aid the testing of unmanned terrestrial and aerial vehicles in a controlled environment. The testbed is equipped with a road network consisting of multiple road type combinations such as single-lane, twolane, multi-lane roads with both bituminous and concrete road surfaces which will be further integrated with IITH campus roads. Additionally, the added infra capabilities include signalized, unsignalized intersections, rotary intersection, parking facility, bus stops with and without bus bays, pedestrian crossing facilities, ITSenabled traffic signals, roadside unit (RSU), smart poles with sprinkler pipes for rain simulation, and variable message signs (VMS) for dynamic speed and route guiding, etc. The CAV use cases discussed in the paper are of great significance, as they emulate naturalistic conditions under which the CAVs are expected to perform and improve traffic safety and efficiency. Keywords Connected Autonomous Vehicle (CAV) · Testbed · Use case D. S. Pawar (B) · A. Singh Department of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India e-mail: [email protected] A. Singh e-mail: [email protected] R. Pachamuthu Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_28
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1 Introduction With the advancements in the area of research in sensor devices, robotics, and intelligent transport systems, we can foresee connected and autonomous vehicles taking over conventional manually driven vehicles. Since these vehicles are equipped with technology that helps them sense the road infrastructure and detect other vehicles around them with the least input from the human driver, this greatly reduces the cognitive burden and physical exhaustion of driving. According to research [1], fully autonomous driving will have a 50% market share by 2050. The inclusion of connected autonomous vehicles into the conventional vehicle traffic stream has a high potential of increasing road safety [2, 3], increasing road capacity, lesser fuel consumption, and scarce carbon emissions [4]. It has also been observed that penetration of CAVs in heterogeneous traffic conditions improved the traffic flow stability and traffic efficiency, particularly under congested traffic conditions [5]. Despite the benefits of autonomous vehicles, integrating them into the current traffic scenario poses some severe obstacles. One such problem is adapting to existing road infrastructure and operating in a mixed-fleet environment where ‘nonintelligent’ cars account for a major portion of the fleet. Also, the upkeep of the sensors, communication technologies and other assisting entities plays a major role in this transition from a manual to an autonomous era. In India, where there is a preponderance of non-conventional vehicles, non-standard highway design, and a diverse mix of various categories of road users using the same road space, there are numerous inherent problems for CAV operation to be addressed. Among the most essential factors for making autonomous and connected vehicles more acceptable to the consumer society is to exhibit their effectiveness in realistic conditions. However, employing operational roadway infrastructure as experimental test tracks for autonomous and connected vehicles may become hazardous, certainly in terms of safety. Also, unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) testing may cause expensive sensors and other components to be damaged. As a result, it is crucial to evaluate new technologies in a safe, controlled environment before deploying them. Limited testbeds or proving grounds exist worldwide to investigate the operation of unmanned and connected vehicles in a controlled environment by simulating various scenarios that may occur in reallife traffic operations, ranging from frequently occurring to extreme cases. In the Indian subcontinent, there is presently no such testbed facility for assessing vehicle performance. As a result, in order to adapt technology linked to unmanned connected vehicles and make it safe and implementable in India, IIT Hyderabad has embarked on a massive and ambitious research project on Autonomous Navigation and Data Acquisition Systems through an efficiently developed Technology Innovation Hub, TiHAN.
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2 Review of Existing Testbeds A few CAV testbed facilities and proving grounds have been developed around the world in recent years. The existing testbed facilities have been discussed in Table 1. with respect to the following aspects: (i) Coverage, (ii) Road features, and (iii) Equipment and facilities. A thorough study of these existing testbeds and their features was carried out to finalize the suitable infrastructure, technology, and equipment required to develop TiHAN CAV testbed facility at IIT Hyderabad.
3 IIT Hyderabad CAV Testbed Facility Technology Innovation Hub on Autonomous Navigation and Data Acquisition Systems (TiHAN) established at IIT Hyderabad, is a multi-departmental effort that has received participation and support from prestigious institutions and industry. Funded by the Department of Science and Technology (DST) under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) Government of India, this hub focuses on addressing various challenges impeding the real-time adoption of unmanned autonomous vehicles for both terrestrial and aerial applications, with a strong emphasis on the research and development of interdisciplinary technologies in the specific domain area of “Autonomous Navigation and Data Acquisition systems.” we intend on focusing our efforts through this hub on the study and development of technologies that can address the aforementioned difficulties, allowing for the production of high-value applications in various sectors. Figure 1 illustrates the detailed layout of the CAV testbed facility developed at IIT Hyderabad. A simulation platform is provided at the testbed, enabling non-destructive testing of algorithms and prototypes. The testbed can simulate a wide range of real-life scenarios. In the case of UGVs, some of these scenarios include operation and response at junctions between vehicles and autonomous vehicular interactions with non-motorized traffic (cyclists and pedestrians). Other important considerations include Wireless communication between an autonomous vehicle (AV) and roadside unit (RSU), control transition between manual and autonomous operation, and public acceptance of driverless vehicles. The autonomous vehicle testbed also features sign boards, dummy pedestrians and an underpass (tunnel). Various facets of the Testbed are addressed in detail in the subsections to follow.
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Table 1 Features of existing testbeds Testbed facility
Coverage
Road features
Equipment and facilities
Millbrook Proving Ground, UK [6]
700 acres
Bituminous pavement, concrete pavement, unpaved surface, rough road, kerbs, speed humps, noise generating surface, bus stop, parking bay, wet surface, driveway ramps, multilane roadway, straight section and sharp curves, etc
5G network for V2X, software development for CAVs, mechanical integration facility, lane departure warning, lane keep assist, active cruise control and parking assistance systems, etc
M-City—Michigan Proving Ground, Michigan, USA [7]
32 acres
Paved/unpaved roads, roundabout, tunnel, tree canopy, multilane roadway, rain simulator, blind curve, ramps, signalized and unsignalized intersections, etc
Augmented reality-based AV testing, 5G network for V2X, traffic flow modelling and simulation, different weather conditions, driverless public bus, wireless, fibre optics, Ethernet, real-time kinematic positioning system, etc
Centre of Excellence 4.5 acres for Testing and Research of Autonomous Vehicles (CETRAN), NTU, Singapore [8]
Bituminous and concrete pavement, s-course, flood simulator, rain simulator, parking, traffic signals, kerbs, gradients, speed humps, etc
Weather conditions simulator, driverless public buses, traffic situations, necessary standards and testing regimes for AVs, etc
K-City, South Korea [9]
28.5 km long road network
Bituminous and concrete pavement, unpaved road, bus lane, cycle lane, bus stop, roundabout, school zone, on-road parking, tunnel, work zones, side walk, ramps, rail road intersections, toll gate etc
Impact test facility, crash test facility, noise, EMC test facility, tire assessment test facility, various driving conditions, etc
Josato Test Center, Japan Automobile Research Institute (JARI), Japan [10]
Oval track size- Paved and unpaved road, 5,500 m long high-speed oval track, long straight lanes, handling and braking test track, slippery test track, noise vibration test track, dirt track area, etc
Hydrogen and fuel cell vehicle safety evaluation facility, bus rapid transit system, camera, radar, etc
Connected Autonomous Vehicles (CAV) Testbed at IIT Hyderabad
Fig. 1 CAV testbed layout at IIT Hyderabad
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3.1 Testbed Features for Connected and Autonomous Vehicles The following subsections describe testbed features in detail:
(i) Basic Roadway Layout. As illustrated in Fig. 1, the layout contains a range of roadway types such as urban roads, multilane highways, collector streets, local streets, cement concrete roads, curved sections, rough unpaved road, open test area, S-course (Refer Fig. 2a), etc. The primary goal is to examine how connected and autonomous vehicles react and adapt to different types of roadways in terms of maintaining safe speeds and performing seamless navigation. The overall length of the roadway is about 800 m, with two large stretches of around 175 m and 200 m running parallel to each other, forming a circuit for continuous movement and testing of vehicles. (ii) Additional Road Infrastructure. The additional road infrastructure includes signalised and unsignalized intersections (Refer Fig. 2b), roundabouts,
Fig. 2 Infrastructure at test bed
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bus stops with and without bus bay (Refer Fig. 2c), pedestrian crossing facilities (Refer Fig. 2d), speed management measures such as speed humps, traffic barricades, rumble strips, etc. (iii) Supporting Infrastructure. The testbed facility also includes infrastructure support systems which are essential to provide a network for communication between connected and unmanned vehicles and the infrastructure. They include ITS-enabled traffic signals, smart poles (equipped with sprinkler pipes for rainfall simulation, Refer Fig. 2e), variable message sign boards (for dynamic speed and route guidance) (Refer Fig. 2f), and road signs.
3.2 Facilities for Drones and UAVs 1. Drone Runway. The layout consists of a multilane highway that is 205 m in length and 10.5 m in width. The landing and take-off of medium-sized fixed-wing drones will take place on this multilane highway. (Refer to Fig. 2g). 2. Controlled Drone Test Centre. It comprises a netted area for controlled testing of vertical take-off and landing (VTOL) type of drone. As sand serves as a shock absorber, 1-foot-deep sand flooring is provided which helps reduce the damage to the drone under test. 3. Drone Landing area. This zone is employed for the operation of VTOL drones. The drones are assessed at the controlled drone testing center before their maiden flight on the drone take-off and landing area. The flooring in this region is comprised primarily of half grass and half cement concrete. 4. Hangar and Mechanical Integration Facility. The Integration facility as shown in Fig. 2h, i, is where the drones are assembled by integrating the components. Further modifications to the drones, such as the incorporation of additional sensors, are possible here. A hangar is a facility where developed drones are housed before and after flights. The hangar stands 7.5 m tall.
3.3 Other Facilities The other facilities available at the testbed include a control room, researcher’s sitting space, conference room, hangar for drone integration, storeroom, and server room.
3.4 Use Case Scenarios The feasibility of the V2X safety applications in Indian mixed traffic conditions was analyzed using road crash data and driver’s perceptions of these technologies. The influencing factors affecting road crashes were investigated by implementing the
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Fig. 3 Summary of driver rating of safety warning systems
Association Rule Mining (ARM) on road crash data collected from First Information Reports (FIR) and Road Accident Sampling System India (RASSI). Also, the driver’s perceptions about this new technology in Indian conditions were analyzed using a questionnaire survey form. The ARM and driver’s perception survey results were used to prioritize and rank the twenty-six V2X safety applications for Indian mixed traffic conditions. Figure 3 shows the summary of driver rating of safety warning systems. Research has shown the effectiveness of field operation tests in validating the inclusion of autonomous vehicles in the conventional traffic stream [11, 12]. The use case scenarios that can be emulated [13, 14] at the testbed facility at IIT Hyderabad have been discussed in Table 2. The pictorial representation of a few of the discussed use cases have been shown in Fig. 4. The ego vehicle (CAV under test) works in tandem with the RSU, to safely maneuver under critical road conditions. The use cases represented in Fig. 4. are (a) Intersection collision warning, (b) Emergency vehicle warning, (c) Stationary vehicle warning, (d) Hazardous location warning, (e) Vulnerable road user (VRU) warning, (f) Speed limit warning.
4 Challenges Encountered During Testbed Development The development of the testbed did not come easy, the team had a plethora of hurdles to overcome. Aside from the development and installation of the CAV testbed, which cost around Rs. 7 crores, some of the other challenges encountered are as follows: (i) The need for comprehensive research on CAV testbed’s already in use around the world; (ii) The selection of the most critical use case scenarios to be tested at the testbed facility; (iii) Management of the land area available at the project’s inception, with the main goal being to fit all of the necessary road infrastructure amenities into the 2-acre land area; (iv) Manpower and machinery arrangements during the facility’s design and construction phase, particularly during the COVID-19 lockdown period; (v) Road infrastructure construction required to emulate the use cases.
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Table 2 CAV use case scenario’s Use case No.
Use case type
Brief description
1
Intersection collision warning
Prevent/mitigate collision between vehicles at intersections by warning the driver. When a vehicle approaches a signalised intersection and the driver is distracted away from the road, the system sends a warning message to the driver to warn about the collision risk.
2
Lane change warning
A lane-changing operation without indication could lead to a rear-end collision. The system warns the driver if driving too close to the adjacent lane or crosses the lane without indicating to the vehicles behind.
3
Co-operative forward collision warning
If the minimum headway is not maintained, the system warns the driver of the possibility of a rear-end collision with the vehicle ahead, that is traveling in the same direction.
4
Adverse condition warning
The system detects and alerts the driver of current weather conditions in the surrounding area. During hazy or rainy weather, the system warns the driver to drive cautiously.
5
Signal violation warning
When a driver inadvertently passes a red signal, the system alerts the driver as well as the nearby RSU. The other vehicles approaching the area are then alerted through the RSU.
6
Vulnerable road user (VRU) warning
Any VRU in the vicinity of the vehicle is detected, and the driver is warned about the presence and chances of a possible collision. When a pedestrian is detected on or near the ego vehicle’s (CAV under test) path, the system notifies the driver. In an emergency, the system may also be equipped to take necessary action, such as application of brakes.
7
Overtaking vehicle warning
The overtaking vehicle communicates its intention to overtake the other local vehicles in order to secure its overtaking operation. When a vehicle is attempting to overtake the lead vehicle, it establishes contact with the vehicle in front and the vehicle approaching from the opposite direction, in order to avoid a possible collision and safely complete the overtaking operation.
8
Do not pass warning
The ego vehicle warns the vehicles behind it, to avoid an overtaking operation under the prevailing unsafe conditions.
9
Curve speed warning
The system warns the driver of an impending horizontal curve along the path and may also advise the driver to reduce vehicle speed to safely navigate the curve.
10
Adaptive cruise control The ACC system allows the vehicle to automatically (ACC) system adjust its speed, in order to maintain a safe headway with the leading vehicle. (continued)
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Table 2 (continued) Use case No.
Use case type
Brief description
11
Road hazard warning
When the ego vehicle detects a safety feature (steering, braking, etc.) that is out of its normal state and posing a potential risk to others, it alerts the driver and the nearby RSU.
12
Emergency vehicle warning
When the system detects the presence of an emergency vehicle in the area, it alerts the RSU and other nearby vehicles. (An Ambulance would be given priority to proceed without delay.)
13
Slow vehicle warning
When the system detects the presence of a slower-moving vehicle in the area, it notifies the driver and nearby RSU. Latency can thus be avoided by taking a different travel path.
14
Wrong way driving warning
Any driver driving in the wrong direction of traffic is informed of the predicament, and a warning is issued.
15
Stationary vehicle warning
If a vehicle becomes dangerously immobilized on the road, other approaching vehicles are warned of the dangers associated with this hazardous road condition. Prevents a dangerously immobilized vehicle from being the cause of a series of crashes.
16
Traffic condition warning
The system provides information about the current state of traffic in the area. (For instance, informing about a traffic jam on the road ahead.)
17
Co-operative glare reduction system
Under low light or night conditions, When the ego vehicle senses any vehicle approaching from the opposite direction, it automatically switches headlights from high to low beam condition.
18
Hazardous location warning
The system warns the driver of any potentially hazardous situation ahead, whether temporary or permanent. (For example, a major road defect such as a pothole could be a potential hazard.)
19
Co-operative merging assistance system
The driver when approaching a merging road is cautioned about the presence of other vehicles on the other road to avoid a side swipe. If both cars are CAVs, they may co-ordinate the merging process and travel safely along the path ahead.
20
Roadwork warning
The driver is informed about existing roadwork and other related restrictions to vehicles in the area. When in a work zone, RSU sends the information to the system and warns the driver to be cautious.
21
Blind spot warning
If the ego vehicle’s blind-spot zone is occupied by another vehicle traveling in the same direction, the system informs the driver about the scenario. (continued)
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Table 2 (continued) Use case No.
Use case type
Brief description
22
Motorcycle warning
The system warns the vehicle driver about the presence of a motorcycle nearby. Motorcyclists bear heavy losses in the case of the occurrence of an accident, often leading to extreme physical injury.
23
Speed limit warning
If the vehicle exceeds the posted speed limit of the road section, the system warns the driver to slow down immediately.
24
Emergency electronic brake lights system
The ego vehicle informs the nearby RSU, when an emergency brake has been applied by itself or other nearby vehicles, thereby preventing rear-end collisions. (Critical during foggy, heavy rain conditions with low visibility.)
Fig. 4 Representation of a few use cases emulated at IIT Hyderabad testbed
The testbed is under the scope of being further expanded, with the addition of an overpass facility, rail-road intersection, gravel road, etc. to the existing testbed.
5 Conclusion With the world shifting towards autonomous vehicles from conventional vehicles, it is imperative to test and calibrate the speed, acceleration, braking, stability, and safety aspects of the autonomous vehicle. IIT Hyderabad has taken a step forward in this direction to develop an efficiently equipped CAV testbed with a wide variety of
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vehicle test courses, and the technical team is working progressively to develop the testbed further. Potential research impacts: The development of the CAV testbed at IIT Hyderabad is likely to attract companies involved in the development of indigenous autonomous vehicles. This will improve the CAV production rates in India. Thus, lowering CAV purchase prices and increasing their likelihood of becoming a part of the Indian traffic stream. Local CAV availability would encourage researchers to conduct indepth research, expanding India’s potential for autonomous vehicle research. With the CAV industry thriving, the country may see the establishment of newer manufacturing facilities and testbeds, increasing CAV penetration into the traffic stream, thus resulting in safer roads for all and increased job opportunities. With numerous unique features, this connected and unmanned vehicles testbed facility is a one-of-a-kind in the Indian subcontinent. As discussed in the earlier sections the developed testbed is fully equipped with the infrastructure and technology required to test CAVs under heterogeneous traffic conditions. With this, IIT Hyderabad aims to become the epicenter of CAV research and testing. IIT Hyderabad is also willing to offer a helping hand to aid other Research centers and Institution’s in the sector of CAV testing and other related research, ultimately leading to a safer road environment for all mankind. Acknowledgements The authors would like to acknowledge and thank, Department of Science and Technology (DST) under the National Mission on Interdisciplinary Cyber Physical Systems (NM-ICPS), Government of India, for funding this research work through ‘Technical Innovation Hub on Autonomous Navigation and Data Acquisition Systems’ (TiHAN), IIT Hyderabad.
References 1. Kyriakidis M, Happee R, de Winter JCF (2015) Public opinion on automated driving: results of an international questionnaire among 5000 respondents. Transp Res Part F: Traffic Psychol Behav 32:127–140 2. Kent T et al (2020) A connected autonomous vehicle testbed: capabilities, experimental processes and lessons learned. Automation 1(1):17–32 3. Hult R et al (2016) Coordination of cooperative autonomous vehicles: toward safer and more efficient road transportation. IEEE Signal Process Mag 33(6):74–84 4. Liljamo T, Liimatainen H, Pöllänen M (2018) Attitudes and concerns on automated vehicles. Transp Res F: Traffic Psychol Behav 59:24–44 5. Xie D-F, Zhao X-M, He Z (2018) Heterogeneous traffic mixing regular and connected vehicles: modeling and stabilization. IEEE Trans Intell Transp Syst 20(6):2060–2071 6. Millbrook Vehicle Proving Grounds. https://www.millbrook.co.uk/services/proving-grounds/. Last Accessed 14 Apr 2022 7. Mcity Testbed. https://mcity.umich.edu/our-work/mcity-test-facility/. Last Accessed 14 Apr 2022 8. CETRAN—Centre of Excellence for Testing and Research of Autonomous Vehicles—NTU. https://cetran.sg/test-center/. Last Accessed 14 Apr 2022
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9. 5G Communication based Automated Vehicle Test-bed (K-City), Korea-EU Research Centre. https://k-erc.eu/5g-communication-based-automated-vehicle-test-bed-k-city/. Last Accessed 14 Apr 2022 10. Japan Automobile Research Institute (2022) Japan Automobile Research Institute, https:// www.jari.or.jp/en/. Last Accessed 14 Apr 2022 11. Broggi A et al (2014) Proud-public road urban driverless test: architecture and results. In: 2014 IEEE intelligent vehicles symposium proceedings. IEEE 12. Ziegler J et al (2014) Making bertha drive—an autonomous journey on a historic route. IEEE Intell Transp Syst Mag 6(2):8–20 13. De Gelder E, Op den Camp O, de Boer N (2020) Scenario categories for the assessment of automated vehicles. CETRAN, Singapore, Version 1 14. Turnbull, Katherine F et al (2020) Automated and Connected Vehicle (AV/CV) test bed to improve transit, bicycle, and pedestrian safety: Phase II Technical Report. No. FHWA/TX-18/ 0-6875-01-R1, 0-6875-01-R1. Texas A&M Transportation Institute
Community and Social Well-Being and Safety
Measuring Impacts of Delhi-Meerut Expressway on Land Cover and Land Use Aayush Keshri, Aditya Manish Pitale, and Shubhajit Sadhukhan
Abstract The purpose of this study is to analyze the impact of the newly constructed Delhi- Meerut Expressway on the surrounding land use characteristics through spatial analysis. Delhi-Meerut Expressway was announced in early 2013 and completed in late 2021. It starts from the Nizamuddin bridge located in Delhi and terminates at the Partapur area of Meerut city located in Western Uttar Pradesh. For this study, the Delhi-Meerut expressway is selected as a case expressway and its radius of 2000-m buffer zone as the study area. To analyze the change in the characteristics before and after construction, LANDSAT 8-9 OLI data for April 2013 and March 2022 were collected. Remote sensing technology was applied to classify the land use map with seven different types of land use. Geographic information system tools such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI) were also used for analyzing variation in vegetation, built-up, and water-related features, respectively, along the Delhi-Meerut expressway. According to the initial findings of the study, a major increase in the built-up area has taken place between Delhi and Ghaziabad while the least amount of land use development has taken place between Dasna and Partapur, Meerut, which was mostly agricultural and barren land before the development of the expressway. It can be clearly seen in the early phase of construction that most of the area surrounding the expressway was agricultural land or barren land, which is now observed with built structures. On the other hand, a significant reduction in the water-related features and vegetation has been observed along the corridor. The result obtained can be useful for the planners in identifying the direction and trends of change in built-up, vegetation, and water features, along the expressway.
A. Keshri (B) · A. M. Pitale · S. Sadhukhan Centre for Transportation Systems (CTRANS), Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India e-mail: [email protected] A. M. Pitale e-mail: [email protected] S. Sadhukhan e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_29
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Keywords Transport corridor · Impact assessment · Land use development
1 Introduction Humans have brought numerous changes for their advancement, including industrialization and urbanization. The world has been transformed into a fascinating system in which anthropogenic infrastructures, complex processing systems, and urban sprawl have replaced the naturally occurring components. This transformation is taking place at an accelerating rate. Similarly, new road construction has an impact on the population and land use characteristics of an undeveloped area. The introduction of a new road system can hugely change the land use characteristics in the peripheral areas [1]. Expressways are among the most highly regarded roads in the context of the Indian road network, and they are access controlled. Expressways are planned for regulated high-speed vehicular traffic. Traffic congestion and air pollution had become a top priority for the state and central governments as population growth continues to outpace infrastructure capacity. To transfer the traffic load and pollution caused due to Delhi-Meerut bypass road, Delhi-Meerut expressway was planned in the National Capital Region (NCR). Another aim to develop this expressway was to develop Meerut as the new industrial hub for India. The Delhi-Meerut expressway was first planned in early 2013 and the construction of all the four phases was completed in late 2021. Conversion of natural and semi-natural ecosystems, such as forests, grasslands, farmlands, and rivers, into transportation infrastructure is at the core of expressway construction [2]. In the immediate vicinity of an expressway, land use and land cover change significantly. Many studies show that transportation, land use, and population all interact in a feedback relationship [3]. Some urban areas will become more accessible as a result of the construction of transportation facilities and the improvement of transportation conditions. In addition, it encourages the development of new commercial and residential areas and increases the population, improving accessibility [4, 5]. Nevertheless, infrastructure cannot be seen as a savior without drawbacks, as it is not just a socioeconomic phenomenon but also a natural phenomenon [6]. China’s Nanping city has undergone dramatic changes in its terrain and land use types due to the development and operation of expressways. As a result, the ecology was negatively impacted, including the degradation of natural environments [2]. Therefore, ecological equilibrium can be disrupted by development at the cost of nature. However, the Govt. of India focused on building expressways keeping sustainability and the natural environment into consideration. With the construction of the DelhiMeerut Expressway, they had pledged to plant 1,00,000 trees around the corridor [7]. Geographical information systems (GIS) and remote sensing are extensively utilized in research examining changes in land cover, land use characteristics, and population density [8, 9]. For quantitative investigation of land cover changes, GIS provides a spatial statistic and mapping tool for the interpretation and comparison
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of remote sensing pictures recorded over time [10]. Remote sensing technologies and tools like Normalized difference built-up index (NDBI), Normalized difference vegetation index (NDVI), and Normalized difference water index (NDWI) are used to investigate the built-up and natural cover of a region. This paper aims to show changes in the built-up, vegetation cover, and water-related features along the expressway corridor since the announcement of the expressway in early 2013 and then classify those built-ups into seven different land use types, as an effect of the announcement of the expressway. For this purpose, Landsat OLI data between 2013.05.13 and 2022.03.11 have been used. In this paper, Sect. 2 broadly talks about the Study area and its characteristics. Section 3 talks about the approach adopted to conduct the whole study. Section 4 talks about the basis on which primary data was collected on-site. Section 5 is related to the results and discussions related to the study. Lastly, Sect. 6 talks about the conclusion and beneficiaries of this study.
2 Study Area Delhi-Meerut Expressway is located in the National Capital Region (NCR). It covers an area of 55,083 km2 (NCRPB). NCR has a population of 46,069,000 and an urbanization level of 62.6% (Census 2011). It is one of the most populated regions in the world. Over the years, it has undergone remarkable urban and population expansion. The expressway is located in the northern part of India and is spread across the union territory of Delhi and the districts of Ghaziabad and Meerut in the state of Uttar Pradesh. It is the widest expressway in India and extends to 14 lanes at some points. It has a total length of about 60-km, starting at Nizamuddin Bridge (28°35, N–77°15, E) located in the Northern Sarai Kale Khan area of New Delhi connecting Partapur, Meerut (28°55, N–77°38, E) via Dasna. This is a controlled-access expressway that is divided into four phases. The first phase connects Nizamuddin Bridge to Delhi-UP Gate, the second phase links Delhi-UP Gate to Dasna while the third phase joins Dasna to Hapur, and finally, the fourth phase, which is a completely new alignment, connects Dasna to Meerut bypass at Partapur (see Fig. 1). Interestingly it is also the very first expressway to dedicate bicycle tracks. Our study area is confined to the 2000-m buffer area surrounding all the phases of the expressway corridor. The entire corridor passes through the plain terrain. Most of which was earlier barren or agricultural land. The first phase of the corridor which runs through Nizamuddin Bridge to the Delhi-UP Border was already a well-established and saturated built-up area. Prior to the construction of this expressway, commuters had to travel between Delhi to Meerut via NH 24 or NH 34. The journey from Delhi to Meerut which would earlier take 4–5 h has now been cut short to about 45 min.
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Fig. 1 Study area
3 Study Approach To examine the influence of the Delhi-Meerut Expressway on the change in built-up, vegetation, and water index along its corridor and to conduct its analysis, remote sensing data and geospatial techniques were used to interpret the satellite imageries of different years. Landsat data were considered for this study since they covered the entire study area. Since the expressway was first announced in 2013, Landsat 8 OLI data for 2013.05.13 was used. Landsat 9 OLI data for 2022.03.11 was used as the most recent data for the study. Google Earth Pro was used for preliminary analysis and digitizing of the expressway corridor. ArcMap software was used for creating buffers of 2000-m. ArcMap software was also used for the analysis of built-up, vegetation, and water bodies along the corridor using spatial indices analysis tools.
3.1 Preliminary Analysis Google Earth Pro software was used for the digitization of the expressway corridor of 60 km length. 14 different points were marked on the corridor. Circles of radius 2000 m were marked on each of the 14 points, and all the 14 points and their buffers
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were visualized and compared for different timelines. Satellite images of April 2013 and February 2022 were visualized to make the comparison. To carry out the primary survey and analysis, 6 points were selected out of the 14 points based on the change in a built-up area and their number, where two points were selected based on major built-up changes, two of which had undergone moderate changes and the remaining two had undergone very little or no changes. To further verify the visualized data, NDBI spatial analysis was carried out.
3.2 Spatial Analysis GIS and remote sensing are the most often utilized technological techniques to analyze land use patterns and their changes, and they are also extensively employed in road ecology [11]. Remote sensing is one of the most significant data sources for land cover spatial and temporal change investigations. When properly processed, multi-temporal remote sensing datasets may be used to detect landscape changes, allowing for an effective effort toward sustainable landscape management [12]. With the use of GIS and remote sensing, it is feasible to study the long-term changes in land cover and so get an understanding of what’s going on in the region of interest. For this study, a buffer analysis of GIS data was used to define the influence region of the expressway, and spatial statistical analysis of GIS data was utilized to produce important data and associated parameters. ArcMap 10.8 was used for data processing and spatial analysis, using tools such as buffer, clip, intersect, and raster. Satellite images offer a wide range of options for monitoring the environment quickly, especially in areas where a field survey is impossible due to topography, dense vegetation, or other local factors [13]. These studies make use of a wide variety of earth observation satellites with varying levels of spatial and spectral resolution [14]. Remote sensing methods provide a wide range of options for analyzing local or global settlements and environmental dynamics. For example, Landsat pictures with their 30 m resolution may be used to map land cover and monitor change. Land cover types were taken into consideration while studying three spectral indices: NDBI, NDVI, and NDWI. Landsat 8-9 OLI image was used in the analysis. The flowchart of the methodology is given (see Fig. 2). The NDVI is a popular tool for biomass estimation. It takes into consideration the red (RED) and the near-infrared bands (NIR). In the case of Landsat 8-9, it was the band #4 and band #5, respectively: NDVI = (SWIR − NIR)/(SWIR + NIR)
(1)
NDWI was developed to enhance the water-related features of the landscapes. This index uses the near-infrared (NIR) and green bands. In the case of Landsat 8-9, it was band #5 and band #3, respectively: NDWI = (Green − NIR)/(Green + NIR)
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A. Keshri et al. Export the Study Corridor to ArcMap as Layer
Adding Landsat data as basemap
Creating Buffer of 2000 m along the Study corridor
NDBI, NDVI and NDWI analysis using Spatial Analyst Tool
Extraction of Landsat data
Fig. 2 Flowchart for methodology
Zha proposed the NDBI algorithm to automate the detection of built-up regions [15]. In this algorithm, built-up areas are automatically identified by taking only positive difference values of binary NDBI and normalized difference vegetation index (NDVI) images. This index uses Short Wave Infrared (SWIR) and Near Infrared bands. In the case of Landsat 8-9 OLI, it is band #6 and band #5, respectively: NDBI = (SWIR − NIR)/(SWIR + NIR)
(3)
The expressway corridor was digitized using the Google Earth Pro software. The digitized data were exported to ArcMap 10.8 software as a layer. Cloud-free Landsat 8-9 OLI remote sensing imageries for May 2013 and March 2022 were downloaded from the US Geological Survey (USGS) website. All the Landsat 8-9 OLI remote sensing imageries were acquired for the dry season. During this season, cloud cover is low and ground surface reflectance fluctuations are less pronounced than in the other seasons [16]; hence, all satellite images were taken during this period. The pixel size of the Landsat image is 30 m. Spectral indices for the Landsat 8-9 OLI imageries, dated 13 May 2013 and 11 March 2022, were calculated using the Spatial Analyst tool in ArcMap 10.8.
4 Data Collection and Database The selection of six locations with a buffer zone of 2000-m was chosen to carry out the primary survey based on visualization on Google Earth Pro. The selected locations were Nizamuddin Bridge in Delhi, Rahul Vihar, Ghaziabad, Lal Kuan, Ghaziabad, Dasna, Kalchhina, and Partapur in Meerut. The locations were visualized and the points with built-up changes were marked. This was done to note the increase in the built-up and land use type. The built-up count increase was based on the number of built-up structures and not the number of floors. The locations were classified into three types on the basis of visualization on Google Earth Pro, and they were
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major changes, moderate changes, and minor changes. Rahul Vihar and Lal Kuan from Ghaziabad were selected as locations that have undergone a major increase in built-up, since May 2013. Nizamuddin bridge, Delhi, and Kalchhina were selected as the location with the least increase in built-up, since May 2013. Dasna and Partapur, Meerut, was selected as moderate built-up increase locations. Selected areas were surveyed, and land use classification was done in seven categories, i.e., Residential built-up, Commercial built-up, Industrial built-up, Recreational built-up, Public/ Semi-Public built-up, Logistics built-up, and Mixed (Residential-cum- Commercial) built-ups. The Residential built-up consisted of single residential buildings, low-rise buildings, apartments, residential colonies, etc. The Commercial built-up consisted of hotels, shopping centers, restaurants, petrol stations, etc. The Industrial built-up consisted of low-scale industries, medium-scale industries, and large-scale industries. The Recreational built-ups consisted of churches, temples, mosques, museums, etc. The Public/Semi-public built-ups consisted of offices, schools, hospitals, etc. The logistics built-ups consisted of ports, bus terminals, truck terminals, air terminals, etc. The Mixed built-ups consisted of residential-cum-commercial built-ups. The Primary survey focused on assessing the increase in the built-up and its classification in the type of land use. Vegetation and water-related features along the corridor were analyzed using the Landsat 8-9 OLI data.
5 Data Analysis and Results This section briefly talks about the result obtained from NDBI, NDVI, and NDWI analysis of Landsat 8-9 OLI data. It also talks about the results obtained from the land use type classification survey. Landsat 8 OLI and Landsat 9 OLI imageries were downloaded for May 2013 and March 2022, respectively. Both these imageries were used to perform the NDBI, NDVI, and NDWI for both years, and the results were compared. The NDBI results for the years 2013 and 2022, respectively, are given (see Fig. 3). The orange color seen in the figures represents the built-up. When the result for 2022 is compared to that of 2013, it can be noticed that the built-up has increased between Delhi and Ghaziabad and areas beyond Ghaziabad till Dasna. Some changes in builtup can also be noticed in the areas around Partapur in Meerut. Therefore, it can be assumed that the built-up has drastically increased in those areas between 2013 and 2022. The reason behind the increase in the built-up is due to the improved connectivity between Delhi and Meerut. The NDVI results for the years 2013 and 2022, respectively, are given (see Fig. 4). The light green color represents the vegetation. Non-vegetation portions have been represented by other colors. When the result for 2022 is compared to that of 2013, there has been an increase in the light green spots from Dasna to the Partapur, Meerut, which indicates there has been an increase in the vegetation. It can also be noticed in areas around Delhi and Ghaziabad, and there has been a decrease in the light green spots, which indicates the depletion of vegetation. This is due to the increase
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Fig. 3 NDBI 2013 (Left) and NDBI 2022 (Right)
in the built-up area, influenced by the development of the Delhi-Meerut expressway corridor. The NDWI results for the years 2013 and 2022, respectively, are given (see Fig. 5). The blue color represents the water-related features in the study. Non-waterrelated portions have been represented by other colors. When the result for 2022 is compared to that of 2013, it can be noticed that there has been a slight decrease in the blue spots between Nizamuddin Bridge and Ghaziabad, whereas there has been a major decrease in water-related features between Ghaziabad and Partapur, Meerut. However, it cannot be concluded that the depletion in water-related features along the corridor is caused due to the construction of the Delhi-Meerut Expressway, as the area beyond the study area has also seen significant depletion in the water-related features. Comparing and summarizing the results of the NDBI, NDVI, and NDWI analysis, it can be observed that there has been a growth of physical built-up infrastructure steadily all over the study area. Along with this, it can be noticed that the vegetation
Fig. 4 NDVI 2013 (Left) and NDVI 2022 (Right)
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Fig. 5 NDWI 2013 (Left) and NDWI 2022 (Right)
cover has been densified between Dasna and Partapur, Meerut, over the years, barring some exceptions. It can also be noted that when compared to the results of 2013, water-related features have been reduced significantly throughout the study corridor. Similar pattern of land cover has been obtained in the studies performed by [11, 12, 17]. The decline in vegetation and natural features along the expressway can be attributed to the increase in settlement and built-up features. Along with NDBI, NDVI, and NDWI analysis, land use type count was conducted based on the primary survey. The survey was conducted at six different locations along the study area. It was noted that there has been a significant increase in the builtup areas around Delhi-UP border and Ghaziabad. The land use type which has come up in these areas are mostly residential land use followed by mixed (residential-cumcommercial) land use and commercial land use. The areas surrounding Nizamuddin Bridge were noted to undergo no significant increase in the built-up, being a welldeveloped and saturated area. Places like Dasna and Partapur, Meerut, were noted to undergo moderate changes. There has been a major increase in industrial land use, followed by residential land use in Partapur, Meerut. There has been a slight increase in the residential land use in Dasna. Dasna is slowly emerging as a new city on the outskirts of Ghaziabad. Similarly, Partapur located on the outskirts of Meerut held several industries and even in recent times has seen huge industrial growth in that region. The area around Kalchhina, located between Dasna and Partapur, has not seen any changes, as this place has been very recently connected with the expressway alignment. Though, some traces of industrial development can be seen between Dasna-Partapur route. Otherwise, most of the area around this newly built alignment is either barren or agricultural land. Hence, it can be assumed that there is a huge scope of industrial development in this section.
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6 Conclusion Delhi-Meerut expressway corridor and peripheral areas have been profoundly altered by land use land cover’s major shifts. It was only after urbanization that the landscape changed from a normal agricultural landscape to a physically built-up one. Generally, transportation infrastructure has a very demeaning effect on the vegetation. This research found that the expressway has supported positive land cover change (increased built-up area), as well as the growth of natural vegetation. It was only possible due to proactive steps such as mass afforestation taken by the concerning authorities. For decentralized expansion in the form of subcenters, proactive planning is important, as shown by Suzuki et al. [18], who demonstrated that transportation networks reinforce and frequently accelerate suburbanization to some degree. The decline in vegetation and water-related features can be directly attributed to the increase in the built-up features along the Delhi-Meerut expressway. A balanced development needs to be checked using policies and regulations. This research portrayed the temporal as well as spatial changes of the land since the announcement of the expressway in 2013. The output of this study gave out the increase in the different built-up forms of land use since 2013. The information obtained can identify several environmental and safety issues and hence can assist the planners, environmentalists, and several decision-making authorities to frame and implement the policies accordingly. Also, the study can help in estimating the probable change in land cover due to the introduction of a new expressway. This will assist the planners, environmentalists, and policymakers to control the development along the corridors in the future and maximize the benefit. In this research, remote sensing and geographic information systems were shown to be effective tools for studying land use/land cover changes. A nine-year period’s worth of land use/land cover changes was successfully derived from the Landsat data, which is especially useful in the absence of the necessary data from the local administrations. Remote Sensing is, therefore, a very important tool for decisionmakers and planners.
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Comparison of Vehicular Emissions from BS-III and BS-VI Motorized Two-Wheelers Ankit Kumar Singh and Abhisek Mudgal
Abstract To ensure better air quality, the Indian vehicular emission standard has been upgraded nation-wide from BS-III to BS-IV and BS-IV to BS-VI in 2017 and 2020, respectively. However, there is a lack of attention to real-world emissions from M2W given its importance in the Indian scenario because laboratory tests do not fully capture real-world driving behavior. It is important to evaluate if there was a significant reduction in emissions from motorcycles because of upgrading to better BS standards. In this regard, two motorbikes complying with BS-III and BS-VI specifications were evaluated. An on-board vehicular gas analyser and a GPS were used to collect emission and vehicle kinematics data on different road sections in Varanasi during both off-peak and peak hours to ensure most speed and acceleration patterns are captured. The difference between the driving condition of the real world and the Indian driving cycle (IDC) was captured. The percentage of idling time in real traffic is low as compared to that in IDC. BS-III produces more CO and HC and less CO2 and NOx as compared to BS-VI. The emission factor of BS-III motorbikes for pollutants CO and HC was 9.68 and 25.69 times that of BS-VI motorbikes. The emission factor of BS-VI motorbikes for CO2 and NOx was 3.57 and 2.22 times of BS-III motorbikes. The switching from BS-III to BS-VI motorcycles will reduce CO and HC emission by 89.7% and 96.55% while increasing CO2 and NOx emission by 179% and 53.8%, respectively. Keywords Emission factor · Emission rate · Bharat stage (BS) · Motorcycle
1 Introduction Indian cities are among the most polluted cities in the world as reported by WHO. The transportation sector being one of the major sources of air pollution in urban cities is responsible for 24% of CO2 production. Out of that CO2 , 73% is from road A. K. Singh (B) · A. Mudgal Department of Civil Engineering, Indian Institute of Technology BHU, Varanasi, Uttar Pradesh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_30
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transport globally [24] and road transport in India emits as high as 243.82 Tons of CO2 (94.5%) and small quantities of other pollutants [12]. To solve the air pollution problem in urban areas, the government of India decided to upgrade Indian vehicular emission standards national-wide from BS-III to BS-IV and BS-IV to BS-VI in 2017 and 2020, respectively [9, 15]. As per the Transport Research Wing (Ministry of Surface Transport, Government of India), the number of registered two-wheelers in India stood at 64.7 million (72.2%) in 2006 and rose to 169 million (73.5%) in 2016. The total number of registered vehicles was 89.6 million and 230 million in 2006 and 2016, respectively [22]. In terms of the number of vehicles produced in India given by the Society of Indian Automobile Manufacturers, during the financial years 2006–07 and 2016–17, 8.7 million (76.4%) and 19.9 million (78.7%) of the 11.1 million and 25.3 million total vehicles produced were motorcycles, respectively (Ministry of Statistics and Programme Implementation). The growth rate of two-wheeler was 14.8% in the year 2018 in India [16]. Two-wheelers are the major contributors to air pollution as compared to other vehicles in India mainly due to the sheer number of motorcycles as compared to others. They are the major source of CO (23.7%), CH4 (46.6%), and HC (64.2%) in on-road transport in India (2005) [12]. The contribution of motorcycles for CO has increased to 37% when estimated a few years later in 2009 [13]. They consume more than 61% of petrol from the transport sector [16]. In major metropolitan cities, vehicular pollution is estimated to contribute ~70% CO, ~50% HC, and ~30–40% NOx of which motorcycles alone contribute two-thirds of the pollution [20]. Some studies have been carried out on motorcycles in other countries using their standard or derived driving cycle on a chassis dynamometer, but these cannot be directly used in the Indian scenario due to differences in vehicle standard and driver behavior. Tsai et al. [17] used ECE driving cycle to determine emission factor of various gasses and fuel consumption and to model these with respect to mileage of these motorcycles. Hassani and Hosseini [7] did test by using four driving cycles, cold start Euro-3 emissions test procedures, World Motorcycle Test Cycle (WMTC), Tehran Highway, and Urban driving cycle to determine emission factor and emission rate of pollutants. Yang et al. [19] used ECE cycle under cold start to find the emission factor with 2-stroke and 4-stroke engines for the motorcycle in use and for new. Tung et al. [18] developed driving cycle for Hanoi city, Vietnam, for motorcycle and LDV and determined the vehicles’ emission factors using the same driving cycle on the chassis dynamometer.
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To see the change in the contribution of vehicular emission that will be bought by increasing BS standards, two-wheelers should be the primary focus. Some studies in India deal with emissions from different vehicle categories. Baidya and BorkenKleefeld [4] estimated emission factor by vehicle category and age group for the whole of India and for different cities in India (7 mega cities) based on emission modeling. Goel and Guttikunda [5] and Goel et al. [6] estimated the emission factor by vehicle category for the Greater Delhi region for the year 2012 based on different emission models. Adak et al. [1] compare emission factors derived from CMEM using Indian driving cycle (IDC) and local driving cycle (LDC) (Dhanbad, India). They used Indian vehicular emission standards as an input in CMEM to convert emission rate to an emission factor for both DCs. LDC gave higher EF for CO but lower for HC and NOx as compared to IDC. Few studies have been carried out on two-wheelers incorporating different BS stages. Mahesh et al. [10] studied real-world emission modeling and emission factor on arterial road in Chennai, India, using BSII and BS-III two-wheelers. The emission factor for CO was ~7.76 higher than the emission standards but was within regulation for [HC + NOx]. Jaiprakash and Habib [8] measured emission factor of motorcycles on jack with no load and operated them using IDC from 3 vehicles of different BS norms (BS-I, II, and III). It has been observed that the CO emission factor has decreased significantly but CO2 and NOx emission factors have not decreased with the increase in BS. Sharma et al. [14] observed no significant change in fuel consumption of two-wheelers from pre-BS to BS-IV vehicles during idling. No studies have compared the BS-VI motorcycle with any other to get an idea of the advantage provided by BS-VI concerning emission and fuel consumption. The study was done in Varanasi, a tier-II city in the northern part of India in the state of Uttar Pradesh. As of March 2019, the total number of registered vehicles are more than 1 million out of which 81% are motorized-two-wheeler and 9% are cars [11]. Of all registered motorcycles about 14.43% have BS-IV engine while the rest of them have BS-III or older engine [11, 21]. In India, the domestic sales of two-wheelers increased till 2018–19 but declined from 2019–20. The sales of twowheelers has decreased by 17.77% and 28.61% in year 2019–20 and 2020–21 with respect to sales in year 2018–19 [23]. If we assume the same (India) percentage sales drop for Varanasi, BS-IV motorcycles will make ~26% of total motorcycle till March, 2021 after which BS-VI was implemented. The percentage of BS-III motorcycle is three times higher than BS-IV. It also has a higher emission standard value than BS-IV which will make the contribution of BS-III much higher in terms of vehicular emission as compared to BS-IV motorcycles. In this paper, vehicular emissions from BS-III and BS-VI have been compared with speed and different categories of driving parameters using on-board emission data.
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2 Methodology Emission testing was done on motorbikes in on-road condition in Varanasi using a portable emissions measurement instrument systems (PEMS) Kane exhaust gas analyser Autoplus 5-2 and GPS. The PEMS provides volume by volume percentage of carbon monoxide (CO), carbon dioxide (CO2 ), and oxygen (O2 ) and PPM of hydrocarbons (HC) and oxides of nitrogen (NOx). It generates instantaneous data every 2 s. The GPS was used to capture the kinematic characteristics of motorbikes. Bajaj discover 100 cc was used as a BS-III motorbike and Honda SP 125 cc was used as a BS-VI motorbike for data collection. Both motorbikes come in class 1 as classified by ARAI [3]. About 200 km and 110 km of data were collected on-road in Varanasi for BS-III and BS-VI, respectively. The data collection was done everyday of the week (weekdays and weekends), during different peak and off-peak hours and on different types of road sections. This was done to ensure most speed and acceleration are captured and which could represent the driving scenario of the city. Every test on the vehicle was done after warm-up to disregard emission due to the cold start condition. The readings given by PEMS have a timelag with respect to GPS as gasses take time to travel through a sampling tube. This timelag lag was corrected based on the maximum correlation between different gasses concentration and speed from GPS. After data synchronization, it was cleaned using Inter-Quantile range of outlier detection between gasses concentration and speed bin of 1 kmph. The concentration of vehicle exhaust given by PEMS is in percentage or PPM. The concentration was converted into emission rate (gm/s) using the density of gasses and the exhaust flow rate from the vehicle tailpipe as shown in Eq. (1). Exhaust flow rate (L/s) which changes with the speed of the vehicles is calculated as half of the multiple of engine displacement (liters) of a vehicle and engine RPS (revolution/s) for a 4-stroke engine as shown in Eq. (2) [10]. Engine RPM is calculated by multiplying tire RPM and transmission losses as shown in Eq. (3). Transmission losses are a product of final reduction (2–3.5), primary reduction (3–4), and gear ratio (0.7–1.2) of the vehicle used which is mainly dependent on the type of crank gear and driver gear. The Transmission losses value ranges from 4.2 to 16.8 for motorbikes and was assumed to be equal to 10 for this study. The average speed of the motorbikes during on-road data collection was around 20 kmph with a wheelbase diameter of 45 cm. Based on the calculation following the formulas and assumption, the average engine speed was taken to be 2500 rpm for both motorcycles. The exhaust flow rates of BS-III 100 cc and BS-VI 125 cc motorbikes are calculated to be 2 and 2.6 L/s, respectively. The on-road emission factor for various gasses was calculated based on Eq. (4). In Eq. (4) the emission rate is multiplied by two as PEMS generates data every 2 s. Emission rate = Concentration × Density (gm/lit) × Exhaust flow rate
(1)
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Exhaust flow rate = 0.5 × Engine displacement (litres) × engine RPS
(2)
Engine RPM = Tire RPM × Transmission losses
(3)
Emission factor = Σ(Emission rate × 2)/Total Distance
(4)
Emission rate in gm/s. Concentration as %/100 or PPM/106 . Density of various gasses in gm/liter. Exhaust flow rate from the tailpipe in liter/s. Transmission losses = 10 (assumed) (range 4.2–16.8). Distance in km. Emission factor in gm/km.
3 Result and Discussion The GPS data from on-road was distributed into different parameters and compared with the Indian driving cycle (IDC) [3] as shown in Table 1. It has been observed that the percent of time idling is much less in on-road data as compared to IDC. This is because IDC considers a bigger idle time which could represent the delay time at the signalized intersection and traffic jam but in Varanasi which has a limited number of signalized intersections and also there is a tendency of motorcycle riders to filter through the traffic and stop in front of all vehicles waiting. This filtering through traffic at the intersection and in traffic jam is part of creep time. Creep has been defined as a speed greater than 0 kmph and less than or equal to 5 kmph. The creep time is less in IDC which is present before and after idling time as compared to the real world where motorcycle users ride in this speed range due to high traffic and filtering techniques used by them in this situation. Cruise, acceleration, and deceleration are defined at speed higher than 5 kmph with the acceleration of the vehicle in range (−0.03, 0.03) m/s2 in cruise, higher than 0.03 m/s2 in acceleration, and less than −0.03 m/s2 in deceleration. Though the average speed of motorbikes used for data collection is approximately equal, the maximum speed observed for real world is much higher than considered in IDC (42 kmph) [3]. These changes in traveling parameters will affect the emission factor of the vehicle. Most parameters shown in Table 1 have comparable values for BS-III and BS-VI as they are both taken on similar conditions except in the case of the maximum speed which can be achieved quickly and easily in the BS-VI vehicle. Table 2 shows the emission factor (gm/km) of CO, CO2 , HC, and NOx for different conditions except for idling conditions which is shown as emission rate (gm/s). The emission factor for CO for BS-III is 6.38 times the standard but the [HC + NOx] emission factor is within the limit. Similar results were found during real-world
386 Table 1 Comparison of speed and acceleration observed during real-world testing
A. K. Singh and A. Mudgal
Parameter
BS-III
BS-VI
IDC
Average speed (kmph)
22.38
20.65
22
Maximum speed (kmph)
58.46
77.08
42
Idle (%)
0.6
1.3
16.52
Creep (%)
9.28
8.39
3.7
Cruise (%)
13.98
15.53
10.43
Acceleration (%)
38.33
36.16
36.11
Deceleration (%)
36.79
36.25
31.48
emission testing of BS-III two-wheelers in Chennai, India [10]. The BS-VI emission factor for CO is 1.23 times the standard but HC and NOx are within the limit. The emission factor of CO is high even for new BS-VI vehicle pertaining to different test conditions. The limiting standards are set using a standard driving cycle on chassis dynamometer whereas in this study real-world test was done using PEMS. The emission factors for cruise, acceleration, and deceleration states are not significantly different for respective BS motorbikes. The ratio of emission factors for BS-III to BS-VI are 10, 0.28, 25, and 0.5 for CO, CO2 , HC, and NOx, respectively, in the state of cruise, acceleration, deceleration, and total trip. This ratio changes to 11.75, 0.22, 27, and 1 in the creep state. This change in the ratio for the creep state is due to more incomplete burning of fuel in BS-III as compared to other states and lower distance covered by the vehicle in the creep state. The mean distance traveled (MDT) in Indian mega cities is 24 km [20] and in the tier-II city of Coimbatore, Tamil Nadu, where the MDT is 25 km [2] which is also prominent and uses motorized-two-wheeler. The MDT of Varanasi city is estimated to be 9 km which is based on the MDT and area (246.8 km2 ) of Coimbatore and area (82 km2 ) of Varanasi. There are 734 thousand registered BS-III motorcycles in Varanasi City [11, 21]. They annually produce 78.81, 82.2, 3.77, and 0.13 metric ton of CO, CO2 , HC, and NOx, respectively. Switching from BS-III to BS-VI motorcycles will reduce CO and HC emissions by 89.7% and 96.55% but increase CO2 and NOx emissions by 179% and 53.8% respectively. Speed was divided into bins of intervals 5 kmph and the emission rate of both motorcycles was plotted as shown in Fig. 1. It is observed that the emission rate for CO and HC increases and then decreases with an increase in speed. However, their concentration increases after 45 kmph in BS-VI whereas sudden reduction is observed in BS-III. They follow a similar trend and are higher for BS-III as compared to BS-VI as both represent the incomplete burning or oxidation of petrol. The average emission rate for CO and HC pollutants for BS-III motorbike is 3.4 and 23 times for BS-VI, respectively. Maximum CO and HC emission rate is observed in the speed range of (15, 40) kmph and (5, 25) kmph for both BS-III and BS-VI. CO2 emission increases with speed for BS-III but for BS-VI it increases then decreases and then again increases with an increase in speed. The maximum concentration of CO2 for BS-VI is in the range of (0,10) kmph and higher than 40 kmph. The average
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Table 2 Emission factor (gm/km) and the ratio of BS-III by BS-VI of CO, CO2 , HC, and NOx in different parameters BS Standard Total
Idleb (mg/s)
Deceleration
a Standards b Emission
NOx
1.87
–
VI
1.00
–
0.10
0.06
III
11.93
13.20
0.57
0.02
VI
1.23
47.16
0.02
0.05
Ratio
9.68
0.28
25.69
0.45
28.73
24.32
1.73
0.04
III
1.15
110.38
0.05
0.01
Ratio
24.90
0.22
32.21
2.69
III
80.74
71.69
4.77
0.12
0.16
0.12
29.01
1
0.55
0.02
6.87
327.34
Ratio
11.75
0.22
III
11.66
VI Acceleration
HC
III
VI Cruise
CO2
1.08a
VI Creep
CO
12.82
1.08
46.40
0.02
0.04
Ratio
10.83
0.28
26.78
0.47
III
11.30
12.26
0.56
0.02
VI
1.25
43.92
0.02
0.05
Ratio
9.05
0.28
24.90
0.42
III
10.86
12.69
0.48
0.02
VI
1.12
43.89
0.02
0.05
Ratio
9.67
0.29
25.37
0.44
[3] of BS-III for HC and NOx are combined rate is given in idle condition
CO2 emission rate for BS-VI is 4 times that of BS-III motorbike. NOx emission rate increases with an increase in speed. NOx concentration is higher for BS-III at a lower speed as evident by the emission rate at the idle condition in Table 2 but BS-VI has a higher concentration at a higher speed. This is due to the fact that oxidation of nitrogen requires a higher temperature which is achieved at a higher speed and BS-VI is more efficient at a higher speed than BS-III due to being a newer model, in better condition, and having higher engine displacement value. CO and HC concentration is maximum at minimum positive acceleration and decreases with increases in acceleration and deceleration for every speed range.
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4 Conclusion An inadequate amount of attention has been received by motorcycles which are one of the major pollution sources in urban areas. In this paper, a comparison of emissions of CO, CO2 , HC, and NOx from motorbikes corresponding to BS-III and BS-VI standards on-road testing is done using PEMS. The difference between the driving condition of the real world and IDC is captured. The percentage of idling time is real is low and creep is high for the real world as compared to IDC. The emission factor for CO for BS-III is 6.38 times the standard but the [HC + NOx] emission
Fig. 1 Comparison of speed with an emission rate of various gasses for BS-III and BS-VI motorbike
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Fig. 1 (continued)
factor is within the limit. The BS-VI emission factor for CO emission factor is 1.23 but within the limit for HC and NOx standards. BS-III produces more CO and HC and less CO2 and NOx as compared to BS-VI. The emission factor for BS-III for pollutants CO and HC is 9.68 and 25.69 times for BS-VI. The emission factor for BS-VI for CO2 and NOx is 3.57 and 2.22 times for BS-III. CO and HC increase and then decrease with speed and CO2 and NOx increase with speed. Some variations are observed in these trends for BS-VI for CO2 and other gasses at higher speeds. The switching from BS-III to BS-VI motorcycles will reduce CO and HC emissions by 89.7% and 96.55%, respectively, but it will increase CO2 and NOx emissions by 179% and 53.8%, respectively.
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Funding This work has been funded by DST/SERB project number SRG/2020/000036.
References 1. Adak P, Sahu R, Elumalai SP (2016) Development of emission factors for motorcycles and shared auto-rickshaws using real-world driving cycle for a typical Indian city. Sci Total Environ 544:299–308. https://doi.org/10.1016/j.scitotenv.2015.11.099 2. Amjad S, Rudramoorthy R, Neelakrishnan S (2011) Assessment of petroleum saving and greenhouse gas emission reduction from two-wheeler segment: 2011–2021. Transp Res Part D: Transp Environ 16(3):265–269. https://doi.org/10.1016/j.trd.2010.10.003 3. ARAI (2021) Indian emission regulation booklet 4. Baidya S, Borken-Kleefeld J (2009) Atmospheric emissions from road transportation in India. Energy Policy 37(10):3812–3822. https://doi.org/10.1016/j.enpol.2009.07.010 5. Goel R, Guttikunda SK (2015) Evolution of on-road vehicle exhaust emissions in Delhi. Atmos Environ 105:78–90. https://doi.org/10.1016/j.atmosenv.2015.01.045 6. Goel R, Guttikunda SK, Mohan D, Tiwari G (2015) Benchmarking vehicle and passenger travel characteristics in Delhi for on-road emissions analysis. Travel Behav Soc 2(2):88–101. https:/ /doi.org/10.1016/j.tbs.2014.10.001 7. Hassani A, Hosseini V (2016) An assessment of gasoline motorcycle emissions performance and understanding their contribution to Tehran air pollution. Transp Res Part D: Transp Environ 47(October 2002):1–12. https://doi.org/10.1016/j.trd.2016.05.003 8. Jaiprakash, Habib G (2018) On-road assessment of light duty vehicles in Delhi city: emission factors of CO, CO2 and NOX. Atmos Environ 174(July 2017):132–139. https://doi.org/10. 1016/j.atmosenv.2017.11.039 9. Khodke A, Watabe A, Mehdi N (2021) Implementation of accelerated policy-driven sustainability transitions: case of Bharat stage 4 to 6 leapfrogs in India. Sustainability (Switzerland) 13(8):1–25. https://doi.org/10.3390/su13084339 10. Mahesh S, Ramadurai G, Shiva Nagendra SM (2019) Real-world emissions of gaseous pollutants from motorcycles on Indian urban arterials. Transp Res Part D: Transp Environ 76(September):72–84. https://doi.org/10.1016/j.trd.2019.09.010 11. Ministry of Road Transport & Highways (n.d.) Road transport year book (2017-2018 & 20182019). Government of India, vol 59 12. Ramachandra TV, Shwetmala (2009) Emissions from India’s transport sector: statewise synthesis. Atmos Environ 43(34):5510–5517. https://doi.org/10.1016/j.atmosenv.2009.07.015 13. Sahu SK, Beig G, Parkhi N (2014) Critical emissions from the largest on-road transport network in South Asia. Aerosol Air Quality Res 14(1):135–144. https://doi.org/10.4209/aaqr.2013.04. 0137 14. Sharma N, Kumar PP, Dhyani R, Ravisekhar C, Ravinder K (2019) Idling fuel consumption and emissions of air pollutants at selected signalized intersections in Delhi. J Clean Prod 212:8–21. https://doi.org/10.1016/j.jclepro.2018.11.275 15. Singh S, Kulshrestha MJ, Rani N, Kumar K, Sharma C, Aswal DK (2022) An overview of vehicular emission standards. MAPAN-J Metrol Soc India. https://doi.org/10.1007/s12647022-00555-4 16. Sithananthan M, Kumar R (2021) A framework for development of real-world motorcycle driving cycle in India 235(6):1497–1515. https://doi.org/10.1177/0954407020977533 17. Tsai JH, Huang PH, Chiang HL (2017) Air pollutants and toxic emissions of various mileage motorcycles for ECE driving cycles. Atmos Environ 153:126–134. https://doi.org/10.1016/j. atmosenv.2017.01.019
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Webpage and Book 20. CPCB 2010 (n.d.) Status of pollution generated from road transport in six mega cities. http://www.indiaenvironmentportal.org.in/files/status%20of%20the%20vehicular%20p ollution.pdf. Accessed 22 Apr 2022 21. Ministry of Housing and Urban Affairs (2022), June 22. https://smartcities.data.gov.in/resour ces/no-vehicle-registration-varanasi-2014-15-17-18 22. Ministry of Statistics and Programme Implementation (n.d.) MOTOR VEHICLES—Statistical year book India 2018. https://www.mospi.gov.in/web/mospi/reports-publications/-/rep orts/view/templateTwo/9504?q=RPCAT. Accessed 22 Apr 2022 23. Society of Indian Automobile Manufacturers (n.d.). https://www.siam.in/statistics.aspx? mpgid=8&pgidtrail=14. Accessed 22 June 2022 24. White SL (2007) Carbon finance: the financial implications of climate change. John Wiley & Sons Inc., New Jersey
Road Safety Inspection of NH-205A: A Case Study Ankur Sharma, Har Amrit Singh Sandhu, Sovina Sood, and Rajan Dabral
Abstract Safety improvement measures are necessary if transportation safety is to be enhanced. To properly implement a specific safety improvement, however, it is vital to first establish the desired objective of each measure, like averting an accident or limiting the impacts of an accident once it has occurred. The present study discusses the suggested proposals that resulted from a road safety inspection of eight MoRTH-identified black spots on a semi-urban stretch of NH-205A between the Kharar and Banur towns in the north Indian state of Punjab. Due consideration of the accident data, detailed topographic surveys, traffic surveys, road inventory, and pavement condition surveys of the study stretch resulted in several observations and inferences based on which possible problems were identified and suitable solutions were drafted to overcome them. It was found that most of the minor intersections had inadequate visibility between the cross-traffic movements, especially during nighttime. The lack of traffic calming measures in built-up zones severely impacted the safety of pedestrian road users and two-wheeler traffic. The presence of industries between the adjacent Banur and Tepla stretch of the highway caused an increased movement of large vehicular traffic influencing the traffic dynamics, compromising the pavement’s structural integrity, causing traffic congestion, and time delays leading to a decline in the level of service. Suitable measures were suggested to ease the stress on pedestrian users, improve visibility at intersections, enhance ride quality, and enrich the user experience cost-effectively and efficiently. Keywords Road safety inspection · Traffic safety · Black spot rectification
A. Sharma (B) · H. A. S. Sandhu · S. Sood · R. Dabral Department of Civil Engineering, Punjab Engineering College, Chandigarh, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_31
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1 Introduction Improving the safety of the highways, by reducing injuries and fatalities, has been the focus of transportation safety researchers and engineers across the world. The level of safety is partly dependent on the way people use the roads and carry on their dayto-day activities. Numerous different groups of people are impacted by traffic safety like children, the elderly, the poor, the disabled, workers and commuters, customers, citizens, visitors, etc. According to WHO, road crashes are the leading cause of death globally among the younger age groups [1]. The poor are particularly vulnerable, in low-quality infrastructure areas. Older pedestrians and cyclists can account for up to 45% of pedestrian fatalities and up to 70% of cyclist fatalities [2]. Research also shows that pedestrians and other accidents are linked with locations of retail land uses, like places where people buy food, clothes, and other consumer goods [3]. A Road Safety Inspection (RSI) is carried out to determine if the safety needs of all road users are being served and to devise ways to ensure that safety outcomes are fulfilled. Safety outcomes include deaths and injuries recorded by police, health authorities, hospitals, or other sources of such information. RSI recognizes that the roadways may change over time due to changes in road use, encroachments, design inconsistency, aging infrastructure, and inadequate maintenance of roads, traffic control devices, or other measures. Points to be emphasized are adequacy of roadway, roadside, intersections, interchanges, grade separators, location of bus stops, lay byes, needs of the vulnerable road users, and access management among other things. The present study focuses on a 21 km semi-urban stretch of the national highway NH-205A which is located between the towns of Kharar and Banur in the north Indian state of Punjab. A total of eight black spots already identified by MoRTH lie within this small study stretch. The locations of the black spots along with their influence lengths are enumerated as: near Chandigarh sweets (0 + 000 km to 2 + 500 km), Village Sante Majra bus stop (2 + 500 km to 5 + 000 km), Landran light point (5 + 000 km to 8 + 000 km), Village Bhago Majra (8 + 000 km to 10 + 000 km), near Reliance petrol pump (10 + 000 km to 12 + 000 km), near railway over-bridge (ROB) located at Saneta (12 + 000 km to 14 + 000 km), Village Tangori (16 + 500 km to 18 + 500 km), and near Fauji colony (18 + 500 km to 20 + 500 km). These locations were rigorously inspected by the team to find possible causes of such a high frequency of accidents in this relatively small span of the highway. There were three objectives for carrying out this RSI of the study stretch; they were i.) Identifying road safety concerns for all categories of road users, ii.) Providing recommendations with necessary justifications for addressing safety concerns, and iii.) Enabling road authorities to make decisions on implementing the recommendations. To accomplish these tasks, accident data were collected from four different police stations, namely City Kharar, Sohana, Sadar Kharar, and Banur police stations, to identify likely causes of accidents, vehicles involved, time, and location of accidents, and the number of accidents at each of the black spots. Multiple reconnaissance surveys were performed to ascertain the traffic dynamics, travel times, causes of delays, and other possible problems. Intersection turning movement and
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classified traffic volume count were calculated at Landran light point and village Tangori respectively. Road inventory and pavement condition assessment surveys were performed to assess the vertical and horizontal profile of the road, the pavement width, and its condition. After due consideration and analysis of the collected data, suitable measures are suggested to counteract the identified problems cost-effectively and efficiently.
2 Study Area The current study focuses on the Kharar to Banur stretch of NH-205A, a national highway in the Indian state of Punjab. The section begins at Kharar, marked by a chainage of 0 + 000 km, and extends to Banur, reaching a chainage of 20 + 500 km. This area is situated in the Sahib Ajit Singh Nagar (SAS Nagar) district of Punjab. In terms of topography, the Kharar to Banur road section of NH-205A traverses flat terrain consistently along a northwest trajectory.
3 Methodology The methodology adopted for this study involved two stages: collection, assimilation, and analysis of the traffic data followed by the recommendation of suitable measures based on the traffic characteristics and analyzed results. Detailed methodology is discussed in detail in the following subsections.
3.1 Collection of Accident Data The past three years’ accident data (May 2018 and April 2021) was collected from the police stations in the form of registered FIRs of the accidents. The police stations with the requisite jurisdiction from where the FIRs were collected were City Kharar, Sohana, Sadar Kharar, and Banur police stations. The collected data were analyzed at each black spot for the number of fatalities and injuries, the time of occurrence of the accidents, the number of accidents, and the types of vehicles involved. It is to be noted that the black spots were already identified by MoRTH and the accident data were collected only to gain insights into the possible causes of the accidents. The below table enumerates the MoRTH ID, the influence lengths, and the concerned police stations for all the black spots (Table 1).
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Fig. 1 Map showing alignment of the national highway NH 205A and the study stretch located between the towns of Kharar and Banur in the state of Punjab, India
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Table 1 Detailed information about black spots and their influence lengths Sr. No MoRTH ID
Location/Place
Start chainage End chainage Police Station
1
PB-(02)-230 Bhagomajra
8 + 791
9 + 291
Sohana
2
PB-(02)-232 Reliance petrol pump
10 + 686
11 + 186
Sohana
3
PB-(02)-233 Tangori
18 + 603
19 + 103
Sohana
4
PB-(02)-235 Landran light point
6 + 400
6 + 900
Sohana
5
PB-(02)-236 ROB Saneta
12 + 017
12 + 517
Sohana
6
PB-(02)-237 Near Chandigarh sweets
1 + 366
1 + 866
City Kharar
7
PB-(02)-238 Sante Majra bus stop
3 + 125
3 + 625
Sadar Kharar
8
PB-(02)-243 Near Fauji colony, Banur 20 + 221
20 + 721
Banur
3.2 Traffic Surveys on the Study Stretch Various traffic surveys were conducted on the study stretch based on the methodologies detailed by the various relevant codes published by the Indian Roads Congress (IRC) from time to time. These surveys helped the team identify any possible problems plaguing the study stretch. The surveys carried out at the study stretch are discussed briefly in the subsections below: Reconnaissance survey. A field reconnaissance survey was carried out to get acquainted with the general alignment and characteristics of the highway and the roadside features. Intersections and junctions, breaks in medians, traffic signs, road markings, alignments of high tensile transmission lines near the highway, etc., were observed and noted during this phase. Road inventory and condition survey. This survey was carried out as per the provisions and recommendations of IRC: SP-019 (2001) to capture the characteristics of the pavement like the pavement width, vertical profile, horizontal profile, and riding quality. The pavement width and vertical and horizontal profiles of the study stretch were measured by conducting a topographic survey using high-precision surveying tools while the riding quality was subjectively evaluated based on the recommendations of the World Bank Technical Paper Number 46 [3]. From this survey, the International Roughness Index (IRI) value, arrived at by carrying multiple transits, was correlated with the 5th Wheel Bump Integrator roughness value using the following equation: RI = 630 × (IRI)1.12 where, RI = Roughness Index (Bump Integrator Roughness) in mm/km IRI = International Roughness Index in m/km.
(1)
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Intersection turning movement count. It was observed during the reconnaissance survey and speed and delay survey that there was a severe decline in the level of service during morning and evening peak hours at the major intersection situated at Landran light point. Regular traffic jams and long traffic queues were observed at the intersection. There was a noticeable increase in pedestrian traffic due to the presence of educational institutions, numerous shops, and a local bus stand near the intersection. A turning movement count was carried out at this location which helped the team understand the traffic movements passing through different arms of the intersection. This helped the team assess the efficacy of the intersection design and the effect of the local bus stand at the intersection. IRC: 108 (2015), recommends including turning movement counts at major intersections (which act as major points of diversion along the project alignment), intersections having turning movements predominantly of non-motorized vehicular modes and/or pedestrian movements (which substantially affect the highway traffic operations during peak hours) in the primary traffic survey [3]. Classified traffic volume count. Traffic volume count is one of the basic traffic surveys undertaken for many types of highway projects. For the present study, a classified traffic volume count was carried out at the black spot situated near Village Tangori. The survey was conducted as per the directions of IRC: SP-019 (2001) under the guidance of IRC: 9 (1972) [4]. First, a classified traffic volume count was carried out for 7 days as per the prescribed procedure. Then, the average daily traffic was calculated and converted to the average Passenger Car Unit (PCU) values to arrive at the total average PCU per day for the study stretch.
4 Results and Discussions Road Safety Inspections are carried out for existing highways to systematically review the existing road or section of road to identify hazardous conditions, deficiencies, or faults that may cause severe accidents. In the present study, RSI was carried out for a semi-urban stretch of NH-205A between Kharar and Banur towns in the north Indian state of Punjab. The span of the said study stretch was 21 km long. The team analyzed the data from accident records, reconnaissance survey, classified traffic volume count, intersection turning movement, road inventory, pavement condition survey, etc. to identify possible causes of the occurrence of the high number of accidents in such a small span of the highway. A reconnaissance survey of the study stretch was carried out by the team to get aquatinted with the alignment of the highway. A total of 14 population centers (villages) were located along the highway between the start and end of the alignment. The performance of RSI was warranted for the said stretch because of the presence of eight MoRTH-identified permanent black spots very close to each other. The traffic accident data was used to analyze the number of fatalities and the injuries resulting from the accidents at the black spots. The analysis revealed that
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the black spot near Chandigarh sweets was the most severe in terms of fatalities and injuries with the number of accidents consistently remaining high from 2018 through 2021. The black spot near the Landran light point was also severe with the total number of accidents only trailing the number of accidents near Chandigarh Sweets. On performing field investigations, it was found that Chandigarh Sweets and Landran light point both were built-up areas with shops and residences nearby and considerable unregulated pedestrian and 2-wheeler traffic. Roadside parking was an issue, particularly because of the scarcity of formation width and illegal encroachments on both sides of the highway. Unauthorized parking on the roadsides restricted the available space for smooth traffic flow and unregulated traffic often caused accidents. The accident data also revealed that except for village Sante Majra and village Tangori, the number of accidents at nighttime either equaled or exceeded the number of accidents during the daytime at the same locations. Field investigations revealed that at a majority of the black spot locations, the junctions were improperly illuminated at nighttime and the intersection geometry allowed little warning to the highway users about oncoming traffic from the cross-traffic movements and viceversa. The provisions of setback distances were openly flouted. Traffic guiding and other safety measures like blinkers, signboards, traffic calming devices, road safety convex mirrors, etc. were also absent at such locations. The data about the vehicles involved in the accidents showed that 2-wheelers and cars were the most vulnerable vehicle types. Another important observation was also made regarding pedestrian road users at Landran light point and Chandigarh Sweets, where they were particularly vulnerable because of the presence of educational institutions in the area and an increased number of shops along the highway respectively. Landran light point had a local bus stop within 20 m distance of the major intersection ignoring the codal recommendations. This also caused an increase in accidents involving 2-wheelers, cars, and trucks because the stopped buses forced an abrupt change in the traffic flow and forced the vehicles to change lanes abruptly (Figs. 2, 3 and 4). To assess the pavement condition along the study alignment, the International Roughness Index (IRI), was evaluated to be 7 m/km, during the road inventory and condition assessment survey, using the perception of ride comfort during trial passes conducted by the team. The value of RI was evaluated to be 5570 mm/km using Eq. (1). The condition of the road surface was analyzed according to the codal provisions prescribed by IRC: SP-16 (2019) and was judged to be needing interventions for improvement of the ride quality. Table 2 presents a description of the maximum permissible values of RI and IRI for the study stretch as recommended by the IRC code. It was found that the paved shoulder had deteriorated in non-urban stretches of the highway while the medians were damaged in the urban stretches. One major cause of this deterioration was associated with the movement of heavy vehicles on the highway. Heavy vehicles exert a larger force on the surface during braking operations which lays undue stress on the pavement material. At some of the locations,
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Fig. 2 Field photos from reconnaissance survey: a Shops on one side and the protruding wall mask road opening at the junction b 2-wheeler parked on carriageway waiting to cross the highway c Broken drain covers and shrubs cause problems at nighttime due to improper lighting d A car suddenly comes onto the highway causing a possible risk of collision
particularly between Landran light point and Banur, spots were found where pavement subgrade had failed due to excessive loading with visible signs of rutting and shoving. The observed traffic volume from the classified traffic volume count also exceeded the design service volume by more than a factor of two which also showed the excessive stress on the pavement. The observed traffic volume on the highway was observed to be 32,043 PCU/day, far exceeding the codal limits (Table 3). Table 4 below presents the recommended design service volume as per the provisions of the IRC codes. For straight sections of the highway in plain areas, the design service volume is 15000 PCU/day and for curved sections with design curvature exceeding 51°/km, it is 12500 PCU/day. The data collected during the intersection turning movement count is presented in Table 5. This survey was used to assess the average PCU traffic load on each leg of the intersection to verify the efficiency of the signalized intersection at the Landran light point. It is clear that a considerable chunk of the traffic flows from Kharar towards Tepla and the traffic in the reverse direction is relatively lower. Similarly, the traffic flowing from Mohali to Kharar, Chunni to Kharar, Mohali to Tepla, Mohali to Chunni, and Chunni to Tepla was higher than the traffic in the respective reverse directions. Overall, it was found that the short green time for the Kharar to Tepla leg was causing an inefficient traffic flow leading to traffic jams and long waiting queues. Throughout the total span of the highway, a paucity of traffic signs and road markings was observed by the team. Signs that are mandatory, cautionary, or informatory
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401
Fig. 3 Analysis of the accident data of the black spots: a Record of fatal accidents b Record of injurious accidents c Record of time of occurrence of accidents d Vehicles involved in the accidents
and markings like longitudinal or transverse markings, directional markings, hazard markings, block markings, arrow markings, facility markings, etc. were lacking at many locations or completely obscured by vegetation at many others.
5 Recommendations After due consideration of the field conditions and the detailed analysis of the collected data, suitable measures were suggested to mitigate the identified problems. To begin with, road signs were adequately provided as per IRC: 67 (2012) [5] to inform or warn about various features like intersections, junctions, breaks in medians, speed limit, allowed traffic movements, etc. wherever required. Road markings [6] were adequately provided to delineate the pavement’s various parts, including directional markings, zebra crossings, road studs, hazard markings, etc. New curves were designed to take care of the visibility issue at all the minor junctions with inadequate setback distances. Reflectorized hazard marker tape was recommended on the structure of the ROB at Saneta to improve its nighttime visibility. Placement of hazard
402
A. Sharma et al.
Fig. 4 The proposed layout of the junction at the blackspot a Bhagomajra b Reliance Petrol Pump c Village Tangori d Landran Light Point e ROB at Saneta f Near Chandigarh Sweets g Sante Majra bus stop, and h Near Fauji Colony
Road Safety Inspection of NH-205A: A Case Study
403
Fig. 4 (continued)
Table 2 Maximum permissible values of roughness Sr. no
Type of surface
Condition of road surface Good
Fair RI
Poor
RI
IRI
IRI
RI
IRI
1
Bituminous (BC, SMA, SDBC)
< 1800
< 2.55 1800–2400
2.55–3.30
> 2400
> 3.30
2
Cemented
< 2000
< 2.81 2000–2400
2.81–3.30
> 2400
> 3.30
markers was also recommended at all the junctions and breaks in the median as per the codal provisions to alleviate the nighttime visibility issue. Reconstruction of a new median was recommended after the dismantling of the existing one with provisions for street lights, wherever lacking. To protect the median against damage and improve the safety of the road users, a provision of a w-type thrie beam crash barrier was also recommended for a total length of 9250 running meters on the median while widening the gaps in the median wherever required. At Landran light point, the median from the Banur side was proposed to be extended 12.5 m into the intersection while the median opening at chainage 6 + 820 km was proposed to be closed to prevent wrong-side traffic movements. A speed zone was suggested at the Sante Majra bus stop using speed tables before and after the intersection, where bus commuters board and alight the buses, to improve their overall safety outlook. Similar speed zones were suggested at four other places, namely at an intersection near Chandigarh Sweets within a commercial zone, the junction from Mohali to Reliance petrol pump on the NH-205A, the junction from Mohali to ROB at Saneta, and the major intersection at village Bhagomajra. Speed control devices were suggested on the minor roads meeting the highway at 29 junctions and intersections with adequate warning signs to give priority to the highway users and slow down the traffic on the minor road. Pedestrian crossings were suggested at 18 places (2 Near Chandigarh Sweets, 2 Sante Majra, 4 Landran light point, 4 village Bhagomajra, 1 Reliance
404
A. Sharma et al.
Table 3 Classified traffic volume count at village Tangori Type of vehicle
Total traffic: up direction (7 days)
Total traffic: down direction (7 days)
Total traffic: both directions (7 days)
Average Daily Traffic in both directions
PCU conversion Average factor as per IRC PCU per 106 (1990) day
Car/Jeep/ Taxi/Van
15,183
15,412
30,595
4371
1
4371
Bus
607
721
1328
190
3
570
Mini Bus
712
669
1381
198
1.5
297
LCV
4422
4665
9087
1299
1.5
1948.5
Tractor
951
832
1783
255
0.5
127.5
Truck (2 Axle)
5349
7000
12,349
1765
3
5295
Truck (3 Axle)
7824
10,131
17,955
2565
4.5
11,542.5
Truck (4 Axles)
776
682
1458
209
4.5
940.5
Truck (> 4 Axles)
1891
2590
4481
641
4.5
2884.5
Construction Machinery
98
43
141
21
2
42
2-Wheelers
12,062
12,514
24,576
3511
0.5
1755.5
Cycle
942
508
1450
208
8
1664
3-Wheelers
1753
2481
4234
605
1
605
Total
52,570
58,248
110,818
15,838
–
32,043
Table 4 Recommended design service volumes Sr. no
Terrain
Design curvature (°/km)
Design service volume (PCU/day)
1
Plain
High (0–50)
15,000
Low (above 51)
12,500
High (0–100)
11,000
2 3
Rolling Hilly
Low (above 101)
10,000
High (0–200)
7000
Low (above 201)
5000
Petrol Pump, 1 ROB Saneta, 2 village Tangori, 2 Fauji Colony) with provisions for pedestrian traffic lights and pedestrian guard rails were suggested near population and commercial centers. A total length of 1420 m of 1.5 m wide drain-cum-footpath was suggested near Landran light point to facilitate and regulate pedestrian traffic movement.
Road Safety Inspection of NH-205A: A Case Study Table 5 Turning movement count for the major intersection at Landran light point
405
Sl. No
Road section
Average PCU
1
Kharar to Mohali
4921.5
2
Kharar to Tepla
9885.5
3
Kharar to Chunni
1963
4
Mohali to Tepla
3241
5
Mohali to Chunni
6406.5
6
Mohali to Kharar
5103.5
7
Tepla to Chunni
2908.5
8
Tepla to Kharar
7273
9
Tepla to Mohali
1409
10
Chunni to Kharar
2315.5
11
Chunni to Mohali
5139.5
12
Chunni to Tepla
3875
Total
54,441
References 1. WHO factsheet on Road Traffic Injuries, https://www.who.int/news-room/fact-sheets/detail/ road-traffic-injuries, last accessed 2022/07/02 2. Oxley J, Corben B, B. Fildes, and M. O’Hare, “Older Vulnerable Road Users—Measures to Reduce Crash and Injury Risk”, Monash University Accident Research Centre, Report number 218 (2004) 3. Wedagamaa DMP, Bird RN, Metcalfe AV (2006) The influence of urban land-use on nonmotorised transport casualties. Accid Anal Prev 38(6):1049–1057 4. Indian Roads Congress Special Publications 019, “Manual for survey, investigation and preparation of road projects” (2001). 5. Indian Roads Congress 108,” Guidelines for Traffic Forecast on Highways (First Revision)”, (2015). 6. Indian Roads Congress 9, “Traffic Census on Non-Urban Roads”, (1972). 7. Indian Roads Congress 67, “Code of Practice for Road Signs (Third Revision)”, (2012). 8. Indian Roads Congress 35, “Code of Practice for Road Markings (Second Revision)”, (2015).
Analysis and Prediction of Hit-and-Run Road Accidents Divya Solanki and Pankaj Prajapati
Abstract The hit-and-run (H-N-R) crashes are increasing in Vadodara. The purpose of this research is to investigate the pattern of H-N-R crashes and to determine the likelihood of a crash being a H-N-R crash. For the study, data was collected from the police department in the form of an FIR (first investigation report) and then extracted into a spreadsheet. To get insights about the data, exploratory analysis was performed, followed by χ2 -test to find out the correlation between independent variables. Once the valid variables were identified, a binomial logistic regression model was developed to predict the probability of a crash being a H-N-R crash. From the model developed the influencing factors, confusion matrix, and ROC curve were obtained. It was found that the victim vehicle types, like four-wheelers, twowheelers, and auto rickshaws, are at higher risk in cases of H-N-R crashes. The maneuvers of an impacting vehicle, like turning or reversing, were found to reduce the probability of a H-N-R crash with respect to going straight. It was also found that the victim’s gender and the number of victims also affected the H-N-R crash. Keywords Hit-and-run accident · Binomial regression · ROC curve
1 Introduction Transportation infrastructure is an important element of a country. The purpose of providing well-designed and efficient transportation infrastructure is to provide higher mobility and accessibility along with increased safety. But achieving all three together is difficult, and in most cases, safety is something that remains compromised. The number of crashes is an indicator of the safety of the infrastructure or road network of a city. D. Solanki (B) · P. Prajapati The Maharaja Sayajirao University of Baroda, Vadodara, Gujarat, India e-mail: [email protected] P. Prajapati e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 R. Rastogi et al. (eds.), Recent Trends in Transportation Infrastructure, Volume 1, Lecture Notes in Civil Engineering 354, https://doi.org/10.1007/978-981-99-3142-2_32
407
408 Table 1 Statistical data
D. Solanki and P. Prajapati
Year
Number of crashes
% Hit-and-run
2017
556
62.04
2018
540
70.03
2019
473
70.38
A crash happens when a road vehicle collides with another road user, or a fixed object such as a divider, pole, or tree. According to previous studies, road traffic crashes are the second leading cause of fatalities after cardiovascular disorders [1]. Around 1.35 million people lose their life each year due to road crashes globally [2]. India accounts for 11% of all road crash fatalities. Every year, 4.4 lakh road crashes occur in India, and these crashes claim the lives of 1.50 lakh people [3]. Among the all the crashes, H-N-R crashes are the most dangerous and difficult to analyze because of missing data. Different countries have different laws regarding H-N-R crashes, and in most cases, it is considered a criminal offense. H-N-R crashes are those crashes in which the driver responsible for the crash leaves the crash site without reporting it to the police authorities. As a result of the impactor fleeing the site of the crash, emergency response to the authorities might be delayed, which may result into increased crash severity. In India, the number of H-N-R crashes has increased in comparison to prior years [3]. In 2018, from all road crash deaths 18.9% (28,619) of them are accounted by H-N-R crashes, which is increased to 19.4% (29,354) by 2019. In Vadodara city, the number of crashes were decreasing but the percentage of H-N-R crashes was increasing. Table 1 shows the number of crashes and H-N-R percentage. Much prior research on H-N-R crash analysis has been conducted in developed countries, despite the fact that emerging countries have greater traffic, a higher vehicle population, and a higher death rate. This research focuses on the impact of several factors on H-N-R crashes, as well as determining the probability of a H-N-R crashes.
2 Literature Review Many studies have been conducted to predict crashes, with various mathematical models and machine learning approaches being used to identify key contributing factors. Some of them have been considered as research sources. This section discusses about the literature which focused on the road crashes in general. Using the models of Smeed’s and Andressen’s, P. Vally (2005) investigated the nature and scope of road crash causes. For each city, empirical models for total road crashes, fatalities, and injuries were developed using vehicle and city population [4]. Anukesh and Kumar gathered six years of road crash data along with geometry data. Crash prediction models were developed using fuzzy logic, sensitivity analysis, and other statistical methodologies. According to the author, two-wheelers and threewheelers are the most accused types of vehicles for causing road crashes, and the
Analysis and Prediction of Hit-and-Run Road Accidents
409
victims are usually two-wheeler operators and pedestrians. Fuzzy logic has provided better results in forecasting road crashes as compared to other models [5]. Lee et al. examined univariate and multivariate models for predicting vehicle crashes for motorized and non-motorized vehicles. According to the author, the multivariate model structure was shown to be more significant for motorized as well as non-motorized vehicles. Across three modes of transportation, there are substantial relationships between zone-mode specific random errors in crashes. This relationship is particularly significant between bicycle and pedestrian collisions, while it is weaker between motor vehicle and bicycle collisions [6]. This section discusses research that employed several mathematical models to determine the likelihood of H-N-R crashes based on various parameters. To investigate the influence of several factors on H-N-R crashes, Tay et al. built a binary logistic model. The results of the binary logistic model showed that the occurrence of H-N-R is higher at night, on bridges, curves, and straight roads with two vehicles, according to the author. Right turns, U-turns, and undivided roads were also shown to have an inverse effect on H-N-R crashes [7]. To assess the impact of several factors on pedestrian hit-and-run incidents, E.N. Aidoo et al. constructed a binary logistic regression model. The authors discovered that pedestrian H-N-R crashes occurs more frequently when the crashes are fatal, poor weather, during night, and straight and flat road segments without medians and intersections [8]. To investigate factors linked to H-N-R, G. Zhang et al. (2014) used a logistic regression model and found that the H-N-R is more likely when a pedestrian is involved in a crash, the crash occurs in low-light conditions, and drivers are male, middle-aged, and lack a valid driver’s license, substantial driving experience, or automotive insurance [9]. The difference between H-N-R and non-H-N-R crashes for victim injury severity was investigated by Jiang et al. The relative crash exposures between H-N-R and non-H-N-R collisions was measured using the quasi-induced exposure approach. According to the author, the severity of H-N-R crashes is lower than non-hit-and-run incidents, and the contributing variables differ in both situations. Injury severity was dramatically elevated by factors such as crash ccurring in rural regions, at night, at junctions, collision type, and alcohol participation [10]. Research was conducted by A.N. Jha et al. to estimate the offending vehicle in H-N-R traffic crash. Multiple statistical models such as Logistic Reasoning, Nave Bayes, Linear Discriminant Analysis, Classification and Regression Trees, k-Nearest Neighbor (K-NN), and Support Vector Machine (SVM) were created as supervised learning classification models. As a result, the author discovered that support vector machines had the best chance of accurately predicting an unknown impacting vehicle. For most cities, the Nave Bayes model performed poorly [11].
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D. Solanki and P. Prajapati
3 Study Area and Objective The selected study area for this research is in Vadodara, Gujarat. As per 2011 census the population of Vadodara city was 17.41 lakhs [12]. According to the road transport book the vehicle population of Vadodara is 2.3 million (31st March 2019) [13]. The road network of Vadodara is 1716 km in a 420.18km2 area. The objective of this study is to predict the probability of H-N-R crashes using a mathematical model. To find out what factor is responsible for H-N-R crashes, to develop suitable measures for reducing the number of H-N-R crashes.
4 Methodology Collision data for this study has been collected from the Vadodara police department for 3 calendar years (2017–2019). Collected data was in the form of a First Investigation Report (FIR). A total of 1569 road crashes were reported between 2017 and 2019. This crash data was extracted manually into a spread sheet and 69 different variables were created, which included road characteristics, crash characteristics, vehicle characteristics, victim characteristics, etc. The location of the crash in the form of latitude and longitude were obtained by reading the description. And by using these locations, the road characteristics of each crash were obtained from the Google maps. Once the data extraction was done, the descriptive analysis was carried out using the SPSS tool. Using cross-tabulation, descriptive analysis was performed to know the distribution of crashes within the different categories, and a Chi-square test was performed along with Phi and Cramer’s V, and lambda analysis to determine the correlation between different independent variables. After the primary analysis, a binomial logistic regression model was performed. Multiple runs were performed to get the best fit for the binomial logistic regression model.
5 Statistical Analysis 5.1 Descriptive Analysis A descriptive analysis was performed using a statistical tool to get different measures of all the variables. From the analysis, it was found that of the total crashes, around 67.48% of crashes were H-N-R. In terms of severity, the grievous account for 48.44% of the rest, while minor and fatal have equal shares. In terms of collision type, pedestrian collisions have the highest share with 31.49%. Most H-N-R crashes occurred on straight roads with a 60.03% share and at intersections with a 26.12% share. In time of the day, daytime crashes account for 70.30% of H-N-R crashes. There was
Analysis and Prediction of Hit-and-Run Road Accidents
411
Unknown Auto Ricksha Non-motorized
Auto Ricksha
Pedestrian
Victim vehicle
Nonmotorized
Twowheeler
Fourwheeler
Bus
Two-wheeler Goods Vehicle
% no. of accidents
Impacting/Victim vehicle 100% 80% 60% 40% 20% 0%
Four-wheeler Bus Goods Vehicle
Fig. 1 Impacting versus victim vehicle
insignificant difference between H-N-R and all crashes in monthly, weekly, daily, and hourly variation. The following Fig. 1 shows the percentage shares of the impacting and victim vehicles in the H-N-R crash. Table 2 shows the share of H-N-R and non-H-N-R crashes across various categories. This table will give a brief idea of the factors influencing the occurrence of H-N-R crashes.
5.2 Chi-Square Test The χ2 -test is commonly used to determine the statistical significance of a relationship between two independent variables of a nominal category. For one categorical variable, the frequency of each category is compared with categories of the second categorical variable. The data can be shown in form of contingency table, with each row indicating the category of one variable and each column representing the category of the other variable. Phi and Cramer’s V, and lambda Statistics were used to check the correlation between these two independent variables. In the symmetric measure table, the values were shown to be between 0 and 1. The value of 0 shows the least correlation between the variables. In the below Table 3, some highly corelated independent variables are shown.
5.3 Binomial Logistic Regression Model To predict the probability, logistic models are widely used. In this study, the dependent variable is binary (0 for Non-H-N-R and 1for H-N-R) therefore, binomial logistic regression model was adopted. This type of study is used to predict the probability of a driver’s staying or leaving after a collision based on independent variables. In a binomial logistic regression model, independent variables should be quantitative in nature. In a binomial logistic model, a linear relationship should be there between
22.4
28.2
Fall
Winter
9.8
4.0
11.2
Sunday
1419
Location
64.1
26.3
Yes
Didn’t Leave
435
Divider
Bridge
U-turn
Intersection
Straight Road
Collision spot
Local Street
No
7.5
20.2
Weekend
1134
237
197
249
213
205
Leave vehicle at collision
18.8
53.5
Weekday
Weekend
3.6
9.0
Saturday
3.3
4.0
10.3
11.9
Thursday
Friday
3.3
NH
Wednesday
250
218
City road
4.3
11.6
3.8
10.1
Multiple victim
Single victim
Tuesday
466
1103
Total victim
Fatal
Major
Minor
Severity
Variable
Monday
8.7
17.6
612
471
486
Total no. of crashes
Road Category
21.0
Night time
10.8
7.6
7.9
Non-Hit-and-run
Weekday
52.7
Day time
Time of the day
23.1
Percentage (%)
Hit-and-run
Summer
Season
Variable
Table 2 Descriptive statistics
19.5
54.2
6.9
3.3
19.2
44.2
2.2
17.1
54.3
19.1
54.6
18.9
35.7
19.1
Percentage (%)
Hit-and-run
6.9
19.4
3.0
1.3
6.7
15.3
0.8
6.1
19.4
9.9
16.4
4.0
14.0
8.3
Non-Hit-and-run
415
1154
156
72
407
934
48
364
1157
455
1114
360
780
429
(continued)
Total no. of crashes
412 D. Solanki and P. Prajapati
Variable
Hit-and-run
9.2
3.7
20.3
8.2
16.1
Hit from back
Hit from side
Unknown
1.3
0.1
0.0
4.5
14.0
3.0
0.1
8.5
Goods vehicle
Bus
Nonmotorized
Unknown
5.9
1.3
133
3
67
311
90
Stopped
Overtaking
Turning
Straight
Victim maneuver
Nonmotorized
Auto
509
456
Pedestrian
9.1
23.4
Four-wheeler
8.7
20.3
Two-wheeler
Goods vehicle
Auto Bus
307
186
Four-wheeler
Impacting vehicle type
3.5
463
143
Two-wheeler
2.4
0.1
4.3
36.5
3.8
23.3
0.4
1.1
1.8
2.6
40.7
Victim type
3.1
23.2
6.0
Hit-Pedestrian
Head on
470
30.7
6.8
43.0
150 Outskirt
Leave
Urban
0.0
9.6
Total no. of crashes Percentage (%)
Non-Hit-and-run
Percentage (%)
Hit-and-run
Collision Type
Variable
Table 2 (continued)
3.0
0.1
1.8
13.5
1.5
6.8
0.4
3.6
0.6
1.4
12.1
9.9
16.4
Non-Hit-and-run
84
2
96
784
83
471
12
73
38
63
829
637
932
(continued)
Total no. of crashes
Analysis and Prediction of Hit-and-Run Road Accidents 413
Percentage (%)
Hit-and-run
34.0
8.3
7.3
25.4
26.3
25–44
45–69
527
Gender
In victim
In impacting
528
No vehicle
5.0
10.7
246
34.3
36.1
1.8
1.5
49.6
0.6
23.5
Occupant vehicle of Victim
< 25
754
Unknown
Age of Victim
14.0
62
Effected
Unknown
2.7
733
1.2
8.7
38.0
Effected
20
2.7
9.4
5.1
Victim vehicle disposition
Roadworthy
0.9
328
3.3
Standing
Crossing
Along road
Roadworthy
17.7
Unknown
39
0.8
21
78
0.4
1.7
Overtaking
0.6
2.0
13.4
Percentage (%)
Hit-and-run
Pedestrian movement
Unknown
Variable
Unroadworthy
0.7
Reversing
1103
Total no. of crashes
Unroadworthy
3.0
Turning
19.7
Non-Hit-and-run
Impacting vehicle disposition
50.6
Straight
Impacting vehicle maneuver
Variable
Table 2 (continued)
15.6
3.8
6.9
12.0
12.7
0.7
0.8
1.6
2.5
1.6
2.2
Non-Hit-and-run
1023
69
477
727
766
40
36
67
186
105
245
(continued)
Total no. of crashes
414 D. Solanki and P. Prajapati
3.0
16.7
Fatal
309
4.1 23.5 0.9
Unknown
45.2
Pedestrian
Driver
Passenger
13.6
33.5
Major 739
Type of Victim 521
Minor
9.8
23.5
Victim severity
Female
13.5
60.2
209
Male
5.0
59
0.8
8.3
Hit-and-run
3.0
Variable
> 70
Total no. of crashes
Unknown
Non-Hit-and-run Percentage (%)
Hit-and-run
Percentage (%)
Variable
Table 2 (continued)
0.1
6.9
16.8
2.4
3.8
22.5
Non-Hit-and-run
16
477
973
103
272
1297
Total no. of crashes
Analysis and Prediction of Hit-and-Run Road Accidents 415
416 Table 3 Chi-square correlation test
D. Solanki and P. Prajapati
Independent variable Independent variable Correlation Victim vehicle disposition
Collision type
0.67
Speed limit
Road category
0.99
Speed limit
Location
0.64
Location
Road category
0.96
Type of victim vehicle
Victim vehicle occupant
0.98
Victim vehicle
Type of victim
0.97
Victim vehicle disposition
Victim vehicle occupant
0.66
Victim vehicle disposition
Type of victim
0.66
Dead at place
Severity
0.70
Type of victim
Victim vehicle occupant
0.84
Vehicle pedestrian
Victim vehicle disposition
0.66
the dependent and independent variable. The model assumes a binomial distribution for the binomial dependent variable. The results of the regression model are shown in Table 4. The binomial logistic model was prepared in SPSS using various variables and the above Table 4 shows the model which was obtained after removing insignificant variables. In the case of an impacting vehicle maneuver, reversing and turning were found to negatively impact the probability of a crash being a H-N-R crash. It was found that when an impacting vehicle is in a turning maneuver, the probability of a H-N-R crash is decreased to 0.488 times to that of straight maneuvering, whereas the reversing maneuver was found to reduce the probability of the same by 0.252 times that of straight maneuver. From the regression model, it was found other than buses and pedestrians, every other vehicle is found to be significantly impacting the H-N-R crash. For victim vehicle maneuver it was observed that, the probability of a H-N-R crash was reduced if the victim vehicle was stopped at the time of collision. In terms of victim gender, males are less likely to be involved in H-N-R crashes. It was found that if there is a male victim, then the probability of H-N-R is decreased by 0.657 times compared to a female victim. It was observed that if there was a single victim, the probability of a crash being a H-N-R crash increased by 1.577 times as compared to a multiple victim crash. The confusion matrix is used to measure the performance of the model. By giving an interpretation of all four possibilities False Positive (FP), False Negative (FN), True Positive (TP), True Negative (TN), it gives the results in the form of recall and specificity, which show the probability of correct projection in terms of percentage. For this model, the cut value for the probability is taken as 0.5. It was observed from
Analysis and Prediction of Hit-and-Run Road Accidents
417
Table 4 Variables in binomial logistic model Independent variables
Co-efficient
Standard error
Impacting Maneuver (relative to straight)
p-value ( 60
8.4
3.2
11.6
4 Method 4.1 Model Development Poisson regression and negative binomial (NB) regression are two techniques for predicting count outcomes that occur within a particular location or time range [4]. The Poisson and NB regressions do not assume that the residuals are normally distributed and have a constant variance [5].The conditional mean and variance of the count distribution are assumed to be equal in Poisson regression [11]—a condition referred to as equi-dispersion [4]. Overdispersion occurs when the variance of the count outcome is greater than the mean [4]. The Poisson and NB models can be compared to see which one provides the best fit to the data. Comparisons of the log-likelihood, Akaike’s information criterion (AIC), and Bayesian information criterion (BIC) can be used to measure relative model fit (Table 5).
4.1.1
Negative Binomial Regression Model
Failure to satisfy the Poisson distribution’s requirement that the mean and variance must be equal is a typical analysis error. If this equality does not hold, the data are said to be under-dispersed (E[yi] > VAR[yi]) and the parameter vector is biased if corrective measures are not taken. Depending on the topic under research, overdispersion can occur for a variety of reasons. The negative binomial model function can be written as follows. Table 5 Variables used in model development
Variables in model Independent variable
Dependent variable
Number of lanes
Number of crashes occurred at road link
Presence of on-street parking length of road segment (km) Traffic flow (PCU/hr.) Access density (Number/Kms)
428
J. R. Suthar and P. Prajapati
λi = EXP(bXi + εi) where EXP(εi) is a Gamma-distributed disturbance term with mean 1 and variance α. The addition of this term allows the variance to differ from the mean as shown below. VAR[yi] = E[yi][1 + αE[yi]] = E[yi] + αE[yi]2. The Poisson regression model is regarded as a limiting model of the negative binomial regression model as α approaches zero, which means that the selection between these two models is dependent upon the value of α. The parameter α is often referred to as the overdispersion parameter. The negative binomial distribution has the form. Γ 1 +y P(yi ) = Γ( α1 λi ) (α) i
4.1.2
[
1 α 1 α +λi
] yi ] α1 [ λi f 1 +λ α
i
Goodness of Fit
The Poisson and NB models can be compared to gain insight into which represents a better fit to the data. The judgement of relative model fit can be based on comparisons of the log-likelihood, Akaike’s information criterion (AIC), and Bayesian information criterion (BIC). The AIC and BIC account for model complexity when evaluating relative fit. Assuming equal levels of absolute fit between competing models, the AIC and BIC should select the model that is more parsimonious. When evaluating the log-likelihood, AIC, and BIC, the preferred model from a set of candidate models will be the one with the lowest values on these indices. In those cases, where these indices are negative, the preferred model is the one with the most negative value.
5 Result and Discussion Single-vehicle crashes depend on a number of variables. These variables and their relation with each other have been systematically investigated using Poisson and NB regression model. The result of the Poisson and NB models are represented in below table (Table 6). Table 6 Goodness of fit for two models Poisson regression
Negative binomial regression
Log Likelihood
−262.823
−246.314
Akaike’s Information Criterion (AIC)
539.647
506.628
Bayesian Information Criterion (BIC)
570.437
537.418
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Table 7 Parameters estimates Parameter
B
Std. Error
Sig
Exp(B)
(Intercept)
−2.042
0.4160
0.000
0.130
[No_lane = 2]
−1.741
0.4635
0.000
0.175
[No_lane = 4]
−0.597
0.2999
0.047
0.551
[No_lane = 6]
0a
[PARKING = 0]
−0.006
[PARKING = 1]
0a
Length_km
0.906
1 0.3029
0.985
0.994 1
0.1785
0.000
2.474
Traffic Flow
0.199
0.0636
0.002
1.221
Access density
−0.044
0.0226
0.050
0.957
From the table, it is observed that the AIC and BIC value comes to be lowest for the NB regression model which indicates that the NB model represents the best fit for the crashes data used for this study. The parameter estimation table for the NB regression is shown below (Table 7). Model form for single-vehicle crashes at mid-block per 5 years = exp[ intercept + b1(Number of lane) + b2(length_km) + b3(traffic flow) + b4(Access density). The negative binomial regression shows that four variables (Number of lanes, length of the road, access density, and traffic on the road link) are found to be a significant contributor to the single-vehicle crashes while the presence of on-street parking was not statistically significant.
5.1 Impact of Number of Lanes Looking to the Exp(B) column in the table above indicates that the single-vehicle crashes rate for 2 lanes road is 0.175 times the single-vehicle crashes rate at 6 lanes road and likewise SV crashes rate at 4 lanes road is 0.551 times the SV crashes rate at 6 lanes road. Past researchers [6] had confirmed from their study that as the number of lanes and road width increases, it decreases the rate of road crashes.
5.2 Impact of Road Segment Length From the table above, the Exp(B) value for the road segment length indicates that for increasing every 1 km length of the road segment there is an increase of the single-vehicle crashes by 2.474 times. This is also confirmed by [9] that the addition of extra km of road length is responsible for a higher number of fatalities.
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5.3 Impact of Traffic Flow The positive sign of the intercept indicates that as the traffic flow increases the singlevehicle crashes risk also increases. From the value of Exp(B) column, it is clear that for every 1000 PCU increase in the traffic flow the single-vehicle crashes increase by 22%. It is confirmed by [3] that there is an increase in the road crashes with an increase in the traffic flow.
5.4 Impact of Access Density The negative sign of the intercept indicates that as the access density is increasing, the number of the single-vehicle crashes reduces. The main reason behind this could be as the number of access points to major road increases, it increases the number of junctions and the driver will be cautious about driving as other vehicles can come from other directions. The NB model was developed for the reported single-vehicle crashes in the Vadodara, and from the result, it is found that the number of lanes, traffic flow, and road segment length were significant for the crashes. Single-vehicle crashes are associated with roll over of vehicle, Collison with median, dizziness, sudden application of the break, etc. For the M2W, the main reason for crashes is roll over of the vehicle with a 63% share among the other reasons for M2W crashes. Auto rickshaw stands at number two with a 14% share of total single-vehicle crashes. The reason for auto rickshaw crashes is also roll over of the vehicle with 93% of share among the other reason of crashes for auto rickshaw. May be the over speeding of the vehicle in which the driver might lose the control due to sudden obstacle comes on the roadway which was the reason for this crash. At the urban planning stage, planner needs to know that smaller road segment lengths and less width of the road will reduce the traffic flow on the road which will reduce the number of single-vehicle crashes in the city.
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