Models for Accurate Prediction of Road Surfaces & Pavement’s Performance | TechGape

Models for Accurate Prediction of Road Surfaces & Pavement’s Performance


Models for Accurate Prediction of Road Surfaces & Pavement’s Performance

Models for Accurate Prediction of Road Surfaces & Pavement’s Performance 

-Navneet Kumar Gupta 

Indian Institute of Technology Hyderabad Researchers have developed Models and Computational Simulation Studies that can predict the performance of road surfaces or pavements and compare these predictions with conventional road designs. Their work has been recently published in the Journal of Transport Engineering, a reputed peer-reviewed journal.

Models for Accurate Prediction
India has the second largest road network in the world, after the United States, and has about 4.37 km of roads per 1,000 people. Indian roads are of different types including highways, alleyways, paved roads and unpaved roads, among others. The past two decades have seen a drive to pave the Indian roadway network, and as of 2016, 62.5 percent of Indian roads has been paved.

Construction of the road surface or pavement is a complex process because they must be able to provide for comfortable riding quality, good skid resistance, favorable light reflecting characteristics, and low noise pollution. The design of pavement is the first and essential step towards building roads that can meet the needs of the traffic demands as well as to balance the demand on natural materials used in paving them.

This Research offers a route to accurate prediction of pavement performance, which can help in construction of long-lasting roads in India.

Speaking about the importance of this research, Prof. Sireesh Saride, Department of Civil Engineering, IIT Hyderabad, said, “The pavements are complex layered structures influenced by many factors such as material properties, environmental and climatic conditions, traffic volume, subgrade soil profile, construction practices, and pavement aging process. Hence, transportation agencies require innovative techniques to address the variabilities associated with the influencing factors.”

A road surface or pavement typically consists of superimposed layers of various materials above the natural soil and help in the distribution of the load of the traversing vehicles for a smooth ride. There are two types of pavements – rigid and flexible. While rigid pavements are made of high strength concrete to resist the vehicle load directly, flexible pavements transmit the load downwards from the surface through successive layers of materials.

“The advantages of flexible pavements are that they are adaptable to stage-wise construction, can be made of low-cost materials and can be easily opened and patched”, added Dr. Saride on the applicability of flexible pavements to Indian roads.

In modern pavement construction, accurate prediction of pavement performance has become important in order to develop robust design procedures.

“Reliability-Based Design Optimization – RBDO – is a modeling technique that combines optimization approaches with reliability assessment of structures” explained Dr. Saride. His team, including Dr. B. Munwar Basha, Associate Professor, Department of Civil Engineering, IIT Hyderabad, and Mr. P.R.T. Pranav, Research Scholar, IIT Hyderabad, has used RBDO to predict safety of multi-layered flexible pavement structures against fatigue and rutting criteria while simultaneously considering the variability arising from individual design parameters. The flexible pavement was modelled as containing four layers – subgrade, granular subbase, base, and bitumenous layers. Modelling studies showed that the bituminous layer’s thickness and resilient modulus of the base layer are the most influential parameters for the fatigue failure.

The results of the simulation studies were compared with data from American Association of State Highway and Transportation Officials (AASHTO) guide for the design of pavements. “AASHTO overestimated reliability by 10-40 per cent compared to RBDO because the former did not consider the variability associated with geometrical and material properties” explained Dr. Munwar Basha.

The Ministry of Road Transport and Highways of the Government of India aims to construct 65,000 km of national highways by 2022. Such ambitious projects would benefit from studies such as those conducted by Dr. Saride and his colleagues. keywords:



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TechGape: Models for Accurate Prediction of Road Surfaces & Pavement’s Performance
Models for Accurate Prediction of Road Surfaces & Pavement’s Performance
Models for Accurate Prediction of Road Surfaces & Pavement’s Performance
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