DESIGN OF 4-LANE FLEXIBLE PAVEMENT USING IIT PAVE SOFTWARE AND IRC 37

Authors

  • V Kavitha, E Nandhini, K Arun Nayak, K Balaji Author

DOI:

https://doi.org/10.64751/15mm4w05

Abstract

The project “Design of 4-Lane Flexible Pavement Using IIT PAVE Software and IRC 37” focuses on the structural design of a four-lane flexible pavement capable of safely carrying the expected traffic loads over its design life. Flexible pavement design requires proper consideration of traffic volume, axle loading, pavement materials, subgrade strength, climatic conditions, and drainage characteristics. The study follows the guidelines of IRC 37 and uses IIT PAVE software to determine the required pavement layer thicknesses and evaluate pavement performance. The design process begins with the collection of essential input parameters such as design traffic, vehicle damage factors, lane distribution, growth rate, design period, and subgrade CBR. Material properties of the bituminous layers, granular base, and sub-base are considered according to the selected pavement composition. IIT PAVE is used to analyze the pavement structure under the calculated traffic loading and to evaluate critical responses such as tensile strain at the bottom of the bituminous layer and compressive strain on top of the subgrade. These responses are used to assess fatigue cracking and rutting performance. The proposed pavement design is evaluated to ensure that the calculated strains remain within the permissible limits specified by the relevant design criteria. Different pavement layer combinations can be examined to obtain a suitable and economical pavement structure while maintaining adequate strength and serviceability. The software-based approach reduces repetitive calculations and provides an efficient method for pavement thickness design and performance evaluation.

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Published

2026-09-05

How to Cite

V Kavitha, E Nandhini, K Arun Nayak, K Balaji. (2026). DESIGN OF 4-LANE FLEXIBLE PAVEMENT USING IIT PAVE SOFTWARE AND IRC 37. International Journal of AI Electrical Civil and Mechanical Engineering, 2(3), 470-477. https://doi.org/10.64751/15mm4w05