Pave Core-Thickness a Software Driven Approach

India's rapidly expanding transportation infrastructure has created a growing need for efficient, durable, and standardized pavement design solutions. Flexible pavements, being the most widely adopted form of road construction, demand accurate design to ensure structural stability, cost-efficiency, and long-term performance. This research presents the development of a user-friendly software tool that automates the design of flexible pavement thickness in strict accordance with the latest IRC:37-2018 guidelines issued by the Indian Roads Congress. The software is designed to assist highway engineers and planners by simplifying the traditionally complex and manual pavement design process. It accepts essential input parameters such as traffic loading (in million standard axles), subgrade CBR, lane configuration, and material properties, and intelligently computes the required thickness for each pavement layer—including surface course, base, and sub-base. The tool integrates IRC-specified design charts and algorithms to ensure accuracy and standard compliance. Key features of the software include a graphical interface, automated design summary report generation, and optional modules for material estimation and cost approximation. These capabilities enhance the efficiency and accuracy of the design process while minimizing human error. By bridging the gap between academic knowledge and field application, this project supports smarter, faster, and more reliable pavement engineering practices. The proposed software contributes significantly to standardized infrastructure development, helping engineers make informed decisions and improving the overall quality and durability of road networks across the country.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-05
DOI
https://doi.org/10.5281/zenodo.15345643
Primary Topic
Neurogenesis and neuroplasticity mechanisms
Type
article
Field-Weighted Citation Impact
0.00
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article

Pave Core-Thickness a Software Driven Approach

Zenodo (CERN European Organization for Nuclear Research)
Neurogenesis and neuroplasticity mechanisms
article

Pave Core-Thickness a Software Driven Approach

article en

Abstract

India's rapidly expanding transportation infrastructure has created a growing need for efficient, durable, and standardized pavement design solutions. Flexible pavements, being the most widely adopted form of road construction, demand accurate design to ensure structural stability, cost-efficiency, and long-term performance. This research presents the development of a user-friendly software tool that automates the design of flexible pavement thickness in strict accordance with the latest IRC:37-2018 guidelines issued by the Indian Roads Congress. The software is designed to assist highway engineers and planners by simplifying the traditionally complex and manual pavement design process. It accepts essential input parameters such as traffic loading (in million standard axles), subgrade CBR, lane configuration, and material properties, and intelligently computes the required thickness for each pavement layer—including surface course, base, and sub-base. The tool integrates IRC-specified design charts and algorithms to ensure accuracy and standard compliance. Key features of the software include a graphical interface, automated design summary report generation, and optional modules for material estimation and cost approximation. These capabilities enhance the efficiency and accuracy of the design process while minimizing human error. By bridging the gap between academic knowledge and field application, this project supports smarter, faster, and more reliable pavement engineering practices. The proposed software contributes significantly to standardized infrastructure development, helping engineers make informed decisions and improving the overall quality and durability of road networks across the country.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Neurogenesis and neuroplasticity mechanisms
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