Cost Estimation Models for Sustainable Infrastructure Using Recycled Materials for Road Engineering

Authors

  • Mittal Chaudhari
  • Mayur Parmar
  • Harshit Sheladiya

Keywords:

Economic feasibility, Lifecycle cost analysis (LCCA), Pavement performance, Reclaimed asphalt pavement (RAP), Recycled concrete aggregates (RCA), Road engineering

Abstract

The increasing demand for sustainable road infrastructure has driven interest in recycled materials like reclaimed asphalt pavement (RAP) and recycled concrete aggregates (RCA), yet accurate cost estimation remains a barrier to their adoption. This study develops and validates lifecycle cost estimation models tailored to RAP and RCA in road engineering, addressing economic and performance considerations. Through a methodology combining literature review, industry surveys, and three case studies (urban RAP resurfacing, rural RCA base layer, suburban RAP-RCA rehabilitation), key cost components—material procurement, processing, transportation, labor, quality control, and indirect costs—were identified. The proposed model, built on lifecycle cost analysis principles, integrates regional factors and performance metrics, achieving cost prediction errors of 1.0–2.8%. Results show lifecycle savings of 14–17% ($28,000–$45,000/km) compared to conventional materials, with RAP and RCA pavements meeting performance standards (e.g., 5 mm rutting after 5 years). Transportation and material quality significantly influence costs, with rural projects facing higher logistics expenses. The study recommends regional material databases, enhanced processing infrastructure, and policy incentives to promote adoption. These findings provide engineers and policymakers with a practical tool to support sustainable infrastructure, aligning with global recycling targets and reducing environmental impacts.

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Published

25.06.2020

How to Cite

Mittal Chaudhari, Mayur Parmar, & Harshit Sheladiya. (2020). Cost Estimation Models for Sustainable Infrastructure Using Recycled Materials for Road Engineering. International Journal of Intelligent Systems and Applications in Engineering, 8(2), 121–129. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7521

Issue

Vol. 8 No. 2 (2020)

Section

Research Article

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