Publication Detail

Development of a Cracking Performance Prediction Model for Replaced Concrete Slabs in California

UCD-ITS-RP-18-64

Reprint

UC Pavement Research Center

Available online at: https://trid.trb.org/view/1496384

Suggested Citation:
Saboori, Ashkan, Jeremy D. Lea, Venkata N. Kannekanti, Arash Saboori, John T. Harvey (2018) Development of a Cracking Performance Prediction Model for Replaced Concrete Slabs in California. Transportation Research Board 97th Annual Meeting

Cracking and faulting are typical distresses in concrete pavements in California. These distresses at their initial stages cause poor ride quality and higher fuel consumption. With further progress, they lead to loss of structural capacity and serious safety issues. To maintain the road’s condition at an acceptable level, the timing of maintenance and preservation operations should be optimized. Slab replacement is a maintenance operation performed to improve the pavement condition by replacing cracked slabs with new ones. However, there is currently no performance prediction model for replaced slabs in the California pavement management system (PMS). This paper addresses issues with collecting cracking data from the California pavement network and developing performance prediction models for slab replacement. Cracking data for each project are collected from the California PMS and are used to develop survival and performance models. The models show that survival rate for thinner slabs (with a thickness less than 0.8 ft) drops drastically after seven years compared to thicker slabs that show low failure rates in the first twelve years of service. The performance prediction model is the probability of failure of replaced slabs versus time and is determined based on age, thickness, and traffic. The developed models will be used in the Caltrans Pavement Management System (PaveM) for recommending the best timing for future maintenance. The results will also be used for conducting life cycle cost analysis (LCCA) and environmental life cycle assessment (LCA).

Key words: Cracking, data collection, life cycle analysis, life cycle costing, maintenance management, mathematical models, mathematical prediction, pavement management systems, pavement performance