TECHNICAL PAPERS
May 1, 2009

Stochastic Modeling for Pavement Warranty Cost Estimation

Publication: Journal of Construction Engineering and Management
Volume 135, Issue 5

Abstract

This paper presents a cost estimation model for long-term pavement warranties with multiple distress indicators. One application area for such warranties involves performance-based specifications (PBSs). In contrast to traditional approaches, PBS gives contractors the flexibility to select construction methods, materials, and even design. However, the contractors then must warrant the performance of their work for a specified period of time. Therefore, an accurate estimation of the risks associated with the warranty is a significant cost issue for any contractor to cover potential risks while still being competitive in bidding. Quantitative evaluation of the cost of risk incurred by the warranty has several difficulties. The deterioration of a highway project is a complex process, which is affected by pavement structure, material, traffic load, and weather conditions. Based on a probabilistic risk analysis of failures of performance indicators, the resulting model can estimate the warranty cost at a detailed level. The application of the model has been demonstrated via a numerical case study using long-term pavement performance data.

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Acknowledgments

The writers would like to thank the University Transportation Center for Alabama and Alabama Contractors’ Fee Fund for providing financial support for this study. The opinions and findings expressed here, however, are those of the writers alone.

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Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 135Issue 5May 2009
Pages: 352 - 359

History

Received: Feb 22, 2008
Accepted: Aug 14, 2008
Published online: May 1, 2009
Published in print: May 2009

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Authors

Affiliations

Gary Moynihan
Professor, Dept. of Civil, Construction, and Environmental Engineering, Univ. of Alabama, Tuscaloosa, AL 35487.
Hao Zhou
Former Graduate Student, Dept. of Industrial Engineering, Univ. of Alabama, Tuscaloosa, AL 35487.
Qingbin Cui
Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742.

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