Predicting Remaining Strength of Flexible Pavement and Overlay Design Thickness with Stochastic Modeling

Author:

Abaza Khaled A.1,Murad Maher M.2

Affiliation:

1. Department of Civil Engineering, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.

2. Department of Civil Engineering Technology, University of Pittsburgh at Johnstown, 450 Schoolhouse Road, Johnstown, PA 15904.

Abstract

A pavement's remaining strength is predicted from initial pavement strength by means of layer structural capacity adjustment factors. “Initial pavement strength” is defined as the total structural capacity associated with the asphalt concrete and underlying granular layers estimated by appropriate relative strength indicators such as the gravel equivalent or structural number. The pavement's future remaining strength is estimated as the product sum of multiplying the initial layer strength by the corresponding adjustment factor. The structural adjustment factor represents the percentage of remaining strength for a particular pavement layer at a specified service time ( t). The structural capacity adjustment factor associated with the asphalt layer is the principal factor estimated from a project performance curve generated with stochastic modeling. The discrete time Markov model is used to predict pavement distress ratings for a particular project over a specified service life ( T). A simplified approach is presented for estimating a project transition matrix using only initial and terminal transition probabilities. The predicted distress ratings are used to construct a project performance curve. The area falling under the performance curve has long been recognized as a direct measure of the pavement relative strength. Therefore, the principal structural capacity adjustment factor is defined as the ratio of the area under the performance curve for the remaining service period ( T - t) and the area under the entire performance curve for a service life ( T). A sample application is provided with results used to generate empirical models to aid in developing rehabilitation strategies and management policies at the network level.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

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