UC Pavement Research Center
Available online at doi: 10.1061/(ASCE)TE.1943-5436.0000292
Coleri, Erdem and John T. Harvey (2011) Evaluation of Laboratory, Construction, and Performance Variability by Bootstrapping and Monte Carlo Methods for Rutting Performance Prediction of Heavy Vehicle Simulator Test Sections. Journal of Transportation Engineering 137 (12), 897 - 906
This paper demonstrates an innovative reliability analysis approach for prediction of asphalt rutting performance. In this approach, reliability was evaluated by considering the variability in laboratory test results, layer thicknesses, stiffnesses, and measured in situ performance. The effects of input design parameters variability on predicted performance were determined using the calculated distributions of calibration coefficients. To assess the contribution of each input parameter’s precision to the precision of calculated calibration coefficients, various cases were created by including and excluding the variability in these parameters in the calibration process. These distributions were also used for rutting performance prediction and reliability evaluation of highway sections. In this way, rut depths for different reliability levels can be predicted without performing computationally intensive calculations within the design software. The results indicated that distributions of calibration coefficients calculated by using measured rut depths (performance variability) are very similar to calibration coefficient distributions calculated by using thickness and stiffness (construction) distributions. This result suggests that variability in performance can be effectively predicted by using the variability in thickness and stiffness for HVS test sections because thickness and stiffness were found to be the major factors that control the variability in measured rut depths. The effect of laboratory test results variability on calibration coefficient distributions was found to be negligible when compared to the effects of stiffness and thickness variability. Although the reliability approach proposed in this study was developed using the results of a specific laboratory test and rutting models used for design in California, the general procedure can be applied to any pavement design software for any type of distress.
Keywords: Monte Carlo method; bootstrapping method; variability; reliability; rutting; heavy vehicle simulator; simple shear test