Statistical Mixed Effects Models for Evaluation and Prediction of Accelerated Pavement Testing Results
Publication: Journal of Transportation Engineering
Volume 132, Issue 10
Abstract
We elucidate the usefulness of the mixed-effects models in analyzing performance-type data resulting from accelerated pavement testing (APT) experiments. Our analysis is based on an APT test designed to evaluate the performance of materials and pavement structures using rut depth as the response variable. The model results indicate that both binder type and temperature are significant factors in rut depth development. By capturing the left-over variability associated with each test track unexplained by the experimental factors, the mixed effects models employed herein also allow inference to be made about unobserved phenomena such as failure probabilities and their confidence intervals, where failure is defined as the passage of a particular threshold such as a maximum rut depth. These failure probabilities provide estimates of the percentage of sections that would fail after a certain accumulated traffic load, which could help trigger maintenance actions in the field. This paper also provides insights regarding the duration of APT experiments conducted with a heavy vehicle simulator (HVS) from the perspective of stable parameter estimation, which may prove beneficial in optimizing loading time and testing focus in HVS experiments.
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Acknowledgments
Work on this project was made possible for the first writer by a James W. McLamore Summer Research Grant from the University of Miami Research Council, NIH Cancer Support Grant CA21765 and the American Lebanese Syrian Associated Charities; and for the second writer by financial support from the Swedish Road Administration and the Swedish Governmental Agency for Innovation Systems. The writers also acknowledge the insightful comments of the two referees and the Associate Editor, which led to an improved version of the manuscript.
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© 2006 ASCE.
History
Received: Sep 15, 2005
Accepted: Dec 22, 2005
Published online: Oct 1, 2006
Published in print: Oct 2006
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