Prediction of Asphalt Pavement Temperature Profile During FWD Testing: Simplified Analytical Solution with Model Validation Based on LTPP Data
Publication: Journal of Transportation Engineering
Volume 139, Issue 1
Abstract
A pavement temperature profile is indispensable for analyzing and interpreting falling weight deflectometer (FWD) testing data. This paper presents a simple analytical approach to rapidly predicting the transient temperature profile within the asphalt layer of a flexible pavement on the basis of measured surface temperatures during FWD testing. The proposed analytical approach consists of the classical solution of a one-dimensional heat equation in a homogeneous half-space subjected to specified surface temperatures and a Gaussian-quadrature numerical scheme to approximate the classical solution. Model validation was conducted using a large temperature database. Comparisons between predicted and measured pavement subsurface temperatures suggest that the proposed simplified analytical method generated a reasonable asphalt temperature profile during the short period of FWD testing. The main advantage of the proposed method is that it can be easily applied to assist field engineers in rapidly estimating the temperature profile within the asphalt layer of a multilayered flexible pavement based on measured pavement surface temperatures during FWD testing.
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Acknowledgments
This research was performed while the author held a National Research Council Research Associateship Award at the Turner-Fairbank Highway Research Center, Federal Highway Administration. The author thanks Jane Jiang for her suggestion on error analysis and Dr. Sean Lin for his help in extracting LTPP FWD temperature data in this study.
References
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 139 • Issue 1 • January 2013
Pages: 109 - 113
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Mar 6, 2012
Accepted: Jul 24, 2012
Published online: Dec 16, 2012
Published in print: Jan 1, 2013
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