Prediction of Time-Dependent Temperature Distribution within the Pavement Surface Layer during FWD Testing
Publication: Journal of Transportation Engineering
Volume 142, Issue 7
Abstract
This paper presents an infinite series solution to predict the time-dependent temperature profile within the pavement surface layer on the basis of measured pavement surface temperature data during falling weight deflectometer (FWD) testing. The infinite series solution was derived using the method of eigenfunction expansions. The model validation was conducted based on the long-term pavement performance (LTPP) program FWD temperature data. The interpolatory trigonometric polynomials were used to approximate a pavement surface temperature history by using temperatures measured at different times during FWD testing. Total of 2,066 and 1,968 pavement subsurface temperatures within surface layers were predicted by using the derived infinite series solution for flexible and rigid pavements, respectively. These temperature profile predictions were compared with the measured pavement subsurface temperatures, showing that the proposed solution can rapidly and accurately predict the transient temperature profile within the pavement surface layer during the short time period of FWD testing with limited inputs.
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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 Dr. Huang-Hsiung Sean Lin for his help in extracting LTPP FWD temperature data in this study. The author also expresses his gratitude to Ms. Mary Deeney who proofread this paper.
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Information & Authors
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Published In
Journal of Transportation Engineering
Volume 142 • Issue 7 • July 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Nov 16, 2015
Accepted: Jan 20, 2016
Published online: Mar 21, 2016
Published in print: Jul 1, 2016
Discussion open until: Aug 21, 2016
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