Prediction Models for Transverse Cracking of Jointed Concrete Pavements: Development with Long-Term Pavement Performance Database

doi:10.3141/2068-03

機構典藏 > College of Engineering > Graduate Institute & Department of Civil Engineering > Journal Article > Item 987654321/90448

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/90448

Title:	Prediction Models for Transverse Cracking of Jointed Concrete Pavements: Development with Long-Term Pavement Performance Database
Authors:	Ker, Hsiang-Wei;Lee, Ying-Haur;Lin, Chia-Huei
Contributors:	淡江大學土木工程學系
Date:	2008
Issue Date:	2013-06-24 13:18:24 (UTC+8)
Publisher:	Washington: U.S. National Research Council * Transportation Research Board
Abstract:	The main objective of this study was to develop improved prediction models for transverse cracking of jointed concrete pavements with the Long-Term Pavement Performance database. The retrieval, preparation, and cleaning of the database were carefully handled with a systematic and automatic approach. The prediction accuracy of the existing prediction models implemented in the recommended MechanisticâEmpirical Pavement Design Guide (NCHRP Project 1-37A) was found to be inadequate. Exploratory data analysis indicated that the normality assumption with random errors and constant variance by using conventional regression techniques might not be appropriate for this study. Therefore, several modern regression techniques, including the generalized linear model and the generalized additive model, along with the assumption of Poisson distribution, were adopted for the modeling process. The resulting mechanisticâempirical model included several variablesâsuch as pavement age, yearly equivalent single-axle loads (ESALs), accumulated ESALs, annual precipitation, freezeâthaw cycle, annual temperature range, stress ratio, and percent steelâfor the prediction of transverse cracking. The goodness of fit was further examined through significant testing and various sensitivity analyses of pertinent explanatory parameters. The tentatively proposed predictive models appeared to agree reasonably with the pavement performance data, although their further enhancements are possible and recommended.
Relation:	Transportation Research Record: Journal of the Transportation Research Board 2068, pp.20-31
DOI:	10.3141/2068-03
Appears in Collections:	[Graduate Institute & Department of Civil Engineering] Journal Article

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