4.5 Article

Preliminary calibration and validation of the Texas Mechanistic-Empirical flexible pavement design

期刊

INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
卷 23, 期 11, 页码 3879-3891

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10298436.2021.1926458

关键词

Mechanistic design; calibration; rutting; cracking; bias; standard error

资金

  1. Texas Department of Transportation

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This paper presents a concise approach for calibrating the damage models in the TxME, focusing on rutting, bottom-up fatigue cracking, and transverse cracking models. By using ANOVA to establish similar groups of sections and various calibration methods, significant improvements in fit quality were achieved.
This paper presents a concise approach for calibrating the damage models in the TxME, a mechanistic-empirical flexible pavement design model developed for Texas. The models calibrated are rutting, bottom-up fatigue cracking and transverse (thermal) cracking. Pavement performance observations from the Texas Department of Transportation (TxDOT) maintained Data Storage System (DSS) were used for this purpose. Prior to calibration, Analysis of Variance (ANOVA) was used to establish similar groups of sections in terms of structural, traffic and environmental conditions. For the rutting model, the layer calibration coefficients weighed plastic deformations linearly, hence it was possible to establish them by minimising the sum of the squared errors (SSE) between the estimated and observed surface (i.e. total) rutting using the generalised gradient method (GRG) through the MS (R) Excel solver. For the fatigue cracking model, calibration focused on the transfer function between the accumulated fatigue damage and the observed fatigue cracked area. Curve fitting was done using the bi-square robust algorithms in MATLAB (R). For the transverse cracking model, the exponent of the pavement life ratio p/m was established through curve-fitting on transverse cracking observations. In general, the calibration resulted in significant quality of fit improvements.

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