Local Recalibration of JPCP Performance Models and Pavement-ME Implementation Challenges in Michigan

Project Details
STATE

MI

SOURCE

TRID

START DATE

03/01/20

RESEARCHERS

Haider, Syed Waqar; Musunuru, Gopikrishna; Buch, Neeraj; Brink, Wouter C

KEYWORDS

Calibration, Computer models, Concrete pavements, Mechanistic-empirical pavement design, Pavement performance, Rigid pavements, Transverse cracking

Project description

The AASHTOWare Pavement Mechanistic-Empirical (ME) Design version 2.0 performance models were locally calibrated in 2014. Subsequently, the software was updated to versions 2.2 (2015) and 2.3 (2016) since the last calibration effort in Michigan. In the newer versions, several bugs were fixed, and some of the performance models were modified. As a result, concrete pavement designs were impacted. Thus, there is an urgent need to verify the performance predictions for rigid pavements in the State of Michigan for the Pavement-ME versions 2.2 and 2.3. Performance model predictions for rigid pavement between different versions were compared in order to highlight the changes in models. Also, this paper compares observed and predicted performance for testing the need for recalibration. The results show that performance models for rigid pavements [transverse cracking and international roughness index (IRI)] have changed since the Pavement-ME version 2.0. Recalibration is warranted because of model changes and additional time series availability. The recalibration of transverse cracking and IRI model reduced the standard error of estimate (SEE) and bias for both the models. Several challenges in the implementation of the Pavement-ME after recalibration were encountered. This paper documents the lessons learned while addressing these issues. For cumulative damage lower than 0.1, the predicted cracking levels are negligible. The local calibration model coefficients can be further improved by considering the project-specific permanent curl value. A model was developed to predict the permanent curl value for a location based on the site-specific climate and design properties.
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