The implementation of findings from accelerated pavement testing in pavement design and construction practice

2012 ◽  
pp. 425-431 ◽  
Author(s):  
J Kwon ◽  
M Wayne ◽  
G Norwood ◽  
J Tingle
Keyword(s):  
Pavement Design ◽  
Accelerated Pavement Testing ◽  
Pavement Testing ◽  
Construction Practice ◽  
Design And Construction

Calibrating the Mechanistic–Empirical Pavement Design Guide Rutting Models using Accelerated Pavement Testing

2018 ◽  
Vol 2672 (40) ◽  
pp. 304-314 ◽  
Author(s):  
Yu Tian ◽  
Jusang Lee ◽  
Tommy Nantung ◽  
John E. Haddock
Keyword(s):  
Measurement Errors ◽  
Prediction Models ◽  
Asphalt Mixture ◽  
Calibration Method ◽  
Pavement Design ◽  
Data Generation ◽  
Accelerated Pavement Testing ◽  
Design Guide ◽  
High Distress ◽  
Pavement Testing

This paper presents a new method for the local calibration of the rutting models in the Mechanistic–Empirical Pavement Design Guide (MEPDG) for Indiana’s pavements using accelerated pavement testing (APT). The study focused on the verification, calibration, and validation of the rutting models in the MEPDG using both field and APT sections. In this study, a new calibration methodology was developed that uses layer rutting distribution. Also, a procedure was developed to provide the most realistic simulations of APT conditions (climate, traffic, and aging) using virtual weather station data generation, a special traffic configuration, and falling weight deflectometer evaluation. The primary benefits of APT are that it uses test sections with high distress levels and low measurement errors and it provides findings about the contributions of each layer to the total rut depth (i.e., pavement surface rutting). The accuracy of the MEPDG’s rutting prediction models was improved significantly following implementation of the new calibration process. The sum of squared errors (SSE) was reduced by 73% and the standard error of estimates was reduced by 38%. No significant differences were found between the predicted and measured asphalt layer, subgrade, and total rut depths at the 95% confidence level. When compared with the conventional calibration method, which uses the total rut depth without knowing the rut depth of each layer, the proposed method provides more reliable predictions for both asphalt mixture and subgrade rutting, most especially for the latter. The bias and SSE of the predicted subgrade rutting were improved by 46% and 62%, respectively.

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