Local Calibration of the MEPDG Distress and Performance Models for Ontario’s Flexible Roads: Overview, Impacts, and Reflection

Abstract

Built upon a seven-year local calibration study of Ontario’s flexible pavements, this paper provides a summary of the calibration results and design impact and, more importantly, shares the experience and lessons learned from the process. The best results have been achieved on the local calibration of the rutting, bottom-up fatigue cracking, and international roughness index (IRI) distress models minimizing the residual sum of squares (RSS) while maintaining the average bias at zero. Significant efforts have been made to calibrate the other distress models with limited success. A design impact study found that local calibration of the rutting models was very important, whereas the alligator fatigue cracking did not usually govern the design in Ontario, although the global model was found to under-predict the cracking damage. The performance of the calibrated IRI model in the design of heavy traffic freeways for both reconstructed and rehabilitated sections was unsatisfactory and needs further study. The paper also presents several open questions for future research. These include the handling of section-length effects of observed cracking data, the determination of initial IRI, the updating of standard deviation functions and the overall reliability models, and the prioritization of pavement research under the new paradigm of the Mechanistic–Empirical Pavement Design Guide (MEPDG).

An advanced local calibration method for mechanistic‐empirical pavement design

“…For more careful discussions about how the observed cracking data were mapped to the different cracking mechanisms (fatigue, thermal, reflective, etc. ), interested readers are referred to Yuan et al (2017) and Yuan and Nemtsov (2018). When more accurate sensing technologies are developed and deployed, it is expected that this external uncertainty will decrease.…”

“…), interested readers are referred to Yuan et al. (2017) and Yuan and Nemtsov (2018). When more accurate sensing technologies are developed and deployed, it is expected that this external uncertainty will decrease.…”

“…In general, the term “mechanistic‐empirical” describes a pavement analysis framework that includes both pavement stress analysis and a suite of empirical distress prediction models that must be validated and calibrated before they can be used effectively by any highway agency (Haas & Hudson, 2015; Huang, 1993). The MEPDG implementation experiences over the past decade in North America and beyond have consistently suggested that LC and recalibration will be a long‐term endeavor accompanied by the continuous efforts in model development, enhancement, and national calibration (AASHTO, 2010; Ceylan, Kim, Gopalakrishnan, & Ma, 2013; Hall, Xiao, & Wang, 2011; Muthadi & Kim, 2008; NCHRP, 2014; Pierce & McGovern, 2014; Pierce & Smith, 2015; Sinha & Labi, 2016; Wang, Li, Hall, Nguyen, & Xiao, 2011; Yuan, Lee, & Li, 2017; Yuan & Nemtsov, 2018). It is important to recognize that the strength of the MEPDG does not lie in the reliability of the current distress prediction models, but in the common platform that allows researchers and professional engineers to research, develop, test, and deploy ideas by using the same protocol.…”

Development of a Performance-Volumetric Relationship for Asphalt Mixtures

“…The focus of recent research in the asphalt pavement industry has been changing from empirical concepts to mechanistic concepts. Applications of this new focus include balanced mixture design, performance-engineered mixture design, mechanistic-empirical pavement design, and performance-related specifications (1)(2)(3)(4)(5)(6). In these applications, the key is to predict the performance of asphalt pavements using mechanistic models.…”

Evaluation of climate data sources and investigation of performance prediction models for mechanistic-empirical pavement designs

“…Some recent studies have highlighted the use of updated models and enhanced optimization methods for local calibration (Gong. et al, 2017;Haider, et al, 2017;Esfandiarpour and Shalaby 2017;Yuan and Nemtsov 2018). However, very few states have performed local calibration for composite pavement systems, even though almost all the states must perform frequent maintenance and rehabilitation on existing pavements.…”