This guide provides guidance to calibrate the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to local conditions, policies, and materials. It provides the highway community with a state-of-the-practice tool for the design of new and rehabilitated pavement structures, based on mechanistic-empirical (M-E) principles. The design procedure calculates pavement responses (stresses, strains, and deflections) and uses those responses to compute incremental damage over time. The procedure empirically relates the cumulative damage to observed pavement distresses.

A mechanistic-empirical (ME) pavement design procedure allows for analyzing and selecting pavement structures based on predicted distress progression resulting from stresses and strains within the pavement over its design life. The Virginia Department of Transportation (VDOT) has been working toward implementing ME design by characterizing traffic and materials inputs, training with the models and design software, and analyzing current pavement designs in AASHTOware Pavement ME Design software. This study compared the measured performance of asphalt and continuously reinforced concrete pavements (CRCP) from VDOTs Pavement Management System (PMS) records to the predicted performance in AASHTOware Pavement ME Design. Model coefficients in the software were adjusted to match the predicted asphalt pavement permanent deformation, asphalt bottom-up fatigue cracking, and CRCP punchout outputs to the measured values from PMS records. Values for reliability, design life inputs, and distress limits were identified as a starting point for VDOT to consider when using AASHTOware Pavement ME Design through consideration of national guidelines, existing VDOT standards, PMS rating formulas, typical pavement performance at time of overlay, and the data used for local calibration. The model calibration coefficients and design requirement values recommended in this study can be used by VDOT with AASHTOware Pavement ME Design as a starting point to implement the software for design, which should allow for more optimized pavement structures and improve the long-term performance of pavements in Virginia.

This report documents efforts of the Arizona Department of Transportation (ADOT) to implement the American Association of State Highway and Transportation Officials (AASHTO) DARWin-ME pavement design guide in Arizona. The research team also prepared a practical stand-alone user's guide that provides guidance for obtaining inputs, conducting design, and establishing the recommended pavement design. Implementation focused on identifying the desired pavement design application of flexible hot-mix asphalt (HMA) pavements, composite pavements (thin asphalt rubber friction course over jointed plain concrete pavement [JPCP] and continuously reinforced concrete pavement [CRCP]), JPCP, and HMA overlays of flexible pavement; characterizing materials and subgrades; determining traffic loadings (conducted under Darter et al. 2010); collecting and assembling DARWin-ME input data from 180 Long Term Pavement Performance and pavement management system sections of flexible, rigid, composite, and rehabilitated pavements; calibrating the DARWin-ME distress and International Roughness Index (IRI) prediction models to Arizona conditions; and training ADOT staff. Several biased distress and IRI models were corrected through the local calibration of Arizona pavements. Several key inputs were more accurately defined and Arizona defaults provided (e.g., subgrade resilient modulus). The calibration process improved these models through verification, validation, and calibration with Arizona data. Overall, the inputs and calibrated models will provide more accurate, reliable, and cost-effective pavement designs than designs created with global calibrations.--Abstract, Technical report documentation page.

The AASHTOWare Pavement ME Design (PMED) is a novel design method for new and rehabilitated pavement designs based on mechanistic-empirical design principles. The design process includes several empirical models calibrated with pavement performance data from pavement sections throughout the United States. Improved accuracy of the design process requires that the models be calibrated to local conditions. Therefore, the objective of this study was to implement the AASHTOWare PMED software for rehabilitated pavement design by performing local calibration for state-managed roads in Kansas, New Jersey, and Maine. Transfer functions for translating mechanistic pavement responses into visible distresses embedded in the AASHTOWare PMED software were locally calibrated to eliminate bias and reduce the standard error for rehabilitated pavements in Kansas and New York. Calibration was performed using version 2.5 and then verified with version 2.6.2.2, which was released in September 2022. Rehabilitated pavement sections included asphalt concrete (AC) over AC in Kansas and the New England region and jointed plain concrete pavement (JPCP) sections in Kansas. Because the PMED software requires periodic recalibration of the prediction models to account for improvements in the models, changes in agency design and construction strategies, and updates in performance data, this study also developed an automated technique for calibrating the AASHTOWare PMED software performance models. This automated methodology incorporated robust sampling techniques to verify calibrated PMED models. In addition, statistical equivalence testing was incorporated to ensure PMED-predicted performance results tended to agree with the in-situ data. A comparison of results for the AASHTOWare PMED versions 2.5 and 2.6.2.2 showed that most predicted distress values in Kansas remained the same, except for the predicted AC total fatigue cracking, specifically asphalt bottom-up fatigue cracking. For both distress types, slightly higher values were obtained with version 2.6.2.2. Results of three candidate crack tests showed that IDEAL-CT test results can be used as cracking-resistance criterion for mixtures in Kansas. The rehabilitation models were also successfully calibrated for the New England region.