Sensitivity Evaluation of MEPDG Performance Prediction

The American Association of State Highway and Transportation Officials (AASHTO) interim edition of the "Mechanistic-Empirical Pavement Design Guide (MEPDG) Manual of Practice" was published in 2008. This Guide and related software provide a methodology for the analysis and performance prediction of flexible and rigid pavements based on mechanistic-empirical principles. For given pavement structure, material properties, environmental conditions, and traffic loading characteristics, the structural responses such as stresses, strains, and deflections are mechanistically calculated using multilayer elastic theory or finite element methods. Thermal and moisture distributions are also mechanistically determined using an Enhanced Integrated Climate Model. These responses are then used as inputs to empirical models for predicting pavement performance in terms of distresses such as cracking, rutting, faulting, and smoothness. These empirical models have been calibrated using data from the Long-Term Pavement Performance (LTPP) database for in-service pavements that are representative of the conditions encountered in the United States. The performance predicted by these models depends on the values of input parameters that characterize the pavement materials, layers, design features, and condition. However, because these input parameter values are expected to differ from those for the constructed pavement, the predicted performance will also vary to some degree depending on the input parameter values. Earlier studies conducted to relate predicted performance to differences in input parameter values have not addressed this relationship in a systematic manner to identify the relative influence of input parameter values on predicted performance. Also, these studies have not considered the combined effects of variations in two or more input parameter values on predicted performance in a comprehensive manner. Research was needed to determine the degree of sensitivity of the performance predicted by the MEPDG to input parameter values and identify, for specific climatic region and traffic conditions, the input parameters that appear to substantially influence predicted performance. In this manner, users can focus efforts on those input parameters that will greatly influence the pavement design. NCHRP Project 1-47 was conducted to address this need; this digest summarizes the findings of this research.