Zhong, Jian2017-09-272017-09-272017-09-272017-09-22http://hdl.handle.net/10012/12474The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been introduced to transportation agencies as an innovative method for analysis and design of pavements. However, the MEPDG cannot be used by highway agencies without calibration due to the different situations in Canada. Local calibration the MEPDG, which means adjusting the coefficients of performance prediction models to meet the local conditions, should be an essential step for any agencies before the official acceptation of the MEPDG. As the part of the project, Local Calibration of the MEPDG Prediction Models Using More Accurate Field Measurements funded by Highway Infrastructure Innovation Funding Program (HIIFP), this research involved the local calibration of the models for Jointed Plain Concrete Pavement (JPCP) in the Province of Ontario. Using the field measurements collected by Ministry of Transportation in Ontario (MTO), the study performed local calibration for 32 rigid (JPCP) pavement sections. The primary objective of this study was to examine prediction results using global models; then if not agree with the measurements, refine the coefficients of the MEPDG performance models using the nonlinear optimization methods. The proposed calibration was applied by using the sections located in different zones throughout Ontario to represent the local features, including climate and traffic conditions. Finally, the local calibration results are presented and compared with previous results of global models to assess the robustness of local calibration. The research shows the feasibility of the mathematical optimization method for in local calibration in Ontario, and it also provides some useful findings for future uses of the MEPDG.enMEPDGCalibrationPrediction modelsMaster Thesis