Sensitivity Evaluation and Optimization of Calibration Coefficients of AASHTOWare Pavement ME Design Jointed Plain Concrete Pavement Faulting Models

The AASHTOWare Pavement ME Design software uses faulting predictions as one of the performance measures for Jointed Plain Concrete Pavement (JPCP) structural designs. Faulting prediction is calculated as the sum of incremental change (monthly) in mean transverse joint faulting during each month in design service life. The faulting prediction computation requires eight input variables along with eight calibration coefficients (C1 to C8). It is obvious that these input variables and calibration coefficients are needed to calibrate JPCP faulting model. However, in the computation of the incremental change in mean transverse joint faulting, three interdependent equations are used, which makes this computation long and complicated. This study evaluates the sensitivity of calibration coefficients associated with the JPCP faulting model for optimization of calibration coefficients under local conditions and presents discussions on the feasibility of developing of a simplified faulting prediction equation having comparable accuracy to AASHTOWare Pavement ME Design faulting prediction equation.