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Improving Prediction Accuracy In Mechanistic-Empirical Pavement Design Guide, Scott Schram, Magdy Abdelrahman
Improving Prediction Accuracy In Mechanistic-Empirical Pavement Design Guide, Scott Schram, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Model calibration plays a fundamental role in the implementation of the mechanistic-empirical pavement design guide. The data used in the default calibration effort, which were afforded by the Long Term Pavement Performance (LTPP) database, have a network-level inference space. As implementation proceeds, state highway agencies may be inclined to calibrate at a local network level. However, with a focus on the calibration data set to local project-level conditions, model prediction error can be reduced further. Under this study, Nebraska Department of Roads Pavement Management System data were used to calibrate two design guide smoothness models at the local project level. …