Effect of the Calibration Protocol on the Prediction of Rutting Performance of Granular Materials

Rutting is a common distress in asphalt pavements, characterized by surface depressions in the wheel paths. Understanding the mechanisms and predicting rutting performance is crucial for pavement design and maintenance. There is a Brazilian model by Guimarães used for rut depth prediction of granular and soil materials used as input to predict pavement performance in terms of permanent deformation and there is the need to solve a nonlinear regression to obtain this model’s calibration coefficients. This chapter investigates the effect of different calibration protocols on the prediction of rutting performance in granular materials and compares the rut depth prediction by considering two different software, Solver and LabFit, in the calibration of the model for permanent deformation. Materials from the subbase layer and the subgrade of an experimental test section are tested and considered as constituting materials of a typical Brazilian pavement structure. Results indicate that LabFit provides a better fit than Solver, resulting in improved match between observed and predicted data. The analysis demonstrates that different calibration protocols lead to significantly different rut depth predictions. The findings highlight the importance of carefully selecting a calibration protocol and provide insights into improving rutting prediction models for asphalt pavements.