Use of Superpave Gyratory Compaction Data for Rutting Prediction

Abstract

This paper presents the estimation results of an improved nonlinear rutting progression model for asphalt concrete mixes. Rutting is modeled as a function of traffic, temperature, and mix characteristics, including voids filled with asphalt, asphalt content, in-place air voids, surface area, and the densification slope. Mixed effects, an advanced statistical technique that allows the consideration of several sources of randomness and autocorrelated disturbances, is used for the estimation of the model parameters. The estimation results with measurements from WesTrack indicate that the model is statistically significant. Further, the model correctly anticipates the dramatic failure of the WesTrack replacement sections (approximately