New Model for Predicting Rutting Performance of Superpave Asphalt Mixes

Abstract

This study presents a new model for predicting rutting performance and stripping characteristics of Superpave asphalt concrete (AC) mixes from laboratory Hamburg Wheel Tracking Device (HWTD) test data. A total of 33 AC mixes were used and tested for HWTD to determine the rutting and stripping susceptibility of the mixes. The combined Franken–power approach was used to fit the rut data. The pertinent regression coefficients were then correlated to the mix’s physical and volumetric properties, that is, binder grade, reclaimed asphalt pavement content, effective asphalt content, voids in mineral aggregate, and aggregate gradation. A logistic regression analysis was employed in the model to capture the stripping characteristic of the mixes. The developed model was validated with a new set of HWTD test data. The model was observed to be capable of predicting the rutting and stripping characteristics of the AC mixes, which agreed reasonably well with laboratory test results. Therefore, the proposed model could be used for mix screening purposes at the mix design stage to avoid the significant consequences of failure in the field, and as a tool to determine rutting performance when laboratory testing is not feasible.

Laboratory Investigation of Open Graded Friction Courses with Different Binder Grades and Aggregate Gradations

“…Figures 6 a and b show that the CA loss decreases as the binder grade increases regardless of aggregate gradation for both unconditioned and moisture conditioned states, respectively. This is probably a result of the modification of binders, binders with higher grades have better damage tolerances ( 21 , 22 ). Thus, the PG 76-22+ OGFCs have the lowest CA mass losses, followed by the PG 70-28+ OGFCs, regardless of aggregate gradation.…”