Static creep of modified superpave asphalt concrete mixtures using crumb tire rubber, microcrystalline synthetic wax, and nano-silica

Abstract

ABSTRACT This research investigates the effect of adding three different modifiers to laboratory-prepared Superpave asphalt concrete mixtures to evaluate their ability to strengthen and reinforce asphalt concrete mixtures and improve their rutting resistance. The three used modifiers were Crumb Tire Rubber (CTR), Microcrystalline Synthetic Wax (MSW), and Nano Silica (NS). The CTR, MSW, and NS modifiers were added at their optimum contents determined previously which were 12%, 2%, and 5% by weight of asphalt binder, respectively. Asphalt concrete mixtures were tested at two temperature levels; 40°C and 55°C, and were compacted at two compactive efforts to simulate high and low levels of traffic with N des = 119 and 82, respectively. Static creep test was used to evaluate the effect of changing modifier type, temperature, and compactive effort on creep properties and rutting potential of modified mixtures through studying five creep parameters. These parameters were accumulated axial micro-strain, creep stiffness, steady state creep slope, creep compliance, and creep compliance parameters. Results revealed that all the used modifiers had improved mixture performance. It was found that CTR modified mixtures had the best performance at high temperature level, while NS modified mixtures showed the best performance at medium temperatures. Moreover, it was found that lower temperatures and higher compactive efforts increase mixture stiffness and decrease deformation and their rutting potential. Statistical analysis was carried out and regression models were developed for the prediction of stiffness modulus, accumulated axial micro-strain, and steady state creep slope as a function of modifier type (MT), testing temperature (Temp) and compactive effort (CE). Models yielded relatively high coefficients of determination (R 2) and adjusted R 2, indicating their ability in explaining much of the variability in the response variables.