Viscosity-Based Complex Modulus and Phase-Angle Predictive Models for the Superpave Asphalt Mixtures of New Mexico

Abstract

The recently developed mechanistic-empirical design method of pavement uses the nationally calibrated dynamic modulus predictive model for the design and analysis of asphalt pavements. This study calibrates this model for the local Superpave asphalt concrete mixtures of New Mexico. Although the calibrated model shows good correlation, this study develops a new regression-based model which shows improved correlation with the tested data. A total of 54 asphalt-aggregate mixtures are compacted, cored, and sawed to cylindrical specimens and tested for dynamic modulus and phase angle. The time-temperature superposition principle is applied to develop master curves at a reference temperature of 7°F (21.1°C). The master curve parameters are correlated with the aggregate and binder properties. The local predictive models are validated for the dynamic modulus and phase angle of other AC mixtures which were not used to develop the models. Statistical evaluation shows that fairly accurate estimations of dynamic modulus and phase angle of the local mixes are possible by using these local predictive models.