Predictive Framework for Modeling Changes in Asphalt Mixture Moduli with Oxidative Aging
Nooralhuda F. Saleh, Douglas Martins Mocelin, Farhad Yousefi Rad, Cassie Castorena, B. Shane Underwood, Y. Richard Kim
Abstract
This paper presents a predictive framework for asphalt mixture moduli as a function of aging time with two levels of sophistication. This work is built on the method currently implemented in Pavement mechanistic-empirical (ME) that uses an effective time/frequency concept based on time-aging superposition to model the effect of aging on a mixture’s modulus. Time-aging superposition implies that an asphalt mixture’s modulus mastercurves, corresponding to different aging levels, coincide when they are shifted horizontally on the log-frequency axis. This study improves the accuracy of the existing model by decoupling the time-temperature and time-aging shifts. The new framework also uses the binder dynamic shear modulus | G*| as an aging index instead of the viscosity, which is used in Pavement ME. The | G*| aging index is used to calculate an effective frequency at short-term aging (STA), which is then used in the asphalt mixture sigmoidal model to calculate the corresponding asphalt mixture modulus with aging. The pavement aging model introduced by NCHRP 09-54 predicts log | G*| at 64°C and 10 rad/s for a specific field-aged condition and pavement depth. The proposed framework can use the predicted log | G*| to predict the mixture’s corresponding dynamic modulus (| E*|) at that aging level and pavement depth. Level 1 of this framework requires characterizing the | G*| at STA and calibrating the NCHRP 09-54 pavement aging model as well as measuring the mixture | E*| at STA. Level 2 does not require any binder testing, providing relatively less accurate predictions but relieving some testing requirements.