Many predictive techniques for determining the dynamic modulus of asphalt concrete mixes have evolved over the past 25 years. One such model, developed at the University of Maryland, has been widely incorporated in design manuals and methods used throughout the world. However, the current predictive model only allows the determination of the dynamic modulus from the original bitumen properties among other variables. This model has been developed from dynamic (complex) modulus tests on laboratory-prepared specimens and does not take into account the hardening effects that take place during short- and long-term aging. By incorporating recent field studies on the aged viscosity of conventional asphalt cements, a revised model for the dynamic modulus of asphalt mixtures has been developed using the actual bitumen viscosity as the most important predictor variable in place of temperature. This modification now allows the model to be used to predict dynamic modulus for mixtures exhibiting any degree of binder aging. Also, by using a sigmoidal function model form, significant improvement in prediction rationality was achieved for using the model at extreme temperature conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.