Inclusion of aggregate angularity, texture, and form in estimating dynamic modulus of asphalt mixes

Abstract

The present study was undertaken to develop a model that utilizes aggregate shape parameters (i.e. angularity, texture and form) in estimating the dynamic modulus of asphalt mixes. Dynamic modulus tests were conducted on 20 different mixes comprised of different aggregate sources, sizes, asphalt binder, and air void levels. The coarse and fine aggregates were recovered from each mix, and their shape parameters were measured using an automated aggregate image measurement system (AIMS). A nonlinear regression model was developed to estimate the dynamic modulus of the mix in terms of its aggregate gradation, aggregate shape parameters, viscosity of asphalt binder, and volumetric properties. The correlation coefficient (R 2) for the developed model was found to be 0.95 and 0.92 on logarithmic and arithmetic scales, respectively, with a mean average relative error (MARE) of 21.9%. The performance of this model was compared with the widely accepted Witczak model that does not use the shape parameters of the aggregates. The MARE for the Witczak model was estimated significantly higher than the developed model. Results show that the dynamic modulus of the mix increases with an increase in the angularity and texture of aggregates and that the inclusion of shape parameters can enhance the prediction capability of a model.