3D Microstructural Models for Asphalt Mixtures Using X-Ray Computed Tomography Images

Abstract

In this paper, aggregate orientation, aggregate gradation, sand mastic (a very fine sand-asphalt mixture) distribution, and air void distribution in the asphalt mixture were analyzed and modeled by capturing images using the X-ray Computed Tomography (CT) techniques. The mixture properties were predicted from X-ray CT images of the aggregate, mastic, and air voids. Moreover, the asphalt mixture images were utilized in modeling using the distinct element method approach for both two-dimensional (2D) and three-dimensional (3D) approaches. Three replicates of 3D distinct element model and six replicates of 2D distinct element model were simulated. 2D images were visualized by vertical orientation so that real distribution of air void levels could be captured. The mastic dynamic modulus and aggregate elastic modulus were determined and used as input parameters in the distinct element modeling. The strain responses of the asphalt mastic and mixture models under compressive load were monitored, and the dynamic moduli computed. The experimental measurements were compared with the 2D and 3D predictions. The 3D distinct element models were able to predict the asphalt mixture dynamic modulus. The 3D model's prediction is much better than that of 2D models. This outcome is a significant breakthrough in the modeling of asphalt mixture from 2D approach to 3D.