Abstract

The void distribution in concrete materials strongly affects its material properties. Therefore, identification of the spatial void distribution is important to understand and estimate material behavior. To quantify the void distribution inside lightweight aggregates, a computed tomography (CT) image can be effective, as it is non-destructive. Here, three-dimensional void images of lightweight aggregates are generated by stacking cross-sectional CT images. The spatial distribution of voids in the aggregate along a direction is visualized on a sphere using a probability distribution function. To describe the void distribution of aggregates, a two-point correlation function is used. The stiffness of the lightweight aggregate for a direction is also examined. We find that the direction-based probability distribution and stiffness from the CT images are effective for characterizing the void distributions of aggregates. In addition, the anisotropy ratio of voids and the stiffness are closely related along with the void volume fraction.

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