Abstract

This study develops a computational framework for highly efficient generation of realistic mesoscale concrete models by exploiting micro XCT 3D images, a bin packing algorithm and an open-source dynamic physics engine (“Bullet”). The aggregates extracted from an XCT image dataset are first smoothed by the HC-Laplacian algorithm and then surface-meshed with optimisation. A library of aggregates characterised with five shape indices is then built and subsequently used with a “greedy search” bin packing algorithm to generate meso-models of concrete according to specified volume fraction and size gradation. To build concrete models with high compactness, for example, with 40–60% contents of aggregates, the Bullet physics engine, based on a hard-contact discrete element method, is further applied to simulate the complicated compaction and vibration process in real casting procedures. The developed framework provides a promising basis for further mesoscale studies, such as 3D printing, multiscale homogenization, damage and fracture mechanisms, and environmental factors-induced degradation.

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