@article{Hart2020,
    author = {Hart, Kenneth A and Rimoli, Julian J},
    title = {Generation of statistically representative microstructures with direct grain geomety control},
    journal = {Computer Methods in Applied Mechanics and Engineering},
    volume = {370},
    pages = {113242},
    year = {2020},
    issn = {0045-7825},
    doi = "https://doi.org/10.1016/j.cma.2020.113242",
    url = "http://www.sciencedirect.com/science/article/pii/S0045782520304278",
    keywords = "Microstructure, Polycrystal, Finite element modeling, Laguerre tessellation, Multi-sphere",
    abstract = "Microstructural characteristics play a significant role in the determination of effective properties of materials. Consequently, most numerical tools aimed at predicting such properties require, as a starting point, the availability of geometric representations of such microstructures. In this paper, we introduce a method for generating statistically representative synthetic microstructures for materials involving multiple phases. Our method is based on traditional seed placement and tessellation approaches, with three critical improvements: (i) allowing for controlled seed overlap to better represent microstructural statistics, (ii) multi-sphere representation of 3D ellipsoids to account for arbitrarily elongated grains, and (iii) novel application of the axis aligned bounding box tree structure for accelerated seed placement. Our method recreates a diverse set of microstructural features, including the presence of spherical and non-spherical grain geometries, amorphous phases, and voids. After the method is presented, we proceed with a rigorous numerical analysis demonstrating its ability to reproduce key statistical features of target microstructures. The algorithms presented are freely available and open source through the package MicroStructPy."
}
