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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Computer Methods in Applied Mechanics and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
