{"title":"MatGBM: A Computer Vision-Aided Triangular Mesh Generator for High-Fidelity Grain-Based Model","authors":"","doi":"10.1016/j.compgeo.2024.106871","DOIUrl":null,"url":null,"abstract":"<div><div>The grain-based model (GBM) stands as a renowned model for polycrystalline simulations in computational mechanics. Despite its popularity, there remains a critical need for a more advanced and user-friendly tool to generate high-fidelity microstructures with specified grain size distributions. Addressing this need, this paper introduces ’MatGBM’, an innovative modeling tool that aspires to enhance numerical simulations of polycrystalline materials. MatGBM seamlessly integrates three modules: a computer vision-aided mineral grain distribution detection, Voronoi tessellation processing, and triangular mesh generation. To accurately capture the two-dimensional structural characteristics of polycrystalline materials, the mineral grain distribution detection module employs computer vision functions to pinpoint particle coordinates and areas. The weighted Voronoi tessellation is generated and processed based on the original grain distribution features, resembling the original image of the polycrystalline material more closely than basic Voronoi tessellation. Finally, MatGBM directly outputs triangular mesh using two optional meshing tools based on the Voronoi polygons. Our rigorous testing via uniaxial compressive tests, Brazilian splitting tests, and three-point bending tests in crystalline rocks and metals, using the combined finite-discrete element method, validates that MatGBM can reliably reproduce the key deformation, damage, and failure characteristics of polycrystalline materials. Overall, MatGBM emerges not only as a promising tool for numerical simulations of rock, metallurgic, and ceramic materials, but also as a potent pre-processing tool for multiple numerical methods.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Geotechnics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0266352X24008103","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The grain-based model (GBM) stands as a renowned model for polycrystalline simulations in computational mechanics. Despite its popularity, there remains a critical need for a more advanced and user-friendly tool to generate high-fidelity microstructures with specified grain size distributions. Addressing this need, this paper introduces ’MatGBM’, an innovative modeling tool that aspires to enhance numerical simulations of polycrystalline materials. MatGBM seamlessly integrates three modules: a computer vision-aided mineral grain distribution detection, Voronoi tessellation processing, and triangular mesh generation. To accurately capture the two-dimensional structural characteristics of polycrystalline materials, the mineral grain distribution detection module employs computer vision functions to pinpoint particle coordinates and areas. The weighted Voronoi tessellation is generated and processed based on the original grain distribution features, resembling the original image of the polycrystalline material more closely than basic Voronoi tessellation. Finally, MatGBM directly outputs triangular mesh using two optional meshing tools based on the Voronoi polygons. Our rigorous testing via uniaxial compressive tests, Brazilian splitting tests, and three-point bending tests in crystalline rocks and metals, using the combined finite-discrete element method, validates that MatGBM can reliably reproduce the key deformation, damage, and failure characteristics of polycrystalline materials. Overall, MatGBM emerges not only as a promising tool for numerical simulations of rock, metallurgic, and ceramic materials, but also as a potent pre-processing tool for multiple numerical methods.
期刊介绍:
The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.