MatGBM: A Computer Vision-Aided Triangular Mesh Generator for High-Fidelity Grain-Based Model

IF 5.3 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Louis Ngai Yuen Wong, Zihan Liu
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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.
MatGBM:用于高保真纹理模型的计算机视觉辅助三角网格生成器
基于晶粒的模型(GBM)是计算力学中多晶体模拟的著名模型。尽管该模型广受欢迎,但仍迫切需要一种更先进、更方便用户使用的工具,以生成具有指定晶粒尺寸分布的高保真微结构。为了满足这一需求,本文介绍了 "MatGBM",这是一种创新的建模工具,旨在增强多晶材料的数值模拟。MatGBM 无缝集成了三个模块:计算机视觉辅助矿物晶粒分布检测、Voronoi 镶嵌处理和三角网格生成。为了准确捕捉多晶材料的二维结构特征,矿物晶粒分布检测模块利用计算机视觉功能精确定位颗粒坐标和区域。根据原始晶粒分布特征生成并处理加权 Voronoi 网格,与基本 Voronoi 网格相比,加权 Voronoi 网格更接近多晶材料的原始图像。最后,MatGBM 使用两个基于 Voronoi 多边形的可选网格工具直接输出三角形网格。我们使用有限元和离散元相结合的方法,对晶体岩石和金属进行了单轴压缩试验、巴西劈裂试验和三点弯曲试验等严格测试,验证了 MatGBM 能够可靠地再现多晶材料的关键变形、损伤和破坏特征。总之,MatGBM 不仅是岩石、冶金和陶瓷材料数值模拟的理想工具,也是多种数值方法的有效预处理工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers and Geotechnics
Computers and Geotechnics 地学-地球科学综合
CiteScore
9.10
自引率
15.10%
发文量
438
审稿时长
45 days
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.
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