3D finite element meshing from imaging data
3D finite element meshing from imaging data
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DOI：
10.1016/j.cma.2004.11.026
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发表时间：
2005-01-01
影响因子：
7.2
通讯作者：
Sohn, BS
中科院分区：
文献类型：
--
作者：
Zhang, YJ;Bajaj, C;Sohn, BS
本文描述了一种直接从体积成像数据中提取自适应和高质量 3D 网格的算法。提取的四面体和六面体网格广泛用于有限元法（FEM）。自上而下的八叉树细分与双轮廓方法相结合，用于从体积成像数据中快速提取具有正确拓扑的自适应 3D 有限元网格。边缘收缩和平滑方法用于提高网格质量。主要贡献是将双轮廓方法扩展到具有边界特征敏感自适应的无裂纹间隔体积 3D 网格划分。与其他从成像数据中提取四面体的方法相比，我们的方法可以生成自适应且高质量的 3D 网格，而无需引入任何悬挂节点。该算法已成功应用于构建有限元计算的高质量网格。 (c) 2005 Elsevier B.V. 保留所有权利。
This paper describes an algorithm to extract adaptive and quality 3D meshes directly from volumetric imaging data. The extracted tetrahedral and hexahedral meshes are extensively used in the finite element method (FEM). A top-down octree subdivision coupled with a dual contouring method is used to rapidly extract adaptive 3D finite element meshes with correct topology from volumetric imaging data. The edge contraction and smoothing methods are used to improve mesh quality. The main contribution is extending the dual contouring method to crack-free interval volume 3D meshing with boundary feature sensitive adaptation. Compared to other tetrahedral extraction methods from imaging data, our method generates adaptive and quality 3D meshes without introducing any hanging nodes. The algorithm has been successfully applied to constructing quality meshes for finite element calculations. (c) 2005 Elsevier B.V. All rights reserved.