| 基于特征保持的三维模型四面体化及优化 |
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| 引用本文： | 王君良,李重,金小刚,马利庄.基于特征保持的三维模型四面体化及优化[J].软件学报,2015,26(S2):42-51. |
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| 作者姓名： | 王君良 李重 金小刚 马利庄 |
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| 作者单位： | 浙江理工大学数学科学系, 浙江杭州 310018,浙江理工大学数学科学系, 浙江杭州 310018,CAD & CG国家重点实验室(浙江大学), 浙江杭州 310058,上海交通大学计算机科学与工程系, 上海 200240 |
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| 基金项目： | 国家自然科学基金(61272298, 61133009);教育部留学回国人员科研启动基金([2009]1590);浙江省自然科学基金(LY14A010032);浙江理工大学521人才资助项目(11430032521301) |
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| 摘 要： | 三维模型四面体化是一种重要的有限元网格生成技术.介绍了一种特征保持的四面体网格生成及优化算法.首先使用三维模型主成分分析进行预处理,然后用体心立方构建初始四面体,接着通过拉普拉斯坐标改变模型边界切点的移动方式保持模型的局部特征,最后构造改进的密度能量误差函数优化四面体网格质量.实验结果表明,该方法可行、有效,且能很好地保持模型特征.
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| 关 键 词： | 四面体化 主成分分析 拉普拉斯坐标 密度能量误差 |
| 收稿时间： | 2014/1/3 0:00:00 |
| 修稿时间： | 2014/4/18 0:00:00 |
Feature-Preserving Tetrahedralization and Optimization for 3D Models |
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| WANG Jun-Liang,LI Zhong,JIN Xiao-Gang and MA Li-Zhuang.Feature-Preserving Tetrahedralization and Optimization for 3D Models[J].Journal of Software,2015,26(S2):42-51. |
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| Authors: | WANG Jun-Liang LI Zhong JIN Xiao-Gang and MA Li-Zhuang |
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| Affiliation: | Department of Mathematical Sciences, Zhejiang Sci-Tech University, Hangzhou 310018, China,Department of Mathematical Sciences, Zhejiang Sci-Tech University, Hangzhou 310018, China,State Key Laboratory of CAD & CG(Zhejiang University), Hangzhou 310058, China and Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200240, China |
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| Abstract: | Tetrahedralization of 3D models is an important technique in finite element mesh generation. An algorithm of tetrahedral mesh generation and optimization is proposed in this paper. It first uses principal component analysis of 3D models for the preprocessing. Then the initial tetrahedral mesh is built based on the body-centered cubic while the movement of cutting point is improved via Laplacian coordinates for keeping local features. Finally, it optimizes the quality of the tetrahedral mesh by using the function of energy-density error. Experimental results demonstrate that this method is viable, effective, and can preserve the model feature well. |
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| Keywords: | tetrahedralization PCA (principal component analysis) Laplacian coordinate energy-density error |
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