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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Centroidal Voronoi tessellation based polycube construction for adaptive all-hexahedral mesh generation
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Centroidal Voronoi tessellation based polycube construction for adaptive all-hexahedral mesh generation

机译：基于质心Voronoi细分的多立方体构造，用于自适应全六面体网格生成

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This paper presents a novel automatic polycube construction algorithm using centroidal Voronoi tessellation (CVT) based surface segmentation. Given a smooth surface triangle mesh, we segment triangles into six clusters in the surface normal space while satisfying the constraints of polycube construction. A bijective mapping between the input mesh and polycube surfaces is then built via a planar domain parameterization. We develop a new harmonic boundary-enhanced centroidal Voronoi tessellation (HBECVT) method by including local neighbouring information in the energy function. Improving upon the classic CVT method, the HBECVT algorithm can not only overcome the sensitivity to the initialization and noise, but also improve the segmentation results and the resulting polycubes by reducing non-monotone boundaries. Based on the constructed polycube, we then generate quality all-hexahedral (all-hex) meshes. The uniform all-hex mesh and volumetric T-mesh can be obtained through the octree subdivision and mapping. We can also generate adaptive all-hex meshes by extracting the dual mesh from a hybrid octree, which consists of polyhedral cells and each grid point is always shared by eight cells. Several examples are presented in this paper to show the robustness of our algorithms. (C) 2016 Elsevier B.V. All rights reserved.
机译：本文提出了一种新的基于质心Voronoi细分（CVT）的表面分割的自动多立方体构造算法。给定一个平滑的表面三角形网格，我们将三角形在表面法线空间中划分为六个簇，同时满足多立方体构造的约束。然后，通过平面域参数化在输入网格和多立方体曲面之间建立双射映射。通过在能量函数中包含局部邻近信息，我们开发了一种新的谐波边界增强型质心Voronoi曲面细分（HBECVT）方法。 HBECVT算法在经典CVT方法的基础上进行了改进，不仅可以克服对初始化和噪声的敏感性，而且还可以通过减少非单调边界来改善分割结果和生成的多立方体。基于构造的多维数据集，我们然后生成高质量的全六面体（全十六进制）网格。可以通过八叉树细分和映射来获得统一的全六角网格和体积T网格。我们还可以通过从混合八叉树提取双网格来生成自适应全六角网格，混合八叉树由多面体单元组成，每个网格点始终由八个单元共享。本文提供了几个示例，以展示我们算法的鲁棒性。 （C）2016 Elsevier B.V.保留所有权利。

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