首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Constructing volumetric parameterization based on directed graph simplification of ℓ_1 polycube structure from complex shapes
【24h】

Constructing volumetric parameterization based on directed graph simplification of ℓ_1 polycube structure from complex shapes

机译:基于复杂形状的ℓ_1多立方体结构的有向图简化构造体积参数化

获取原文
获取原文并翻译 | 示例

摘要

Volumetric spline parameterization of complex geometry plays a key role in isogeometric analysis (IGA). In this paper, we propose a general framework to construct volumetric parameterization from complex shapes based on directed graph simplification of the l(1) polycube structure. By minimizing the l(1)-norm of the normals on the input triangular meshes, a polycube structure can be generated with robustness, efficiency, and controllability. Then an algorithm is proposed for l(1) polycube structure simplification with a directed graph, which is an abstract structure generated from the polycube. After simplification, the vertex number of the directed graph will decrease, and the polycube structure will become more simple. From the simplified polycube structure, we construct a segmented surface by spline fitting techniques, and finally we fill each block with a trivariate B-spline volume with C-0-constraints. The proposed method can generate volumetric parameterization without an interior extraordinary vertex, and it has very high potential for constructing volumetric parameterization in IGA simulations. Some volume parameterization examples from complex shapes are presented to show the robustness and efficiency of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.
机译:复杂几何体的体积样条曲线参数化在等几何分析(IGA)中起关键作用。在本文中,我们提出了一个基于l(1)多立方体结构的有向图简化从复杂形状构造体积参数化的通用框架。通过最小化输入三角形网格上法线的l(1)-范数,可以生成具有鲁棒性,效率和可控性的多立方体结构。然后提出了一种有向图简化l(1)多维数据集结构的算法,该图是从多维数据集生成的抽象结构。简化后,有向图的顶点数将减少,并且多立方体结构将变得更简单。通过简化的多维数据集结构,我们通过样条拟合技术构造了一个分段曲面,最后,我们使用C-0约束的三元B样条曲线填充每个块。所提出的方法可以在没有内部非寻常顶点的情况下生成体积参数化,并且在IGA仿真中具有构建体积参数化的巨大潜力。给出了一些复杂形状的体积参数化示例,以显示该方法的鲁棒性和效率。 (C)2019 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号