Volume 27, Issue 5
Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy

Lin Fu, Xiangyu Hu & Nikolaus A. Adams

Commun. Comput. Phys., 27 (2020), pp. 1275-1308.

Published online: 2020-03

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  • Abstract

In this paper, we extend the method (Fu et al., [1]) to anisotropic meshes by introducing an adaptive SPH (ASPH) concept with ellipsoidal kernels. First, anisotropic target feature-size and density functions, taking into account the effects of singularities, are defined based on the level-set methodology. Second, ASPH is developed such that the particle distribution relaxes towards the target functions. In order to prevent SPH particles from escaping the mesh generation regions, a ghost surface particle method is proposed in combination with a tailored interaction strategy. Necessary adaptations of supporting numerical algorithms, such as fast neighbor search, for enforcing mesh anisotropy are addressed. Finally, unstructured meshes are generated by an anisotropic Delaunay triangulation conforming to the Riemannian metrics for the resulting particle configuration. The performance of the proposed method is demonstrated by a set of benchmark cases.

  • Keywords

Adaptive unstructured meshes, anisotropic meshes, level-set, SPH, anisotropic Delaunay triangulation.

  • AMS Subject Headings

65M50, 51F99, 68U05, 34C40, 65M60, 65E05

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

lin.fu@tum.de (Lin Fu)

xiangyu.hu@tum.de (Xiangyu Hu)

nikolaus.adams@tum.de (Nikolaus A. Adams)

  • BibTex
  • RIS
  • TXT
@Article{CiCP-27-1275, author = {Fu , Lin and Hu , Xiangyu and A. Adams , Nikolaus }, title = {Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy}, journal = {Communications in Computational Physics}, year = {2020}, volume = {27}, number = {5}, pages = {1275--1308}, abstract = {

In this paper, we extend the method (Fu et al., [1]) to anisotropic meshes by introducing an adaptive SPH (ASPH) concept with ellipsoidal kernels. First, anisotropic target feature-size and density functions, taking into account the effects of singularities, are defined based on the level-set methodology. Second, ASPH is developed such that the particle distribution relaxes towards the target functions. In order to prevent SPH particles from escaping the mesh generation regions, a ghost surface particle method is proposed in combination with a tailored interaction strategy. Necessary adaptations of supporting numerical algorithms, such as fast neighbor search, for enforcing mesh anisotropy are addressed. Finally, unstructured meshes are generated by an anisotropic Delaunay triangulation conforming to the Riemannian metrics for the resulting particle configuration. The performance of the proposed method is demonstrated by a set of benchmark cases.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2019-0049}, url = {http://global-sci.org/intro/article_detail/cicp/15771.html} }
TY - JOUR T1 - Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy AU - Fu , Lin AU - Hu , Xiangyu AU - A. Adams , Nikolaus JO - Communications in Computational Physics VL - 5 SP - 1275 EP - 1308 PY - 2020 DA - 2020/03 SN - 27 DO - http://dor.org/10.4208/cicp.OA-2019-0049 UR - https://global-sci.org/intro/cicp/15771.html KW - Adaptive unstructured meshes, anisotropic meshes, level-set, SPH, anisotropic Delaunay triangulation. AB -

In this paper, we extend the method (Fu et al., [1]) to anisotropic meshes by introducing an adaptive SPH (ASPH) concept with ellipsoidal kernels. First, anisotropic target feature-size and density functions, taking into account the effects of singularities, are defined based on the level-set methodology. Second, ASPH is developed such that the particle distribution relaxes towards the target functions. In order to prevent SPH particles from escaping the mesh generation regions, a ghost surface particle method is proposed in combination with a tailored interaction strategy. Necessary adaptations of supporting numerical algorithms, such as fast neighbor search, for enforcing mesh anisotropy are addressed. Finally, unstructured meshes are generated by an anisotropic Delaunay triangulation conforming to the Riemannian metrics for the resulting particle configuration. The performance of the proposed method is demonstrated by a set of benchmark cases.

Lin Fu, Xiangyu Hu & Nikolaus A. Adams. (2020). Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy. Communications in Computational Physics. 27 (5). 1275-1308. doi:10.4208/cicp.OA-2019-0049
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