Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy

Adaptive Anisotropic Unstructured Mesh Generation Method Based on Fluid Relaxation Analogy

Year:    2020

Author:    Lin Fu, Xiangyu Hu, Nikolaus A. Adams

Communications in Computational Physics, Vol. 27 (2020), Iss. 5 : pp. 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.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2019-0049

Communications in Computational Physics, Vol. 27 (2020), Iss. 5 : pp. 1275–1308

Published online:    2020-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    34

Keywords:    Adaptive unstructured meshes anisotropic meshes level-set SPH anisotropic Delaunay triangulation.

Author Details

Lin Fu

Xiangyu Hu

Nikolaus A. Adams