Variable resolution Poisson-disk sampling for meshing discrete fracture networks

نویسندگان

چکیده

We present the near-Maximal Algorithm for Poisson-disk Sampling (nMAPS) to generate point distributions variable resolution Delaunay triangular and tetrahedral meshes in two three-dimensions, respectively. nMAPS consists of principal stages. In first stage, an initial distribution is produced using a cell-based rejection algorithm. second holes sample are detected efficient background grid filled obtain near-maximal covering. Extensive testing shows that generates mesh linear run time with number accepted points. demonstrate capabilities by meshing three-dimensional discrete fracture networks (DFN) surrounding volume. The discretized boundaries fractures, which represented as planar polygons, used seed 2D-nMAPS produce conforming triangulation. combined DFN 3D-nMAPS, produces tetrahedra network. Under set conditions naturally arise maximal samples satisfied nMAPS, two-dimensional triangulations guaranteed only have well-behaved faces. While does not provide triangulation quality bounds more than dimensions, we found low-quality 3D infrequent, can be readily removed, high balanced produced.

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ژورنال

عنوان ژورنال: Journal of Computational and Applied Mathematics

سال: 2022

ISSN: ['0377-0427', '1879-1778', '0771-050X']

DOI: https://doi.org/10.1016/j.cam.2022.114094