4.7 Article

An anisotropic scale-invariant unstructured mesh generator suitable for volumetric imaging data

期刊

JOURNAL OF COMPUTATIONAL PHYSICS
卷 228, 期 3, 页码 619-640

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jcp.2008.09.030

关键词

Computational fluid dynamics; Meshing biological structures; Delaunay

资金

  1. NHLBI NIH HHS [R01 HL073598-01A1, R01 HL073598] Funding Source: Medline

向作者/读者索取更多资源

We present a boundary-fitted, scale-invariant unstructured tetrahedral mesh generation algorithm that enables registration of element size to local feature size. Given an input triangulated Surface mesh, a feature size field is determined by casting rays normal to the Surface and into the geometry and then performing gradient-limiting operations to enforce continuity of the resulting field. Surface mesh density is adjusted to be proportional to the feature size field and then a layered aniscitropic Volume mesh is generated. This mesh is scale-invariant in that roughly the same number of layers of mesh exist in mesh cross-sections, between a minimum scale size L-min and a maximum scale size L,,,,x. We illustrate how this field can be used to produce quality grids for computational fluid dynamics based simulations of challenging, topologically complex biological surfaces derived from magnetic resonance images. The algorithm is implemented in the Pacific Northwest National Laboratory (PNNL) version of the Los Alamos grid toolbox LaGriT. Research funded by the National Heart and Blood Institute Award 1RO1HL073598-01A1. (c) 2008 Elsevier Inc. All rights reserved.

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