4.7 Article

Tetrahedral Meshing in the Wild

期刊

ACM TRANSACTIONS ON GRAPHICS
卷 37, 期 4, 页码 -

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3197517.3201353

关键词

Mesh Generation; Tetrahedral Meshing; Robust Geometry Processing

资金

  1. NSF CAREER award [1652515]
  2. NSF [IIS-1320635, DMS-1436591]
  3. NSERC Discovery Grants [RGPIN-2017-05235, RGPAS-2017-507938]
  4. Canada Research Chair award
  5. Connaught Fund

向作者/读者索取更多资源

We propose a novel tetrahedral meshing technique that is unconditionally robust, requires no user interaction, and can directly convert a triangle soup into an analysis-ready volumetric mesh. The approach is based on several core principles: (1) initial mesh construction based on a fully robust, yet efficient, filtered exact computation (2) explicit (automatic or user-defined) tolerancing of the mesh relative to the surface input (3) iterative mesh improvement with guarantees, at every step, of the output validity. The quality of the resulting mesh is a direct function of the target mesh size and allowed tolerance: increasing allowed deviation from the initial mesh and decreasing the target edge length both lead to higher mesh quality. Our approach enables black-box analysis, i.e. it allows to automatically solve partial differential equations on geometrical models available in the wild, offering a robustness and reliability comparable to, e.g., image processing algorithms, opening the door to automatic, large scale processing of real-world geometric data.

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