Keywords :
background mesh; curvature; feature size; mesh generation; octree; size field; surface proximity; Discrete curvatures; Medial axis transforms; Minimal interactions; Octree data structure; Surface curvatures; Surface triangulation; Three-dimensional mesh generations; Threedimensional (3-d); Numerical Analysis; Engineering (all); Applied Mathematics; General Engineering
Abstract :
[en] This article presents a methodology aiming at easing considerably the generation of high-quality meshes for complex three-dimensional (3D) domains. To this end, a mesh size field h(x) is computed, taking surface curvatures and geometric features into account. The size field is tuned by five intuitive parameters and yields quality meshes for arbitrary geometries. Mesh size is initialized on a surface triangulation of the domain based on discrete curvatures and medial axis transform computations. It is then propagated into the volume while ensuring the size gradient ∇h is controlled so as to obtain a smoothly graded mesh. As the size field is stored in an independent octree data structure, it can be computed separately, then plugged into any mesh generator able to respect a prescribed size field. The procedure is automatic, in the sense that minimal interaction with the user is required. Applications of our methodology on CAD models taken from the very large ABC dataset are presented. In particular, all presented meshes were obtained with the same generic set of parameters, demonstrating the universality of the technique.
Funding text :
The authors would like to thank the Belgian Fund for Scientific Research (FRIA/FC 29571) for their support. Financial support from the Simulation‐based Engineering Science (Génie Par la Simulation) program funded through the CREATE program from the Natural Sciences and Engineering Research Council of Canada is also gratefully acknowledged. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement ERC‐2015‐AdG‐694020).information Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada, Fonds pour la Formation ? la Recherche dans l'Industrie et dans l'Agriculture, FRIA/FC 29571; H2020 European Research Council, ERC-2015-AdG-694020The authors would like to thank the Belgian Fund for Scientific Research (FRIA/FC 29571) for their support. Financial support from the Simulation-based Engineering Science (G?nie Par la Simulation) program funded through the CREATE program from the Natural Sciences and Engineering Research Council of Canada is also gratefully acknowledged. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement ERC-2015-AdG-694020).Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada, Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture, FRIA/FC 29571; H2020 European Research Council, ERC‐2015‐AdG‐694020 Funding information
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