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Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy
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  • Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy
  • Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy
저자명
Imai. Yusuke,Hiraoka. Hiroyuki,Kawaharada. Hiroshi
간행물명
Journal of computational design and engineering
권/호정보
2014년|1권 2호|pp.88-95 (8 pages)
발행정보
한국CAD/CAM학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Because the cost of performance testing using actual products is expensive, manufacturers use lower-cost computer-aided design simulations for this function. In this paper, we propose using hexahedral meshes, which are more accurate than tetrahedral meshes, for finite element analysis. We propose automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated using a voxel-based algorithm. In our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vectors in the fitting to preserve sharp features. However, this method could not represent concave sharp features precisely. In this proposal, we improve our previous Laplacian energy minimization by adding a term that depends on multi-normal vectors instead of using normal vectors. Furthermore, we accentuate a convex/concave surface subset to represent concave sharp features.