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Bc-hexmatching: an improved hexahedral mesh matching approach based on base-complex structure

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Abstract

Automatic generation of hexahedral meshes for complex geometries is still a challenging problem, the domain-decomposition based method is one of the promising methods for such problems. When generating the meshes of sub-components of a domain, it is often necessary to impose consistent mesh constraints on the interfaces between sub-components. The adoption of mesh matching algorithms can relax such constraints, and improve the efficiency and robustness of mesh generation framework. In this paper, a new mesh matching algorithm based on base-complex structure is proposed. In our method, the base-complex structures of the sub-components to be matched are obtained and optimized first, and then they are used to match the interfaces between the sub-components via dual chord operations on the base-complex structures. After the matching process, an optimization problem is formulated and solved to adjust the positions of corresponding vertices on the interfaces. Compared to the current mesh matching algorithms, instead of performing dual operations directly on mesh elements, the proposed method needs less dual operations and is able to obtain higher quality elements near the interfaces. Finally, the effectiveness of the proposed algorithm is verified by several matching examples.

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Funding

This research was supported by the National Key R &D Program of China under Grant No.2020YFB1709402, the Zhejiang Provincial Science and Technology Program in China under Grant 2021C01108, the National Natural Science Foundation of China (No.U22A2033, 62202130, U1909210), the Zhejiang Provincial Science and Technology Program in China (No.LQ22F020026), and the Open project of State Key Laboratory of CAD & CG at Zhejiang University (No.A2212).

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Correspondence to Gang Xu or Yufei Pang.

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Zhao, Q., Xu, G., Xiao, Z. et al. Bc-hexmatching: an improved hexahedral mesh matching approach based on base-complex structure. Engineering with Computers (2023). https://doi.org/10.1007/s00366-023-01908-6

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