Abstract
Aiming at the infeasibility of using quadrilateral-prisms to describe sharp shapes, an improved vertical stretch algorithm was proposed to generate three-dimensional (3D) hybrid meshes based on the quadrilateral mesh converted from triangles to discretize the geometric models with pinch-out features. A robust and automatic mesh generator was developed, which served as a preprocessing tool for simulating metal forming, water flows and transports. An initial mixed mesh composed of cuspate hexahedra, quadrilateral- and triangular-prisms was constructed to capture the sharp features of pinch-out regions effectively. Five splitting templates were established to divide the 3D elements derived from pinch-out sub-domains into tetrahedra and triangular-prisms. The concept of splitting points was defined, based on which the appropriate implementation mode of each splitting template could be determined, so as to achieve the conformity and consistency of common faces and edges between different kinds of elements. Two topological optimization templates were established to improve the quality of degenerated triangular-prisms and tetrahedra. A new pinch-out boundary quadrilateral insertion method was proposed to avoid the generation of cuspate hexahedra, which simplified the conformity treatment strategies and improved the quality of the resulting mesh to a certain extent. Practical applications confirmed that the hybrid mesh generation methods proposed in this paper could discretize the geometric models with pinch-out features precisely. The requirements on mesh conformity and refinement were also able to be fully satisfied.
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Acknowledgements
This project is supported by National Natural Science Foundation of China (Grant No. 51705290), the Young Scholars Program of Shandong University (No. 2018WLJH28), and Project funded by China Postdoctoral Science Foundation (Grant No. 2018 M640626).
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Sun, L., Zhao, G. & Yeh, GT. 3D hybrid mesh generation with an improved vertical stretch algorithm for geometric models with pinch-out features. Comput Geosci 25, 575–599 (2021). https://doi.org/10.1007/s10596-020-10026-x
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DOI: https://doi.org/10.1007/s10596-020-10026-x