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Generation of adaptive refinement tetrahedral meshes over domains of multi-chamber partition

Haoyu Huang (State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, Dalian, China) (Department of Engineering Mechanics, Dalian University of Technology, Dalian, China)
Julin Shan (Institute of Information Sensing, Xidian University, Xi’an, China)
S.H. Lo (Department of Civil Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR)
Fei Yu (Hong Kong Quantum AI Lab, Hong Kong, Hong Kong SAR)
Jie Cao (School of Mathematics and Physics, University of South China, Hengyang, China)
Jihai Chang (School of Electronic Engineering, Xidian University, Xi’an, China)
Z.Q. Guan (State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, Dalian, China) (Department of Engineering Mechanics, Dalian University of Technology, Dalian, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 30 September 2024

56

Abstract

Purpose

In this study, we propose a tetrahedral mesh generation and adaptive refinement method for multi-chamber, multi-facet, multiscale and surface-solid mesh coupling with extremely thin layers, solving the two challenges of mesh generation and refinement in current electromagnetic simulation models.

Design/methodology/approach

Utilizing innovative topology transformation techniques, high-precision intersection judgment algorithms and highly reliable boundary recovery algorithms to reduce the number of Steiner locking points. The feasible space for the reposition of Steiner points is determined by using the linear programming. During mesh refinement, an edge-split method based on geometric center and boundary facets node size is devised. Solving the problem of difficult insertion of nodes in narrow geometric spaces, capable of filtering the longest and boundary edges of tetrahedrons, refining the mesh layer by layer through multiple iterations, and achieving collaborative optimization of surface and tetrahedral mesh. Simultaneously, utilizing a surface-facet preserving mesh topology optimization algorithm to improve the fit degree between the mesh and geometry.

Findings

Initial mesh generation for electromagnetic models, compared to commercial software, the method proposed in this paper has a higher pass rate and better mesh quality. For the adaptive refinement performance of high-frequency computing, this method can generate an average of 50% fewer meshes compared to commercial software while meeting simulation accuracy.

Originality/value

This paper proposes a complete set of mesh generation and adaptive refinement theories and methods designed for the structural characteristics of electromagnetic simulation models, which meet the needs of real-world industrial applications.

Keywords

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2023YFB3309100, 2021YFB3302200). The authors would also like to appreciate the joint support provided by Xidian University and Wuxi Flytrum Electronic Information Technology Co., Ltd.

Citation

Huang, H., Shan, J., Lo, S.H., Yu, F., Cao, J., Chang, J. and Guan, Z.Q. (2024), "Generation of adaptive refinement tetrahedral meshes over domains of multi-chamber partition", Engineering Computations, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EC-09-2023-0617

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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