A New Adaptive Mesh Refinement Method in FEA Based on Magnetic Field Conservation at Elements Interfaces and Non-Conforming Mesh Refinement Technique
| Autor: | Akihisa Kameari, Takuto Naoe, Hajime Igarashi, So Noguchi, Shinya Matsutomo, Akira Ahagon, Vlatko Cingoski |
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| Rok vydání: | 2017 |
| Předmět: |
element surface integral term
010302 applied physics Computer and information sciences Computer science Adaptive mesh refinement Estimator Curvature 01 natural sciences Finite element method Magnetic flux Electronic Optical and Magnetic Materials Mesh generation error estimation 0103 physical sciences Adaptive meshing finite-element analysis (FEA) Other engineering and technologies Image-based meshing Electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Algorithm Realization (systems) |
| Zdroj: | IEEE Transactions on Magnetics. 53:1-4 |
| ISSN: | 1941-0069 0018-9464 |
| Popis: | Mesh quality strongly affects the solution accuracy in electromagnetic finite-element analysis. Hence, the realization of adequate mesh generation becomes a very important task. Several adaptive meshing methods for automatic adjustments of the mesh density in accordance with the shape and complexity of the analyzed problem have been proposed. However, the most of them are not enough robust, some are quite laborious and could not be universally used for adaptive meshing of complex analysis models. In this paper, a new adaptive mesh refinement method based on magnetic field conservation at the border between finite elements is proposed. The proposed error estimation method provides easy mesh refinements, and generates smaller element within regions with large curvature of the magnetic flux lines. The proposed adaptive mesh refinement method based on non-conforming edge finite elements, which could avoid generation of flat or ill-shaped elements, was applied to a simple magnetostatic permanent magnet model. To confirm the validity and accuracy, the obtained results were compared with those obtained by means of the Zienkiewicz-Zhu (ZZ) error estimator. The results show that the computational error using the proposed method was reduced down to 1% compared with that of the ZZ method, which yields error of 8.6%, for the same model. |
| Databáze: | OpenAIRE |
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