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Diagonalized Macromodels in Finite Element Method for Fast Electromagnetic Analysis of Waveguide Components
Abstract
A new technique of local model-order reduction (MOR) in 3-D finite element method (FEM) for frequency-domain electromagnetic analysis of waveguide components is proposed in this paper. It resolves the problem of increasing solution time of the reduced-order system assembled from macromodels created in the subdomains, into which an analyzed structure is partitioned. This problem becomes particularly relevant for growing size and count of the macromodels, and when they are cloned in multiple locations of the structures or are used repeatedly in a tuning and optimization process. To significantly reduce the solution time, the diagonalized macromodels are created by means of the simultaneous diagonalization and subsequently assembled in the global system. For the resulting partially diagonal matrix, an efficient dedicated solver based on the Schur complement technique is proposed. The employed MOR method preserves frequency independence of the macromodels, which is essential for efficient diagonalization, as it can be performed once for the whole analysis bandwidth. The numerical validation of the proposed procedures with respect to accuracy and speed was carried out for varying size and count of macromodels. An exemplary finite periodical waveguide structure was chosen to investigate the influence of macromodel cloning on the resultant efficiency. The results show that the use of the diagonalized macromodels provided a significant solution speedup without any loss of accuracy
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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Electronics
no. 8,
pages 1 - 23,
ISSN: 2079-9292 - Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Nyka K.: Diagonalized Macromodels in Finite Element Method for Fast Electromagnetic Analysis of Waveguide Components// Electronics -Vol. 8,iss. 3 (2019), s.1-23
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/electronics8030260
- Sources of funding:
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- Project Aggregate Farming in the Cloud
- Verified by:
- Gdańsk University of Technology
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