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Abstract
One of steps in the design of microwave filters is numerical tuning using full-wave simulators. Typically, it is a time-consuming process as it uses advanced computational methods, e.g. the finite-element method (FEM) and it usually requires multiple optimization steps before the specification goals are met. FEM involves solving a large sparse system of equations at many frequency points and therefore its computational cost is high. One of the ideas to speed up the numerical optimization is parametrized model-order reduction (PMOR). The key point in model order reduction, is that the original large sparse system of FE equations is replaced with a small and dense one, that can be solved at many frequency points with substantially smaller computational effort. PMOR yields in the parameter dependent reduced-order model which might be reused in subsequent optimization steps.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Mul M., Mrozowski M.: Deflated Preconditioned Solvers for Parametrized Local Model Order Reduction// / : , 2020,
- Verified by:
- Gdańsk University of Technology
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