Ion, Ion Gabriel ; Bontinck, Zeger ; Loukrezis, Dimitrios ; Römer, Ulrich ; Lass, Oliver ; Ulbrich, Stefan ; Schöps, Sebastian ; De Gersem, Herbert (2018):
Robust Shape Optimization of Electric Devices Based on Deterministic Optimization Methods and Finite Element Analysis With Affine Decomposition and Design Elements.
In: Electrical Engineering (Archiv für Elektrotechnik), ISSN 1432-0487,
DOI: 10.1007/s00202-018-0716-6,
[Article]
Abstract
In this paper, gradient-based optimization methods are combined with finite-element modeling for improving electric devices. Geometric design parameters are considered by affine decomposition of the geometry or by the design element approach, both of which avoid remeshing. Furthermore, it is shown how to robustify the optimization procedure, i.e., how to deal with uncertainties on the design parameters. The overall procedure is illustrated by an academic example and by the example of a permanent-magnet synchronous machine. The examples show the advantages of deterministic optimization compared to standard and popular stochastic optimization procedures such as, e.g., particle swarm optimization.
| Item Type: | Article |
|---|---|
| Erschienen: | 2018 |
| Creators: | Ion, Ion Gabriel ; Bontinck, Zeger ; Loukrezis, Dimitrios ; Römer, Ulrich ; Lass, Oliver ; Ulbrich, Stefan ; Schöps, Sebastian ; De Gersem, Herbert |
| Title: | Robust Shape Optimization of Electric Devices Based on Deterministic Optimization Methods and Finite Element Analysis With Affine Decomposition and Design Elements |
| Language: | English |
| Abstract: | In this paper, gradient-based optimization methods are combined with finite-element modeling for improving electric devices. Geometric design parameters are considered by affine decomposition of the geometry or by the design element approach, both of which avoid remeshing. Furthermore, it is shown how to robustify the optimization procedure, i.e., how to deal with uncertainties on the design parameters. The overall procedure is illustrated by an academic example and by the example of a permanent-magnet synchronous machine. The examples show the advantages of deterministic optimization compared to standard and popular stochastic optimization procedures such as, e.g., particle swarm optimization. |
| Journal or Publication Title: | Electrical Engineering (Archiv für Elektrotechnik) |
| Uncontrolled Keywords: | uncertainty, optimization, robust |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute of Electromagnetic Field Theory (from 01.01.2019 renamed Institute for Accelerator Science and Electromagnetic Fields) 18 Department of Electrical Engineering and Information Technology > Institute of Electromagnetic Field Theory (from 01.01.2019 renamed Institute for Accelerator Science and Electromagnetic Fields) > Computational Engineering (from 01.01.2019 renamed Computational Electromagnetics) Exzellenzinitiative Exzellenzinitiative > Graduate Schools Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE) |
| Date Deposited: | 18 Aug 2018 17:35 |
| DOI: | 10.1007/s00202-018-0716-6 |
| URL / URN: | https://doi.org/10.1007/s00202-018-0716-6 |
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