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Mixed-integer simulation-based optimization for a superconductive magnet design

Hemker, T. ; Glocker, M. ; Gersem, Herbert De ; Stryk, Oskar von ; Weiland, Thomas (2006)
Mixed-integer simulation-based optimization for a superconductive magnet design.
Sixth International Conference on Computational Elektromagnetics, Proceedings, 4-6 April 2006 in Aachen. Achen
Konferenzveröffentlichung, Bibliographie

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Kurzbeschreibung (Abstract)

The optimization of continuous parameters in electrotechnical designs using electromagnetic field simulation is already standard. Typically, the simulation tools only carry out evaluations of the objective function and do not provide gradient information. If in addition to continuous design parameters also integer design parameters have to be optimized, only computational expensive random search methods like genetic algorithms are well known. In this paper, we present a new sequential modeling approach to solve mixed-integer simulation-based optimiza-tion problems for an electrotechnical design problem for superconductive magnets. Each step of this approach uses stochastic modeling techniques to predict the simulation output by a surrogate function. The surrogate function treats the integer variables as real-valued ones. New promising parameter con-figurations are predicted by a “branch-and-bound” method, which solves the purely continuous subproblems by classical optimization methods for continuous and differentiable functions. The additional information of these simulation runs improves the quality of the surrogate function step by step. The proposed approach is applied to optimize the distribution of coil blocks and coil windings of a superconduc-tive magnet such that a maximal homogeneity of the magnetic field in the aperture is achieved.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2006
Autor(en): Hemker, T. ; Glocker, M. ; Gersem, Herbert De ; Stryk, Oskar von ; Weiland, Thomas
Art des Eintrags: Bibliographie
Titel: Mixed-integer simulation-based optimization for a superconductive magnet design
Sprache: Englisch
Publikationsjahr: 2 April 2006
Ort: Achen
Veranstaltungstitel: Sixth International Conference on Computational Elektromagnetics, Proceedings, 4-6 April 2006 in Aachen
Veranstaltungsort: Achen
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Kurzbeschreibung (Abstract):

The optimization of continuous parameters in electrotechnical designs using electromagnetic field simulation is already standard. Typically, the simulation tools only carry out evaluations of the objective function and do not provide gradient information. If in addition to continuous design parameters also integer design parameters have to be optimized, only computational expensive random search methods like genetic algorithms are well known. In this paper, we present a new sequential modeling approach to solve mixed-integer simulation-based optimiza-tion problems for an electrotechnical design problem for superconductive magnets. Each step of this approach uses stochastic modeling techniques to predict the simulation output by a surrogate function. The surrogate function treats the integer variables as real-valued ones. New promising parameter con-figurations are predicted by a “branch-and-bound” method, which solves the purely continuous subproblems by classical optimization methods for continuous and differentiable functions. The additional information of these simulation runs improves the quality of the surrogate function step by step. The proposed approach is applied to optimize the distribution of coil blocks and coil windings of a superconduc-tive magnet such that a maximal homogeneity of the magnetic field in the aperture is achieved.

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Teilchenbeschleunigung und Theorie Elektromagnetische Felder > Theorie Elektromagnetischer Felder
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Teilchenbeschleunigung und Theorie Elektromagnetische Felder
20 Fachbereich Informatik
20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik
Hinterlegungsdatum: 09 Jul 2019 09:55
Letzte Änderung: 09 Jul 2019 09:55
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