Jankoski, Radoslav ; Römer, Ulrich ; Schöps, Sebastian (2017)
Modeling of Spatial Uncertainties in the Magnetic Reluctivity.
In: COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 36 (4)
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Purpose In this paper a computationally efficient approach is suggested for the stochastic modeling of an inhomogeneous reluctivity of magnetic materials. These materials can be part of electrical machines, such as a single phase transformer (a benchmark example that is considered in this paper). The approach is based on the Karhunen-Loève expansion. The stochastic model is further used to study the statistics of the self inductance of the primary coil as a quantity of interest (QoI). Design/methodology/approach The computation of the Karhunen–Loève expansion requires solving a generalized eigenvalue problem with dense matrices. The eigenvalues and the eigenfunction are computed by using the Lanczos method that needs only matrix vector multiplications. The complexity of performing matrix vector multiplications with dense matrices is reduced by using hierarchical matrices. Findings The suggested approach is used to study the impact of the spatial variability in the magnetic reluctivity on the QoI. The statistics of this parameter are influenced by the correlation lengths of the random reluctivity. Both, the mean value and the standard deviation increase as the correlation length of the random reluctivity increases. Originality/value The Karhunen–Loève expansion, computed by using hierarchical matrices, is used for uncertainty quantification of low frequency electrical machines as a computationally efficient approach in terms of memory requirement as well as computation time.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Jankoski, Radoslav ; Römer, Ulrich ; Schöps, Sebastian |
| Art des Eintrags: | Bibliographie |
| Titel: | Modeling of Spatial Uncertainties in the Magnetic Reluctivity |
| Sprache: | Englisch |
| Publikationsjahr: | April 2017 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering |
| Jahrgang/Volume einer Zeitschrift: | 36 |
| (Heft-)Nummer: | 4 |
| URL / URN: | https://doi.org/10.1108/COMPEL-10-2016-0438 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Purpose In this paper a computationally efficient approach is suggested for the stochastic modeling of an inhomogeneous reluctivity of magnetic materials. These materials can be part of electrical machines, such as a single phase transformer (a benchmark example that is considered in this paper). The approach is based on the Karhunen-Loève expansion. The stochastic model is further used to study the statistics of the self inductance of the primary coil as a quantity of interest (QoI). Design/methodology/approach The computation of the Karhunen–Loève expansion requires solving a generalized eigenvalue problem with dense matrices. The eigenvalues and the eigenfunction are computed by using the Lanczos method that needs only matrix vector multiplications. The complexity of performing matrix vector multiplications with dense matrices is reduced by using hierarchical matrices. Findings The suggested approach is used to study the impact of the spatial variability in the magnetic reluctivity on the QoI. The statistics of this parameter are influenced by the correlation lengths of the random reluctivity. Both, the mean value and the standard deviation increase as the correlation length of the random reluctivity increases. Originality/value The Karhunen–Loève expansion, computed by using hierarchical matrices, is used for uncertainty quantification of low frequency electrical machines as a computationally efficient approach in terms of memory requirement as well as computation time. |
| Freie Schlagworte: | uncertainty |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Theorie Elektromagnetischer Felder (ab 01.01.2019 umbenannt in Institut für Teilchenbeschleunigung und Theorie Elektromagnetische Felder) 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Theorie Elektromagnetischer Felder (ab 01.01.2019 umbenannt in Institut für Teilchenbeschleunigung und Theorie Elektromagnetische Felder) > Computational Engineering (ab 01.01.2019 umbenannt in Computational Electromagnetics) Exzellenzinitiative Exzellenzinitiative > Graduiertenschulen Exzellenzinitiative > Graduiertenschulen > Graduate School of Computational Engineering (CE) |
| Hinterlegungsdatum: | 23 Sep 2017 17:02 |
| Letzte Änderung: | 02 Jan 2019 14:18 |
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