<div class="csl-bib-body">
<div class="csl-entry">Lackner, C. (2016). <i>Reduced basis methods for low frequency electromagnetic problems</i> [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.40146</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2016.40146
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/3342
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dc.description.abstract
In this thesis we introduce a new way for adaptively selecting snapshots to con- struct a reduced basis (RB) subspace for the numerical solution of parabolic differential equations. Our main insterest is in low frequency electromagnetic equations where the displacement currents can be neglected. Constructing the RB subspace by solving shifted stationary problems is a natural and often used attempt, based on the work of Grimme [7]. In [9] the identity of shifts and eigen- values of the reduced system was derived as a necessary optimality condition. Because the optimal spaces are not nested, Druskin, Lieberman and Zaslavsky proposed the usage of a nested sequence of spaces with adaptivly chosen shifts fitted to the eigenvalues in [6]. Using a modified version of the Kolmogorov Smirnow test statistic we derive an algorithm with a better fitting of the shifts to the eigenvalues than in [6]. We present tests on a 2D heat equation example and a 3D electromagnetic one and observe an improved convergence rate with our method.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
reduced Basis Method
en
dc.subject
Maxwell equations
en
dc.title
Reduced basis methods for low frequency electromagnetic problems
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dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.identifier.doi
10.34726/hss.2016.40146
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dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Christopher Lackner
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dc.publisher.place
Wien
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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tuw.publication.orgunit
E101 - Institut für Analysis und Scientific Computing
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dc.type.qualificationlevel
Diploma
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dc.identifier.libraryid
AC13352656
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dc.description.numberOfPages
45
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dc.identifier.urn
urn:nbn:at:at-ubtuw:1-7219
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dc.thesistype
Diplomarbeit
de
dc.thesistype
Diploma Thesis
en
dc.rights.identifier
In Copyright
en
dc.rights.identifier
Urheberrechtsschutz
de
tuw.advisor.staffStatus
staff
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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item.mimetype
application/pdf
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item.openairecristype
http://purl.org/coar/resource_type/c_bdcc
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item.languageiso639-1
en
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item.openaccessfulltext
Open Access
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item.openairetype
master thesis
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item.grantfulltext
open
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crisitem.author.dept
E101-03 - Forschungsbereich Scientific Computing and Modelling
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crisitem.author.parentorg
E101 - Institut für Analysis und Scientific Computing