Reduced Basis Modeling for Uncertainty Quantification of Electromagnetic 
Problems in Stochastically Varying Domain

Benner, Peter; Hess, Martin W.

doi:10.1007/978-3-319-30399-4_21

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Reduced Basis Modeling for Uncertainty Quantification of Electromagnetic Problems in Stochastically Varying Domain

Benner, P., & Hess, M. W. (2016). Reduced Basis Modeling for Uncertainty Quantification of Electromagnetic Problems in Stochastically Varying Domain. In A. Bartel, M. Clemens, M. Günther, & E. J. W. ter Maten (Eds.), Scientific Computing in Electrical Engineering (pp. 215-222). Cham: Springer International Publishing.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002A-EF54-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-D4A9-9

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Creators:
Benner, Peter¹, Author
Hess, Martin W.¹, Author

Affiliations:
1Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738141

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Dates: Date issued: 2016

Publication Status: Issued

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Rev. Type: Peer

Identifiers: DOI: 10.1007/978-3-319-30399-4_21

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Project name : nanoCOPS - Nanoelectronic COupled Problems Solutions

Grant ID : 619166

Funding program : Funding Programme 7 (FP7)

Funding organization : European Commission (EC)

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Title: Scientific Computing in Electrical Engineering

Subtitle : SCEE 2014, Wuppertal, Germany, July 2014

Source Genre: Book

Creator(s):
Bartel, Andreas, Editor
Clemens, Markus, Editor
Günther, Michael, Editor
ter Maten, E. Jan W., Editor

Affiliations:
-

Publ. Info: Cham : Springer International Publishing

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 215 - 222 Identifier: ISBN: 978-3-319-30398-7
ISBN: 978-3-319-32149-3

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Title: Mathematics in Industry / The European Consortium for Mathematics in Industry

Source Genre: Series

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Pages: - Volume / Issue: 23 Sequence Number: - Start / End Page: - Identifier: ISSN: 1612-3956