Loukrezis, Dimitrios (2019)
Adaptive approximations for high-dimensional uncertainty quantification in stochastic parametric electromagnetic field simulations.
Technische Universität Darmstadt
Ph.D. Thesis, Primary publication
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Item Type: | Ph.D. Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Adaptive approximations for high-dimensional uncertainty quantification in stochastic parametric electromagnetic field simulations | ||||
Language: | English | ||||
Referees: | De Gersem, Prof. Dr. Herbert ; Römer, Prof. Dr. Ulrich | ||||
Date: | 4 February 2019 | ||||
Place of Publication: | Darmstadt | ||||
Date of oral examination: | 4 February 2019 | ||||
Abstract: | The present work addresses the problems of high-dimensional approximation and uncertainty quantification in the context of electromagnetic field simulations. In the presence of many parameters, one faces the so-called curse of dimensionality. The focus of this work lies on adaptive methods that mitigate the effect of the curse of dimensionality, and therefore enable otherwise intractable uncertainty quantification studies. Its application scope includes electromagnetic field models suffering from moderately high-dimensional input uncertainty. However, the presented methods can be used in a black-box fashion and are therefore applicable to other types of problems as well. |
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URN: | urn:nbn:de:tuda-tuprints-84854 | ||||
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering | ||||
Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields > Electromagnetic Field Theory (until 31.12.2018 Computational Electromagnetics Laboratory) 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE) |
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Date Deposited: | 05 Mar 2019 09:30 | ||||
Last Modified: | 08 Mar 2019 07:53 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/8485 | ||||
PPN: | 445817135 | ||||
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