Loukrezis, Dimitrios ; Römer, Ulrich ; De Gersem, Herbert (2018)
Adaptive Sparse Interpolation Methods for Electromagnetic Field Computation with Random Input Data.
2018 SIAM Conference on Uncertainty Quantification. Garden Grove, USA (16.-19.04.2018)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In many applications of science and engineering, time-or resource-demanding simulation models are often sub-stituted by inexpensive polynomial surrogates in order toenable computationally challenging tasks, e.g. optimiza-tion or uncertainty quantification studies of field mod-els. For such approaches, the surrogate model’s accu-racy is of critical importance. Moreover, in the case ofmany input parameters, the curse-of-dimensionality sub-stantially hampers the surrogate’s construction. State-of-the-art methods employ interpolation on adaptively con-structed sparse grids, typically based on Clenshaw-Curtis[B. Schieche,Unsteady Adaptive Stochastic CollocationMethods on Sparse Grids, TU Darmstadt, 2012] or, morerecently, Leja [A. Narayan and J.D. Jakeman,AdaptiveLeja Sparse Grid Constructions for Stochastic Collocationand High-Dimensional Approximation,SIAMJ.Sci.Com-put., 2014] nodes. These methods provide accurate surro-gate models, mitigating or altogether avoiding the curse-of-dimensionality, at the cost of a relatively small numberof unused original model evaluations. In this work, we shalluse a benchmark example from the field of computationalelectromagnetics in order to compare the aforementionedmethods with respect to computational cost and accuracy.Moreover, we will suggest enhancement approaches, aim-ing to reduce the costs caused by unused model evaluationsduring the surrogate model’s construction.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Loukrezis, Dimitrios ; Römer, Ulrich ; De Gersem, Herbert |
| Art des Eintrags: | Bibliographie |
| Titel: | Adaptive Sparse Interpolation Methods for Electromagnetic Field Computation with Random Input Data |
| Sprache: | Englisch |
| Publikationsjahr: | 2018 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Proceedings of the SIAM Conference on Uncertainty Quantification |
| Jahrgang/Volume einer Zeitschrift: | 2018 |
| Veranstaltungstitel: | 2018 SIAM Conference on Uncertainty Quantification |
| Veranstaltungsort: | Garden Grove, USA |
| Veranstaltungsdatum: | 16.-19.04.2018 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | In many applications of science and engineering, time-or resource-demanding simulation models are often sub-stituted by inexpensive polynomial surrogates in order toenable computationally challenging tasks, e.g. optimiza-tion or uncertainty quantification studies of field mod-els. For such approaches, the surrogate model’s accu-racy is of critical importance. Moreover, in the case ofmany input parameters, the curse-of-dimensionality sub-stantially hampers the surrogate’s construction. State-of-the-art methods employ interpolation on adaptively con-structed sparse grids, typically based on Clenshaw-Curtis[B. Schieche,Unsteady Adaptive Stochastic CollocationMethods on Sparse Grids, TU Darmstadt, 2012] or, morerecently, Leja [A. Narayan and J.D. Jakeman,AdaptiveLeja Sparse Grid Constructions for Stochastic Collocationand High-Dimensional Approximation,SIAMJ.Sci.Com-put., 2014] nodes. These methods provide accurate surro-gate models, mitigating or altogether avoiding the curse-of-dimensionality, at the cost of a relatively small numberof unused original model evaluations. In this work, we shalluse a benchmark example from the field of computationalelectromagnetics in order to compare the aforementionedmethods with respect to computational cost and accuracy.Moreover, we will suggest enhancement approaches, aim-ing to reduce the costs caused by unused model evaluationsduring the surrogate model’s construction. |
| Zusätzliche Informationen: | TEMF-Pub-DB TEMF002695 |
| 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 Teilchenbeschleunigung und Theorie Elektromagnetische Felder |
| Hinterlegungsdatum: | 16 Feb 2021 10:05 |
| Letzte Änderung: | 16 Feb 2021 10:05 |
| PPN: | |
| Zugehörige Links: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum