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Dynamical low-rank approximation for Marshak waves

Ceruti, Gianluca; Frank, Martin 1,2; Kusch, Jonas
1 Institut für Angewandte und Numerische Mathematik (IANM), Karlsruher Institut für Technologie (KIT)
2 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)

Abstract:

Marshak waves are temperature waves which can arise from the background radiation in a material. A core limitation in the simulation of these temperature waves is the high-dimensional phase space of the radiation solution, which depends on time, the spatial position as well as the direction of flight. To obtain computationally efficient methods, we propose to use dynamical low-rank approximation (DLRA) which is a model order reduction method that dynamically determines and adapts dominant modes of the numerical solution. This is done by projecting the original dynamics onto the tangent space of the low-rank manifold. In this work, we investigate discontinuous Galerkin discretizations for two robust time integrators. By performing the derivation of the DLRA evolution equations on the continuous level, we are able to apply the needed slope limiter on the low-rank factors instead of the full solution. The efficiency of the method is presented through computational results for a Marshak wave originating from a heated wall.


Volltext §
DOI: 10.5445/IR/1000154134
Veröffentlicht am 02.01.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Scientific Computing Center (SCC)
Sonderforschungsbereich 1173 (SFB 1173)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 12.2022
Sprache Englisch
Identifikator ISSN: 2365-662X
KITopen-ID: 1000154134
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Verlag Karlsruher Institut für Technologie (KIT)
Umfang 10 S.
Serie CRC 1173 Preprint ; 2022/76
Projektinformation SFB 1173/2 (DFG, DFG KOORD, SFB 1173/2 2019)
Externe Relationen Siehe auch
Schlagwörter dynamical low-rank approximation, kinetic equations, rank adaptivity, model order reduction
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