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Titel: Low‐rank linear fluid‐structure interaction discretizations
Autor(en): Weinhandl, RomanIn der Gemeinsamen Normdatei der DNB nachschlagen
Benner, PeterIn der Gemeinsamen Normdatei der DNB nachschlagen
Richter, ThomasIn der Gemeinsamen Normdatei der DNB nachschlagen
Erscheinungsdatum: 2020
Art: Artikel
Sprache: Englisch
URN: urn:nbn:de:gbv:ma9:1-1981185920-876915
Schlagwörter: ChebyshevT
GMREST
Low-rank
Parameter-dependent fluid-structure interaction
Tensor
Zusammenfassung: Fluid-structure interaction models involve parameters that describe the solid and the fluid behavior. In simulations, there often is a need to vary these parameters to examine the behavior of a fluid-structure interaction model for different solids and different fluids. For instance, a shipping company wants to know how the material, a ship's hull is made of, interacts with fluids at different Reynolds and Strouhal numbers before the building process takes place. Also, the behavior of such models for solids with different properties is considered before the prototype phase. A parameter-dependent linear fluid-structure interaction discretization provides approximations for a bundle of different parameters at one step. Such a discretization with respect to different material parameters leads to a big block-diagonal system matrix that is equivalent to a matrix equation as discussed in [1]. The unknown is then a matrix which can be approximated using a low-rank approach that represents the iterate by a tensor. This paper discusses a low-rank GMRES variant and a truncated variant of the Chebyshev iteration. Bounds for the error resulting from the truncation operations are derived. Numerical experiments show that such truncated methods applied to parameter-dependent discretizations provide approximations with relative residual norms smaller than 10−8 within a twentieth of the time used by individual standard approaches.
URI: https://opendata.uni-halle.de//handle/1981185920/87691
http://dx.doi.org/10.25673/85739
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY-NC-ND 4.0) Creative Commons Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International(CC BY-NC-ND 4.0) Creative Commons Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International
Sponsor/Geldgeber: Projekt DEAL 2020
Journal Titel: ZAMM
Verlag: Wiley-VCH
Verlagsort: Berlin
Band: 100
Heft: 11
Originalveröffentlichung: 10.1002/zamm.201900205
Seitenanfang: 1
Seitenende: 28
Enthalten in den Sammlungen:Fakultät für Mathematik (OA)

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