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Sensitivity Analysis of Discrepancy Terms introduced in Turbulence Models using Field Inversion

Jäckel, Florian (2021) Sensitivity Analysis of Discrepancy Terms introduced in Turbulence Models using Field Inversion. In: 22nd STAB/DGLR Symposium on New Results in Numerical and Experimental Fluid Mechanics XIII, 151, pp. 625-634. Springer Nature. 22. STAB/DGLR Symposium 2020, 15.07.2020, Göttingen, Deutschland. doi: 10.1007/978-3-030-79561-0_59. ISBN 978-3-030-79560-3. ISSN 1612-2909.

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Official URL: https://link.springer.com/book/10.1007/978-3-030-79561-0#editorsandaffiliations

Abstract

RANS simulations with the Spalart-Allmaras turbulence model are improved for cases with flow separation using the Field Inversion and Machine Learning approach. A compensatory discrepancy term is introduced into the turbulence model and optimized using high-fidelity reference data from experiments. Influences on the optimization results with respect to regularization, grid resolution and areas in which the optimization is active are investigated. Finally, a neural network is trained and used to augment simulations on a test case.

Item URL in elib:https://elib.dlr.de/136236/
Document Type:Conference or Workshop Item (Other)
Additional Information:Hardcover ISBN 978-3-030-79560-3 Softcover ISBN 978-3-030-79563-4 eBook ISBN 978-3-030-79561-0 Series ISSN 1612-2909 Series E-ISSN 1860-0824
Title:Sensitivity Analysis of Discrepancy Terms introduced in Turbulence Models using Field Inversion
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Jäckel, FlorianFlorian.Jaeckel (at) dlr.deUNSPECIFIED
Date:14 July 2021
Journal or Publication Title:22nd STAB/DGLR Symposium on New Results in Numerical and Experimental Fluid Mechanics XIII
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:151
DOI :10.1007/978-3-030-79561-0_59
Page Range:pp. 625-634
Editors:
EditorsEmailEditor's ORCID iD
Dillmann, AndreasAndreas.Dillmann@dlr.deUNSPECIFIED
Heller, GerdAirbus BremenUNSPECIFIED
Krämer, EwaldInstitut für Aerodynamik und Gasdynamik, Universität StuttgartUNSPECIFIED
Wagner, ClausClaus.Wagner@dlr.deUNSPECIFIED
Publisher:Springer Nature
Series Name:Notes on Numerical Fluid Mechanics and Multidisciplinary Design
ISSN:1612-2909
ISBN:978-3-030-79560-3
Status:Published
Keywords:data-driven turbulence modeling, machine learning, field inversion
Event Title:22. STAB/DGLR Symposium 2020
Event Location:Göttingen, Deutschland
Event Type:international Conference
Event Dates:15.07.2020
Organizer:STAB/DGLR
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:other
DLR - Research area:Aeronautics
DLR - Program:L - no assignment
DLR - Research theme (Project):L - no assignment
Location: Göttingen
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > CASE, GO
Deposited By: Jäckel, Florian
Deposited On:10 Dec 2020 11:44
Last Modified:22 Feb 2022 18:21

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