Bleh, Alexander und Morsbach, Christian und Backhaus, Jan (2022) Investigating the Nature and Invariance of Field Inversion based on Transition in a Turbine Cascade. In: ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition, GT 2022. ASME Turbo Expo, 2022-06-13 - 2022-06-17, Rotterdam, Niederlande. doi: 10.1115/GT2022-82917. ISBN 978-079188612-0.
![]() |
PDF
- Nur DLR-intern zugänglich
1MB |
Kurzfassung
The generation of data-driven turbulence models inherently requires the use of a sufficiently large database of high-fidelity reference data from DNS or LES. For technically relevant flows, such data is usually not readily available. However, in many cases there is a significant amount of experimental data available, though data points are mostly few and sparse. An approach which aims at deriving modelling errors by evaluating deviations from a given reference data set is the field inversion method proposed in [1]. Our aim is to verify this method as a tool which gives insight in the cause and nature of a given model's inconsistencies. We therefore apply field inversion on the turbine cascade T106C for different reference data setups. We find, that for the investigated case, field inversion proved to qualitatively give the right hints towards the expected model correction, when only few data points were used as reference.
elib-URL des Eintrags: | https://elib.dlr.de/187172/ | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
Titel: | Investigating the Nature and Invariance of Field Inversion based on Transition in a Turbine Cascade | ||||||||||||||||
Autoren: |
| ||||||||||||||||
Datum: | 2022 | ||||||||||||||||
Erschienen in: | ASME Turbo Expo 2022: Turbomachinery Technical Conference and Exposition, GT 2022 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Nein | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
DOI: | 10.1115/GT2022-82917 | ||||||||||||||||
ISBN: | 978-079188612-0 | ||||||||||||||||
Status: | akzeptierter Beitrag | ||||||||||||||||
Stichwörter: | Field inversion, data-driven, turbulence modelling, CFD | ||||||||||||||||
Veranstaltungstitel: | ASME Turbo Expo | ||||||||||||||||
Veranstaltungsort: | Rotterdam, Niederlande | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 13 Juni 2022 | ||||||||||||||||
Veranstaltungsende: | 17 Juni 2022 | ||||||||||||||||
Veranstalter : | ASME | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Luftfahrt | ||||||||||||||||
HGF - Programmthema: | Umweltschonender Antrieb | ||||||||||||||||
DLR - Schwerpunkt: | Luftfahrt | ||||||||||||||||
DLR - Forschungsgebiet: | L CP - Umweltschonender Antrieb | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | L - Virtuelles Triebwerk, L - Virtuelles Flugzeug und Validierung | ||||||||||||||||
Standort: | Köln-Porz | ||||||||||||||||
Institute & Einrichtungen: | Institut für Antriebstechnik > Numerische Methoden | ||||||||||||||||
Hinterlegt von: | Bleh, Alexander | ||||||||||||||||
Hinterlegt am: | 18 Jul 2022 12:16 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:48 |
Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags