Versenden
Drucken
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, Seiten 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.
![[img]](https://elib.dlr.de/style/images/fileicons/application_pdf.png) |
PDF
965kB |
Offizielle URL: https://link.springer.com/book/10.1007/978-3-030-79561-0#editorsandaffiliations
Kurzfassung
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.
| elib-URL des Eintrags: | https://elib.dlr.de/136236/ | ||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dokumentart: | Konferenzbeitrag (Anderer) | ||||||||||||||||||||
| Zusätzliche Informationen: | 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 | ||||||||||||||||||||
| Titel: | Sensitivity Analysis of Discrepancy Terms introduced in Turbulence Models using Field Inversion | ||||||||||||||||||||
| Autoren: |
| ||||||||||||||||||||
| Datum: | 14 Juli 2021 | ||||||||||||||||||||
| Erschienen in: | 22nd STAB/DGLR Symposium on New Results in Numerical and Experimental Fluid Mechanics XIII | ||||||||||||||||||||
| Referierte Publikation: | Ja | ||||||||||||||||||||
| Open Access: | Ja | ||||||||||||||||||||
| Gold Open Access: | Nein | ||||||||||||||||||||
| In SCOPUS: | Ja | ||||||||||||||||||||
| In ISI Web of Science: | Nein | ||||||||||||||||||||
| Band: | 151 | ||||||||||||||||||||
| DOI: | 10.1007/978-3-030-79561-0_59 | ||||||||||||||||||||
| Seitenbereich: | Seiten 625-634 | ||||||||||||||||||||
| Herausgeber: |
| ||||||||||||||||||||
| Verlag: | Springer Nature | ||||||||||||||||||||
| Name der Reihe: | Notes on Numerical Fluid Mechanics and Multidisciplinary Design | ||||||||||||||||||||
| ISSN: | 1612-2909 | ||||||||||||||||||||
| ISBN: | 978-3-030-79560-3 | ||||||||||||||||||||
| Status: | veröffentlicht | ||||||||||||||||||||
| Stichwörter: | data-driven turbulence modeling, machine learning, field inversion | ||||||||||||||||||||
| Veranstaltungstitel: | 22. STAB/DGLR Symposium 2020 | ||||||||||||||||||||
| Veranstaltungsort: | Göttingen, Deutschland | ||||||||||||||||||||
| Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
| Veranstaltungsdatum: | 15.07.2020 | ||||||||||||||||||||
| Veranstalter : | STAB/DGLR | ||||||||||||||||||||
| HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
| HGF - Programm: | Luftfahrt | ||||||||||||||||||||
| HGF - Programmthema: | keine Zuordnung | ||||||||||||||||||||
| DLR - Schwerpunkt: | Luftfahrt | ||||||||||||||||||||
| DLR - Forschungsgebiet: | L - keine Zuordnung | ||||||||||||||||||||
| DLR - Teilgebiet (Projekt, Vorhaben): | L - keine Zuordnung | ||||||||||||||||||||
| Standort: | Göttingen | ||||||||||||||||||||
| Institute & Einrichtungen: | Institut für Aerodynamik und Strömungstechnik > CASE, GO | ||||||||||||||||||||
| Hinterlegt von: | Jäckel, Florian | ||||||||||||||||||||
| Hinterlegt am: | 10 Dez 2020 11:44 | ||||||||||||||||||||
| Letzte Änderung: | 22 Feb 2022 18:21 |
Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags
