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Bleh, Alexander (2023) Data-driven Turbulence Modelling with the Machine Learning Toolbox of the CFD Solver TRACE. AI4aerospace, 2023-05-30, Paris.
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Abstract
The presentation shall give an overview over the machine learning interface of the flow solver TRACE, developed at the Institute of Propulsion of the German Aerospace Center (DLR) as well as recent work and results achieved using it. Firstly, focus is laid on the general philosophy of augmenting turbulence models using data-driven methods. Secondly, features and design of the TRACE machine learning toolbox are presented. Lastly, a selection of recent results is shown
| Item URL in elib: | https://elib.dlr.de/201711/ | ||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||
| Title: | Data-driven Turbulence Modelling with the Machine Learning Toolbox of the CFD Solver TRACE | ||||||||
| Authors: |
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| Date: | 30 May 2023 | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | No | ||||||||
| Gold Open Access: | No | ||||||||
| In SCOPUS: | No | ||||||||
| In ISI Web of Science: | No | ||||||||
| Status: | Published | ||||||||
| Keywords: | Machine Learning, Turbulence Modelling, CFD, Fieldinversion | ||||||||
| Event Title: | AI4aerospace | ||||||||
| Event Location: | Paris | ||||||||
| Event Type: | Workshop | ||||||||
| Event Date: | 30 May 2023 | ||||||||
| Organizer: | ONERA/DLR | ||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||
| HGF - Program: | Aeronautics | ||||||||
| HGF - Program Themes: | Clean Propulsion | ||||||||
| DLR - Research area: | Aeronautics | ||||||||
| DLR - Program: | L CP - Clean Propulsion | ||||||||
| DLR - Research theme (Project): | L - Virtual Engine | ||||||||
| Location: | Köln-Porz | ||||||||
| Institutes and Institutions: | Institute of Propulsion Technology > Numerical Methodes | ||||||||
| Deposited By: | Bleh, Alexander | ||||||||
| Deposited On: | 03 Jan 2024 15:17 | ||||||||
| Last Modified: | 24 Apr 2024 21:02 |
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