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Modeling Unsteady Flows for Aeroelasticity Through Machine Learning and Data-Driven Methods

; ; ;

In
AIAA SCITECH 2024 Forum : 8-12 January 2024, Orlando, FL, Seiten/Artikel-Nr: AIAA 2024-2262

Konferenz/Event:AIAA SCITECH 2024 Forum , Orlando, FL , USA , 2024-01-08 - 2024-01-12

ImpressumReston, Virginia : American Institute of Aeronautics and Astronautics

UmfangAIAA 2024-2262

ISBN978-1-62410-711-5

Online
DOI: 10.2514/6.2024-2262


Einrichtungen

  1. Lehrstuhl für Strömungslehre und Aerodynamisches Institut (415110)



Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85196809410
WOS Core Collection: WOS:001375987905009

Interne Identnummern
RWTH-2024-00774
Datensatz-ID: 977531

Beteiligte Länder
Germany, USA

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The record appears in these collections:
Document types > Events > Contributions to a conference proceedings
Document types > Books > Contributions to a book
Faculty of Mechanical Engineering (Fac.4)
Public records
Publications database
415110
 Record created 2024-01-24, last modified 2025-03-11
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