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Dokumenttyp:
Zeitschriftenaufsatz 
Autor(en):
Chen, Li-Wei; Cakal, Berkay A.; Hu, Xiangyu; Thuerey, Nils 
Titel:
Numerical investigation of minimum drag profiles in laminar flow using deep learning surrogates 
Abstract:
Efficiently predicting the flow field and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular interest for such problems due to their success in solving inverse problems in other fields. In the present study U-net-based deep neural network (DNN) models are trained with high-fidelity datasets to infer flow fields and then employed as surrogate models to carry out the shape optimisation problem i.e.To find a minimal d...    »
 
Stichworte:
computational methods; general fluid mechanics; Navier-Stokes equations 
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften 
Horizon 2020:
Eurpoean Research Council, grants 637014, 838342 
Zeitschriftentitel:
Journal of Fluid Mechanics 
Jahr:
2021 
Band / Volume:
919 
Nachgewiesen in:
Scopus 
Volltext / DOI:
Verlag / Institution:
Cambridge University Press (CUP) 
E-ISSN:
0022-11201469-7645 
Publikationsdatum:
01.06.2021 
TUM Einrichtung:
Lehrstuhl für Aerodynamik und Strömungsmechanik