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Document type:
Zeitschriftenaufsatz 
Author(s):
Zahn, Rebecca; Winter, Maximilian; Zieher, Moritz; Breitsamter, Christian 
Title:
Application of a long short-term memory neural network for modeling transonic buffet aerodynamics 
Abstract:
In the present work, a reduced-order modeling (ROM) framework based on a long short-term memory (LSTM) neural network is applied for the prediction of transonic buffet aerodynamics. This type of network has a high potential for modeling sequential data, which is favorable for capturing the time-delayed effects associated with unsteady aerodynamics. Therefore, the nonlinear identification procedure as well as the generalization of the resulting ROM are presented. Further, a Monte-Carlo-based trai...    »
 
Keywords:
Nonlinear system identification; Reduced-order model; Long short-term memory neural network; Buffet aerodynamics; Computational fluid dynamics 
Dewey Decimal Classification:
620 Ingenieurwissenschaften 
Journal title:
Aerospace Science and Technology 
Year:
2021 
Journal volume:
113 
Pages contribution:
106652 
Covered by:
Scopus 
Language:
en 
Publisher:
Elsevier BV 
E-ISSN:
1270-9638 
Notes:
The authors would like to thank the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for the funding of the project BR1511/11-1 . Further, the authors thank the Gauss Centre for Supercomputing e.V. ( www.gauss-centre.eu ) for funding this project by providing computing licences and computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Center ( www.lrz.de ). 
Accepted:
13.03.2021 
Date of publication:
01.06.2021 
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik