Deep Learning Framework for Predicting Transonic Wing Buffet Loads Due to Structural Eigenmode-Based Deformations

Deep Learning Framework for Predicting Transonic Wing Buffet Loads Due to Structural Eigenmode-Based Deformations

In the present paper, a reduced-order modeling (ROM) approach based on a hybrid neural network is presented in order to calculate wing buffet pressure distributions due to structural eigenmode-based deformations. The accurate prediction of unsteady surface pressure distributions is crucial for asses...

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Bibliographic Details
Main Authors: Rebecca Zahn, Moritz Zieher, Christian Breitsamter
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Aerospace
Subjects:
deep learning
convolutional autoencoder
long short-term memory neural network
wing buffet aerodynamics
NASA CRM
Online Access:https://www.mdpi.com/2226-4310/12/5/415
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