Aerodynamic and aeroacoustic optimization of an isolated propeller based on variable-fidelity deep neural network surrogate model with uncertainty quantification

Publisher DOI:	10.1016/j.ast.2026.112283
Title:	Aerodynamic and aeroacoustic optimization of an isolated propeller based on variable-fidelity deep neural network surrogate model with uncertainty quantification
Language:	English
Authors:	Geng, Xin Liu, Peiqing Hu, Tianxiang Qu, Qiulin Li, Yunlong Ge, Yunsong Wang, Jun Guo, Hao Noack, Bernd R. Akkermans, Rinie A. D.
Keywords:	Propeller; Optimization; Variable-fidelity deep neural network; Surrogate model; Uncertainty quantification
Issue Date:	Oct-2026
Publisher:	Elsevier
Journal or Series Name:	Aerospace science and technology
Volume:	177
Issue:	Part A
URI:	https://hdl.handle.net/20.500.12738/19426
ISSN:	1626-3219
Review status:	This version was peer reviewed (peer review)
Institute:	Fakultät Luftfahrt- und Fahrzeugsysteme Forschungs- und Transferzentrum Future Mobility and Acoustics
Type:	Article
Additional note:	article number: 112283
Appears in Collections:	Publications without full text

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