AI-driven prediction of aerodynamic coefficients using VAE-GAN and MLP models for 2D airfoils

Accurate prediction of aerodynamic coefficients is essential for airfoil design, yet high-fidelity Computational Fluid Dynamics (CFD) simulations are computationally expensive and unsuitable for real-time or large-scale screening. This study presents a novel end-to-end AI-driven framework that integ...

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Egile Nagusiak:	Manuel Berger, Sophia Pellegrini, Thomas Senfter, Martin Pillei
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Elsevier 2026-03-01
Saila:	Results in Engineering
Gaiak:	Surrogate modeling Aerodynamic coefficients Deep learning VAE-GAN Lift and drag prediction XFOIL
Sarrera elektronikoa:	http://www.sciencedirect.com/science/article/pii/S259012302600544X
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