CNNFOIL: convolutional encoder decoder modeling for pressure fields around airfoils

In this study, we propose an encoder–decoder convolutional neural network-based approach for estimating the pressure field around an airfoil. The developed tool is one of the early steps of a machine-learning-based aerodynamic performance prediction tool. Network training and evaluation are performe...

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Vydáno v:	Neural computing & applications Ročník 33; číslo 12; s. 6835 - 6849
Hlavní autoři:	Duru, Cihat, Alemdar, Hande, Baran, Özgür Uğraş
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.06.2021 Springer Nature B.V
Témata:	Aerodynamics Algorithms Angle of attack Artificial Intelligence Artificial neural networks Cambering Coders Computational Biology/Bioinformatics Computational fluid dynamics Computational grids Computational Science and Engineering Computer Science Computer simulation Data Mining and Knowledge Discovery Flow distribution Image Processing and Computer Vision Mach number Machine learning Mathematical models Model accuracy Neural networks Original Article Performance prediction Probability and Statistics in Computer Science Reynolds averaged Navier-Stokes method Thin airfoils Two dimensional flow Aerodynamics Computational fluid dynamics Convolutional neural network Machine learning
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
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