Journal article 788 views 195 downloads
An application of neural networks to the prediction of aerodynamic coefficients of aerofoils and wings
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Oubay Hassan ,
Kenneth Morgan
Applied Mathematical Modelling, Volume: 96, Pages: 456 - 479
Swansea University Authors:
Kensley Balla, Rubén Sevilla , Oubay Hassan , Kenneth Morgan
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DOI (Published version): 10.1016/j.apm.2021.03.019
Abstract
This work proposes a novel multi-output neural network for the prediction of aerodynamic coefficients of aerofoils in two dimensions and wings in three dimensions. Contrary to existing neural networks that are often designed to predict aerodynamic quantities of interest, the proposed network conside...
| Published in: | Applied Mathematical Modelling |
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| ISSN: | 0307-904X |
| Published: |
Elsevier BV
2021
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa56398 |
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| Abstract: |
This work proposes a novel multi-output neural network for the prediction of aerodynamic coefficients of aerofoils in two dimensions and wings in three dimensions. Contrary to existing neural networks that are often designed to predict aerodynamic quantities of interest, the proposed network considers as output the pressure at a number of selected points on the aerodynamic shape. The proposed multi-output neural network is compared with other approaches found in the literature. Furthermore, a detailed comparison of the proposed neural network with the popular proper orthogonal decomposition method is presented. The numerical results, involving high dimensional problems with flow and geometric parameters, show the benefits of the proposed approach. |
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| Keywords: |
neural network, proper orthogonal decomposition, CFD, NURBS, aerofoil, wing |
| College: |
Faculty of Science and Engineering |
| Start Page: |
456 |
| End Page: |
479 |