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An application of neural networks to the prediction of aerodynamic coefficients of aerofoils and wings

Kensley Balla, Rubén Sevilla Orcid Logo, Oubay Hassan Orcid Logo, Kenneth Morgan Orcid Logo

Applied Mathematical Modelling, Volume: 96, Pages: 456 - 479

Swansea University Authors: Kensley Balla , Rubén Sevilla Orcid Logo, Oubay Hassan Orcid Logo, Kenneth Morgan Orcid Logo

  • Accepted Manuscript under embargo until: 23rd March 2022

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...

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Published in: Applied Mathematical Modelling
ISSN: 0307-904X
Published: Elsevier BV 2021
Online Access: Check full text

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.
Keywords: neural network, proper orthogonal decomposition, CFD, NURBS, aerofoil, wing
College: College of Engineering
Start Page: 456
End Page: 479