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Inverse Aerodynamic Design Using Neural Networks
,
Oubay Hassan ,
Kenneth Morgan
Advances in Computational Methods and Technologies in Aeronautics and Industry, Volume: 57, Pages: 131 - 143
Swansea University Authors:
Rubén Sevilla , Oubay Hassan , Kenneth Morgan
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1007/978-3-031-12019-0_10
Abstract
An efficient computational framework is presented and applied to the inverse aerodynamic shape design problem. The main building block is a novel neural network capable to accurately predict the pressure distribution on aerofoils and wings. The trained neural network is used to accelerate the evalua...
| Published in: | Advances in Computational Methods and Technologies in Aeronautics and Industry |
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| ISBN: | 9783031120183 9783031120190 |
| ISSN: | 1871-3033 2543-0203 |
| Published: |
Cham
Springer International Publishing
2022
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa62238 |
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| Abstract: |
An efficient computational framework is presented and applied to the inverse aerodynamic shape design problem. The main building block is a novel neural network capable to accurately predict the pressure distribution on aerofoils and wings. The trained neural network is used to accelerate the evaluation of the objective function in an optimisation algorithm based on the gradient-free modified cuckoo search method. Two applications are presented in two and three dimensions for problems involving up to 50 geometric parameters. |
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| Keywords: |
Aerodynamic design; Neural network; Optimisation |
| College: |
Faculty of Science and Engineering |
| Start Page: |
131 |
| End Page: |
143 |