유전 알고리즘과 인공 신경망 기법을 이용한무인항공기 로터 블레이드 공력 최적설계

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In the present study, an aerodynamic design optimization of UAV rotor blades was conducted using a genetic algorithm(GA) coupled with computational fluid dynamics(CFD). To reduce computational cost in making databases, a function approximation was applied using artificial neural networks(ANN) based on a radial basis function network. Three dimensional Reynolds-Averaged Navier-Stokes(RANS) solver was used to solve the flow around UAV rotor blades. Design directions were specified to maximize thrust coefficient maintaining torque coefficient and minimize torque coefficient maintaining thrust coefficient. Design variables such as twist angle, thickness and chord length were adopted to perform a planform optimization. As a result of an optimization regarding to maximizing thrust coefficient, thrust coefficient was increased about 4.5% than base configuration. In case of an optimization minimizing torque coefficient, torque coefficient was decreased about 7.4% comparing with base configuration.
Publisher
한국전산유체공학회
Issue Date
2014-09
Language
Korean
Citation

한국전산유체공학회지, v.19, no.3, pp.29 - 36

ISSN
1598-6071
URI
http://hdl.handle.net/10203/195760
Appears in Collection
AE-Journal Papers(저널논문)
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