Journal of computational fluids engineering (한국전산유체공학회지)

Korean Society of Computational Fluids Engineering (한국전산유체공학회)
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AERODYNAMIC DESIGN OPTIMIZATION OF UAV ROTOR BLADES USING A GENETIC ALGORITHM AND ARTIFICIAL NEURAL NETWORKS

유전 알고리즘과 인공 신경망 기법을 이용한 무인항공기 로터 블레이드 공력 최적설계

  • 이학민 (한국과학기술원 항공우주공학과) ;
  • 유재관 (LIG 넥스원) ;
  • 안상준 (한국과학기술원 항공우주공학과) ;
  • 권오준 (한국과학기술원 항공우주공학과)
  • Received : 2014.06.09
  • Accepted : 2014.07.11
  • Published : 2014.09.30
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Abstract

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.

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