유전 알고리즘을 이용한 무인항공기 로터 블레이드 공력 최적설계 = Aerodynamic design optimization of UAV rotor blades using a genetic algorithm

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 finding optimum value using a genetic algorithm, a function approximation was applied using artificial neural networks (ANN) based on a radial basis function. Three dimensional and compressible ReynoldsAveraged Navier-Stokes (RANS) flow solver was used to analyze the flow around UAV rotor blades. Design variables such as pitch angle, chord length and thickness were adopted to perform aerodynamic design optimization. The objective functions were specified to maximize thrust coefficient maintaining torque coefficient and minimize torque coefficient maintaining thrust coefficient In case of optimization minimizing torque coefficient, torque coefficient was decreased 5.5% comparing with baseline configuration. As a result of optimization regarding to maximizing thrust coefficient, thrust coefficient was increased 2.8% than that of baseline configuration.