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http://dx.doi.org/10.6112/kscfe.2014.19.3.029

AERODYNAMIC DESIGN OPTIMIZATION OF UAV ROTOR BLADES USING A GENETIC ALGORITHM AND ARTIFICIAL NEURAL NETWORKS  

Lee, H.M. (Dept. of Aerospace Engineering, KAIST)
Ryu, J.K. (LIG Nex1)
Ahn, S.J. (Dept. of Aerospace Engineering, KAIST)
Kwon, O.J. (Dept. of Aerospace Engineering, KAIST)
Publication Information
Journal of computational fluids engineering / v.19, no.3, 2014 , pp. 29-36 More about this Journal
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.
Keywords
GA; ANN; CFD; OPTIMIZATION;
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Times Cited By KSCI : 1  (Citation Analysis)
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