| Citation: | WANG Qing, LU Bo, WANG Liangquan. Rotor blade aerodynamic shape optimization based on RBF neural network[J]. Journal of Aerospace Power, 2026, 41（1）：20240182 doi: 10.13224/j.cnki.jasp.20240182
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A good aerodynamic profile of a helicopter rotor blade can effectively improve its aerodynamic performance, but complex blade profiles are characterized by many degrees of freedom and high nonlinearity, so the traditional gradient optimization algorithm is vunerable to fall into the local optimal trap. To solve these problems, an optimal design method of rotor blade aerodynamic profile was established by combining RBF neural network method, genetic algorithm and computation fluid dynamics (CFD) method, which can obtain global optimization results in a small amount of computation. On this basis, the aerodynamic shape optimization design of Helishape 7A rotor blade was studied. The optimized blade had the form of front-sweep combination. The numerical calculation results showed that the torque coefficient was reduced by 3.81% under the same tension coefficient, so the hover efficiency of the optimized rotor was effectively improved, and the maximum hover efficiency was increased by 3.99%, indicating that the rotor with optimized blade had better hover performance and can effectively improve the takeoff load of the helicopter.
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