A structure parametric design method of scissors tail rotor was established

in combination with areodynamic noise prediction technique based on CFD(computational fluid dynamics)/FW-H(Ffowcs Williams-Hawkings) equations and combinatorial optimization algorithm. The embedded grid method was developed to predict the flowfield of scissor tail rotor in steady flow. Based on the Navier-Stokes (RANS) equations

a high-effciency CFD simulation method was adopted for aerodynamic characteristics prediction of scissor tail rotor in hover. Based on the previous flowfield calculations

FW-H equations was established to predict the aerodynamic noise of scissor tail rotors. Then

to improve the hover efficiency and reduce the aerodynamic noise

optimization design for structural parameters of scissor tail rotor (scissors angle and shaft spacing) with constant thrust coefficient and constant pitch was conducted respectively. The genetic algorithm and surrogated model based on latin hypercube sampling (LHS) design and radial basis function (RBF) were combined as a hybrid optimization technique. The noise reduction mechanism of the tail rotor was obtained by these results. And the results show that

different combinations of scissors angle and shaft spacing can reduce the blade-vortex interaction phenomenon to cut down rotor blade-vortex interaction noise. Under the current calculation state

compared with conventional rail rotor

the hover efficiency of the optimized tail rotor increased by 16%

and the average sound pressure level decreased by 2.3 dB.