Aerodynamic and Aeroacoustic Optimization of UAV Rotor Based on Proper Orthogonal Decomposition Method

Abstract

Aiming at raising the efficiency of multidisciplinary optimization of UAV rotor aerodynamics and aeroacoustics, this paper established a low-order method of rotor aerodynamics and noise prediction based on lifting line theory (LLT) and FWH acoustic analogy theory. The maximum errors between the low-order method and the high-fidelity CFD results are 1.53% and 3.3 dB for the thrust and overall sound pressure level (OASPL) respectively, demonstrating the ability of design optimization by the low-order LLT method. Combined with the proper orthogonal decomposition (POD) dimension reduction technique to reduce the variable space, a multidisciplinary optimization of rotor aerodynamics and noise was implemented. The rotor thrust and OASPL were taken as the optimization objectives, and the chord length, thickness, and blade twist angle at different spanwise positions were taken as the design variables. The results show that the proposed optimization strategy effectively reduces the design space, the convergence process is greatly accelerated by coupling the low-order LLT-FWH prediction method, and the whole optimization process is only about 0.094% of the computational resource of the method based on unsteady CFD and conventional optimization method. Compared with the original rotor, the thrust at the design condition is increased by 1.66%, and the OASPL is maximally reduced by 3.10 dB. After optimization, the aerodynamic load fluctuation in the middle of the rotor blade (40%–80% spanwise) is significantly reduced, and the high vorticity area in the wake is reduced from the middle to the blade tip (45%–100% spanwise).