UC Davis

Airfoil optimization for rotor blades is a critical endeavor aimed at enhancing aerodynamic performance and reducing noise. This paper employs a Kriging surrogate model combined with a multi-objective genetic algorithm to optimize thrust, power, and broadband noise. Three airfoil parameterization methods including ParFoil, PARSEC, and CST are compared when used to generate various airfoil shapes for the surrogate model and optimization process. We utilize low-fidelity aerodynamic tools such as XFOIL and blade element momentum theory for aerodynamics. In addition, acoustic modeling is conducted using Lee's wall pressure spectrum model alongside Amiet's trailing-edge noise model. The paper focuses on small-scale rotor configurations, specifically an ideally twisted rotor using the NACA 0012 airfoil and a modified XV-15 blade. Both blades are used as baseline models for hover optimization. The optimization of the ideally twisted rotor across various parameterization methods demonstrates a significant reduction in A-weighted overall sound pressure level by approximately 4.0 dBA. The primary contributors to this noise reduction are identified as a decrease in the chordwise pressure gradient and wall shear stress, which are key factors that contribute to the wall pressure spectrum and resulting trailing-edge noise. Similarly, the optimization of the modified XV-15 blade using the ParFoil method achieves a notable decrease in noise of 3.5 dBA. Further analysis is extended to axial flight conditions, with axial velocities of 5.0, 10.0, and 20.0 m/s, to simulate vertical climb. The results show that these hover-optimized blades are capable of sustaining noise decreases of 3.0-4.0 dBA compared to the baseline, provided that the thrust coefficient is maintained through adjustments in collective pitch.