A CFD-based methodology for aerodynamic-aeroacoustic shape optimization of airfoils

The dominant noise mechanism in most rotating machines and aircrafts is trailing edge noise. In particular, wind turbines are seeing ever greater usage, however their noise pollution is a consistent challenge. Current trends in noise reduction mechanisms focus on utilizing additional components, rather than the optimization of the basic airfoil profile a priori. The existing literature regarding a priori shape optimization for noise reduction primarily relies on low fidelity aerodynamic solvers, which may provide inaccurate or low-sensitivity input to the aeroacoustic solvers. In this paper, a computational fluid dynamics based, multi-objective shape optimization is performed, in regards to maximizing the lift coefficient, minimizing the drag coefficient, and minimizing the trailing edge noise of an airfoil. The solving strategy combines a higher fidelity Reynolds-averaged Navier-Stokes solver with a state-of-the-art wall pressure spectrum model and Amiet’s model for trailing edge noise. The higher fidelity input to the state-of-the-art acoustic models should produce more reliable results overall. A multi-objective optimizer based on genetic algorithm is utilized for the optimization of a 2D NACA0012, where a noise reduction of 2.24 dB(A) is achieved, whilst simultaneously improving the aerodynamics. In general, the multi-objective approach highlights a correlation between increased lift generally resulting in increased noise, decreased drag resulting in decreased noise, and subsequently a clear correlation between the lift-drag ratio and the far field noise. Further investigations involving higher fidelity aeroacoustic predictions are required to further validate the outcomes.