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.
|Title of host publication||AIAA Scitech 2020 Forum|
|Number of pages||12|
|Publication status||Published - 5 Jan 2020|
|Event||AIAA SciTech Forum - Hyatt Regency, Orlando, United States|
Duration: 6 Jan 2020 → 10 Jan 2020
|Conference||AIAA SciTech Forum|
|Period||6/01/20 → 10/01/20|