Gradient-Free Aeroacoustic Shape Optimization Using Large Eddy Simulation

We present an aeroacoustic shape optimization framework that relies on high-order flux reconstruction, the gradient-free Mesh Adaptive Direct Search optimization algorithm, and large eddy simulation. Our parallel implementation ensures consistent runtime for each optimization iteration, regardless of the number of design parameters, provided that sufficient resources are available. The objective is to minimize the overall sound pressure level (OASPL) at a near-field observer by computing it directly from the flowfield. We evaluate this framework across three problems. First, an open deep cavity is considered at a freestream Mach number of M infinity=0.15 and Reynolds number of Re=1500, reducing the OASPL by 12.9 dB. Next, we considered tandem cylinders at Re=1000 and M infinity=0.2, achieving over 11 dB of noise reduction by optimizing cylinder spacing and diameter ratio. Lastly, a baseline NACA0012 airfoil at Re=23,000 and M infinity=0.2 is optimized to generate a new four-digit NACA airfoil at an appropriate angle of attack to minimize the OASPL while ensuring the baseline time-averaged lift coefficient is maintained and prevents any increase in the baseline time-averaged drag coefficient. The OASPL and mean drag coefficient are reduced by 5.7 dB and more than 7%, respectively. These results highlight the feasibility and effectiveness of our aeroacoustic shape optimization framework.