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arXiv · 2501.05709

Far-Field Aeroacoustic Shape Optimization Using Large Eddy Simulation

Mohsen Hamedi·Brian Vermeire
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Abstract

This study presents a shape optimization framework that combines a Flux Reconstruction (FR) spatial discretization, Large Eddy Simulation (LES), the Ffowcs-Williams and Hawkings (FW-H) formulation, and the gradient-free Mesh Adaptive Direct Search (MADS) optimization algorithm. We emphasize the necessity of duplicating the data surface to achieve accurate far-field noise prediction in spanwise periodic problems using the FW-H formulation. The proposed parallel implementation of the optimization framework ensures consistent runtime per optimization iteration, regardless of the number of design parameters, thereby addressing a common limitation of many gradient-free algorithms. The framework is demonstrated through far-field aeroacoustic shape optimization of NACA 4-digit airfoils at a Reynolds number of $23,000$. The objective function minimizes the Overall Sound Pressure Level (OASPL) at a far-field observer positioned $10$ unit chords below the trailing edge, while preserving the mean lift coefficient and reducing the mean drag coefficient. The optimized airfoil achieves an OASPL reduction of $5.9~dB$ and over $14\%$ decrease in mean drag, while maintaining the mean lift coefficient. These results underscore the feasibility and effectiveness of the proposed approach for practical shape optimization applications.

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BibTeXRIS

Mohsen Hamedi, Brian Vermeire. 2025-10-11. Far-Field Aeroacoustic Shape Optimization Using Large Eddy Simulation. https://doi.org/10.1016/j.jsv.2025.119492

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