Abstract
This paper presents an aerodynamic/aeroacoustic shape optimization framework, running on GPUs, based on the continuous adjoint method. The noise prediction tool and its adjoint are developed by implementing the Ffowcs Williams and Hawkings (FW-H) analogy, after integrating flow time-series, computed by an unsteady Euler equations solver, along a permeable surface. The accuracy of this hybrid solver is verified by comparing its outcome with that of a CFD run, for a 2D pitching airfoil in an inviscid flow. For the same case, the aeroacoustic noise and time-averaged lift gradients computed using the adjoint solver are verified w.r.t. finite differences. Finally, the adjoint solver is used to optimize the shape of the pitching airfoil, aiming at min. noise.
Published Version
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