Data-driven determination of low-frequency dipole noise mechanisms in stalled airfoils

Abstract

Abstract An aeroacoustic investigation of planar time-resolved particle image velocimetry (PIV) measurements in the streamwise surface-normal plane of a NACA 0012 airfoil in static stall is presented at chord-based Reynolds number $$\textrm{Re}_c=7.1\times 10^4$$ Re c = 7.1 × 10 4 . Instantaneous planar pressure reconstructions are obtained using a Poisson solver and the dipole noise emanating from the surface is extrapolated via Curle’s acoustic analogy. To correlate structure in the velocity field to the generation of noise, a data-driven framework utilising the proper orthogonal decomposition (POD) and the spectral Linear Stochastic Estimation (sLSE) is employed. The flow structures responsible for noise are found to concentrate in proximity to the trailing edge. In addition, a conditional analysis for the extreme noise events reveals that downwash and upwash events in proximity to the trailing edge, coupled with slow and fast-moving fluid at the incipient shear layer, are correlated to local maxima and minima in the acoustic fluctuations, respectively. Graphical abstract