Validation of Broadband Noise Prediction Methodology Based on Linearized Navier–Stokes Analyses

Abstract

Abstract This article presents an integral validation of a synthetic turbulence broadband noise prediction methodology for fan/outlet-guide-vane (OGV) interaction. The test vehicle is the ACAT1 fan, a modern scaled-down fan, experimentally analyzed in 2018 within the TurboNoiseBB project. Three operating points, namely, Approach, Cutback, and Sideline, and two different rig configurations in terms of the axial gap between the fan and OGV are examined within this work. The methodology consists of using a Reynolds-averaged Navier–Stokes (RANS) solver to model the fan wake and the use of two-dimensional frequency domain linearized Navier–Stokes simulations to resolve the acoustics, including quasi-3D corrections to obtain representative results. The RANS results with no ad hoc tuning are compared in detail against hotwire data to determine the degree of uncertainty incurred by this kind of approach. The predicted broadband noise spectra and noise azimuthal decompositions are compared against the experimental data. The spectral levels are well predicted despite an average underprediction of around 3dB. The noise azimuthal decompositions feature a remarkable agreement with the experiment, denoting accurate modeling of the main physics governing the problem. The impact of increasing the fan/OGV axial gap is quantified numerically for the first time. It is concluded that increasing the gap is detrimental for the broadband noise footprint, unlike intuitively could be expected. Overall, the presented broadband noise methodology yields robust broadband noise predictions at an industrially feasible cost and enables a deeper understanding of the problem.