A CAA Based Approach to Tone Haystacking

Abstract

The far-field noise spectra of jet engines show for certain jet configurations and turbine tones a characteristic spectral broadening effect, causing a reduction of tone peaks in favor of a more distributed spectral hump around each tone frequency. This haystacking effect likely occurs due to the interaction of the turbine tones with the unsteady turbulent jet shear layer. A better understanding of this effect may help to utilize it for noise reduction purposes. Furthermore, the effect is of interest for the measurement of tone sources in an open acoustic wind tunnel test section, since the tone will be scattered in the open jet shear layer. A correction for this measured broadening effect is desirable. A non-empirical computational approach to predict tone haystacking as a function of Reynolds number/jet shear layer characteristics is currently missing. This paper reports about ongoing work to utilize Computational Aeroacoustics (CAA) methods for the prediction of haystacking. In a first step CAA techniques are applied to simulate the propagation of tones through the time averaged steady exhaust of a jet engine. To simulate the haystacking effect with CAA, the unsteady turbulent base-flow is modeled with a 4D synthetic turbulence method. The employed RPM approach generates turbulence with all local statistical features as predicted by time-averaged RANS. To study the spectral broadening effect computationally, the experimental set-up of Candel is considered first, which involves an omnidirectional sound source located on the axis of a round jet. The analytical predictions show very good agreement with the general trends as measured by Candel for an observer position normal to the jet axis. The computations reveal a spectral shape, which is in good agreement with those found in the experiments. In a next step the methodology is combined with the exhaust problem to simulate sound propagation through the unsteady turbulent exhaust.