Synthetic Turbulence Methods for Leading Edge Noise Predictions

Abstract

An advanced digital filter method to generate synthetic turbulence is presented for efficient two- and three-dimensional leading edge noise predictions. The technique, which is based on the Random Particle-Mesh method, produces a turbulent inflow that matches a target isotropic energy spectrum. The discretized equations for the synthetic eddies, and the input parameters needed to recover the desired turbulence statistics, are presented. Moreover, a simple and fast implementation strategy, which does not require an additional boundary condition, is presented under the frozen turbulence assumption. The method is used in a linearized Euler solver to predict turbulence-airfoil interaction noise from a number of configurations, including variations in airfoil thickness, angle of attack and Mach number. For the first time, noise predictions from a digital filter method are directly compared to those provided by synthetic turbulence based on a summation of Fourier modes. The comparison indicates that the advanced digital filter method gives enhanced performance in terms of computational cost and simulation accuracy. In addition, initial tests show that this method is capable of reproducing experimental noise measurements within 3 dB accuracy.