Broadband slat noise prediction based on CAA and stochastic sound sources from a fast random particle-mesh (RPM) method

Abstract

The application of a low-cost computational aeroacoustics (CAA) approach to a slat noise problem is studied. A fast and efficient stochastic method is introduced to model the unsteady turbulent sound sources in the slat-cove of a high-lift airfoil. It is based on the spatial convolution of spatiotemporal white-noise and can reproduce target distributions of turbulence kinetic energy and length scales, such as that provided by a RANS computation of the time-averaged turbulent flow problem. The computational method yields a perfectly solenoidal velocity field. For homogeneous isotropic turbulence, the complete second-order two-point velocity correlation tensor is realized exactly. Two RANS turbulence models are applied to the slat noise problem to study how sensitive the aeroacoustics predictions depend on turbulence kinetic energy predictions. Results for the sound generation at the slat are given for a Menter SST turbulence model with and without Kato–Launder modification. The aeroacoustic simulations yield a characteristic narrow band spectrum that compares very well with the experimental data. The directivities found point toward an edge noise mechanism at the slat as the main cause for slat noise sound generation.