Estimating turbulent-boundary-layer wall-pressure spectra from CFD RANS solutions

A stochastic model for the space–time turbulent boundary-layer wall-pressure spectrum is developed that uses statistical data from Reynolds-Averaged Navier–Stokes (RANS) solutions as input. The model integrates the source terms for the surface-pressure covariance across the boundary layer for user-specified space and time separations to form a discrete surface-pressure correlation function, the Fourier transform of which yields the surface-pressure wavenumber-frequency spectrum. By integrating RANS data into the model, it is able to respond to local geometry and flow conditions. Validation cases show that predicted surface-pressure power spectra respond appropriately to favorable, zero, and adverse pressure gradients. By operating as a post-processor of CFD RANS analyses, the model is a predictive tool that can be used in flow and flow-induced noise analyses. Because contemporary RANS models are able to predict flow statistics well for configurations of practical interest, this approach to modeling the turbulent boundary-layer forcing function is expected to generalize well to new flow configurations without requiring flow-specific tuning.