TY - JOUR
T1 - Estimating turbulent-boundary-layer wall-pressure spectra from CFD RANS solutions
AU - Peltier, L. J.
AU - Hambric, S. A.
N1 - Funding Information:
The authors would like to thank the Office of Naval Research under ONR Contract N00014-00-G-0058, monitored by Lynn Peterson. The authors would like to also acknowledge contributions from Dr Charles Knight who developed an earlier model for a RANS-based turbulent boundary-layer forcing-function tool that motivated this work.
PY - 2007/8
Y1 - 2007/8
N2 - 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.
AB - 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.
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U2 - 10.1016/j.jfluidstructs.2007.01.003
DO - 10.1016/j.jfluidstructs.2007.01.003
M3 - Article
AN - SCOPUS:34547130552
SN - 0889-9746
VL - 23
SP - 920
EP - 937
JO - Journal of Fluids and Structures
JF - Journal of Fluids and Structures
IS - 6
ER -