scholarly journals On the use of two-point velocity correlation in wall-pressure models for turbulent flow past a trailing edge under adverse pressure gradient

2020 ◽  
Vol 32 (10) ◽  
pp. 105105
Author(s):  
Prateek Jaiswal ◽  
Stéphane Moreau ◽  
Francesco Avallone ◽  
Daniele Ragni ◽  
Stefan Pröbsting
Author(s):  
Frank J. Aldrich

A physics-based approach is employed and a new prediction tool is developed to predict the wavevector-frequency spectrum of the turbulent boundary layer wall pressure fluctuations for subsonic airfoils under the influence of adverse pressure gradients. The prediction tool uses an explicit relationship developed by D. M. Chase, which is based on a fit to zero pressure gradient data. The tool takes into account the boundary layer edge velocity distribution and geometry of the airfoil, including the blade chord and thickness. Comparison to experimental adverse pressure gradient data shows a need for an update to the modeling constants of the Chase model. To optimize the correlation between the predicted turbulent boundary layer wall pressure spectrum and the experimental data, an optimization code (iSIGHT) is employed. This optimization module is used to minimize the absolute value of the difference (in dB) between the predicted values and those measured across the analysis frequency range. An optimized set of modeling constants is derived that provides reasonable agreement with the measurements.


1986 ◽  
Vol 108 (3) ◽  
pp. 308-314 ◽  
Author(s):  
M. A. Z. Hasan ◽  
M. J. Casarella ◽  
E. P. Rood

The flow and wall-pressure field around a wing-body junction has been experimentally investigated in a quiet, low-turbulence wind tunnel. Measurements were made along the centerline in front of the wing and along several spanwise locations. The flow field data indicated that the strong adverse pressure gradient on the upstream centerline causes three-dimensional flow separation at approximately one wing thickness upstream and this induced the formation of the horseshoe root vortex which wrapped around the wing and became deeply embedded within the boundary layer. The wall-pressure fluctuations were measured for their spectral content and the data indicate that the effect of the adverse pressure gradient is to increase the low-frequency content of the wall pressure and to decrease the high-frequency content. The wall pressure data in the separated region, which is dominated by the horseshoe vortex, shows a significant increase in the low-frequency content and this characteristic feature prevails around the corner of the wing. The outer edge of the horseshoe vortex is clearly identified by the locus of maximum values of RMS wall pressure.


2018 ◽  
Vol 840 ◽  
pp. 25-55 ◽  
Author(s):  
Myriam Slama ◽  
Cédric Leblond ◽  
Pierre Sagaut

The present study addresses the computation of the wall pressure spectrum for a turbulent boundary layer flow without pressure gradient, at high Reynolds numbers, using a new model, the Kriging-based elliptic extended anisotropic model (KEEAM). A space–time solution to the Poisson equation for the wall pressure fluctuations is used. Both the turbulence–turbulence and turbulence–mean shear interactions are taken into account. It involves the mean velocity field and space–time velocity correlations which are modelled using Reynolds stresses and velocity correlation coefficients. We propose a new model, referred to as the extended anisotropic model, to evaluate the latter in all regions of the boundary layer. This model is an extension of the simplified anisotropic model of Gavin (PhD thesis, 2002, The Pennsylvania State University, University Park, PA) which was developed for the outer part of the boundary layer. It relies on a new expression for the spatial velocity correlation function and new parameters calibrated using the direct numerical simulation results of Sillero et al. (Phys. Fluids, vol. 26, 2014, 105109). Spatial correlation coefficients are related to space–time coefficients with the elliptic model of He & Zhang (Phys. Rev. E, vol. 73, 2006, 055303). The turbulent quantities necessary for the pressure computation are obtained by Reynolds-averaged Navier–Stokes solutions with a Reynolds stress turbulence model. Then, the pressure correlations are evaluated with a self-adaptive sampling strategy based on Kriging in order to reduce the computation time. The frequency and wavenumber–frequency wall pressure spectra obtained with the KEEAM agree well with empirical models developed for turbulent boundary layer flows without pressure gradient.


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