Turbulence effects of wall-pressure fluctuations for reattached flow

Lee, Yu‐Tai; Farabee, Theodore M.; Blake, William K.

doi:10.1016/j.compfluid.2008.01.012

Cited by 18 publications

(20 citation statements)

References 19 publications

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“…The model was then applied to an equilibrium flow with a fairly good agreement. It has been extended to non-equilibrium flows by adding a non-linear source term in the Poisson equation [10]. Based on the same idea of modeling the spacetime velocity correlation using RANS data, Peltier & Hambric [11] proposed a stochastic model to predict wall-pressure spectra.…”

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confidence: 99%

Wall-Pressure Spectral Model Including the Adverse Pressure Gradient Effects

2012

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An empirical model to predict the wall-pressure fluctuations spectra beneath adverse pressure gradient flows is presented. It is based on Goody's model which already incorporates the effect of Reynolds number but is limited to zero-pressure gradient flows. The extension relies on 6 test-cases from 5 experimental or numerical studies covering a large range of Reynolds number, 5.6 × 10 2 < R θ < 1.72 × 10 4 , in both inter-

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confidence: 99%

Wall-Pressure Spectral Model Including the Adverse Pressure Gradient Effects

2012

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“…Berntsen et al (2006) assumed isotropy, but in their study the coarsest simulations were done using a resolution in millimeters compared with meters in this paper. In the DNS simulations by Le et al (1997) and the LES simulations by Neumann and Wengle (2004), the Kolmogorov scales are resolved and isotropic turbulence is assumed, while in the RANS study by Lee et al (2009), the k − model is used to determine the eddy viscosities and diffusivities.…”

Section: Closing the Systemmentioning

confidence: 99%

“…Model experiments have also been done on flow over a backward-facing step, both through direct numerical simulations (Le et al 1997), large eddy simulations (Akselvoll and Moin 1996), and Reynoldsaveraged Navier-Stokes models (Lee et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Flow over a rounded backward-facing step, using a z-coordinate model and a σ-coordinate model

Rygg¹,

Alendal

Haugan

2011

Ocean Dynamics

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Homogeneous, nonrotating flow over a backward-facing rounded step is simulated using the 2D vertical version of two general circulation models, a z-coordinate model-the Massachusetts Institute of Technology general circulation model (MITgcm)-and a σ -coordinate model-the Bergen Ocean Model (BOM). The backward-facing step is a well-known testcase since it is geometrically simple but still embodies important flow characteristics such as separation point, reattachment length, and recirculation of the flow. The study compares the core of the two models and uses constant eddy viscosities and diffusivities. The Reynolds numbers ranges from 2·10 2 to 2·10 6 . The results correspond with previously published results having a relatively stationary separation point and a fluctuating reattachment length due to downslope propagating eddies released from the reattachment zone for Reynolds numbers higher than or equal to 2 · 10 4 . For Reynolds number within the laminar regime, the flow is stationary. The discrepancies between the models increase by enhancing Reynolds numbers. The σ -coordinate model experiences a reduction in eddy sizes with increasing resolution and Reynolds numbers in correspondence with published experiments, while the size of the eddies are independent of the Reynolds number using the MITgcm. Due to mixing generated by the staircase topography, the z-coordinate model gives a better convergence of the separation point and reattachment length compared with the BOM; however, this conclusion might change with the inclusion of a relevant turbulence scheme.

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“…In this model, the effect of Reynolds number and frequency were included. Chase [12], Lee et al [25], Peltier and Hambric [26], and Chang et al [27] estimated the surface spectra directly from the turbulence statistics. In the study presented here, a model based on those statistics will be presented.…”

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confidence: 99%

“…The modeling of point surface pressure spectrum has extended Chase's model cross spectrum with the introduction of anisotropic turbulence. The turbulent anisotropy is derived from RANS solution directly rather than assuming it as Lee et al [25] did. This allows the model to be applied to a wider range of flows.…”

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Prediction of Trailing-Edge Noise Based on Reynolds-Averaged Navier–Stokes Solution

Chen

MacGillivray

2014

AIAA Journal

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Trailing-edge noise is a significant component of the noise generated by low-Mach-number wall-bounded turbulent flow. It is therefore important to develop an efficient method for computing this noise in practical applications. Instead of using computationally expensive methods or an empirical model to predict the true time history of surface pressure, a model of trailing-edge noise for a hydrofoil combining widely used computational-fluid-dynamics Reynoldsaveraged Navier-Stokes solutions with the edge source acoustic Green's function of arbitrary chord is presented. The model takes the nature of the anisotropic turbulence in boundary-layer flow derived from Reynolds-averaged Navier-Stokes solution into consideration. The model has been applied to the trailing-edge noise of a NACA 0012 foil at a chord-based Reynolds number equal to 2.36 × 10 6 and to a strut with hemicylindrical leading edge and tapered trailing edge at Reynolds number equal to 5.12 × 10 5 . It has been compared with existing empirical models, and a significant improvement has been obtained. The predicted results are in good agreement with existing experimental data. Nomenclaturein the model spectrum density c 0 = speed of sound in the far field, m∕s E 0 ψ , E N ψ = normalized model cross-spectrum density of velocity E N 22 = normalized cross-spectrum density of u 0 2 G = Green's function K = κ 2 1 κ 2 3 p , 1∕m K ν = νth-order Bessel function k = turbulence kinetic energy, m 2 ∕s 2 L s = spanwise length of foil, m l i = pressure fluctuation correlate length scale in i direction, m p = hydrodynamic pressure, Pa p = mean pressure, Pa p 0 = pressure fluctuation, Pa p a = acoustic pressure, Pa p aI = incident acoustic pressure, Pa U c = convection velocity in streamwise direction, m∕s u = velocity vector, m∕s u i = mean velocity in i direction, m∕s u 0 i = velocity fluctuation in i direction, m∕s u = wall shear velocity, m∕s x, x 0 = coordinate vector, with i equal to 1 (streamwise), 2 (vertical), or 3 (spanwise), m y y i = observation coordinates, m δ = boundary-layer thickness, m δ = boundary-layer displacement thickness, m κ i = wave number in i direction, 1∕m κ 0 = acoustic wave number, 1∕m Λ = streamwise turbulence integral length scale, m μ = dynamic viscosity of fluid, kg∕m · s ρ = density of fluid kg∕m 3= radiated trailing-edge noise spectrum for a semiinfinite foil, Pa 2 ∕Hz ϕ pp = point surface pressure spectrum, Pa 2 ∕Hz ψ = angle between the observer direction and the trailing edge of a foil, deg ω = angular frequency, rad∕s

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Turbulence effects of wall-pressure fluctuations for reattached flow

Cited by 18 publications

References 19 publications

Wall-Pressure Spectral Model Including the Adverse Pressure Gradient Effects

Wall-Pressure Spectral Model Including the Adverse Pressure Gradient Effects

Flow over a rounded backward-facing step, using a z-coordinate model and a σ-coordinate model

Prediction of Trailing-Edge Noise Based on Reynolds-Averaged Navier–Stokes Solution

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