An Improved Wall-Distance-Free Version of the Baldwin-Barth Turbulence Model

2003 ◽  
Author(s):  
Michel Elkhoury
Keyword(s):  
Pressure Gradient ◽  
Skin Friction ◽  
Turbulence Model ◽  
Eddy Viscosity ◽  
Present Model ◽  
Adverse Pressure Gradient ◽  
Wall Functions ◽  
Friction Prediction ◽  
Naca 0012 ◽  
Good Agreement

This paper presents a modified version of the Baldwin-Barth (BB) turbulence model. This modification accounts for the asymptotic boundary value of the pseudo eddy viscosity as the wall is approached. The BB Model tends to respond strongly to an adverse pressure gradient, in the sense that it always predicts a large decrease in skin friction relative to the measured values. Hence, in the present work, the importance of the modifications for improving the skin friction prediction of flows with adverse pressure gradient is addressed. All of the implemented modifications are free of wall functions and coordinate independent, which renders the model advantageous relative to other wall dependent models. The results are compared with both the original BB and the Spalart-Allmaras (SA) models. The accuracy of these and the present model is assessed against experimental data for transonic flows over NACA-0012 and RAE 2822 airfoils. In general, good agreement with experiments is indicated.

Scrutinizing the k-ε Turbulence Model Under Adverse Pressure Gradient Conditions

1986 ◽  
Vol 108 (2) ◽  
pp. 174-179 ◽  
Author(s):  
W. Rodi ◽  
G. Scheuerer
Keyword(s):  
Pressure Gradient ◽  
Experimental Evidence ◽  
Skin Friction ◽  
Boundary Layers ◽  
Turbulence Model ◽  
Adverse Pressure Gradient ◽  
Equation Model ◽  
Log Law ◽  
The One ◽  
Simple Flows

The k-ε model and a one-equation model have been used to predict adverse pressure gradient boundary layers. While the one-equation model gives generally good results, the k-ε model reveals systematic discrepancies, e.g. too high skin friction coefficients, for these relatively simple flows. These shortcomings are examined and it is shown by an analytical analysis for the log-law region that the generation term of the ε-equation has to be increased to conform with experimental evidence under adverse pressure gradient conditions. A corresponding modification to the ε-equation emphasizing the generation rate due to deceleration was employed in the present investigation and resulted in improved predictions for both moderately and strongly decelerated flows.

An Improved Version of the Cebeci-Smith Eddy-Viscosity Model

1978 ◽  
Vol 29 (3) ◽  
pp. 207-225 ◽  
Author(s):  
M.J. Nituch ◽  
S. Sjolander ◽  
M.R. Head
Keyword(s):  
Pressure Gradient ◽  
Skin Friction ◽  
Boundary Layers ◽  
Eddy Viscosity ◽  
Adverse Pressure Gradient ◽  
Turbulent Boundary Layers ◽  
Viscosity Model ◽  
Eddy Viscosity Model ◽  
Smith Method

SummaryAlthough the Cebeci-Smith method of calculating turbulent boundary layers is widely used and generally gives acceptably accurate results, highly inaccurate skin-friction values are obtained for relaxing flows and equilibrium layers in strong adverse pressure gradient. In the present paper, these anomalies are removed by suitable modifications to the basic eddy-viscosity model.

Structural Parameters and Prediction of Adverse Pressure Gradient Turbulent Flows: An Improved k-ε Model

1995 ◽  
Vol 117 (3) ◽  
pp. 424-432 ◽  
Author(s):  
G. Chukkapalli ◽  
O¨. F. Turan
Keyword(s):  
Pressure Gradient ◽  
Turbulent Flows ◽  
Reynolds Stress ◽  
Eddy Viscosity ◽  
Structural Parameters ◽  
Adverse Pressure Gradient ◽  
Reynolds Stress Model ◽  
Model Representation ◽  
Stress Model ◽  
Kinetic Diffusion

A modified k-ε model is proposed to predict complex, adverse pressure gradient, turbulent diffuser flows. The need for an eddy viscosity is eliminated by using three structural parameters. A fuller treatment of the rate of kinetic diffusion terms is incorporated with a Reynolds stress model representation. A thorough evaluation is given of the three structural parameters in three decreasing and one increasing adverse pressure gradient diffuser flows leading to a three-layer representation. The results indicate the need for better modeling of the ε-equation.

Reynolds Averaged Navier Stokes Models Compared to Direct Numerical Simulations in an Adverse Pressure Gradient Boundary Layer Over a Flat Plate

2013 ◽  
Author(s):  
Daniel Routson ◽  
James Ferguson ◽  
John Crepeau ◽  
Donald McEligot ◽  
Ralph Budwig
Keyword(s):  
Boundary Layer ◽  
Pressure Gradient ◽  
Flat Plate ◽  
National Laboratory ◽  
Adverse Pressure Gradient ◽  
Skin Friction Coefficient ◽  
Navier Stokes ◽  
Transition Model ◽  
Wall Functions ◽  
Reynolds Averaged Navier Stokes

In Reynolds-Averaged Navier Stokes (RANS) models simplifying assumptions breakdown in near wall regions. Wall functions/treatments become inaccurate and the homogeneity and isotropy models may not hold. To see the effect that these assumptions have on the validity of boundary layer results in a commercially available RANS code, key boundary layer parameters are compared from laminar, transitional, and fully turbulent RANS results to an existing direct numerical simulation (DNS) simulation for flow over a flat plate with an adverse pressure gradient (APG). Parameters compared include velocity profiles in the free stream, boundary layer thicknesses, skin friction coefficient and the pressure gradient parameter. Results show comparable momentum thickness and pressure gradient parameters between the transition RANS model and the DNS simulation. Differences in the onset of transition between the RANS transition model and DNS are compared as well. These simulations help evaluate the models used in the RANS code. Of most interest is the transition model, a transition shear-stress transport (SST) k–omega model. The RANS code is being used in conjunction with an APG boundary layer experiment being undertaken at the Idaho National Laboratory (INL).

A Critical Assessment of Reynolds Analogy for Turbine Flows

2005 ◽  
Vol 127 (5) ◽  
pp. 472-485 ◽  
Author(s):  
J. Bons
Keyword(s):  
Heat Transfer ◽  
Surface Roughness ◽  
Reynolds Number ◽  
Pressure Gradient ◽  
Skin Friction ◽  
Adverse Pressure Gradient ◽  
Design Parameters ◽  
Freestream Turbulence ◽  
Reynolds Analogy ◽  
Pressure Drag

The application of Reynolds analogy 2St/cf≅1 for turbine flows is critically evaluated using experimental data collected in a low-speed wind tunnel. Independent measurements of St and cf over a wide variety of test conditions permit assessments of the variation of the Reynolds analogy factor (i.e., 2St/cf) with Reynolds number, freestream pressure gradient, surface roughness, and freestream turbulence. While the factor is fairly independent of Reynolds number, it increases with positive (adverse) pressure gradient and decreases with negative (favorable) pressure gradient. This variation can be traced directly to the governing equations for momentum and energy which dictate a more direct influence of pressure gradient on wall shear than on energy (heat) transfer. Surface roughness introduces a large pressure drag component to the net skin friction measurement without a corresponding mechanism for a comparable increase in heat transfer. Accordingly, the Reynolds analogy factor decreases dramatically with surface roughness (by as much as 50% as roughness elements become more prominent). Freestream turbulence has the opposite effect of increasing heat transfer more than skin friction, thus the Reynolds analogy factor increases with turbulence level (by up to 35% at a level of 11% freestream turbulence). Physical mechanisms responsible for the observed variations are offered in each case. Finally, synergies resulting from the combinations of pressure gradient and freestream turbulence with surface roughness are evaluated. With this added insight, the Reynolds analogy remains a useful tool for qualitative assessments of complex turbine flows where both heat load management and aerodynamic efficiency are critical design parameters.

scholarly journals Direct Numerical Simulation of separated turbulent flow in axisymmetric diffuser

2021 ◽  
Vol 2103 (1) ◽  
pp. 012214
Author(s):  
A S Stabnikov ◽  
D K Kolmogorov ◽  
A V Garbaruk ◽  
F R Menter
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
Turbulent Flow ◽  
Turbulence Model ◽  
Eddy Viscosity ◽  
Separated Flow ◽  
Model Improvement ◽  
Good Agreement

Abstract Direct numerical simulation (DNS) of the separated flow in axisymmetric CS0 diffuser is conducted. The obtained results are in a good agreement with experimental data of Driver and substantially supplement them. Along with other data, eddy viscosity extracted from performed DNS could be used for RANS turbulence model improvement.

Separated Turbulent Boundary Layer Under Unsteady Adverse Pressure Gradients: DNS and RANS

2014 ◽  
Author(s):  
Junshin Park
Keyword(s):  
Numerical Simulation ◽  
Boundary Layer ◽  
Pressure Gradient ◽  
Eddy Viscosity ◽  
Adverse Pressure Gradient ◽  
Velocity Profiles ◽  
Navier Stokes ◽  
Pressure Gradients ◽  
Recirculation Bubble ◽  
Rans Models

Predicitve capabilities of Reynolds Averaged Navier-Stokes (RANS) techniques have been assessed using SST k–ω model and Spalart-Allmaras model by comparing its results with direct numerical simulation (DNS) results. It has been shown that Spalart-Allmaras and SST k–ω model predict an earlier separation point and a bigger recirculation bubble as compared to the DNS result. Velocity profiles predicted by RANS for both models closely match with DNS results for the steady adverse pressure gradient case. However, the RANS fail to predict correct velocity profiles for unsteady adverse pressure gradients not only for inside the bubble but also after the reattachment zone. To provide the backgrounds for improving RANS models, these differences are explained with Reynolds stress and eddy viscosity which differ between the steady and unsteady adverse pressure gradient RANS cases.

The reduction of skin friction by riblets under the influence of an adverse pressure gradient

1993 ◽  
Vol 15 (1) ◽  
pp. 17-26 ◽  
Author(s):  
F. T. M. Nieuwstadt ◽  
W. Wolthers ◽  
H. Leijdens ◽  
K. Krishna Prasad ◽  
A. Schwarz-van Manen
Keyword(s):  
Pressure Gradient ◽  
Skin Friction ◽  
Adverse Pressure Gradient
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