An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications

2004 ◽  
Vol 16 (10) ◽  
pp. 3670-3681 ◽  
Author(s):  
A. W. Vreman
Keyword(s):  
Shear Flow ◽  
Eddy Viscosity ◽  
Algebraic Theory ◽  
Scale Model ◽  
Turbulent Shear ◽  
Turbulent Shear Flow ◽  
Subgrid Scale ◽  
Subgrid Scale Model

An Energy-Based Similarity Subgrid-Scale Model in Two-Dimensional Planar Shear Flow

2013 ◽  
Vol 694-697 ◽  
pp. 594-600
Author(s):  
Yu Xuan Zhang ◽  
Song Ping Wu
Keyword(s):  
Shear Flow ◽  
Scale Model ◽  
Two Dimensional ◽  
Subgrid Scale ◽  
Planar Shear ◽  
New Type ◽  
Subgrid Scale Model ◽  
Layer Flow ◽  
Refined Grid ◽  
Dissipative Scale

A new type of similarity subgrid-scale (SGS) model which based on energy and dissipative scale isotropy assumption is presented. This model combines the advantages of traditional Smagorinsky SGS model with similarity SGS model. And a two-dimensional shear layer flow is simulated using refined grid result as a standard and comparing witch LES method including multiple SGS models. The results indicate that the result of SIM model much approximates to refined grid result than other SGS models.

On the properties of similarity subgrid-scale models as deduced from measurements in a turbulent jet

1994 ◽  
Vol 275 ◽  
pp. 83-119 ◽  
Author(s):  
Shewen Liu ◽  
Charles Meneveau ◽  
Joseph Katz
Keyword(s):  
Stress Tensor ◽  
Eddy Viscosity ◽  
Weighting Function ◽  
A Priori ◽  
Scale Model ◽  
Solid Boundary ◽  
Strain Rate Tensor ◽  
Subgrid Scale ◽  
The Real ◽  
Subgrid Scale Model

The properties of turbulence subgrid-scale stresses are studied using experimental data in the far field of a round jet, at a Reynolds number of Rλ ≈ 310. Measurements are performed using two-dimensional particle displacement velocimetry. Three elements of the subgrid-scale stress tensor are calculated using planar filtering of the data. Using a priori testing, eddy-viscosity closures are shown to display very little correlation with the real stresses, in accord with earlier findings based on direct numerical simulations at lower Reynolds numbers. Detailed analysis of subgrid energy fluxes and of the velocity field decomposed into logarithmic bands leads to a new similarity subgrid-scale model. It is based on the ‘resolved stress’ tensor Lij, which is obtained by filtering products of resolved velocities at a scale equal to twice the grid scale. The correlation coefficient of this model with the real stress is shown to be substantially higher than that of the eddy-viscosity closures. It is shown that mixed models display similar levels of correlation. During the a priori test, care is taken to only employ resolved data in a fashion that is consistent with the information that would be available during large-eddy simulation. The influence of the filter shape on the correlation is documented in detail, and the model is compared to the original similarity model of Bardina et al. (1980). A relationship between Lij and a nonlinear subgrid-scale model is established. In order to control the amount of kinetic energy backscatter, which could potentially lead to numerical instability, an ad hoc weighting function that depends on the alignment between Lij and the strain-rate tensor, is introduced. A ‘dynamic’ version of the model is shown, based on the data, to allow a self-consistent determination of the coefficient. In addition, all tensor elements of the model are shown to display the correct scaling with normal distance near a solid boundary.

Assessment of anisotropic minimum-dissipation (AMD) subgrid-scale model: Gently-curved backward-facing step flow

2021 ◽  
pp. 2150068
Author(s):  
Amir-Pouyan Zahiri ◽  
Ehsan Roohi
Keyword(s):  
Eddy Viscosity ◽  
Scale Model ◽  
Subgrid Scale ◽  
Backward Facing Step ◽  
Step Flow ◽  
Numerical Predictions ◽  
Turbulent Inflow ◽  
Model Predictions ◽  
Subgrid Scale Model ◽  
The Impact

The impetus of this study is to evaluate the performance of the anisotropic minimum-dissipation (AMD) subgrid-scale model (SGS) for flow over a gently-curved backward-facing step (BFS) at a Reynolds number of 13 700. Minimum-dissipation sub-grid models were developed as simple alternatives to the dynamic eddy-viscosity SGS models. AMD model is a static type of eddy-viscosity SGS model incorporating anisotropic SGS effects into numerical predictions through the large-eddy simulation (LES) approach. The open-source CFD package of OpenFOAM was used to implement the AMD model. Before focusing on the BFS flow, we investigated the impact of the AMD model coefficient magnitude on the numerical predictions of the decaying isotropic turbulence flow. In the next step, numerical solutions were obtained for the curved backward-facing step using the AMD model and Dynamic Smagorinsky model (DSM). The curved backward-facing step was considered here for the evaluation of the SGS model predictions due to its weak adverse pressure gradient and high sensitive flow mechanism. The rescaling/recycling method was employed as a turbulent inflow generation technique. The AMD model results were compared with the prediction of the DSM and Vreman model. Moreover, AMD model predictions were compared with the reported solutions obtained using different turbulent inflow generation methods. The assessments revealed the high capability of the AMD model to capture decaying turbulence and predict velocity profiles and resolved flow statistics turbulent parameters in the gently-curved backward step flow.

Large Eddy Simulation of Rotating Finite Source Convection

2005 ◽  
Vol 73 (1) ◽  
pp. 79-87
Author(s):  
Shari J. Kimmel-Klotzkin ◽  
Fadi P. Deek
Keyword(s):  
Large Eddy Simulation ◽  
Eddy Viscosity ◽  
Rotating Flows ◽  
Scale Model ◽  
Subgrid Scale ◽  
Smagorinsky Model ◽  
Convective Flows ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Subgrid Scale Model

Numerical simulations of turbulent convection under the influence of rotation will help understand mixing in oceanic flows. Though direct numerical simulations (DNS) can accurately model rotating convective flows, this method is limited to small scale and low speed flows. A large eddy simulation (LES) with the Smagorinsky subgrid scale model is used to compute the time evolution of a rotating convection flow generated by a buoyancy source of finite size at a relatively high Rayleigh number. Large eddy simulations with eddy viscosity models have been used successfully for other rotating convective flows, so the Smagorinsky model is a reasonable starting point. These results demonstrate that a LES can be used to model larger scale rotating flows, and the resulting flow structure is in good agreement with DNS and experimental results. These results also demonstrate that the qualitative behavior of vorticies which form under the source depend on the geometry of the flow. For source diameters that are small compared to the size of the domain, the vortices propagate away from the source. On the other hand, if the ratio of source diameter to domain size is relatively large, the vortices are constrained beneath the source. Though the results are qualitatively similar to a direct numerical simulation (DNS) and other LES, in this simulation the flow remains laminar much longer than the DNS predicts. This particular flow is complicated by the turbulence transition between the convective plume and the quiescent ambient fluid, and an eddy viscosity model is inadequate to accurately model this type of flow. In addition, the Smagorinsky model is not consistent in a noninertial reference frame. Thus the Smagorinsky model is not the optimal choice for this type of flow. In particular, the estimation model has demonstrated better results for other types of rotating flows and is the recommended subgrid scale model for future work.

Open-loop control of compensation for optical propagation through a turbulent shear flow

1998 ◽  
Author(s):  
C. Truman ◽  
Lenore McMackin ◽  
Robert Pierson ◽  
Kenneth Bishop ◽  
Ellen Chen
Keyword(s):  
Shear Flow ◽  
Open Loop ◽  
Turbulent Shear ◽  
Turbulent Shear Flow ◽  
Open Loop Control ◽  
Loop Control ◽  
Optical Propagation
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