scholarly journals A fractional subgrid-scale model for turbulent flows: Theoretical formulation and a priori study

2020 ◽  
Vol 32 (5) ◽  
pp. 055102 ◽  
Author(s):  
Mehdi Samiee ◽  
Ali Akhavan-Safaei ◽  
Mohsen Zayernouri
Keyword(s):  
Turbulent Flows ◽  
A Priori ◽  
Scale Model ◽  
Subgrid Scale ◽  
Theoretical Formulation ◽  
Subgrid Scale Model

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.

scholarly journals Scale dependence of subgrid-scale model coefficients: An a priori study

2008 ◽  
Vol 20 (11) ◽  
pp. 115106 ◽  
Author(s):  
Elie Bou-Zeid ◽  
Nikki Vercauteren ◽  
Marc B. Parlange ◽  
Charles Meneveau
Keyword(s):  
A Priori ◽  
Scale Dependence ◽  
Scale Model ◽  
Subgrid Scale ◽  
Subgrid Scale Model

Statistical Properties of Subgrid-Scale Turbulence Models

2021 ◽  
Vol 53 (1) ◽  
pp. 255-286
Author(s):  
Robert D. Moser ◽  
Sigfried W. Haering ◽  
Gopal R. Yalla
Keyword(s):  
Turbulent Flows ◽  
A Priori ◽  
Turbulence Models ◽  
Statistical Characteristics ◽  
Scale Model ◽  
Subgrid Scale ◽  
Dissipation Energy ◽  
Eddy Simulation ◽  
Scale Turbulence ◽  
Subgrid Stress

This review examines large eddy simulation (LES) models from the perspective of their a priori statistical characteristics. The most well-known statistical characteristic of an LES subgrid-scale model is its dissipation (energy transfer to unresolved scales), and many models are directly or indirectly formulated and tuned for consistency of this characteristic. However, in complex turbulent flows, many other subgrid statistical characteristics are important. These include such quantities as mean subgrid stress, subgrid transport of resolved Reynolds stress, and dissipation anisotropy. Also important are the statistical characteristics of models that account for filters that do not commute with differentiation and of the discrete numerical operators in the LES equations. We review the known statistical characteristics of subgrid models to assess these characteristics and the importance of their a priori consistency. We hope that this analysis will be helpful in continued development of LES models.

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