scholarly journals An Anisotropic Subgrid-Scale Parameterization for Large-Eddy Simulations of Stratified Turbulence

2020 ◽  
Vol 148 (10) ◽  
pp. 4299-4311
Author(s):  
Sina Khani ◽  
Michael L. Waite
Keyword(s):  
Equations Of Motion ◽  
Computational Cost ◽  
Large Eddy Simulations ◽  
Subgrid Scale ◽  
Stratified Turbulence ◽  
Grid Spacing ◽  
Large Eddy ◽  
Vertical Grid ◽  
Ocean Models ◽  
Les Model

AbstractSubgrid-scale (SGS) parameterizations in atmosphere and ocean models are often defined independently in the horizontal and vertical directions because the grid spacing is not the same in these directions (anisotropic grids). In this paper, we introduce a new anisotropic SGS model in large-eddy simulations (LES) of stratified turbulence based on horizontal filtering of the equations of motion. Unlike the common horizontal SGS parameterizations in atmosphere and ocean models, the vertical derivatives of the horizontal SGS fluxes are included in our anisotropic SGS scheme, and therefore the horizontal and vertical SGS dissipation mechanisms are not disconnected in the newly developed model. Our model is tested with two vertical grid spacings and various horizontal resolutions, where the horizontal grid spacing is comparatively larger than that in the vertical. Our anisotropic LES model can successfully reproduce the results of direct numerical simulations, while the computational cost is significantly reduced in the LES. We suggest the new anisotropic SGS model as an alternative to current SGS parameterizations in atmosphere and ocean models, in which the schemes for horizontal and vertical scales are often decoupled. The new SGS scheme may improve the dissipative performance of atmosphere and ocean models without adding any backscatter or other energizing terms at small horizontal scales.

Mixing efficiency in large-eddy simulations of stratified turbulence

2018 ◽  
Vol 849 ◽  
pp. 373-394 ◽  
Author(s):  
Sina Khani
Keyword(s):  
Numerical Simulations ◽  
Large Eddy Simulations ◽  
Mixing Efficiency ◽  
Stratified Turbulence ◽  
Grid Spacing ◽  
Computational Costs ◽  
Large Eddy ◽  
Ozmidov Scale ◽  
Computational Resources ◽  
Scaling Coefficient

The irreversible mixing efficiency is studied using large-eddy simulations (LES) of stratified turbulence, where three different subgrid-scale (SGS) parameterizations are employed. For comparison, direct numerical simulations (DNS) and hyperviscosity simulations are also performed. In the regime of stratified turbulence where $Fr_{v}\sim 1$, the irreversible mixing efficiency $\unicode[STIX]{x1D6FE}_{i}$ in LES scales like $1/(1+2Pr_{t})$, where $Fr_{v}$ and $Pr_{t}$ are the vertical Froude number and turbulent Prandtl number, respectively. Assuming a unit scaling coefficient and $Pr_{t}=1$, $\unicode[STIX]{x1D6FE}_{i}$ goes to a constant value $1/3$, in agreement with DNS results. In addition, our results show that the irreversible mixing efficiency in LES, while consistent with this prediction, depends on SGS parameterizations and the grid spacing $\unicode[STIX]{x1D6E5}$. Overall, the LES approach can reproduce mixing efficiency results similar to those from the DNS approach if $\unicode[STIX]{x1D6E5}\lesssim L_{o}$, where $L_{o}$ is the Ozmidov scale. In this situation, the computational costs of numerical simulations are significantly reduced because LES runs require much smaller computational resources in comparison with expensive DNS runs.

Buoyancy scale effects in large-eddy simulations of stratified turbulence

2014 ◽  
Vol 754 ◽  
pp. 75-97 ◽  
Author(s):  
Sina Khani ◽  
Michael L. Waite
Keyword(s):  
Scale Effects ◽  
Vertical Direction ◽  
Local Maximum ◽  
Large Eddy Simulations ◽  
Energy Spectra ◽  
Buoyancy Frequency ◽  
Stratified Turbulence ◽  
Grid Spacing ◽  
Smagorinsky Model ◽  
Large Eddy

AbstractIn this paper large-eddy simulations (LES) of forced stratified turbulence using two common subgrid scale (SGS) models, the Kraichnan and Smagorinsky models, are studied. As found in previous studies using regular and hyper-viscosity, vorticity contours show elongated horizontal motions, which are layered in the vertical direction, along with intermittent Kelvin–Helmholtz (KH) instabilities. Increased stratification causes the layer thickness to collapse towards the dissipation scale, ultimately suppressing these instabilities. The vertical energy spectra are relatively flat out to a local maximum, which varies with the buoyancy frequency $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}N$. The horizontal energy spectra depend on the grid spacing $\varDelta $; if the resolution is fine enough, the horizontal spectrum shows an approximately $-5/3$ slope along with a bump at the buoyancy wavenumber $k_b = N/u_{rms}$, where $u_{rms}$ is the root-mean-square (r.m.s.) velocity. Our results show that there is a critical value of the grid spacing $\varDelta $, below which dynamics of stratified turbulence are well-captured in LES. This critical $\varDelta $ depends on the buoyancy scale $L_b$ and varies with different SGS models: the Kraichnan model requires $\varDelta < 0.47 L_b$, while the Smagorinsky model requires $\varDelta < 0.17 L_b$. In other words, the Smagorinsky model is significantly more costly than the Kraichnan approach, as it requires three times the resolution to adequately capture stratified turbulence.

Subgrid-scale models for large-eddy simulations of compressible wall bounded flows

AIAA Journal ◽  
2000 ◽  
Vol 38 ◽  
pp. 1340-1350 ◽  
Author(s):  
E. Lenormand ◽  
P. Sagaut ◽  
L. Ta Phuoc ◽  
P. Comte
Keyword(s):  
Large Eddy Simulations ◽  
Subgrid Scale ◽  
Scale Models ◽  
Large Eddy ◽  
Wall Bounded Flows

scholarly journals Statistical ensemble of large-eddy simulations

2002 ◽  
Vol 455 ◽  
pp. 195-212 ◽  
Author(s):  
DANIELE CARATI ◽  
MICHAEL M. ROGERS ◽  
ALAN A. WRAY
Keyword(s):  
Large Scale ◽  
Isotropic Turbulence ◽  
Velocity Fields ◽  
Large Eddy Simulations ◽  
Statistical Ensemble ◽  
Model Parameters ◽  
Spatial Averaging ◽  
Subgrid Scale ◽  
Large Eddy ◽  
New Models

A statistical ensemble of large-eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large-scale velocity fields is used in an ensemble-averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble-averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES provides statistics of the large-scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble-averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time-developing plane wake. It is found that the results are almost independent of the number of LES in the statistical ensemble provided that the ensemble contains at least 16 realizations.

Subgrid scale variance and dissipation of a scalar field in large eddy simulations

2001 ◽  
Vol 13 (6) ◽  
pp. 1748-1754 ◽  
Author(s):  
C. Jiménez ◽  
F. Ducros ◽  
B. Cuenot ◽  
B. Bédat
Keyword(s):  
Scalar Field ◽  
Large Eddy Simulations ◽  
Subgrid Scale ◽  
Large Eddy

scholarly journals A new subgrid-scale representation of hydrometeor fields using a multivariate PDF

2016 ◽  
Author(s):  
Brian M. Griffin ◽  
Vincent E. Larson
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Vertical Velocity ◽  
Lognormal Distribution ◽  
Large Eddy Simulations ◽  
Subgrid Scale ◽  
Microphysical Process ◽  
Large Eddy ◽  
Probability Density Function Pdf

Abstract. The subgrid-scale representation of hydrometeor fields is important for calculating microphysical process rates. In order to represent subgrid-scale variability, the Cloud Layers Unified By Binormals (CLUBB) parameterization uses a multivariate Probability Density Function (PDF). In addition to vertical velocity, temperature, and moisture fields, the PDF includes hydrometeor fields. Previously, each hydrometeor field was assumed to follow a multivariate single lognormal distribution. Now, in order to better represent the distribution of hydrometeors, two new multivariate PDFs are formulated and introduced. The new PDFs represent hydrometeors using either a delta-lognormal or a delta-double-lognormal shape. The two new PDF distributions, plus the previous single lognormal shape, are compared to histograms of data taken from Large-Eddy Simulations (LES) of a precipitating cumulus case, a drizzling stratocumulus case, and a deep convective case. Finally, the warm microphysical process rates produced by the different hydrometeor PDFs are compared to the same process rates produced by the LES.

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