Dynamic Structure Models for Scalar Flux and Dissipation in Large Eddy Simulation

Chumakov, Sergei; Rutland, Christopher J.

doi:10.2514/1.10416

Cited by 23 publications

(22 citation statements)

References 20 publications

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“…However, the value of ␥ was not found to be constant, as was assumed in previous studies by various authors, 11,14,15 but rather to depend on the proximity of the LES filter size ⌬ to the forcing length scale. None of the observed scalings are close to ⑀ s ϳ k s 3/2 , which is widely used in the current literature.…”

Section: ͑6͒mentioning

confidence: 85%

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Scaling properties of subgrid-scale energy dissipation

Chumakov

2007

Physics of Fluids

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We use direct numerical simulation of forced homogeneous isotropic turbulence with 256 3 and 512 3 grid points and Reynolds number based on Taylor microscale up to 250 to examine a priori the scaling properties of the subgrid-scale kinetic energy and its dissipation rate. It is found that the two quantities are strongly correlated and a power-law scaling assumption holds reasonably well. However, the scaling exponent, which was assumed to be weakly varying in previous studies, is found to change considerably with the filter characteristic width.In the large eddy simulation ͑LES͒, the large-scale features of the flow are resolved directly via a numerical scheme while the effect of the unresolved scales of motion is accounted for by using subgrid-scale ͑SGS͒ models. 1 From the point of view of LES model development, the statistical information about behavior of the small-scale flow quantities is of great importance, for it can be used to verify the underlying assumptions of existing SGS models and provide constraints that have to be satisfied by the ones currently in development. [2][3][4][5] The governing equations for LES are obtained by applying a filtering procedure to the Navier-Stokes equations. In this study, we consider the incompressible case,Here ū i = u i ‫ء‬ G is the filtered velocity, P = p / is the modified pressure, is the kinematic viscosity, and ij = u i u j − ū i ū j is the SGS stress tensor, which has to be modeled. Summation over repeated indices is implied. The filter kernel G is assumed to be non-negative and satisfy ʈGʈ 1 =1. To solve Eqs. ͑1͒ and ͑2͒ numerically, one needs to have a model for ij . A sizable fraction of models for ij in the current literature, referred to as one-equation models, employ the SGS kinetic energy k s = ii / 2 for modeling ij : as a part of scalar eddy viscosity, 6-8 tensor eddy viscosity 9 or a particular scaling factor. 10-12 To obtain k s , one needs to solve an auxiliary transport equation,Here ⌸ =− ij S ij is the term responsible for the energy transfer between resolved and subgrid scales ͑energy transfer term͒; S ij = 1 2 ͑‫ץ‬ū i / ‫ץ‬x j + ‫ץ‬ū j / ‫ץ‬x i ͒ is the resolved strain-rate tensor; Q i is the flux of k s due to inertial and pressure terms, which is usually modeled using an eddy-viscosity ansatz, and ⑀ s is the dissipation rate of k s given byThe quality of models for ij and ⑀ s is crucial for maintaining the correct energy budget in LES. While modeling ij is responsible for the correct energy transfer between the resolved and subgrid scales and is ultimately responsible for the stability of LES calculations that employ zero-equation models, the model for ⑀ s plays the same role in LES calculations with one-equation models. Usually modeling of ⑀ s is dealt with by using

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Section: ͑6͒mentioning

confidence: 85%

“…A sizable fraction of models for ij in the current literature, referred to as one-equation models, employ the SGS kinetic energy k s = ii / 2 for modeling ij : as a part of scalar eddy viscosity, 6-8 tensor eddy viscosity 9 or a particular scaling factor. [10][11][12] To obtain k s , one needs to solve an auxiliary transport equation,…”

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confidence: 99%

Scaling properties of subgrid-scale energy dissipation

Chumakov

2007

Physics of Fluids

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“…The strong sensitivity of computed mean and rms velocity profiles to variations in the SFS turbulence model is an encouraging result. This suggests that better results might be obtained using more advanced models, such as dynamic models and/or non-dissipative models [51]. Such models will be explored in future work.…”

Section: Resultsmentioning

confidence: 99%

Large-Eddy Simulation for an Axisymmetric Piston-Cylinder Assembly With and Without Swirl

Haworth

2010

Flow Turbulence Combust

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Large-eddy simulation (LES) has been performed for an axisymmetric piston-cylinder assembly with and without swirl. For both cases, the LES mean and rms velocity profiles show better agreement with experimental data than profiles obtained using a Reynolds-averaged Navier-Stokes (RANS) approach with a standard k − ε turbulence model. The sum of the resolved and modeled contributions to turbulence kinetic energy (TKE) approaches grid independence for the meshes used in this study. The sensitivity of LES to key numerical and physical model parameters has been investigated. Results are especially sensitive to mesh and to the subfilterscale (SFS) turbulence models. Satisfactory results can be obtained using simple viscosity-based SFS turbulence models, although there is room for improvement. No single model gives uniformly best agreement between model and measurements at all spatial locations and at all times. The strong sensitivity of computed mean and rms velocity profiles to variations in the SFS turbulence model suggests that better results might be obtained using more sophisticated models.

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“…Various subgrid-scale (SGS) models such as the Smagorinsky model (Smagorinsky, 1963;Moin et al, 1991;Germano et al, 1991), one-equation viscosity model (Menon et al, 1996), subgrid k model (Sone and Menon, 2003;Menon, 2000), scale similarity model (Bardina et al, 1980) and one-equation dynamic structure model Chumakov and Rutland, 2004) have been proposed and tested. LES using different SGS models were applied to study turbulent spray combustion processes using various combustion models.…”

Section: Introductionmentioning

confidence: 99%

Large-eddy simulation of air entrainment during diesel spray combustion with multi-dimensional CFD

Azimov

Kim

2011

Int.J Automot. Technol.

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Large-Eddy Simulation (LES) was used to perform computations of air entrainment and mixing during diesel spray combustion. The results of this simulation were compared with those of Reynolds Averaged Navier Stokes (RANS) simulations and an experiment. The effect of LES on non-vaporizing and vaporizing sprays was evaluated. The validity of the grid size used for the LES analysis was confirmed by determining the subgrid-scale (SGS) filter threshold on the turbulent energy spectrum plot, which separates a resolved range from a modeled one. The results showed that more air was entrained into the jet with decreasing ambient gas temperatures. The mass of the evaporated fuel increased with increasing ambient gas temperatures, as did the mixture fraction variance, showing a greater spread in the profile at an ambient gas temperature of 920 K than at 820 K. Flame lift-off length sensitivity was analyzed based on the location of the flame temperature iso-line. The results showed that for the flame temperature iso-line of 2000 o C, the computed lift-off length values in RANS matched the experimental values well, whereas in LES, the computed lift-off length was slightly underpredicted. The apparent heat release rate (AHRR) computed by the LES approach showed good agreement with the experiment, and it provided an accurate prediction of the ignition delay; however, the ignition delay computed by the RANS was underpredicted. Finally, the relationships between the entrained air quantity and mixture fraction distribution as well as soot formation in the jet were observed. As more air was entrained into the jet, the amount of air-fuel premixing that occurred prior to the initial combustion zone increased, upstream of the lift-off length, and therefore, the soot formation downstream of the flame decreased.

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Dynamic Structure Models for Scalar Flux and Dissipation in Large Eddy Simulation

Cited by 23 publications

References 20 publications

Scaling properties of subgrid-scale energy dissipation

Scaling properties of subgrid-scale energy dissipation

Large-Eddy Simulation for an Axisymmetric Piston-Cylinder Assembly With and Without Swirl

Large-eddy simulation of air entrainment during diesel spray combustion with multi-dimensional CFD

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