On the turbulent diffusion velocity in mixing layer simulated using the vortex method and the subgrid scale vorticity model

Milane, R. E.; Nourazar, S. Salman

doi:10.1016/0093-6413(95)00032-m

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…z @x − e z 2 @ @y |S| @! z @y (17) The constant C r is uniquely speciÿed in 2D simulation, unlike 3D simulation where the constant is over speciÿed and error minimization is invoked. For any ÿltered variable calculated at the nodes, such as !…”

Section: Sgs Modelsmentioning

confidence: 99%

“…In the Lagrangian representation, the e ect of eddy viscosity model was implemented by modifying the strength of the particles using the particle strength exchange (PSE) [15]. Other LES based on corespreading, valid in the limit of vanishing viscosity [5,16], have been used by Milane and Nourazar [17,18]. Cottet [19] presented SGS model based on a rigorous analysis of truncation error of the ÿltered vorticity transport and developed a scheme based on the PSE method for small-scale contribution.The di usion-velocity method is an alternative way for simulating the di usion equation and can be extended to an eddy-viscosity-based LES formulation.…”

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confidence: 99%

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Large eddy simulation (2D) of spatially developing mixing layer using vortex-in-cell for flow field and filtered probability density function for scalar field

Wang

Milane

2005

Int. J. Numer. Meth. Fluids

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SUMMARYA large eddy simulation based on ÿltered vorticity transport equation has been coupled with ÿltered probability density function transport equation for scalar ÿeld, to predict the velocity and passive scalar ÿelds. The ÿltered vorticity transport has been formulated using di usion-velocity method and then solved using the vortex method. The methodology has been tested on a spatially growing mixing layer using the two-dimensional vortex-in-cell method in conjunction with both Smagorinsky and dynamic eddy viscosity subgrid scale models for an anisotropic ow. The transport equation for ÿltered probability density function is solved using the Lagrangian Monte-Carlo method. The unresolved subgrid scale convective term in ÿltered density function transport is modelled using the gradient di usion model. The unresolved subgrid scale mixing term is modelled using the modiÿed Curl model. The e ects of subgrid scale models on the vorticity contours, mean streamwise velocity proÿles, root-mean-square velocity and vorticity uctuations proÿles and negative cross-stream correlations are discussed. Also the characteristics of the passive scalar, i.e. mean concentration proÿles, root-mean-square concentration uctuations proÿles and ÿltered probability density function are presented and compared with previous experimental and numerical works. The sensitivity of the results to the Schmidt number, constant in mixing frequency and in ow boundary conditions are discussed.

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Section: Sgs Modelsmentioning

confidence: 99%

mentioning

confidence: 99%

Large eddy simulation (2D) of spatially developing mixing layer using vortex-in-cell for flow field and filtered probability density function for scalar field

Wang

Milane

2005

Int. J. Numer. Meth. Fluids

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“…It was first introduced by Fronteau & Combis [1] in 1984 and popularized by Degond & Mustieles [2,3], Ogami & Akamatsu [4] and Kempka & Strickland [5] in the early 1990s. This method was then largely analysed [6][7][8][9][10], adapted to dispersion equations [10][11][12], coupled with turbulence models [13,14] and extended to the diffusion of a vector field and to axisymmetric flows [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A self-regularising DVM–PSE method for the modelling of diffusion in particle methods

Mycek

Pinon

Germain

et al. 2013

Comptes Rendus. Mécanique

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The modelling of diffusive terms in particle methods is a delicate matter and several models have been proposed in the literature. The Diffusion Velocity Method (DVM) consists in rewriting these terms in an advective way, thus defining a so-called diffusion velocity. In addition to the actual velocity, it is used to compute the particles displacement. On the other hand, the well-known and commonly used Particle Strength Exchange method (PSE) uses an approximation of the Laplacian operator in order to model diffusion. This approximation is based on an exchange of particles strength. Although DVM is particularly well suited to particle methods since it preserves their Lagrangian aspect, its major drawback stems in the fact that it suffers from severe singular behaviours. This paper intends to give insights and ideas for coping with these issues, based on an exact decomposition of the diffusion coefficient allowing a hybrid DVM-PSE treatment of diffusive terms.

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Large eddy simulation (2D) using diffusion–velocity method and vortex‐in‐cell

Milane

2004

Numerical Methods in Fluids

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A large eddy Simulation based on the diffusion‐velocity method and the discrete vortex method is presented. The vorticity‐based and eddy viscosity type subgrid scale model simulating the enstrophy transfer between the large and small scale appears as a convective term in the diffusion‐velocity formulation. The methodology has been tested on a spatially growing mixing layer using the two‐dimensional vortex‐in‐cell method and the Smagorinsky subgrid scale model. The effects on the vorticity contours, momemtum thickness, mean streamwise velocity profiles, root‐mean‐square velocity and vorticity fluctuations and negative cross‐stream correlation are discussed. Comparison is made with experiment and numerical work where diffusion is simulated using random walk. Copyright © 2004 John Wiley & Sons, Ltd.

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On the turbulent diffusion velocity in mixing layer simulated using the vortex method and the subgrid scale vorticity model

Cited by 5 publications

References 6 publications

Large eddy simulation (2D) of spatially developing mixing layer using vortex-in-cell for flow field and filtered probability density function for scalar field

Large eddy simulation (2D) of spatially developing mixing layer using vortex-in-cell for flow field and filtered probability density function for scalar field

A self-regularising DVM–PSE method for the modelling of diffusion in particle methods

Large eddy simulation (2D) using diffusion–velocity method and vortex‐in‐cell

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