Large Eddy Simulations of turbulent particle-laden channel flow

Mallouppas, George; Wachem, Berend van

doi:10.1016/j.ijmultiphaseflow.2013.02.007

Cited by 79 publications

(35 citation statements)

References 28 publications

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“…(1) using the filtered fluid velocity provided by LES. Other works followed (see [6,7,26,27,66,69,70,131,132] among others), which were based on the same assumption. As discussed in Sect.…”

Section: Governing Equations and Relevant Modelling Parametersmentioning

confidence: 99%

Large-eddy simulation of turbulent dispersed flows: a review of modelling approaches

Marchioli

2017

Acta Mech

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In large-eddy simulation (LES) of turbulent dispersed flows, modelling and numerical inaccuracies are incurred because LES provides only an approximation of the filtered velocity. Interpolation errors can also occur (on coarse-grained domains, for instance). These inaccuracies affect the estimation of the forces acting on particles, obtained when the filtered fluid velocity is supplied to the Lagrangian equation of particle motion, and accumulate in time. As a result, particle trajectories in LES fields progressively diverge from particle trajectories in DNS fields, which can be considered as the exact numerical reference: the flow fields seen by the particles become less and less correlated, and the forces acting on particles are evaluated at increasingly different locations. In this paper, we review models and strategies that have been proposed in the EulerianLagrangian framework to correct the above-mentioned sources of inaccuracy on particle dynamics and to improve the prediction of particle dispersion in turbulent dispersed flows.

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“…(1) using the filtered fluid velocity provided by LES. Other works followed (see [6,7,26,27,66,69,70,131,132] among others), which were based on the same assumption. As discussed in Sect.…”

Section: Governing Equations and Relevant Modelling Parametersmentioning

confidence: 99%

Large-eddy simulation of turbulent dispersed flows: a review of modelling approaches

Marchioli

2017

Acta Mech

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“…It is implemented in MultiFlow, a parallel multi-phase flow solver (van Wachem, 2013). A detailed description of the standard CFD-DEM model can be referred in the literature (Deen et al, 2007;Liu et al, 2013;Mallouppas and van Wachem, 2013).…”

Section: Modelmentioning

confidence: 99%

An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

et al. 2016

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Nanoparticle fluidization is an efficient technique to disperse and process nanoparticles. Previous studies show that nanoparticles are not fluidized individually, but as agglomerates with hierarchical fractal structures. In this study, an adhesive CFD-DEM (Computational Fluid Dynamics -Discrete Element Modelling) model is developed, in which we use the simple agglomerate as the discrete element, which are the building blocks of the larger complex agglomerates found in a fluidized bed. We show that both the particle contact model and drag force interaction in the conventional CFD-DEM model need modification for properly simulating fluidization of nanoparticle agglomerates. The contact model includes collision mechanisms of elastic-plastic, cohesive and viscoelastic forces, and the drag force is approximately corrected by a scale factor resulting from particle agglomeration. The model is tested for different cases, including the normal impact, response of angle, and fluidization. The simulation results are promising. With increasing particle cohesive force, the fluidized bed goes from a uniform fluid-like regime, to an agglomerate bubbling regime, and finally to defluidization. The current study provides a tool for gaining insights into the characteristics of nanoparticle fluidization.

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“…By integrating the equations of motion, using the Verlet algorithm (Mallouppas & van Wachem, 2013), we obtained the evolution in time of the particle positions and velocities.…”

Section: Equations Of Motionmentioning

confidence: 99%

Lateral solid mixing in gas-fluidized beds: CFD and DEM studies

Oke

Wachem

Mazzei

2016

Chemical Engineering Research and Design

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We investigated lateral solid mixing in gas-fluidized beds using CFD and DEM. We ran 3D CFD simulations, comparing the results with those formerly obtained in 2D CFD simulations. We observed that the frictional stress model affects the numerical results. This was also observed in 2D simulations, but in 3D simulations the effect is less pronounced. The 3D simulations described the lateral solid mixing process more accurately than the 2D simulations, simulation dimensionality being an important factor. To analyse further the role of frictional stress models, we ran 3D DEM simulations, employing the soft-sphere approach to model the particle-particle contact forces. The simulation results agreed reasonably well with the empirical data, but their accuracy depended on the values used for the collision parameters; also, the 3D CFD simulations matched the empirical data more closely.Altogether, we concluded that the simulation dimensionality plays the dominant role in predicting lateral solid mixing accurately.

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Large Eddy Simulations of turbulent particle-laden channel flow

Cited by 79 publications

References 28 publications

Large-eddy simulation of turbulent dispersed flows: a review of modelling approaches

Large-eddy simulation of turbulent dispersed flows: a review of modelling approaches

An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

Lateral solid mixing in gas-fluidized beds: CFD and DEM studies

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