Shear improved Smagorinsky model for large eddy simulation of flow in a stirred tank with a Rushton disk turbine

Malik, Satish V.; Lévêque, Emmanuel; Bouaifi, Mounir; Gamet, Lionel; Flottes, Eglantine; Simoëns, Serge; Hajem, Mahmoud El

doi:10.1016/j.cherd.2016.02.035

Cited by 17 publications

(10 citation statements)

References 18 publications

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“…Figure 3 shows the Power number Np (eq. 5), calculated for various Reynolds numbers for Rushton turbine and Novel impeller, and compared with the experimental data from the literature for Rushton turbine [16]. As can be seen, the prediction for the Rushton turbine agrees relatively well with numerical results.…”

Section: Resultsmentioning

confidence: 53%

“…In this work Ansys Fluent was used as a fluid flow solver. To produce a reliable model to study the flow generated by the novel impeller, the simulation results were compared with the results for a Rushton Turbine obtained in literature [16]. For the validation analysis, the same as in literature conditions were used: water as a working fluid with a viscosity of =0.001003 kg/(m•s) and a density of ρ998.2 kg/m 3 .…”

Section: Analysis and Modellingmentioning

confidence: 99%

“…Those analyses are ultimately useful for the optimal design of tanks, and there is still the necessity to extend current knowledge about fluid physics in a stirred vessel. Although H. Patil et al [16] developed a CFD model for a stirred tank to optimise the dimensions of the inner rotating fluid zone using MRF model and to consider the optimal zone where simulation results for velocity predictions were found to be in reasonable agreement with literature data available. Authors investigated the efficiency of optimal MRF zone by comparing the power number predictions at various Reynolds numbers with the experimental results of J. H Rushton et al [17].…”

Section: Introductionmentioning

confidence: 96%

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An experimental and numerical analysis of the fluid flow in a mechanically agitated vessel

2019

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The mixing process is a widespread phenomenon, which plays an essential role among a large number of industrial processes. The effectiveness of mixing depends on the state of mixed phases, temperature, viscosity and density of liquids, mutual solubility of mixed fluids, type of stirrer, a what is the most critical - the shape of the impeller. In the present research, the objective is to analyse the process of the fluid flow in the mechanically agitated vessel with new impeller type. Velocity field values were determined using computer simulation and experimental particle image velocimetry method. The basis for the assessment of the intensity degree and efficiency of mixing was the analysis of velocity vectors distribution and power number. An experimental and numerical study was carried out for various stirred process parameters to determine optimal conditions for the mixing process.

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Section: Resultsmentioning

confidence: 53%

Section: Analysis and Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

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An experimental and numerical analysis of the fluid flow in a mechanically agitated vessel

2019

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“…As a matter of fact, turbulence has a direct influence on mixing processes. Recent studies focus on this aspect and investigate the potential of advanced turbulence models, like Large Eddy Simulation (LES), to enhance stirring models performances [24,25]. Once again, these developments are made possible by the increase of computational capacities.…”

Section: State Of the Artmentioning

confidence: 99%

Mechanical stirring influence on solute segregation during plane front directional solidification

Chatelain

Botton

Albaric

et al. 2018

International Journal of Thermal Sciences

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The present paper focuses on directional solidification processes for photovoltaic silicon purification. The use of a mechanical stirrer in the melt to enhance impurity segregation is investigated through numerical simulations. The 3D forced convection flow is resolved in a transient regime thanks to a sliding mesh approach. The hydrodynamic model is coupled to a solute transport simulation in a quasi-steady approximation (i.e. with constant liquid height). Velocity measurements are performed by Particle Image Velocimetry on a water model in order to validate hydrodynamic simulations. Numerical results show that an efficient segregation can be achieved, even for high solidification rates, thanks to mechanical stirring. The numerical model provides meaningful insights for process optimization as it correlates the impurity repartition on the solidification front to the stirring parameters. Finally, the numerical segregation results are compared to an analytical model of the solute boundary layer. It is found that the analytical model provides a good estimate of the mean segregation regime from an hydrodynamic simulation of the forced convection flow, which makes it a useful tool for process design.

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“…It could be seen that there was a difference between the velocity of the simulations and experiments at both ends of the jet flow area. The fine distinction of the mean velocity might be caused by the geometrical shape, experimental methods and operating conditions [33][34][35].…”

Section: Mean Velocitymentioning

confidence: 99%

The Process of the Intensification of Coal Fly Ash Flotation Using a Stirred Tank

Zhu

et al. 2018

Minerals

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Pulp preconditioning using a stirred tank as a pretreatment process is vital to the flotation system, which can be used to improve the flotation efficiency of mineral particles. The kinetic energy that is dissipated in the stirred tank could strengthen the interaction process between mineral particles and flotation reagents to improve the flotation efficiency in the presence of the preconditioning. In this paper, the effect of the conditioning speed on the coal fly ash flotation was investigated using numerical simulations and conditioning-flotation tests. The large eddy simulation coupled with the Smagorinsky-Lilly subgrid model was employed to simulate the turbulence flow field in the stirred tank, which was equipped with a six blade Rushton turbine. The impeller rotation was modelled using the sliding mesh. The simulation results showed that the large eddy simulation (LES) well matched the previous experimental data. The turbulence characteristics, such as the mean velocity, turbulent kinetic energy, power consumption and instantaneous structures of trailing vortices were analysed in detail. The turbulent length scale (η) decreased as the rotation speed increased, and the minimum value of η was almost unchanged when the rotation speed was more than 1200 rpm. The conditioning-flotation tests of coal fly ash were conducted using different conditioning speeds. The results showed that the removal of unburned carbon was greatly improved due to the strengthened turbulence in the stirred tank, and the optimal results were obtained with an LOI of 3.32%, a yield of 78.69% and an RUC of 80.89% when the conditioning speed was 1200 rpm.

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Shear improved Smagorinsky model for large eddy simulation of flow in a stirred tank with a Rushton disk turbine

Cited by 17 publications

References 18 publications

An experimental and numerical analysis of the fluid flow in a mechanically agitated vessel

An experimental and numerical analysis of the fluid flow in a mechanically agitated vessel

Mechanical stirring influence on solute segregation during plane front directional solidification

The Process of the Intensification of Coal Fly Ash Flotation Using a Stirred Tank

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