2011
DOI: 10.1088/1742-6596/333/1/012015
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Statistical analysis of the influence of forces on particles in EM driven recirculated turbulent flows

Abstract: The present paper contains an analysis of the statistical distribution of forces affecting non-conducting particles dispersed in an EM induced recirculated flow in induction furnaces. The simulation is conducted adopting the LES-based Euler-Lagrange approach in the limit of dilute conditions (one-way coupling). It is done by means of a development of OpenFOAM software code. The used Lagrange equation for particle tracking includes drag, EM, buoyancy, lift, acceleration and added mass forces. The relevant appro… Show more

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Cited by 12 publications
(11 citation statements)
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“…The model of the analyzed process requires the coupling of the electromagnetic field with hydrodynamic field. It is possible to apply the commonly used one-way coupling of these fields [12][13][14][15] due to the fact that in the modeled process the magnetic Reynolds number is low; the moving (during the infiltration of catalyst carrier) phase boundary is present only in the area of the ceramic carrier and does not influence the distribution of the electromagnetic field because of zero macroscopic conductivity of the carrier capillary structure (independent of the presence of metal). This made it possible to divide simulation into two separate stages-the quasi-static simulation of the electromagnetic field giving the distribution of Lorentz force acting on liquid metal and the unsteady hydrodynamic simulation (Figure 1).…”
Section: Model Of Processmentioning
confidence: 99%
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“…The model of the analyzed process requires the coupling of the electromagnetic field with hydrodynamic field. It is possible to apply the commonly used one-way coupling of these fields [12][13][14][15] due to the fact that in the modeled process the magnetic Reynolds number is low; the moving (during the infiltration of catalyst carrier) phase boundary is present only in the area of the ceramic carrier and does not influence the distribution of the electromagnetic field because of zero macroscopic conductivity of the carrier capillary structure (independent of the presence of metal). This made it possible to divide simulation into two separate stages-the quasi-static simulation of the electromagnetic field giving the distribution of Lorentz force acting on liquid metal and the unsteady hydrodynamic simulation (Figure 1).…”
Section: Model Of Processmentioning
confidence: 99%
“…In the case of the considered process a multiphysical model taking into account coupling of the electromagnetic field with the hydrodynamic field has to be developed. Such models were previously developed for many industrial processes [12][13][14][15] but without a porous medium limiting the impact of electromagnetic field on the molten metal. Only paper [16] describes such a simple one-dimensional model of the Lorentz force infiltration of the porous structure.…”
Section: Introductionmentioning
confidence: 99%
“…The melt flow in such an ICF has often been investigated, both numerically and experimentally. [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] Baake et al 5 investigated the flow in an ICF numerically and experimentally, reporting that the standard k À e turbulence model can provide good agreement with the time-averaged flow field measured in a reference experiment. However, this model could not predict the low-frequency velocity pulsations that occur in the region between toroidal vortices, which is significant to describe the heat and mass transfer in the ICF.…”
Section: Introductionmentioning
confidence: 99%
“…[14] Kirpo et al [15] created the Euler-Lagrangian model of a particle-laden flow in the ICF, which was later improved by Ščepanskis et al taking into account all of the inertial forces moving a particle in the turbulent liquid metal flow upon the presence of electromagnetic (EM) field. [16] The analysis of the homogenization of solid inclusions from an open surface of the melt in the ICF as well as a theoretical investigation of the observed dependences was done by applying this LES-based model. [17] However, a significant obstacle for a direct industrial utilization of this model is a long time of the LES calculation, which makes it unfeasible for an optimization task.…”
Section: Introductionmentioning
confidence: 99%