2017
DOI: 10.1016/j.apt.2017.02.002
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Effect of impeller on sinking and floating behavior of suspending particle materials in stirred tank: A computational fluid dynamics and factorial design study

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Cited by 17 publications
(8 citation statements)
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“…Whether it is gas mixing [7] or mechanical mixing [8] , the appropriate mixing of biomass particles needs to be solved to improve anaerobic digestion [9] . Computational fluid dynamics (CFD) simulation technology is a promising technique to study the mixing process between particles and fermentation fluids to optimize the agitator design [10][11][12] by visualizing the mixing process with simulation.…”
Section: Introductionmentioning
confidence: 99%
“…Whether it is gas mixing [7] or mechanical mixing [8] , the appropriate mixing of biomass particles needs to be solved to improve anaerobic digestion [9] . Computational fluid dynamics (CFD) simulation technology is a promising technique to study the mixing process between particles and fermentation fluids to optimize the agitator design [10][11][12] by visualizing the mixing process with simulation.…”
Section: Introductionmentioning
confidence: 99%
“…may have an obvious influence on the solid–liquid two-phase flow simulation. Through literature research, it was found that the drag force plays the leading role among interphase forces when ρ s /ρ l > 2, and other forces can be neglected. , The coefficient of momentum exchange was computed by using the Gidaspow model. …”
Section: Numerical Methodologymentioning
confidence: 99%
“…The E–E method treats the solid particle mathematically as a continuous phase considering the interpenetration and interaction of the solid and liquid phases [ 41 ]. This method has been widely employed by scholars due to the relatively low requirements of computing resources and it was validated by comparing the computational results to the experimental results [ 10 , 30 , 42 , 43 ]. Turbulence effects are important for solid-liquid mixing processes and need to be considered in the creating of mathematical models.…”
Section: Introductionmentioning
confidence: 99%
“…Siddiqui et al [ 44 ] also demonstrated the RNG k–ε model can fairly predict the velocity contours and streamlines. Based on the E–E model along with the RNG k–ε turbulence model, scholars have conducted multiple verification work by comparing the simulation data with the experimental results and a large amount of work on multiphase mixing operations ([ 30 , 43 ]).…”
Section: Introductionmentioning
confidence: 99%