(479d) The Effect of Rpm and Particle Number on the Solid-Liquid Mixing Tank Performance: Application of CFD-DEM and ERT Experimental Measurements

Solid-liquid mixing tanks are widely employed in various industries including chemical, food, pharmaceutical and mining [1]. A CFD-DEM study of these unit operations has rarely been reported in literature and the majority of research has been conducted experimentally due to the complexity of the mixing tanks.

In the current study, a two-way coupled computational fluid dynamics (CFD) and discrete element method (DEM) model was developed using EDEM, a DEM code, and FLUENT, a CFD code. The locally averaged Navier-Stokes equations were solved in the CFD solver in order to simulate the liquid flow. The motion of particles in the mixing tank was tracked by solving Newton’s second law of motion in the EDEM software. The two software were then fully coupled through the momentum transfer between phases [2]. In order to validate the CFD-DEM model, a set of experimental data was collected by employing an Electrical Resistance Tomography (ERT) system. The particle volume fractions at three different surface planes (i.e. 0.045, 0.09 and 0.18 m from the bottom of the mixing tank) were measured experimentally and compared to the simulation results in order to evaluate the model accuracy. In both CFD-DEM simulations and experiments, spherical glass beads with a density of 2500 kg/m³ and a diameter of 0.002 m were used. The number of particles was 50,000 and the impeller RPM was set at 650. The mixing tank internal diameter and height were 0.25 and 0.4 m, respectively. The mixing tank was filled with water with an initial liquid height of 0.3 m. It was equipped with a pitched blade impeller with a 45^áµ’ angle and four baffles in order to prevent the vortex formation. The mixing tank was made of clear PVC.

The presence of liquid between particles and the geometry can drastically change the particle-geometry contact parameters. Therefore, in the first stage of this study the particle-geometry contact parameters (i.e. coefficient of restitution, coefficient of static friction and coefficient of rolling friction) were calibrated. The values of particle-particle contact parameters and the models of particle-fluid interaction forces (i.e. drag and lift force models) were selected based on our previous study on the CFD-DEM simulation of a mixing tank [3]. Through performing the calibration of particle-geometry contact parameters, a very close agreement between the CFD-DEM simulation results and the experimental measurements was obtained. The results proved that the CFD-DEM method can be used as a valuable tool to simulate the underlying phenomena occurring in a solid-liquid mixing tank.

The validated CFD-DEM model was then used to investigate the influence of operational parameters including the impeller RPM and particle number (i.e. particle volumetric concentration) on the mixing quality. The impeller RPM was varied from 400 to 700 with an increment of 50 for the particle number of 50,000. In addition, the particle number was varied from 25,000 to 100,000 with an increment of 25,000, while the RPM was fixed at 650 RPM. The maximum particle number in this study (i.e. 100,000) was selected to ensure a reasonable computational time. Various particle suspension regimes such as on-bottom motion, off-bottom (complete suspension) and uniform were recognized through the CFD-DEM simulations. Furthermore, the cloud height, power and homogeneity parameters were calculated for all simulation cases. Comparing these parameters enabled us to comprehensively analyze the influence of RPM and particle volumetric concentration on the mixing tank performance.

This research study demonstrated that a validated CFD-DEM model can be employed as a promising approach to design, analyze and optimize the solid-liquid mixing tanks.

References

[1] E.L. Paul, V.A. Atiemo-Obeng, S.M. Kresta, Handbook of industrial mixing: science and practice, John Wiley & Sons, 2004.

[2] M. Ebrahimi, CFD-DEM modelling of two-phase pneumatic conveying with experimental validation., The University of Edinburgh, 2014.

[3] M. Ebrahimi, A. Kazemzadeh, C. Tran, F. Ein‐Mozaffari, A. Lohi, The application of CFD-DEM and tomography to analyze the particle suspension in a solid-liquid mixing tank, in: XXIX Interam. Congr. Chem. Eng., Toronto, 2018.