Numerical study on the effect of airflow on powder mixing in a container blender

Abstract

Powder mixing is critical in many industries. Despite the wide variety of available mixers, the container blender is favored in industries due to easy manufacturing and convenient operation. As fine powders are frequently encountered in practical mixing, the presence of air during mixing may significantly impact the process. However, a scientific understanding of air–particle interactions in powder mixing has not been established so far. From a physical view, the air drag force on particles might be significant when the gas velocity is high and the particles are fine. Therefore, this novel study numerically investigates the effects of particle size and air presence on powder mixing under typical conditions, such that the relationship between particle–fluid dynamics and mixing performance is clarified for the first time. In the calculation, our advanced computational fluid dynamics–discrete element method, namely, the flexible Eulerian–Lagrangian method with an implicit algorithm, is utilized. To examine the effect of particle size on powder mixing, the coarse-grained discrete element method is employed for fine particle systems. Through the advanced numerical framework, the effect of airflow on powder mixing can be discussed in depth. The numerical results show that airflow accelerates the mixing of fine particles under the investigated rotation speeds. Based on the calculation results of the particle kinetics and fluid velocity distribution, it is clarified that the accelerated mixing results from the fine particle movement under air entrainment. How the movement of fine particles is developed is also elucidated by the continuously circulating gas flow and fluid drag force. Thus, this study provides a new understanding of the effects of airflow on powder mixing, which has not been scientifically clarified in previous studies.

Large-Scale Discrete Element Modeling for a Gas–Solid–Liquid Flow System

“…The drag force model plays an essential role in the DEM-CFD simulations . Adequacy of the employed drag force model, namely eqs to , has been thoroughly validated in various systems, such as fluidized bed, die filling, , and container blenders . Additionally, several drag force models − have been proposed as the coarse-grid DEM-CFD method, which can account for the effects of unresolved subgrid scale structures.…”

“…The wall boundary for the fluid phase simulation is realized by the immersed boundary model (IBM). ,,, Here, the volume fraction of the solid wall object should be introduced to represent the wall boundary. In the IBM, the local volume-weighted average velocity is calculated by u = false( 1 − α normalw false) u f + α w U w where α w and U w are the volume fraction of wall and the wall velocity, respectively.…”

“…The wall boundary for the fluid phase simulation is realized by the immersed boundary model (IBM). 34,35,50,51 Here, the volume fraction of the solid wall object should be introduced to represent the wall boundary. In the IBM, the local volume-weighted average velocity is calculated by…”

Optimization of ship hull forms by changing CM and CB coefficients to obtain optimal seakeeping performance

“…The encounter frequency will alter with the heading angles as the ship moves across the waves. The link between the encounter frequency and the wave frequency is as follows because the wave spectral density function at the encounter frequency and the wave spectral density function at the wave frequency have the same amount of energy [ 76 ]: …”

“…Hence, the represents the RMS motion, and the significant motion amplitude is twice the RMS motion. In addition, the RMS velocity and acceleration are given by and [ 76 ].…”