DEM study of the effect of blade-support spokes on mixing performance in a ribbon mixer

Abstract

Simulations based on Discrete Element Method3 (DEM) are carried out to investigate the effect of blade-supporting spokes of the impeller on overall mixing performance in a ribbon mixer. The influences of some key variables are studied, which include spoke number, particle cohesiveness and fill-level. The overall mixing performance is mainly assessed using the Lacey's mixing index based on the coordination number. The axial velocity variation, axial diffusion coefficient, and contact forces are also analysed to depict the effect of spokes on the mixing. It is found that for non-cohesive particles, increasing the number of spokes is favourable for achieving faster overall mixing when the fill level is large. But this comes at the expense of increased contact forces. It is also found that particle dispersion due to axial velocity fluctuations plays a major role in mixing of non-cohesive particles, but not the axial diffusion. For cohesive particles, no-spokes impeller shows the best overall mixing performance. The effect of spokes on the overall mixing performance is complex and depends on the fill level. At higher fill-levels, the mixing curves are relatively less affected by the number of spokes, while at lower fill-levels, mixing is delayed extensively for 2 and 6 spokes impellers, but the 4-spokes impeller shows some recovery of mixing performance towards that of no-spoke impeller. At low fill-levels, axial diffusion is a governing factor of the mixer performance. Conversely, at high fill-levels, particle dispersion due to the velocity fluctuations become the dominant mixing mechanism for all types of impellers considered. Generally, adding spokes to impellers causes only a slight increase in the contact forces between particles when mixing cohesive particles but a very significant increase in the contact forces when mixing non-cohesive particles. The results indicate that the attached parts in the impeller should be optimized under different operational conditions, which can be guided by DEM simulations.