CFD modelling of particle classification in mini-hydrocyclones

摘要

This work presents validated Computational Fluid Dynamics (CFD) predictions of the effect that changes in vortex finder and spigot diameters have on the classification performance of mini-hydrocyclones. Mini-hydrocyclones (e.g. 10 mm in diameter) have been applied successfully to the separation of micron-sized particles since their bypass fraction is larger than the water recovery, which results in a high particle recovery to the underflow, as well as low water recovery. However, a larger bypass fraction can be a disadvantage when the purpose of the hydrocyclone is particle classification, because of the large amount of fine particles that are misplaced in the underflow. Although it is well known that changes in the outlets of the hydrocyclone affect its performance, there is limited research on the effect of these design parameters in mini-hydro cyclones, in particular with regard to particle classification. The aim of this study is to computationally explore the influence of spigot and vortex finder on the classification process. To this end, CFD simulations were carried out and the predictions experimentally validated in a 3D printed mini-hydrocyclone using glass beads (below 20 mu m) as the particulate system. The numerical results showed very good agreement with the experimental data for recovery of solids, concentration ratio, pressure drop and particle size distribution. A trade-off was observed between the solids recovery and concentration ratio, while the solids recovery was found to be inversely proportional to the pressure drop when vortex finder diameters were kept constant. It was found that the design that yielded the lowest recovery among those tested also resulted in a particle size distribution furthest away from that of the feed. We show how the model can be used to assess changes in design parameters in order to inform the selection of designs that exhibit lower energy requirements without compromising separation performance.