Abstract
The dynamics of hydrocyclones is complex, because it is a multiphase flow problem that involves interaction between a discrete phase and multiple continuum phases. The performance of hydrocyclones is evaluated by using Computational Fluid Dynamics (CFD), and it is characterized by the pressure drop, split water ratio, and particle collection efficiency. In this paper, a computational model to improve and evaluate hydrocyclone performance is proposed. Four known computational turbulence models (renormalization group (RNG) k- ε , Reynolds stress model (RSM), and large-eddy simulation (LES)) are implemented, and the accuracy of each for predicting the hydrocyclone behavior is assessed. Four hydrocyclone configurations were analyzed using the RSM model. By analyzing the streamlines resulting from those simulations, it was found that the formation of some vortices and saddle points affect the separation efficiency. Furthermore, the effects of inlet width, cone length, and vortex finder diameter were found to be significant. The cut-size diameter was decreased by 33% compared to the Hsieh experimental hydrocyclone. An increase in the pressure drop leads to high values of cut-size and classification sharpness. If the pressure drop increases to twice its original value, the cut-size and the sharpness of classification are reduced to less than 63% and 55% of their initial values, respectively.
Highlights
This factor is correlated with the collection efficiency, which indicates the number of particles that move toward the underflow
This study showed that increasing the size of the vortex finder leads to a decrease in separation efficiency as well as an increase in pressure drop
It was found that Reynoldsstress stressmodel model frequently (RSM) can reproduce most of the flow patterns of the continuous phase at a relatively low computational cost
Summary
Some advantages of these devices are the low operation and maintenance cost and no moving parts. The cut size is defined as the size at which a particle has a 50% probability of leaving the hydrocyclone through either the underflow or overflow This factor is correlated with the collection efficiency, which indicates the number of particles that move toward the underflow. Another critical factor is the pressure drop, which is an indicator of how much energy the hydrocyclone wastes, as a measure of the main system’s loss
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
