Study on Internal Flow Characteristics of Hydrocyclone with Guide Vanes

Abstract

Hydrocyclone with guide vanes is one type of swirl flow launching device without energy input. For researching the flow characteristics of that hydrocyclone, the flow distribution of the sections and their variation along the flow were studied using numerical simulation and physical experiment. In addition, the flow field was convenient to be divided into three-dimensional velocities: axial velocity, circumferential velocity, radial velocity and the static pressure. The result showed that the water flow had obvious diversion by the effect of guide vanes. The axial velocity varied into the distribution of higher values emerging away from the pipe wall and the surfaces of guide vanes, and the value was higher on downstream surfaces than upstream surfaces of the guide vanes. The radial velocity’s direction pointed at the axis of pipe on upstream surfaces, and pointed at the pipe wall on the downstream surfaces of the guide vanes; the influenced range was larger in sections along the flow. The circumferential velocity increased along the flow, closing the distorted guide vanes; the value of that velocity was larger closer to the guide vanes, especially the downstream surfaces of the guide vanes. The static pressure decreased along the flow, and the value was larger on the upstream surfaces than the downstream surfaces of the guide vanes. The results can provide some theory references to improve the construction of the hydrocyclone.

Designing the Spigot Structure of Hydrocyclones to Reduce Fine Particle Misplacement in Underflow

“…The CFD method has been extensively applied to the optimization design of hydrocyclones to study internal flow fields and particle micromotion characteristics, with the advantages of accuracy, high efficiency, and short duration [32,33]. For the numerical simulation of hydrocyclones, multiphase models commonly utilize the VOF model, mixture model, and Eulerian model, while turbulence models include RSM and LES models; the DPM is used to track particle trajectories [34][35][36]. Durango-Cogollo et al [37] reported that the RSM and LES models have higher computational accuracy than the k-ε model, but the RSM has faster computational efficiency and lower mesh quality requirements.…”