Multiphase Flow Characteristics in the Classification Process of a Novel Wide Neck Thickener: Experiment and Simulation

Abstract

A novel thickening equipment known as a wide neck thickener (WNT) was designed to solve the problem of depending only on gravity settlement of the thickener. The computational fluid dynamics method with the Reynolds stress and the volume of fluid models and the particle image velocimetry experimental method were both applied to investigate the pressure and velocity variation and turbulent characteristics of the WNT under different parameter settings. The results indicate that experiments and simulations are consistent. Under four parameter settings, the axial and tangential velocities decrease to the minimum and then increase from the wall to the center. Under different feed velocity, cone angle, and spigot diameter settings, turbulent kinetic energy k and intensity I decrease from the cylinder to the cone and from the wall to the center; the max k and I correspond to the area near the inlet followed by the cylinder, and k and I in the cone are the smallest. When the classification overflow outlet (COO) diameter is 200 mm, k and I increase rapidly, the max k and I are transferred from near the inlet to near the cylinder wall at the COO, and the k and I near the wall decrease significantly.

Study on the Classification Performance of a Novel Wide-Neck Classifier

“…The VOF model was used to characterize the liquid–gas two phase using water and air in WNC. 1 ρ q [ ∂ ∂ t false( α q ρ q false) + ∇ · false( α q ρ q u⃗ q false) ] = prefix∑ p = 1 n ( m italicpq . − m italicpq . ) ∑ q = 1 n α q = 1 ∂ ∂ t ( ρ v⃗ ) + ∇ · ( ρ v⃗ v⃗ ) = prefix− ∇ p + μ ( ∇ v⃗ + ∇ v⃗ T ) + ρ g⃗ + F⃗ where α q is the volume fraction of phase q in the computing cell, m pq . ( m italicqp . ) indicates the mass transfer from phase p ( q ) to phase q ( p ), u⃗ q and v⃗ are the velocity vectors, ρ q is the density of phase q , ∇ represents the Hamiltonian, p denotes the fluid pressure, and F⃗ denotes the Saffman lift force, virtual mass f...…”

“…The volume of fluid (VOF) and the Reynolds stress model (RSM) were used to calculate the flow field of WNC. The SIMPLEC scheme was adopted for the The VOF model 37 was used to characterize the liquid−gas two phase using water and air in WNC.…”

“…Particle classification plays an important role in mineral separation, of which the particle density and size are decisive properties. , Thickener and hydrocyclones are two classical separators of mineral particles. The thickener classifies particles in the gravitational field, while the hydrocyclone classifies particles in the centrifugal field. − In mineral preparation plants, the thickener occupies a large space and classifies particles at a slow rate, − but it presents a large throughput. , Hydrocyclone is an efficient classifier for particles; − however, the efficiency is sensitive to the operating and structural parameters …”

“…11,12 Hydrocyclone is an efficient classifier for particles; 13−16 however, the efficiency is sensitive to the operating and structural parameters. 17 The sensitivity of the classification efficiency of hydrocyclones to operational and structural parameters has been extensively studied by predecessors. The dewatering rate of overflow and the deoiling rate of underflow were found to be sensitively affected by changing the swill chamber and overflow pipe diameters.…”

“… 11 , 12 Hydrocyclone is an efficient classifier for particles; 13 − 16 however, the efficiency is sensitive to the operating and structural parameters. 17 …”