The movement of particles inside a jig ultimately determines the efficiency of the jig. The movement
of these particles is a function of the particle properties (size, density and shape) and the jigging
parameters (pulse shape, water flow, etc.). The purpose of this study was to investigate how particle
properties affect the movement of particles inside a jig.
Positron Emission Particle Tracking (PEPT) is one of the few techniques that can trace the
movement of particles inside an enclosed system without interfering with the particle flow and has
successfully been used to study mills, hydrocyclones and flotation. In this study, PEPT was evaluated
as a possible technique to study the flow of iron ore particles inside a laboratory scale jig. The results
showed that very accurate three dimensional trajectories could be obtained, with a temporal
resolution high enough to see the movement of a particle during a single pulse.
The vertical component from the trajectories showed the rate at which particles moved through the jig
bed (stratification rate). The particle property that affected the stratification rate the most was density,
followed by size. Shape didn't have a large influence on the stratification rate. However, it was
evident that the flat particles have a slightly higher rate, compared to cubic and elongated particles.
The PEPT testwork showed the existence of a circular flow pattern (secondary flow) that emerged
inside the batch jig. Throughout the test results, the effects of the secondary flow pattern on the
movement of the tracer particles was observed. It was seen that particles with densities close to that
of the jigging bed were affected the most and that some of these particles showed no degree of
stratification .A possible origin of this secondary flow can be the uneven water velocity under the jig
bed. The uneven velocity profile was confirmed by looking at the difference in pulse height at different
position in the jig bed, with the help of PEPT.
None of the existing jigging models in literature take into account this back mixing caused by the
secondary flow. An attempt was made to add this effect to King's potential energy model to improve
its accuracy with regards to iron ore jigging. From the PEPT observations, the assumption was made
that the back mixing experienced by a particle is related to the difference between the mass of the
tracer particle and the average particle mass inside the jig. Simulated stratification profiles generated
with the modified stratification model were compared to published data of batch iron ore jigging and
showed better correlation compared to the standard model.
Dissertation (MEng)--University of Pretoria, 2017.