2104 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
the feed size distributions for the two components similar.
For each test the samples collected from the overflow and
underflow streams of the hydrocyclone were analysed. The
product streams’ particle size distribution, solids, and water
recovery were used to calculate indices used to evaluate
the performance of the hydrocyclone for each component,
and the performance of the overall mixture was obtained
by reconstituting the individual component data by mass
balancing.
Multicomponent Numerical Experiments
The numerical modelling was performed to study the flow
behaviour to gain an understanding of the multicompo-
nent particle interaction during the classification process in
a hydrocyclone. The numerical simulations were performed
using the commercial package, ANSYS FLUENT with
additional user-defined functions to account the additional
forces at high solids loadings. The method used to set up
and perform the computational simulations was discussed
by Narasimha, 2010[16] and Vakamalla, 2016 [17]. The
numerical tests were set up to match the conditions that
were used in physical laboratory experiments performed
using magnetite and silica particles at varying proportions
of feed mixture. The deportment of different density com-
ponents from the numerical simulations was validated using
the corresponding experimental data from physical experi-
ments. To ensure the correctness of the physical properties
the viscosity model was modified to the multi-component
viscosity model developed for the bi-density and poly dis-
persed particles.
SLURRY PROPERTIES
Relative Slurry Viscosity
Slurry viscosity in a mixture is attributed to the hydrody-
namic particle interactions. As discussed earlier, the particle
size distribution, particle density, total solids concentra-
tions, and the proportion of the components in the mixture
affects the property of suspension. The non-Newtonian
behaviour of ore suspension in the similar range of shear
rate as the hydrocyclone (50–350 s–1) was considered to
develop the mixture relative viscosity model, presented in
Padhi et al., (2019) [5]. The solids concentration utilized
for the determination of the viscosity is in range of that
of hydrocyclone experiments. The effect of fines (F–38µ)
was incorporated using the Ishii &Mishima [15] model
Figure 1. Details of the hydrocyclone dimensions utilized for the experiments
Figure 2. Particle size distribution for magnetite and silica
the feed size distributions for the two components similar.
For each test the samples collected from the overflow and
underflow streams of the hydrocyclone were analysed. The
product streams’ particle size distribution, solids, and water
recovery were used to calculate indices used to evaluate
the performance of the hydrocyclone for each component,
and the performance of the overall mixture was obtained
by reconstituting the individual component data by mass
balancing.
Multicomponent Numerical Experiments
The numerical modelling was performed to study the flow
behaviour to gain an understanding of the multicompo-
nent particle interaction during the classification process in
a hydrocyclone. The numerical simulations were performed
using the commercial package, ANSYS FLUENT with
additional user-defined functions to account the additional
forces at high solids loadings. The method used to set up
and perform the computational simulations was discussed
by Narasimha, 2010[16] and Vakamalla, 2016 [17]. The
numerical tests were set up to match the conditions that
were used in physical laboratory experiments performed
using magnetite and silica particles at varying proportions
of feed mixture. The deportment of different density com-
ponents from the numerical simulations was validated using
the corresponding experimental data from physical experi-
ments. To ensure the correctness of the physical properties
the viscosity model was modified to the multi-component
viscosity model developed for the bi-density and poly dis-
persed particles.
SLURRY PROPERTIES
Relative Slurry Viscosity
Slurry viscosity in a mixture is attributed to the hydrody-
namic particle interactions. As discussed earlier, the particle
size distribution, particle density, total solids concentra-
tions, and the proportion of the components in the mixture
affects the property of suspension. The non-Newtonian
behaviour of ore suspension in the similar range of shear
rate as the hydrocyclone (50–350 s–1) was considered to
develop the mixture relative viscosity model, presented in
Padhi et al., (2019) [5]. The solids concentration utilized
for the determination of the viscosity is in range of that
of hydrocyclone experiments. The effect of fines (F–38µ)
was incorporated using the Ishii &Mishima [15] model
Figure 1. Details of the hydrocyclone dimensions utilized for the experiments
Figure 2. Particle size distribution for magnetite and silica