920 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
the slurry directly passes through the rougher and rougher/
scavenger stages which should have a greater influence on
dissolved component build-up than cleaner section tail
contribution.
Even though dissolution and flotation occur concur-
rently, the model considers dissolution followed by flota-
tion. The dissolution model uses the same residence time
distribution than for flotation with the same size (number
of banks, number of cells per bank and cell volume). By
doing so, it is assumed that the composition of water in the
whole flotation bank is the one of its outputs, concentrate
and tailings, even though it is not entirely true for a bank
of several cells, because of the increase in concentration in
the solution and the decrease in mean residence time from
one cell to the next.
As full water recycling is not possible, water intake
from other source than flotation circuit itself is mandatory.
In the studied case, process water recirculated from tailings
is considered. The simulation series carried out with this
structure aimed at assessing the impact of the S/L separa-
tion rate from Cu circuit tailings on the potential reachable
recirculation ratio and the obtained pseudo equilibrium
sulfate concentration. Liquid output of the S/L separation
is fully recirculated at grinding/flotation input. The amount
of required additional process water is adapted to match the
complement and maintain the %-solids in flotation feed.
The impact of these recirculation is then assessed by
integrating the semi-empiric laws of flotation. The flotation
modelling is based on the first order kinetic model with two
populations of particles: floating particles with a propor-
tion of R∞
and no-floating particles: Based on the experimental results obtained on batch
flotation test series (Le et al., 2020), the impact of water
quality is a variation of the kinetic constant depending on
the concentration of the water components. For the sake
of simplicity, only the sulphate, magnesium, calcium and
residual reagent concentrations are considered for this
study, with linear dependance over a relative concentration
compared to a reference concentration (taken as the one of
PW):
k c c
cMg
c
cCollector
Cu SO
ref
ref
Ca
ref
0
4
4 4
4
=+
+
+
+
e
f
e
e
o
p
o
o
6Ca
6Mg
6SO
6Ca@ref
6Mg@
6Collector@-6Collector@
6SO
6Collector@ref
@-6Ca@ref
@-6Mg@
@-6SO
@ref
@ref
Figure 5 .Simulation flowsheet of Cu circuit including dissolution and water recycling without treatment
the slurry directly passes through the rougher and rougher/
scavenger stages which should have a greater influence on
dissolved component build-up than cleaner section tail
contribution.
Even though dissolution and flotation occur concur-
rently, the model considers dissolution followed by flota-
tion. The dissolution model uses the same residence time
distribution than for flotation with the same size (number
of banks, number of cells per bank and cell volume). By
doing so, it is assumed that the composition of water in the
whole flotation bank is the one of its outputs, concentrate
and tailings, even though it is not entirely true for a bank
of several cells, because of the increase in concentration in
the solution and the decrease in mean residence time from
one cell to the next.
As full water recycling is not possible, water intake
from other source than flotation circuit itself is mandatory.
In the studied case, process water recirculated from tailings
is considered. The simulation series carried out with this
structure aimed at assessing the impact of the S/L separa-
tion rate from Cu circuit tailings on the potential reachable
recirculation ratio and the obtained pseudo equilibrium
sulfate concentration. Liquid output of the S/L separation
is fully recirculated at grinding/flotation input. The amount
of required additional process water is adapted to match the
complement and maintain the %-solids in flotation feed.
The impact of these recirculation is then assessed by
integrating the semi-empiric laws of flotation. The flotation
modelling is based on the first order kinetic model with two
populations of particles: floating particles with a propor-
tion of R∞
and no-floating particles: Based on the experimental results obtained on batch
flotation test series (Le et al., 2020), the impact of water
quality is a variation of the kinetic constant depending on
the concentration of the water components. For the sake
of simplicity, only the sulphate, magnesium, calcium and
residual reagent concentrations are considered for this
study, with linear dependance over a relative concentration
compared to a reference concentration (taken as the one of
PW):
k c c
cMg
c
cCollector
Cu SO
ref
ref
Ca
ref
0
4
4 4
4
=+
+
+
+
e
f
e
e
o
p
o
o
6Ca
6Mg
6SO
6Ca@ref
6Mg@
6Collector@-6Collector@
6SO
6Collector@ref
@-6Ca@ref
@-6Mg@
@-6SO
@ref
@ref
Figure 5 .Simulation flowsheet of Cu circuit including dissolution and water recycling without treatment