XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 2709
we have pursued the froth stability method mentioned in
6 above. In the current study, the froth stability is mea-
sured using a non-overflowing column by e method origi-
nally proposed by Bikerman (1973). Froth stability (Σ) is
measured as the change in maximum froth height (Hmax)
versus the change in superficial gas velocity (Jg) as shown in
Equation 3:
J
H
max
g
R =(3)
The effect of the froth stability on the froth recovery at par-
ticular froth retention times is investigated and explained
for two different ore types, an iron ore and copper-nickel
ore. The-values for the two ore types are determined and
explained with reference to the ore mineral composition.
The feasibility of this methodology to be used as a simple
means of estimating froth recovery for online process con-
trol is discussed.
EXPERIMENTAL
Results from two ore types are presented in this paper: a
Cu- and Ni-containing PGM ore, processed by direct flota-
tion, and an itabirite iron ore, processed by reverse flota-
tion. The details of the ore types are not of interest except in
so far as their ability to stabilise the froth phase. Parameters
that were varied in order to change froth characteristics
were the collector and depressant dosage for the Cu, Ni ore
and particle size for the iron ore.
Froth Stability and Metallurgical Tests
Froth stability and metallurgical tests were performed in the
same device shown in Figure 1. In moving from metallurgi-
cal test work to froth stability test work, the launder section
shown in (a), was simply replaced with a non-overflowing
column shown in (b). In this way, all other parameters such
as bubble size, energy input and cell configuration were
kept constant.
Froth Recovery by Variable Froth Depth Method
Froth recovery was measured using the method of Vera et
al., 2002, in which the froth depth is systematically var-
ied, metallurgical samples of feed, concentrate and tails are
collected, and the rate constant determined at each froth
depth. The rate constant was plotted against froth depth
and the resulting straight line was extrapolated to zero froth
depth, where the rate constant is equal to the pulp zone rate
constant, kc. At a given froth height, x, the rate constant is
kx and the froth recovery is given by (Dobby and Finch,
1991):
R k
k
f
c
x =(4)
RESULTS AND DISCUSSION
Froth recoveries were determined for 24 different condi-
tions of the reverse flotation of an itabirite iron ore. The
froth recoveries were determined using the variable froth
(a) (b)
Figure 1. Hybrid mechanical flotation cell with (a) overflowing launder for metallurgical tests
and (b) non-overflowing column for froth stability tests

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Extracted Text (may have errors)

XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 2709
we have pursued the froth stability method mentioned in
6 above. In the current study, the froth stability is mea-
sured using a non-overflowing column by e method origi-
nally proposed by Bikerman (1973). Froth stability (Σ) is
measured as the change in maximum froth height (Hmax)
versus the change in superficial gas velocity (Jg) as shown in
Equation 3:
J
H
max
g
R =(3)
The effect of the froth stability on the froth recovery at par-
ticular froth retention times is investigated and explained
for two different ore types, an iron ore and copper-nickel
ore. The-values for the two ore types are determined and
explained with reference to the ore mineral composition.
The feasibility of this methodology to be used as a simple
means of estimating froth recovery for online process con-
trol is discussed.
EXPERIMENTAL
Results from two ore types are presented in this paper: a
Cu- and Ni-containing PGM ore, processed by direct flota-
tion, and an itabirite iron ore, processed by reverse flota-
tion. The details of the ore types are not of interest except in
so far as their ability to stabilise the froth phase. Parameters
that were varied in order to change froth characteristics
were the collector and depressant dosage for the Cu, Ni ore
and particle size for the iron ore.
Froth Stability and Metallurgical Tests
Froth stability and metallurgical tests were performed in the
same device shown in Figure 1. In moving from metallurgi-
cal test work to froth stability test work, the launder section
shown in (a), was simply replaced with a non-overflowing
column shown in (b). In this way, all other parameters such
as bubble size, energy input and cell configuration were
kept constant.
Froth Recovery by Variable Froth Depth Method
Froth recovery was measured using the method of Vera et
al., 2002, in which the froth depth is systematically var-
ied, metallurgical samples of feed, concentrate and tails are
collected, and the rate constant determined at each froth
depth. The rate constant was plotted against froth depth
and the resulting straight line was extrapolated to zero froth
depth, where the rate constant is equal to the pulp zone rate
constant, kc. At a given froth height, x, the rate constant is
kx and the froth recovery is given by (Dobby and Finch,
1991):
R k
k
f
c
x =(4)
RESULTS AND DISCUSSION
Froth recoveries were determined for 24 different condi-
tions of the reverse flotation of an itabirite iron ore. The
froth recoveries were determined using the variable froth
(a) (b)
Figure 1. Hybrid mechanical flotation cell with (a) overflowing launder for metallurgical tests
and (b) non-overflowing column for froth stability tests

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2710 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
depth method as outlined in the experimental section.
These were then plotted against the froth retention time
(FRT) for each experimental condition (Figure 2). Froth
retention time, in its simplest form is calculated by dividing
the froth depth by the superficial gas velocity. In this case
FRT was varied by varying the froth depth. The superficial
gas velocity was maintained constant. Figure 2 shows that
there is considerable variation in the relationship between
froth recovery and froth retention time depending upon
the different conditions of pulp solids concentration and
amount of ultrafine material present. However, both of
these factors affect the froth stability. It is possible to have
different froth recoveries for the same froth retention time if
the froth stabilities are different. Consider a full-scale flota-
tion bank with all cells operating at the same conditions of
froth depth and superficial gas velocity. The froth recoveries
will be different for each cell, depending on the amount
and type of material that is being introduced to the froth.
To account for the effect of the froth stability on the
froth recovery, froth retention times were divided by the
froth stability. This resulted in the experimental data points
(from the iron ore example in Figure 2) falling onto a com-
mon line as shown in Figure 3 (grey squares). Equation 2
can be fitted to the data, which returns a beta value of 2.4.
A similar study was conducted using a copper- and
nickel-containing PGM ore. However, in this instance a
methodology was attempted to minimise the effort spent
on conducting time-consuming froth recovery tests. In this
case, only three froth recovery values were determined using
the variable froth depth method and these were plotted
against the froth retention time, corrected for froth stabil-
ity, as shown in Figure 3 (blue triangles, Cu, and orange
circles, Ni). Froth recovery and beta values for copper and
nickel were very similar, which lends credibility to the data
as one would expect froth characteristics to be the similar,
irrespective of pulp zone behaviour, particularly in an ore
that is strongly dominated by gangue flotation. The value of
beta for this ore was higher than for the iron ore. A higher
beta value implies a stronger dependence on the froth reten-
tion time and froth stability. That is, froth recovery will
decrease more quickly as the froth retention time increases
or froth stability decreases. This difference between these
two beta values is consistent with the fact that the iron ore
is a bulk float, with between 10% and 30% of the solids
mass being recovered to the concentrate, which stabilises
the froth, while the solids recovery in the Cu-Ni ore was
between 1% and 16%. Particle size and hydrophobicity
also play a role in determining the froth behaviours.
Figure 4 shows the data from the iron ore example
where froth recovery calculated using Equation 2 versus
the froth recovery measured using the method of variable
froth heights (Equation 4) for every condition. This shows
that there is reasonable correlation between them, with an
R2 of 0.67. This implies that a simple froth stability test
will give sufficient information to calculate froth recovery
as long as the measurement can be calibrated by the beta
value. Currently, this would need to be done by one of the
other methods of determining froth recovery, such as the
variable depth method. The benefit of being able to use a
froth stability measurement once it is calibrated, is the ease
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 20 40 60 80 100
FRT (s)
Figure 2. Froth recovery as a function of the froth retention time (FRT) for the reverse flotation
of an itabirite iron ore under varying conditions of fines contents and solids concentrations
Froth
recovery
(-)

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Extracted Text (may have errors)

2710 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
depth method as outlined in the experimental section.
These were then plotted against the froth retention time
(FRT) for each experimental condition (Figure 2). Froth
retention time, in its simplest form is calculated by dividing
the froth depth by the superficial gas velocity. In this case
FRT was varied by varying the froth depth. The superficial
gas velocity was maintained constant. Figure 2 shows that
there is considerable variation in the relationship between
froth recovery and froth retention time depending upon
the different conditions of pulp solids concentration and
amount of ultrafine material present. However, both of
these factors affect the froth stability. It is possible to have
different froth recoveries for the same froth retention time if
the froth stabilities are different. Consider a full-scale flota-
tion bank with all cells operating at the same conditions of
froth depth and superficial gas velocity. The froth recoveries
will be different for each cell, depending on the amount
and type of material that is being introduced to the froth.
To account for the effect of the froth stability on the
froth recovery, froth retention times were divided by the
froth stability. This resulted in the experimental data points
(from the iron ore example in Figure 2) falling onto a com-
mon line as shown in Figure 3 (grey squares). Equation 2
can be fitted to the data, which returns a beta value of 2.4.
A similar study was conducted using a copper- and
nickel-containing PGM ore. However, in this instance a
methodology was attempted to minimise the effort spent
on conducting time-consuming froth recovery tests. In this
case, only three froth recovery values were determined using
the variable froth depth method and these were plotted
against the froth retention time, corrected for froth stabil-
ity, as shown in Figure 3 (blue triangles, Cu, and orange
circles, Ni). Froth recovery and beta values for copper and
nickel were very similar, which lends credibility to the data
as one would expect froth characteristics to be the similar,
irrespective of pulp zone behaviour, particularly in an ore
that is strongly dominated by gangue flotation. The value of
beta for this ore was higher than for the iron ore. A higher
beta value implies a stronger dependence on the froth reten-
tion time and froth stability. That is, froth recovery will
decrease more quickly as the froth retention time increases
or froth stability decreases. This difference between these
two beta values is consistent with the fact that the iron ore
is a bulk float, with between 10% and 30% of the solids
mass being recovered to the concentrate, which stabilises
the froth, while the solids recovery in the Cu-Ni ore was
between 1% and 16%. Particle size and hydrophobicity
also play a role in determining the froth behaviours.
Figure 4 shows the data from the iron ore example
where froth recovery calculated using Equation 2 versus
the froth recovery measured using the method of variable
froth heights (Equation 4) for every condition. This shows
that there is reasonable correlation between them, with an
R2 of 0.67. This implies that a simple froth stability test
will give sufficient information to calculate froth recovery
as long as the measurement can be calibrated by the beta
value. Currently, this would need to be done by one of the
other methods of determining froth recovery, such as the
variable depth method. The benefit of being able to use a
froth stability measurement once it is calibrated, is the ease
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 20 40 60 80 100
FRT (s)
Figure 2. Froth recovery as a function of the froth retention time (FRT) for the reverse flotation
of an itabirite iron ore under varying conditions of fines contents and solids concentrations
Froth
recovery
(-)

2708
Exploring Froth Zone Performance in Flotation
Circuit Optimization
B. McFadzean, S. Geldenhuys, N. Buthelezi
Centre for Minerals Research, University of Cape Town, South Africa
N.P. Lima
Vale S.A., Av. Dr. Marco Paulo Simon Jardim, Bairro Piemonte, Nova Lima, Brasil
ABSTRACT: Quantifiable measurement of froth zone performance has posed persistent challenges for flotation
circuit optimization and modelling. While at the laboratory scale, the batch flotation cell has long served as
the conventional tool for flotation test work, it has obvious inherent issues when it comes to assessing froth
characteristics, including shallow froth depths and non-equilibrium froths. At full scale, various methods for
measuring froth recovery or using proxies have been employed, each yielding varying levels of success. This
paper explores simple and practical methods for estimating froth zone performance using examples from iron
and PGM ores.
INTRODUCTION
The measurement of froth recovery remains problematic
in flotation modelling. Most models of flotation perfor-
mance use some measure of froth zone performance and,
in most cases, this measure is the froth recovery. There have
been various methods attempted to measure froth recovery.
Some of these include:
1. Direct measurements of bubble load (Falutsu and
Dobby, 1992 Seaman et al., 2006 Yianatos et al.,
2008 Rahman et al., 2013),
2. Mass balance estimations of bubble load (Savassi
et al., 1997),
3. The method of varying froth depth (Feteris et al.,
1987 Vera et al., 1998),
4. Air recovery, which has been linked in various ways
to froth recovery (Neethling, 2008 Quintanilla et
al., 2021), and sometimes used directly as a froth
recovery measurement, which is questionable
(Oosthuizen et al., 2021),
5. Using froth retention time (FRT) as shown in
Equation 1, where β is an empirical fitting param-
eter (Gorain et al., 1998),
R e
f
FRTh =b- ^(1)
6. Using the froth retention time (FRT) modified
for some form of froth stability measurement as
shown in Equation 2, where t1/2 is the measured
froth half-life time (Tsatouhas et al., 2006 Zanin
et al., 2009).
R e /2
f
t1
FRT =b- `j (2)
In the current paper, the objective is to use the simplest and
easiest of methods to measure froth recovery and, therefore,

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Extracted Text (may have errors)

2708
Exploring Froth Zone Performance in Flotation
Circuit Optimization
B. McFadzean, S. Geldenhuys, N. Buthelezi
Centre for Minerals Research, University of Cape Town, South Africa
N.P. Lima
Vale S.A., Av. Dr. Marco Paulo Simon Jardim, Bairro Piemonte, Nova Lima, Brasil
ABSTRACT: Quantifiable measurement of froth zone performance has posed persistent challenges for flotation
circuit optimization and modelling. While at the laboratory scale, the batch flotation cell has long served as
the conventional tool for flotation test work, it has obvious inherent issues when it comes to assessing froth
characteristics, including shallow froth depths and non-equilibrium froths. At full scale, various methods for
measuring froth recovery or using proxies have been employed, each yielding varying levels of success. This
paper explores simple and practical methods for estimating froth zone performance using examples from iron
and PGM ores.
INTRODUCTION
The measurement of froth recovery remains problematic
in flotation modelling. Most models of flotation perfor-
mance use some measure of froth zone performance and,
in most cases, this measure is the froth recovery. There have
been various methods attempted to measure froth recovery.
Some of these include:
1. Direct measurements of bubble load (Falutsu and
Dobby, 1992 Seaman et al., 2006 Yianatos et al.,
2008 Rahman et al., 2013),
2. Mass balance estimations of bubble load (Savassi
et al., 1997),
3. The method of varying froth depth (Feteris et al.,
1987 Vera et al., 1998),
4. Air recovery, which has been linked in various ways
to froth recovery (Neethling, 2008 Quintanilla et
al., 2021), and sometimes used directly as a froth
recovery measurement, which is questionable
(Oosthuizen et al., 2021),
5. Using froth retention time (FRT) as shown in
Equation 1, where β is an empirical fitting param-
eter (Gorain et al., 1998),
R e
f
FRTh =b- ^(1)
6. Using the froth retention time (FRT) modified
for some form of froth stability measurement as
shown in Equation 2, where t1/2 is the measured
froth half-life time (Tsatouhas et al., 2006 Zanin
et al., 2009).
R e /2
f
t1
FRT =b- `j (2)
In the current paper, the objective is to use the simplest and
easiest of methods to measure froth recovery and, therefore,