2444 XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3
The sensitivity analysis was performed using the pro-
cedure described in Figure 1. Figures 3 illustrates examples
of the successive model fitting, assuming the SFR model
of Equation (1). Figure 3(a) presents the baseline condi-
tion, without data removal. Figures 3(b), 3(c) and 3(d)
show 3 examples of model fitting after the removal of one
datapoint at a time, depicting the cases in which the first,
second and last datapoints were omitted in the model fit-
ting. Figure A1 of Appendix A presents the same examples
assuming the Gamma model of Equation (4).
Figure 4 presents the estimated f(k)s for the SFR
[Figure 4(a) and 4(b)], Rectangular [Figure 4(c) and 4(d)]
and Gamma [Figure 4(e) and 4(f)] models. The baseline f(k)
s are presented on the left, whereas the f(k)s obtained from
the sensitivity analysis are shown on the right (“Sens. n” in
the legend indicates that the n-th datapoint was omitted in
the parameter estimation). The SFR not only presented poor
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Data
SFR
Rectangular
Gamma
Figure 2. Kinetic response in the baseline condition, without
data removal
(a) (b)
(c) (d)
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
Figure 3. Examples of model fitting in the sensitivity analysis, using the Single Flotation Rate model: (a) model fitting with no
data removal (b) model fitting omitting the first datapoint (c) model fitting omitting the second datapoint (d) model fitting
omitting the last datapoint
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%
The sensitivity analysis was performed using the pro-
cedure described in Figure 1. Figures 3 illustrates examples
of the successive model fitting, assuming the SFR model
of Equation (1). Figure 3(a) presents the baseline condi-
tion, without data removal. Figures 3(b), 3(c) and 3(d)
show 3 examples of model fitting after the removal of one
datapoint at a time, depicting the cases in which the first,
second and last datapoints were omitted in the model fit-
ting. Figure A1 of Appendix A presents the same examples
assuming the Gamma model of Equation (4).
Figure 4 presents the estimated f(k)s for the SFR
[Figure 4(a) and 4(b)], Rectangular [Figure 4(c) and 4(d)]
and Gamma [Figure 4(e) and 4(f)] models. The baseline f(k)
s are presented on the left, whereas the f(k)s obtained from
the sensitivity analysis are shown on the right (“Sens. n” in
the legend indicates that the n-th datapoint was omitted in
the parameter estimation). The SFR not only presented poor
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Data
SFR
Rectangular
Gamma
Figure 2. Kinetic response in the baseline condition, without
data removal
(a) (b)
(c) (d)
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
0
10
20
30
40
50
60
70
80
90
100
0 4 8 12 16 20 24 28 32
Time, min
Regression Data
Omitted Datum
SFR Model
Figure 3. Examples of model fitting in the sensitivity analysis, using the Single Flotation Rate model: (a) model fitting with no
data removal (b) model fitting omitting the first datapoint (c) model fitting omitting the second datapoint (d) model fitting
omitting the last datapoint
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%
Cu
Recovery,
%