XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 2449
Villeneuve, J., Guillaneau, J. C., &Durance, M. V. (1995).
Flotation modelling: A wide range of solutions for
solving industrial problems. Minerals Engineering,
409–420.
Vinnett, L., Yianatos, J. &Flores, S. (2016). On the min-
eral recovery estimation in Cu/Mo flotation plants.
Mining, Metallurgy &Exploration 33, 97–106.
Vinnett L, Waters K.E. (2020). Representation of Kinetics
Models in Batch Flotation as Distributed First-Order
Reactions. Minerals 10(10), 913.
Xiao, Z., Vien, A., (2004). Experimental designs for precise
parameter estimation for non-linear models. Minerals
Engineering 17, 431–436.
APPENDIX A
Figures A1 presents examples of the successive model fitting
in txhe sensitivity analysis, assuming the Gamma model of
Equation (4). Figure A1(a) shows the baseline condition,
using the entire dataset. Figures A1(b), A1(c) and A1(d)
present examples of model fitting after removing one data-
point at a time, as in Figure 3 for the SFR model.
(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
Gamma 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
Gamma 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
Gamma 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
Gamma Model
Figure A1. Examples of the procedure in the sensitivity analysis, using the Gamma 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,
%
Villeneuve, J., Guillaneau, J. C., &Durance, M. V. (1995).
Flotation modelling: A wide range of solutions for
solving industrial problems. Minerals Engineering,
409–420.
Vinnett, L., Yianatos, J. &Flores, S. (2016). On the min-
eral recovery estimation in Cu/Mo flotation plants.
Mining, Metallurgy &Exploration 33, 97–106.
Vinnett L, Waters K.E. (2020). Representation of Kinetics
Models in Batch Flotation as Distributed First-Order
Reactions. Minerals 10(10), 913.
Xiao, Z., Vien, A., (2004). Experimental designs for precise
parameter estimation for non-linear models. Minerals
Engineering 17, 431–436.
APPENDIX A
Figures A1 presents examples of the successive model fitting
in txhe sensitivity analysis, assuming the Gamma model of
Equation (4). Figure A1(a) shows the baseline condition,
using the entire dataset. Figures A1(b), A1(c) and A1(d)
present examples of model fitting after removing one data-
point at a time, as in Figure 3 for the SFR model.
(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
Gamma 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
Gamma 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
Gamma 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
Gamma Model
Figure A1. Examples of the procedure in the sensitivity analysis, using the Gamma 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,
%