XXXI International Mineral Processing Congress 2024 Proceedings/Washington, DC/Sep 29–Oct 3 717
high molecular weight organic polyacrylamide polymers,
showing improved flocculation properties. Anionic floccu-
lants proved superior to neutral or cationic counterparts.
Combining polymers yielded enhanced results (W. E.
Pittman, Jr., 1983). Another study on acrylamide polymer
(NALCO 7877) for 3%wt phosphatic clay slurry demon-
strated a two to threefold increase in initial settling rates
with flocculant addition. Higher plasticity clays required
proportionally higher doses for optimal performance,
reaching 0.27 kg/tds for low-plasticity and 1.09 kg/tds for
high-plasticity clays. Exceeding optimal doses reduced set-
tling rates (Ardaman &Associates, 1985), while lower ini-
tial solid content increased ISRs significantly (Ardaman &
Associates, 1985).
Considering all the examined parameters, the anionic
flocculant Magnafloc 5250 emerges as the most favourable
polymer, offering a balanced performance across ISR, water
recovery, and recycled water turbidity compared to other
tested flocculants. The supernatant exhibited a turbidity
of 2.08 ± 0.04 NTU, an initial settling rate of 13.67 cm/
min, a water recovery of 83.20%, and a final solid con-
tent of 35.58%. Magnafloc 5250 also resulted in a super-
natant with low electrical conductivity and total dissolved
solids (512 µS/cm and 368 ppm). When employing the
Magnafloc 5250, the formation of medium and large
floc sizes is observed. This observation can be attributed
to the electrostatic repulsion between the COO− groups
in the anionic flocculant and the negatively charged slip-
ping plane of the FPTs particles. This interaction results
in the formation and creation of fragile and large flocs,
allowing faster settling compared to the cationic polyacryl-
amides (Bahmani-Ghaedi et al., 2022 Liu et al., 2020).
Identifying Magnafloc 5250 as the most promising floccu-
lant, the study now employs a comprehensive experimental
design to delve into the factors influencing FPTs floccula-
tion. Focusing on dose, pH, and mixing rate, the research
aims to understand their individual and combined impacts
on process efficiency. The investigation anticipates yielding
insights for optimizing tailings management, ensuring a
sustainable approach to managing FPTs.
Response Surface Analysis
The influence of flocculant dosage, pH and mixing rate on
the flocculation and sedimentation performance was stud-
ied and the design matrix showing the full results from the
experimental study and that predicted using the regression
model are shown in Table 5.
Multiple regression analyses and ANOVA for Initial
Settling Rate (ISR), Water Recovery (WR), and water
turbidity were performed, and the results are presented in
Table 6. The ANOVA analysis revealed that the models for
the three studied responses exhibited a P-value of 0.0001,
which is less than 0.05, indicating a high level of signifi-
cance for the obtained models. The R2 values for the models
Table 5. CCD: experimental results for the studied responses
Std Run X1 (g/tds) X2 X3 (rpm) ISR (cm/min) W.R (%)Turbidity (NTU)
4 1 100 10 60 15.12 78.69 3.7
9 2 40 8 100 11.72 81.11 2.2
8 3 100 10 140 13.92 85.79 8.5
20 4 70 8 100 13.46 83.53 0.82
13 5 70 8 60 14.36 77.36 1.64
17 6 70 8 100 13.03 82.93 0.85
2 7 100 6 60 10.27 80.3 7.35
19 8 70 8 100 13.31 83.14 0.89
5 9 40 6 140 9.42 74.38 12.6
3 10 40 10 60 12.68 81.48 1.87
10 11 100 8 100 14.65 84.76 1.54
6 12 100 6 140 10.14 78.15 5.68
16 13 70 8 100 13.15 83.64 1.04
18 14 70 8 100 13.28 83.76 0.94
7 15 40 10 140 9.45 82.64 3.95
12 16 70 10 100 12.87 83.64 2.85
11 17 70 6 100 8.67 81.45 6.48
14 18 70 8 140 12.56 83.76 2.74
15 19 70 8 100 13.24 83.35 1.08
1 20 40 6 60 8.13 71.92 14.12
high molecular weight organic polyacrylamide polymers,
showing improved flocculation properties. Anionic floccu-
lants proved superior to neutral or cationic counterparts.
Combining polymers yielded enhanced results (W. E.
Pittman, Jr., 1983). Another study on acrylamide polymer
(NALCO 7877) for 3%wt phosphatic clay slurry demon-
strated a two to threefold increase in initial settling rates
with flocculant addition. Higher plasticity clays required
proportionally higher doses for optimal performance,
reaching 0.27 kg/tds for low-plasticity and 1.09 kg/tds for
high-plasticity clays. Exceeding optimal doses reduced set-
tling rates (Ardaman &Associates, 1985), while lower ini-
tial solid content increased ISRs significantly (Ardaman &
Associates, 1985).
Considering all the examined parameters, the anionic
flocculant Magnafloc 5250 emerges as the most favourable
polymer, offering a balanced performance across ISR, water
recovery, and recycled water turbidity compared to other
tested flocculants. The supernatant exhibited a turbidity
of 2.08 ± 0.04 NTU, an initial settling rate of 13.67 cm/
min, a water recovery of 83.20%, and a final solid con-
tent of 35.58%. Magnafloc 5250 also resulted in a super-
natant with low electrical conductivity and total dissolved
solids (512 µS/cm and 368 ppm). When employing the
Magnafloc 5250, the formation of medium and large
floc sizes is observed. This observation can be attributed
to the electrostatic repulsion between the COO− groups
in the anionic flocculant and the negatively charged slip-
ping plane of the FPTs particles. This interaction results
in the formation and creation of fragile and large flocs,
allowing faster settling compared to the cationic polyacryl-
amides (Bahmani-Ghaedi et al., 2022 Liu et al., 2020).
Identifying Magnafloc 5250 as the most promising floccu-
lant, the study now employs a comprehensive experimental
design to delve into the factors influencing FPTs floccula-
tion. Focusing on dose, pH, and mixing rate, the research
aims to understand their individual and combined impacts
on process efficiency. The investigation anticipates yielding
insights for optimizing tailings management, ensuring a
sustainable approach to managing FPTs.
Response Surface Analysis
The influence of flocculant dosage, pH and mixing rate on
the flocculation and sedimentation performance was stud-
ied and the design matrix showing the full results from the
experimental study and that predicted using the regression
model are shown in Table 5.
Multiple regression analyses and ANOVA for Initial
Settling Rate (ISR), Water Recovery (WR), and water
turbidity were performed, and the results are presented in
Table 6. The ANOVA analysis revealed that the models for
the three studied responses exhibited a P-value of 0.0001,
which is less than 0.05, indicating a high level of signifi-
cance for the obtained models. The R2 values for the models
Table 5. CCD: experimental results for the studied responses
Std Run X1 (g/tds) X2 X3 (rpm) ISR (cm/min) W.R (%)Turbidity (NTU)
4 1 100 10 60 15.12 78.69 3.7
9 2 40 8 100 11.72 81.11 2.2
8 3 100 10 140 13.92 85.79 8.5
20 4 70 8 100 13.46 83.53 0.82
13 5 70 8 60 14.36 77.36 1.64
17 6 70 8 100 13.03 82.93 0.85
2 7 100 6 60 10.27 80.3 7.35
19 8 70 8 100 13.31 83.14 0.89
5 9 40 6 140 9.42 74.38 12.6
3 10 40 10 60 12.68 81.48 1.87
10 11 100 8 100 14.65 84.76 1.54
6 12 100 6 140 10.14 78.15 5.68
16 13 70 8 100 13.15 83.64 1.04
18 14 70 8 100 13.28 83.76 0.94
7 15 40 10 140 9.45 82.64 3.95
12 16 70 10 100 12.87 83.64 2.85
11 17 70 6 100 8.67 81.45 6.48
14 18 70 8 140 12.56 83.76 2.74
15 19 70 8 100 13.24 83.35 1.08
1 20 40 6 60 8.13 71.92 14.12