- Email: [email protected]
Troubleshooting and Diagnostic of Industrial Flotation Cells
Troubleshooting and Diagnostic of Industrial Flotation Cells J.B. Yianatos, L.G. Bergh and F. Díaz*
Automation and Supervision Centre for Mining Industry, CASIM Santa María University, Valparaíso, Chile, (e-mail: [email protected]). * Chilean Commission of Nuclear Energy, Nuclear Applications Department La Reina, Santiago, Chile Abstract: The residence time distribution of liquid, gas and solid per size class was measured in large flotation cells in different flotation plants. The RTD measurement was developed using radioactive tracers. Results allowed the estimation of effective pulp volumes of 82-85% of the total nominal volume in large flotation cells. It was found that single large industrial flotation cells have different flow regimes and can be significantly different from a perfect mixer (N>1 or N<1). Measurement of RTD also allowed the identification of operating control problems such as solid segregation (affecting the mean residence time for kinetic modeling), cells embankment, and increasing short-circuit because of cell design characteristics and circuit arrangement (i.e. input-output location ). Measurement of local superficial gas rate and improved measurement of bubble size distribution, using new software, allowed the estimation of the bubble surface area flux (SB around 40s-1), key parameter describing the quality (level) of gas dispersion in industrial flotation cells. Also, typical boundaries for superficial gas rate (1-2 cm/s) and mean bubble size (1-2mm) have been identified for stable flotation operation from different plant experiences. Bubble load measurement was carried out for estimating the froth recovery in large flotation cells. Froth recovery is relevant for flotation process modeling and control because of the critical role the froth transport plays in large cells. Recent development on automated froth visual analysis (i.e., bubble size, bubble collapse and froth overflow velocity) poses new challenges to link this information with the actual internal process variables (i.e. froth recovery). Keywords: froth flotation, RTD, radioactive tracer, flotation machines, modeling, troubleshooting
1. INTRODUCTION In the last years flotation equipment has increased dramatically in size together with the large increase in mineral processing by flotation. The largest flotation cells presently used in industrial flotation operations all over the world are 100, 130, 160 m3, and more recently have reached 250-300m3 per single cell. Improvements in simplicity (low number of cells), low specific energy consumption and less space have been in most cases the reasons for using these new designs. Industrial flotation cells need to accomplish several functions such as: air dispersion, solid suspension, bubble-particle collision and aggregate formation, as well as provide the best conditions for floatable mineral separation in the froth zone. For this reason, cells are typically provided with mechanical agitation systems which generate the required mixing conditions for pulp suspension and air dispersion in small bubbles. Also, cells are provided with a quiet zone in the upper part where a distinctive pulp-froth interface is created. Froth crowders and internal launders are typically used to improve the froth transport and recovery. Figure 1shows the main characteristics of a self-aerated cell, where the feed pulp circulates upwards through a draft tube by the rotor, while the air is self-aspirated from the top of the cell by the rotor.
AIR
FROTH CROWDER
CONCENTRATE
ROTOR FEED PULP CIRCULATION
FEED
PULP/FROTH INTERFACE
TAIL
Fig. 1 Large flotation cell In an industrial continuous flotation cell, the mixing condition prevents that particles have the same opportunity to be collected, because a significant fraction of them actually spent a very short time in the cell (in a well-mixed condition almost 40% of particles stay in the cell for less than a half of the mean residence time). Because of the large short circuit in single continuous cells, the industrial flotation circuits consider the arrangement of cells in banks. For example,
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
banks of 5-10 cells in series are commonly used in plant practice (Yianatos et al., 2008d).
interface level, sanding-up due to particle settling and other disturbing condition in the cell (Yianatos et al., 2008b).
Besides normal changes in feed grade and flowrate, and the need for periodic maintenance of instrumentation (level control, air flowrate) the following common troubles have been observed in plant practice,
1.2 Bubble load measurement and froth recovery estimation
x
Improper calibration and maintenance of instrumentation to measure froth depth and gas rate
x
Uneven pulp distribution in parallel lines (solid percentage, mass flowrate and grade)
x
Short-circuit in single cells
x
Embankment and by-pass flow in single cells
x
Uneven froth discharge (froth recovery)
x
Lack of robustness of control strategies
Other parameter which affects the plant stability is the feed solid percentage (25-40%) including the corresponding time delays (a typical condition is 38% solid). The flotation circuit takes long time for solid percentage stabilization. 1.1 Tracer technique In order to study the hydrodynamic behaviour of large flotation cells, the radioactive tracer technique has been used to measure the residence time distribution (RTD) of the liquid, solid and gas in industrial rougher flotation banks. For this purpose, a pneumatic system of high reliability was used in order to introduce a small amount of radioactive tracer (around 100 mL of liquid or pulp) at the feed pulp entrance. Then, the time response of the radioactive tracer was measured on-line, at different points along the bank, using non-invasive sensors located directly in the discharge pipe of each cell. Activity (cps) was measured by scintillating crystal sensors of NaI(Tl) of 1”x1.5”, Saphymo Srat, thus allowing the simultaneous data acquisition of up to 12 control points, with a minimum period of 50 milliseconds. Br-82 in solution was used as liquid tracer and Bromine Tri-Fluor-Methane (CF3Br), also called Freon 13B1, was used as gaseous tracer. Solid radioactive tracers were prepared by neutron activation in the 5 MW Nuclear Reactor of the Chilean Commission of Nuclear Energy. The solid tracer was tested at three size classes (coarse: +150, intermediate: -150+45 and, fine –45 microns) in order to evaluate solids segregation. An advantage of using the radioactive tracer technique is the direct testing of the actual solid particles (similar physical and chemical properties, size distribution, shape, etc.). Tracer injection is almost instantaneous because only a small amount of radioactive tracer is required. Another advantage is its capability for on-line measurement at various locations in the system without disturbances related to process sampling. Also a gamma ray scanning was performed in an industrial large cell using a neutron backscatter technique, across a vertical plane, to measure the relative density as a function of height. This technique was useful to identify pulp-froth
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
A special device for bubble load measurement has been used to estimate the amount of solid particles collected by true flotation (bubble-particle aggregates formation) that reaches the pulp-froth interface being transported along the froth into the concentrate. The bubble load measurement device also allows the local superficial gas rate measurement. This information and the mass balance are fundamental to estimate the froth recovery in large flotation cells (Yianatos et al., 2008c). 1.3 Bubble surface area flux SB The bubble surface area flux SB (s-1) is a hydrodynamic parameter which describes the level of the gas dispersion. SB = 6 JG/dB
(1)
where JG is the superficial gas rate (cm/s) and dB is the mean bubble diameter. In recent years the development of new instrumentation for local gas rate and bubble size distribution measurement has allowed the estimation of SB at industrial scale. For example, bubble size distribution has been measured in several flotation circuits using the McGill bubble size analyzer (Hernandez-Aguilar et al., 2002). Also, in order to improve the mean bubble size estimation in presence of large bubbles and/or bubble clusters, usually encountered in large cells, new software for semi-automated image analysis was recently developed (Vinnett et al., 2009). 2. EXPERIMENTAL 2.1 Pulp distribution in rougher flotation circuits In order to estimate the mean residence of minerals in industrial flotation circuits a common practice consists of estimating the volumetric flowrate of the feed pulp entering the rougher circuit. The volumetric flowrate can be estimated from the solids mass flowrate measurement, by weightmeters located at the grinding stage feed, and measurement of the solids percentage in the flotation feed pulp. However, in large rougher circuits there are three or more parallel flotation banks typically. For this reason, despite the normal errors in estimating the solid mass flowrate and pulp density, the feed volumetric flowrate estimation can be biased because of uneven feed pulp distribution. For process modelling and diagnosis, the actual distribution of the feed volumetric flowrate was measured in industrial rougher flotation circuits using the radioactive tracer technique. The experimental test consisted of the injection of a tracer signal at the common distribution box, and simultaneous on-line measurement of RTD in parallel flotation banks. The mean residence time for each flotation bank was then calculated by de-convolution between the input and output signals. The pulp distribution was calculated
considering the volumetric flowrate of each flotation bank proportional to the inverse of residence time. Using this approach it was found that the volumetric flowrate distribution in large size circuits can be significantly different. Table 1 shows the volumetric flowrate distribution evaluated in four industrial circuits. In circuit A, tests were performed only with liquid tracer, while circuits B, C and D were tested for liquid, and solids per size class, allowing the evaluation of the standard deviation. From these results
differences up to 15-20%, above or below the expected flowrate for even distribution, were found. This is a relevant point considering the impact these differences can have on process characterization (i.e. residence time and kinetics) and process automation (i.e. reagents addition control). Also, significant differences in mineral grade and solid percentage were found in feed samples taken from different parallel banks in the same circuit.
Table 1. Volumetric flowrate distribution in parallel rougher banks Circuit
Nº of banks
A B C D
4 3 3 3
Bank 1 % 24.5 31.6 ± 0.7 31.2 ± 2.3 33.6 ± 0.4
Bank 2 % 24.0 31.8 ± 0.5 29.2 ± 0.7 36.0
From direct measurement of effective residence time of liquid and solids per size class, in flotation cells and banks, it was possible to estimate the effective cell volume occupied by the pulp. Thus, under normal operating conditions, i.e. superficial gas rate JG=1.3-1.8 cm/s, dB=1.2-2.2mm and no embankment, the typical range of effective cell volume was 82-85% of the total nominal volume.
Bank 3 % 27.7 36.6 ± 0.6 39.6 ± 1.7 30.4 ± 0.1
Bank 4 % 23.8
Total Flow % 100 100 100 100
2.2 RTD of Flotation Banks The RTD was measured on-line in the tailings stream at different locations along the banks in different flotation circuits. For example, Figure 2 shows a circuit arrangement (1-2-2-2) consisting of seven 130m3 cells, the tracer injection point at the feed inlet and the sensors location along the bank.
CONCENTRATE E(t) W FEED
t
1 1
2 RTD CELL1
3
4 RTD
5
6 RTD
CELLS 1 to 3
CELLS 1 to 5
7
TAIL
RTD CELLS 1 to 7
Fig. 2 Tracer impulse test and sensors location in a flotation bank Figure 3 shows the liquid residence time distribution after 1, 3, 5 and 7 cells in the bank, where a significant decrease in the pulp short-circuit, by increasing the number of cells in the flotation bank, was observed. These results confirm that a minimum number of 4 or 5 cells per bank is recommended, to minimize the problem of short-circuit in flotation cells. Also, the continuous lines show a good agreement between the data points and a RTD model, typically represented by N perfect mixers in series (Mavros, 1992). The same procedure has been used to characterize the individual performance of each cell along the rougher flotation banks (Yianatos et al., 2008a).
2.3 Scale-up of RTD in large self-aerated mechanical cells Figure 4 shows experimental data and model fitting for RTD of single mechanical cells of 130 and 250m3 (Yianatos et al. 2008a). The comparison of both RTD shows that despite the increase in size, almost twice, the mixing conditions are similar, thus allowing for effective scale-up in terms of the hydrodynamic behaviour. Using the N cells model the equivalent number of perfect mixers for both flotation cells was NC approximately 1.4. Also, the good fit of a large and small tank in series model (LTST) is presented.
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
0.0035 0.0030
N=1
RTD, E(t)
0.0025
E(t )
t N 1 exp(tN / W ) (W / N ) N *( N )
Cells number 1 3 5 7
0.0020
N=3
0.0015
N=5
0.0010
N 1.3 3.1 4.9 6.8
N=7
0.0005 0.0000 0
500
1000
1500
2000
2500
3000
3500
4000
Time, s
Fig. 3
RTD in a flotation bank after 1, 3, 5 and 7 cells in series.
130 m3 250 m3
Figure 6 shows the liquid RTD in an industrial self-aerated cell of 130m3, located in the middle of a rougher bank, where an abnormal operating condition due to by-pass flow (shortcircuiting) was observed, mainly related to solid settling and pulp channelling (Yianatos et al., 2008a).
LTST Model
0.80
0.0028
0.60 0.40
By-pass flow model
0.0020
0.20 0.00 0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.0016 0.0012 0.0008
Dimensionless time, T
Fig. 4 RTD in 130 and 250m3 cells (Yianatos et al., 2008a).
0.0004 0.0000 0
2.4 RTD and by-pass flow in single cells
0,0060 Data LSTS Model SC Model E(t) Model
0,0050 0,0040 0,0030 0,0020 0,0010 0,0000 0
300
600
200
400
600
800
1000
1200
1400
1600
time, s
Figure 5 shows the solid RTD measured in a large cell of different design, where the rotor is located near the bottom. In this case the residence time distribution was equivalent to less than one perfect mixer (NC<1). This operation showed the presence of a larger short circuit which was augmented because of the discharge orientation (less than 180º relative to the cell input) due to space constraints. The model adjustment, considering a mixing component model (LSTS) plus a by-pass fraction (short-circuiting SC model), allowed the estimation of a by-pass flow fraction around 10%.
RTD
Data cell 3
0.0024
RTD
Dimensionless RTD, E(T)
1.00
These results are in good agreement with previous simulations for this kind of cells (50-160m3) derived from the combined use of CFD and DEM, where the by-pass flow of particles (50-300 microns) was reported in the range 2-20%, mainly depending on particle size, inlet velocity and discharge orientation (Lichter et al., 2007). Despite the important simplifications of the CFD simulation, such as the exclusion of air from the slurry system, the CFD technique has a very good potential to provide a detailed insight on how specific design parameters would impact the performance of the flotation cell.
900
1200
1500
Time, s
Fig. 5 Liquid RTD model with by-pass flow in a large cell
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
Fig. 6
Liquid RTD in an industrial cell showing by-pass flow
Figure 6 also shows the fitting of a RTD model, including bypass flow. The model considers the split of the feed stream into a smaller feed fraction (a), representing the by-pass flow (closer to a plug flow) and a larger feed fraction (1-a), which represents the overall mixing condition in the cell (Yianatos et al., 2008a). The modelling results showed the presence of 6-9% by-pass flow. The impact of these percentages of bypass flow are not significant in terms of mineral recovery; however the prompt detection of this kind of problem prevents operating troubles in the long time, because of solid embankment. The short time delay observed in these results corroborates the existence of by-pass flow, because the time delay observed was lower than the time required for pulp recirculation throughout the rotor, approximately 70 seconds (Yianatos et al., 2008b). From a hydrodynamic point of view, the new experimental data confirmed that a single mechanical flotation cells, of large size, can deviate significantly from perfect mixing. Experimental evidence has shown that mixing characteristics of a single cell can be equivalent to a number of perfect mixers larger or lower than one (NC>1 or NC<1). In terms of process modelling the mixing conditions in a flotation bank
2.5 Solid particles segregation A less turbulent or quiet zone is required in the upper part of flotation cells, below the pulp-froth interface, in order to create the best conditions for bubble-particle aggregates separation. Below the interface the superficial gas rate increases due to the presence of the froth crowder, an inverted cone used to decrease the cross sectional area of the cell around 40%. Also, the lower turbulence favors the particle segregation mainly for large particle sizes (>150 microns). Fig. 7 shows the solid percentage profiles per size class in a large cell, where the total solid percentage decreases almost 10% because of coarse mineral segregation.
the range JG=1.2-2.0 cm/s. From these results, it was found that the bubble surface area flux in different large cell operations was in the range SB=15-60 (s-1). A typical SB value around 40 (s-1) was found for a good operation in different cell sizes. 1 Ratio : (T class i ) / (T fine).
of N mechanical cells with NC>1 can be well described as a series of N continuous perfectly mixed tanks, where N corresponds to the actual number of cells in the bank. However, for the case of NC<1, the number of equivalent cells per bank can be significantly less than the actual number of cells N. This observation is relevant for process modeling, scale-up and circuit design.
0,9 0,8 0,7 08-jan-08 09-jan-08
0,6 0,5 0
50
100
150
200
250
Mean particle size class i , microns
Fig. 8 Effect of particle size on solid residence time
0,0
Interface
Cell Depth, m
0,5 % Coarse
1,0
Local gas holdup measurements were performed below the pulp-froth interface to observe the gas holdup in the quiet zone (EG=12-14%). Results showed a reasonably good agreement with theoretical expectations, from drift-flux analysis, for the range of gas rate and mean bubble size independently measured. Effective pulp volumes of 82-85% of the total cell volume were observed in large flotation cells.
% Medium coarse
1,5
% Medium fine
2,0
% Fine % Total
2,5 3,0 3,5 0
10
20
30
40 Solids, %
50
60
Fig. 7 Solid segregation in large flotation cells Figure 8 shows the effect of particle size on non-floatable solid residence time in a large flotation cell. In this experience, it was observed that residence time of coarse particles (<150 microns) can be as low as 80% of the fine particle residence time. Measurements of mean residence time of solids also confirmed the significant segregation of medium and coarse size particles. The significant difference in solid residence time per size class is relevant and must be considered for process modelling and scale-up. Recent experiments in large cells confirmed that the mean residence time of the total solid (23%+212 microns) was around 90% of the liquid, which is in good agreement with previous studies. 2.6 Bubble surface area flux estimation in large cells Bubble size distribution measurements allowed the estimation of Sauter mean bubble diameters in the range of dB=1.4-5.4mm. Also, local gas rate measurements varied in
2.7 Bubble Load measurement in large flotation cells The mass flowrate of particles (ton/h), entering the froth by true flotation, was evaluated from direct measurement of bubble load (ton/m3) and gas flowrate (m3/h). This information, together with the concentrate mass flowrate, allowed the estimation of the froth recovery of floatable mineral in 130m3 rougher flotation cells. It was found that mineral transport along the froth was mainly non-selective, and also the contribution of valuable minerals recovered by entrainment was negligible, if compared with minerals recovered by true flotation. Thus, a direct estimation of the froth recovery was obtained, without arbitrary assumptions about the grade of mineral transport by entrainment and drainage. This simple procedure allows a non-biased and independent evaluation of the effect that design and operating variables have, upon the collection and froth zones performance, in large flotation cells. Experimental studies have shown that operating variables affect the pulp and froth zones performance in a different and often opposite way. In this sense, the procedure developed for bubble load measurement allows the direct estimation of the froth recovery, as well as to determine the pulp zone
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
recovery. The knowledge of all these parameters is relevant for flotation process diagnosis and to develop more efficient flotation control strategies. Measurement of bubble load, local gas rate and mass balances in different flotation cells type and sizes, allowed the estimation of froth recoveries in the range of 30% to 80%. These results clearly show the large potential for flotation improvement in terms of cell design and particularly in terms of process control. The froth transport plays a key role not only in terms of mineral separation and upgrading but also in terms of process recovery. At present new efforts have been addressed related to automatic analysis of the top of froth characteristics (i.e. use of cameras and automatic image processing). The challenge now is how to relate this information with internal process variables and their effect upon the froth performance (grade and recovery), which in most cases is the controlling step for mineral separation and recovery, particularly in large size cells. 2.8 Operating control problems Measurement of residence time distribution in industrial equipment and estimation of the pulp flowrate in flotation lines using radioactive tracers, as well as air flowrate measurements, allowed the observation of different operating problems, such as uneven pulp distribution in parallel flotation lines, solid segregation and cells embankment. Also, a common problem observed in plant operation is the lack of proper calibration of air flowmeters and pulp level sensors. 3. CONCLUSIONS Common operating control problems in flotation circuits, such as uneven pulp distribution in parallel rougher flotation banks, solid segregation and bypass flow in large flotation cells, were identified and evaluated from RTD measurements. The mean residence time of solid (23%+212 microns) was 10% lower than liquid in large cells, while the coarse mineral (> 150 microns) showed a residence time up to 20% lower than the liquid residence time. The flow regime in a single cell was equivalent to more than one perfect mixer in series (NC>1), or lower (NC<1) depending of the type of cell design. Also, it was found that RTD in flotation banks was equivalent to a number of perfect mixers in series equal or lower than the actual number of cells in the bank, depending of the type of cell design. This is a key aspect in terms of process modeling for scale-up purposes and circuit design. Local superficial gas rate and bubble size distribution measurements were developed for bubble surface area flux estimation. SB values around 40s-1 were observed under normal operating conditions. Thus, typical boundary conditions for superficial gas rate (1-2 cm/s) and mean bubble size (1-2mm), based on plant experience, have been identified for stable flotation operations. Also, an effective
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
pulp volume of 82-85% of the total cell volume was observed in large flotation cells. Froth recovery in large flotation cells was evaluated from bubble load measurement. The froth recovery data is relevant for flotation process modelling and control because of the critical role the froth transport plays in large size cells. Recent development on automated froth visual analysis (i.e., bubble size, bubble collapse and froth overflow velocity) poses new challenges to link this information with the actual internal process variables (i.e. froth recovery). ACKNOWLEDGEMENTS The authors are grateful to El Teniente Division CodelcoChile for providing access to their plant and for valuable assistance in the experimental work. Funding for process modelling research is provided by CONICYT, project Fondecyt 1070106, Chilean Commission of Nuclear Energy, and Santa María University, project 270522. REFERENCES Hernandez-Aguilar, J., Gomez, C., Finch, J., 2002. A technique for the direct measurement of bubble size distributions in industrial flotation cells. Proceedings of the 34th Annual Meeting of the Canadian Mineral Processors, pp. 389–402. Lichter, J., Potapov, A., Peaker, R., 2007. The use of Computational Fluid Dynamics and Discrete Element Modelling to Understand the Effect of cell Size and Inflow rate on Flotation bank Retention Time Distribution and Mechanism Performance. Canadian Minerals Processors Conference, CMP’07, Canada. Mavros, P., 1992. Mixing and hydrodynamics in flotation cells. Innovations in flotation technology. P. Mavros and K.A. Matis, eds., NATO ASI Series, Kluwer Academic Pub., London, 211-234. Vinnett, L., Contreras, F., Yianatos, J., 2009. BSD analysis for automatic control purposes in industrial flotation cells. International Conference IFAC MMM, Viña del Mar, Chile. Yianatos, J.B., Bergh, L.G., Tello, K., Díaz, F. and Villanueva, A., 2008a. Residence time distribution in single big industrial flotation cells, Miner. Metall. Process. J., Vol.25, Nº1, pp.46-52. Yianatos, J.B., Larenas, J., Moys, M., Díaz, F., 2008b. Short time response in a big flotation cell, International Journal of Mineral Processing, Vol. 89, pp.1-8. Yianatos J.B., Moys M.H., Contreras F. and Villanueva, A. 2008c. Froth recovery of industrial flotation cells. Minerals Engineering, Vol.21, pp.817-825. Yianatos, J., Bergh, L., Osorio, C., Villanueva, A., 2008d. A practical model for industrial flotation banks. International Mineral Processing Congress, XXIV IMPC, Beijing, CHINA, September.
Automation and Supervision Centre for Mining Industry, CASIM Santa María University, Valparaíso, Chile, (e-mail: [email protected]). * Chilean Commission of Nuclear Energy, Nuclear Applications Department La Reina, Santiago, Chile Abstract: The residence time distribution of liquid, gas and solid per size class was measured in large flotation cells in different flotation plants. The RTD measurement was developed using radioactive tracers. Results allowed the estimation of effective pulp volumes of 82-85% of the total nominal volume in large flotation cells. It was found that single large industrial flotation cells have different flow regimes and can be significantly different from a perfect mixer (N>1 or N<1). Measurement of RTD also allowed the identification of operating control problems such as solid segregation (affecting the mean residence time for kinetic modeling), cells embankment, and increasing short-circuit because of cell design characteristics and circuit arrangement (i.e. input-output location ). Measurement of local superficial gas rate and improved measurement of bubble size distribution, using new software, allowed the estimation of the bubble surface area flux (SB around 40s-1), key parameter describing the quality (level) of gas dispersion in industrial flotation cells. Also, typical boundaries for superficial gas rate (1-2 cm/s) and mean bubble size (1-2mm) have been identified for stable flotation operation from different plant experiences. Bubble load measurement was carried out for estimating the froth recovery in large flotation cells. Froth recovery is relevant for flotation process modeling and control because of the critical role the froth transport plays in large cells. Recent development on automated froth visual analysis (i.e., bubble size, bubble collapse and froth overflow velocity) poses new challenges to link this information with the actual internal process variables (i.e. froth recovery). Keywords: froth flotation, RTD, radioactive tracer, flotation machines, modeling, troubleshooting
1. INTRODUCTION In the last years flotation equipment has increased dramatically in size together with the large increase in mineral processing by flotation. The largest flotation cells presently used in industrial flotation operations all over the world are 100, 130, 160 m3, and more recently have reached 250-300m3 per single cell. Improvements in simplicity (low number of cells), low specific energy consumption and less space have been in most cases the reasons for using these new designs. Industrial flotation cells need to accomplish several functions such as: air dispersion, solid suspension, bubble-particle collision and aggregate formation, as well as provide the best conditions for floatable mineral separation in the froth zone. For this reason, cells are typically provided with mechanical agitation systems which generate the required mixing conditions for pulp suspension and air dispersion in small bubbles. Also, cells are provided with a quiet zone in the upper part where a distinctive pulp-froth interface is created. Froth crowders and internal launders are typically used to improve the froth transport and recovery. Figure 1shows the main characteristics of a self-aerated cell, where the feed pulp circulates upwards through a draft tube by the rotor, while the air is self-aspirated from the top of the cell by the rotor.
AIR
FROTH CROWDER
CONCENTRATE
ROTOR FEED PULP CIRCULATION
FEED
PULP/FROTH INTERFACE
TAIL
Fig. 1 Large flotation cell In an industrial continuous flotation cell, the mixing condition prevents that particles have the same opportunity to be collected, because a significant fraction of them actually spent a very short time in the cell (in a well-mixed condition almost 40% of particles stay in the cell for less than a half of the mean residence time). Because of the large short circuit in single continuous cells, the industrial flotation circuits consider the arrangement of cells in banks. For example,
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
banks of 5-10 cells in series are commonly used in plant practice (Yianatos et al., 2008d).
interface level, sanding-up due to particle settling and other disturbing condition in the cell (Yianatos et al., 2008b).
Besides normal changes in feed grade and flowrate, and the need for periodic maintenance of instrumentation (level control, air flowrate) the following common troubles have been observed in plant practice,
1.2 Bubble load measurement and froth recovery estimation
x
Improper calibration and maintenance of instrumentation to measure froth depth and gas rate
x
Uneven pulp distribution in parallel lines (solid percentage, mass flowrate and grade)
x
Short-circuit in single cells
x
Embankment and by-pass flow in single cells
x
Uneven froth discharge (froth recovery)
x
Lack of robustness of control strategies
Other parameter which affects the plant stability is the feed solid percentage (25-40%) including the corresponding time delays (a typical condition is 38% solid). The flotation circuit takes long time for solid percentage stabilization. 1.1 Tracer technique In order to study the hydrodynamic behaviour of large flotation cells, the radioactive tracer technique has been used to measure the residence time distribution (RTD) of the liquid, solid and gas in industrial rougher flotation banks. For this purpose, a pneumatic system of high reliability was used in order to introduce a small amount of radioactive tracer (around 100 mL of liquid or pulp) at the feed pulp entrance. Then, the time response of the radioactive tracer was measured on-line, at different points along the bank, using non-invasive sensors located directly in the discharge pipe of each cell. Activity (cps) was measured by scintillating crystal sensors of NaI(Tl) of 1”x1.5”, Saphymo Srat, thus allowing the simultaneous data acquisition of up to 12 control points, with a minimum period of 50 milliseconds. Br-82 in solution was used as liquid tracer and Bromine Tri-Fluor-Methane (CF3Br), also called Freon 13B1, was used as gaseous tracer. Solid radioactive tracers were prepared by neutron activation in the 5 MW Nuclear Reactor of the Chilean Commission of Nuclear Energy. The solid tracer was tested at three size classes (coarse: +150, intermediate: -150+45 and, fine –45 microns) in order to evaluate solids segregation. An advantage of using the radioactive tracer technique is the direct testing of the actual solid particles (similar physical and chemical properties, size distribution, shape, etc.). Tracer injection is almost instantaneous because only a small amount of radioactive tracer is required. Another advantage is its capability for on-line measurement at various locations in the system without disturbances related to process sampling. Also a gamma ray scanning was performed in an industrial large cell using a neutron backscatter technique, across a vertical plane, to measure the relative density as a function of height. This technique was useful to identify pulp-froth
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
A special device for bubble load measurement has been used to estimate the amount of solid particles collected by true flotation (bubble-particle aggregates formation) that reaches the pulp-froth interface being transported along the froth into the concentrate. The bubble load measurement device also allows the local superficial gas rate measurement. This information and the mass balance are fundamental to estimate the froth recovery in large flotation cells (Yianatos et al., 2008c). 1.3 Bubble surface area flux SB The bubble surface area flux SB (s-1) is a hydrodynamic parameter which describes the level of the gas dispersion. SB = 6 JG/dB
(1)
where JG is the superficial gas rate (cm/s) and dB is the mean bubble diameter. In recent years the development of new instrumentation for local gas rate and bubble size distribution measurement has allowed the estimation of SB at industrial scale. For example, bubble size distribution has been measured in several flotation circuits using the McGill bubble size analyzer (Hernandez-Aguilar et al., 2002). Also, in order to improve the mean bubble size estimation in presence of large bubbles and/or bubble clusters, usually encountered in large cells, new software for semi-automated image analysis was recently developed (Vinnett et al., 2009). 2. EXPERIMENTAL 2.1 Pulp distribution in rougher flotation circuits In order to estimate the mean residence of minerals in industrial flotation circuits a common practice consists of estimating the volumetric flowrate of the feed pulp entering the rougher circuit. The volumetric flowrate can be estimated from the solids mass flowrate measurement, by weightmeters located at the grinding stage feed, and measurement of the solids percentage in the flotation feed pulp. However, in large rougher circuits there are three or more parallel flotation banks typically. For this reason, despite the normal errors in estimating the solid mass flowrate and pulp density, the feed volumetric flowrate estimation can be biased because of uneven feed pulp distribution. For process modelling and diagnosis, the actual distribution of the feed volumetric flowrate was measured in industrial rougher flotation circuits using the radioactive tracer technique. The experimental test consisted of the injection of a tracer signal at the common distribution box, and simultaneous on-line measurement of RTD in parallel flotation banks. The mean residence time for each flotation bank was then calculated by de-convolution between the input and output signals. The pulp distribution was calculated
considering the volumetric flowrate of each flotation bank proportional to the inverse of residence time. Using this approach it was found that the volumetric flowrate distribution in large size circuits can be significantly different. Table 1 shows the volumetric flowrate distribution evaluated in four industrial circuits. In circuit A, tests were performed only with liquid tracer, while circuits B, C and D were tested for liquid, and solids per size class, allowing the evaluation of the standard deviation. From these results
differences up to 15-20%, above or below the expected flowrate for even distribution, were found. This is a relevant point considering the impact these differences can have on process characterization (i.e. residence time and kinetics) and process automation (i.e. reagents addition control). Also, significant differences in mineral grade and solid percentage were found in feed samples taken from different parallel banks in the same circuit.
Table 1. Volumetric flowrate distribution in parallel rougher banks Circuit
Nº of banks
A B C D
4 3 3 3
Bank 1 % 24.5 31.6 ± 0.7 31.2 ± 2.3 33.6 ± 0.4
Bank 2 % 24.0 31.8 ± 0.5 29.2 ± 0.7 36.0
From direct measurement of effective residence time of liquid and solids per size class, in flotation cells and banks, it was possible to estimate the effective cell volume occupied by the pulp. Thus, under normal operating conditions, i.e. superficial gas rate JG=1.3-1.8 cm/s, dB=1.2-2.2mm and no embankment, the typical range of effective cell volume was 82-85% of the total nominal volume.
Bank 3 % 27.7 36.6 ± 0.6 39.6 ± 1.7 30.4 ± 0.1
Bank 4 % 23.8
Total Flow % 100 100 100 100
2.2 RTD of Flotation Banks The RTD was measured on-line in the tailings stream at different locations along the banks in different flotation circuits. For example, Figure 2 shows a circuit arrangement (1-2-2-2) consisting of seven 130m3 cells, the tracer injection point at the feed inlet and the sensors location along the bank.
CONCENTRATE E(t) W FEED
t
1 1
2 RTD CELL1
3
4 RTD
5
6 RTD
CELLS 1 to 3
CELLS 1 to 5
7
TAIL
RTD CELLS 1 to 7
Fig. 2 Tracer impulse test and sensors location in a flotation bank Figure 3 shows the liquid residence time distribution after 1, 3, 5 and 7 cells in the bank, where a significant decrease in the pulp short-circuit, by increasing the number of cells in the flotation bank, was observed. These results confirm that a minimum number of 4 or 5 cells per bank is recommended, to minimize the problem of short-circuit in flotation cells. Also, the continuous lines show a good agreement between the data points and a RTD model, typically represented by N perfect mixers in series (Mavros, 1992). The same procedure has been used to characterize the individual performance of each cell along the rougher flotation banks (Yianatos et al., 2008a).
2.3 Scale-up of RTD in large self-aerated mechanical cells Figure 4 shows experimental data and model fitting for RTD of single mechanical cells of 130 and 250m3 (Yianatos et al. 2008a). The comparison of both RTD shows that despite the increase in size, almost twice, the mixing conditions are similar, thus allowing for effective scale-up in terms of the hydrodynamic behaviour. Using the N cells model the equivalent number of perfect mixers for both flotation cells was NC approximately 1.4. Also, the good fit of a large and small tank in series model (LTST) is presented.
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
0.0035 0.0030
N=1
RTD, E(t)
0.0025
E(t )
t N 1 exp(tN / W ) (W / N ) N *( N )
Cells number 1 3 5 7
0.0020
N=3
0.0015
N=5
0.0010
N 1.3 3.1 4.9 6.8
N=7
0.0005 0.0000 0
500
1000
1500
2000
2500
3000
3500
4000
Time, s
Fig. 3
RTD in a flotation bank after 1, 3, 5 and 7 cells in series.
130 m3 250 m3
Figure 6 shows the liquid RTD in an industrial self-aerated cell of 130m3, located in the middle of a rougher bank, where an abnormal operating condition due to by-pass flow (shortcircuiting) was observed, mainly related to solid settling and pulp channelling (Yianatos et al., 2008a).
LTST Model
0.80
0.0028
0.60 0.40
By-pass flow model
0.0020
0.20 0.00 0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.0016 0.0012 0.0008
Dimensionless time, T
Fig. 4 RTD in 130 and 250m3 cells (Yianatos et al., 2008a).
0.0004 0.0000 0
2.4 RTD and by-pass flow in single cells
0,0060 Data LSTS Model SC Model E(t) Model
0,0050 0,0040 0,0030 0,0020 0,0010 0,0000 0
300
600
200
400
600
800
1000
1200
1400
1600
time, s
Figure 5 shows the solid RTD measured in a large cell of different design, where the rotor is located near the bottom. In this case the residence time distribution was equivalent to less than one perfect mixer (NC<1). This operation showed the presence of a larger short circuit which was augmented because of the discharge orientation (less than 180º relative to the cell input) due to space constraints. The model adjustment, considering a mixing component model (LSTS) plus a by-pass fraction (short-circuiting SC model), allowed the estimation of a by-pass flow fraction around 10%.
RTD
Data cell 3
0.0024
RTD
Dimensionless RTD, E(T)
1.00
These results are in good agreement with previous simulations for this kind of cells (50-160m3) derived from the combined use of CFD and DEM, where the by-pass flow of particles (50-300 microns) was reported in the range 2-20%, mainly depending on particle size, inlet velocity and discharge orientation (Lichter et al., 2007). Despite the important simplifications of the CFD simulation, such as the exclusion of air from the slurry system, the CFD technique has a very good potential to provide a detailed insight on how specific design parameters would impact the performance of the flotation cell.
900
1200
1500
Time, s
Fig. 5 Liquid RTD model with by-pass flow in a large cell
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
Fig. 6
Liquid RTD in an industrial cell showing by-pass flow
Figure 6 also shows the fitting of a RTD model, including bypass flow. The model considers the split of the feed stream into a smaller feed fraction (a), representing the by-pass flow (closer to a plug flow) and a larger feed fraction (1-a), which represents the overall mixing condition in the cell (Yianatos et al., 2008a). The modelling results showed the presence of 6-9% by-pass flow. The impact of these percentages of bypass flow are not significant in terms of mineral recovery; however the prompt detection of this kind of problem prevents operating troubles in the long time, because of solid embankment. The short time delay observed in these results corroborates the existence of by-pass flow, because the time delay observed was lower than the time required for pulp recirculation throughout the rotor, approximately 70 seconds (Yianatos et al., 2008b). From a hydrodynamic point of view, the new experimental data confirmed that a single mechanical flotation cells, of large size, can deviate significantly from perfect mixing. Experimental evidence has shown that mixing characteristics of a single cell can be equivalent to a number of perfect mixers larger or lower than one (NC>1 or NC<1). In terms of process modelling the mixing conditions in a flotation bank
2.5 Solid particles segregation A less turbulent or quiet zone is required in the upper part of flotation cells, below the pulp-froth interface, in order to create the best conditions for bubble-particle aggregates separation. Below the interface the superficial gas rate increases due to the presence of the froth crowder, an inverted cone used to decrease the cross sectional area of the cell around 40%. Also, the lower turbulence favors the particle segregation mainly for large particle sizes (>150 microns). Fig. 7 shows the solid percentage profiles per size class in a large cell, where the total solid percentage decreases almost 10% because of coarse mineral segregation.
the range JG=1.2-2.0 cm/s. From these results, it was found that the bubble surface area flux in different large cell operations was in the range SB=15-60 (s-1). A typical SB value around 40 (s-1) was found for a good operation in different cell sizes. 1 Ratio : (T class i ) / (T fine).
of N mechanical cells with NC>1 can be well described as a series of N continuous perfectly mixed tanks, where N corresponds to the actual number of cells in the bank. However, for the case of NC<1, the number of equivalent cells per bank can be significantly less than the actual number of cells N. This observation is relevant for process modeling, scale-up and circuit design.
0,9 0,8 0,7 08-jan-08 09-jan-08
0,6 0,5 0
50
100
150
200
250
Mean particle size class i , microns
Fig. 8 Effect of particle size on solid residence time
0,0
Interface
Cell Depth, m
0,5 % Coarse
1,0
Local gas holdup measurements were performed below the pulp-froth interface to observe the gas holdup in the quiet zone (EG=12-14%). Results showed a reasonably good agreement with theoretical expectations, from drift-flux analysis, for the range of gas rate and mean bubble size independently measured. Effective pulp volumes of 82-85% of the total cell volume were observed in large flotation cells.
% Medium coarse
1,5
% Medium fine
2,0
% Fine % Total
2,5 3,0 3,5 0
10
20
30
40 Solids, %
50
60
Fig. 7 Solid segregation in large flotation cells Figure 8 shows the effect of particle size on non-floatable solid residence time in a large flotation cell. In this experience, it was observed that residence time of coarse particles (<150 microns) can be as low as 80% of the fine particle residence time. Measurements of mean residence time of solids also confirmed the significant segregation of medium and coarse size particles. The significant difference in solid residence time per size class is relevant and must be considered for process modelling and scale-up. Recent experiments in large cells confirmed that the mean residence time of the total solid (23%+212 microns) was around 90% of the liquid, which is in good agreement with previous studies. 2.6 Bubble surface area flux estimation in large cells Bubble size distribution measurements allowed the estimation of Sauter mean bubble diameters in the range of dB=1.4-5.4mm. Also, local gas rate measurements varied in
2.7 Bubble Load measurement in large flotation cells The mass flowrate of particles (ton/h), entering the froth by true flotation, was evaluated from direct measurement of bubble load (ton/m3) and gas flowrate (m3/h). This information, together with the concentrate mass flowrate, allowed the estimation of the froth recovery of floatable mineral in 130m3 rougher flotation cells. It was found that mineral transport along the froth was mainly non-selective, and also the contribution of valuable minerals recovered by entrainment was negligible, if compared with minerals recovered by true flotation. Thus, a direct estimation of the froth recovery was obtained, without arbitrary assumptions about the grade of mineral transport by entrainment and drainage. This simple procedure allows a non-biased and independent evaluation of the effect that design and operating variables have, upon the collection and froth zones performance, in large flotation cells. Experimental studies have shown that operating variables affect the pulp and froth zones performance in a different and often opposite way. In this sense, the procedure developed for bubble load measurement allows the direct estimation of the froth recovery, as well as to determine the pulp zone
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
recovery. The knowledge of all these parameters is relevant for flotation process diagnosis and to develop more efficient flotation control strategies. Measurement of bubble load, local gas rate and mass balances in different flotation cells type and sizes, allowed the estimation of froth recoveries in the range of 30% to 80%. These results clearly show the large potential for flotation improvement in terms of cell design and particularly in terms of process control. The froth transport plays a key role not only in terms of mineral separation and upgrading but also in terms of process recovery. At present new efforts have been addressed related to automatic analysis of the top of froth characteristics (i.e. use of cameras and automatic image processing). The challenge now is how to relate this information with internal process variables and their effect upon the froth performance (grade and recovery), which in most cases is the controlling step for mineral separation and recovery, particularly in large size cells. 2.8 Operating control problems Measurement of residence time distribution in industrial equipment and estimation of the pulp flowrate in flotation lines using radioactive tracers, as well as air flowrate measurements, allowed the observation of different operating problems, such as uneven pulp distribution in parallel flotation lines, solid segregation and cells embankment. Also, a common problem observed in plant operation is the lack of proper calibration of air flowmeters and pulp level sensors. 3. CONCLUSIONS Common operating control problems in flotation circuits, such as uneven pulp distribution in parallel rougher flotation banks, solid segregation and bypass flow in large flotation cells, were identified and evaluated from RTD measurements. The mean residence time of solid (23%+212 microns) was 10% lower than liquid in large cells, while the coarse mineral (> 150 microns) showed a residence time up to 20% lower than the liquid residence time. The flow regime in a single cell was equivalent to more than one perfect mixer in series (NC>1), or lower (NC<1) depending of the type of cell design. Also, it was found that RTD in flotation banks was equivalent to a number of perfect mixers in series equal or lower than the actual number of cells in the bank, depending of the type of cell design. This is a key aspect in terms of process modeling for scale-up purposes and circuit design. Local superficial gas rate and bubble size distribution measurements were developed for bubble surface area flux estimation. SB values around 40s-1 were observed under normal operating conditions. Thus, typical boundary conditions for superficial gas rate (1-2 cm/s) and mean bubble size (1-2mm), based on plant experience, have been identified for stable flotation operations. Also, an effective
IFACMMM 2009. Viña del Mar, Chile, 14 -16 October 2009.
pulp volume of 82-85% of the total cell volume was observed in large flotation cells. Froth recovery in large flotation cells was evaluated from bubble load measurement. The froth recovery data is relevant for flotation process modelling and control because of the critical role the froth transport plays in large size cells. Recent development on automated froth visual analysis (i.e., bubble size, bubble collapse and froth overflow velocity) poses new challenges to link this information with the actual internal process variables (i.e. froth recovery). ACKNOWLEDGEMENTS The authors are grateful to El Teniente Division CodelcoChile for providing access to their plant and for valuable assistance in the experimental work. Funding for process modelling research is provided by CONICYT, project Fondecyt 1070106, Chilean Commission of Nuclear Energy, and Santa María University, project 270522. REFERENCES Hernandez-Aguilar, J., Gomez, C., Finch, J., 2002. A technique for the direct measurement of bubble size distributions in industrial flotation cells. Proceedings of the 34th Annual Meeting of the Canadian Mineral Processors, pp. 389–402. Lichter, J., Potapov, A., Peaker, R., 2007. The use of Computational Fluid Dynamics and Discrete Element Modelling to Understand the Effect of cell Size and Inflow rate on Flotation bank Retention Time Distribution and Mechanism Performance. Canadian Minerals Processors Conference, CMP’07, Canada. Mavros, P., 1992. Mixing and hydrodynamics in flotation cells. Innovations in flotation technology. P. Mavros and K.A. Matis, eds., NATO ASI Series, Kluwer Academic Pub., London, 211-234. Vinnett, L., Contreras, F., Yianatos, J., 2009. BSD analysis for automatic control purposes in industrial flotation cells. International Conference IFAC MMM, Viña del Mar, Chile. Yianatos, J.B., Bergh, L.G., Tello, K., Díaz, F. and Villanueva, A., 2008a. Residence time distribution in single big industrial flotation cells, Miner. Metall. Process. J., Vol.25, Nº1, pp.46-52. Yianatos, J.B., Larenas, J., Moys, M., Díaz, F., 2008b. Short time response in a big flotation cell, International Journal of Mineral Processing, Vol. 89, pp.1-8. Yianatos J.B., Moys M.H., Contreras F. and Villanueva, A. 2008c. Froth recovery of industrial flotation cells. Minerals Engineering, Vol.21, pp.817-825. Yianatos, J., Bergh, L., Osorio, C., Villanueva, A., 2008d. A practical model for industrial flotation banks. International Mineral Processing Congress, XXIV IMPC, Beijing, CHINA, September.