Assessing Your Plants Flotation Behaviour Using Gas Dispersion Parameters

Transcription

1 Assessing Your Plants Flotation Behaviour Using Gas Dispersion Parameters Jan E. Nesset Peru II International Metallurgical Conference, Lima, Peru November 1-3, 213

2 The Presentation will cover The importance of bubble size and therefore frother in flotation performance The gas dispersion parameters The concepts of CCC, CCCX and HLB How the key operating variables affect bubble size (a model for D 32 ) A Road Map for process optimization Some implications for process improvement Case study: Lac des Iles 2

3 Illustrating the importance of frother and small bubbles in flotation (video) View inside a Denver laboratory flotation machine: water-air system: no air/air added/air with frother Courtesy of McGill and Metso CBT Flotation Module 22 (originally BPT 1996) 3

4 Frother functions are multiple: 1. Stabilizing small bubbles (.5 2 mm) in pulp phase by preventing coalescence 2. Bubble size and shape affect bubble surface area flux, gas hold-up and interfacial surface area of gas and hence particle collection efficiency and flotation kinetics 3. Froth formation and stability thus influencing water drainage/recovery, hence gangue rejection and concentrate grade 4

5 Adding frother affects the size, shape and distribution of bubbles FREQUENCY DISTRIBUTION D32 (mm) FREQUENCY DISTRIBUTION FREQUENCY DISTRIBUTION FREQUENCY DISTRIBUTION FREQUENCY DISTRIBUTION mm D b (mm) FROTHER ADDITION (ppm) D b (mm) Coalescing Non-coalescing D b (mm) D b (mm) D b (mm) Sauter Mean Bubble Diameter D 32 = n 1 d 3 n 1 d 2 (Not the average bubble size) 5

6 Gas Dispersion Terminology Sauter mean bubble size (mm) characteristic of the bubble size distribution (gas volume/surface area) D 32 = n 1 n 1 d 3 d 2 Superficial gas velocity (cm/s) gas flow/unit of cell x-sect area Bubble surface area flux (1/s) area of bubble surface/sec/unit of cell x-sect area Flotation rate constant (1/s) R froth is recovery across the froth P is the floatability factor for particles k overall J g = Q gas A Xsect S b = 6 J g D 32 = R frot h k pulp k pulp = PS b 6

7 What is the relationship between flotation (rate, k) and bubble size? The k-s b relationship (Gorain): k pulp = PS b = P 6 J g D 32 Hence: k 1 d But does P also vary with bubble size? Hernandez Aguilera et al 1 have found Others 2 suggest a stronger dependence k 1 d 2 k 1 d 3 1 Hernandez-Aguilar, J.R.; Basi, J.; Finch, J.A. Improving column flotation operation in a copper/molybdenum separation circuit. CIM J. 21, 2 Yoon, R.H. Microbubble flotation. Miner. Eng. 1993, 6,

8 What is the relationship between flotation (rate, k) and bubble size? Use a 1 st order recovery model having n cells in series Recovery R 1 (1 k t /(1 i i k i t i )) n Assumptions 1 st order flotation kinetics, fully mixed cells k base line =.1 s -1 8 Flotation cells in series (n=8) Flotation time t = 3 min R = 9%, Froth recovery = 1% (R froth = 1) 8

9 RECOVERY (%) An example: Why bubble size is important in flotation recovery Impact on recovery of reducing bubble size (D 32 ) from 1.7 to 1.2 mm by changing frother type/concentration k 1 d k 1 d 2 k 1 d k =.1 k =.14 % Recovery Baseline 1/d 1/d 2 1/d 3 Rec y % K s D 32 mm k = k = FLOTATION TIME DOWN BANK (min) 9

10 D 32 (mm) The CCC and CCCX (%) concepts and modeling D CCC5 CCC85 CCC95 CCC99 a d l Frother Addition (ppm) CCC value CCC95 values closely approximate Laskowski s CCC (critical coalescence concentration) values but easier to establish mathematically D 32 = d l + a exp b CCCX % = 1 (1 exp b ppm CCC95 ppm CCC95 ) Modeling D 32 Represents the % reduction in a 1

11 Linking D 32 to frother type (CCC95) and Concentration (ppm) normalized by (PPM/CCC95) D 32 (mm) Jg=.5 cm/s Jg=1 cm/s Model All Data Model Jg=.5 cm/s Model Jg=1 cm/s 5 frother types 2 gas rates (J g ) Frother Addition (ppm/ccc95) Frother can be characterized by its CCC95 (@ J g =.5 cm/s) D exp [ 3.9 ppm CCC95 ] 11

12 The link between CCC95 and HLB HLB Hydrophile Lipophile Balance A measure of the solubility of a surfactant in water. Calculated empirically from the molecular structure (Davies method) HLB = 7 + Σ(hydrophilic group numbers) + Σ(lipophilic group numbers) Functional group Group contribution number Hydrophilic OH 1.9 O 1.3 Lipophilic (or hydrophobic) CH CH2.475 CH 3 =CH From Zhang et al, 212, Minerals, Vol 2, pp

13 The limiting bubble size d l is controlled d limiting by molecular structure (HLB) Tested at J g =.5 cm/s MIBC Alcohols PPGAE PPG Commercial F14 R² =.94 (not including commercial frothers) HLB DF112 DF25 INCREASING SOLUBILITY F15 Frother Family Type HLB MW CCC95 Dlim ppm mm Aliphatic Alcohols 1 Propanol Butanol Pentanol Hexanol Heptanol Octanol Propanol Butanol Pentanol Hexanol Heptanol Octanol Pentanol Hexanol Polypropylyne Glycol Ethers Propylene Glycol Methyl Ether Propylene Glycol Propyl Ether Propylene Glycol Butyl Ether Di(Propylene Glycol) Methyl Ether Di(Propylene Glycol) Propyl Ether Di(Propylene Glycol) Butyl Ether Tri(Propylene Glycol) Methyl Ether Tri(Propylene Glycol) Propyl Ether Tri(Propylene Glycol) Butyl Ether Polypropylene Glycols DiPropylene Glycol TriPropylene Glycol TetraPropylene Glycol Polypropylene Glycol Polypropylene Glycol Polypropylene Glycol Commercial Frothers FX12-1 (MIBC) DowFroth DowFroth FX FX F F Data from Zhang et al, 212, Minerals, Vol 2, pp Frothers with higher HLB (solubility) = smaller limiting bubble size 13

14 CCC95 - HLB/MW relationship 8 CCC95 Jg=.5cm/s F15 DF25 MIBC Alcohols PPGAE PPG Commercial MW = molecular weight HLB/MW CCC95 values can be predicted from molecular structure of the frother. Zhang et al (212, Minerals, Vol2) have developed specific equations for predicting CCC95 from HLB 14

15 D 32 Model Development: Operating variables investigated Frother type and concentration Gas rate J g (volumetric air flow/cell area) Power input ( impeller speed 3 ) Gas Density (altitude) Viscosity (water temperature) Testing in 2-phase water- gas system Metso.8 m 3 RCS cell 15

16 D 32 relationships developed for J g, viscosity and gas density (altitude) D Gas Rate, J g.5 32 D a ( 1 J g ) Power Input No significant impact on D 32 for impeller speed 4 to 1 m/s Viscosity factor ƒ v f v = μ μ 2 μ 2 is viscosity at 2 o C.776 Density factor ƒ d f d = ρ o ρ g.132 ρ o is density of air at sea level (STP) 16

17 Interaction effects: normalized relative to HLB and CCC95 at J g =.5 cm/s Polyglycol frothers (e.g. DF25, F14, F15) CCC95 CCC95Jg. 5 ( J g Alcohol frothers (e.g. MIBC, Pentanol) CCC95 CCC95Jg. 5 ( J g ) ) Adjustment factor for the limiting bubble size (±) f l = HLB 17

18 Overall D 32 model Overall equation for determining D 32 from the key flotation variables factors ƒ v (viscosity), ƒ d (density), ƒ l (limiting D l ) as described earlier D 32 = f v f d φ J g, frother(ppm, CCC95, HLB) Note that a model for D 32 also becomes a model for predicting the bubble surface area flux S b since S b = 6J g D 32 18

19 D 32 (mm) Overall D 32 model.267 f The function φ is given by.5.5 ppm.64 (1 J ) ( f.267).619 (1 J ) exp 3.9 l g l g CCC95 The effect of J g and frother type on the CCC 99 curve (minimum limiting bubble size) The effect of J g on the CCC curve (maximum limiting bubble size) The exponential-decay effect of frother concentration and type on the CCC curve 5 4 CCC - Maximum D CCC99 - Minimum D J g (cm/s) PPM Frother 4 PPM DF25 8 PPM DF25 16 PPM DF25 32 PPM DF25 19

20 Gas Dispersion Data Collection in Plant 2

21 D 32 (mm) S b (s -1 ) Model validation with plant data - notion of a Process Road Map Company NA Palladium 5 Operating Plants WMC* Xstrata Ni Escondida Operating Plant Site Lac des Iles Leinster Raglan Los Colorados Cell Manufacturer Outotec TC Outotec 16U Outotec 28U Outotec TC Impala Platinum UG2 Bateman TC, Metso TC Cell Size (vol), m , 3 Circuit Duty R/S R/S R/S R R, C Site Location Canada Australia Canada Chile South Africa Metal/mineral floated Palladium Nickel Nickel Copper Platinum * Now BHP Billiton, R = rougher, S = scavenger, C=cleaner Plant data (3- phase) fit completely within model predictions (2-phase) Plant Data max min PPM Frother 4 PPM DF25 8 PPM DF25 16 PPM DF25 32 PPM DF25 Lac des Iles WMC-LNO Plant Data max Limiting DF25 CCC 16 PPM DF25 8 PPM DF25 4 PPM DF25 PPM Frother Lac des Iles WMC-LNO Raglan Escondida Los Colorados Impala 2 min Raglan Escondida Los Colorados Impala J g (cm/s) J g (cm/s) Model curves are for DowFroth 25 equivalent frother concentration 21

22 D 32 (mm) S b (s -1 ) D 32 (mm) S b (s -1 ) Examples of model prediction DowFroth 25 Jg = 2 cm/s 4 Jg = 1.5 cm/s Jg = 1 cm/s 3 Jg =.5 cm/s Jg =.2 cm/s 2 1 = CCC95 Operating Point Frother Concentration (ppm) 12 DowFroth 25 Jg = 2 cm/s 1 Jg = 1.5 cm/s 8 Jg = 1 cm/s 6 Jg =.5 cm/s 4 Jg =.2 cm/s 2 = CCC95 Operating Frother Concentration (ppm) Increasing bubble size requires that the optimum frother concentration increases with increasing gas rate (J g ) J g = 1.5 cm/s MIBC (Alcohol) DowFroth 25 (PPGAE) F-15 (PPG) Frother Concentration (ppm) 12 J g = 1.5 cm/s MIBC (Alcohol) DowFroth 25 (PPGAE) 4 F-15 (PPG) Frother Concentration (ppm) Higher HLB frothers yield lower limiting bubble size As a result, these frothers provide opportunity for increasing S b, hence flotation kinetics and fine particle recovery 22

23 Coarse versus fine particle flotation: Factor Fines Coarse Comment Bubble Size Small Larger (and very small) Probability of Collision Bubble Water Film Thin Thick Probability of attachment Flotation time More Less important Fines are slow Turbulence Ok Quiescent Zone Probability of detachment Collector strength hydrodynamic implications* High dose, Selective More hydrophobic Reduce induction time Frother strength Weaker Stronger Reduce detachment Conditioning Separate Separate Not together Most Important Small bubbles, time and kinetics Chemistry *Slide courtesy of Frank Cappuccitti, Flottec 23

24 Using the Model to Benchmark Plant Performance Case Study: Lac des Iles Pd Concentrator (Ontario, Canada) 1% Difference in Pd recovery between plant and pilot testing (testing in 23 and 25) 24

25 % minus 1 mm bubbles Large difference in plant and pilot plant/lab bubble size Lab Tests Plant and Pilot Tests Rougher cells Scavenger cells Flotation Feed Scavenger tails Combined final tails Cleaner tails Bubble Size Distribution - % minus 1mm bubbles Final concentrate 1 Pilot /lab cells Plant cells Plant Cells Pilot Plant Cells Std Lab Float Cell No 25

26 S b (s -1 ) D 32 (mm) LDI - Comparison of 23 and 25 D 32 and S b with road map model 25 test of blended frother to 6 th scavenge cell 4 Lac des Iles Case Study PPM Frother 5 PPM MIBC 1 PPM MIBC 6 th Scavenger cell 3 Limiting MIBC CCC 2 LDI 23 Original Study LDI 25 Re-Study 1 LDI 23 Pilot Plant J g (cm/s) 1 Lac des Iles Case Study LDI 25 w/blendedl Frother Limiting MIBC CCC 1 PPM MIBC 5 PPM MIBC PPM Frother LDI 23 Original Study LDI 25 Re-Study LDI 23 Pilot Plant Additional PG frother added to 6 th cell Note repeatability of 23 and 25 5 ppm MIBC J g (cm/s) Data from Hernandez-Aguilar et al (26) LDI 25 w/blendedl Frother additional frother moves D 32 to match23 pilot plant values 26

27 LDI Pd recovery improvement resulting from decrease in bubble size with increased frother Particle Size Fraction Pd Recovery for D 32 in Specified Bubble Size Range (microns) < 1.2 mm 1.2 mm to > 1.6 mm 1.6 mm Pd recovery across 6 th cell with additional frother to increase %-1mm bubbles (Hernandez-Aguilar et al, 26) 27

28 Maneuvering on the Process Roadmap - A benchmarking tool Sb (1/s) C B A J g (cm/s) CCC99 CCC9 CCC75 CCC5 CCC Increasing S b by J g alone will achieve only a limited increase and loose small bubbles Increasing S b by increasing frother concentration, CCCX, is far more effective than increasing J g Frother Jg D32 Sb A CCC B CCC eliminated small bubbles C CCC increased small bubbles 28

29 D 32 (mm) S b (s -1 ) Do you know where your plant is located on the D 32 -S b -J g road map? 5 1 PPM Frother 4 CCC - Maximum D 32 8 CCC99 - Maximum S b 4 PPM DF PPM DF25 2? 4? 16 PPM DF CCC99 - Minimum D PPM DF25 CCC - Minimum S b J g (cm/s) J g (cm/s) 32 PPM DF25 16 PPM DF25 8 PPM DF25 4 PPM DF25 PPM Frother Note: These curves are for DF25 equivalent concentrations based on the D 32 model equations. Curves for other frothers will be somewhat different 29

30 Conclusions 1. A robust empirical bubble size (D 32 ) and bubble surface area flux (S b ) model is developed incorporating the key operating variables (J g, frother type and concentration, viscosity and gas density) 2. The critical role of frother in a plant s flotation performance is demonstrated 3. The model and process road map provide a powerful benchmarking tool for flotation plant optimization 3

31 Acknowledgements NSERC, Metso Minerals, AMIRA P9O Industrial Chair corporate sponsors Flottec (Frank Cappuccitti), Teck, Vale, Xstrata Process Support, Agnico-Eagle, COREM, SGS Lakefield Re, Barrick, Shell Many talented and enthusiastic students, colleagues and collaborators at McGill and at various plant sites

32 For a copies of papers contact: nessetech@bell.net Thank You 32