Unit Operations in Mineral Processing Prof. Rodrigo Serna Aalto University

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1 Unit Operations in Mineral Processing Prof. Rodrigo Serna Aalto University Operations after enrichment After enrichment, slurries will require further handling Concentrate will be transported to smelters To decrease concentrate handling volumes and to recycle process water, it is a common practice to use dewatering operations for the slurries Tailings will be sent to: Tailings ponds Dry tailings stacks Dangerous Beauty by Garth Lenz Oil sands tailings pond in Canada National Geographic 1

2 Dewatering Dewatering can be performed in stages, typically thickening filtration and drying: Slurry (Concentrate) Conditioning Thermal drying Dry product is classified into: Gravitational (a.k.a. thickening) Centrifugal Widely used dewatering technique Relatively cheap Can handle large throughputs It is based on the density difference between solid particles and liquid carrier Minerals have higher density than water, the most common carrier But this may be problematic if particles are too small, or if carrier is a high density liquor 2

3 Design and operation Thickener tank (top) and flocculation plant (bottom) in an uranium mine (Australia) 2016 Siteforce Australia Pty Ltd Sizing of settling tanks We can determine the liquid linear velocity flowing from the thickner as a funciton of solids content, feed flow rate and thickener area: ( V = X U )W AS Since we need to promote settling of solids, the highest velocity of the liquid cannot exceed the settling velocity of the solids A = X U ( )W RS Question: How do we determine the settling velocity? 3

4 Batch settling curve Zone A: Clear liquid Zone B: Initial solids concentration Zone C: Variable concentration zone Zone D: Settled bed B A B C D A C D A D Solidliquid height interface B A Critical sedimentation point C D t 0 t 1 t 2 t Time Sizing of settling tanks We can calculate settling velocities from the experimental batch settling curve, but this varies as sedimentation progresses A sound approach is to use sedimentation rate at the critical sedimentation point By drawing a tangent to the experimental curve, and knowing that Solidliquid height interface H 0 H H u Slope = sedimentation rate Critical sedimentation point CH = C 0 H 0 t u and R = H H u t u Time 4

5 Sizing of settling tanks Using this approach, we can calculate the thickener area with: H W ŁC A = 0 H 0 ł H u Ł ŁC 0 H 0 łł = W t u ( H H u )t u C 0 H 0 We can see that the required area will be larger for slower settling rates (i.e., longer t u ) This becomes problematic, particularly in the case of very fine particles As can be deduced from Stoke s law: S = 2 ( r s r l ) 9 m gd p 2 In case of sedimentation of fine particles, there are two options: Supply additional force to increase settling velocity (e.g., centrifugal) Aggregate particles into large agglomerates, a process called flocculation Metcon 5

6 Flocculation Solid particles in water will have a similar (negative) charge They will not aggregate spontaneously To form agglomerates, we use: Flocculant molecules, typically, soluble long chain polymers like polyacrylamide (PAM) Coagulants, low molecular weight cationic polymers, e.g., polyamines Naturally repelling solids Coagulation mechanism: Charge neutralization Flocculation mechanism: Bridging Process of separating solids from liquid through a porous medium Cake filtration is the most common type in mineral processing Liquid passing is called filtrate Solids build up is called filter cake Cake filtration is a process involving five steps Cake formation Moisture reduction Cake washing Cake discharge Medium washing 6

7 Filter Medium Its main purpose is to support the formation of cake Once formed, the filter cake is itself the true separation medium Should retain solids without binding Mechanically strong Corrosion resistant Some examples are linen, silk, nylon, metals, glass fiber, polyester Cotton fabrics are among the most favored filter medium due to cost and variety Filters can be classified in two major groups Pressure filter: Positive pressure applied at the feed Vacuum filter: Vacuum is applied at the product end Examples of pressure filters Horizontal pressure filter 7

8 Examples of pressure filters Vertical pressure filter Examples of pressure filters Tube press 8

9 Examples of vacuum filters Rotarydrum filter Continuous operation, one of the most widely used in mineral processing Examples of vacuum filters Disc filter Filter can be cloth or microporous ceramic Gardner Denver Nash (gdnash.com) 9

10 Examples of vacuum filters Horizontal belt filter In order for filtration to occur, there must be a pressure difference driving the flow of filtrate across the filtering media The total resistance in a filter is the sum of the cake resistance and the medium resistance Although for practical purposes, medium resistance is sometimes considered negligible Feed DP mv = am c + R DP = pressure drop across cake and medium [N/m2] m = liquid viscosity [N s/m2] v = filtrate flow rate [m/s] a = specific cake resistance m c = mass of dry filter cake R = specific medium resistance Slurry Cake Medium DP Filtrate (v) 10

11 The cake resistance behavior can be thus deduced by plotting DP mv = am c + R 1. R is zero and a is constant 2. R and a are constant 3. R is constant but a increases due to compression 4. R and a are constant, but filter medium gets dirty 5. R and a get blocked DP/mv m c Another way to see this is that the rate at which filtrate is produced is a function of this driving force (DP): v = 1 A dv dt = DP maw V Ł A +R ł Which can be rearranged to: DP = dv dt m A Ł awv A + R ł = dv dt v = filtrate flow rate [m/s] A = area of filter [m2] V = accumulated filtrate volume [m3] t = time [s] DP = pressure drop across cake and medium [N/m2] m = liquid viscosity [N s/m2] a = specific cake resistance w = feed slurry concentration, dry solids per unit of filtrate volume [kg/m3] R = specific medium resistance maw A 2 ( V +V e ) V e = theoretical volume of filtrate necessary to build a filter cake 11

12 The cake specific resistance depends on the characteristic of the solid particles, as proposed by the CarmanKozeny equation: a = K 2 1e S 0 r s e 3 K = constant, equal to 4,17 S 0 = specific surface area of cake particles e = cake void fraction And the mass of solids collected can be calculated by mass balance m c = w V A The pressure drop equation can also be used in a linearized form to obtain experimental values for resistance dt dv = maw ( A 2 DP V +V e) Running filtration experiments at constant pressure drop (DP), we can calculate values of a With data obtained at various DP, we can obtain a parameter called compressibility value (n), which correlates cake resistance to operating pressure: a = a 0 ( DP) n Data for filtration of calcite; the reported values of cake resistance and compressibility factor are a 0 = 5,53 E09 and n = 0,18 (Mahdi and Holdich, Chem. Eng. Res. Design, 91 (2013) 1145) 12

13 Due to cake buildup, filtration is performed at either: Constant pressure dt dv = maw ( A 2 DP V +V e) Constant filtrate flow rate DP = maw A 2 dv dt V + mr A dv dt And we choose the relevant design equation to calculate filter dimensions (A) based on the desired operating mode, flow and slurry characteristics Calcite filtration data (Mahdi and Holdich, Chem. Eng. Res. Design, 91 (2013) 1145) Final exam Friday :00 13:00 Lecture hall V1 Registration before at (WebOodi) Nickel Tailings #34, Sudbury, Ontario Edward Burtynsky 13

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