4.3 Article

Multiphase CFD Modelling of Mineral Separators Performance: Validation Against Tomography Data

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SPRINGER INDIA
DOI: 10.1007/s12666-016-0995-4

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Hydrocyclone; Dense medium cyclone; Column; Computational fluid dynamics; Tomography

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This paper aims on application of computational fluid dynamic (CFD) modelling on two-phase and multiphase flows in 75 mm conventional hydrocyclone, 350 mm dense medium cyclone (DMC) and 100 mm diameter laboratory column flotation. Along with classification experiments, a dual-planar high speed electrical resistance tomography (ERT) is used to measure the internal flow dynamics in situ in 75 mm hydrocyclone and column flotation at different operating conditions. Experiments are carried out in 75 mm hydrocyclone for different operational parameters and feed solids content varying in the range of 0-30 wt%. Results are presented in terms of the air core diameter and solids volume fraction contours using Maxwell's conductivity equation. It is confirmed by ERT that the air core occupied area and wall solids conductivity levels decreases with increasing the feed solids concentration. Similarly, ERT is used to estimate the mean gas hold-up and radial distribution in order to understand the hydrodynamics of the column flotation. The effect of air superficial velocity and liquid flow rate on gas hold-up is discussed. Algebraic slip mixture model modified with lift, drag and rheology is used to predict the air core size, the solid concentration distribution and classification performance for the hydrocyclone. Validation of air core size and mean solid volume fractions by ERT measurements with the CFD simulations is attempted. The CFD predicted air core radius and medium segregation in the DMC is validated against literature based gamma ray tomography data. Further discrete phase model (DPM) is used to track and measure the residence times of different size and density coal particles. CFD predicted gas hold-up in the column flotation is also validated against in-house measured ERT and imaging data.

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