Mangadody, Narasimha and V T S R, Kumar Reddy
(2012)
Simulating magnetite medium segregation in a dense medium cyclone using rheology based CFD model.
In: 26th International Mineral Processing Congress, 24-28, September 2012, New Delhi; India.
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Abstract
The complex nature of multi-phase flow in dense medium cyclones has restricted plant operators and designers to rely on empirical equations for predicting the performance. A number of empirical cyclone models have been developed in the past (Wood, 1990; Dunglison, 2002). In recent years, this subject has been broached with computational fluid dynamics (CFD). Most of the CFD models have not considered the correct rheological behavior of magnetite medium while simulating the medium segregation inside the cyclone. These models mostly predict excessive underflow volumetric flow rates. In this paper simulations of magnetite medium in a dense medium cyclone, were conducted in FLUENT where the particle phases were simulated using the modified Mixture model. The turbulence was resolved using Large Eddy Simulation (LES) model. The rheological behavior of medium was considered in the form of Granular viscosity, Newtonian and Non-Newtonian models corrected with particle loadings and fraction of ultrafines. Multi-phase simulations using granular viscosity option although predict the overall split product medium densities reasonably close to experiments, the mixture viscosity values are restricted to substantially lower values, similar to water viscosity. Simulations using Newtonian viscosity model corrected with particle loading, and fine fraction below 53μm size is predicting overall mixture viscosity levels well over water viscosity levels, but under predicting the under flow the underflow medium density. Multi-phase simulations using Non-Newtonian Herschel-Buckley model, calibrated for superfine magnetite medium measured viscosities, is closely predicting the medium segregation with gamma ray tomography data. Overall predicted product medium densities, underflow volume split are close to the experimental data. This model is can be further used to simulate coal portioning and hence in developing new designs.
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