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Computational fluid dynamic modeling of hydrocyclones
T.R. Vakamalla, S. Rajendran, M. Padhi,
Published in Elsevier
2023
Pages: 287 - 323
Abstract
A comprehensive computational fluid dynamic multiphase model development for dense slurry flow in hydrocyclone is presented in this chapter. A suitable turbulence model is initially selected by comparing the predicted flow field data against laser measurements. In addition, turbulence intensity levels distribution inside the cyclones are also analyzed to understand the turbulence levels. Particle dispersion using a two-phase flow field is analyzed critically to determine the effect of turbulence on different-sized particles. Further, the algebraic slip mixture model multiphase model is modified with additional shear lift, hindered settling drag forces, and Newtonian rheology and tested at dilute to dense feed solids concentration (0–50wt.%) to predict the performance characteristics in hydrocyclones. The multiphase results in cut size and particle size segregation are presented and compared against experiments. Finally, multicomponent studies with silica and magnetite are performed, and the effect of the addition of heavy-density particles on the light-density particle performance is evaluated. The interaction coefficient is utilized to explain the interaction between components during the classification performance. The centrifugal, drag, and turbulent dispersion forces are quantified and assessed to understand the particle separation mechanism. © 2023 Elsevier Inc. All rights reserved.
About the journal
JournalMineral Processing: Beneficiation Operations and Process Optimization through Modeling
PublisherElsevier