This research addresses various hydrodynamic aspects and the separation performance of a novel cross-flow filtration hydrocyclone (CFFH) using computational fluid dynamics. A CFFH is a device that combines the desirable attributes of a cross-flow filter and a vortex separator into one unit to separate oil from water. The velocity and pressure fields within the CFFH are estimated by numerically solving the filtered Navier-Stokes equations (by using a Large Eddy Simulation (LES) approach). The Lagrangian approach is employed for investigating the trajectories of dispersed droplets based on a stochastic tracking method called the Discrete Phase Model (DPM). The mixture theory with the Algebraic Slip Model (ASM) is also used to compute the dispersed phase fluid mechanics and for comparing with results obtained from the DPM. In addition, a comparison between the statistically steady state results obtained by the LES with the Wall Adaptive Local Eddy-Viscosity (WALE) subgrid scale model and the Reynolds Average Navier-Stokes (RANS) closed with the Reynolds Stress Model (RSM) is performed for evaluating their capabilities with regards to the flow field within the CFFH and the impact of the filter medium. Effects of the Reynolds number, the permeability of the porous filter, and droplet size on the internal hydrodynamics and separation performance of the CFFH are investigated. Results indicate that for low feed concentration of the dispersed phase, separation efficiency obtained based on multiphase and discrete phase simulations is almost the same. Higher Reynolds number flow simulations exhibit an unstable core and thereby numerous recirculation zones in the flow field are observed. Improved separation efficiency is observed at a lower Reynolds number and for a lower permeability of the porous filter.

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