CFD-DEM simulation and optimization of gas-cyclone performance with realistic macroscopic particulate matter

Abstract

Most of research concerns have been focused on developing new methods and parameters to make the cyclone separator performance better. In this work, the inverse-flow cyclone type geometry was performed and optimized through the modulation of changing the position and dimensions of the involute inlet portion and cyclone barrel section length at a fixed inlet air velocity of 30 ms−1. Cyclones of different inlet sizes and portions were computationally modeled which named as cyclones I, II, III, IV, and V. The study was successfully accomplished for two heterogeneous groups of particulate matter mixed with air flow for applications pertinent to agricultural engineering. To capture the phenomena of constitutive air-granular materials behavior in the optimized separator, numerical simulations were generated using one-way coupling of commercial ANSYS-Fluent® 18.0 (CFD) and Rocky® 4.13 (DEM) software, which is considered as the first head start research approach in the cyclonic separation and purification field. Discrete Element Method (DEM) which was represented by Rocky® package simulates the movement of each particle individually, taking into consideration the interaction and collision of the particles. Whereas, the highly curved streamlines and the chaotic turbulence of the continuum air flow in the cyclone separator were modeled through the Computational Fluid Dynamics (CFD-Fluent®) technique using advanced turbulence model RNG k-ε. The numerical results successfully captured the effects of new geometrical modifications done on the original cyclone separator. Numerically, the cyclone inlet height significantly improved the cyclone performance by increasing the separation efficiency, cleaning efficiency, and cyclone effectiveness, while other parameters had a negative effect. These data were useful for considering cyclone (III) as the most suitable modification and optimization design geometry for harvesting jojoba seeds with the lowest operation cost and highest performance.