The Effects of the Guide Cone on the Flow Field and Key Classification Performance of an Industrial-Scale Micron Air Classifier

Abstract

In this study, the effects of the structural parameters (SPs) of the guide cone, such as the surface inclination and the material recirculation gap size, on the two-phase flow field and classification performance of a real-sized industrial-scale micron air classifier were investigated. This was achieved using the two-way coupling of a computational fluid dynamics–discrete phase model in ANSYS 2022 R2, with the assistance of a high-performance system (HPC). The objective of this study was to determine the optimal SPs of the guide cone so as to achieve the best classification efficiency and satisfy the required particle size distribution curve, named the know-how curve (KHC), for the particle size range (0 ÷ 400 μm) used in producing quartz-based artificial stone. The bottom diameter (d) of the guide cone (CHL) was altered while keeping the outer diameter of the feeding tube unchanged. As a consequence, the material recirculation gap size was changed, and the size, shape, position, and rotational direction of the vortices formed in the secondary classification space and classification chamber were also changed. These vortices significantly affected the classification performance. Specifically, the classifiers with different guide cone structures, named CHL1, CHL2, CHL3, and CHL4, yielded Newton efficiencies of 75.06%, 87.26%, 95.5%, and 94.02%, respectively. According to the simulation results, the best guide cone structure is recommended to satisfy objectives such as (i) the highest classification efficiency, the smallest cut size, and the smallest classification sharpness index and (ii) those in (i) under the constraint of the required KHC.