Modern challenges in chemical technology require effective solutions for separating bulk materials into fractions with specified granulometric characteristics. This is especially important for processes involving the handling of fine-dispersed materials, where particle separation plays a key role in improving the quality of the final product and reducing costs. The article presents a multi-vortex classifier designed for particle size fractionation. The aim of the study is to numerically investigate the influence of the geometric parameters of the classifier on its efficiency. Numerical modeling is performed in the Ansys Fluent software environment using the k–ω SST turbulence model and the Discrete Phase Model (DPM) to track particle motion in the gas flow. During the calculations, the inner pipe diameter d and the degree of rectangular slit opening k are varied. It is found that the efficiency of bulk material separation in the multi-vortex classifier is determined by the interaction of airflows through the lower opening of the inner pipe and the rectangular slits. The flow through the lower opening forms an upward current that destabilizes the vortex structure, while the flow through the rectangular slits ensures the stability of the vortices in the annular space. An increase in the inner pipe diameter d leads to a decrease in particle capture efficiency. For example, as d increases from 43 to 66 mm, the average efficiency E decreases from 79.7 to 32.1%, which is associated with the intensification of the destabilizing upward flow. This occurs because the number of rectangular slits increases from 4 to 8 (resulting in a larger total cross-sectional area of the slits), which reduces the effect of the centrifugal forces. A decrease in d contributes to the stabilization of vortices, resulting in additional pronounced efficiency peaks in the fine particle range up to 40 μm. Reducing the degree of rectangular slit opening k to values of k ≤ 20% ensures a sharp increase in particle fractionation efficiency, achieving values greater than 95% for particles with sizes >55 μm. At k ≥ 40%, a significant decrease in the classifier efficiency is observed.
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