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Abstract <p>In the petrochemical industry, a critical challenge is the effective control of the granulometric composition of dispersed materials to optimize reaction processes, improve the quality of final products, and reduce energy consumption. One promising approach in this field involves the development and refinement of equipment capable of achieving high selectivity in the separation of fine-dispersed powder systems. This article examines the fractionation of fine particles in an air stream using a novel multi-vortex classifier. Numerical experiments are conducted in Ansys Fluent using the <i>k</i>−ω SST turbulence model, which ensures accurate modeling of high velocity gradients in the vortex zones. The study aims to numerically investigate the fractionation of a solid dispersed phase in an air stream by varying the structural parameters of the multi-vortex classifier. Based on 3D models of the apparatus, 35 numerical experiments are performed, covering a wide range of adjustable parameters. The simulation analyzes the behavior of fractional efficiency for particle sizes ranging from 1 to 200 μm, identifying five characteristic points on the curve that reflect the boundary and transitional states of the separation process. It is established that increasing the vortex diameter promotes the formation of stable multivortex structures and enhances overall separation efficiency. The highest efficiency and a pronounced extremal curve shape are observed at vortex diameters of 27.5–29 mm. Power-law correlations are derived between characteristic particle sizes and flow velocity ratios, enabling the application of these results for engineering optimization of classifiers operating in petrochemical powder processing.</p>

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Fractional of the Solid Dispersed Phase in an Air Flow in a Multi-Vortex Classifier

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • M. A. Prets,
  • V. E. Zinurov,
  • A. V. Dmitriev,
  • A. M. Muginov

摘要

Abstract

In the petrochemical industry, a critical challenge is the effective control of the granulometric composition of dispersed materials to optimize reaction processes, improve the quality of final products, and reduce energy consumption. One promising approach in this field involves the development and refinement of equipment capable of achieving high selectivity in the separation of fine-dispersed powder systems. This article examines the fractionation of fine particles in an air stream using a novel multi-vortex classifier. Numerical experiments are conducted in Ansys Fluent using the k−ω SST turbulence model, which ensures accurate modeling of high velocity gradients in the vortex zones. The study aims to numerically investigate the fractionation of a solid dispersed phase in an air stream by varying the structural parameters of the multi-vortex classifier. Based on 3D models of the apparatus, 35 numerical experiments are performed, covering a wide range of adjustable parameters. The simulation analyzes the behavior of fractional efficiency for particle sizes ranging from 1 to 200 μm, identifying five characteristic points on the curve that reflect the boundary and transitional states of the separation process. It is established that increasing the vortex diameter promotes the formation of stable multivortex structures and enhances overall separation efficiency. The highest efficiency and a pronounced extremal curve shape are observed at vortex diameters of 27.5–29 mm. Power-law correlations are derived between characteristic particle sizes and flow velocity ratios, enabling the application of these results for engineering optimization of classifiers operating in petrochemical powder processing.