Gas Cyclone Performance Prediction: A State-of-the-Art Review of Theoretical Modeling Approaches

Document Type : Review Article

Authors

1 1 Department of Mechanical Engineering, Semnan University, P.O. Box 35131-191, Semnan, Iran

2 Behbahan Khatam Alanbia University of Technology, Department of Mechanical Engineering, Faculty of Engineering, Behbahan, Iran

10.22075/jhmtr.2025.37145.1693

Abstract

Existing investigation presents numerous theoretical frameworks for analyzing conventional gas cyclones, focusing on key performance indicators (KPIs) such as inlet velocities, pressure drop, and collection efficiency. These KPIs are critical in industries where understanding the transport and behavior of solid particles is paramount. Traditionally, predicting the complex swirling gas flow within these cyclones has relied on empirical studies, which are both resource-intensive and time-consuming. While theoretical models offer a potentially more efficient and cost-effective approach, they have received comparatively less attention in previous investigations of overall gas cyclone performance. This research endeavors to rigorously evaluate the accuracy of established gas separator theories. The methodology involves comparing theoretical predictions with numerical simulations and experimental data obtained at a controlled solid loading rate of 1 g/m3, across velocities of 5 and 10 m/s. A notable consensus emerged, favoring Muschelknautz's approach for predicting collection efficiency. Similarly, the Lapple and Shepherd model demonstrated utility in estimating pressure drop under conditions of low solid loading. However, several scholars have highlighted discrepancies arising from the influence of wall friction within gas cyclones and a general insensitivity to the particle phase within these models. This section provides an overview of the published CFD simulation studies on cyclones, specifically examining the effects of high particle loading, at room and at high temperatures. Furthermore, the Mothes and Löffler model was identified as capable of accurately predicting the natural vortex length, a critical parameter for the design and optimization of conventional gas cyclones.

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Articles in Press, Accepted Manuscript
Available Online from 26 October 2025
  • Receive Date: 17 March 2025
  • Revise Date: 08 September 2025
  • Accept Date: 26 October 2025