MATHEMATICAL-MODELLING METHODS FOR AIR CLEANING IN MULTICYCLONE DUST COLLECTORS
Keywords:
Multicyclone, cyclone separator, particulate matter, CFD, Leith–Licht model, pressure drop, PM₂․₅, air-pollution control, energy efficiency.Abstract
This paper presents an integrated mathematical framework for predicting the aerodynamic behaviour and particulate collection efficiency of multicyclone dust collectors that are widely deployed as pre-cleaners in high-temperature, high-dust industrial gas streams. The approach couples classic empirical models (Leith–Licht and Stairmand formulae), pressure–loss correlations, and three-dimensional Computational Fluid Dynamics (CFD) simulations based on the Reynolds-Averaged Navier–Stokes (RANS) equations and a Discrete Phase Model (DPM). The hybrid methodology is verified against laboratory and full-scale operating data for medium-pressure (ΔP < 1 kPa) units treating flue gases laden with PM₂․₅. Results reveal the trade-off between inlet velocity, pressure drop and fine-particle capture, and deliver design heuristics that boost PM₂․₅ removal by 12 % while lowering fan energy consumption by 0.3 %. Practical recommendations and research directions for nano-aerosol control and AI-assisted adaptive operation are outlined.
