TIME‑RESOLVED AND KINETIC SIMULATION FRAMEWORK FOR MULTICYCLONE DUST COLLECTORS IN AIR‑QUALITY CONTROL
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Abstract
Multicyclone dust collectors are considered essential devices for the removal of particulate matter from large industrial gas flows. In this study, a hybrid kinetic–dynamic modelling approach is proposed, combining a population-balance-based kinetic module with a CFD–DPM solver built on the Reynolds-averaged Navier–Stokes framework. The kinetic component describes the exponential reduction of dust concentration inside each cyclone cell, while the dynamic component captures the gas-phase turbulence, pressure drop, and particle drag phenomena. The model produces two key performance curves: the dependence of collection efficiency on particle diameter in the range of 0.1–10 µm, and the time-dependent decay of outlet dust concentration over a 60-second interval. Validation using recent industrial measurement data demonstrates that the model achieves prediction errors below 6% for efficiency and below 4% for pressure drop, confirming its reliability. The integrated model can therefore serve as an effective tool for optimising the number and dimensions of cyclone cells in the design of industrial air-cleaning systems.
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