CFD analysis of microscopic particle separation in low-volumetric classifiers: DPM tracking and experimental validation for enhanced efficiency using geometric modification strategy

Abstract

The increasing demand for advanced air quality management technologies highlights the need for efficient separators capable of classifying microparticles by size. This study introduces a novel approach of geometric modifications to optimize low-volumetric environmental separators through Computational Fluid Dynamics (CFD) simulations. This study investigated micron particle flow behaviour, vortex strength, and separation chamber design using Lagrangian particle tracking to capture the complex particle–fluid interactions. Key geometry modifications included optimizing internal configurations, such as tube arrangements and discharge tube lengths, which resulted in significantly improved separation efficiency. The CFD simulations were validated against experimental data with flow rates ranging from 10 to 20 LPM (Re = 1008, 1512, 2016), demonstrating flow patterns, vorticity, and particle retention. A major contribution of this study is the particle retention efficiency analysis across a wide range of particle sizes. Particles larger than 10 µm were captured with near-perfect efficiency, while capturing finer particles (1–8 µm) proved more challenging, highlighting areas for future improvement. Notably, increasing the number of separation tubes from 3 to 4 and adjusting their heights led to a 10 % increase in particle retention for particle diameters of 10 and 20 µm. Additionally, higher flow rates, especially at 17 LPM (Re = 1714), increased capture rates for medium-sized particles by prolonging residence times through increased turbulence. This research advances micron particle separation technologies through design optimizations, supported by experimental and numerical analysis. The findings have broad implications for improving the performance of environmental separators in industrial applications, and for future developments in air quality management systems.