CFD-DEM simulation and experimental validation of air classification for tobacco particles

Abstract

In cigarette processing, the challenge is particularly significant during the air classification of tobacco and stems due to their similar characteristics. This paper employs computational fluid dynamics (CFD) combined with the discrete element method (DEM) to analyze factors affecting separation efficiency and improve performance. The results were validated through laboratory and production line experiments at a 1:1 scale. The tobacco (length: 0 mm–4.75 mm, diameter: 0.32 mm) and stem (length: 0–25.145 mm, diameter: 1.51 mm) were modeled based on production samples. Findings suggest that particle feeding speed primarily impacts tobacco loss rate, while inlet air velocity mainly influences stem removal rate. Optimizing the chamber structure in the simulation resulted in a 63.66 % improvement in separation efficiency. Airflow streamlines, particle distribution, trajectory, and collision behaviors were discussed to illuminate motion characteristics. The flexible particle model moderately influenced separation efficiency and collision behaviors. These insights enhance the understanding of particle separation and the design of separation devices.