4.7 Article

Numerical investigation on the mixing mechanism in a cross-torus paddle mixer using the DEM-CFD method

期刊

POWDER TECHNOLOGY
卷 377, 期 -, 页码 89-102

出版社

ELSEVIER
DOI: 10.1016/j.powtec.2020.08.085

关键词

Discrete element method; Signed distance function; Mixing index; Mixing mechanism

资金

  1. China Scholarship Council (CSC) [201906380026]

向作者/读者索取更多资源

This study investigated the impact of operational parameters such as rotational speed, filling level, liquid viscosity, and paddle obliquity on powder mixing performance in a cross-torus paddle mixer. Results showed that higher rotational speed led to more efficient mixing due to enhanced convective motion, while smaller number of particles inside the vessel led to better mixing performance attributed to enhanced diffusive motion. Decreasing liquid viscosity or increasing paddle obliquity also improved mixing efficiency in a diffusive dominant mode.
Studies on powder mixing in industrial mixers are crucial for the improved criteria of mixing equipment design and optimization within various mixing unit operations. In the present study, a series of simulation for the powder mixing in an elaborately designed mixer, called a cross-torus paddle mixer, is conducted using the Advanced DEM-CFD method. The effects of various operational parameters on the mixing performance are analyzed and discussed in detail. Through these investigations, it is found that rotational speed, filling level, liquid viscosity, and paddle obliquity can significantly affect mixing performance. Owing to a much-enhanced convective motion of particles, a higher rotational speed exhibits a more efficient mixing process. Smaller number of particles inside the vessel shows the better mixing performance, which is attributed to an enhanced diffusive motion of particles. Decreasing the liquid viscosity or increasing the paddle obliquity can also result in a more efficient mixing in a diffusive dominant mode. By performing the simulation of mixing behavior in a mono-dispersed system, the present work provides significant evidence and novel insights to further understand the mixing mechanisms. (C) 2020 Elsevier B.V. All rights reserved.

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