Mixing performance analysis of non-cohesive particles in a double paddle blender using DEM and experiments

Discrete element method (DEM) and statistical analysis were employed to analyze the flow patterns and mixing mechanisms of a double paddle blender. The scarcity of analysis of mixing performance of this kind of blender in literature motivated the authors to conduct this research. The DEM input param...

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Veröffentlicht in:Powder technology 2022-01, Vol.397, p.117122, Article 117122
Hauptverfasser: Jadidi, Behrooz, Ebrahimi, Mohammadreza, Ein-Mozaffari, Farhad, Lohi, Ali
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Sprache:eng
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Zusammenfassung:Discrete element method (DEM) and statistical analysis were employed to analyze the flow patterns and mixing mechanisms of a double paddle blender. The scarcity of analysis of mixing performance of this kind of blender in literature motivated the authors to conduct this research. The DEM input parameters were calibrated using an experimentally measured dynamic angle of repose. It was found that the impeller speed and the initial loading pattern had significant effects on the mixing performance. Diffusion and granular temperature analysis explained the mixing quality improvement due to an increase in rpm. Generally, fill level did not affect mixing efficiency. Calculating the Peclet number revealed that diffusion was the dominant mixing mechanism in the current mixer. A statistical equation for RSD in terms of operating parameters investigated was derived. ANOVA results revealed that the interaction between rpm and initial loading pattern had a negligible impact on the mixing quality. [Display omitted] •Mixing of monodisperse particles in a double paddle blender was investigated.•The influence of various operating parameters on mixing quality was studied.•In the double paddle blender, diffusion was the main mixing mechanism.•A statistical model for RSD was developed in terms of the operating parameters.•Impeller speed and loading pattern had significant effects on mixing performance.
ISSN:0032-5910
1873-328X
DOI:10.1016/j.powtec.2022.117122