Issue 39, 2017

Diversity and controllability of particle distribution under coupling vibration and airflow

Abstract

The vertical, horizontal, and three-dimensional (3D) distribution of binary particles with different diameters are investigated simultaneously in a cylindrical container under coupling vibration and airflow. Airflow is blown into the vertically vibrating granular bed from its bottom with vibration frequency of f = 15, 30, and 45 Hz; vibration acceleration Γ = 2–7; and air velocity u = 0–1.82 m s−1 (fluidization number u/umf = 0–1.49). In our experiments, several distribution states have been observed, such as the mixing state, where particles are uniformly mixed; Brazil nut separation (BN), where large particles rise to the top; reverse Brazil nut separation (RBN), where large particles sink to the bottom; horizontal separation (HS), where binary particles separate horizontally; and combined distribution of BN/RBN and HS, in which one type of particles is above the other and close to one side of the container wall. Briefly, the vertical distribution forms five pattern types, and the horizontal distribution has four pattern types. The resultant pattern of 3D distribution exhibits 15 pattern types. These patterns can be always obtained under the conditions of certain control parameters, but the condition differs with the diameter ratio of binary particles. Phase diagrams of vertical, horizontal, and 3D distributions are drawn to provide the excitation condition of various patterns. These experimental results contribute to the further understanding of the entire distribution of particles and the control of particle distribution for different industry requirements.

Graphical abstract: Diversity and controllability of particle distribution under coupling vibration and airflow

Article information

Article type
Paper
Submitted
19 May 2017
Accepted
12 Aug 2017
First published
25 Aug 2017

Soft Matter, 2017,13, 7034-7045

Diversity and controllability of particle distribution under coupling vibration and airflow

L. Li, P. Wu, S. Zhang and L. Wang, Soft Matter, 2017, 13, 7034 DOI: 10.1039/C7SM01001J

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