DEM study and machine learning model of particle percolation under vibration

Abstract

This paper aims to understand model the effect of vibration on particle percolation. The percolation of small particles in a vibrated bed of big particles is studied by DEM. It is found the percolation velocity (Vp) decreases with increasing vibration amplitude (A) and frequency (f) when the size ratio of small to large particles (d/D) is smaller than the spontaneous percolation threshold of 0.154. Vibration can enable percolation when the size ratio is larger than 0.154, while Vp increases with increasing A and f first and then decreases. Vp can be correlated to the vibration velocity amplitude under a given size ratio. Previous radial dispersion model can still be applied while the dispersion coefficient is affected by vibration conditions and size ratio. Furthermore, a machine learning model is trained to predict Vp as a function of A, f and d/D, and is then used to obtain the percolation threshold size ratio as a function of vibration conditions.