A fast adhesive discrete element method for random packings of fine particles

TL;DR

This paper introduces a fast adhesive discrete element method (DEM) that scales particle properties to enable quicker simulations of fine particle packings with adhesion, maintaining accuracy while reducing computational effort.

Contribution

A novel scaling law-based DEM framework and an inversion method for parameter determination are proposed for efficient simulation of adhesive fine particle systems.

Findings

Accurate packing simulations with reduced computational cost.

Validation shows good agreement with original property-based simulations.

Method accelerates DEM for systems with aggregates or agglomerates.

Abstract

Introducing a reduced particle stiffness in discrete element method (DEM) allows for bigger time steps and therefore fewer total iterations in a simulation. Although this approach works well for dry non-adhesive particles, it has been shown that for fine particles with adhesion, system behaviors are drastically sensitive to the particle stiffness. Besides, a simple and applicable principle to set the parameters in adhesive DEM is also lacking. To solve these two problems, we first propose a fast DEM based on scaling laws to reduce particle Young's modulus, surface energy and to modify rolling and sliding resistances simultaneously in the framework of Johnson-Kendall-Roberts (JKR)-based contact theory. A novel inversion method is then presented to help users to quickly determine the damping coefficient, particle stiffness and surface energy to reproduce a prescribed experimental result. After validating this inversion method, we apply the fast adhesive DEM to packing problems of microparticles. Measures of packing fraction, averaged coordination number and distributions of local packing fraction and contact number of each particle are in good agreement with results simulated using original value of particle properties. The new method should be helpful to accelerate DEM simulations for systems associated with aggregates or agglomerates.