A software-agnostic benchmark for DEM simulation of cohesive and non-cohesive materials

Abstract

Although DEM (Discrete Element Method) was introduced >40 years ago, there are still various challenges in applying it with a certain level of confidence. To develop a realistic material model, calibration, validation, particle shape representation and scaling are well-known challenges that have been studied by various researchers over the past two decades. In addition, once a realistic DEM material model is developed and published in line with open science principles, it is unknown to what extent the calibrated values can be used across software packages. Although a benchmark between 8 open source codes was recently published, it did not cover cohesive materials, rolling friction models, realistic calibrated material behaviour, and commercial software that is widely used in industries.

The aim of this study is to investigate the portability of input parameters between different codes and to identify if software independent calibration is possible. We propose a framework to assist DEM users in industry and academia to reach a software independent DEM simulation when required.

To compare the results between software packages, the framework considers the following aspects: 1) identical implementation of contact models, 2) single contact modelling, 3) bulk level simulation, and 4) identical post-processing. This framework is demonstrated for two contact models (Hertz-Mindlin and Edinburgh Elasto Plastic Adhesive) with rolling friction model and two commercial software packages (EDEM and PFC) but is applicable for any other (open-source) software. Moreover, two realistic calibrated material models are included to cover a range of material characteristics, from free-flowing incompressible materials to cohesive compressible materials. This study shows that individual particle level simulations give identical results, bulk level simulations show differences for both contact models. In general, users should use parameter values from other software packages with caution, especially where critical or sensitive applications are modelled. This paper also highlights the use of novel computation techniques, such as the GPU engine, to achieve practical computation times when modelling industrial applications.