Mercury DPM: fast, flexible particle simulations in complex geometries part II: applications

MercuryDPM is a particle-simulation software developed open-source by a global network of researchers. It was designed ​ab initio to simulate realistic geometries and materials, thus it contains several unique features not found in any other particle simulation software. These features have been discussed in a companion paper published in the DEM7 conference proceedings; here we present several challenging setups implemented in MercuryDPM ​ . Via these setups, we demonstrate the unique capability of the code to simulate and analyse highly complex geotechnical and industrial applications.These tups implemented include complex geometries such as (i) a screw conveyor, (ii) steady-state inflow conditions for chute flows, (iii) a confined conveyor belt to simulate a steady-state breaking wave, and(iii)aquasi-2D cylindrical slice to efficiently study shear flows.​MercuryDPM is also parallel, which we showcase via a multi-million particle simulations of a rotating drum. We further demonstrate how to simulate complex particle interactions, including: (i)deformable, charged clay particles; and (ii) liquid bridges and liquid migration in wet particulates, (iii) non-spherical particles implemented via superquadrics. Finally, we show how to analyse and complex systems using the unique micro-macro mapping (coarse-graining) tool MercuryCG

Comparing open-source DEM frameworks for simulations of common bulk processes

Multiple software frameworks based on the Discrete Element Method (DEM) are available for simulating granular materials. All of them employ the same principles of explicit time integration, with each time step consisting of three main steps: contact detection, calculation of interactions, and integration of the equations of motion. However, there exist significant algorithmic differences, such as the choice of contact models, particle and wall shapes, and data analysis methods. Further differences can be observed in the practical implementation, including data structures, architecture, parallelization and domain decomposition techniques, user interaction, and the documentation of resources.This study compares, verifies, and benchmarks nine widely-used software frameworks. Only open-source packages were considered, as these are freely available and their underlying algorithms can be reviewed, edited, and tested. The benchmark consists of three common bulk processes: silo emptying, drum mixing, and particle impact. To keep it simple and comparable, only standard features were used, such as spherical particles and the Hertz-Mindlin model for dry contacts. Scripts for running the benchmarks in each software are provided as a dataset

A review of recent work on the discrete particle method at the University of Twente: an introduction to the open-source package MercuryDPM

In this paper we review some recent advances in DEM (DPM) modelling undertaken at the University of Twente. We introduce the new open-source package MercuryDPM that we have been developing over the last few years.\ud MercuryDPM is an object-oriented program with a simple C++ implementation and includes: support for moving and complex walls, such as polyhedra or screw-threads; state-of-the-art granular contact models; multi-species support; specialised classes, allowing the easy implementation of common geometries like chutes, hoppers, etc.; common handler interfaces for particles, walls and boundaries (so all type of objects are changed using the same interfaces); restarting; large self-test suite and numerous simple demos; and, visualisation support, both internal and using Visual Molecular Dynamics.\ud Additionally to these features, MercuryDPM has two major components that, to the best of our knowledge, cannot be found in other DPM packages. Firstly, it uses a novel advanced contact detection method that is able of dealing with multiple distinct granular components with sizes ranging over many orders of magnitude: the hierarchical grid. We explain how this algorithm works and demonstrate the speedup gained over the traditional linked cell approach. This algorithm has lower complexity for poly-dispersed ows which means for the first time large simulations with extremely wide size distributions are feasible.\ud Secondly, we present a novel way to extract continuum fields from discrete particle systems that is applicable to mixtures as well as boundaries and interfaces. The particle data is coarse grained in a way that is by construction compatible with the continuum equations of mass-, momentum-, and energy balance. Boundary interaction forces are taken into account in a self-consistent way and thus allow the construction of a continuous stress field even within one particle radius of the boundaries. The method does not require temporal averaging and thus can be used to investigate time-dependent flows as well as static and steady situations. This coarse-graining method is available from MercuryDPM either as a post-processing tool or it can be run in real time. In real-time mode, it not only reduces the data which has to be stored but also allows boundary conditions etc. to be updated depending on the current macroscopic state of the system, e.g. allowing the creation of a pressure-release wall.\ud Finally, we illustrate these tools and a selection of other features of MercuryDPM via various problems including size-driven segregation in chute flow, rotating drums, and screw-conveyer

Rigid Clumps in the MercuryDPM Particle Dynamics Code

Discrete particle simulations have become the standard in science and industrial applications exploring the properties of particulate systems. Most of such simulations rely on the concept of interacting spherical particles to describe the properties of particulates, although, the correct representation of the nonspherical particle shape is crucial for a number of applications. In this work we describe the implementation of clumps, i.e. assemblies of rigidly connected spherical particles, which can approximate given nonspherical shapes, within the \textit{MercuryDPM} particle dynamics code. \textit{MercuryDPM} contact detection algorithm is particularly efficient for polydisperse particle systems, which is essential for multilevel clumps approximating complex surfaces. We employ the existing open-source \texttt{CLUMP} library to generate clump particles. We detail the pre-processing tools providing necessary initial data, as well as the necessary adjustments of the algorithms of contact detection, collision/migration and numerical time integration. The capabilities of our implementation are illustrated for a variety of examples

Hygroscopicity issues in powder and grain technology

The effect of hygroscopicity on flowability of powders and bulk solids with applications in the packaging industry is experimentally and numerically investigated. Firstly, four granular materials are tested at different water contents to study the impact of relative humidity on some hydro-mechanical properties, namely the hydraulic diffusivity on wetting, as well as the shear strength and compressibility properties of the materials. Next, a capillary model covering a wider water content range –compared to the previous tests– is applied to discrete element simulations of a granular column collapse set-up. These simulations give further insight into important aspects of grain hygroscopicity in packaging and other industrial applications (such as the kinematics of flow and flowability issues), which are outside the scope of conventional experimental testing.Postprint (published version

Rigid clumps in the <em>MercuryDPM</em> particle dynamics code

Discrete particle simulations have become the standard in science and industrial applications exploring the properties of particulate systems. Most of such simulations rely on the concept of interacting spherical particles to describe the properties of particulates, although, the correct representation of the nonspherical particle shape is crucial for a number of applications. In this work we describe the implementation of clumps, i.e. assemblies of rigidly connected spherical particles, which can approximate given nonspherical shapes, within the MercuryDPM particle dynamics code. MercuryDPM contact detection algorithm is particularly efficient for polydisperse particle systems, which is essential for multilevel clumps approximating complex surfaces. We employ the existing open-source CLUMP library to generate clump particles. We detail the pre-processing tools providing necessary initial data, as well as the necessary adjustments of the algorithms of contact detection, collision/migration and numerical time integration. The capabilities of our implementation are illustrated for a variety of examples

Mercury-DPM: Fast particle simulations in complex geometries

Mercury-DPM is a code for performing discrete particle simulations. That is to say, it simulates the motion of particles, or atoms, by applying forces and torques that stem either from external body forces, (e.g. gravity, magnetic fields, etc…) or from particle interactions. For granular particles, these are typically contact forces (elastic, viscous, frictional, plastic, cohesive), while for molecular simulations, forces typically stem from interaction potentials (e.g. Lennard-Jones). Often the method used in these packages is referred to as the discrete element method (DEM), which was originally designed for geotechnical applications. However, as Mercury-DPM is designed for simulating particles with emphasis on contact models, optimized contact detection for highly different particle sizes, and in-code coarse graining (in contrast to post-processing), we prefer the more general name discrete particle simulation. The code was originally developed for granular chute flows, and has since been extended to many other granular applications, including the geophysical modeling of cinder cone creation. Despite its granular heritage it is designed in a flexible way so it can be adapted to include other features such as long-range interactions and non-spherical particles, etc