Investigation of adequacy of multi-sphere approximation of elliptical particles for DEM simulations

Adequacy of approximation of ellipsoidal particles composed of a set of sub-spheres for numerical Discrete Element Method (DEM) simulations is examined. The algorithm of adaptive hierarchical multi-sphere (MS) model is suggested for composing elliptical particles. Numerical simulation of the piling problem is used as a test problem for evaluating the adequacy of MS model approximation in comparison to the model of smooth ellipses for multiparticle system. The accuracy of MS approximation with the increasing number of sub-spheres is examined in detail by comparison of macroscopic and microscopic parameters of granular dynamics. It was determined that the data on macroscopic parameters yielded by the MS model tend to converge to those of the smooth ellipsoid with the increasing number of the constituent sub-spheres, and the MS model approximates the smooth perfect ellipsoid with a reasonable number of sub-spheres within the limits of the appropriate tolerance. It can be concluded that a multi-sphere model remains a realistic and relatively simple particle model applicable to DEM simulations of the behaviour of the real smooth and rough elliptically shaped particles

Simulation of the normal impact of randomly shaped quasi-spherical particles

The paper reports the modelling of randomly shaped partieles. An emphasis is placed on the illustration of random properties of particles, using simulations with a controlled probability distribution for the depth of the surface profile. The randornly-shaped quasi-spherical particles were described by applying a multi-sphere approximation and a statistical evaluation technique, and the surface of the partieles was approximated using randornly located overlapping subspheres. The concept of statistically similar particles, i.e., partieles characterised by having a similar probability distribution for the depth of the surface profile, was employed for these purposes, and an original method involving the application of a stochastic optimisation was developed. The optimization method was demonstrated by generating statistically similar particles. The contact behaviour was investigated by simulating a random particle impact against a wall, using the discrete element method. It was observed that statistically similar particles did not show statistically similar contact characteristies. The results of this study suggested that the refinement of the multi-sphere model (achieved by increasing the number of subspheres) was non-unique, not only in a deterministic context but also in statistical context, and that this subject requires further investigation

The Impact of the Temperature Control Strategy in Steady-State Virtual Vacuum Simulation on the Spontaneous Evaporation Rate and Corresponding Evaporation Coefficient

In the present paper, we propose a novel simulation approach that allows one to capture the steady-state evaporation into virtual vacuum state by maintaining a constant number of atoms within the liquid phase during the simulations. The proposed method was used to perform virtual vacuum simulations of argon at a temperature of 90 K in order to study the effects of the chosen simulation temperature control approach on the system’s temperature profiles, spontaneous evaporation rates, and the energetic characteristics of the evaporating atoms. The results show that the expected non-uniform temperature profile across the liquid phase can be flattened out by dividing the liquid phase into separately thermostated bins. However, the desired liquid surface temperature can be achieved only when the thermostat region boundary is placed outside the liquid phase. The obtained relationship between the surface temperature and the spontaneous evaporation rate show that the spontaneous evaporation rate and corresponding evaporation coefficient evaluation may change up to 21% when the surface temperature changes in a narrow temperature interval of 2.45 K. Furthermore, the results demonstrate that the thermostat region boundary position has no impact on the energetic characteristics of the evaporating argon atoms, even when the boundary is placed outside the liquid phase

Numerical simulation of mixing and segregation of granular material

Mixing and segregation of granular material, consisting of spherical particles of various sizes, stirred by a periodically moving bar was simulated numerically, using the discrete element method. It was shown that smaller particles of the granulated material tend to sink to the bottom while the larger particles rise to the top. The segregation process depends on mixing, which is more intense for higher values of the dynamic friction coefficient of the particle material. This dependence is similar to the case of hydrodynamics where mixing is more intense in more viscous fluids, but more thorough understanding of this dependence for the case of granular matter requires further investigations

Parallel DEM software for simulation of granular media

The paper describes the development and performance of parallel algorithms for the discrete element method (DEM) software. Spatial domain decomposition strategy and message passing inter-processor communication have been implemented in the DEMMAT code for simulation of visco-elastic frictional granular media. The novel algorithm combining link-cells for contact detection, the static domain decomposition for parallelization and MPI data transfer for processors exchanging particles has been developed for distributed memory PC clusters. The parallel software DEMMAT_PAR has been applied to model compacting of spherical particles in the rectangular box. Two benchmark problems with different numbers of particles have been solved in order to measure parallel efficiency of the code. The inter-processor communication has been examined in order to improve domain decomposition topology and to achieve better load balancing. The speed-up equal to 11 has been obtained on 16 processors. The parallel performance study has been performed on the PC cluster VILKAS of Vilnius Gediminas Technical University, Lithuania