Potential for interactive design simulations in discrete element modelling

This study investigates the potential for combining lower fidelity models with high performance solution strategies such as efficient graphical processing unit (GPU) based discrete element modelling (DEM) to not only do simulations faster but differently. Specifically this study investigates interactive simulation and design for which the simulation environment BlazeDEM-GPU was developed that allows researchers and engineers to interact with simulations. The initial results prove to be promising and warranting extensive research to be conducted in future which may allow for the development of alternative paradigms. In addition to the design cycle, the role that this interactive simulation and design will play in education is invaluable as an in-house corporate training tool for young engineers to actively train and develop understanding for specific industrial processes. This would also allow engineers to conduct just-in-time (JIT) simulation based assessment of processes before commencing on actual site visits, allowing for shorter and more focussed site excursions

Validation of the gpu based blaze-dem framework for hopper discharge

Understanding the dynamical behavior of particulate materials is extremely important to many industrial processes, with typical applications that range from hopper flows in agriculture to tumbling mills in the mining industry. The discrete element method (DEM) has become the defacto standard to simulate particulate materials. The DEM is a compu- tationally intensive numerical approach that is limited to a moderate amount (thousands) of particles when considering fully coupled densely packed systems modeled by realistic par- ticle shape and history dependent constitutive relationships. A large number (millions) of particles can be simulated when the coupling between particles is relaxed to still accurately simulated lesser dense systems. Massively large scale simulations (tens of millions) are possi- ble when particle shapes are simplified, however this may lead to oversimplification when an accurate representation of the particle shape is essential to capture the macroscopic transport of particulates. Polyhedra represent the geometry of most convex particulate materials well and when combined with appropriate contact models predicts realistic mechanical behavior to that of the actual system. Detecting collisions between polyhedra is computationally ex- pensive often limiting simulations to only hundreds of thousands of particles. However, the computational architecture e.g. CPU and GPU plays a significant role on the performance that can be realized. The parallel nature of the GPU allows for a large number of simple independent processes to be executed in parallel. This results in a significant speed up over conventional implementations utilizing the Central Processing Unit (CPU) architecture, when algorithms are well aligned and optimized for the threading model of the GPU. We recently introduced the BLAZE-DEM framework for the GPU architecture that can model millions of pherical and polyhedral particles in a realistic time frame using a single GPU. In this paper we validate BLAZE-DEM for hopper discharge simulations. We firstly compare the flow-rates and patterns of polyhedra and spheres obtained with experiment to that of DEM. We then compare flow-rates between spheres and polyhedra to gauge the effect of particle shape. Finally we perform a large scale DEM simulation using 16 million articles to illustrate the capability of BLAZE-DEM to predict bulk flow in realistic hoppers

Autoconception d'un module numérique d'autoformation par les apprenants eux-mêmes : application pour l'apprentissage d'un logiciel de DAO

Ce travail se propose de présenter un bilan intermédiaire d'une expérience pédagogique (AAPMA) qui consiste à mettre en place par des étudiants-ingénieurs eux-mêmes un module d'autoformation pour leur propre promotion (Autoformation à AutoCad). Un premier bilan montre que le fait de rendre les étudiants à la fois apprenants et formateurs dans un contexte d'autoformation tend à une appropriation du module plus importante et une responsabilisation de la part des étudiants-ingénieurs. This work proposes to present an intermediate feedback of a pedagogical experiment which consists in designing a self-training module by students-engineers themselves for their own class (self-training at AutoCad). The first feedback shows that making students both as learners and trainers in an autotraining context leads the students to appropriate the module and to take responsibility

Numerical study on the effect of particle shape on mixers

Homogenization of particulate systems is a critical part in the processing of particulate materials to achieve consistency and ensure product quality. Homogenization is achieved by mixing, the aim is to obtain a final mixture that is homogeneous when mixing individual particulate constituents, in the sense of a uniform spatial mass distribution. Although there is always some measure of heterogeneity in a mixture this can be quantified by Gys sampling theory. This is critical for pharmaceutical industries in which it is essential that the variance of the active ingredients between tablets are within specified bounds. Although there have been numerous numerical studies on mixing using the Discrete Element Method (DEM), most studies to date have incorporated significant simplifications to reduce the computational time such as using mono-disperse size distributions, scaling up of particle size and spherical estimations of shape. The development of GPU based DEM simulations in the past few years significantly increased the number of spherical particles however most often at the expense of simplifying the physical interaction between particles. This oversimplification of particle shape has much wider primary implications as primary contact mechanisms such as angularity and locking are omitted. This is important in the pharmaceutical industry where the feed powders are often made from crystalline solids in which the shape of the individual particles are polyhedral. As this study demonstrates, this is significant in that the underlining dynamics of polyhedral particles is vastly different to that of spherical particles, resulting in tighter packing fractions different flow patterns, and percolation. In this paper we use the GPU based DEM code BlazeDEM3D-GPU to study and quantify the effect of particle shape in a high shear blade mixer

3D laser scanning technique coupled with DEM GPU simulations for railway ballasts

Spheres with complex contact models or clumped sphere models are classically used to model ballast for railway applications with the Discrete Element Method (DEM). These simplifications omits the angularity of the actual ballast by assuming the ballast is either round or has rounded edges. This is done by necessity to allow for practically com- putable simulations that may consist of a few hundred particles. This study demonstrates that an experimentally validated DEM simulation environment, BlazeDEM-3DGPU, that computes on the graphical processing unit (GPU) is able to simulate railway ballast with a more realistic shapes that includes angularity for railway applications. In particular, a procedure is developed that extracts polyhedral shaped ballast geometries digitized from 3D-laser scanning for use in DEM simulations. The results show that much larger number of particles can be successfully modelled allowing for new possibilities offered by the GPUs to investigate model railway problems using DEM. Specifically, in this study a typical experimental ballast box that contains up to 60 000 polyhedral particles have been simulated with the BlazeDEM-3DGPU computing environment within reasonable computing times

Utilisation conjointe des méthodes des éléments discrets et des éléments finis pour modéliser la compaction de poudres céramiques uranifères agrégées

La simulation des procédés d'élaboration de pièces à partir de poudres passe par la prise en compte du caractère particulaire des matériaux mis en jeux. La méthode des éléments discrets (Discrete Element Method, DEM) est bien adaptée pour cette tâche. Elle permet de calculer le comportement d'un ensemble de particules à partir des forces de contact exercées sur chacune d'elles. Nous montrons comment la DEM peut être utilisée pour alimenter un code aux éléments finis en lois constitutives. Le code éléments finis simule quant à lui le comportement de la pièce entière lors de la compaction en matrice. Nous nous concentrons ici sur la génération des surfaces de charge et de rupture. L'application visée est la simulation de la compaction de poudres d'oxyde d'uranium qui se présentent sous forme d'agrégats poreux. Nous proposons une loi de contact adaptée pour décrire l'indentation, la décharge élastique et la décohésion de ces agrégats

New advances in large scale industrial DEM modeling towards energy efficient processes

Granular material processing is crucial to a number of industries such as pharmaceuticals, construction, mining, geology and primary utilities. The handling and processing of granular materials represents roughly 10% of the annual energy consumption [1]. A recent study indicated that in the US alone, current energy requirements across Coal, Metal and Mineral Mining amounts to 1246 TBtu/yr, whereas the practical minimum energy consumption is estimated to be 579 TBtu/yr, while the theoretical limited is estimated around 184 TBtu/yr [2]. It is evident that design modification allowing for process optimization can play a significant role in realizing a more energy efficient industry sector that can have significant implications on the annual global energy demands. The status quo in industry when facing the complex physics governing granular materials, is that current industry developed strategies to handle granular materials remain overly conservative and often energy-wasteful to prevent or reduce industrial-related bulk material handling problems like segregation, arching formation, insufficient handleability. Granular scale approaches have also been developed to both understand the fundamental physics governing granular flow and to study industrial applications, especially to improve the understanding and estimation of energy dissipation and energy efficiency of granular flow processes. The Discrete Element Method (DEM) proposed by Cundall and Strack [3] is starting to mature and evolve into a systematic approach to estimate and predict the response of granular systems. However, DEM is computationally intensive and is limited by the number of particles that can be considered realistically are limited to hundreds of thousands or low millions. However, before DEM can be practically considered for industrial applications the number of particles need be increased to tens of millions particles for a sufficient amount of processing time. This study discusses new advances and perspectives made possible by the Graphical Processor Unit (GPU) when simulating discrete element models, specifically for granular industrial applications. Attention is specifically focussed on the newly developed BlazeDEM3D-GPU framework for an industrial flow investigation [4]. Note that BlazeDEM3D-GPU is an open-source DEM code developed by Govender et al. [5] that has been validated for industrial ball mill simulations and hopper discharge applications using ten of millions of particles using a single NVIDIA GPU card on a desktop computer [4, 6]. The industrial granular flow investigation considered in this study is of the storage silos located at the industrial concrete central in France. The typical silo diameter is 8m with a height of around 17m. Three dimensional DEM studies were been performed to investigate the influence of particle sizes and inter-particle cohesion on the bulk flow rate and induced shear stresses for various hopper designs located at concrete central. As required for this industrially relevant application, up to 32 million particles were required to be simulated within a reasonable computing time. These simulations were performed within these requirements but only made possible by the utilization of GPUs. These results show that the GPU computing allows for realistically relevant number of simulated particles for the 3D DEM applications within a reasonable time frame. This makes large-scale analysis practically relevant but more importantly allows for a number of analyses to be conducted to steer granular processing solutions towards an increased efficiency in energy utilization

Boundary condition enforcement for renormalised weakly compressible meshless Lagrangian methods

This paper introduces a boundary condition scheme for weakly compressible (WC) renormalised first-order accurate meshless Lagrangian methods (MLM) by considering both solid and free surface conditions. A hybrid meshless Lagrangian method-finite difference (MLM-FD) scheme on prescribed boundary nodes is proposed to enforce Neumann boundary conditions. This is used to enforce symmetry boundary conditions and the implied Neumann pressure boundary conditions on solid boundaries in a manner consistent with the Navier-Stokes equation leading to the accurate recovery of surface pressures. The free surface boundary conditions allow all differential operators to be approximated by the same renormalised scheme while also efficiently determining free surface particles. The boundary conditions schemes are implemented for two renormalised MLMs. A WC smoothed particle hydrodynamics (SPH) solver is compared to a WC generalised finite difference (GFD) solver. Applications in both 2D and 3D are explored. A substantial performance benefit was found when comparing the WCGFD solver to the WCSPH solver with the WCGFD solver realising a maximum speedup in the range of three times over WCSPH in both 2D and 3D configurations. The solvers were implemented in C++ and used the NVIDIA CUDA 10.1 toolkit for the parallelisation of the solvers.http://www.elsevier.com/locate/enganaboundhj2022Mechanical and Aeronautical Engineerin

A study on the effect of grain morphology on shear strength in granular materials

The Discrete Element Method (DEM) has been successfully used to further understand GM behaviour where experimental means are not possible or limited. However, the vast majority of DEM publications use simplified spheres with rolling friction to account for particle shape, with a few using clumped spheres and super quadratics to better capture grain geometric detail. In this study, we compare the shear strength of packed polyhedral assemblies to spheres with rolling resistance to account for shape. Spheres were found to have the highest shear resistance as the limited rolling friction model could not capture the geometric of rotation grains which caused reordering and dilation. This geometric arrangement causes polyhedra to align faces in the shear direction, reducing the resistance to motion. Conversely, geometric interlocking can cause jamming resulting in a dramatic increase in shear resistance. Particle aspect ratio (elongation and fatness) was found to significantly lower shear resistance, while more uniform aspect ratio’s increased shear resistance with shape non-convexity showing extremes of massive slip or jamming. Thus, while spheres with rolling friction may yield bulk shear strength similar to some polyhedra with a mild aspect ratio, the grain scale effect that leads to compaction and jamming from rotation and interlocking is missed. These results shed light on the complex impact that individual grain shape has on bulk behaviour and its importance

BlazeDEM3D-GPU A Large Scale DEM simulation code for GPUs

Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing. Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers, silos and ball mills, as laboratory scale tests comes at a significant cost. However, the computational time required to simulate an industrial scale simulation which consists of tens of millions of particles can take months to complete on large CPU clusters, making the Discrete Element Method (DEM) unfeasible for industrial applications. Simulations are therefore typically restricted to tens of thousands of particles with highly detailed particle shapes or a few million of particles with often oversimplified particle shapes. However, a number of applications require accurate representation of the particle shape to capture the macroscopic behaviour of the particulate system. In this paper we give an overview of the recent extensions to the open source GPU based DEM code, BlazeDEM3D-GPU, that can simulate millions of polyhedra and tens of millions of spheres on a desktop computer with a single or multiple GPUs