This work presents the developments in the use of coupled Discrete Element Method and Multibody Dynamics (DEM–MBD) in particle-based system-related fields with a particular focus on the applications in design of bulk handling and processing equipment. We first show the trends in the use of DEM–MBD and present applications in five categories: load-bearing terramechanics, load-loosening terramechanics, bulk material processing, bulk material handling, and vibration attenuation. We present a set of reference simulations with analytical solutions that can be used for DEM–MBD coupling verification. In addition, we address the coupling stability and an approach on its assessment. Furthermore, we present a general framework describing how DEM–MBD models can be developed for specific applications. This includes calibration and validation and shows how these models can be used ultimately for design optimisation. Finally, we give an outlook on the role of DEM–MBD in advancing analysis and design of granular systems.

The design of machinery for handling granular materials relies mainly on empirical methods and in-house engineering knowledge. This traditional approach provides incremental improvements that are often limited. Advancements in simulation and optimization can offer a promising alternative approach. Most of the research involved in improving or optimizing equipment design does not include the realistic performance of the new prototype and as such it is uncertain that the predicted performance is also guaranteed in practice. In this study, a design framework for a new generation of machinery handling granular materials, grabs, has been established that includes a full-scale validation step. This has been proven to lead to a breakthrough in equipment design. This design framework uses a co-simulation between Discrete Element Method (DEM) and Multi Body Dynamics (MBD), thus, capturing operational conditions in full-scale. The DEM simulation supported design step integrated as the main step to generate new prototypes. The performance of the prototype is evaluated by conducting full-scale experiments, thus validating the adequacy of the new design as well as the accuracy of the co-simulation. Through this a full design cycle has been fulfilled and a validated model has been achieved that is independent of specific design configurations.

The traditional design approach of grabs and other bulk handling equipment consists of manufacturing and testing physical prototypes. A novel design approach is to use a co-simulation of MultiBody Dynamics (MBD) and Discrete Element Method (DEM), in which the virtual prototype of a new concept interacts with bulk solids. Therefore, this study develops and validates a full-scale co-simulation that models the grabbing process of cohesive and stress-history dependent iron ore. First, by executing in-situ measurements during the unloading of a vessel, grab-relevant bulk properties of the cargo, such as penetration resistance, are determined. Second, full-scale grabbing experiments are conducted in the cargo hold, which allows the process to be recorded in realistic operational conditions. Third, full-scale co-simulation is set up using the material model that has been calibrated based on an elasto-plastic adhesive contact model. Fourth, the co-simulation is validated by comparing its predictions to experimental data from various aspects, such as the force in cables and the torque in winches. The validated co-simulation proves that the stress-dependent behaviour of cohesive cargo as it interacts with the grab could be captured successfully. Valuable information such as a grab's kinematics and dynamics, as well as the porosity distribution of collected bulk solids, can be extracted from the simulation, supporting engineers to enhance the design and operation of equipment.

Ship unloader grabs are usually designed using the manufacturer's in-house knowledge based on a traditional physical prototyping approach. The grab performance depends greatly on the properties of the bulk material being handled. By considering the bulk cargo variability in the design process, the grab performance can be improved significantly. A multi-objective simulation-based optimization framework is therefore established to include bulk cargo variability in the design process of grabs. The primary objective is to reach a maximized and consistent performance in handling a variety of iron ore cargoes. First, a range of bulk materials is created by varying levels of cohesive forces and plasticity in the elasto-plastic adhesive DEM contact model. The sensitivity analysis of the grabbing process to the bulk variability allowed three classes of iron ore materials to be selected that have significant influence on the product performance. Second, 25 different grab designs are generated using a random sampling method, Latin Hypercube Design, to be assessed as to their handling of the three classes of iron ore materials. Of this range of grab designs, optimal solutions are found using surrogate modelling-based optimization and the NSGA-II genetic algorithm. The optimization outcome is verified by comparing predictions of the optimization algorithm and results of DEM-MBD co-simulation. The established optimization framework offers a straightforward and reliable tool for designing grabs and other similar equipment.

This paper presents a multi-step DEM calibration procedure for cohesive solid materials, incorporating feasibility in finding a non-empty solution space and definiteness in capturing bulk responses independently of calibration targets. Our procedure follows four steps: (I) feasibility; (II) screening of DEM variables; (III) surrogate modeling-based optimization; and (IV) verification. Both types of input parameter, continuous (e.g. coefficient of static friction) and categorical (e.g. contact module), can be used in our calibration procedure. The cohesive and stress-history-dependent behavior of a moist iron ore sample is replicated using experimental data from four different laboratory tests, such as a ring shear test. This results in a high number of bulk responses (i.e. ≥ 4) as calibration targets in combination with a high number of significant DEM input variables (i.e. > 2) in the calibration procedure. Coefficient of static friction, surface energy, and particle shear modulus are found to be the most significant continuous variables for the simulated processes. The optimal DEM parameter set and its definiteness are verified using 20 different bulk response values. The multi-step optimization framework thus can be used to calibrate material models when both a high number of input variables (i.e. > 2) and a high number of calibration targets (i.e. ≥ 4) are involved.

The computation time of Discrete Element Method (DEM) simulations increases exponentially when particle size is reduced or the number of particles increased. This critical challenge limits the use of DEM simulation for industrial applications, such as powder flow in silos. Scaling techniques can offer a solution to reduce computation time. In this paper, we have developed a hybrid particle-geometric scaling approach with a focus on Elasto-Plastic Adhesive contact models. It established relationships between particle scaling factors and DEM contact input parameters. The isolated effects of varying particle size and geometric dimensions on bulk properties were also evaluated using uniaxial consolidation, static angle of repose, and ring shear tests. This paper shows how the particle scaling can be applied together with geometric scaling to incorporate two important aspects of bulk materials, their Elasto-Plastic behaviour and their cohesive forces.

An ideal unit of bulk transport or storage equipment is able to handle cohesive iron ore with consistent productivity. In practice, however, uncontrollable bulk property variations affect the productivity. Therefore, it is important to understand the effect of uncontrollable variations on the process. This study quantifies variability and interdependency of bulk property of a range of cohesive iron ore products. Three different laboratory tests relevant to storage and excavation processes are used. Using a multi-variate experimental plan, three influencing characteristics of iron ore – type, moisture content and consolidation state – are included. A stress-history dependent behavior is captured in both the shear and penetration tests, with the results being highly dependent on the pre-consolidation stress. The outcome of this study enables future research on minimizing the effect of uncontrollable bulk properties variability of iron ore and other cohesive materials in the design procedure of transport and storage processes.

Purpose: The development of bulk material handling equipment can be accelerated and made less expensive when testing of virtual prototypes is adopted. However, the modelling of a grab unloader requires a large volume (77 m3) of iron ore pellets, making the computational costs prohibitive. This paper investigates the extent to which the original particles can be substituted by larger, coarser grains. It is crucial that this particle upscaling does not alter the realistic behaviour of the simulated bulk material, nor its interaction with the bulk handling equipment. Approach: First, our coarse graining technique is explained and set out for the particle system at hand. The material behaviour is then characterized using three laboratory experiments (two angle of repose tests and a penetration test). Next, the results of simulations using two contact models with and without coarse graining with different scale factors are compared with the measured material behaviour and material-equipment interaction. This includes a comparison of the macrobehaviour of the bulk material and the tool interaction of coarser grains in a cutting and sliding process. After reaching a satisfactory verified solution on the laboratory scale, the material behaviour and interaction behaviour of a large-scale experiment are modelled. A simulation model of a grab unloader was used for validation of the chosen coarse graining approach. Findings: Using the scaling method presented, the macroscopic tests indicated consistent material behaviour, regardless of the chosen particle scale for two contactmodels. Scaling of the tool interaction process produced mixed results: the sliding process scaled consistently but the penetration process did not, most likely because it is significantly harder for coarser grains to move since they have to move further to the sides before the tool can pass, leading to higher normal forces and frictional forces on the tip. This inconsistency was compensated for by adjusting the wall friction coefficient in the tip of the penetration tool. Once this adapted coarse graining scheme was applied to the industrial-scale simulation of a grab unloader, it produced consistent particle-scale invariant results. Originality/value: This research is the first to show how coarse graining schemes for DEM simulations can be applied to large-scale bulk handling equipment involving dominance of material equipment interaction through penetration of the bulk material.