This study introduces a computational framework for modelling raw chicken breast fillets using the Discrete Element Method (DEM), aimed at providing a baseline efficient simulation model for large-scale poultry handling processes. A bonded multi-sphere meta-particle representation was developed and calibrated through mechanical testing of raw fillets. Compression experiments yielded a Young’s modulus of approximately 48.6 kPa, which informed the stiffness properties of the DEM sub-particle assembly. Numerical Design of Experiments (DoEs) highlighted the need for an unbalanced ratio between normal and shear bond stiffness to ensure correct damping behaviour and preserve realistic flexibility. The framework was validated using a full-scale hopper–conveyor discharge experiment, demonstrating the model’s ability to reproduce key physical behaviours such as large deformations, curling during discharge, and the transition between jammed and free-flow regimes. The simulation closely matched the measured discharge rate, with all chicken fillets discharged within 4 s at a 6 cm gate opening height. The proposed model required approximately 9 mins to simulate a 10-second industrial-scale process, underscoring the model’s practical suitability for simulation-aided design and optimisation of poultry processing equipment.

Powder flowability underlies reliable solids handling, influencing dosing accuracy and production stability. Wood powders are usually cohesive and susceptible to flow problems like bridging because of their irregular, fibrous particles that are hygroscopic and heterogeneous. Two lignocellulosic powders were tested: spruce (softwood) and poplar (hardwood). Their particle size distribution, particle shape, and density were measured experimentally. Crucially, the interparticle parameters that govern powder bulk behavior, which are the cohesion energy density (CED), rolling friction coefficient (μᵣ), and sliding friction coefficient (μₛ), are not directly measurable at the scale and morphological complexity of fibrous wood particles. Therefore, using the Discrete Element Method (DEM), (μₛ,μᵣ, CED) were identified as effective DEM parameters by inverse calibration against rotating drum tests. A novel calibration workflow was developed to compare DEM simulations with real rotating drum experiment indicators, which can be used for unconfined, dynamic flow. These indicators correspond to newly discovered macroscopic flow descriptors that are processed from the powder bed: average projected area Area¯, its fluctuation σArea, and the average surface profile irregularity r²¯. Wood particles were modeled as multi-sphere clumps with different sizes to balance realism and computational cost. The calibrated parameters were: spruce—μ_s=0.10, μ_r=0.367, CED=130 kJ/m³; poplar—μ_s=0.10, μ_r=0.772, CED=100 kJ/m³. Following a comprehensive results analysis, increasing CED and friction parameters deteriorates powder unconfined flowability by promoting agglomeration and particle interlocking. The resulting calibrated DEM inputs provide a baseline for predicting and improving the handling of wood powders in hoppers, feeders, and conveying screws.

The offshore wind industry has grown significantly over the past decade with the increasing demand for clean energy, and over 80% of offshore wind turbines have monopile foundations. The installation of these foundations requires monopiles to penetrate several pre-installed scour protection rock layers before reaching the required penetration depth. With the increasing sizes of both monopiles and the extent of scour protection layers, various challenges arise during the monopile’s driving and self-weight penetration process, such as misalignment and early pile refusal. Lab scale testing and empirical modelling are time-consuming and normally not general enough to be applied to different scenarios. Within the Optimising Pile Installation through Scour Protection (OPIS) project, the high fidelity discrete element method (DEM) has been deployed to consider both the discrete nature and shapes of the scour protection rocks. A double-layer (armour & filter) scour protection with a sand layer underneath was simulated using the DEM. Detailed rock dynamics and the armour rocks dragging down during penetration are revealed and particle-geometry rolling friction is identified as the dominant parameter. The effects of the sand layer thickness and pile wall thickness on penetration resistance are also addressed.

Conventional scour protection installation around monopiles for offshore wind farms involves placement of smaller filter layer rocks and larger armor layer rocks in two separate operations, requiring multiple visits of the rock dumping vessel to the site which increases costs, time spent offshore by the vessels, and consequently carbon emissions. The joint industry project Optimizing Pile Installation through Scour Protection (OPIS), established in 2023, helps reaching the target of energy transmission by streamlining the pile and scour protection installations, reducing costs and carbon emissions associated with offshore wind developments. The project investigates the technical feasibility of pile installation through coarse rock to enhance the feasibility of the operation. A series of small and medium scale laboratory experiments has been conducted, considering different scour protection designs such as single- and double-layer systems, and different rock densities (high and normal density rocks). This paper delves into the physical modelling aspects of the OPIS research project. Furthermore, this contribution elaborates on the design and intricacies of the scaled laboratory tests, providing in-depth insights into the design and implementation of laboratory setups, along with a detailed account of experimental procedures. Moreover, preliminary results and challenges encountered during the experiments are discussed, and innovative solutions devised to overcome specific challenges are highlighted.

Locomotion over granular terrain poses significant challenges for autonomous robotic systems, particularly in coastal regions characterized by loose, shifting sands. To optimize the locomotion on these challenging terrains, a simulation-aided design approach was used to develop a soft, shape-adapting, wheeled locomotion system. A co-simulation framework combining the discrete element method (DEM) and multibody dynamics (MBD) is employed to simulate the locomotion of a wheeled robot on varying sandy soils, covering both dry and wet sandy soil conditions. A shape-adapting wheel design is proposed, incorporating soft, inflatable elements that enable the wheel to transform between lugged and circular configurations. A discretized flexbody approach is adopted to model the interactions between the sandy soil and the soft, flexible bodies of the shape-adapting wheel design. Simulation results demonstrate improved performance of the shape-adapting wheels across a variety of sandy terrains, including slopes and obstacles. Integrating softness into the wheel improves obstacle climbing performance, while a lugged wheel configuration performs particularly well on loose, dry sandy slopes. This DEM-MBD co-simulation further enables efficient evaluation of locomotion strategies without the need for extensive physical prototyping.

Monopiles are the dominant foundation type for offshore wind turbines, accounting for approximately 80% of the installed capacity. Installing offshore monopile foundations on seabeds susceptible to scour erosion requires monopiles to penetrate several pre-installed scour protection rock layers before securing them into the seabed. The accurate prediction of the pile penetration resistance is crucial to ensure successful monopile installations. To complement, and potentially reduce the dependence on the costly and labour-intensive experimental small-scale penetration tests, a numerical model has been developed using the Discrete Element Method (DEM) that captures the discrete nature of interactions between rocks and piles and predicts the resistance during the penetration process. The developed DEM model includes armour and filter rocks represented by multispheres and sand particles represented by spheres. A multistage calibration, verification and validation DEM modelling framework is proposed and examined with small-scale penetration tests conducted using plates and piles in a double-layer scour protection configuration. The sand material model is calibrated and verified using penetrometer tests and the rock material models are calibrated and verified using a plate penetration test. The DEM model with three verified materials predicts the penetration resistance well in small-scale pile penetration tests and proves the validity of the proposed framework. The DEM model presented in this paper facilitates the modelling in areas where traditional continuum-based numerical methods give less accurate predictions and provide insights that are difficult or nearly impossible to obtain through experimental methods.

Segregation of granular materials is a critical phenomenon in various industries, such as food processing, pharmaceuticals, and mining. The Discrete Element Method (DEM) is an effective tool for gaining insight into granular segregation by providing particle-level information and the freedom to model mixtures that are often difficult or impossible to achieve through experiments. To ensure realistic material behaviour and correct representation of segregation, it is essential to calibrate the model parameters systematically. However, in the context of multi-component segregation, it is extremely challenging and computationally expensive to consider all parameters in the calibration procedure since interaction parameters between components must also be considered. This work aims to identify the dominant DEM parameters for modelling multi-component segregation during hopper discharge, chute flow and heap formation in a mixture of pellet and sinter. Utilising a representative example of a multi-component mixture with different sizes, densities and shapes used in blast furnaces, the investigation is done for various initial configurations as well as various mass ratios of the mixture. Our findings revealed that, while only particle-geometry interaction parameters dominate the segregation after the hopper and chute flow, particle-particle parameters are also significant for segregation in the heap. We also demonstrated that the downstream segregation is significantly influenced by the segregation upstream. Moreover, we found that the effect of pellet-sinter interactions is negligible. This research provides insights into the dominant DEM parameters, facilitating more efficient and robust calibration of multi-component models in future research endeavours.

Granular materials play a crucial role in various geotechnical, mining, and bulk handling applications. Understanding their mechanical properties is essential for optimal use in these industries. Traditional experimental methods like Cone Penetration Test (CPT) and open pile testing have limitations on their repeatability and offer little insight into the contact mechanics. The Discrete Element Method (DEM) is a powerful tool for investigating and simulating granular material behaviour at the element scale and provides deeper understanding in geometry-material interactions. However, due to computational costs, spherical particles are often preferred, though they may not always capture realistic particle interactions. In the current study, the packing density and the penetration resistance of particle beds with different particle shapes, including sphere, multi-spheres and polyhedrons, are compared using a plate penetration test modelled in DEM. Sensitivity analyses are performed for sliding friction, consolidation pressure, and Particle Size Distribution (PSD). Results indicate that polyhedral shapes show lower penetration resistance compared to spherical and multi-spherical shapes. Sliding friction has the most significant impact on resistance, while consolidation pressure has minimal effect on porosity. The study highlights the importance of particle shape in granular media modelling and emphasizes the need for further research in this area.

This work aims to identify the most influential DEM parameters for modelling multi-component segregation during heap formation, hopper discharge, and chute flow.

We introduce the open-source package MercuryDPM, which we have been developing over the last few years. MercuryDPM is a code for discrete particle simulations. It simulates the motion of particles by applying forces and torques that stem either from external body forces, (gravity, magnetic fields, etc.) or particle interactions. The code has been developed extensively for granular applications, and in this case these are typically (elastic, plastic, viscous, frictional) contact forces or (adhesive) short-range forces. However, it could be adapted to include long-range (molecular, self-gravity) interactions as well. MercuryDPM is an object-oriented algorithm with an easy-to-use user interface and a flexible core, allowing developers to quickly add new features. It is parallelised using MPI and released under the BSD 3-clause licence. Its open-source developers’ community has developed many features, including moving and curved walls; state-of-the-art granular contact models; specialised classes for common geometries; non-spherical particles; general interfaces; restarting; visualisation; a large self-test suite; extensive documentation; and numerous tutorials and demos. In addition, MercuryDPM has three major components that were originally invented and developed by its team: an advanced contact detection method, which allows for the first time large simulations with wide size distributions; curved (non-triangulated) walls; and multicomponent, spatial and temporal coarse-graining, a novel way to extract continuum fields from discrete particle systems. We illustrate these tools and a selection of other MercuryDPM features via various applications, including size-driven segregation down inclined planes, rotating drums, and dosing silos. Program summary: Program Title: MercuryDPM Program Files doi: http://dx.doi.org/10.17632/n7jmdrdc52.1 Licensing provisions: BSD 3-Clause Programming language: C++, Fortran Supplementary material: http://mercurydpm.org Nature of problem: Simulation of granular materials, i.e. conglomerations of discrete, macroscopic particles. The interaction between individual grains is characterised by a loss of energy, making the behaviour of granular materials distinct from atomistic materials, i.e. solids, liquids and gases. Solution method: MercuryDPM (Thornton et al., 2013, 2019; Weinhart et al., 2016, 2017, 2019) is an implementation of the Discrete Particle Method (DPM), also known as the Discrete Element Method (DEM) (Cundall and Strack, 1979). It simulates the motion of individual particles by applying forces and torques that stem either from external forces (gravity, magnetic fields, etc.) or from particle-pair and particle–wall interactions (typically elastic, plastic, dissipative, frictional, and adhesive contact forces). DPM simulations have been successfully used to understand the many unique granular phenomena – sudden phase transitions, jamming, force localisation, etc. – that cannot be explained without considering the granular microstructure. Unusual features: MercuryDPM was designed ab initio with the aim of allowing the simulation of realistic geometries and materials found in industrial and geotechnical applications. It thus contains several bespoke features invented by the MercuryDPM team: (i) a neighbourhood detection algorithm (Krijgsman et al., 2014) that can efficiently simulate highly polydisperse packings, which are common in industry; (ii) curved walls (Weinhart et al., 2016) making it possible to model real industrial geometries exactly, without triangulation errors; and (iii) MercuryCG (Weinhart et al., 2012, 2013, 2016; Tunuguntla et al., 2016), a state-of-the-art analysis tool that extracts local continuum fields, providing accurate analytical/rheological information often not available from experiments or pilot plants. It further contains a large range of contact models to simulate complex interactions such as elasto-plastic deformation (Luding, 2008), sintering (Fuchs et al., 2017), melting (Weinhart et al., 2019), breaking, wet and dry cohesion (Roy et al., 2016, 2017), and liquid migration (Roy et al., 2018), all of which have important industrial applications.