A large share of global shipped tonnage concerns dry bulk materials, which are typically unloaded from ships using large mechanical grabs, a slow process with long waiting times and high emissions. This process can be modelled and its performance improved using the Discrete Element Method (DEM). While such research has been performed for materials like iron ore or coal, no accurate and efficient material model exists for coarse limestone, a coarse material that is difficult to penetrate and for which large improvements in handling efficiency are expected, reducing waiting times and emissions. Previous research using a material model with two-spherical particles focused on the penetration resistance of limestone and experimentally determined various characteristics of limestone, but with a computational time of 18 days did not result in a feasible full-scale material model . Particle shape-related characteristics like interlocking and dilatancy are expected to influence the bulk material behaviour of limestone, to be taken into account when making a numerical model.

A numerical model is to be created in order to evaluate and improve the grab performance in limestone. Using the state of the art experimental results as a basis, additional experimental setups were designed to determine additional material and particle characteristics, like coefficients of sliding friction, the Angle of Repose (AoR). A method was set up to classify the particle shape. Degrading particles showed that the particle roundness (angularity) influences a particle’s frictional behaviour (and thus AoR). Full-scale experiments were performed in-situ using a full-sized grab.

A DEM material model of limestone is created based on a smaller-scale lifting cylinder (AoR) setup and a full-scale grab setup. Ten different particle shapes are modelled using 5-spherical particles fitted to particle templates, while discarding the PSD. The model is first calibrated for the small-scale setup. These settings are then verified and optimised for the full-scale setup, with the optimised model coarse-grained with a factor of ×1.5, resulting in a calculation time of 3 hours and a standard deviation of 1.8% of the mean. The model accurately represents payload, knife penetration, and knife path.

Design improvements are modelled. Analysis showed that small design improvements are possible, increasing the grab performance significantly. The thesis showed that it is possible to make an efficient material model which accurately represents the coarse material by using multi-spherical particles reflecting the material’s particle shape distribution and calibrated based on a lifting cylinder (AoR) and full-scale (payload, knife path, penetration) experiment. The selection of particle shapes allows for accurate modelling of interlocking and dilatancy in a computationally efficient material model.

Locomotion over granular terrain poses significant challenges for autonomous robotic systems, particularly in coastal regions characterized by loose, shifting sands. These sandy surfaces exhibit unpredictable behaviour, alternating between solid-like and fluid-like states, making movement across them particularly difficult. Ensuring reliable mobility on such terrains is essential for tasks like environmental monitoring, infrastructure inspection, and search-and-rescue missions. This thesis presents a simulation-aided design approach to develop a soft, shape-adapting, wheeled locomotion system optimized for sandy terrains. 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. DEM models individual sand particles and their contact interactions, while MBD captures the robot’s motion and mechanical behaviour. Using this approach, a shape-adapting wheel was designed with inflatable soft elements placed between rigid lugs. The inflation state changes the wheel geometry, allowing it to adapt to different terrain conditions. The wheel can transform between a lugged configuration for increased traction and a circular configurations for smoother travel. The robot prototype, built around this wheel concept, was evaluated in simulations on various sandy soils, including dry, wet, and very wet sand. Additionally, the prototype was evaluated in simulations on different terrain configurations, such as slopes and obstacles. 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. Overall, the DEMMBD co-simulation framework offers a powerful tool for evaluating and optimizing robotic locomotion strategies in granular environments. It enables rapid iteration of design configurations without the need for extensive physical prototyping, reducing development time and cost.

This study investigates the feasibility of scaling Discrete Element Method (DEM) simulations to model the penetration of monopiles through protective scour armour layers in offshore wind turbine installations. A reference model is constructed to simulate monopile penetration through a scour protection layer composed of granular material. Three distinct scaling approaches are investigated: exact scaling, coarse-graining technique, and hybrid scaling. The results of this study show that scaled DEM simulations can achieve high reliability and accuracy when appropriate scaling techniques are selected based on specific simulation requirements, proper scaling laws are applied with careful consideration of physical principles, and scaling limits are respected. The successful implementation of these scaling techniques opens new possibilities for efficient simulation of industrial-scale offshore wind turbine installations while maintaining physical accuracy.