Calibration of discrete element method (DEM) models is crucial for the realistic simulation of granular materials. However, it remains a challenging task, especially for multi-component mixtures due to their higher complexity and larger number of parameters involved. This study presents a systematic and computationally efficient calibration framework designed to address these challenges, focusing on pellet-sinter mixtures, as a representative case of two-component mixtures commonly used in blast furnace steelmaking. The framework integrates sensitivity analysis, machine learning-based surrogate modelling with adaptive sampling, and genetic algorithm-driven optimisation techniques to minimise the number of required DEM simulations. Using this approach, we achieved a high-accuracy surrogate model (R² = 0.95) for seven DEM parameters with only 110 data points, highlighting the efficiency and robustness of the framework. These parameters were successfully calibrated with a relative error of less than 2 %. Moreover, the calibrated parameters for the base case (i.e., 50–50 pellet-sinter mass ratio) remained valid across different mass ratios and layering orders, eliminating the need for recalibration. Overall, the proposed framework offers a reliable, cost-effective, and adaptable solution for DEM calibration of two-component mixtures. Its flexibility and efficiency make it a promising tool for extending to more complex systems, facilitating the development of DEM models for a wide range of industrial applications involving granular mixtures.

To reduce global emissions, hydrogen is increasingly considered as an energy carrier for renewable energy storage. However, traditional storage methods for hydrogen such as compression or liquefaction require high pressures, extremely low temperatures, and still result in a low volumetric energy density. As a solution, sodium borohydride (NaBH₄) is proposed as an alternative method to store hydrogen. NaBH₄ is a granular material that can be stored using ambient temperature and pressure, and has a relatively high volumetric and gravimetric energy density compared to traditional hydrogen storage. This paper explores the application of NaBH₄ as a fuel in the maritime industry, and elaborates on how the use of NaBH₄ leads to a circular bunkering (refuelling) process. By using hydrolysis to extract hydrogen from NaBH₄ during vessel operation, a so called spent fuel remains and needs to be stored on the vessel until next port call. Additionally, examples of various bunkering equipment that can be used to design the circular bunkering process of NaBH₄ are presented. Moreover, it explains how design of bunkering equipment depends on the mechanical characteristics of the fuel and spent fuel. The main finding of this work is that NaBH₄ is a promising solution for a sustainable future. Before NaBH₄ can be used as a fuel, vessels and ports need to be adapted to facilitate circular bunkering with such a novel solid-state energy carrier.

In this study we investigate the mechanochemical regeneration of sodium borohydride (NaBH₄) from a system comprising hydrated sodium metaborate ( [Formula presented] ) and magnesium hydride (MgH₂). We explore the individual and joint impact of key operational parameters (rotational speed, milling time, ball-to-powder ratio (BPR), and molar ratio) on the regeneration yield. Furthermore, a method for quantifying chemical conversion is introduced relying only on water and thus, offering environmental benefits. This approach additionally facilitates the production and storage of a “ready-to-use” NaBH₄ solution with minimal losses at room temperature. Notably, a yield of 90% is achieved, with a 20% reduction in rotational speed compared to prior literature. This research contributes to sustainable hydrogen storage and presents practical advancements in mechanochemical processes.

The use of optimization procedures for designing acoustic/elastic metamaterials (A/E MMs) has gained significant interest since they enable the efficient attainment of unique functionalities often contradicting. When it comes to vibration attenuation caused by mechanical stress waves, such as impact loads, the dynamic properties of A/E MMs are optimized so that their wave-control ability is maximized. However, the mechanical performance of A/E MMs during the propagation of such waves is normally not evaluated into the design optimization stages. This may compromise not only the load-bearing capacity of MMs, but also their ability in attenuating vibrations. To prevent such effects, we propose a design strategy that incorporates the stress analysis in the early design phase of A/E MMs subjected to an impact load. The effective mass density approach is applied, from which the vibration attenuation is identified at frequency ranges where the resonator moves out-of-phase in relation to the applied excitation. Regarding to the A/E MM mechanical behavior, maximum von Mises stress is calculated through the transient analysis of a unit cell array subjected to a dynamic load. A Pareto front shows a trade-off behavior between the A/E MM functionalities. With that, we emphasize the importance of incorporating the mechanical performance into the design stage of A/E MMs for vibration attenuation of structures undergoing high impact loads, such as installation of foundations by impact hammering. This brings A/E MMs closer to real applications involving energy filtering at specific frequencies from transient loads, designed in an optimized and efficient way.

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.

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.

High-energy ball milling is a versatile method utilized in mechanochemical reactions and material transformations. Understanding and characterizing the relevant mechanical variables is crucial for the optimization and up-scaling of these processes. To achieve this, the present study delves into differentiating the contributions of normal and tangential interactions during high-energy collisions. Using Discrete Element Method (DEM) simulations, we characterize how operational parameters influence these energy dissipation modes, emphasizing the significance of tangential interactions. Our analysis also reveals how different operational parameters such as ball size, fill ratio, and rotational speed affect the mechanical action inside the milling jar giving rise to multiple operating zones where different modes of energy dissipation can thrive. Finally, we present master curves that generalize findings across a wide range of configurations, offering a tool for characterizing and predicting mechanochemical processes beyond the presented cases. These results provide a robust framework for improving mechanochemical reaction efficiency, and equipment design.

The growth of offshore wind farms is accelerating to meet the renewable energy target by 2030, driving the development of larger offshore wind turbines (OWTs) to boost energy capacity. To support these OWTs, large monopiles are being installed by using impact hammers, which in turn emit low-frequency underwater noise, posing challenges for traditional noise mitigation systems and increasing risks to marine life. To address this, a metamaterial-based cushion (meta-cushion) was proposed, embedding resonators to filter longitudinal waves associated with high underwater noise levels. While prior work has demonstrated the meta-cushion's noise attenuation potential, design guidelines are required for adaptation to various monopile installations. This paper introduces, for the first time, a design methodology for the meta-cushion, which based on the input parameters of the monopile system, it details the procedure for selecting the resonant elements contributing to the attenuation performance and their spatial arrangement on the cushion for enhancing mechanical performance. Such performance indicators are evaluated via finite element simulations and experimental modal analyses. The methodology concludes with a nondimensional study of the spiral resonator, which showed the best attenuation response in experiments, exploring its behavior under varying material and geometric parameters. This methodology enables the development of meta-cushions adaptable to monopile installations under any environmental conditions.

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.

Mechanical metamaterials are architected structures with unique functionalities, such as negative Poisson's ratio and negative stiffness, which are widely employed for absorbing energy of quasi-static and impact loads, giving improved mechanical response. Acoustic/elastic metamaterials, their dynamic counterparts, rely on frequency-dependent properties of their microstructure elements, including mass density and bulk modulus, to control the propagation of waves. Although such metamaterials introduced significant contribution for solving independently static and dynamic problems, they were facing certain resistance to their use in real-world engineering problems, mainly because of a lack of integrated systems possessing both mechanical and vibration attenuation performance. Advances in manufacturing processes and material and computational science now enable the creation of hybrid mechanical metamaterials, offering multifunctionality in terms of simultaneous static and dynamic properties, giving them the ability of controlling waves while withstanding the applied loading conditions. Exploring towards this direction, this review paper introduces the hybrid mechanical metamaterials in terms of their design process and multifunctional properties. We emphasize the still remaining challenges and how they can be potentially implemented as engineering solutions.

The International Maritime Organization aims to achieve full decarbonization by 2050 in response to climate change. This ambitious goal demands well-defined strategies guided by techno-economic assessments. The complexity of global shipping systems makes predicting long-term maritime trade patterns challenging, necessitating scenario-building rather than precise forecasts. Investigating shipping demand scenarios is crucial due to the uncertainty brought by the energy transition and its role as the primary driver of shipping emissions. This paper improves the representation of maritime shipping in Integrated Assessment Models (IAMs) by examining the impacts of climate targets on future shipping demand. A novel econometric model, grounded in advanced gravity theory and integrated with machine-learning algorithms, is proposed to estimate the elasticities of variables in bilateral seaborne trade. By coupling this model with the WITCH IAM, we explore various scenarios, providing deeper insights into trade patterns and their implications. The results show that stricter climate policies and higher carbon taxes reduce GDP due to higher abatement costs, higher fuel prices, and therefore reduced seaborne trade, especially for oil products and containerized cargo. Early adoption of carbon taxes in Europe may shift oil production and consumption patterns, temporarily boosting seaborne trade. Sub-Saharan Africa could experience significant demand growth due to economic and population increases.

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.

Although DEM (Discrete Element Method) was introduced >40 years ago, there are still various challenges in applying it with a certain level of confidence. To develop a realistic material model, calibration, validation, particle shape representation and scaling are well-known challenges that have been studied by various researchers over the past two decades. In addition, once a realistic DEM material model is developed and published in line with open science principles, it is unknown to what extent the calibrated values can be used across software packages. Although a benchmark between 8 open source codes was recently published, it did not cover cohesive materials, rolling friction models, realistic calibrated material behaviour, and commercial software that is widely used in industries.

The aim of this study is to investigate the portability of input parameters between different codes and to identify if software independent calibration is possible. We propose a framework to assist DEM users in industry and academia to reach a software independent DEM simulation when required.

To compare the results between software packages, the framework considers the following aspects: 1) identical implementation of contact models, 2) single contact modelling, 3) bulk level simulation, and 4) identical post-processing. This framework is demonstrated for two contact models (Hertz-Mindlin and Edinburgh Elasto Plastic Adhesive) with rolling friction model and two commercial software packages (EDEM and PFC) but is applicable for any other (open-source) software. Moreover, two realistic calibrated material models are included to cover a range of material characteristics, from free-flowing incompressible materials to cohesive compressible materials. This study shows that individual particle level simulations give identical results, bulk level simulations show differences for both contact models. In general, users should use parameter values from other software packages with caution, especially where critical or sensitive applications are modelled. This paper also highlights the use of novel computation techniques, such as the GPU engine, to achieve practical computation times when modelling industrial applications.

Soft grippers have shown their ability to grasp fragile and irregularly shaped objects, but they often require external mechanisms for actuation, limiting their use in large-scale situations. Their limited capacity to handle loads and deformations also restricts their customized grasping capabilities. To address these issues, a model-based soft gripper with adaptable stiffness was proposed. The proposed actuator comprises a silicone chamber with separate units containing hydrogel spheres. These spheres exhibit temperature-triggered swelling and shrinking behaviors. In addition, variable stiffness strips embedded in the units are introduced as the stiffness variation method. The validated finite element method model was used as the model-based design approach to describe the hydrogel behaviors and explore the affected factors on the bending performance. The results demonstrate that the actuator can be programmed to respond in a desired way, and the stiffness variation method enhances bending stiffness significantly. Specifically, a direct correlation exists between the bending angle and hydrogel sphere layers, with a maximum of 128° achieved. In addition, incorporating gap configurations into the chamber membrane results in a maximum threefold increase in the bending angle. Besides, the membrane type minimally impacts the bending angle from 21.3° to 24.6°. In addition, the embedded variable stiffness strips substantially increase stiffness, resulting in a 30-fold rise in bending stiffness. In conclusion, the novel soft gripper actuator enables substantial bending and stiffness control through active actuation, showcasing the potential for enhancing soft gripper performance in complex and multiscale grasping scenarios.