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.

Sodium borohydride (NaBH₄) is a promising hydrogen carrier for maritime applications due to its high gravimetric and volumetric energy densities compared to compressed or liquefied hydrogen. As a solid granular material, NaBH₄ can be stored under atmospheric pressure and room temperature, eliminating the need for extreme pressures, or cryogenic conditions. Although NaBH₄ is hygroscopic and can become cohesive when exposed to humid environments, when stored and handled sufficiently dry it remains free-flowing, which is essential for reliable conveying, storage, and discharge operations. Designing equipment for these processes requires an accurate understanding of NaBH₄’s free-flowing behaviour, motivating the need for modelling tools. To address this, we model granular, free-flowing NaBH₄ using the Discrete Element Method. Granular flow behaviour depends strongly on the flow regime—defined by the applied shear and confining pressure through the inertial number—and practical handling systems typically operate in the dense flow regime; consequently, this study focuses on dense-flow conditions. A standard calibration–verification–validation methodology is applied, using a ledge test and rotating drum for calibration and verification, and an inclined surface test for validation. In parallel, we evaluate the inertial number across all setups using a velocity-based approach to characterise both the global flow regime and locally occurring flow regimes within the flowing layer. Rather than assigning a single characteristic value per setup, we demonstrate that distinct segments exhibit different inertial numbers, indicating that the inertial number is spatially dependent.

Soft robotics requires structural systems capable of performing complex and programmable deformations to adapt to unstructured or dynamic environments. Shape memory materials (SMMs) offer a promising solution owing to their shape memory effect and stimulus-responsive adaptability. However, actuators relying on a single type of SMM are often constrained by nonlinear actuation behavior and limited stiffness variation, which restrict their ability to achieve coordinated, multifunctional responses. Addressing these challenges, this study introduces a hybrid programmable morphing structure that integrates a shape memory polymer (SMP) and a shape memory alloy (SMA) to realize cooperative actuation and adaptive stiffness variation within a single unit. In the proposed configuration, the SMA springs act as thermally activated actuators that generate deformation. The SMP cylindrical core employs its shape memory effect to realize reversible shape locking and serves as a thermal switch that enables controlled stiffness variation through temperature regulation. A coupled numerical model was established to describe the cooperative behavior between the SMA and SMP components, and the numerical results were validated through experimental testing. The agreement between simulations and experiments confirms the feasibility and repeatability of the proposed design. The structure achieves a maximum bending angle of 55° under dual-SMA actuation and 42° under single-SMA actuation, while maintaining any intermediate shape during thermal cycling. Furthermore, the hybrid system demonstrates a reversible six-fold increase in stiffness and a motion range extending up to three times its original length, representing a significant improvement over conventional single-material soft actuator. Moreover, the proposed hybrid structure offers a flexible strategy for programmable morphing and demonstrates scalable applicability in practical applications, such as adaptive grasping, reconfigurable locomotion, and environmental exploration. In conclusion, this work provides a feasible and generalizable framework for integrating multiple SMM into programmable morphing structures which can be applied into multifunctional soft robotic systems.

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.

In blast furnace ironmaking, a mixture of iron ore pellets and sinter is charged in layers at the furnace top, with particle velocities reaching up to ∼10 m/s at the stock surface. The inherent differences in particle size, shape, and density between pellets and sinter pose challenges for maintaining a uniform mixture during this high-velocity charging, leading to segregation and uneven material distribution. This non-uniformity can negatively affect furnace efficiency and stability. Understanding segregation during charging is therefore crucial for optimizing the ironmaking process. The Discrete Element Method (DEM) can offer valuable insights, provided that the model parameters are calibrated and verified. This study presents a calibrated DEM model for a pellet–sinter mixture with a 50–50 mass ratio of both components. A novel high-velocity laboratory setup was used to simultaneously measure five different key performance indicators (KPIs) related to flow and packing behavior at various discharge heights, corresponding to different flow velocities. Calibration was performed at the highest flow velocity, representative of actual blast furnace conditions. The process involved creating response surface models for each KPI and using a multi-objective optimization approach with a desirability function to determine the model parameters. A step-wise calibration strategy was employed, first optimizing pellet and sinter interaction parameters individually, followed by calibration of the pellet–sinter interaction parameters. This approach proved effective, as the calibrated model accurately reproduced experimental data. Results also suggest that the calibration outcome is flow-invariant in this setup, with the model successfully predicting flow and packing behavior at lower discharge heights.

Segregation of the ferrous burden during blast furnace (BF) charging can cause uneven layer formation at the furnace throat, reducing bed permeability and disrupting gas–solid interaction. This study applies a discrete element method (DEM) model to the industrial-scale BF charging system (from the skip car to top hopper discharge) to examine segregation under real operating conditions. The model includes the full ferrous mixture (pellets, sinter, lump ore, and nut coke) and the real-scale geometries. A reference case representing current practice is analysed in detail and compared with systematically varied case studies. The results show that segregation generally decreases from the skip car to the top hopper due to partial remixing, but strong segregation is still observed. Lump ore and nut coke exhibit the strongest segregation, while pellets remain the least segregated. The order of pellets and sinter in the weighing bunkers strongly influences their segregation patterns, whereas variations in the sinter particle size distribution (PSD) and particle shape have only limited effects. The insights from this study provide a basis for developing practical strategies to mitigate segregation in industrial BF charging.

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.