Anthony R. Thornton

Laser powder bed fusion (LPBF) is an additive manufacturing technique that utilizes laser-induced melting of specific regions within a powder layer to create complex parts. Achieving high-quality products in LPBF requires the optimization of process parameters based on the unique characteristics of the powder material. Since experimental optimisation can be both time-consuming and costly, we propose a computational model capable of simulating the particle micro-mechanics in LPBF, offering a more cost-effective solution. We have developed a novel thermal discrete particle and contact model that accurately captures the essential phenomena of melting, coalescence, and consolidation within LPBF. Our model assumes that solid particles partially melt under the influence of heat, subsequently coalesce, and form solid bonds during the cooling phase. The rate of coalescence is determined by the material’s surface tension and viscosity as it undergoes melting. To account for phase transitions, we employ an apparent heat capacity method. We first introduce our contact model and provide verification against analytical solutions for a two-particle system. We then demonstrate the efficacy of our model by applying it to a multi-particle example, successfully capturing the coalescence and consolidation behaviour observed in LPBF. The model has been implemented in the open-source code MercuryDPM. The current model is developed for polymer material, but it can be extended to metal and ceramic. Graphical Abstract

Aeolian sand transport on beaches is strongly affected by surface moisture, but its influence on transport evolution remains poorly understood. We present a novel discrete particle modeling framework to systematically investigate how moisture from liquid bridges affects the development of transport toward steady state after initiation. Moist sediment particles are modeled using a particle-based approach with evolving liquid bridges coupled to a one-dimensional airflow solver. The model captures realistic grain-scale collision dynamics under moist conditions and reproduces key features of aeolian transport in the dry limit. Simulations reveal two distinct behaviors: In steady state, the transport rate remains insensitive to moisture as lower saltation concentrations are compensated by higher saltation velocities; in the transient phase, however, increasing moisture prolongs the growth phase and delays the peak in transport rate. This delay arises because sand concentration peaks increasingly later than mean saltation velocity as moisture content increases. By projecting the temporal model results into a spatial representation, the position of peak transport is found to scale linearly with wind shear velocity, showing greater sensitivity at higher moisture levels. A preliminary test suggests that evaporation is essential for the initial grain dislodgement by wind alone but is unlikely to affect steady-state transport. This study explains the longer fetch distances observed on moist beaches before transport equilibrates and provides a physics-based tool for predicting sediment transport under varying moisture conditions.

The presence of surface moisture on sandy beaches has long been acknowledged as a complicating factor in the process of aeolian sediment transport, reported by Belly (1964), Neuman and Scott (1998) and Davidson-Arnott et al. (2008). Many studies have been conducted on this subject, each offering a wind initiation threshold formula that incorporates the moisture effect differently, found in Belly (1964), Chepil (1956), Fecan et al. (1998), Wang (2006) and Haehnel et al. (2014). However, the impact dynamics in the transport process, regarded as the dominant mechanism for particle entrainment, was neglected in the derivation phase of these existing formulations. Therefore, to gain some insights into the physical mechanism where moisture plays a role in the aeolian process, as well as its impact on various other transport characteristics, this study employs a numerical model on the grain scale.

As the world moves more toward unpredictable renewable energy sources, better energy storage devices are required. Supercapacitors are a promising technology to meet the demand for short-term, high-power energy storage. Clearly, understanding their charging and discharging behaviors is essential to improving the technology. Molecular Dynamics (MD) simulations provide microscopic insights into the complex interplay between the dynamics of the ions in the electrolyte and the evolution of the charge distributions on the electrodes. Traditional MD simulations of (dis)charging supercapacitors impose a pre-determined evolving voltage difference between the electrodes, using the Constant Potential Method (CPM). Here, we present an alternative method that explicitly simulates the charge flow to and from the electrodes. For a disconnected capacitor, i.e., an open circuit, the charges are allowed to redistribute within each electrode while the sum charges on both electrodes remain constant. We demonstrate, for a model capacitor containing an aqueous salt solution, that this method recovers the charge–potential curve of CPM simulations. The equilibrium voltage fluctuations are related to the differential capacitance. We next simulate a closed circuit by introducing equations of motion for the sum charges, by explicitly accounting for the external circuit element(s). Charging and discharging of the model supercapacitor via a resistance proceed by double exponential processes, supplementing the usual time scale set by the electrolyte dynamics with a novel time scale set by the external circuit. Finally, we propose a simple equivalent circuit that reproduces the main characteristics of this supercapacitor.

Increasingly, society requires high power, high energy storage devices for applications ranging from electric vehicles to buffers on the electric grid. Supercapacitors are a promising contribution to meeting these demands, though there still remain unsolved practical problems. Molecular dynamics simulations can shed light on the relevant molecular level processes in electric double layer capacitors, but these simulations are computationally very demanding. Our focus here is on the algorithmic complexity of the constant potential method (CPM), which uses dedicated electrostatics solvers to maintain a fixed potential difference between two conducting electrodes. We show how any standard electrostatics solver—capable of calculating the energies and forces on all atoms—can be used to implement CPM with a minimum of coding. As an example, we compare our generalized implementation of CPM, based on invocations of the particle–particle–particle–mesh routine of the Large-scale Atomic/Molecular Massively Parallel Simulator, with a traditional implementation based on a dedicated re-implementation of Ewald summation. Both methods yield comparable results on four test systems, with the former achieving a substantial gain in speed and improved scalability. The step from dedicated electrostatic solvers to generic routines is made possible by noting that CPM’s traditional narrow Gaussian point-spread of atomic charges on the electrodes effectively endows point-like atoms with chemical hardness, i.e., an intra-atomic energy quadratic in the charge.

In this paper we introduce the open-source code MercuryDPM: a code for simulating discrete particles. The paper discusses software and management issues that may be interesting for the developers of other open-source codes. Then we review the new features that have been added since the last publication: an improved Hertz-Mindlin model; a new liquid bridge model of Lian and Seville; a droplet-spray model; better support for re-creating complex, measured particle size distributions; a new implementation of rigid clumps; an implementation of elastic membranes; a wear model for walls; a soft-kill feature and a cloud-deployment interface for AWS.

It is well known that granular mixtures that differ in size or shape segregate when sheared. In the past, two mechanisms have been proposed to describe this effect, and it is unclear if both exist. To settle this question, we consider a bidisperse mixture of spheroids of equal volume in a rotating drum, where the two mechanisms are predicted to act in opposite directions. We present evidence that there are two distinct segregation mechanisms driven by relative overstress. Additionally, we showed that, for nonspherical particles, these two mechanisms (kinetic and gravity) can act in different directions leading to a competition between the effects of the two. As a result, the segregation intensity varies nonmonotonically as a function of aspect ratio (AR), and, at specific points, the segregation direction changes for both prolate and oblate spheroids, explaining the surprising segregation reversal previously reported. Consistent with previous results, we found that the kinetic mechanism is dominant for (almost) spherical particles. Furthermore, for moderate aspect ratios, the kinetic mechanism is responsible for the spherical particles' segregation to the periphery of the drum, and the gravity mechanism plays only a minor role. Whereas, at the extreme values of AR, the gravity mechanism notably increases and overtakes its kinetic counterpart.