In this paper, we present a number of key numerical methods that can be used to study elongated particles in fluid flows, with a specific emphasis on fluidised beds. Fluidised beds are frequently used for the production of biofuels, bioenergy, and other products from biomass particles, which often have an approximate elongated shape. This raises numerous issues in a numerical approach such as particle-particle contact detection and the accurate description of the various hydrodynamic forces, such as drag, lift, and torque, that elongated particles experience when moving in a fluid flow. The modelling is further complicated by a separation of length scales where industrial flow structures that can extend for many metres evolve subject to solid-solid and solid-fluid interactions at the millimetre scale. As a result, it is impossible to simulate both length scales using the same numerical approach, and a multiscale approach is necessary. First, we outline the direct numerical simulation (DNS) approach that may be employed to estimate hydrodynamic force closures for elongated particles in a fluid flow. We then describe the key aspects of a CFD-DEM approach, which can be used to simulate laboratory scale fluidisation processes, that must be addressed to study elongated particles. Finally, we briefly consider how current industrial-scale models, which concretely assume particle sphericity, could be adapted for the simulation of large collections of elongated particles subject to fluidisation.

Collective motion can be observed in many systems at various length scales. Ranging from the interaction of microswimmers at the microscopic scale to the dynamics of people and flocking behaviours of birds at the macroscopic scale, the natural world is home to many examples of collective responses. The emergence of collective motion in systems has long fascinated the scientific community with the classical approach for their study based on experimental observation. However, the development of suitable computer algorithms has significantly supplemented and complemented these empirical studies while also motivating new research fields on collective behaviour. This chapter outlines methods for measuring collective motion and key algorithms for the simulation of collective responses in birds, fish, mammals and people.

The various radiation types that make up the electromagnetic (EM) spectrum are ubiquitous and highly significant in modern society. Detection of visible light by the eye facilitates sight, radio waves and microwaves are used in communication technologies, x-rays are used in medical imaging, and gamma rays are frequently employed in medical procedures. Although radiation plays a predominant role in daily life, many students have developed and retain misconceptions concerning EM radiation. These misconceptions could be addressed through the use of popular culture content such as superheroes in the classroom. In a number of superhero narratives, EM radiation plays a key role in the emergence or development of superpowers. In this paper, we outline three approaches for using superheroes to support the learning of the EM spectrum, and to potentially address key student misconceptions. In one approach we have designed a student worksheet based on Captain America and vita-rays, a fictional radiation type that plays a key role in his superpowers. The worksheet has been designed to instigate critical reflection on the part of the student, while allowing the student to apply their understanding of other forms of radiation.

The aim of many industrial processes is to manipulate solid particle aggregates within gas suspensions. Prime examples of such processes include fluidised bed reactors, cyclone separators, and dust collectors. In recent years, fluidised bed reactors have been used in the gasification of biomass particles. When fluidised, these particles are subject to various hydrodynamic forces such as drag, lift and torque due to interactions with the fluid. Computational approaches, which can be used to replicate laboratory and industrial scale processes, offer a crucial method for the study of reactor design and for the formulation of optimal operating procedures. Until now, many computer models have assumed particles to be spherical whereas, in reality, biomass feedstocks typically consist of non-spherical particles. While lift and torque are of minimal importance for spherical particles, non-spherical particles experience varying lift force and torque conditions, depending on particle orientation relative to the direction of the fluid velocity. In this study, we present a numerical investigation on the effect of different lift force and torque correlations on fluidised spherocylindrical particles. We find that lift force has a significant influence on particle velocities parallel to the direction of gravity. On the other hand, particle orientation is dependent on hydrodynamic torque. Results from this numerical study provide new insight with regards to the dynamics of non-spherical particles that can be of paramount importance for industrial processes involving non-spherical particles.

An updated mesoscopic model for transient forces between two star polymers is presented. Calculation of the transient forces is based on the response of a vectorial structure parameter between two star polymers and differs from previous models that used a scalar structure parameter. The update of the model is motivated by the occurrence of two distinct processes in previous small-scale simulations of two star polymers moving past each other. A simple model that takes these processes into account turns out to fit into an obvious generalization of the RaPiD model introduced by us some time ago. The model reproduces forces from the simulation quite well, and at the same time removes an unphysical feature of the RaPiD model used so far.

We present results from a new variant of a diffusion hopping model, the convective diffusive lattice model, to describe the behavior of a particulate flux around bluff obstacles. Particle interactions are constrained to an underlying square lattice where particles are subject to excluded volume conditions. In an extension to previous models, we impose a real continuous velocity field upon the lattice such that particles have an associated velocity vector. We use this velocity field to mediate the position update of the particles through the use of a convective update after which particles also undergo diffusion. We demonstrate the emergence of an expected wake behind a square obstacle which increases in size with increasing object size. For larger objects we observe the presence of recirculation zones marked by the presence of symmetric vortices in qualitative agreement with experiment and previous simulations.

Multiphase (gas-solid) flows are encountered in numerous industrial applications such as pharmaceutical, food, agricultural processing and energy generation. A coupled computational fluid dynamics (CFD) and discrete element method (DEM) approach is a popular way to study such flows at a particle scale. However, most of these studies deal with spherical particles while in reality, the particles are rarely spherical. The particle shape can have significant effect on hydrodynamics in a fluidized bed. Moreover, most studies in literature use inaccurate drag laws because accurate laws are not readily available. The drag force acting on a non-spherical particle can vary considerably with particle shape, orientation with the flow, Reynolds number and packing fraction. In this work, the CFD-DEM approach is extended to model a laboratory scale fluidized bed of spherocylinder (rod-like) particles. These rod-like particles can be classified as Geldart D particles and have an aspect ratio of 4. Experiments are performed to study the particle flow behavior in a quasi-2D fluidized bed. Numerically obtained results for pressure drop and bed height are compared with experiments. The capability of CFD-DEM approach to efficiently describe the global bed dynamics for fluidized bed of rod-like particles is demonstrated.