Prediction of industrial, biophysical and extreme geophysical flows using particle methods

Purpose - The purpose of this paper is to show how simulation of the flow of particulates and fluids using discrete element modelling (DEM) and smoothed particle dynamics (SPH) particle methods, offer opportunities for better understanding the dynamics of flow processes. Design/methodology/approach - DEM and SPH methods are demonstrated in a broad range of computationally-demanding applications including comminution, biomedical, geophysical extreme flow events (risk/disaster modelling), eating of food by humans and elite water-based sports. Findings - DEM is ideally suited to predicting industrial and geophysical applications where collisions between particles are the dominant physics. SPH is highly suited to multi-physics fluid flow applications in industrial, biophysical and geophysical applications. The advantages and disadvantages of these particle methods are discussed. Research limitations/implications - Research results are limited by the numerical resolution that can currently be afforded. Practical implications - The paper demonstrates the use of particle-based computational methods in a series of high value applications. Enterprises that share interests in these applications will benefit in their product and service development by adopting these methods. Social implications - The ability to model disasters provides governments and companies with the opportunity and obligation to use these to render knowable disasters which were previously considered unknowable. The ability to predict the breakdown of food during eating opens up opportunities for the design of superior performing foods with lower salt, sugar and fat that can directly contribute to improved health outcomes and can influence government food regulatory policy. Originality/value - The paper extends the scale and range of modelling of particle methods for demanding leading-edge problems, of practical interest in engineering and applied sciences.