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

Paul W. Cleary (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)
Raymond C.Z. Cohen (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)
Simon M. Harrison (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)
Matthew D. Sinnott (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)
Mahesh Prakash (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)
Stuart Mead (Mathematics, Informatics and Statistics, CSIRO, Clayton, Australia)

Engineering Computations

ISSN: 0264-4401

Publication date: 22 February 2013

Abstract

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.

Keywords

Citation

Paul W. Cleary, Raymond C.Z. Cohen, Simon M. Harrison, Matthew D. Sinnott, Mahesh Prakash and Stuart Mead (2013) "Prediction of industrial, biophysical and extreme geophysical flows using particle methods", Engineering Computations, Vol. 30 No. 2, pp. 157-196

Download as .RIS

DOI

: https://doi.org/10.1108/02644401311304845

Publisher

:

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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