How well do models of particle motion represent industrial reality?

Lead Research Organisation: University of Birmingham
Department Name: Chemical Engineering


Granular or particulate materials are common in nature and in process engineering, particularly as products such as instant foods, pharmaceuticals and consumer goods such as washing powders. Compared with simple fluids, they show interesting and useful behaviour, from kinetic free-flow in some circumstances to slow friction-dominated motion in others. In recent years there has been much progress in modelling their behaviour, particularly using the Discrete Element Method (DEM), in which each particle is considered separately and its interactions with its neighbours computed in order to predict its next position. Many industrial companies are now using such methods for design and process prediction but testing of such models against reality is difficult because the systems of interest are usually opaque and often held within metal-walled containers. This project will make use of a cutting-edge technique for tracking particle motion called Positron Emission Particle Tracking (PEPT) to map particle behaviour in a set of experiments which will be simultaneously modelled using DEM. The goal is to devise calibration tests for models which are able to discriminate between good and bad modelling approaches. The work is collaborative with a number of industrial partners through the International Fine Particle Research Institute (IFPRI), a US-based organisation of international industrial members, many of whom will be actively participating in the work through their in-house modelling teams. The ideal candidate will have an interest in coding to develop protocols to enable processing and comparison of large data sets, as well as an interest in the physics and engineering of particulate systems.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023070/1 01/10/2019 31/03/2028
2433815 Studentship EP/S023070/1 28/09/2020 27/09/2024 Andrei Leonard Nicusan