Projects | John P. Morrissey

TUSAIL Project

Fri, 01 Jan 2021 00:00:00 +0000

Introduction

TUSAIL is an Innovative Training Network funded by Horizon 2020 which comprises 16 academic and industrial partners in total, led by the University of Edinburgh. TUSAIL stands for “Training in Upscaling particle Systems: Advancing Industry across Length-scales”. Over the course of four years, TUSAIL will train 15 early-career researchers (ESRs) through a combination of PhD research, scientific training and industrial secondments.
The reliable, validated simulation methodologies and tools developed in TUSAIL will be disseminated to industry, enabling quantitative predictions of large industrial processes which will be of value for design, operation and optimisation.

About the TUSAIL Project

The overarching research goal of TUSAIL is to establish physics-based modelling, starting from characterising a small amount of a powder, to predict the behaviour of large industrial unit operations and processes via reliable upscaling methodologies and tools, bridging the gap between micro-mechanics and the industrial scale. Four main unit operations will be considered: mixing, transport and discharge, milling and agglomeration. Three complementary upscaling approaches will be developed based on (i) population balance modelling (PBM), (ii) coarse-grained meso-particle methods, and (iii) coupling between discrete and continuum methods. Each of these three upscaling approaches forms a core work package (WP) of TUSAIL; similar numbers of early-stage researchers (ESRs) will contribute to each of these WPs.

A fourth, overarching WP involves experiments at various length scales including single-particle characterisation tests and element tests for calibration, and lab-scale, pilot-scale and industrial-scale experiments for process validation. The interaction of the four scientific work packages and the participation of ESRs in them is graphically summarised in an interaction roadmap.

Discrete Element Modelling of High-Speed Railway Embankments

Wed, 27 Apr 2016 00:00:00 +0000

Introduction

Ever greater demands are being placed on rail networks around the world. Lack of funding for additional infrastructure means that growing traffic on existing infrastructure pushes the operating limits of the existing infrastructure – the extra traffic is included through a combination of higher train speeds to run more services and higher axle loads to carry more per train.

In recent decades high speed rail has seen rapid growth around the world, particularly with 1#tens of thousands of kilometres of new track being built. In the UK HS2, the first new line in almost a century, is being built for high speed rail. In many cases High Speed Rail (HSR) utilises embankments that are of the ballasted type – this is particularly true in the case of mixed use track. DEM is ideally suited to use to study the ballasted railway infrastructure considering the naturally discrete inhomogeneous structure.

This project is being carried out in collaboration with Zhejiang University funded by the Royal Newton Fund.

Project Parties

The research is focused on quantifying the effect of particle shape, size and packing structure on the stress distribution and deformation patterns that develop in the ballast-track system and providing scientific insights into the ballasted tracks deformation modes. It will explore the interplay between inter-particle contact friction and geometric interaction due to ballast interlocking in producing the complex dynamic responses observed in trackbed.

Full-scale experiments will be carried out on Zhejiang University Physical Model (ZJU-iHSRT), a full scale reconstruction of a ballasted railtrack that can apply loads from various train types and speeds up to 360 km/h.

Zhejiang University High Speed Rail Physical Model (ZJU-iHSRT)

DEM simulations will be calibrated from experimental tests such as triaxial tests and direct shear tests. Calibrated DEM simulations of the full embankment are carried out and compared to the full-scale experimental results.

Bulk friction calibration via Direct Shear tests

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Models for the Manufacturing of Particulate Process (Models MPP)

Wed, 27 Apr 2016 00:00:00 +0000

Introduction

Particle processes in industry are both common and challenging. The complexity of particulate systems means that it is prohibitively difficult to gain a comprehensive understanding of the particulate mechanics which control a process using solely laboratory experiments. Even though some numerical models are available in the literature which describe particle processes, these tend to be inadequate to meet the requirements of industry. Industry requires robust models which contain the key relevant physics, which are user-friendly and which are focused on delivering the output product specifications given a limited number of measured input parameters.

Despite the significant academic activity in the development of multi-scale, multi-phase modelling approaches, few of the models originating in academia are fully implemented in industrial practice. As a result, the full benefits of model-based development have not been derived. The creation and implementation of a better approach to implementing useful models from academia into industrial practice could therefore lead to significant economic benefits relating to enhanced speed of development, reduced development costs and improved product quality.

This project aims to create a generally applicable framework for transferring academic innovations in the modelling of particulate materials into industrial practice in the UK. The process of twin-screw granulation has been selected as an exemplar industrial process which is simulated across multiple scales using the coupled methods of population balance modelling and the discrete element method.

Project Members

The project involved two academic partners, the University of Edinburgh and the University of Sheffield, and six industrial partners: Pfizer, AstraZeneca, Procter and Gamble, Johnson Matthey, Process Systems Enterprise and DEM Solutions (Now Altair EDEM). The project was led by the Centre for Process Innovation with funding coming from Innovate UK.

Project Summary

The two-year Models for the Manufacturing of Particulate Process (Models MPP) project focused on establishing a generic framework and core capability to improve industrial productivity.

As part of the drive to provide more leverage and integration of the wealth of formulations expertise in the UK, the £700,000 project, funded by Innovate UK as part of CPI’s National Formulation Centre Strategic Projects Programme, has facilitated the translation of the UK’s world-leading expertise in computational modelling and simulation for the manufacturing of particulate processes.

Connecting industry and university research groups with state-of-the-art technology has resulted in the development of a generic framework for translating particle models of industrial relevance into industrial practice. The developed framework incorporates a decision support methodology/tool for models development that will allow easier access and adoption by leading UK-based industrial organisations. These models are expected to be deployed within industry to accelerate the development of innovative products and improve productivity and cost-effectiveness of product manufacturing processes.

This framework will provide guidance for the coupling of well-established computer modelling techniques at different size scales, to enable development scientists and engineers to develop models that simulate different parts of manufacturing processes from the dispensing of input materials through mixing, agglomeration and other subsequent processing steps.

Twin-screw wet granulation, a method used in a number of industry sectors, was used as an exemplar. Wet granulation is a process in which small primary particles are joined together using agitation and a liquid binder. The purpose is to improve the properties of very fine cohesive powders used in formulated products such as pharmaceuticals, ceramics, detergents and fertilizers. Granulation is commonly used in the pharmaceutical industry during tablet manufacturing. Fine powders are granulated to improve flow prior to tableting and reduce the potential for dusting and other production issues. The formation of granules also helps to reduce segregation and improve the content uniformity of the final product which is critical for consistent product performance.

The academic partners at the Universities of Edinburgh and Sheffield conducted a review of the current state of the art and used this insight to develop coupled models using EDEM and PSE software platforms and the technology vendor’s expertise in developing industrially robust models. These models were validated using real life trials at the industrial partner’s production facilities.

While granulation is an important process in many industries, including pharmaceuticals, foods and agrochemicals, the framework provided by Models MPP means it can be broadly re-applied to other manufacturing operations and industries.

The legacy capability established from this project will be applied to other CPI strategic projects, e.g. in the development of a digital twin with a sister National Formulation Centre strategic project focused on a fully PAT enabled twin screw extruder (‘PROSPECT CP’).

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VELaSSCo: Visualization for Extremely Large-scale Scientific Computing

Wed, 27 Apr 2016 00:00:00 +0000

Introduction

One of the major problems experienced by engineers and scientists running high-end real-scale simulation models is the management and exploitation (in terms of visualization) of the outputs of their models. Inspecting large dataset distributed over numerous clusters located remotely, is often a significant difficulty to be overcome to ensure that users (both in academia and industry) are able to take the best advantage of current (and future) HPC infrastructures.

The Vision of VELaSSCo is to provide new approaches for visual analysis of large-scale simulations for the Exabyte era. It does this by building on big data tools and architectures for the engineering and scientific community and by adopting new ways of in-situ processing for data analytics and hardware accelerated interactive visualization.

To better manipulate the data from simulations with billions of records it is crucial that the engineering and scientific community adopts big data tools. VELaSSCo will provide a simulation data analysis platform consisting of:

A database structure, based on widely used technologies such as Hadoop-HBase, that can organise and store a diverse range of large-scale simulation data sets for collaborative use.
An innovative approach, adopting big data best practices, to handle large scale simulation data sets that have to be stored on multiple servers.
A framework equipped with advanced in-situ processing tools to analyse the output of parallel simulation solvers.
An analysis platform to analyse and visualize large-scale data sets interactively. This builds on leading edge graphics hardware.

Project Partners

The VELaSSCo consortium has a wide variety of expertise aligned with the objectives of the project. Expertise of the partners can be classified mainly in two principal categories: Institutions specialized in the development and implementation of visualization software, particularly addressed to facilitate analysis of HPC simulations in engineering and scientific first-class problems (CIMNE, UNEDIN and FRAUNHOFER); and institutions with experience in Data Analytics, Big Data, Big Data Handling and Cloud Computing (SINTEF, INRIA, JOTNE and ATOS).

The partnership also counts with a large group of potential end-users of the outcomes of the projects, ranging from large engineering companies, SME’s on engineering modelling and software houses, to research organisations doing large scale engineering modelling, linked to the User Panel already described.

List of partners:

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Transporting, handling and storing behaviour of iron ore fines

Sat, 27 Jul 2013 00:00:00 +0000

Introduction

This project attempts to deal with the challenges associated with handling and storage of cohesive solids in the mining industry. An adhesive-frictional model has been recently developed for DEM simulation of cohesive particles at the University of Edinburgh. This project will exploit the new method for modelling cohesive particulates for specific problems, such as effect of fines in silo discharge and the effect of time consolidation.

Fines are produced during transportation, handling and storing of iron pellets. The presence of fines can significantly affect the behaviour of iron ore pellets during these processes. In addition, increased volumes of sinter fines are being produced and handled and their behaviour can also be significantly affected.
Silos and other equipment handling the fines can experience such phenomena as caking, arching and alteration of flow pattern, leading to operational difficulties.

The behaviour of fines is extremely complex, affected by numerous factors such as particle size, size distribution, stress level (e.g. the maximum vertical stress in a silo), stress state (i.e. the stresses in different directions), stress history, temperature, moisture content, time and chemical bond/fusion. Different combinations of these factors can lead to different behaviours, such as caking with different strength and size, which in turn result in different effects on the solids flow in silos and other handling scenarios in the mining industry.

DEM simulations can also be affected by the prescribed boundary conditions and as such the effect of oversimplification of the degrees of freedom for a Jenike cell are explored in detail, through the use of fully coupled multi-body dynamics for all geometry movements.

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Discrete Element Modelling of Iron Ore Pellets to Include the Effects of Moisture and Fines

Sun, 27 Sep 2009 00:00:00 +0000

Introduction

Across industry the majority of raw materials handled are particulate in nature, ranging in size and properties from aggregates to powders. The stress regimes experienced by the granular solids vary and the exhibited bulk behaviours can be complex and unexpected. The prevalence of granular solids makes them an area of interest for industry and researchers alike as many challenges still remain, such as dealing with complex cohesive behaviour in materials, which often gives rise to handling difficulties. The cohesive strength of a bulk material depends on the consolidation stress it has experienced. As a result, the stress history in the material leading up to a handling scenario needs to be considered when evaluating its handling behaviour.

Storage and transportation are an important part of the process chain for industries where particulate solids are commonplace. Failure to properly account for the cohesive nature of a particulate solid can be costly as it can easily lead to blockages in a silo such as ratholing or arching near the outlet during discharge.

Research Goals

Cohesive granular solids such as powders can have a very loose, highly porous structure under very low stresses. While it is possible to generate similar initial packing structures in a DEM simulation, it is not feasible to attempt to match all stress states. In this study, stress states larger than 5-10 kPa are of interest and as such all packing structures will aim to match the experimental results from this stress level.

Numerical

The main aim of the research is to develop an improved contact model to better capture the behaviour of cohesive granular solids, particularly iron ore fines, which are significantly affected by the presence of moisture. In order for numerical simulations to be successfully used for more efficient design and management of industrial equipment and structures, the transition from qualitative to quantitative prediction needs to be made.

In this study a mesoscopic adhesive contact model that accounts for contact plasticity and stress history dependency in the bulk solid, the Edinburgh Elasto-Plastic Adhesion (EEPA) mode, has been presented and mathematically verified. A parametric study of the DEM contact model parameters was conducted to gain a deeper understating of the effect of input parameters on the simulated cohesive bulk behaviour.

Edinburgh Elasto-Plastic Adhesion (EEPA) Model

The EEPA contact model has been used to predict an experimental flow function of KPRS iron ore fines. The contact model has demonstrated the ability to capture the stress history dependent behaviour that exists in cohesive granular solids. The DEM simulations provide a very close match to the experimental flow functions, with the predicted unconfined strengths found to be within the standard deviations of the experimental results.

Comparison between Experimental and DEM Flow Functions for Iron ore fines

Investigations into the failure mode predicted by the DEM simulations show that the samples are failing from the development of shear planes similar to those observed experimentally.

Shear Failure mode in DEM Simulations: a) DEM Simulation b) Coarse-grained angular velocity in sample c) Coarse-grained solid fraction in sample

Experimental

To help achieve this a secondary aim is to rigorously characterise the properties of the material that are required for calibration of a numerical model. A study of the effect of the parameters of the adhesive contact model is also carried out. In this study a particular focus is paid to the two types of iron ore fines: KPBO and KPRS, with the purpose of characterising the different materials types and assessing the distinct behaviour exhibited by the different fines.

A comprehensive study on the effect of cohesion arising from the addition of moisture on the behaviour of two types of LKAB iron ore fines (KPBO and KPRS) has been carried out using a uniaxial tester, the Edinburgh Powder Tester (EPT).

Edinburgh Powder Tester (EPT)

The addition of moisture to the sample has been found to have a significant effect on both kinds of fines. KPRS fines were found to have a much higher unconfined strength and flow function at higher moisture contents, and also show a greater increase in cohesion with the addition of moisture, while at moisture contents of less than 2% the KPBO fines demonstrate higher unconfined yield strength. The KPBO fines were also found to achieve a significantly looser initial packing at much lower moisture content when compared to the KPRS fines. The lateral pressure ratio has also been evaluated.

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Granular Mechanics and Industrial Infrastructure Research Group

Sun, 27 Sep 2009 00:00:00 +0000

Introduction

The Granular Mechanics and Industrial Infrastructure research group is part of the School of Engineering at the University of Edinburgh. This group contains more than 20 members and is led by Prof. Jin Ooi. Members use a combination of experimental testing, analytical methods and simulations (with appropriate verification and validation) to investigate the behaviour of a diverse range of granular materials.

The group is characterised by a multi-scale philosophy: the application of multiple complementary approaches to a given system to enable exploration of a broad range of scales from the single particle to the bulk material. The group also actively research multi-phase systems in which one or more fluids must be considered to fully understand the system’s behaviour.

Research emanating from this long-established group has had a considerable impact. Within an academic context, group members disseminate their research results in peer-reviewed journal publications and at major international conferences, and the group collaborate with many leading academic research groups around the world. Outside of academia, many well-known companies have benefited from the group’s expertise through consultancy and/or collaborative research projects, e.g., AstraZeneca, Johnson Matthey, P&G and Pfizer.

In recent years, the group have been highly successful in winning research funding from EPSRC, the European Union, the Royal Society and IFPRI, in addition to industrial funding. The group at Edinburgh currently coordinate the EU FP7 Marie Curie Initial Training Network TUSAIL (2021–Pres.), which follows on from a previous highly successful FP7 projects T-MAPPP (2014–2018) and PARDEM (2009–2013).

Research Activities

The research activities of the group may be divided into the following broad themes

Featured Research

Furthermore, the group have a strong track record of research commercialisation. Two software companies, DEM Solutions (now Altair EDEM) and Particle Analytics, have been formed as spin-out companies from this group, and in 2016 Freeman Technology launched the Uniaxial Powder Tester based on the Edinburgh Powder Tester with the technology licensed from the University of Edinburgh.

Edinburgh Powder Tester