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Effect of particle shape, size and particle friction in granular solid flow in railway ballast |
Prof. Xuecheng Bian
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The aim is to develop a new understanding of the micromechanics of railway trackbed subjected to dynamic loads induced by high speed trains. This should lead to safer design of high-speed railway systems which require less maintenance and, therefore, are more sustainable.
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Discrete Element Modeling of High-Speed Railway Embankment |
Prof. Xuecheng Bian
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The aim is to develop a new understanding of the micromechanics of railway trackbed subjected to dynamic loads induced by high speed trains. This should lead to safer design of high-speed railway systems which require less maintenance and, therefore, are more sustainable.
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Challenging RISK: Achieving Resilience by Integrating Societal and Technical Knowledge |
Professor Luke Bisby
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This project is concerned with socially integrated mitigation of multiple structural risks in the urban environment, with a focus on the linked risks of earthquake and fire. Fire is the largest contributor to building damage following earthquakes. To date, this research area has largely been ignored as it crosses the boundaries between the knowledge areas of earthquake and fire safety engineering. The combination of factors adds to the challenges in risk estimation already existing in each distinct area. There is currently no universally accepted method for accounting for the effect of strengthening practices on building vulnerability to earthquakes (let alone earthquakes followed by fire). In the case of fire safety engineering, few credible techniques for damage estimation or risk-based design currently exist due to a lack of requisite input data. This project will develop, through large scale structural testing and computational analysis, new technical engineering solutions to these problems. And, for the first time, these technical engineering solutions will be developed explicitly accounting for the social context within which they are to be enacted.
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Transporting, handling and storing behaviour of iron ore fines |
Prof. Jin Ooi
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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.
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Measurement and modelling of powder flow in flexible containers |
Prof. Jin Ooi
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The research focuses on understanding cohesive powder flow in flexible bulk solid containers (buggies and bulk bags) with a view to develop a design methodology for ensuring reliable discharge from these containers. The project involves experimental powder flowability characterisation, finite element analysis of the stresses in flexible containers and pilot scale experiments to study the powder flow field and validate the new design methodology for reliable discharge.
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T-MAPPP: Training in Multiscale Analysis of multi-Phase Particulate Processes |
Prof. Jin Ooi
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T-MAPPP is an Initial Training Network funded by FP7 Marie Curie Actions with 10 full partners and 6 associate partners, aiming to train the next generation of researchers who can support and develop the emerging inter- and supra-disciplinary community of Multiscale Analysis (MA) of multi Phase Particulate Processes.
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A multi-scale approach to characterising fluid contribution to conductive heat transfer in dense granular systems |
Prof. Jin Ooi
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Heat transfer in granular materials is a common occurrence in many industrial applications. One such application is the heating of recycled asphalt product (RAP).
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VELaSSCo: Visualization for Extremely Large-scale Scientific Computing |
Prof. Jin Ooi
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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.
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IFPRI Grindability Project: modelling, measurement and mill fingerprinting |
Prof. Jin Ooi
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This project aims to develop a robust methodology to characterise the grindability of particulate products in milling operations which will in turn provide a step-change in mill fingerprinting and optimisation. This involves developing a “grindability test” to measure the comminution characteristics of the particulates which, when coupled with the computational modelling work to characterise the milling function, will evaluate the milling performance measures including energy utilisation, breakage kernels for scale-up modelling such as population balance model of the mill.
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Multi-scale analysis of DEM data to enhance the prediction at system scale |
Prof. Jin Ooi
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While the discrete element method (DEM) can provide particle-scale information to inform the design of particulate equipment, many industrial sectors are interested in large-scale modelling and scaling-up processes [1].
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