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Multi-scale analysis of DEM data to enhance the prediction at system scale |
Prof. Jin Ooi
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Infrastructure and Environment |
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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Measurement and modelling of powder flow in flexible containers |
Prof. Jin Ooi
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Infrastructure and Environment |
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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DEM model calibration and validation for cohesive soil-machine interactions |
Prof. Jin Ooi
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Infrastructure and Environment |
The modelling of cohesive soils is a challenging task of great importance in many earth moving processes. In these cases, the understanding of the interaction soil-machine is vital to try to optimize the process and avoid problems. This project aims to investigate the capabilities of DEM cohesive contact models to capture with a sufficient level of accuracy the mechanical behaviours involved in soil-machine interactions.
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Transporting, handling and storing behaviour of iron ore fines |
Prof. Jin Ooi
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Infrastructure and Environment |
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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VELaSSCo: Visualization for Extremely Large-scale Scientific Computing |
Prof. Jin Ooi
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Infrastructure and Environment |
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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A multi-scale approach to characterising fluid contribution to conductive heat transfer in dense granular systems |
Prof. Jin Ooi
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Infrastructure and Environment |
For granular materials with low thermal conductivity heat transfer occurs through interstitial gases as well as through physical contacts. Existing particle based models are ill suited to dense systems so a multi-scale approach has been used to correlate the local packing structure to the gas contribution to conductive heat transfer in dense granular systems.
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Robust Repeatable Respiratory Monitoring in EIT |
Professor Hugh McCann
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Imaging, Data and Communications |
The project aims at developing a new electrical impedance tomography (EIT) device for medical use. This device, called ReMEIT, should enable 3D absolute conductivity image reconstruction. To achieve this goal the project intends to capture the exact positions of the measuring electrodes and the exact thoracic shape using an optical shape capture device. These are absolutely novel approaches in EIT imaging that, if successful, could represent an immense progress in EIT research and a big step towards reliable clinical use of this technology. The project partners not only plan to develop the device but they also propose a strategy for its validation under invivo conditions. At first, healthy volunteers with no history of lung disease will be examined by ReMEIT and, later, the EIT device will be applied in critically ill patients suffering from various pulmonary diseases. In the former case, reference data will be obtained by magnetic resonance imaging (MRI), in the latter one, routine chest X-ray, computed tomography (CT)and MRI data will be utilised.
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Tackling the looming spectrum crisis in Wireless Communication |
Professor Harald Haas
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Imaging, Data and Communications |
The proposed work in this EPSRC Fellowship is aimed at providing radical new solutions to this fundamental and far reaching challenge. A key pillar of the proposed work is the extension of the RF spectrum to include the infrared as well as the visible light spectra. The recent advancements in light emitting diode (LED) device technology now seems to let the vision of using light for high speed wireless communications become a reality.
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Optical Free-Space Backhaul and Power for Energy Autonomous Small Cells |
Professor Harald Haas
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Imaging, Data and Communications |
The central aim of the project is the design of a novel simple structure for a communication base station. Its operation will be based on off-the-shelf optical components such as white LEDs, laser-diodes and photo-diodes.
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GREENNET An early stage training network in enabling technologies for GREEN radio |
Professor Harald Haas
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Imaging, Data and Communications |
Greenet is an Initial Training Network (ITN) Marie Curie project that is focused on the analysis, design, and optimization of energy efficient wireless communication systems and networks.
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