Date:

2011-2012

Themes:

Modelling and Simulation, Environmental modelling, Condition monitoring

Funding:

National Grid plc

National Grid’s cable tunnel network is a vital component of the power transmission grid within the London area, with the length of cable installed in tunnels scheduled to increase significantly in the coming decades. In order to achieve the required circuit ratings for tunnel cable installations, a degree of forced cooling is necessary. Typically this is achieved through the installation of large ventilation fans to force air through the tunnel network, removing heat generated by the operation of the cable system. Where high circuit ratings are required, very large fans may be specified to provide the appropriate flow rate of cooling air through the tunnel. The maximum emergency rating of the cable circuit can be achieved through operating the fans on a 100% duty cycle, however the costs of such operation (in terms of the electrical power utilised) represent a significant contribution to the OPEX costs associated with the tunnel.

Building on the modelling foundation of the RoCiT Project, this project will investigate the feasibility of advanced ventilation control schemes which will be designed to ensure the minimisation of ventilation running costs while maintaining a high emergency rating on the cable circuits installed in the tunnel. This will involve the further development of thermal models of the tunnel network, along with the analysis of data from operational 400kV transmission circuits.

Primary investigators

• Paul Lewin
• jp2

Partner

• National Grid plc

Associated research group

• Electronics and Computer Science

Date:

2011-2015

Themes:

High Voltage Engineering, Condition monitoring

Funding:

National Grid plc

In recent years a significant volume of research has been undertaken in order to understand the recent failures in oil insulated power apparatus due to deposition of copper sulphide on the conductors and in the insulation paper. Dibenzyl Disulfide (DBDS) has been found to be the leading corrosive sulphur compound in the insulation oil. The most commonly used mitigating technique for corrosive sulphur contaminated oil is passivation, normally using Irgamet 39 or 1, 2, 3-benzotriazole (BTA). The passivator is diluted into the oil where it then reacts with the copper conductors to form a complex layer around the copper, preventing it from interacting with DBDS compounds and forming copper sulphide. This research project will investigate the electrical properties of HV transformers which have tested positive for corrosive sulphur, and the evolution of those properties as the asset degrades due to sulphur corrosion. Parallel to this the long term properties of transformers with passivated insulation oil will be analysed in order to understand the passivator stability and whether it is necessary to keep adding the passivator to sustain its performance.

Primary investigators

• Paul Lewin
• jp2

Secondary investigator

• pa3g08

Associated research group

• Electronics and Computer Science

Date:

2009-2014

Theme:

Modeling and Simulation

Funding:

EPSRC

The human brain remains as one of the great frontiers of science – how does this organ upon which we all depend so critically, actually do its job? A great deal is known about the underlying technology – the neuron – and we can observe in vivo brain activity on a number of scales through techniques such as magnetic resonance imaging, neural staining and invasive probing, but this knowledge - a tiny fraction of the information that is actually there - barely starts to tell us how the brain works, from a perspective that we can understand and manipulate. Something is happening at the intermediate levels of processing that we have yet to begin to understand, and the essence of the brain's information processing function probably lies in these intermediate levels. One way to get at these middle layers is to build models of very large systems of spiking neurons, with structures inspired by the increasingly detailed findings of neuroscience, in order to investigate the emergent behaviours, adaptability and fault-tolerance of those systems.

What has changed, and why could we not do this ten years ago? Multi-core processors are now established as the way forward on the desktop, and highly-parallel systems have been the norm for high-performance computing for a considerable time. In a surprisingly short space of time, industry has abandoned the exploitation of Moore’s Law through ever more complex uniprocessors, and is embracing a 'new' Moore's Law: the number of processor cores on a chip will double roughly every 18 months. If projected over the next 25 years this leads inevitably to the landmark of a million-core processor system. Why wait?

We are building a system containing a million ARM9 cores - not dissimilar to the processor found in many mobile phones. Whilst this is not, in any sense, a powerful core, it possesses aspects that make it ideal for an assembly of the type we are undertaking. With a million cores, we estimate we can sensibly simulate - in real time - the behaviour of a billion neurons. Whilst this is less than 1% of a human brain, in the taxonomy of brain sizes it is certainly not a primitive system, and it should be capable of displaying interesting behaviour.

A number of design axioms of the architecture are radically different to those of conventional computer systems - some would say they are downright heretical. The architecture turns out to be elegantly suited to a surprising number of application arenas, but the flagship application is neural simulation; neurobiology inspired the design.

This biological inspiration draws us to two parallel, synergistic directions of enquiry; significant progress in either direction will represent a major scientific breakthrough: • How can massively parallel computing resources accelerate our understanding of brain function? • How can our growing understanding of brain function point the way to more efficient parallel, fault-tolerant computation?

Primary investigators

• Andrew Brown
• Professor Steve Furber, University of Manchester
• Dr Simon Moore, University of Cambridge

Partners

• University of Manchester
• University of Cambridge
• University of Sheffield

Associated research groups

• Electronic Systems and Devices Group
• Electronics and Electrical Engineering

Date:

2011-2013

Theme:

Knowledge Technologies

Funding:

Technology Strategy Board

The advent of new standards and initiatives for data publication in the context of the World Wide Web (in particular the move to linked data formats) has resulted in the availability of rich sources of information about the changing economic, geographic and socio-cultural landscape of the United Kingdom, and many other countries around the world. In order to exploit the latent potential of these linked data assets, we need to provide access to tools and technologies that enable data consumers to easily select, filter, manipulate, visualize, transform and communicate data in ways that are suited to specific decision-making processes.

In this project, we will enable organizations to press maximum value from the UK’s growing portfolio of linked data assets. In particular, we will develop a suite of software components that enables diverse organizations to rapidly assemble ‘goal-oriented’ linked data applications and data processing pipelines in order to enhance their awareness and understanding of the UK’s geographic, economic and socio-cultural landscape.

A specific goal for the project will be to support comparative and multi-perspective region-based analysis of UK linked data assets (this refers to an ability to manipulate data with respect to various geographic region overlays), and as part of this activity we will incorporate the results of recent experimental efforts which seek to extend the kind of geo-centred regional overlays that can be used for both analytic and navigational purposes. The technical outcomes of this project will lead to significant improvements in our ability to exploit large-scale linked datasets for the purposes of strategic decision-making.

RAGLD is a collaboative research initiative between the Ordnance Survey, Seme4 Ltd and the University of Southampton, and is funded in part by the Technology Strategy Board's “Harnessing Large and Diverse Sources of Data� programme. Commencing October 2011, the project runs for 18 months.

Primary investigator

• Nigel Richard Shadbolt

Secondary investigator

• Ian Charles Millard

Partners

• Ordnance Survey
• Seme4 Limited

Associated research group

• Web and Internet Science

Date:

2006-2009

Themes:

Complex Networks, Bio-inspired computing

Funding:

EPSRC

We are an interdisciplinary team of scientists working on an ambitious three-and-a-half year project titled "Spatially Embedded Complex Systems Engineering" (or SECSE). We are a research cluster spanning neuroscience, artificial intelligence, geography, and complex systems, brought together to understand the role of the spatial organization and spatial processes in complex networks within the domains of neural control, geo-information systems and distributed IT systems such as those implicated in air-traffic control. A key driver for the project is IT's current "network transition": from traditional systems comprising relatively isolated hierarchically organised computational elements to large-scale, massively interconnected systems that are physically distributed and affected by local conditions yet must remain secure, robust, and efficient. The project involves several world-class research groups in the U.K., and takes a highly interdisciplinary approach, bringing together experts in spatial processes, adaptive processes, biosystems and design processes, employing 6 post-doctoral researchers and involving two further doctoral research students.

Primary investigators

• sgb
• Dr E. A. Di Paolo
• Dr D. Ladley

Secondary investigators

• Dr C. L. Buckley
• Dr L. Barnett
• Dr P. Fine
• Dr B. Clark

Associated research groups

• Science and Engineering of Natural Systems Group
• Agents, Interaction and Complexity

Date:

2006-2010

Themes:

Artificial Neural Networks, Complex Networks

Funding:

EPSRC

This interdisciplinary research collaboration arose within the Simple Models of Complex Networks research cluster funded by the EPSRC www.epsrca.ac.uk through the Novel Computation Initiative. Here, leading groups from the Universities of Leeds, Sheffield, Nottingham, Southampton, Royal Holloway and King’s College and industrial partners BT are brought together for the first time to develop novel amorphous computation methods based on the theory of random graphs. In particular we focus on new models with particularly relevant structural features, and on network models in a broad range of biological (neuroscience, epidemics and regulatory networks) and communication (telephone, internet) domains.

Primary investigators

• Prof Chris Cannings
• Dr. Nick Monk
• Dr. Netta Cohen
• Prof. Martin Dyer
• Prof. Vincent Jansen
• Dr Chris Watkins
• Dr Colin Desmond Cooper
• sgb
• Dr Fabrice Saffre

Secondary investigators

• Dr Jonathan Jordon
• Dr David Irons
• Richard Southwell
• Mariusz Jacyno
• Dr Orestis Chrysafis
• Dr James Watson
• Mohanaraj Velum
• Andrew Handley
• Dr Margaritis Voliotis
• Dr John Bryden
• Dr Sebastian Funk
• Dr Nic Geard

Associated research groups

• Science and Engineering of Natural Systems Group
• Agents, Interaction and Complexity

Date:

2011-2016

Themes:

Computational Economics, Complex Networks

Funding:

EPSRC

The Infrastructure Transitions Research Consortium (ITRC) will deliver research, models and decision support tools to enable analysis and planning of a robust national infrastructure system. This research project is divided into several major challenges. University of Southampton is involved in the work stream entitled "Managing Infrastructure as a Complex Adaptive System". Starting with idealised simulations and working up to the national scale, we will develop new models of how infrastructure, society and the economy evolve in the long term. We will use the simulation models to demonstrate alternative long term futures for infrastructure provision and how they might be reached. These simulation models will be combined with the techniques of evolutionary economics to explore the dynamic relationship between infrastructure provision and structural change in the economy. A further avenue will apply approaches based on network dynamics to simulate the evolution of infrastructure networks through time under a variety of external drivers. We will synthesise the most promising approaches and test them to identify patterns of emergence and to understand how in the real world these new insights may be used to steer national infrastructure systems towards sustainable outcomes.

Primary investigators

• Prof Jim Hall
• sgb
• Prof Nick Jenkins
• Dr Nick Eyre
• Prof John Preston
• Prof Chris Kilsby
• Prof Tom Curtis
• Prof William Powrie
• Prof Cliff Jones
• Dr Stuart Barr
• Prof Robert Nicholls
• Prof Pete Tyler
• Prof Mark Birkin
• Dr Jim Watson

Associated research groups

• Science and Engineering of Natural Systems Group
• Agents, Interaction and Complexity

Date:

2010-2015

Themes:

Healthcare, Simulation, Modelling and Evalution, Computational Economics

Funding:

EPSRC

In April 2010, the University of Southampton was awarded over £3million by the EPSRC (Engineering and Physical Sciences Research Council) under its ‘Complexity Science in the Real World’ initiative to carry out a 5 year multidisciplinary research project on the “Care Life Cycle: Responding to the Health and Social Care Needs of an Ageing Society�. This research programme brings together teams of researchers from social sciences, management science and complexity science to develop a suite of models representing the socio-economic and demographic processes and organisations implicated in the UK’s health and social care provision. Integral to the project is working with our partners in the public sector and communicating the results of these models to policymakers allowing them to effectively plan for the future.

Primary investigators

• Prof. J.C.Falkingham
• Prof. S.C.Brailsford
• sgb
• Prof. Maria.Evandrou

Secondary investigators

• Dr J.Bijak
• Dr A.R.Channon
• Dr J.H.Klein
• Dr R.Luff
• jn2
• Dr J.Raymer
• Dr Athina Vlachantoni
• Dr Rosalind Willis
• Dr Olga Maslovskaya
• sr1
• Dr Richard Shaw
• Dr Eric Silverman
• Dr Joe Viana

Associated research groups

• Science and Engineering of Natural Systems Group
• Agents, Interaction and Complexity

Date:

2010-2013

Themes:

Simulation, Modelling and Evalution, Complex Networks, Decentralised and Autonomous Systems

Funding:

ESRC (EP/I005943/1)

The R-Futures programme is a 3 year multidisciplinary research project considering "the future developments in the UK's energy and transport infrastructure and the resilience of these systems to natural and malicious threats and hazards". It aims to identify the resilience implications of infrastructural decision making on a 2030/2050 timescale. Relevant and compelling future scenarios as well as hazard episodes are being developed as a context for analysis. In order to avoid an artificially segregated analysis, diverse stakeholders are being engaged to characterise the horizontal cross-sectoral interdependencies between relevant infrastructures and agencies, and the vertical interplay between micro, meso and macro layers of agencies and infrastructures. Models of relevant socio-technological systems are being built in order to capture the key causal relationships between actors. A fully interactive demonstrator system that operationalises resilience for key stakeholders is also being built.

Primary investigators

• sgb
• Andrew Dainty
• Richard Dawson
• Jonathan Rigg
• Jon Timmis
• Pete Fussey
• Brooke Rogers
• Beverley Searle

Secondary investigators

• mk7
• Paul Andrews
• Julia Pearce
• Gaihua Fu
• Chris Goodier
• Daniel Sage
• Lee Bosher

Associated research groups

• Science and Engineering of Natural Systems Group
• Agents, Interaction and Complexity

Date:

2011-2014

Theme:

Pervasive Healthcare and Telemedicine

Funding:

EUFP7

Stroke is a disease with very high socio-economic impact, the third biggest cause of death and the largest single cause of severe disability in the ageing populations of Europe. The World Health Organization has estimated 1.4 million deaths in Europe from stroke in 1999 and 1.17 million Disability Adjusted Life Years (DALYs) lost. In average the healthcare expenditure cost for Strokes across different countries in Europe and USA is 3% of their entire healthcare expenditure. This includes inpatient treatment cost, outpatient hospital visits and long-term rehabilitation and care. Analysis showed that costs of long-term care have increased from 13% to 49% of overall costs in average in recent years. Stroke has also a very serious impact on the life of affected persons. About one third of all stroke patients loose cognitive and physical abilities and return to their home with some level of permanent disability. This has significant impact on their quality of life as well as on the quality of life of their relatives. Therefore there is an urgent need for devising an effective long-term care and rehabilitation strategy for Stroke patients, which will involve the patients actively in the process while minimising costly human intervention. The StrokeBack project intends to develop an automated remote rehabilitation system by blending advances of ICT and practical clinical knowledge that will empower the patients and their immediate carer for effective application of the rehabilitation protocol in home settings. StrokeBack will combine state-of-the-art monitoring devices forming a wireless Body Area Network that enables simultaneous measurement of multiple vital parameters and currently executed movements that are particularly of interest from a Stroke rehabilitation point of view. The measured parameters will be fused using advanced feature extraction and classification algorithms processed on-body, which will denote the accuracy of the executed exercise. The training parameters along with vital data will be stored in a patient’s personal (under patient’s control) or medical (under control of the medical institution) Electronic Health Record (EHR) to which the responsible clinicians and therapists have access so that they can dynamically update the rehabilitation program. The effectiveness of the rehabilitation training and its attractiveness for patients will be enhanced through the use of game-like interface. This way doctors will be able to ensure that exercises are performed correctly and regularly, as well as easily monitor the progress of recovery having also insight into other patients’ medical parameters and results of relevant medical examinations. From the other side patients compliance will prescribed training procedures will be improved by turning the rehabilitation into an interactive game. By linking rehabilitation with Patient/Personal Electronic Health Record (PHR/EHR) the Stroke back project will offer means of correlating the rehabilitation exercises and personal activity monitoring with progressing changes in patients’ medical condition. This way the StrokeBack system will support medical practitioners in developing more reliable health care models for both prevention and rehabilitation from strokes. By employing manual intervention only when actually necessary, StrokeBack will eliminate costly human intervention and thereby significantly reduce the associated costs. The increased rehabilitation speed as well as the fact that the rehabilitation training can be done at home directly improves quality of life of patients. To sum up StrokeBack will increase rehabilitation speed and offer opportunities for prevention of stroke episodes without jeopardising the quality of care offered while significantly reducing associated health care costs. To achieve the StrokeBack goals research far beyond state of the art in the in the following fields is necessary: • telemedicine supervision of rehabilitation exercise • continuous monitoring of impact of the exercises also in “normal� life situations • integration of telemedicine rehabilitation and Personal Health Records for improved long term evaluation of patient recovery providing feedback to health care professionals on the impact of rehabilitation exercise

Primary investigator

• Koushik Maharatna

Secondary investigators

• Neil White
• Nick Harris
• awc
• Jane Burridge
• Bashir Al-Hashimi

Partner

• 7 EU partners

Associated research groups

• Electronic Systems and Devices Group
• Electronic and Software Systems
• Electronics and Electrical Engineering
• Pervasive Systems Centre