Advanced composite materials consist of reinforcement fibres, usually carbon or glass, embedded within a matrix, usually a polymer, providing a structural material. They are very attractive to a number of user sectors, in particular transportation due to their combination of low weight and excellent material properties which can be tailored to specific applications. Components are typically manufactured either by depositing fibres into a mould and then infusing with resin (liquid moulding) or by forming and consolidation of pre-impregnated fibres (prepreg processing). The current UK composites sector has a value of £1.5 billion and is projected to grow to over £4 billion by 2020, and to between £6 billion and £12 billion by 2030. This range depends on the ability of the industry to deliver structures at required volumes and quality levels demanded by its target applications. Much of this potential growth is associated with next generation single-aisle aircraft, light-weighting of vehicles to reduce fuel consumption, and large, lightweight and durable structures for renewable energy and civil infrastructure. The benefits of lightweight composites are clear, and growth in their use would have a significant impact on both the UK's climate change and infrastructure targets, in addition to a direct impact on the economy through jobs and exports. However the challenges that must be overcome to achieve this growth are significant. For example, BMW currently manufacture around 20,000 i3 vehicles per year with significant composites content. To replace mass produced vehicles this production volume would need to increase by up to 100-times. Airbus and Boeing each produce around 10 aircraft per month (A350 and 787 respectively) with high proportions of composite materials. The next generation single aisle aircraft are likely to require volumes of 60 per month. Production costs are high relative to those associated with other materials, and will need to reduce by an order of magnitude to enable such growth levels. The Future Composites Manufacturing Hub will enable a step change in manufacturing with advanced polymer composite materials. The Hub will be led by the University of Nottingham and University of Bristol; with initial research Spokes at Cranfield, Imperial College, Manchester and Southampton; Innovation Spokes at the National Composites Centre (NCC), Advanced Manufacturing Research Centre (AMRC), Manufacturing Technology Centre (MTC) and Warwick Manufacturing Group (WMG); and backed by 18 leading companies from the composites sector. Between the Hub, Spokes and industrial partners we will offer a minimum of £12.7 million in additional support to deliver our objectives. Building on the success of the EPSRC Centre for Innovative Manufacturing in Composites (CIMComp), the Hub will drive the development of automated manufacturing technologies that deliver components and structures for demanding applications, particularly in the aerospace, transportation, construction and energy sectors. Over a seven year period, the Hub will underpin the growth potential of the sector, by developing the underlying processing science and technology to enable Moore's law for composites: a doubling in production capability every two years. To achieve our vision we will address a number of research priorities, identified in collaboration with industry partners and the broader community, including: high rate deposition and rapid processing technologies; design for manufacture via validated simulation; manufacturing for multifunctional composites and integrated structures; inspection and in-process evaluation; recycling and re-use. Matching these priorities with UK capability, we have identified the following Grand Challenges, around which we will conduct a series of Feasibility Studies and Core Projects: -Enhance process robustness via understanding of process science -Develop high rate processing technologies for high quality structures

Medical imaging has transformed clinical medicine in the last 40 years. Diagnostic imaging provides the means to probe the structure and function of the human body without having to cut open the body to see disease or injury. Imaging is sensitive to changes associated with the early stages of cancer allowing detection of disease at a sufficient early stage to have a major impact on long-term survival. Combining imaging with therapy delivery and surgery enables 3D imaging to be used for guidance, i.e. minimising harm to surrounding tissue and increasing the likelihood of a successful outcome. The UK has consistently been at the forefront of many of these developments. Despite these advances we still do not know the most basic mechanisms and aetiology of many of the most disabling and dangerous diseases. Cancer survival remains stubbornly low for many of the most common cancers such as lung, head and neck, liver, pancreas. Some of the most distressing neurological disorders such as the dementias, multiple sclerosis, epilepsy and some of the more common brain cancers, still have woefully poor long term cure rates. Imaging is the primary means of diagnosis and for studying disease progression and response to treatment. To fully achieve its potential imaging needs to be coupled with computational modelling of biological function and its relationship to tissue structure at multiple scales. The advent of powerful computing has opened up exciting opportunities to better understand disease initiation and progression and to guide and assess the effectiveness of therapies. Meanwhile novel imaging methods, such as photoacoustics, and combinations of technologies such as simultaneous PET and MRI, have created entirely new ways of looking at healthy function and disturbances to normal function associated with early and late disease progression. It is becoming increasingly clear that a multi-parameter, multi-scale and multi-sensor approach combining advanced sensor design with advanced computational methods in image formation and biological systems modelling is the way forward. The EPSRC Centre for Doctoral Training in Medical Imaging will provide comprehensive and integrative doctoral training in imaging sciences and methods. The programme has a strong focus on new image acquisition technologies, novel data analysis methods and integration with computational modelling. This will be a 4-year PhD programme designed to prepare students for successful careers in academia, industry and the healthcare sector. It comprises an MRes year in which the student will gain core competencies in this rapidly developing field, plus the skills to innovate both with imaging devices and with computational methods. During the PhD (years 2 to 4) the student will undertake an in-depth study of an aspect of medical imaging and its application to healthcare and will seek innovative solutions to challenging problems. Most projects will be strongly multi-disciplinary with a principle supervisor being a computer scientist, physicist, mathematician or engineer, a second supervisor from a clinical or life science background, and an industrial supervisor when required. Each project will lie in the EPSRC's remit. The Centre will comprise 72 students at its peak after 4 years and will be obtaining dedicated space and facilities. The participating departments are strongly supportive of this initiative and will encourage new academic appointees to actively participate in its delivery. The Centre will fill a significant skills gap that has been identified and our graduates will have a major impact in academic research in his area, industrial developments including attracting inward investment and driving forward start-ups, and in advocacy of this important and expanding area of medical engineering.

The term "dementia" is used to describe a syndrome that results, initially, in cognitive function impairment and in many cases, a descending staircase of psychological dysfunction, leading eventually to death. It is a major socio-economic challenge with care costs approaching 1% of global GDP. Several conditions that lead to serious loss of cognitive ability are grouped under this syndrome, including Alzheimer's disease (AD), Vascular Dementia (VaD), Frontotemporal Dementia, etc. A high publicity announcement was made in 2012, by the Prime Minister, emphasising the high priority that should be given to dementia-related research and that funding will more than double in the immediate future, to partially remedy the fact that the overwhelming impact of the syndrome has been over-looked (Guardian, 26/3/12). On Dec 2013, the G8 Summit hosted in London brought together G8 ministers, researchers, pharmaceutical companies, and charities to develop co-ordinated global action on dementia. Dementia has marked adverse effects on the quality of life of tens of millions of people (both patients and carers) and exerts tremendous pressure on healthcare systems, especially when clear trends towards an ageing population, changing environmental influences and contemporary lifestyle choices are considered. Ca. 35M people suffer from dementia worldwide, a figure to quadruple by 2050. Europe and North America share a disproportionally high burden: the effects of ageing are particularly stark for these regions, exacerbating the healthcare provision implications. The Clinical Relevance: Vascular Cognitive Impairment (VCI). VCI defines alterations in cognition attributable to cerebrovascular causes, ranging from subtle or fixed deficits to full-blown dementia. VCI is a wide and accepted term referring to the "syndrome with evidence of clinical stroke or subclinical vascular brain injury and cognitive impairment affecting at least one cognitive domain", with resulting VaD being its most severe form. VaD is responsible for at least 20% of dementias, second only to AD, with a prevalence doubling every 5. 3 years. Several trials examined cholinesterase inhibitors for the treatment of vascular dementia, but the benefits are very modest, except in the individuals with a combination of AD and VaD. Vascular changes result in white matter (WM) damage (leukoaraiosis), which profoundly affect the fidelity of the information transfer underlying brain function and cognitive health8. Cerebral Magnetic Resonance Imaging (MRI) of Diffusion and Perfusion. MRI is a medical imaging technique affording non-invasive investigation of anatomy and tissue function, which is particularly suited to studying cognitive disorders due to its sensitivity and reliability. Our main interest is to characterise vascular and non-vascular tissues using quantitative diffusion and perfusion MR. Our overall aim is to characterise and quantify early differential alterations in brain blood transport and subsequent microstructural tissue damage using one-stop-shop perfusion/diffusion MR GSI incorporating novel MR signal models and optimal MR sequence design based on new human brain histomorphometric data in health and disease.

Launch and recovery of small vehicles from a large vessel is a common operation in maritime sectors, such as launching and recovering unmanned underwater vehicles from a patrol of research vessel or launching and recovering lifeboats from offshore platforms or ships. Such operations are often performed in harsh sea conditions. The recent User Inspired Academic Challenge Workshop on Maritime Launch and Recovery, held in July 2014 and coordinated by BAE systems, identified various challenges associated with safe launch and recovery of off-board, surface and sub-surface assets from vessels while underway in severe sea conditions. One of them is the lack of an accurate and efficient modelling tool for predicting the hydrodynamic loads on and the motion of two floating bodies, such as vessels of different size which may be coupled by a non-rigid link, in close proximity in harsh seas. Such a tool may be employed to minimise the risk of collisions and unacceptable motions, and to facilitate early testing of new concepts and systems. It may also be used to estimate hydrodynamic loads during the deployment of a smaller vessel (for example, a lifeboat) and during recovery of a smaller vessel from the deck of a larger vessel. The difficulties associated with development of such tools lie in the following aspects: (1) the water waves in harsh sea states have to be simulated; (2) the motion of the small vehicle and change in its wetted surface during launch or recovery can be very large, possibly moving from totally dry in air to becoming entirely submerged; (3) the viscous effects may play an important role and cannot be ignored, and will affect the coupling between ocean waves and motion of the vehicles. Existing methods and tools available to the industry cannot deal with all of these issues together and typically require very high computational resources. This project will develop an accurate and efficient numerical model that can be applied routinely for the analysis of the motion and loadings of two bodies in close proximity with or without physical connection in high sea-states, which of course can be employed to analyse the launch and recovery process of a small vehicle from a large vessel and to calculate the hydrodynamics during the process. This will be achieved building upon the recent developed numerical methods and computer codes by the project partners and also the success of the past and ongoing collaborative work between them. In addition, the project will involve several industrial partners to ensure the delivery of the project and to promote impact.

The aim of this proposal is to transform the design and manufacture of structural systems by relieving the bottleneck caused by the current practice of restricting designs to a linear dynamic regime. Our ambition is to not only address the challenge of dealing with nonlinearity, but to unlock the huge potential which can be gained from exploiting its positive attributes. The outputs will be a suite of novel modelling and control techniques which can be used directly in the design processes for structural systems, which we will demonstrate on a series of industry based experimental demonstrators. These design tools will enable a transformation in the performance of engineering structural systems which are under rapidly increasing demands from technological, economic and environmental pressures. The performance of engineering structures and systems is governed by how well they behave in their operating environment. For a significant number of engineering sectors, such as wind power generation, automotive, medical robotics, aerospace and large civil infrastructure, dynamic effects dominate the operational regime. As a result, understanding structural dynamics is crucial for ensuring that we have safe, reliable and efficient structures. In fact, the related mathematical problems extend to other modelling problems encountered in other important research areas such as systems biology, physiological modelling and information technology. So what exactly is the problem we are seeking to address in this proposal? Typically, when the behaviour of an engineering system is linear, computer simulations can be used to make very accurate predictions of its dynamic behaviour. The concept of end-to-end simulation and virtual prototyping, verification and testing has become a key paradigm across many sectors. The problem with this simulation based approach is that it is built on implicit assumptions of repeatability and linearity. For example, many structural analysis methods are based on the concept of a frequency domain charaterisation, which assumes that response of the system can be characterised by linear superposition of the response to each frequency seperately. But, the response of nonlinear systems is known to display amplitude dependence, sensitivity to transient effects in the forcing, and potential bistability or multiplicity of outcome for the same input frequency. As a result, when the system is nonlinear (which is nearly always the case for a large number of important industrial problems) it is almost impossible to make dynamic predictions without introducing very limiting approximations and simplifications. For example, throughout recent history, there have been many examples of unwanted vibrations; Failure of the Tacoma Narrows bridge (1940); cable-deck coupled vibrations on the DongTing Lake Bridge (1999); human induced vibration on the Millennium Bridge (2000); NASA Helios failure (2003); Coupling between thrusters and natural frequencies of the flexible structure on the International Space Station (2009); Landing gear shimmy. In many cases, the complexity of modern designs has outstripped our ability to understand their dynamic behaviour in detail. Even with the benefit of high power computing, which has enabled engineers to carry out detailed simulations, interpreting results from these simulations is a fundamental bottleneck, and it would seem that our ability to match experimental results is not improving, due primarily to the combination of random and uncertain effects and the failure of the linear superposition approach. As a result a new type of structural dynamics, which fully embraces nonlinearity, is urgently needed to enable the most efficient design and manufacture of the next generation of engineering structures.