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13 Projects, page 1 of 2

  • Canada
  • 2017-2021
  • UK Research and Innovation
  • 2015

10
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  • Funder: UKRI Project Code: NE/K005421/2
    Funder Contribution: 159,248 GBP
    Partners: AXYS, Newcastle University, Liquid Robotics

    Variations in sea level have a great environmental impact. They modulate coastal deposition, erosion and morphology, regulate heat and salt fluxes in estuaries, bays and ground waters, and control the dynamics of coastal ecosystems. Sea level variability has importance for coastal navigation, the building of coastal infrastructure, and the management of waste. The challenges of measuring, understanding and predicting sea level variations take particular relevance within the backdrop of global sea level rise, which might lead to the displacement of hundreds of millions of people by the end of this century. Sea level measurement relies primarily on the use of coastal tide gauges and satellite altimetry. Tide gauges provide sea levels at fine time resolutions (up to one second), but collect data only in coastal areas, and are irregularly distributed, with large gaps in the southern hemisphere and at high latitudes. Satellite altimetry, in contrast, has poor time resolution (ten days or longer), but provides near global coverage at moderate spatial resolutions (10-to-100 kilometres). Altimetric sea level products are problematic near the coast for reasons such as uncertainties in applying sea state bias corrections, errors in coastal tidal models, and large geoid gradients. The complicated shoreline geometry means that the raw altimeter data have to either undergo special transformations to provide more reliable measurements of sea level or be rejected. Developments in GPS measurements from buoys are now making it possible to determine sea surface heights with accuracy comparable to that of altimetry. In combination with coastal tide gauges, GPS buoys could be used as the nodes of a global sea level monitoring network extending beyond the coast. However, GPS buoys have several downsides. They are difficult and expensive to deploy, maintain, and recover, and, like conventional tide gauges, provide time series only at individual points in the ocean. This proposal focuses on the development of a unique system that overcomes these shortcomings. We propose a technology-led project to integrate Global Navigation Satellite Systems (GNSS i.e. encompassing GPS, GLONASS and, possibly, Galileo) technology with a state-of-the-art, unmanned surface vehicle: a Wave Glider. The glider farms the ocean wave field for propulsion, uses solar power to run on board equipment, and uses satellite communications for remote navigation and data transmission. A Wave Glider equipped with a high-accuracy GNSS receiver and data logger is effectively a fully autonomous, mobile, floating tide gauge. Missions and routes can be preprogrammed as well as changed remotely. Because the glider can be launched and retrieved from land or from a small boat, the costs associated with deployment, maintenance and recovery of the GNSS Wave Glider are comparatively small. GNSS Wave Glider technology promises a level of versatility well beyond that of existing ways of measuring sea levels. Potential applications of a GNSS Wave Glider include: 1) measurement of mean sea level and monitoring of sea level variations worldwide, 2) linking of offshore and onshore vertical datums, 3) calibration of satellite altimetry, notably in support of current efforts to reinterpret existing altimetric data near the coast, but also in remote and difficult to access areas, 4) determination of regional geoid variations, 5) ocean model improvement. The main thrust of this project is to integrate a state-of-the-art, geodetic-grade GNSS receiver and logging system with a Wave Glider recently acquired by NOC to create a mobile and autonomous GNSS-based tide gauge. By the end of the project, a demonstrator GNSS Wave Glider will be available for use by NOC and the UK marine community. The system performance will be validated against tide gauge data. Further tests will involve the use of the GNSS Wave Glider to calibrate sea surface heights and significant wave heights from Cryosat-2.

  • Funder: UKRI Project Code: EP/M003159/1
    Funder Contribution: 508,163 GBP
    Partners: Lehmann & Voss, University of Cambridge, CECEP DADI, Yunnan Institute of Building Materials, NTU, Federal University of Minas Gerais, Premier Magnesia, Shell Global Solutions UK, University of Toronto, China Three Gorges Corporation...

    Material innovations focussing on delivery and sustainability are key as our global efforts intensify in the development of a secure and sustainable future energy landscape. Many infrastructure-related material challenges have emerged as a result of the need (i) to explore offshore marine environments for wind power generation, (ii) for deeper and more complex underground wellbore systems for new oil & gas explorations, (iii) for robust containment and shielding structures for new nuclear power plants and (iv) for larger dam structures for future hydropower generation. Our vision for this proposal is to build a world leading and long lasting partnership between academics in the UK and China, integrated with industrial partners and other world leading academic groups around the world, to collectively address some of those construction material challenges with a focus on sustainability. The commonality in the assembled group is our interest and expertise in exploring potentials for magnesia-bearing construction materials in solving some of those new challenges, by either providing completely new solutions or enhanced solutions to existing material systems. This is a unique area to China and the UK where there is significant complementary expertise in the different grades of and applications for magnesia. The project consortium from the University of Cambridge, University College London, Chongqing University and Nanjing Tech University has the required interdisciplinary mix of materials, structural and geotechnical engineers, with world leading unique expertise in magnesia-based construction materials. The intention is to share and advance our global understanding of the performance of those proposed materials, road map future research and commercial needs and identify the ideal applications in our future energy infrastructures where most performance impact and sustainability benefits can be achieved. The proposed focusses two main areas of research. The first is the technical advantages and benefits that magnesia can provide to existing cement systems. This includes (i) its use as an expansive additive for large mass concrete constructions e.g. dams and nuclear installations, (ii) its role in magnesium phosphate cements for the developing of low pH cements suitable for nuclear waste applications and (iii) its role in advancing the development of alkali activated cements by providing low shrinkage and corrosion resistance. The second is the delivery of sustainable MgO production processes that focus on the use of both mineral and reject brine resources. An integral part of this project will be the knowledge transfer activities and collaboration with industry and other relevant research centres around the world. An overarching aspect of the proposed research is the mapping out of the team's capabilities and the integration of expertise and personnel exchange to ensure maximum impact. This will ensure that the research is at the forefront of the global pursuit for a sustainable future energy infrastructure and will ensure that maximum impact is achieved. The consortium plans to act as a global hub to provide a national and international platform for facilitating dialogue and collaboration to enhance the global knowledge economy.

  • Funder: UKRI Project Code: NE/M021025/1
    Funder Contribution: 1,473,360 GBP
    Partners: CNRS, LSU, Chiba University, University of Liège, GFZ Potsdam - Geosciences, University of Copenhagen, KU Leuven Kulak, Utrecht University, Danish Geological Survey - GEUS, University of Alberta...

    Concerns are growing about how much melting occurs on the surface of the Greenland Ice Sheet (GrIS), and how much this melting will contribute to sea level rise (1). It seems that the amount of melting is accelerating and that the impact on sea level rise is over 1 mm each year (2). This information is of concern to governmental policy makers around the world because of the risk to viability of populated coastal and low-lying areas. There is currently a great scientific need to predict the amount of melting that will occur on the surface of the GrIS over the coming decades (3), since the uncertainties are high. The current models which are used to predict the amount of melting in a warmer climate rely heavily on determining the albedo, the ratio of how reflective the snow cover and the ice surface are to incoming solar energy. Surfaces which are whiter are said to have higher albedo, reflect more sunlight and melt less. Surfaces which are darker adsorb more sunlight and so melt more. Just how the albedo varies over time depends on a number of factors, including how wet the snow and ice is. One important factor that has been missed to date is bio-albedo. Each drop of water in wet snow and ice contains thousands of tiny microorganisms, mostly algae and cyanobacteria, which are pigmented - they have a built in sunblock - to protect them from sunlight. These algae and cyanobacteria have a large impact on the albedo, lowering it significantly. They also glue together dust particles that are swept out of the air by the falling snow. These dust particles also contain soot from industrial activity and forest fires, and so the mix of pigmented microbes and dark dust at the surface produces a darker ice sheet. We urgently need to know more about the factors that lead to and limit the growth of the pigmented microbes. Recent work by our group in the darkest zone of the ice sheet surface in the SW of Greenland shows that the darkest areas have the highest numbers of cells. Were these algae to grow equally well in other areas of the ice sheet surface, then the rate of melting of the whole ice sheet would increase very quickly. A major concern is that there will be more wet ice surfaces for these microorganisms to grow in, and for longer, during a period of climate warming, and so the microorganisms will grow in greater numbers and over a larger area, lowering the albedo and increasing the amount of melt that occurs each year. The nutrient - plant food - that the microorganisms need comes from the ice crystals and dust on the ice sheet surface, and there are fears that increased N levels in snow and ice may contribute to the growth of the microorganisms. This project aims to be the first to examine the growth and spread of the microorganisms in a warming climate, and to incorporate biological darkening into models that predict the future melting of the GrIS. References 1. Sasgen I and 8 others. Timing and origin of recent regional ice-mass loss in Greenland. Earth and Planetary Science Letters, 333-334, 293-303(2012). 2. Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A. & Lenaerts, J. Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise. Geophys. Res. Lett. 38, L05503, doi:10.1029/2011gl046583 (2011). 3. Milne, G. A., Gehrels, W. R., Hughes, C. W. & Tamisiea, M. E. Identifying the causes of sea-level change. Nature Geosci 2, 471-478 (2009).

  • Funder: UKRI Project Code: NE/M011429/1
    Funder Contribution: 549,872 GBP
    Partners: RPC, Namibia Rare Earths Inc, Mkango Resources Limited, FAPESP, Umwelt und Ingenieurtechnik GmbH, Nuna Minerals A/S, University of Exeter, Maakrish Ltd, UCT, SRK Consulting UK Ltd...

    Rare earth elements (REE) are the headline of the critical metals security of supply agenda. All the REE were defined as critical by the European Union in 2010, and in subsequent analysis in 2014. Similar projects in the UK and USA have highlighted 'heavy' REE (HREE - europium through to lutetium) as the metals most likely to be at risk of supply disruption and in short supply in the near future. The REE are ubiquitous within modern technologies, including computers and low energy lighting, energy storage devices, large wind turbines and smart materials, making their supply vital to UK society. The challenge is to develop new environmentally friendly and economically viable, neodymium (Nd) and HREE deposits so that use of REE in new and green technologies can continue to expand. The principal aims of this project are to understand the mobility and concentration of Nd and HREE in natural systems and to investigate new processes that will lower the environmental impact of REE extraction and recovery. By concentrating on the critical REE, the research will be wide ranging in the deposits and processing techniques considered. It gives NERC and the UK a world-leading research consortium on critical REE, concentrating on deposit types identified in the catalyst phase as most likely to have low environmental impact, and on research that bridges the two goals of the SoS programme. The project brings together two groups from the preceding catalyst projects (GEM-CRE, MM-FREE) to form a new interdisciplinary team, including the UK's leading experts in REE geology and metallurgy, together with materials science, high/low temperature fluid geochemistry, computational simulation/mineral physics, geomicrobiology and bioprocessing. The team brings substantial background IP and the key skills required. The research responds to the needs of industry partners and involves substantive international collaboration as well as a wider international and UK network across the REE value chain. The work programme has two strands. The first centres on conventional deposits, which comprise all of the REE mines outside China and the majority of active exploration and development projects. The aim is to make a step change in the understanding of the mobility of REE in these natural deposits via mineralogical analysis, experiments and computational simulation. Then, based on this research, the aim is to optimise the most relevant extraction methods. The second strand looks to the future to develop a sustainable new method of REE extraction. The focus will be the ion adsorption deposits, which could be exploited with the lowest environmental impact of any of the main ore types using a well-controlled in-situ leaching operation. Impact will be immediate through our industry partners engaged in REE exploration and development projects, who will gain improved deposit models and better and more efficient, and therefore more environmentally friendly, extraction techniques. There will be wider benefits for researchers in other international teams and companies as we publish our results. Security of REE supply is a major international issue and the challenges tackled in this research will be relevant to practically all REE deposits. Despite the UK not having world class REE deposits itself, the economy is reliant on REE (e.g. the functional materials and devices industry is worth ~£3 Bn p.a.) and therefore the UK must lead research into the extraction process. Manufacturers who use REE will also benefit from the research by receiving up to date information on prospects for future Nd and HREE supply. This will help plan their longer term product development, as well as shorter term purchasing strategy. Likewise, the results will be useful to inform national and European level policy and to interest, entertain and educate the wider community about the natural characters and importance of the REE.

  • Funder: UKRI Project Code: BB/M026671/1
    Funder Contribution: 241,275 GBP
    Partners: DFO, MSS, UCC, Institute of Marine Research (IMR), NINA, AgriFood and Biosciences Institute, AquaGen, UHI

    Controversy surrounds the actual impacts of Atlantic salmon farming on wild salmonid stocks, fed by the lack of direct evidence for or against many potential impacts, with uncertainty an increasing impediment to sustainable industry development and effective management of wild stocks. This applies to the potential impact of the introgression of farm genomes into locally adapted wild populations from breeding of farm escapes. Escapes do occur and are recognized as inevitable, but are a very small fraction of farm stocks and vary in numbers both locally and temporally. The majority of escapees are expected to die without breeding but some do remain in or ascend rivers and spawn. However, a detailed understanding of actual levels of interbreeding and introgression in most rivers is lacking which, along with an understanding of the adaptive differentiation of farm and wild salmon, is required to establish the actual impact of this potential interaction on the productivity and viability of wild populations. Detection and quantification of interbreeding and introgression requires diagnostic markers for farm and wild genomes. Genetic differentiation of farm and wild genomes can evolve through founder effects, selective breeding and domestication selection and is observed in respect of a variety of molecular markers. However, existing molecular markers are not fully diagnostic and regionally constrained in their usefulness. Unfortunately, marker panels screened for useful variation have been small and arbitrary such that they are unlikely to include the most informative loci and to be context specific, limiting their power and transferability. To properly address the issue of introgression molecular markers are required that are highly diagnostic across all farm and wild populations. These markers will be in genomic regions involved in domestication and controlling the expression of selected economic traits. What is known of the genomic architecture of domestication and most economic traits indicates their control is polygenic, making the targeting of specific gene regions in the search for markers difficult. In contrast, recent advances in genomics make possible genome scanning and genome-wide association studies (GWAS) which can provide a high resolution assessment of molecular differentiation between different individuals or populations across the genome. Different GWAS strategies can be employed but two are deemed optimal in the current context. Firstly, a GWAS will be carried out using a new Atlantic salmon SNP (single nucleotide polymorphism) containing 930k nuclear SNPs, recently developed in collaboration with the salmon farming industry. This will be carried out on a broad base of representative farm and wild stocks. Secondly, GWAS will be carried out to identify temporally stable epigenetic DNA-methylation base changes induced by rearing fish in culture by comparing groups of single source wild fish reared in the wild and in culture. The study will deliver the first general understanding of domestication related molecular genetic differentiation between farmed and wild salmon and identify the best markers for identifying farm salmon in the wild and assessing genetic introgression of farm genes into wild populations. The work will deliver a more robust and generally applicable tool for determining the actual levels of escapes and introgression in wild salmon populations. Following field calibration and independent validation, the diagnostic methodology defined in the study is expected to provide the basis for generating the evidence needed to clarify the debate on levels of escapes and introgression and the long term impacts of introgression on population viability. This will help to define more clearly the path forward for the sustainable development of the salmon farming industry in the UK and elsewhere in the North Atlantic region and help to inform management priorities for wild Atlantic salmon stocks.

  • Funder: UKRI Project Code: EP/M006255/1
    Funder Contribution: 950,403 GBP
    Partners: Lancaster University, Lancashire Care NHS Foundation Trust, NIHR CRN: North West Coast, SR Research Ltd

    There is mounting evidence that deficits in saccadic and smooth pursuit eye movements are characteristic of dementia. These deficits can be detected in a lab or clinical setting using specialised eye-tracking equipment but this is inconvenient for the patient, costly for the NHS and introduces the risk of sampling bias because clinic visits are inevitably intermittent. The aim of the Monitoring Of Dementia using Eye Movements (MODEM) project is to enable the longitudinal collection of data at low cost and with minimal inconvenience, to provide a novel platform for prognosis and diagnosis of dementia. We propose to tackle monitoring of disease progression with in-home eye tracking and computational analysis of eye movement embedded with patients' everyday activity. This is an entirely novel approach, and hence high risk. However, it has the potential to lead to major breakthroughs, for three reasons: (i) Eye movement and cognitive health are closely linked, including initial evidence of markers for dementia diagnosis. (ii) Eye trackers are on the verge of a step change from lab instrument to widely deployed sensor, and their adoption for contact-less health monitoring is becoming a realistic proposition. (iii) People/patients use their eyes in daily routines that are visually engaging, and that present rich contexts for collection of information about how their eye movement changes over time, as a function of disease progression. Our vision is that rather than patients having to attend a clinic or laboratory, eye movement data can be collected in settings where the technology is ambient and peoples' behaviour is relaxed and natural. The target settings are peoples' own homes and care homes. Eye trackers can be placed strategically to observe eye movement in the context of everyday tasks. For example they can be used to track hand-eye coordination in routine tasks such as tea-making for possible signs of change; these might signal cognitive decline long before routines become more obviously affected. Eye trackers can also be deployed interactively. People spend significant amounts of their daily lives as consumers of visual media, especially through TV, which affords interactive stimulation of eye movement. For example, content (e.g. TV programmes) can be designed to elicit behaviours of interest for diagnosis. People can also be provided with active gaze controls for interaction, for instance as alternative to remote control functions of a TV. Use of gaze for control stimulates specific eye movements which can be used for testing. Though beyond the scope project, this could also lead to therapeutic application of the technology. Moreover, as eye trackers are based on cameras and computer vision, this opens up avenues for integration with other vision-based approaches such as analysis of facial expressions, for multimodal cognitive health analysis.

  • Funder: UKRI Project Code: EP/M019918/1
    Funder Contribution: 4,991,610 GBP
    Partners: Amey Plc, DfT, NAVTECH RADAR LIMITED, Automotive Council UK, UKSA, Tracetronic, FHG, University of Pennsylvania, OC Robotics, McGill University...

    VISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.

  • Funder: UKRI Project Code: EP/M02797X/1
    Funder Contribution: 96,770 GBP
    Partners: Cornell University, University of Waterloo (Canada), LSE

    The proposed research contributes to fundamental topics in Combinatorial Optimisation, aiming to devise strongly polynomial algorithms for new classes of linear and nonlinear optimisation problems. The notion of polynomial-time complexity, introduced in the 1970s, is a standard way to capture computational efficiency of a wide variety of algorithms. Strongly polynomial-time algorithms give a natural strengthening of this notion: the number of arithmetic operations should not depend on numerical parameters such as costs or capacities in the problem description, but only on the number of such parameters. Strongly polynomial algorithms are known for many important optimisation problems. However, it remains an outstanding open problem to devise such an algorithm for a very fundamental optimisation problem: Linear Programming. The most important goal of the proposal is to develop a strongly polynomial algorithm for linear programs with at most two nonzero entries per column. The problem is equivalent to minimum-cost generalised flows, a classical model in the theory of network flows. Finding a strongly polynomial algorithm was a longstanding open question even for the special case of flow maximisation, resolved by the applicant in a recent paper. Further goals of the proposal include strongly polynomial algorithms for related nonlinear optimisation problems. Nonlinear convex network flow models have important applications for market equilibrium computation in mathematical economics. Very few nonlinear problems are known to admit strongly polynomial algorithms. The proposal aims for a systematic study of such problems, and will also contribute to the understanding of computational aspects of market equilibrium models.

  • Funder: UKRI Project Code: NE/M013693/1
    Funder Contribution: 272,801 GBP
    Partners: SFU, Met Office, ECMWF, LANL, University of Reading

    This project is about using moving meshes - r-adaptivity - to improve the predictive power of atmospheric flow simulations, which are used in the fields of numerical weather prediction and climate modelling. When the atmosphere is simulated on a computer, this is done by dividing the sphere into cells which are arranged in a mesh. There is a conflict between the need for accuracy, which requires smaller (and hence more) cells, and computational efficiency, which increases with the number of cells. A reasonable question to ask is: for a given amount of accuracy, what size of cells do I need? The answer can be provided mathematically, but it depends on what is actually happening in the atmosphere simulation. Much smaller cells are required in the regions of smaller scale features such as atmospheric fronts, cyclones, jets, convective cells etc. It then seems like a waste to choose the same cell size all over the globe even in regions where these features are absent. An attractive idea is to try to stretch, deform and move the mesh around so that smaller cells are used in the regions of small scale features, and larger cells are used elsewhere. This would mean that a better compromise can be made between accuracy and computational efficiency, thus improving predictive power for the same resource. This idea has been used successfully in many engineering applications, and the goal of this project is to transmit this technology to atmosphere simulation, where it can be used by meteorologists and climate scientists to take their science forward. There are, however, a number of challenging aspects. Efficient mesh movement algorithms have not previously been developed for the sphere geometry which is needed for global atmosphere simulations. There is the question of how to detect where the mesh should be moved to. It is also the case that it is very challenging to design stable and accurate numerical algorithms for simulating the atmosphere, and these must be adapted to remain stable and accurate under mesh movement. All of these questions and issues will be addressed in this project.

  • Funder: UKRI Project Code: NE/M017028/1
    Funder Contribution: 766,686 GBP
    Partners: University of Salford, WU, University of Guelph

    Soils provide many functions for humans, including the storage of carbon and nutrient cycling, which are crucial for the production of food and mitigation of climate change. However, there is much concern that soils, and the functions that they provide, are being threatened by a range of pressures, including intensive farming methods and increased frequency of extreme climatic events, such as drought. Not only do these disturbances pose an immediate threat to the functioning of soils, but they could also impair their ability to resist and recover from further stresses that come in the future. Our project will tackle this problem by addressing two general questions: first, what makes a soil able to withstand and recover from disturbance events, such as drought, and, second how can we use this knowledge to ensure soils can buffer disturbances in the future? These are questions that have puzzled soil scientists for many years, but so far, remain unresolved. An area that offers much promise, however, in tackling this issue is food web ecology. Food webs are the networks of interactions describing who eats whom amongst the myriad organisms within an ecosystem. And in soil, they are the engine that drives the very processes of nutrient cycling and energy flow on which the functioning of soil and the terrestrial ecosystems they support, depend. It has been proposed for many years, but so far not fully tested in soil, that simple food webs are less able to withstand and recover from disturbance events, such as drought than complex ones. We want to test this theory in soil, which harbours some of the most complex, but also sensitive, food webs on Earth. We test the idea, through experiments and models, that the ability of a soil to withstand, recover and adapt to disturbance events depends on the architecture and diversity of the soil food web, which governs the rate of transfer of nutrients and energy through the plant-soil system. We also propose that soil disturbances associated with intensive land use, such as trampling and fertiliser addition, erode the very food web structures that make the soil system stable, thereby reducing the ability of soil to resist and recover from future disturbances, such as extreme weather events. We will also resolve what makes a food web stable, and test the roles of different types of organisms in soil, such as mycorrhizal fungi, which we believe play a major role. And finally, we will develop new models to help us better predict how soils will respond to future threats and to guide management decisions on sustainable soil management in a rapidly changing world. These question are at the heart of the NERC Soil Security programme which seeks to resolve what controls the ability of soils and their functions to resist, recover and ultimately adapt, to perturbations, such as those caused by land use and extreme climatic events.

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The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
13 Projects, page 1 of 2
  • Funder: UKRI Project Code: NE/K005421/2
    Funder Contribution: 159,248 GBP
    Partners: AXYS, Newcastle University, Liquid Robotics

    Variations in sea level have a great environmental impact. They modulate coastal deposition, erosion and morphology, regulate heat and salt fluxes in estuaries, bays and ground waters, and control the dynamics of coastal ecosystems. Sea level variability has importance for coastal navigation, the building of coastal infrastructure, and the management of waste. The challenges of measuring, understanding and predicting sea level variations take particular relevance within the backdrop of global sea level rise, which might lead to the displacement of hundreds of millions of people by the end of this century. Sea level measurement relies primarily on the use of coastal tide gauges and satellite altimetry. Tide gauges provide sea levels at fine time resolutions (up to one second), but collect data only in coastal areas, and are irregularly distributed, with large gaps in the southern hemisphere and at high latitudes. Satellite altimetry, in contrast, has poor time resolution (ten days or longer), but provides near global coverage at moderate spatial resolutions (10-to-100 kilometres). Altimetric sea level products are problematic near the coast for reasons such as uncertainties in applying sea state bias corrections, errors in coastal tidal models, and large geoid gradients. The complicated shoreline geometry means that the raw altimeter data have to either undergo special transformations to provide more reliable measurements of sea level or be rejected. Developments in GPS measurements from buoys are now making it possible to determine sea surface heights with accuracy comparable to that of altimetry. In combination with coastal tide gauges, GPS buoys could be used as the nodes of a global sea level monitoring network extending beyond the coast. However, GPS buoys have several downsides. They are difficult and expensive to deploy, maintain, and recover, and, like conventional tide gauges, provide time series only at individual points in the ocean. This proposal focuses on the development of a unique system that overcomes these shortcomings. We propose a technology-led project to integrate Global Navigation Satellite Systems (GNSS i.e. encompassing GPS, GLONASS and, possibly, Galileo) technology with a state-of-the-art, unmanned surface vehicle: a Wave Glider. The glider farms the ocean wave field for propulsion, uses solar power to run on board equipment, and uses satellite communications for remote navigation and data transmission. A Wave Glider equipped with a high-accuracy GNSS receiver and data logger is effectively a fully autonomous, mobile, floating tide gauge. Missions and routes can be preprogrammed as well as changed remotely. Because the glider can be launched and retrieved from land or from a small boat, the costs associated with deployment, maintenance and recovery of the GNSS Wave Glider are comparatively small. GNSS Wave Glider technology promises a level of versatility well beyond that of existing ways of measuring sea levels. Potential applications of a GNSS Wave Glider include: 1) measurement of mean sea level and monitoring of sea level variations worldwide, 2) linking of offshore and onshore vertical datums, 3) calibration of satellite altimetry, notably in support of current efforts to reinterpret existing altimetric data near the coast, but also in remote and difficult to access areas, 4) determination of regional geoid variations, 5) ocean model improvement. The main thrust of this project is to integrate a state-of-the-art, geodetic-grade GNSS receiver and logging system with a Wave Glider recently acquired by NOC to create a mobile and autonomous GNSS-based tide gauge. By the end of the project, a demonstrator GNSS Wave Glider will be available for use by NOC and the UK marine community. The system performance will be validated against tide gauge data. Further tests will involve the use of the GNSS Wave Glider to calibrate sea surface heights and significant wave heights from Cryosat-2.

  • Funder: UKRI Project Code: EP/M003159/1
    Funder Contribution: 508,163 GBP
    Partners: Lehmann & Voss, University of Cambridge, CECEP DADI, Yunnan Institute of Building Materials, NTU, Federal University of Minas Gerais, Premier Magnesia, Shell Global Solutions UK, University of Toronto, China Three Gorges Corporation...

    Material innovations focussing on delivery and sustainability are key as our global efforts intensify in the development of a secure and sustainable future energy landscape. Many infrastructure-related material challenges have emerged as a result of the need (i) to explore offshore marine environments for wind power generation, (ii) for deeper and more complex underground wellbore systems for new oil & gas explorations, (iii) for robust containment and shielding structures for new nuclear power plants and (iv) for larger dam structures for future hydropower generation. Our vision for this proposal is to build a world leading and long lasting partnership between academics in the UK and China, integrated with industrial partners and other world leading academic groups around the world, to collectively address some of those construction material challenges with a focus on sustainability. The commonality in the assembled group is our interest and expertise in exploring potentials for magnesia-bearing construction materials in solving some of those new challenges, by either providing completely new solutions or enhanced solutions to existing material systems. This is a unique area to China and the UK where there is significant complementary expertise in the different grades of and applications for magnesia. The project consortium from the University of Cambridge, University College London, Chongqing University and Nanjing Tech University has the required interdisciplinary mix of materials, structural and geotechnical engineers, with world leading unique expertise in magnesia-based construction materials. The intention is to share and advance our global understanding of the performance of those proposed materials, road map future research and commercial needs and identify the ideal applications in our future energy infrastructures where most performance impact and sustainability benefits can be achieved. The proposed focusses two main areas of research. The first is the technical advantages and benefits that magnesia can provide to existing cement systems. This includes (i) its use as an expansive additive for large mass concrete constructions e.g. dams and nuclear installations, (ii) its role in magnesium phosphate cements for the developing of low pH cements suitable for nuclear waste applications and (iii) its role in advancing the development of alkali activated cements by providing low shrinkage and corrosion resistance. The second is the delivery of sustainable MgO production processes that focus on the use of both mineral and reject brine resources. An integral part of this project will be the knowledge transfer activities and collaboration with industry and other relevant research centres around the world. An overarching aspect of the proposed research is the mapping out of the team's capabilities and the integration of expertise and personnel exchange to ensure maximum impact. This will ensure that the research is at the forefront of the global pursuit for a sustainable future energy infrastructure and will ensure that maximum impact is achieved. The consortium plans to act as a global hub to provide a national and international platform for facilitating dialogue and collaboration to enhance the global knowledge economy.

  • Funder: UKRI Project Code: NE/M021025/1
    Funder Contribution: 1,473,360 GBP
    Partners: CNRS, LSU, Chiba University, University of Liège, GFZ Potsdam - Geosciences, University of Copenhagen, KU Leuven Kulak, Utrecht University, Danish Geological Survey - GEUS, University of Alberta...

    Concerns are growing about how much melting occurs on the surface of the Greenland Ice Sheet (GrIS), and how much this melting will contribute to sea level rise (1). It seems that the amount of melting is accelerating and that the impact on sea level rise is over 1 mm each year (2). This information is of concern to governmental policy makers around the world because of the risk to viability of populated coastal and low-lying areas. There is currently a great scientific need to predict the amount of melting that will occur on the surface of the GrIS over the coming decades (3), since the uncertainties are high. The current models which are used to predict the amount of melting in a warmer climate rely heavily on determining the albedo, the ratio of how reflective the snow cover and the ice surface are to incoming solar energy. Surfaces which are whiter are said to have higher albedo, reflect more sunlight and melt less. Surfaces which are darker adsorb more sunlight and so melt more. Just how the albedo varies over time depends on a number of factors, including how wet the snow and ice is. One important factor that has been missed to date is bio-albedo. Each drop of water in wet snow and ice contains thousands of tiny microorganisms, mostly algae and cyanobacteria, which are pigmented - they have a built in sunblock - to protect them from sunlight. These algae and cyanobacteria have a large impact on the albedo, lowering it significantly. They also glue together dust particles that are swept out of the air by the falling snow. These dust particles also contain soot from industrial activity and forest fires, and so the mix of pigmented microbes and dark dust at the surface produces a darker ice sheet. We urgently need to know more about the factors that lead to and limit the growth of the pigmented microbes. Recent work by our group in the darkest zone of the ice sheet surface in the SW of Greenland shows that the darkest areas have the highest numbers of cells. Were these algae to grow equally well in other areas of the ice sheet surface, then the rate of melting of the whole ice sheet would increase very quickly. A major concern is that there will be more wet ice surfaces for these microorganisms to grow in, and for longer, during a period of climate warming, and so the microorganisms will grow in greater numbers and over a larger area, lowering the albedo and increasing the amount of melt that occurs each year. The nutrient - plant food - that the microorganisms need comes from the ice crystals and dust on the ice sheet surface, and there are fears that increased N levels in snow and ice may contribute to the growth of the microorganisms. This project aims to be the first to examine the growth and spread of the microorganisms in a warming climate, and to incorporate biological darkening into models that predict the future melting of the GrIS. References 1. Sasgen I and 8 others. Timing and origin of recent regional ice-mass loss in Greenland. Earth and Planetary Science Letters, 333-334, 293-303(2012). 2. Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A. & Lenaerts, J. Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise. Geophys. Res. Lett. 38, L05503, doi:10.1029/2011gl046583 (2011). 3. Milne, G. A., Gehrels, W. R., Hughes, C. W. & Tamisiea, M. E. Identifying the causes of sea-level change. Nature Geosci 2, 471-478 (2009).

  • Funder: UKRI Project Code: NE/M011429/1
    Funder Contribution: 549,872 GBP
    Partners: RPC, Namibia Rare Earths Inc, Mkango Resources Limited, FAPESP, Umwelt und Ingenieurtechnik GmbH, Nuna Minerals A/S, University of Exeter, Maakrish Ltd, UCT, SRK Consulting UK Ltd...

    Rare earth elements (REE) are the headline of the critical metals security of supply agenda. All the REE were defined as critical by the European Union in 2010, and in subsequent analysis in 2014. Similar projects in the UK and USA have highlighted 'heavy' REE (HREE - europium through to lutetium) as the metals most likely to be at risk of supply disruption and in short supply in the near future. The REE are ubiquitous within modern technologies, including computers and low energy lighting, energy storage devices, large wind turbines and smart materials, making their supply vital to UK society. The challenge is to develop new environmentally friendly and economically viable, neodymium (Nd) and HREE deposits so that use of REE in new and green technologies can continue to expand. The principal aims of this project are to understand the mobility and concentration of Nd and HREE in natural systems and to investigate new processes that will lower the environmental impact of REE extraction and recovery. By concentrating on the critical REE, the research will be wide ranging in the deposits and processing techniques considered. It gives NERC and the UK a world-leading research consortium on critical REE, concentrating on deposit types identified in the catalyst phase as most likely to have low environmental impact, and on research that bridges the two goals of the SoS programme. The project brings together two groups from the preceding catalyst projects (GEM-CRE, MM-FREE) to form a new interdisciplinary team, including the UK's leading experts in REE geology and metallurgy, together with materials science, high/low temperature fluid geochemistry, computational simulation/mineral physics, geomicrobiology and bioprocessing. The team brings substantial background IP and the key skills required. The research responds to the needs of industry partners and involves substantive international collaboration as well as a wider international and UK network across the REE value chain. The work programme has two strands. The first centres on conventional deposits, which comprise all of the REE mines outside China and the majority of active exploration and development projects. The aim is to make a step change in the understanding of the mobility of REE in these natural deposits via mineralogical analysis, experiments and computational simulation. Then, based on this research, the aim is to optimise the most relevant extraction methods. The second strand looks to the future to develop a sustainable new method of REE extraction. The focus will be the ion adsorption deposits, which could be exploited with the lowest environmental impact of any of the main ore types using a well-controlled in-situ leaching operation. Impact will be immediate through our industry partners engaged in REE exploration and development projects, who will gain improved deposit models and better and more efficient, and therefore more environmentally friendly, extraction techniques. There will be wider benefits for researchers in other international teams and companies as we publish our results. Security of REE supply is a major international issue and the challenges tackled in this research will be relevant to practically all REE deposits. Despite the UK not having world class REE deposits itself, the economy is reliant on REE (e.g. the functional materials and devices industry is worth ~£3 Bn p.a.) and therefore the UK must lead research into the extraction process. Manufacturers who use REE will also benefit from the research by receiving up to date information on prospects for future Nd and HREE supply. This will help plan their longer term product development, as well as shorter term purchasing strategy. Likewise, the results will be useful to inform national and European level policy and to interest, entertain and educate the wider community about the natural characters and importance of the REE.

  • Funder: UKRI Project Code: BB/M026671/1
    Funder Contribution: 241,275 GBP
    Partners: DFO, MSS, UCC, Institute of Marine Research (IMR), NINA, AgriFood and Biosciences Institute, AquaGen, UHI

    Controversy surrounds the actual impacts of Atlantic salmon farming on wild salmonid stocks, fed by the lack of direct evidence for or against many potential impacts, with uncertainty an increasing impediment to sustainable industry development and effective management of wild stocks. This applies to the potential impact of the introgression of farm genomes into locally adapted wild populations from breeding of farm escapes. Escapes do occur and are recognized as inevitable, but are a very small fraction of farm stocks and vary in numbers both locally and temporally. The majority of escapees are expected to die without breeding but some do remain in or ascend rivers and spawn. However, a detailed understanding of actual levels of interbreeding and introgression in most rivers is lacking which, along with an understanding of the adaptive differentiation of farm and wild salmon, is required to establish the actual impact of this potential interaction on the productivity and viability of wild populations. Detection and quantification of interbreeding and introgression requires diagnostic markers for farm and wild genomes. Genetic differentiation of farm and wild genomes can evolve through founder effects, selective breeding and domestication selection and is observed in respect of a variety of molecular markers. However, existing molecular markers are not fully diagnostic and regionally constrained in their usefulness. Unfortunately, marker panels screened for useful variation have been small and arbitrary such that they are unlikely to include the most informative loci and to be context specific, limiting their power and transferability. To properly address the issue of introgression molecular markers are required that are highly diagnostic across all farm and wild populations. These markers will be in genomic regions involved in domestication and controlling the expression of selected economic traits. What is known of the genomic architecture of domestication and most economic traits indicates their control is polygenic, making the targeting of specific gene regions in the search for markers difficult. In contrast, recent advances in genomics make possible genome scanning and genome-wide association studies (GWAS) which can provide a high resolution assessment of molecular differentiation between different individuals or populations across the genome. Different GWAS strategies can be employed but two are deemed optimal in the current context. Firstly, a GWAS will be carried out using a new Atlantic salmon SNP (single nucleotide polymorphism) containing 930k nuclear SNPs, recently developed in collaboration with the salmon farming industry. This will be carried out on a broad base of representative farm and wild stocks. Secondly, GWAS will be carried out to identify temporally stable epigenetic DNA-methylation base changes induced by rearing fish in culture by comparing groups of single source wild fish reared in the wild and in culture. The study will deliver the first general understanding of domestication related molecular genetic differentiation between farmed and wild salmon and identify the best markers for identifying farm salmon in the wild and assessing genetic introgression of farm genes into wild populations. The work will deliver a more robust and generally applicable tool for determining the actual levels of escapes and introgression in wild salmon populations. Following field calibration and independent validation, the diagnostic methodology defined in the study is expected to provide the basis for generating the evidence needed to clarify the debate on levels of escapes and introgression and the long term impacts of introgression on population viability. This will help to define more clearly the path forward for the sustainable development of the salmon farming industry in the UK and elsewhere in the North Atlantic region and help to inform management priorities for wild Atlantic salmon stocks.

  • Funder: UKRI Project Code: EP/M006255/1
    Funder Contribution: 950,403 GBP
    Partners: Lancaster University, Lancashire Care NHS Foundation Trust, NIHR CRN: North West Coast, SR Research Ltd

    There is mounting evidence that deficits in saccadic and smooth pursuit eye movements are characteristic of dementia. These deficits can be detected in a lab or clinical setting using specialised eye-tracking equipment but this is inconvenient for the patient, costly for the NHS and introduces the risk of sampling bias because clinic visits are inevitably intermittent. The aim of the Monitoring Of Dementia using Eye Movements (MODEM) project is to enable the longitudinal collection of data at low cost and with minimal inconvenience, to provide a novel platform for prognosis and diagnosis of dementia. We propose to tackle monitoring of disease progression with in-home eye tracking and computational analysis of eye movement embedded with patients' everyday activity. This is an entirely novel approach, and hence high risk. However, it has the potential to lead to major breakthroughs, for three reasons: (i) Eye movement and cognitive health are closely linked, including initial evidence of markers for dementia diagnosis. (ii) Eye trackers are on the verge of a step change from lab instrument to widely deployed sensor, and their adoption for contact-less health monitoring is becoming a realistic proposition. (iii) People/patients use their eyes in daily routines that are visually engaging, and that present rich contexts for collection of information about how their eye movement changes over time, as a function of disease progression. Our vision is that rather than patients having to attend a clinic or laboratory, eye movement data can be collected in settings where the technology is ambient and peoples' behaviour is relaxed and natural. The target settings are peoples' own homes and care homes. Eye trackers can be placed strategically to observe eye movement in the context of everyday tasks. For example they can be used to track hand-eye coordination in routine tasks such as tea-making for possible signs of change; these might signal cognitive decline long before routines become more obviously affected. Eye trackers can also be deployed interactively. People spend significant amounts of their daily lives as consumers of visual media, especially through TV, which affords interactive stimulation of eye movement. For example, content (e.g. TV programmes) can be designed to elicit behaviours of interest for diagnosis. People can also be provided with active gaze controls for interaction, for instance as alternative to remote control functions of a TV. Use of gaze for control stimulates specific eye movements which can be used for testing. Though beyond the scope project, this could also lead to therapeutic application of the technology. Moreover, as eye trackers are based on cameras and computer vision, this opens up avenues for integration with other vision-based approaches such as analysis of facial expressions, for multimodal cognitive health analysis.

  • Funder: UKRI Project Code: EP/M019918/1
    Funder Contribution: 4,991,610 GBP
    Partners: Amey Plc, DfT, NAVTECH RADAR LIMITED, Automotive Council UK, UKSA, Tracetronic, FHG, University of Pennsylvania, OC Robotics, McGill University...

    VISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.

  • Funder: UKRI Project Code: EP/M02797X/1
    Funder Contribution: 96,770 GBP
    Partners: Cornell University, University of Waterloo (Canada), LSE

    The proposed research contributes to fundamental topics in Combinatorial Optimisation, aiming to devise strongly polynomial algorithms for new classes of linear and nonlinear optimisation problems. The notion of polynomial-time complexity, introduced in the 1970s, is a standard way to capture computational efficiency of a wide variety of algorithms. Strongly polynomial-time algorithms give a natural strengthening of this notion: the number of arithmetic operations should not depend on numerical parameters such as costs or capacities in the problem description, but only on the number of such parameters. Strongly polynomial algorithms are known for many important optimisation problems. However, it remains an outstanding open problem to devise such an algorithm for a very fundamental optimisation problem: Linear Programming. The most important goal of the proposal is to develop a strongly polynomial algorithm for linear programs with at most two nonzero entries per column. The problem is equivalent to minimum-cost generalised flows, a classical model in the theory of network flows. Finding a strongly polynomial algorithm was a longstanding open question even for the special case of flow maximisation, resolved by the applicant in a recent paper. Further goals of the proposal include strongly polynomial algorithms for related nonlinear optimisation problems. Nonlinear convex network flow models have important applications for market equilibrium computation in mathematical economics. Very few nonlinear problems are known to admit strongly polynomial algorithms. The proposal aims for a systematic study of such problems, and will also contribute to the understanding of computational aspects of market equilibrium models.

  • Funder: UKRI Project Code: NE/M013693/1
    Funder Contribution: 272,801 GBP
    Partners: SFU, Met Office, ECMWF, LANL, University of Reading

    This project is about using moving meshes - r-adaptivity - to improve the predictive power of atmospheric flow simulations, which are used in the fields of numerical weather prediction and climate modelling. When the atmosphere is simulated on a computer, this is done by dividing the sphere into cells which are arranged in a mesh. There is a conflict between the need for accuracy, which requires smaller (and hence more) cells, and computational efficiency, which increases with the number of cells. A reasonable question to ask is: for a given amount of accuracy, what size of cells do I need? The answer can be provided mathematically, but it depends on what is actually happening in the atmosphere simulation. Much smaller cells are required in the regions of smaller scale features such as atmospheric fronts, cyclones, jets, convective cells etc. It then seems like a waste to choose the same cell size all over the globe even in regions where these features are absent. An attractive idea is to try to stretch, deform and move the mesh around so that smaller cells are used in the regions of small scale features, and larger cells are used elsewhere. This would mean that a better compromise can be made between accuracy and computational efficiency, thus improving predictive power for the same resource. This idea has been used successfully in many engineering applications, and the goal of this project is to transmit this technology to atmosphere simulation, where it can be used by meteorologists and climate scientists to take their science forward. There are, however, a number of challenging aspects. Efficient mesh movement algorithms have not previously been developed for the sphere geometry which is needed for global atmosphere simulations. There is the question of how to detect where the mesh should be moved to. It is also the case that it is very challenging to design stable and accurate numerical algorithms for simulating the atmosphere, and these must be adapted to remain stable and accurate under mesh movement. All of these questions and issues will be addressed in this project.

  • Funder: UKRI Project Code: NE/M017028/1
    Funder Contribution: 766,686 GBP
    Partners: University of Salford, WU, University of Guelph

    Soils provide many functions for humans, including the storage of carbon and nutrient cycling, which are crucial for the production of food and mitigation of climate change. However, there is much concern that soils, and the functions that they provide, are being threatened by a range of pressures, including intensive farming methods and increased frequency of extreme climatic events, such as drought. Not only do these disturbances pose an immediate threat to the functioning of soils, but they could also impair their ability to resist and recover from further stresses that come in the future. Our project will tackle this problem by addressing two general questions: first, what makes a soil able to withstand and recover from disturbance events, such as drought, and, second how can we use this knowledge to ensure soils can buffer disturbances in the future? These are questions that have puzzled soil scientists for many years, but so far, remain unresolved. An area that offers much promise, however, in tackling this issue is food web ecology. Food webs are the networks of interactions describing who eats whom amongst the myriad organisms within an ecosystem. And in soil, they are the engine that drives the very processes of nutrient cycling and energy flow on which the functioning of soil and the terrestrial ecosystems they support, depend. It has been proposed for many years, but so far not fully tested in soil, that simple food webs are less able to withstand and recover from disturbance events, such as drought than complex ones. We want to test this theory in soil, which harbours some of the most complex, but also sensitive, food webs on Earth. We test the idea, through experiments and models, that the ability of a soil to withstand, recover and adapt to disturbance events depends on the architecture and diversity of the soil food web, which governs the rate of transfer of nutrients and energy through the plant-soil system. We also propose that soil disturbances associated with intensive land use, such as trampling and fertiliser addition, erode the very food web structures that make the soil system stable, thereby reducing the ability of soil to resist and recover from future disturbances, such as extreme weather events. We will also resolve what makes a food web stable, and test the roles of different types of organisms in soil, such as mycorrhizal fungi, which we believe play a major role. And finally, we will develop new models to help us better predict how soils will respond to future threats and to guide management decisions on sustainable soil management in a rapidly changing world. These question are at the heart of the NERC Soil Security programme which seeks to resolve what controls the ability of soils and their functions to resist, recover and ultimately adapt, to perturbations, such as those caused by land use and extreme climatic events.