The nuclear industry has some of the most extreme environments in the world, with radiation levels and other hazards frequently restricting human access to facilities. Even when human entry is possible, the risks can be significant and very low levels of productivity. To date, robotic systems have had limited impact on the nuclear industry, but it is clear that they offer considerable opportunities for improved productivity and significantly reduced human risk. The nuclear industry has a vast array of highly complex and diverse challenges that span the entire industry: decommissioning and waste management, Plant Life Extension (PLEX), Nuclear New Build (NNB), small modular reactors (SMRs) and fusion. Whilst the challenges across the nuclear industry are varied, they share many similarities that relate to the extreme conditions that are present. Vitally these similarities also translate across into other environments, such as space, oil and gas and mining, all of which, for example, have challenges associated with radiation (high energy cosmic rays in space and the presence of naturally occurring radioactive materials (NORM) in mining and oil and gas). Major hazards associated with the nuclear industry include radiation; storage media (for example water, air, vacuum); lack of utilities (such as lighting, power or communications); restricted access; unstructured environments. These hazards mean that some challenges are currently intractable in the absence of solutions that will rely on future capabilities in Robotics and Artificial Intelligence (RAI). Reliable robotic systems are not just essential for future operations in the nuclear industry, but they also offer the potential to transform the industry globally. In decommissioning, robots will be required to characterise facilities (e.g. map dose rates, generate topographical maps and identify materials), inspect vessels and infrastructure, move, manipulate, cut, sort and segregate waste and assist operations staff. To support the life extension of existing nuclear power plants, robotic systems will be required to inspect and assess the integrity and condition of equipment and facilities and might even be used to implement urgent repairs in hard to reach areas of the plant. Similar systems will be required in NNB, fusion reactors and SMRs. Furthermore, it is essential that past mistakes in the design of nuclear facilities, which makes the deployment of robotic systems highly challenging, do not perpetuate into future builds. Even newly constructed facilities such as CERN, which now has many areas that are inaccessible to humans because of high radioactive dose rates, has been designed for human, rather than robotic intervention. Another major challenge that RAIN will grapple with is the use of digital technologies within the nuclear sector. Virtual and Augmented Reality, AI and machine learning have arrived but the nuclear sector is poorly positioned to understand and use these rapidly emerging technologies. RAIN will deliver the necessary step changes in fundamental robotics science and establish the pathways to impact that will enable the creation of a research and innovation ecosystem with the capability to lead the world in nuclear robotics. While our centre of gravity is around nuclear we have a keen focus on applications and exploitation in a much wider range of challenging environments.

This project will engage with two project partners (Environment Agency and EDF energy) with significant assets and infrastructure at risk from extreme storm surges. For both partners this project will deliver understanding of the impacts of plausible extreme coastal surge and wave events on the function, resilience, design and standard of protection of key infrastructure. It will provide them and other Flood and Coastal Erosion Risk Management Authorities with an improved level of understanding around current and future standards of protection. For key coastal regions - determined with our partners - we will synthesise a number of "black swan" storm surges - events that have not been observed but that are physically plausible. This has never previously been done for extra-tropical weather systems. It is important to sample storminess beyond the observed range of natural variability since our record of severe storm surges is probably too short (we have only had two extreme North Sea storm surges in 60 years - in 1953 and 2013). We will do this by analysing and grouping European storm systems from reanalysis data, and then perturbing the atmospheric systems using a well tried and tested forecasting tool (made available to us by the Met Office). The modified wind and pressure fields will drive coupled storm surge and wave models to create the plausible worst cases. Our work will provide a credible alternative for worst case storm surges that complements the H++ scenarios obtained from climate models alone. The results of the project will assist our project partners and other stakeholders in planning and mitigation, the siting and protection of coastal infrastructure, and long term investment decisions. Our deliverables will take the form of: 2-D data fields for storm surges and waves along the affected regions (determined with the partners); new calculations of extreme value statistics for those regions; site-by-site analyses of tide/surge/wave combinations that then feed into the downstream modelling of the two partners. For the Environment Agency, the new data would feed into National and / or local flood risk and forecasting models to help understand what impacts would be associated with such events to inform investment decisions and incident preparedness. The outputs would also be used both to quality control the current best-practice statistical methods for estimation of extreme sea levels and extend those. For EDF Energy, the new data will feed into their current statistical methodology for estimating return levels of extreme sea levels and provide information that could be used in strategic decisions on probable maximum extremes and lower bounds on the 10,000-year level for different natural hazards.

The vision for this Programme is to deliver the step changes in Robotics and Autonomous Systems (RAS) capability that are necessary to overcome crucial challenges facing the nuclear industry in the coming decades. The RAS challenges faced in the nuclear industry are extremely demanding and complex. Many nuclear installations, particularly the legacy facilities, present highly unstructured and uncertain environments. Additionally, these "high consequence" environments may contain radiological, chemical, thermal and other hazards. To minimise risks of contamination and radiological shine paths, many nuclear facilities have very small access ports (150 mm - 250 mm diameter), which prevent large robotic systems being deployed. Smaller robots have inherent limitations with power, sensing, communications and processing power, which remain unsolved. Thick concrete walls mean that communication bandwidths may be severely limited, necessitating increased levels of autonomy. Grasping and manipulation challenges, and the associated computer vision and perception challenges are profound; a huge variety of legacy waste materials must be sorted, segregated, and often also disrupted (cut or sheared). Some materials, such as plastic sheeting, contaminated suits/gloves/respirators, ropes, chains can be deformed and often present as chaotic self-occluding piles. Even known rigid objects (e.g. fuel rod casings) may present as partially visible or fragmented. Trivial tasks are complicated by the fact that the material properties of the waste, the dose rates and the layout of the facility within which the waste is stored may all be uncertain. It is therefore vital that any robotic solution be capable of robustly responding to uncertainties. The problems are compounded further by contamination risks, which typically mean that once deployed, human interaction with the robot will be limited at best, autonomy and fault tolerance are therefore important. The need for RAS in the nuclear industry is spread across the entire fuel cycle: reactor operations; new build reactors; decommissioning and waste storage and this Programme will address generic problems across all these areas. It is anticipated that the research will have a significant impact on many other areas of robotics: space, sub-sea, mining, bomb-disposal and health care, for example and cross sector initiatives will be pursued to ensure that there is a two-way transfer of knowledge and technology between these sectors, which have many challenges in common with the nuclear industry. The work will build on the robotics and nuclear engineering expertise available within the three academic organisations, who are each involved in cutting-edge, internationally leading research in relevant areas. This expertise will be complemented by the industrial and technology transfer experience and expertise of the National Nuclear Laboratory who have a proven track record of successfully delivering innovation in to the nuclear industry. The partners in the Programme will work jointly to develop new RAS related technologies (hardware and software), with delivery of nuclear focused demonstrators that will illustrate the successful outcomes of the Programme. Thus we will provide the nuclear supply chain and end-users with the confidence to apply RAS in the nuclear sector. To develop RAS technology that is suitable for the nuclear industry, it is essential that the partners work closely with the nuclear supply chain. To achieve this, the Programme will be based in west Cumbria, the centre of much of the UK's nuclear industry. Working with researchers at the home campuses of the academic institutions, the Programme will create a clear pipeline that propels early stage research from TRL 1 through to industrially relevant technology at TRL 3/4. Utilising the established mechanisms already available in west Cumbria, this technology can then be taken through to TRL 9 and commercial deployment.

The motivation for this proposal is that the global reliance on fossil fuels is set to increase with the rapid growth of Asian economies and major discoveries of shale gas in developed nations. The strategic vision of the IDC is to develop a world-leading Centre for Industrial Doctoral Training focussed on delivering research leaders and next-generation innovators with broad economic, societal and contextual awareness, having strong technical skills and capable of operating in multi-disciplinary teams covering a range of knowledge transfer, deployment and policy roles. They will be able to analyse the overall economic context of projects and be aware of their social and ethical implications. These skills will enable them to contribute to stimulating UK-based industry to develop next-generation technologies to reduce greenhouse gas emissions from fossil fuels and ultimately improve the UK's position globally through increased jobs and exports. The Centre will involve over 50 recognised academics in carbon capture & storage (CCS) and cleaner fossil energy to provide comprehensive supervisory capacity across the theme for 70 doctoral students. It will provide an innovative training programme co-created in collaboration with our industrial partners to meet their advanced skills needs. The industrial letters of support demonstrate a strong need for the proposed Centre in terms of research to be conducted and PhDs that will be produced, with 10 new companies willing to join the proposed Centre including EDF Energy, Siemens, BOC Linde and Caterpillar, together with software companies, such as ANSYS, involved with power plant and CCS simulation. We maintain strong support from our current partners that include Doosan Babcock, Alstom Power, Air Products, the Energy Technologies Institute (ETI), Tata Steel, SSE, RWE npower, Johnson Matthey, E.ON, CPL Industries, Clean Coal Ltd and Innospec, together with the Biomass & Fossil Fuels Research Alliance (BF2RA), a grouping of companies across the power sector. Further, we have engaged SMEs, including CMCL Innovation, 2Co Energy, PSE and C-Capture, that have recently received Department of Energy and Climate Change (DECC)/Technology Strategy Board (TSB)/ETI/EC support for CCS projects. The active involvement companies have in the research projects, make an IDC the most effective form of CDT to directly contribute to the UK maintaining a strong R&D base across the fossil energy power and allied sectors and to meet the aims of the DECC CCS Roadmap in enabling industry to define projects fitting their R&D priorities. The major technical challenges over the next 10-20 years identified by our industrial partners are: (i) implementing new, more flexible and efficient fossil fuel power plant to meet peak demand as recognised by electricity market reform incentives in the Energy Bill, with efficiency improvements involving materials challenges and maximising biomass use in coal-fired plant; (ii) deploying CCS at commercial scale for near-zero emission power plant and developing cost reduction technologies which involves improving first-generation solvent-based capture processes, developing next-generation capture processes, and understanding the impact of impurities on CO2 transport and storage; (iimaximising the potential of unconventional gas, including shale gas, 'tight' gas and syngas produced from underground coal gasification; and (iii) developing technologies for vastly reduced CO2 emissions in other industrial sectors: iron and steel making, cement, refineries, domestic fuels and small-scale diesel power generatort and These challenges match closely those defined in EPSRC's Priority Area of 'CCS and cleaner fossil energy'. Further, they cover biomass firing in conventional plant defined in the Bioenergy Priority Area, where specific issues concern erosion, corrosion, slagging, fouling and overall supply chain economics.

The inspection of safety-critical components in the nuclear power industry depends on procedures that can detect defects to a given threshold of severity; the acceptance process for this is known as inspection qualification. Inspection qualification in the UK is a highly developed formal activity, and is representative of the best practice in the world. However it can be very conservative if there is uncertainty in the expected measured response. A vital example is the scattering of ultrasound from the tips of rough cracks, such as thermal fatigue cracks or stress corrosion cracks. Ultrasound scattering from crack tips is widely exploited to measure crack sizes, but while the nature of the scattering is well understood for smooth cracks, scattering from the tips of rough cracks can differ significantly, and is not readily predictable. Consequently the qualification of ultrasound inspections for rough cracks has to be subject to severely conservative assumptions, and even so there remains a risk of misinterpreting findings. This project aims to bring understanding to the nature of the scattering, and to develop predictive modelling tools, such that these conservative assumptions can be safely eroded and the reliability of inspections improved. This will enable industry to reduce the costs of manufacturing and repairing, and down-time from outages, as well as improving confidence in the safe operation of safety-critical plant. The project will build on a strong UK heritage of the knowledge of ultrasound scattering, including recent work by the proposers on the stochastic nature of wave reflections from rough surfaces. The key aim is to deliver a new analytical approach that will predict the statistically expected scattering from the tips of cracks of given characteristics of roughness. The work will also include experimental investigation of real cracks and numerical modelling studies. The new ideas will be applied to the primary ultrasound inspection techniques of Time-of-Flight-Diffraction, Pulse-Echo, and array imaging. The work will be undertaken as a collaboration between researchers in Mechanical Engineering and in Mathematics at Imperial College. The proposal is being submitted within the UK Research Centre in NDE (RCNDE) to its targeted research programme. The proposal has been reviewed internally by the RCNDE, approved by the RCNDE board, and supported financially by five RCNDE industrial members.