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.

High spectral efficiency is the holy grail of wireless networks due to the well-known scarcity of radio spectrum. While up to recently there seemed to be no way out of the apparent end of the road in spectral efficiency growth, the emerging approach of Network Coding has cast new light in the spectral efficiency prospects of wireless networks [1]. Initial results have demonstrated that the use of network coding increases the spectral efficiency up to 50% [2, 3]. Such a significant performance gain is crucial for many important bandwidth-hungry applications such as broadband cellular systems, wireless sensor networks, underwater communication scenarios, etc. Currently network coding has received a lot of attention from the wireless communication community; however, many existing works focused on the application of network coding to upper layers and the study of its impact on the physical layer (PHY) design only began recently. The aim of this proposal is to systematically study network coding at the physical layer, where we will not only characterize the fundamental limits of physical layer network coding, but also design practical digital signal processing (DSP) algorithms to realize the performance gain promised by those theoretic results. The novelty of the proposed project lies on the fact that this project will be the first UK effort to bridge information-theoretic studies and DSP algorithm design for PHY network coding. This will be done by first deriving the capacity region of network coding, which provides us the upper bound of the system performance. With such a better understanding, we will develop efficient transmission protocols and DSP algorithms to realize such optimal performance in practice. Interference alignment, a technology recently developed to cope with co-channel interference, will be applied to network coding transmissions for further performance improvement. Information-theoretic results, such as outage and symbol error probabilities, will be developed and testbed-based experimental evaluation will be carried out, so a more insightful understanding for our developed schemes can be obtained.

Coal-fired generation accounts for 82% of China's total power supply. Even in the UK the coal-fired generation still accounts for 35% . Because of this, the efficient and clean burn of coal is of great importance to the energy sector. Coal gasification and the proper treatment of the generated syngas before the combustion can reduce emissions significantly through alternative power generation system such as Integrated Gasification Combined Cycle (IGCC). The syngas usually contains varying amounts of hydrogen. The existence of hydrogen in the syngas may cause undesirable flame flashback phenomenon, in which the flame propagates into the burner. The fast flame propagation speed of hydrogen can travel further upstream and even attached to the wall of the combustor. The strong heat transfer to the wall may damage the combustor components. The consequence can be very costly. Because of this, many existing combustors are not suitable for the burning of syngas. To overcome this bottle neck, in-depth knowledge of the flame dynamics of hydrogen enriched fuel is essential, which is still not available. There is also a need to study the flame-wall interactions, which are important to the life span of a combustor but have not been fully understood.In order to understand the complex combustion process of hydrogen enriched fuels, combined efforts from experimentation and numerical simulations are essential. This joint project will investigate the flame dynamics including the flame flashback phenomenon, combustion instability, and flame-wall interactions. The flame dynamics will be investigated for different types of burners with fuel variability. Due to the limitation of optical access, the flame measurements need to be complimented by high-fidelity numerical simulations. The dynamic behaviour of the flame will be experimentally captured by the innovative combustion diagnostic tools developed at Manchester. To complement the experimental work, advanced numerical simulations based on direct numerical simulation and large eddy simulation will be performed at Brunel. The proposed research activities are based on the existing tools developed by the investigators and preliminary studies that have already been carried out by the applicants. The project will further develop innovative combustion diagnostic and advanced numerical tools. The knowledge to be gained from the project research and the physical models to be developed including improved near-wall flow, heat transfer and combustion models can lead to better combustion control and combustor design. The joint project will enhance the understanding on combustion of hydrogen enriched fuels with scientific advancement in flame measurements and near-wall flow modelling. More importantly, it will enhance the development of technologies for clean combustion of hydrogen enriched fuels, leading to a clean coal industry.Collaboration This project has excellent synergy between the UK and Chinese partners. Both partners are linked to BP. The Manchester group is directly supported by BP AE to work on combustion instability. Tsinghua University is one of the few identified links of BP in China. The involvement of Siemens Industrial Turbomachinery Ltd will ensure the maximum input from a gas turbine manufacturer's point of view.Management Both partners have long term informal research connections and the well established communications will ensure the smoothing running of the project. The PIs are well experienced in working with large research consortia. Dr Zhang has close collaboration with the industrial partners.Novelty Valuable physical insight into the potentially damaging combustion phenomena of hydrogen enriched fuels such as syngas burning will be provided; Original combustion diagnostics will be developed; Advanced numerical simulations will be performed; Near-wall flow, heat transfer and combustion models for unsteady reacting flows will be developed.

Understanding the mechanisms that lead to the breakup and evaporation of liquids is a key step towards the design of efficient and clean combustion systems. The complexity of the processes involved in the atomisation of Diesel fuels is such that many facets involved are still not understood. The morphological composition of a typical Diesel spray includes structures such as ligaments, amorphous and spherical droplets, but the quantity of fuel occupied by perfectly spherical droplets can represent a small proportion of the total injected volume. These relatively large non-spherical structures have never been thoroughly investigated and documented in high-pressure sprays, even though the increase in heat transfer surface area of deformed droplets is an influential factor for predicting the correct trend of evaporating Diesel sprays. The characterisation of fuel spray droplets is generally conducted using laser diagnostics that can measure droplet diameters with a high level of accuracy, but they are fundamentally unable to measure the size or shape of non-spherical droplets and ligaments. Hence the data obtained through these diagnostic techniques provide a partial and biased characterisation of the spray. The experimental bias towards spherical droplets is compounded by the complexity of modelling the heating and evaporation of deformed droplets. Consequently, theoretical models for liquid fuel atomisation and vaporisation are based on a number of simplifying hypotheses including the assumption of dispersed spherical droplets. Our proposal seeks to initiate a step change in the description of petroleum and bio fuel spray formation by developing diagnostics and numerical models specifically focused on non-spherical droplets and ligaments. Our approach will build upon recent advances with microscopic imaging to build novel diagnostics and algorithms that can measure the shape, size, velocity and gaseous surrounding of individual droplets and ligaments. This morphological classification, along with the velocity measurements, will be used to develop new phenomenological and numerical models for spray breakup, heating and evaporation. The models will then be implemented into computational fluid dynamics (CFD) codes to simulate spray mixing under modern engine conditions, and generate information where optical diagnostics cannot be applied. These goals will be achieved by combining the expertise of the academic and industrial partners with that of international experts from the University of Bergamo, CORIA, and Moscow State University. The project's concerted approach, aimed at removing the experimental and numerical biases towards spherical droplets, will establish a unique world leading research capability with potential impact for numerous practical spray applications. The project would underpin research in areas that rely upon the atomisation or evaporation of liquids, including the efficient delivery of liquid fuel, pharmaceutical drugs, cryogens, lubricants and selective catalytic reductants.

Moore's Law states that the number of active components on an microchip doubles every 18 months. Variants of this Law can be applied to many measures of computer performance, such as memory and hard disk capacity, and to reductions in the cost of computations. Remarkably, Moore's Law has applied for over 50 years during which time computer speeds have increased by a factor of more than 1 billion! This remarkable rise of computational power has affected all of our lives in profound ways, through the widespread usage of computers, the internet and portable electronic devices, such as smartphones and tablets. Unfortunately, Moore's Law is not a fundamental law of nature, and sustaining this extraordinary rate of progress requires continuous hard work and investment in new technologies most of which relate to advances in our understanding and ability to control the properties of materials. Computer software plays an important role in enhancing computational performance and in many cases it has been found that for every factor of 10 increase in computational performance achieved by faster hardware, improved software has further increased computational performance by a factor of 100. Furthermore, improved software is also essential for extending the range of physical properties and processes which can be studied computationally. Our EPSRC Centre for Doctoral Training in Computational Methods for Materials Science aims to provide training in numerical methods and modern software development techniques so that the students in the CDT are capable of developing innovative new software which can be used, for instance, to help design new materials and understand the complex processes that occur in materials. The UK, and in particular Cambridge, has been a pioneer in both software and hardware since the earliest programmable computers, and through this strategic investment we aim to ensure that this lead is sustained well into the future.