Nuclear technology is, by definition, based around the principle of subatomic physics and the interaction of radiation particles with materials. Whilst the microscopic behaviour of such systems is well understood, the degree of inhomogeneity involved means that the ability to predict the flux of particles through complex physical environments on the macroscopic (human) scale is a significant challenge. This lies at the heart of how we design, regulate and operate some of the most important technologies for the twenty-first century. This includes building new reactors (fission and fusion), decommissioning old ones, medical radiation therapy, as well as opening the way forward into space technologies through e.g. the development of space-bound mini-reactors for off-world bases and protection for high-tech equipment exposed to high-energy radiation such as satellites and spacesuits. Accurate prediction of how radiation interacts with surrounding matter is based on modelling through the so-called Boltzmann transport equation (BTE). Many of the existing methods used in this field date back decades and rely on principles of simulated (e.g. neutron) particle counting obtained by Monte Carlo and other numerical methods. Input from the mathematical sciences community since the 1980s has been limited. In the meantime, various mathematical theories have since emerged that present the opportunity for entirely new approaches. Together with powerful modern HPC and smarter algorithms, they have the capacity to handle significantly more complex scenarios e.g. time dependence, rare-event sampling and variance reduction as well as multi-physics modelling. This five-year interdisciplinary programme of research will combine modern mathematical methods from probability theory, advanced Monte Carlo methods and inverse problems to develop novel approaches to the theory and application of radiation transport. We will pursue an interactive exploration of foundational, translational and application-driven research; developing predictive models with quantifiable accuracy and software prototypes, ready for real-world implementation in the energy, healthcare and space nuclear industries. This programme grant will unite complementary research groups from mathematics, engineering and medical physics, leading to sustained critical mass in academic knowledge and expertise. Through a diverse team of researchers, we will lead advances in radiation modelling that are disruptive to the current paradigm, ensuring that the UK is at the forefront of the 21st century nuclear industry.

Policy makers and regulatory bodies are demanding the aerospace industry reduces CO2 emission by 50% and NOx emission by 80% by 2020. In order to meet these drastic demands and ensure affordable air travel in the future, it is essential to make lighter aircraft which will use minimum fuel. The aerospace research community recognises the need to make a dramatic performance improvement and is considering several new aircraft concepts that move away from the conventional two-wing-one-fuselage configuration. This brings new challenges to aircraft design. A wing is a highly complex structure to design as it needs to consider the complex interaction between aerodynamics and structural behaviour. The current design practice is therefore very much based on using the previous successful design data. The challenge of departing from the conventional aircraft is that there are limited successful historical design data that is applicable to new concept aircraft. Once we have a wing design, however, there are sophisticated computational methods that analyse how the wing behaves under external flight conditions. In fact, there has been a significant level of development in computational analysis methods taking advantage of growing computational power. A prime example of this is the recent development in the computational modelling of materials. Using this technology, new advanced materials can be created in half the time that traditional material development takes and the return on investment in computational materials research has been estimated at between 300 - 900%. This fellowship is at the heart of developing sophisticated computational methods to design aircraft configurations that have not been considered before. The majority of the current methods analyse how a given material or structure responds to the external environment such as in flight at speed Mach 0.8, 38000 ft. What is different about the methods in this research is that they are inverse of the analysis methods: They will determine the best combination of advanced material and structural configuration based on the external environment and hence design the optimum wing for the given flight conditions. My research approach is to represent the design problem as a set of mathematical functions and develop computational methods to find the optimum solution. The methods will therefore, find the optimum design for both materials and structural configuration at the same time. The outcome of this fellowship will provide engineers with a sophisticated tool to design complex aircraft structures. The tools will be developed and disseminated in a way that they can be used on a range of other complex engineering problems. The UK has 17% of the global aerospace market share with revenue of £24 billion and is responsible for 3.6% national employment. With the international civil aerospace market forecast to grow to $4 trillion by 2030, the UK market has the opportunity to grow to $352 billion by 2030. It is critical that the UK develops this unique capability to ensure we maintain the market share of these high value products and processes and its economy has the opportunity for growth. Furthermore, the weight savings which will be made from optimum use of materials lead to meeting the emission targets, thus ensuring sustainable environment for the future generations.

Anthropogenic emissions that affect climate are not just confined to greenhouse gases. Sulfur dioxide (SO2) and other pollutants form atmospheric aerosols that scatter and absorb sunlight, and influence the properties of clouds, modulating the Earth-atmosphere energy balance. Anthropogenic emissions of aerosols exert a significant, but poorly quantified, cooling of climate that acts to counterbalance the global warming from anthropogenic emissions of greenhouse gases. Uncertainties in aerosol-climate impacts are dominated by uncertainties in aerosol-cloud interactions (ACI) which operates through aerosols acting as cloud-condensation nuclei (CCN) which increases the cloud droplet number concentration (CDNC) while reducing the size of cloud droplets and subsequently impact rain formation which may change the overall physical properties of clouds. This consequently impacts the uncertainty in climate sensitivity (the climate response per unit climate forcing) because climate models with a strong/weak aerosol cooling effect and a high/low climate sensitivity respectively are both able to represent the historic record of global mean temperatures. On a global mean basis, the most significant anthropogenic aerosol by mass and number is sulphate aerosol resulting from the ~100Tg per year emissions of sulphur dioxide from burning of fossil fuels, but these plumes are emitted quasi-continuously owing to the nature of industrial processes, meaning that there is no simple 'control' state of the climate where sulphur dioxide is not present. On/off perturbation/control observations have, to date, been limited to observations of ship tracks but the spatial scales of such features are far less than the resolution of the weather forecast models or of the climate models that are used in future climate projections. This situation changed dramatically in 2014 with the occurrence of the huge fissure eruption at Holuhraun in 2014-2015 in Iceland, which was the largest effusive degassing event from Iceland since the eruption of Laki in 1783-17849. The eruption at Holuhraun emitted sulphur dioxide at a peak rate of up to 1/3 of global emissions, creating a massive plume of sulphur dioxide and sulphate aerosols across the entire North Atlantic. In effect, Iceland became a significant global/regional pollution source in an otherwise unpolluted environment where clouds should be most susceptible to aerosol emissions. Thus, the eruption at Holuhraun created an excellent analogy for studying the impacts of anthropogenic emissions of sulphur dioxide and the resulting sulphate aerosol on ACI. Our research will comprehensively evaluate impacts of the Holuhraun aerosol plume on clouds, precipitation, the energy balance, and key weather and climate variables. Observational analysis will be extended beyond that of our pilot study to include high quality surface sites. Two different climate models will be used; HadGEM3, which is the most up to date version of the Met Office Unified model and ECHAM6-HAM, developed by MPI Hamburg. These models are chosen because they produce radically different responses in terms of ACI; ECHAM6-HAM produces far stronger ACI impacts overall than HadGEM3. Additionally, the UK Met Office Unified Model framework means that the underlying physics is essentially identical in low-resolution climate models and high-resolution numerical weather predication models, a feature that is unique in weather/climate research. In the high resolution numerical weather prediction version, parameterisations of convection can be turned off and sub-gridscale processes can be explicitly represented. Thus the impacts of choices of parameterisation schemes and discrete values of variables within the schemes may be evaluated. The research promises new insights into ACI and climate sensitivity promising us great strides improving weather and climate models and simulations of the future.

In this fellowship I will deliver the next generation of magma-filled fracture models, by building on my track record of developing novel methodologies and applying a multidisciplinary approach to instigate a step change in eruption forecasting and volcanic hazard assessment. The communication revolution requires rapid and reliable decision making in the lead up to and during volcanic crises, but existing models of magma sub-surface flow are insufficient to allow this. We need to identify the conditions under which different magma flow regimes and host-rock deformation modes dominate, because these directly affect the eruption potential of underground magma. We need to recognise how magma ascent pathways and eruption potential are influenced by petrological characteristics, 3D geometry and heat transfer. We need to ground-truth our theoretical, physical and chemical understanding in exposed ancient volcanic plumbing systems. Finally, we need to synthesise insight from analogue, mathematical and field experiments and enable these combined models to be deployed to improve the accuracy and reliability of volcanic eruption forecasts. I will use my multidisciplinary expertise in volcanic plumbing systems and work closely with Project Partners from academia and government organisations to integrate analogue modelling, mathematical modelling, geophysical observations and geological analyses of volcanic systems to build the next generation of dyke and sill models. I will use novel imaging techniques combined with analogue modelling to couple the dynamics of magma intrusion and host-rock deformation with the associated surface distortions. I will develop cutting-edge mathematical models to explore the thermal, petrological and geometric behaviour of magma intrusions, considering magma flow dynamics and host-rock deformation, from propagation to solidification. I will perform state-of-the-art field experiments on two complementary and distinct suites of intrusions and use laboratory techniques to understand how the magma flow and host rock deformation occurred. I will compare field, analogue and mathematical model insights and collaborate with volcano and space observatories to test and develop them so they can be integrated into geohazard assessment systems. These models will form part of the international infrastructure of volcanic hazard assessment used to significantly minimise the human and economic cost of volcanic eruptions.

The problem: Building climate change resilience necessarily means building urban resilience. Africa's future is dominated by a rapidly increasing urban population with complicated demographic, economic, political, spatial and infrastructural transitions. This creates complex climate vulnerabilities of critical consequence in the co-dependent city-regions. Climate change substantially complicates the trajectories of African development, exacerbated by climate information that is poorly attuned to the needs of African decision makers. Critical gaps are how climate processes interact at the temporal and spatial scales that matter for decision making, limited institutional capacity to develop and then act on climate information, and inadequate means, methods, and structures to bridge the divides. Current modalities in climate services are largely supply driven and rarely begin with the multiplicity of climate sensitive development challenges. There is a dominant need to address this disconnect at the urban scale, yet climate research in Africa is poorly configured to respond, and the spatial scale and thematic foci are not well attuned to urban problems. Most climate-related policies and development strategies focus at the national scale and are sectorally based, resulting in a poor fit to the vital urban environments with their tightly interlocking place-based systems. Response: FRACTAL's aim is to advance scientific knowledge about regional climate responses to anthropogenic forcings, enhance the integration of this knowledge into decision making at the co-dependent city-region scale, and thus enable responsible development pathways. We focus on city-region scales of climate information and decision making. Informed by the literature, guided by co-exploration with decision makers, we concentrate on two key cross-cutting issues: Water and Energy, and secondarily their influence on food security. We work within and across disciplinary boundaries (transdisciplinarity) and develop all aspects of the research process in collaboration with user groups (co-exploration).The project functions through three interconnected work packages focused on three Tier 1 cities (Windhoek, Maputo and Lusaka), a secondary focus on three Tier 2 cities (Blantyre, Gaborone and Harare), and two self-funded partner cities (Cape Town and eThekwini). Work Package 1 (WP1) is an ongoing and sustained activity operating as a learning laboratory for pilot studies to link research from WP2 and 3 to a real world iterative dialogue and decision process. WP1 frames, informs, and steers the research questions of WP2 and 3, and so centres all research on needs for responsible development pathways of city-region systems. WP2 addresses the decision making space in cities; the political, economic, technical and social determinants of decision making, and seeks to understand the opportunities for better incorporation of climate information into local decision making contexts. WP3, the majority effort, focuses on advancing understanding of the physical climate processes that govern the regional system, both as observed and simulated. This knowledge grounds the development of robust and scale relevant climate information, and the related analysis and communication. This is steered explicitly by WP1's perspective of urban climate change risk, resilience, impacts, and decisions for adaptation and development. The project will frame a new paradigm for user-informed, knowledge-based decisions to develop pathways to resilience for the majority population. It will provide a step change in understanding the cross-scale climate processes that drive change and so enable enhanced uptake of climate information in near to medium-term decision making. The project legacy will include improved scientific capacity and collaboration, provide transferable knowledge to enhance decision making on the African continent, and in this make significant contribution to academic disciplines.