Floods are the most common and widely distributed natural risk to life and property worldwide, causing over £4.5B worth of damage to the UK since 2000. Managing flood risk therefore presents a substantial challenge to this and future governments. Arising from the requirements of the EU Floods Directive (2007/60/EC), flood hazard maps for the UK must be delivered by December 2013. Due to limitations in current methodologies these maps take a deterministic approach to mapping catchment scale flood hazard, and do not incorporate climate change projections. Climate projections are predicted to result in the increase of UK properties at risk from flooding and coastal erosion: understanding the uncertainty these bring to flood hazard is therefore of vital economic significance to the UK. Different methods to assess or determine flood hazards have evolved through research and practice. However, these do not allow for uncertainty estimates to be explicitly included within the process. While uncertainty analysis has been an area of research over a number of years, it has not yet achieved widespread implementation in flood modelling studies and decision making for a number of reasons. With developments in the field, such as improved computational power and newly available standardised climate datasets, incorporating uncertainty into assessments is becoming increasingly possible and indeed essential. It is clear that a gap currently exists in uncertainty estimation in flood hazard prediction, particularly in relation to climate change projections, and that this area of research is critical to current policy and operational drivers. This proposal has been developed to comprehensively address this gap. The project will develop a novel probabilistic modelling framework to assess the impact of uncertainty arising from climate change on flood hazard predictions, generate exemplar probabilistic flood hazard maps for selected case study catchments and attempt to quantify the change to flood hazard as a result of climate projections.

Safety is a paramount consideration for offshore operators. Offshore industries, including oil and gas exploration/production, marine renewable energy and shipping, must abide by industry regulations that take into account the effects of a hostile working environment on structures and ships. The principal aim of this project is to identify a rational and practical data interrogation procedure so that realistic waves and currents can be included, along with winds and sea ice conditions, in structural analysis. This project brings together physical oceanography and the mathematics of fluid structure interaction, to address the likely extreme loads on a selection of structures and ships, in a wide range of offshore environments. This integrated approach requires a synergistic and collaborative effort proposed here, in partnership with industrial partners concerned with marine advice and safety. The substantial and varied datasets to be used for this analysis are obtained from state-of-the-art ocean and wave models, running in both hindcast and forecast mode. We will use data from models with "high to very high" spatial resolution, sampled at high time frequency (ranging hourly to daily), in order to capture extreme forces on structures and ships. Our innovative analysis will refine assessments of structural integrity, a matter of specific interest to ship and offshore structure classification societies. In developing the throughput and use of ocean and wave forecast data, these assessments may also be of use in real-time offshore operations, and we will develop this capability. In summary, we will integrate high-quality hindcasts and forecasts of ocean currents, tides and waves, in a variety of environments, including the effects of sea ice in high latitudes. In this way, we will provide the best possible advice on forces and environmental conditions experienced by offshore structures and ships, for both classification and operational purposes.

The internal combustion engine will remain dominant across high power marine, distributed power generation and off-road vehicles for several decades to come, requiring intensified fundamental research around greener fuels and clean, high efficiency operating modes. The UK has an internationally leading reputation for excellence in fundamental engine research for lighter duty cars, vans and trucks, with clear opportunities now apparent to transfer fundamental knowledge and skills to large engines. At present, the UK academic community is totally lacking large single cylinder engine facilities, with researchers restricted to automotive scale experiments and simulations extrapolated up to larger scale (with significant errors in fundamental predictions). This is a major omission in accelerating Net Zero fuels, disruptive large engine technologies and policies from within the UK. The vision is therefore to establish a world-leading, megawatt scale decarbonised engine experimental facility, with two unique research engines strategically co-located as a new collaborative centre of excellence and nationally accessible asset leveraging existing infrastructure and expertise.

Reliable and comprehensive flood forecasting is crucial to ensure resilient cities and sustainable socio-economic development in a future faced with an unprecedented increase in atmospheric temperature and intensified precipitation. Floodwaters from the areas surrounding a city can heavily affect flood cycle behaviour across urban areas, introducing uncertainties into the forecast that are often non-negligible. However, currently the extent to which we can predict flood hazards is limited, and existing methods cannot for example deal with inter-regional dependencies (e.g. as was seen when floods affected nine different countries across Central and Eastern Europe). Presently in the UK approx. 25% of yearly flood insurance claims are from areas outside the zones forecast to be at flood risk, and annual flood damage costs are already high (approx. £1.5 billion). Also more than 20,000 houses per year continue to be built on floodplains. The need to transform flood forecasting for a range of applications and scales has already been recognised by various parties. The UK Climate Change Risk Assessment 2017 Evidence Report prioritises flooding as the greatest direct climate change related threat for UK cities now and in the future, and urges urgent action to be taken, including the development of new solutions over the next 5 years. The hydraulic software industry and consultancy firms have expressed a desire for more reliable and sophisticated flood forecasting approaches, which can also reduce the manual labour required. In addition, mathematics and engineering research communities are still searching for forecasting models that are joined-up, reliable and efficient, as well as versatile and adaptable. To address this need, 'Multi-Wavelets' technology will be employed in this fellowship with a view to transforming flood forecasting routines from a disparate set of activities into a unified automatic framework. The applicant's vision is to exploit the innate capability of Multi-Wavelets technology to reformulate flood forecasting methods by providing a smart modelling foundation for the delivery of timely and accurate flood maps, alongside statistically quantified uncertainties. This research presents a unique opportunity for the applicant, UK academia and UK industry, to establish a world leading capability in a nascent field while addressing Living With Environmental Change (LWEC) priorities for improved forecasting of environmental change. The fellowship research will stimulate the creation of new software infrastructure capable of significantly improving our flood forecasting ability across length scales and under multiple uncertainties, helping us to better design infrastructure against flood risk and to plan for the consequences.

Fluid dynamics underpins large areas of engineering, environmental and scientific research, and is becoming increasingly important in medical science. At Leeds, we possess research expertise across each of these domains and we have an established record of working across disciplinary boundaries. This proposal builds upon this record through the establishment of a multidisciplinary CDT in Fluid Dynamics. Research techniques that will be applied, and developed, will encompass: mathematical modelling & theory; numerical methods, CFD & high performance computing (HPC); and measurement & experimentation. Engineering application areas to be addressed include: reacting flows; carbon capture, transport & storage; flow of polymer melts; mixing problems; particulate flows; coating & deposition; lubrication; medical devices; pathogen control; heat transport; wind turbines; fluid-structure interaction; and nuclear safety. Environmental application areas will consist of: groundwater flow; river/estuary flows; tidal flows; oceanography; atmospheric pollution; weather forecasting; climate modelling; dynamics of the Earth's interior; and solar & planetary flow problems. Facilities available to undertake this research include: the University's HPC system which, combined with the N8 regional facility that is hosted at Leeds, provides ~10000 computational cores, an extensive suite of licensed software and dedicated support staff; flow measurement techniques (including Particle Imaging Velocimetry (PIV), 2-component Laser Doppler Anemometry (LDA), Phase Doppler Anemometry (PDA) and Ultrasonic Doppler Velocity Profiling (UDVP)); techniques for measuring fluid concentration (Ultrasonic High Concentration Meter (UHCM) and Optical Backscatter Probes (OBS)) and a range of optical metrology systems (e.g. pulsed and continuous wave lasers). The UK has a substantial requirement for doctoral scientists and engineers who have a deep understanding of all aspects of fluid dynamics from theory through to experimental methods and numerical simulation. In manufacturing and process engineering, for example, many processes depend critically on fluid flows (e.g. extrusion of polymer melts, deposition of coatings, spray drying, etc.) and it is essential to understand and control these processes in order to optimize production efficiency and reliability (see letter of support from P&G for example). In large-scale mechanical engineering there is a demand for expertise in reacting turbulent flows in order to optimize fuel efficiency and engine performance, and in wetting and surface flows for the design and manufacture of pumps and filters. There is also a need for a wide variety of skilled experts in environmental fluid flows to support the growing need to understand and predict local pollution and threats to safety (atmospheric, surface water, ocean and sub-surface flows), and to predict weather, climate and space weather for satellite technology. We will train a new generation of researchers who will have a broad range of skills to transfer into industry and environmental agencies, hence our approach will be multi-disciplinary throughout. All students will undertake both modelling and experimental training before embarking on their PhD project - which will be co-supervised by academics from different Schools. The MSc component of the programmee will be specifically tailored to develop expertise in the mathematical background of fluid dynamics, in CFD/HPC, and in experimental techniques. Team-based projects will be used to develop the teamwork and communication skills we believe are essential. Finally, engagement with industry will be a key feature of this CDT: all students will undertake an industrial placement, a large number of projects will be industrially sponsored, and our non-academic partners will contribute actively to our management, implementation and strategic development.