Computational science is a multidisciplinary research endeavour spanning applied mathematics, computer science and engineering together with input from application areas across science, technology and medicine. Advanced simulation methods have the potential to revolutionise not only scientific research but also to transform the industrial economy, offering companies a competitive advantage in their products, better productivity, and an environment for creative exploration and innovation. The huge range of topics that computational science encapsulates means that the field is vast and new methods are constantly being published. These methods relate not only to the core simulation techniques but also to problems which rely on simulation. These problems include quantifying uncertainty (i.e. asking for error bars), blending models with data to make better predictions, solving inverse problems (if the output is Y, what is the input X?), and optimising designs (e.g. finding a vehicle shape that is the most aerodynamic). Unfortunately, the process through which advanced new methods find their way into applications and industrial practice is very slow. One of the reasons for this is that applying mathematical algorithms to complex simulation models is very intrusive; mostly they cannot treat the simulation code as a "black box". They often require rewriting of the software, which is very time consuming and expensive. In our research we address this problem by using automating the generation of computer code for simulation. The key idea is that the simulation algorithm is described in some abstract way (which looks as much like the underlying mathematics as possible, after thinking carefully about what the key aspects are), and specialised software tools are used to automatically build the computer code. When some aspect of the implementation needs to change (for example a new type of computer is being used) then these tools can be used to rebuild the code from the abstract description. This flexibility dramatically accelerates the application of advanced algorithms to real-world problems. Consider the example of optimising the shape of a Formula 1 car to minimise its drag. The optimisation process is highly invasive: it must solve auxiliary problems to learn how to improve the design, and it be able to modify the shape used in the simulation at each iteration. Typically this invasiveness would require extensive modifications to the simulation software. But by storing a symbolic representation of the aerodynamic equations, all operations necessary for the optimisation can be generated in our system, without needing to rewrite or modify the aerodynamics code at all. The research goal of our platform is to investigate and promote this methodology, and to produce publicly available, sustainable open-source software that ensures its uptake. The platform will allow us to make advances in our software approach that enables us to continue to secure industrial and government funding in the broad range of application areas we work in, including aerospace and automotive sectors, renewable energy, medicine and surgery, the environment, and manufacturing.

PREMIERE will integrate challenges identified by the EPSRC Prosperity Outcomes and the Industrial Strategy Challenge Fund (ISCF) in healthcare (Healthy Nation), energy (Resilient Nation), manufacturing and digital technologies (Resilient Nation, Productive Nation) as areas to drive economic growth. The programme will bring together a multi-disciplinary team of researchers to create unprecedented impact in these sectors through the creation of a next-generation predictive framework for complex multiphase systems. Importantly, the framework methodology will span purely physics-driven, CFD-mediated solutions at one extreme, and data-centric solutions at the other where the complexity of the phenomena masks the underlying physics. The framework will advance the current state-of-the-art in uncertainty quantification, adjoint sensitivity, data-assimilation, ensemble methods, CFD, and design of experiments to 'blend' the two extremes in order to create ultra-fast multi-fidelity, predictive models, supported by cutting-edge experimental investigations. This transformative technology will be sufficiently generic so as to address a wide spectrum of challenges across the ISCF areas, and will empower the user with optimal compromises between off-line (modelling) and on-line (simulation) efforts so as to meet an a priori 'error bar' on the model outputs. The investigators' synergy, and their long-standing industrial collaborations, will ensure that PREMIERE will result in a paradigm-shift in multiphase flow research worldwide. We will demonstrate our capabilities using exemplar challenges, of central importance to their respective sectors in close collaboration with our industrial and healthcare partners. Our PREMIERE framework will provide novel and more efficient manufacturing processes, reliable design tools for the oil-and-gas industry, which remove conservatism in design, improve safety management, and reduce emissions and carbon footprint. This framework will also provide enabling technology for the design, operation, and optimisation of the next-generation nuclear reactors, and associated reprocessing, as well as patient-specific therapies for diseases such as acute compartment syndrome.

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.

The UK is at the forefront of the development, adoption and export of Offshore Renewable Energy (ORE) technologies: offshore wind (OW), wave and tidal energy. To sustain this advantage, the UK must spearhead research and innovation in ORE, which will accelerate its adoption and widen the applicability of these technologies. Many organisations across the industry-academia spectrum contribute to ORE research and development (R&D) co-ordination and the ORE Supergen hub strategy will take a leadership role, integrating with these activities to guide and deliver fundamental research to advance the ORE sector. The role of the Supergen ORE hub is to provide research leadership for the ORE community to enable transformation to future scale ORE. The hub will articulate the vision for the future scale ORE energy landscape, will identify the innovations required and the fundamental research needed to underpin the innovation. It will also generate the pathway for translation of research and innovation into industry practice, for policy adaptation and public awareness in order to support the increased deployment of ORE technologies, reducing energy costs while increasing energy security, reducing CO2 emissions and supporting UK jobs. The hub will work closely with the ORE Catapult (ORECAT) and become well-connected with industry, government, the wider research community in the UK and internationally. It will bring together these groups to assemble the expertise and experience to define and target the innovations, research and actions to achieve the ambitious energy transformation envisioned for the UK. The new Supergen ORE hub will continue to support and build on the existing internationally leading academic capacity within these three research areas (OW, wave and tidal technology), whilst also enabling shared learning on common research challenges. The ORE hub will build a multi-disciplinary, collaborative approach, which will bring benefits through the sharing of best practice and exploitation of synergy, support equality and diversity and the development of the next generation of research leaders. The hub strategy provides an overview of research and innovation priorities, which will be addressed through multiple routes but linked through the hub, with activities designed to stimulate alignment across the research community and industry sectors to maximise engagement with prioritised research challenges through and beyond the hub time-scale. These include: 1. Networking and engagement activities to bring the research community together with industry and other stakeholders to ensure research efforts within the community are aligned, complementary and remain inspired by or relevant to industry challenges. This will include support and development of the ECR community to ensure sustainability and promote EDI within the sector as a whole. Actions will also be taken to identify potential cross over research synergies and opportunities for transfer of research between sectors and disciplines, both within and external to ORE. Furthermore, a structured communication plan built around progress of the community towards the sector research challenges will promote exploitation and commercialisation. 2. A set of core research work packages addressing priority topics selected and structured to maximize progress towards the sector objectives and building on the cross cutting expertise of the co-director team. 3. Targeted use of flexible fund as seed-corn activity leading to projects aligned with, and in partnership with, the hub.