Over the past decades, computer simulations have played an increasingly important role in design of numerous complex systems. In particular, computer simulations have played a pivotal role in aerodynamic and structural design of aircraft. It is becoming apparent, however, that current generation software packages used for aerodynamics design are not fit for purpose. Newer software is required, that can make effective use of current and future computing platforms, to perform highly accurate so called 'scale-resolving' simulations of air flow over complex aircraft configurations. Such capability would lead to design of more efficient and capable aerospace technology. In particular, it would greatly improve design of next generation Unmanned Aerial Vehicles (UAVs), which in the coming decades are set to have a significant impact on our society, playing key roles in areas such as defense, border security, search and rescue, farming, fishing, cargo transport, wireless communications, and weather monitoring. The primary objectives of this research are to i.) develop software that can effectively leverage capabilities of current and future computing platforms (with many thousands or even millions of computing cores) to undertaken hitherto intractable simulations of airflow over complex UAV configurations ii.) test and demonstrate cutting edge functionality of this software, iii.) translate the technology to industry, such that it can be used to facilitate design of next generation UAVs. The research program will be lead by Dr. Peter Vincent (a Lecturer in the department of Aeronautics at Imperial College London). It will be undertaken in collaboration with various industrial partners including BAE Systems, NASA Glenn, Nvidia, and Zenotech, and with various academic partners including Stanford University, UC Berkeley, University of Swansea, and University of Utah. This assembled team of project partners, comprising a selection of the world's leading companies, and elite research institutions, will ensure the project successfully delivers its objectives.

This is an extension of the Fellowship: 'Developing Software for High-Order Simulation of Transient Compressible Flow Phenomena: Application to Design of Unmanned Aerial Vehicles' - EP/K027379/1. Over the past decades, computer simulations of fluid flow have emerged as an important tool for design of complex systems across a range of sectors. It is apparent, however, that for a range of flow problem current generation software is not fit for purpose. Newer software is required, that can make effective use of current and future computing platforms, to perform highly accurate so called 'scale-resolving' simulations of unsteady flow phenomena over complex geometric configurations. Such capability would lead to design of more efficient and capable technology across a range of sectors, including aerospace, defense, architecture, automotive, and green energy. Current activities under award EP/K027379/1 have led to development of PyFR (www.pyfr.org), a new software that can effectively leverage capabilities of massively-parallel computing platforms, with a view to undertaking hitherto intractable simulations of unsteady airflow over complex Unmanned Aerial Vehicle (UAV) configurations. The proposed Fellowship extension will address a range of outstanding issues currently blocking wider industrial adoption of PyFR, taking it further "Towards Industry", as well as addressing a range of issues that will block exploitation of PyFR on next-generation exascale supercomputers, taking it further "Towards Exascale". The proposed Fellowship extension will also look to expand the application space of PyFR beyond just UAVs to a range of sectors, and includes test cases involving flow over turbine blades, missiles, buildings, and submarines. The research program will be lead by Dr. Peter Vincent, a Reader in the department of Aeronautics at Imperial College. It will be undertaken in collaboration with various industrial partners including MTU Aeroengines, MBDA, Arup, BAE Systems Submarines, BAE Systems MAI, NASA Glenn, Nasa Langley, NVIDIA, Pointwise, Kitware, Zenotech, and Oak Ridge National Lab, and with various academic partners including Stanford University, and the Massachusetts Institute of Technology. This assembled team of project partners, comprising a selection of the world's leading companies and elite research institutions, will ensure the project successfully delivers its objectives.

Meeting emerging science and engineering modelling challenges requires scientists who can master complex theory and simulation techniques, can assimilate data, and can collaborate in multidisciplinary teams with expertise across a range of modelling scales. Securing the UK's position as a world-leading research hub into the future therefore requires a well-integrated pool of researchers with a skillset that is both broad and deep. HetSys is leading the way in addressing these needs by producing students with the tools necessary to meet the challenges of the future through our training programme. We are training the scientists who will develop the next generation of computational models, implemented in reusable software with robust error bars from uncertainty quantification (UQ), and who can learn from experimental and simulated data on an equal footing through advances in 'scientific machine-learning' (SciML). Linking heterogeneous materials models with UQ allows performance to be improved, enabling the technology needed to reach net zero through a step-change in design capability. The ongoing AI revolution has necessitated a redesign of our training programme to enable us to build on what we learnt during the first funding period and deliver our new vision. In particular, changes to our core training enable our students to (i) embed robust and sustainable research software engineering (RSE) in modelling; (ii) quantify modelling uncertainties through enhanced use of statistical methods; and (iii) exploit new trends in scientific machine learning. The research focus of HetSys on new paradigms in the behaviour of heterogeneous materials remains vital for the competitiveness of the UK's high-value manufacturing and automotive industries. Prominent examples of challenges we are addressing include the design of (i) energy materials for future vehicles with reduced carbon footprints; (ii) low dimensional and/or strongly correlated materials for quantum devices; (iii) high entropy alloys for fusion applications; (iv) biomolecules for combatting infectious diseases. Historically, the modelling pattern has focused on just one length- or time-scale; HetSys transforms this landscape by explicitly targeting the multiscale modelling of heterogeneous systems required by industry. The expertise we have accumulated opens up opportunities to capitalise on the transformative combination of mechanistic modelling with data-driven approaches (SciML). This requires a broader combination of disciplinary expertise, provided through our enhanced bespoke training programme. Only a cohort approach can train high-quality computational scientists who can develop and implement new modelling methods in close collaboration with other scientists. The cohesive, interdepartmental cohorts and training programme we are creating lower many of the current barriers to interdisciplinary work and demonstrate our vision for the future of scientific endeavour, where teams of researchers work together to combine their skills and expertise. Only a critical mass of students and a large and highly collaborative team of supervisors makes this targeted and fully inclusive training approach feasible. HetSys supports the delivery of EPSRC's Physical and Mathematical Sciences Powerhouse strategic priority, helping to provide the platform on which research and innovation across the sciences is built.

The strategic vision of this Prosperity Partnership for Advanced Simulation and Modelling of Virtual Systems (ASiMoV) is to enable the research and development of the next generation of engineering simulation and modelling techniques. Our aim is to achieve the world's first high fidelity simulation of a complete gas-turbine engine during operation, simultaneously including the effects of thermo-mechanics, electromagnetics, and CFD. This level of simulation will require breakthroughs at all levels, including physical models, numerical solvers, algorithms, software infrastructure, and Exascale HPC hardware. Our partnership uniquely combines fundamental engineering and computational science research with two high tech SMEs and Rolls-Royce plc to address a challenge that is well beyond the capabilities of today's numerical solvers. Simulation and modelling, enabled by high performance computing, have transformed the way products are designed and engineered. The technology developed for the Trent XWB, the world's most efficient aero engine, could only have been achieved through simulation and modelling. However, next generation products will place demands on simulation that cannot be met by incremental changes to current techniques. The ACARE Flightpath 2050 goals demand fundamental changes to engine architectures and the 2015 Aerospace Technology Institute Propulsion Strategy identified "virtual certification" as a key technology needed in the 2025-30 timeframe. The journey to virtual certification is an incremental one requiring a thorough evidential database to convince the certification authorities that the analysis can be trusted. It will move forward on a number of fronts. One of those is the whole engine tests to certify operational performance and thrust. Our driving ambition is to realise new simulation technology for the ultra-high resolution and extreme scale needed for meaningful virtual certification models. For Rolls-Royce, virtual certification will bring a major business transformation requiring unprecedented trust in simulation and fundamental changes to design processes and skills. Estimated cost savings for virtual certification are measured in the many £millions per engine programme; but, we also estimate that each simulation will require a billion core hours. At this scale, savings from computational cost and performance optimisation will be £millions per design study. Hence the need for ASiMoV to push forward the boundaries of numerical modelling and simulation on the next generation of Exascale supercomputers.

Launch and recovery of small vehicles from a large vessel is a common operation in maritime sectors, such as launching and recovering unmanned underwater vehicles from a patrol of research vessel or launching and recovering lifeboats from offshore platforms or ships. Such operations are often performed in harsh sea conditions. The recent User Inspired Academic Challenge Workshop on Maritime Launch and Recovery, held in July 2014 and coordinated by BAE systems, identified various challenges associated with safe launch and recovery of off-board, surface and sub-surface assets from vessels while underway in severe sea conditions. One of them is the lack of an accurate and efficient modelling tool for predicting the hydrodynamic loads on and the motion of two floating bodies, such as vessels of different size which may be coupled by a non-rigid link, in close proximity in harsh seas. Such a tool may be employed to minimise the risk of collisions and unacceptable motions, and to facilitate early testing of new concepts and systems. It may also be used to estimate hydrodynamic loads during the deployment of a smaller vessel (for example, a lifeboat) and during recovery of a smaller vessel from the deck of a larger vessel. The difficulties associated with development of such tools lie in the following aspects: (1) the water waves in harsh sea states have to be simulated; (2) the motion of the small vehicle and change in its wetted surface during launch or recovery can be very large, possibly moving from totally dry in air to becoming entirely submerged; (3) the viscous effects may play an important role and cannot be ignored, and will affect the coupling between ocean waves and motion of the vehicles. Existing methods and tools available to the industry cannot deal with all of these issues together and typically require very high computational resources. This project will develop an accurate and efficient numerical model that can be applied routinely for the analysis of the motion and loadings of two bodies in close proximity with or without physical connection in high sea-states, which of course can be employed to analyse the launch and recovery process of a small vehicle from a large vessel and to calculate the hydrodynamics during the process. This will be achieved building upon the recent developed numerical methods and computer codes by the project partners and also the success of the past and ongoing collaborative work between them. In addition, the project will involve several industrial partners to ensure the delivery of the project and to promote impact.