Although computational simulation is extensively employed in industry, its wider use is limited by the complexity of the geometric models involved. This limitation is due to the excessive number of human hours, ranging from days to months, required to transfer information from a computer aided design (CAD) model to a computer aided engineering (CAE) model suitable for simulation. CAD models frequently involve a level of detail much greater than that required to perform a computational simulation with a CAE system. The preparation of CAD models for simulation, including mesh generation, is still a challenging bottleneck that needs to be resolved to enable realisation of the full potential of simulation tools in industry. This challenge is also a crucial factor delaying the industrial uptake of, the often computationally superior, high-order methods. Current research is focused on the development of algorithms for de-featuring complex CAD models. A major drawback of this process is the requirement for human expertise and manual interaction with CAD systems and geometry cleaning tools. Although engineers are aided by the semi-automatic tools that are included in many existing commercial mesh generation packages, such as COMSOL, ANSYS, CATIA, SolidWorks, Patran, MSC, CADfix, ESI Visual Environment, de-featuring cannot be fully automatised. In addition, it is usually not possible to know, a priori, the effect of de-featuring on the results of a simulation because this process depends upon the physical problem and the level of approximation required. At the heart of the problem is the traditional hierarchical paradigm implemented in many commercial mesh generators. The ultimate goal of this project is to develop a new computational environment that includes a feature-independent mesh generation paradigm and plug--and--play libraries to enable direct integration of the meshes into existing commercial and research solvers. The proposed approach is disruptive, as it proposes the development of unconventional computational approaches, not only at the stage of generating suitable meshes for computational simulations but also requires the incorporation of new plug-and-play libraries into existing solvers. The libraries will be delivered as part of this project and it will follow the rationale used in commercial software where the user can select a different type of element depending on the demands of a particular simulation. The advantage of the proposed mesh generation technique is not restricted to removing the bottleneck that has been highlighted by many industries that routinely use computational engineering in their design cycles. In addition, the new meshes will completely remove the uncertainty introduced by de-featuring CAD models. Instead of relying on the opinion of experts, to decide which features might not be relevant in a simulation, the CAD model will not be altered, leading to higher fidelity simulations and more confidence in the results. The proposed research is timely, tackling a problem that has been highlighted in the last three years by independent agencies (e.g. NASA), international associations dedicated to computer modelling (e.g. NAFEMS) and the private sector (e.g. Pointwise Inc.). Since the mid 1990s the research has focused on the development of tools for faster de-featuring. The fact that this issue has not been resolved in over two decades, suggests that the radical new approach proposed here, pursuing an orthogonal research direction, in which no de-featuring is needed, can lead to a breakthrough.

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.

This project is one of the small number of proposals selected by an industrial consortium in collaboration with EPSRC to go forward as full proposals to the EPSRC Launch and Recovery Co-Creation Initiative. It involves a collaboration between Exeter and Southampton Universities, Scripps Institution of Oceanography (USA), BAE Systems, MOD and OCEANWAVES (Germany). It is supported by a mentoring/dissemination group comprising: BAE Systems, MOD, SEA Ltd, Zenotech and ESI Group. The practical driver is to enable a wide range of wave limited maritime operations to be carried out safely at higher sea states than is presently feasible. Particularly important examples are launch and recovery operations from mother ships of small boats, manned and unmanned air vehicles, and submersibles. The research concerns the two coupled areas of: (a) predicting the actual shape of sea waves, termed Deterministic Sea Wave Prediction and the application of this to predicting calmer periods in otherwise large seas (Quiescent Period Prediction), and (b) a comprehensive investigation of the properties of such quiescent periods and the creation of a quiescence simulator. The research involves an integrated combination of challenging fundamental new theory, simulation, large scale data analysis and experimental testing. An applications oversight, designed to facilitate post project the optimum push through to higher technology readiness levels, is provided by the industrial mentoring panel. MOD and BAE Systems are also research partners. The research will provide the predicted wave environment information required by closely allied projects within this EPSRC Launch and Recovery Co-Creation Initiative which are aimed at (a) modelling the motion of small craft in the near wave/flow field of a parent vessel and (b) control of launch and recovery operations. An alternative application of the new science is in the optimal control of wave energy converters where large increases in performance per unit cost are possible (see the impact case).

This is a multidisciplinary project that brings together researchers from different academic backgrounds in order to address reliability, lifetime and efficiency in offshore wind farms, and to meet the needs of the UK electricity generation industry. The overarching aim is the reduction of the (levelised) cost of generation of the large offshore wind farms that the UK will need in order to meet national and international objectives in the reduction of CO2 emissions. The multidisciplinary aspect reflects the different but, in context, linked disciplines and brings together the growing discipline of energy meteorology, of aerodynamics and aeroelasticity, of fatigue and structural mechanics, and of systems control. That is, the approach is a holistic one, linking the environmental conditions with their impact on each rotor and the mechanisms to improve farm performance as a whole. The meteorological contribution is essential because of the range of wind flow conditions that exist, subjecting the turbines and - importantly for large wind farms - the wakes of the turbines to a range of unsteady conditions that are known to reduce wind farm efficiency, and to cause increased structural damage (when compared to small-scale onshore wind farms). Both these contribute to increased capital and operating costs. The energy potential for the UK from offshore wind is huge, but offshore wind energy is still at a relatively early stage in technological terms. The aerodynamic response of each turbine to a variety of conditions imposed by the wind flow and the wakes of upstream turbines depends on the aeroelastic behaviour of the blades, the load in turn imposed upon the turbine generator, and the response by the turbine control system. In a large wind farm, the behaviour of one turbine - principally how much energy it is extracting from the wind flow - affects the behaviour, efficiency and lifetime of wind turbines in its wake; the turbines are not independent of each other. In fact, all aspects of the performance of wind turbines within large offshore wind farms, whether power output, loads or operations, are affected by their interaction through the wakes. Hence, to improve the cost effectiveness of offshore wind energy requires a better understanding of the flow-field through the wind farm. The project will address this issue and develop models to better represent the flow-field including the wakes and turbulence. Furthermore, capitalising on this, the implication for loads on the individual wind turbines will be investigated and the design of control strategies will be explored that achieve optimal operation of a large wind farm with each turbine controlled to keep operations and maintenance costs to acceptably low levels whilst (subject to this constraint) maximising farm output.