Many countries have set ambitious renewable energy targets with offshore sources anticipated to form an important part of this; for example, it is estimated that one fifth of the electrical supply in the UK could come from marine (wave and tidal stream) resources. However, the environmental impacts of tidal turbines on marine wildlife (particularly seals, whales, and dolphins) is largely unknown. One major concern is the potential for marine mammals to collide with the rotating turbine blades causing injury or death. It is critical to learn whether this concern is valid by collecting data on the underwater movements of marine mammals around operating tidal turbines. Collecting these data is extremely challenging and available methods for measuring movements of marine mammals underwater and interactions with tidal turbines are limited. However, a small number of cutting-edge technologies have the ability to detect and track marine mammals underwater; these are underwater video, and active- and passive-acoustic tracking. This project will design and build a standardised marine mammal detection and tracking system based on the integration of this suite of technologies for the tidal energy industry. The system will be designed to be standardised in terms of the data collected but will be flexible to ensure it can be integrated into a range of different tidal turbine designs and can be deployed in a variety of different tidal environments. Effectively, the system will be designed to be 'plug and play' so that it can be integrated easily with future tidal turbines, and can be deployed and retrieved with minimal impact to turbine operation. Further, to ensure that the data collected by the system is standardised and therefore comparable between future monitoring studies, a series of open source and freely available data archiving and analysis tools for the datasets will be provided. Overall, this project aims to deliver a unique monitoring tool that will provide the Tidal Energy Industry with a data collection system that may be required as part of their consent monitoring conditions, and will provide regulatory authorities with the evidence base upon which to make informed decisions about marine mammal collision risk during the consenting process for tidal energy developments. keywords: tidal stream energy, tidal turbines, marine mammals, collision risk, impact assessments, sonar, video, hydrophones, seals, dolphins, porpoises, behaviour, underwater tracking stakeholders: Regulators, Tidal Developers, Statutory Advisors, Scottish Government, Scottish Natural Heritage, Natural Resources Wales, Atlantis Resources Ltd

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.

Electricity can be generated through the conversion of the kinetic energy that resides in tidal currents in a similar way to a wind turbine. The ubiquitous nature of tidal energy, and the predictability and reliability of tidal currents, gives tidal-stream energy distinct advantages compared to other renewable energy technologies. Individual tidal energy devices have been installed and proven, with commercial arrays planned throughout the world. Yet, the true global resource and ocean conditions are broadly unknown, affecting optimal global device design. Present methods are unsuitable as the industry matures beyond the fast, shallow, well-mixed, and wave sheltered "demonstration" sites - influencing investor confidence. Transformative understanding of this sustainable natural resource for the coming century is therefore needed to bring a step change towards a sustainable, high-tech and globally exportable, UK renewable energy industry. CHALLENGE 1: How much tidal energy is there in the world and how is it distributed? OBJECTIVE 1: Resolve the true tidal-stream energy resource using unique datasets, consistent modelling framework, and state-of-the-art modelling techniques. Global tidal resource assessments are based on coarse, data constrained, models that are not validated for the few tidal energy sites resolved, as developed for other applications (e.g. global energy budgets); therefore, the global tidal energy resource is only broadly known. Fine-scale bathymetric constrictions (e.g. coral reef passes), biological communities (e.g. flow diverted around kelp beds) and ocean currents, can all accelerate currents between constrictions; meaning many sites initially dismissed as commercially unviable may actually be suitable. A consistent modelling framework (e.g. resolution and physics), and comparison of modelling techniques, will be developed to reduce bias and determine the potential global resource. CHALLENGE 2: How do conditions vary globally and will this change in the coming century? OBJECTIVE 2: Realistic oceanographic conditions at potential tidal-stream energy sites for the coming century will be determined For sustainable device design, realistic oceanographic conditions must be characterised for the lifetime of deployments, and cascaded through high-fidelity device-scale models (e.g. CFD); yet oceanographic conditions, and the impact of climate change, at tidal energy sites is largely unknown. Previously unviable tidal energy regions may become economically viable in the future (as near-resonant tidal systems and their associated currents are sensitive to sea-level rise), and, due to wave-tide interaction processes, oceanographic conditions at tidal energy sites may change. Dynamically coupled wave-tide ocean-scale models will be developed to inform the developing industry (e.g. optimal and resilient design), with new techniques that can simulate the interaction between the resource and devices. CHALLENGE 3: Are current methods of suitable as the industry develops? OBJECTIVE 3: Improved methods of device behaviour in resource and environmental assessment models The industry is evolving beyond fast, shallow, well-mixed and wave sheltered sites, to areas of the world with complex oceanographic conditions (e.g. ocean currents and swell wave dominated climates). New approaches are needed to understand the interactions between devices, resource and environment. Device-scale interaction studies assume well-mixed (i.e. homogenous) channelized flows, with tidal turbine loading from waves assessed assuming waves travel in-line with tidal currents (waves following or opposing current), which is not the case beyond an extremely limited number of tidal straits (e.g. Pentland Firth). Furthermore, device interaction with the flow must also be resolved within resource assessment, beyond simplified momentum sink terms. Device behaviour and interactions will improved at both ocean and device scales.