Wireless sensor networks using radio technology are used to gather data in many applications for infrastructure monitoring, environment monitoring and security. However this technology cannot be directly applied under water since radio waves are absorbed by water. Technologies exist for underwater communication using acoustic waves (sound) to carry data but this is a complex and demanding task requiring sophisticated processing. Hence these devices are expensive (£5-20k), bulky and power hungry which has generally limited their use to relatively small numbers and short duration. This has prevented the large scale deployment of sensor networks underwater despite huge demand for monitoring of subsea assets and the marine environment. The aim of this project is to create a smart underwater sensing framework based on ultra-low-cost underwater communication and sensing devices ('smart dust'). Pilot studies at Newcastle University have demonstrated the feasibility of producing underwater acoustic communication devices known as "nanomodems" which use novel approaches to signal processing to vastly reduce hardware complexity, size and cost. These have manufacturing cost as low as £50, very low receiver power consumption, to enable long life from small batteries, and tiny dimensions. However they can achieve data transfer and positioning capabilities found in much more expensive devices, over distances up to 1km through water. The communication technology will be extended, to further increase data transfer speed and power efficiency, and low cost sensor modules will be developed, along with flexible interfaces for commercially available sensors, to create mass deployable wireless underwater sensor devices. Protocols will be developed to allow large numbers of units to share the same communication channel efficiently while intelligent sensor processing techniques will ensure that the sensor network reliably extracts the maximum information available from the limited resources available. Hence the system will allow users to fully exploit the power of mass deployment, the whole being far greater than the sum of the parts. This will transform underwater sensor networks to allow long term monitoring with high spatial resolution, frequent updates and near real-time data delivery in a way that has been previously been cost prohibitive and impractical. With highly flexible sensor payload, the technology created may be applied to a wide range of monitoring tasks. However, the project will focus on three main demonstrator scenarios in close collaboration with industry & end users: - subsea asset monitoring e.g. condition of subsea cables, risers, seabed installations - marine environment / biodiversity monitoring - chemical or biological parameters - sensor nets for underwater security - detecting sound emitted or magnetic disturbances from underwater threats The novel contributions of this project will be: - Disruptive, low-cost technology enabling mass deployment with battery life of several years. - Large scale underwater monitoring (>100 devices) with high spatial resolution. - Rapid deployment and online data delivery (as opposed to data logging and collecting later). - Intelligent, adaptive sensing to maximise resource utilisation and fully exploit large scale. To maximise the impact of the project, an open test-bed will be created near the Northumberland coast. Potential end-users from across the subsea sector will be invited to take part in a series of workshops to identify new opportunities in distributed underwater sensing, which will be prototyped and evaluated via trials using the test-bed. The ultimate measurable objective of the project will be to demonstrate a step change in the efficiency of subsea data gathering. This will be defined in terms of the data delivered (volume, quality, coverage) versus overall cost of operations (hardware cost, boat time, staff time, infrastructure cost).

This proposal is for a Doctoral Training Centre to provide a new generation of engineering leaders in Offshore & Marine Renewable Energy Structures. This is a unique opportunity for two internationally leading Universities to join together to provide an industrially-focussed centre of excellence in this pivotal subject area. The majority of informed and balanced views suggest approximately 180 TWh/year of offshore wind, ~300km of wave farms (19 TWh/year), 1,000 tidal stream turbines (6 TWh/year) and 3 small tidal range schemes (3 TWh/year) are desirable/achievable using David MacKay's UK DECC 2050 Pathways calculator. These together would represent 30% of predicted actual UK electricity demand. This would be a truly enormous renewable energy contribution to the UK electricity supply, given the predicted increase of electricity demand in the transport sector. The inclusion of onshore wind brings this figure closer to 38% of UK electricity by 2050. RenewablesUK predicts Britain has the opportunity to lead the world in developing the emerging marine energy industry with the sector having the potential to employ 10,000 people and generate revenues of nearly £4bn per year by 2020. The large scale development of offshore renewable energy (Wind, Wave and Tidal) represents one of the biggest opportunities for sustainable economic growth in the UK for a generation. The emerging offshore wind sector is however unlike the Oil & Gas industry in that structures are unmanned, fabricated in much larger volumes and the commercial reality is that the sector has to proactively take measures to further reduce CAPEX and OPEX. Support structures need to be structurally optimised and to avail of contemporary and emerging methodologies in structural integrity design and assessment. Current offshore design standards and practices are based on Offshore Oil & Gas experience which relates to unrepresentative target structural reliability, machine and structural loading characteristics and scaling issues particularly with respect to large diameter piled structural systems. To date Universities and the Industry have done a tremendous job to help device developers test and trial different concepts however the challenge now moves to the next stage to ensure these technologies can be manufactured in volume and deployed at the right cost including installation and maintenance over the full design life. This is a proposal to marry together Marine and Offshore Structures expertise with emerging large steel fabrication and welding/joining technologies to ensure graduates from the programme will have the prerequisite knowledge and experience of integrated structural systems to support the developing Offshore and Marine Renewable Energy sector. The Renewable Energy Marine Structures (REMS) Doctoral Centre CDT will embrace the full spectrum of Structural Analysis in the Marine Environment, Materials and Engineering Structural Integrity, Geotechnical Engineering, Foundation Design, Site Investigation, Soil-Structure Interaction, Inspection, Monitoring and NDT through to Environmental Impact and Quantitative Risk and Reliability Analysis so that the UK can lead the world-wide development of a new generation of marine structures and support systems for renewable energy. The Cranfield-Oxford partnership brings together an unrivalled team of internationally leading expertise in the design, manufacture, operation and maintenance of offshore structural systems and together with the industrial partnerships forged as part of this bid promises a truly world-leading centre in Marine Structures for the 21st Century.

Over the next decades, there will be a huge expansion of offshore renewable energy facilities to add electricity to the grid and reduce greenhouse gas emissions around the world. Globally, an estimated 17% annual growth from 22 GW to 154 GW in total installed offshore wind power capacity will be seen by 2030. The UK's Offshore Wind Sector Deal (2019) also sets out a goal for the offshore wind sector output being 30 GW by 2030. To meet the ambition of offshore wind energy exploration, it is of great importance to design cost-efficient foundations which, due to the complexity of subsea soil behaviour, remains a major challenge. Offshore foundation designs are well known to be conservative, which has led in part to the foundations accounting for 25-34% of the overall budget of offshore wind farms. The design of offshore foundations is particularly difficult for carbonate soils which cover roughly 35% of the ocean floor because (1) the complex mechanical behaviour of carbonate soils for which a reliable constitutive model is yet unavailable and (2) carbonate soils around foundations often experience large deformations, such as during foundation installation, leading to significant changes of their properties which are difficult to evaluate using traditional finite element techniques. The research proposed in this project aims to develop advanced computer models capable of predicting the mechanical response of carbonate sands at offshore foundations from the installation stage to the operational stage. This will be achieved by developing a novel numerical approach called the particle finite element method (PFEM), for analysing large-deformation soil-water-foundation interactions, and a self-learning simulation framework based on advanced deep-learning techniques for training data-driven constitutive models for carbonate sands. The developed PFEM with the trained data-driven constitutive model for modelling the responses of carbonate sands at offshore structure foundations will be validated under both standard laboratory conditions and high gravity centrifuge testing conditions. The success of the proposed research will not only improve our understanding of the behaviour of carbonate sands surrounding offshore foundations but also provide engineers with a robust open-source computer tool to analyse interactions between submerged carbonate sands and foundations with large deformations and help achieve cost-effective foundation solutions for offshore renewable energy developments.

Robots will revolutionise the world's economy and society over the next twenty years, working for us, beside us and interacting with us. The UK urgently needs graduates with the technical skills and industry awareness to create an innovation pipeline from academic research to global markets. Key application areas include manufacturing, assistive and medical robots, offshore energy, environmental monitoring, search and rescue, defence, and support for the aging population. The robotics and autonomous systems area has been highlighted by the UK Government in 2013 as one the 8 Great Technologies that underpin the UK's Industrial Strategy for jobs and growth. The essential challenge can be characterised as how to obtain successful INTERACTIONS. Robots must interact physically with environments, requiring compliant manipulation, active sensing, world modelling and planning. Robots must interact with each other, making collaborative decisions between multiple, decentralised, heterogeneous robotic systems to achieve complex tasks. Robots must interact with people in smart spaces, taking into account human perception mechanisms, shared control, affective computing and natural multi-modal interfaces.Robots must introspect for condition monitoring, prognostics and health management, and long term persistent autonomy including validation and verification. Finally, success in all these interactions depend on engineering enablers, including architectural system design, novel embodiment, micro and nano-sensors, and embedded multi-core computing. The Edinburgh alliance in Robotics and Autonomous Systems (EDU-RAS) provides an ideal environment for a Centre for Doctoral Training (CDT) to meet these needs. Heriot Watt University and the University of Edinburgh combine internationally leading science with an outstanding track record of exploitation, and world class infrastructure enhanced by a recent £7.2M EPSRC plus industry capital equipment award (ROBOTARIUM). A critical mass of experienced supervisors cover the underpinning disciplines crucial to autonomous interaction, including robot learning, field robotics, anthropomorphic & bio-inspired designs, human robot interaction, embedded control and sensing systems, multi-agent decision making and planning, and multimodal interaction. The CDT will enable student-centred collaboration across topic boundaries, seeking new research synergies as well as developing and fielding complete robotic or autonomous systems. A CDT will create cohort of students able to support each other in making novel connections between problems and methods; with sufficient shared understanding to communicate easily, but able to draw on each other's different, developing, areas of cutting-edge expertise. The CDT will draw on a well-established program in postgraduate training to create an innovative four year PhD, with taught courses on the underpinning theory and state of the art and research training closely linked to career relevant skills in creativity, ethics and innovation. The proposed centre will have a strong participative industrial presence; thirty two user partners have committed to £9M (£2.4M direct, £6.6M in kind) support; and to involvement including Membership of External Advisory Board to direct and govern the program, scoping particular projects around specific interests, co-funding of PhD studentships, access to equipment and software, co-supervision of students, student placements, contribution to MSc taught programs, support for student robot competition entries including prize money, and industry lead training on business skills. Our vision for the Centre is as a major international force that can make a generational leap in the training of innovation-ready postgraduates who are experienced in deployment of robotic and autonomous systems in the real world.

The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services. The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.