Space Weather disruption of the near-Earth space- and ground-based systems is now accepted as having significant socio-economic impact , and is included in the UK National Risk Register for Civil Emergencies as a medium-high likelihood and medium impact civil emergency. Specifically, the UK National Risk Register identifies that "(c)urrent understanding is that a severe space weather event could have impacts upon a range of technologies and infrastructure, including power networks, satellite services, transport and digital control components" and that any industry relying on satellite services, that "(s)evere space weather can interrupt satellite services including Global Navigation Satellite Systems, communications, and Earth observation and imaging systems by damaging the space-based hardware, distorting the satellite signal or increasing the errors in ground-based receivers." The potential impacts of space weather on technological infrastructures, including power grids, satellite and ground communications and navigation systems, have generated world-wide interest at government levels in developing both forecasting and mitigation techniques and strategies. Indeed, the UK government is now seeking to establish a centre for space weather forecasting within the Met Office, who represent the state-of-the-art in forecasting terrestrial weather and can apply their 150 year heritage in forecasting to the field of space weather. The effects of extreme space weather can only be estimated since we do not know it's full extent. However, the potential total cost of an extreme Space Weather event has been estimated as around $2 Trillion in year 1 in the U.S. alone, with a 4-10 year recovery period . Quantifying the effects of Space Weather in all its forms is therefore of paramount importance. Less work has been undertaken in wider infrastructure sectors i.e. beyond those that coincide with technological infrastructures discussed above such as electricity distribution, communications and aviation. However, other infrastructure sectors exhibit important vulnerabilities to space weather, both being dependent on these technologies (e.g. GNSS, radio communication) through a disturbed ionosphere but also through sector-specific vulnerabilities. For example, Atkins has recently undertaken a study in relation to rail infrastructure, which has specific communication technologies and signal networks that are vulnerable to space weather. Therefore there is a need to consider sector vulnerability in more detail and this is particularly important for critical national infrastructure. Whilst much of this infrastructure has been examined, water is an area which merits increased attention. The water sector has extensive metal pipeline networks and is increasingly dependent on remote information collection and real-time control. The last two years of drought and extensive inland and coastal flooding has demonstrated the importance of effectively managing water. Moreover, the water sector uses UHF radio communication as an integral part of their operations and infrastructure. Since space weather is able to influence the propagation of signals through the modification and disturbing of the Earth's ionosphere, this represents an indirect way by which space weather can adversely influence the water sector operations and infrastructure. Atkins is the main stakeholder for this work, and Atkins is currently liaising with major water company clients on this issue. The wider stakeholder sphere will include the Environment Agency (as an asset manager and regulator), Ofwat, the Drinking Water Inspectorate, all water companies and water company supplies including consultants and the asset supply chain.

In this project, we will seamlessly combine two disciplines that have been historically received continuous government and industrial funding: physics-based modelling, which is generalisable and robust but may require tremendous computational cost, and machine learning, which is adaptive and fast to be evaluated but not easily generalisable and robust. The intersection of the two spawns scientific machine learning, which maximises the strengths and minimises the weaknesses of the two approaches. The data will be provided by high-fidelity simulations and experiments, from the UK state-of-the-art facilities and software. The efficiency of the machine learning training will be maximised for the algorithms to require minimal energy (thereby, producing minimal emissions by minimising electricity consumption). This project builds upon large UK and EU funded expertise in scientific machine learning and simulation, which will be generalised to fast, real-time decision making. The most significant bottleneck of most scientific machine learning is that they need time to be re-trained offline when new data becomes available. We will transform offline paradigms into real-time approaches for the models to re-adapt and provide accurate estimates on the fly. This project will culminate into the delivery of practical digital twins (defined as digital counterparts of real world physical systems or processes that can be used for simulation, prediction of behaviour to inputs, monitoring, maintenance, planning and optimisation) to solve currently intractable problems in wind energy, hydrogen, and road transportation. This project will transfer the technical achievements and real-time digital twin to policy-making.

Design in the UK construction sector is held in high regard internationally and produces 3.8 billion of export income per annum (Business and Enterprise Committee, 2008). In construction, design is undertaken as a collaborative activity by necessity, due to the division of labour and expertise between organisations (Bresnen et al., 2005). A consequence of the structure of the sector is that design activity involves the coordination of complex information exchanges in multi-disciplinary design teams. Coordination and communication challenges underlie difficulties in the integration of work activities of design teams. Communication is central to design collaboration and the coordination of design inputs, yet the communicative practices that coordinate design activities remain under-researched.Design team meetings are the locus for activities that are difficult to replicate in technologically-mediated environments (Visser, 2007). Indeed, it is the nuanced, micro-interactional communicative practices that are difficult to replicate but are significant for some shared understanding of a design situation that will be studied through this research. Face-to-face design interactions involve discursive moves where changes to the design are made verbally. In conversation designers with different knowledge backgrounds will negotiate design problems and verbally test alternate design solutions. It is these interactional, self-organising practices that coordinate real-time design activity that will be examined. The coordination of design activities will be investigated as this happens in the collaborative practices and communicative actions of cross-functional teams in design meeting settings. The face-to-face interactions of designers will be analysed from a language-use perspective, where the actions and practices that accomplish design coordination (or misunderstanding, ambiguity and uncertainty) will be investigated. From a conversation analytic-informed perspective patterns of interaction, spoken actions and particles in speech that mark shifts in understanding in the process of design will be analysed to locate interactional cues and communicative practices of design coordination. An intention is to link an understanding of structures and patterns in conversation with the way that engineering and construction management research communities understand design processes.

The United Kingdom has rapidly ageing civil infrastructure. The ability to re-use deep foundation systems and construct new ones more efficiently will pave the way for considerable savings in financial and carbon resources. Geotechnical engineers frequently rely on past records and experience to design foundations. Foundation performance in the stiff deposits in the UK is difficult to estimate and is often reliant on preliminary pile tests to failure being available. If these tests are not available then very conservative design assumptions are used. This research project will provide the UK geotechnical community with an openly accessible database of pile load tests in UK soil deposits. Much of the data for the database will be sourced from the literature and consultants' records. Using the database, different models that can be used to predict pile settlement response will be compared statistically and re-calibrated. Estimates of 'reserve capacity' in UK foundation systems will also be made to search for insights into the potential for foundation re-use in future construction projects. The results of the analysis can also be used to derive improved partial factors for pile design. These can be used in new and updated codes of practice and design guides. A user friendly web-portal will be developed so that designers and researchers can rapidly access the underlying datasets in the database. This will allow others to calibrate their own models for pile behaviour.

The Anaconda is a new concept for wave energy conversion. It is just a rubber tube in the sea, full of water, closed at both ends, anchored head to waves. It is squeezed or enlarged locally by pressure variations that run along its length due to the waves. Squeezing a water-filled rubber tube starts a bulge wave running. The bulge wave travels at a speed that is determined by the geometry and material properties of the tube. The Anaconda is designed so that its bulge wave speed is close to the speed of the water waves above. In these conditions the bulges grow as they travel along the tube, gathering wave energy. Inside the tube, the bulge waves are accompanied by a periodically reversing flow. One way of extracting power from the Anaconda is to use a pair of duck-bill valves to convert this into a rectified flow past a turbine between high and low pressure reservoirs. We have proved the concept of the Anaconda at a scale of about 1:85 in a laboratory wave flume. At this scale a large part of the converted wave energy is lost in heating up the thin wall rubber from which the tube is made, and in the turbulent flow through the valves. Nevertheless, the model absorbed all of the incident wave power over a front equal in width to as much as 5 times its diameter. A power take-off system accounted for about 20% of this, corresponding to more than 250kW for a 7m diameter Anaconda, 150m long, in waves 2m high. At larger scale, energy losses would be much less significant and the proportion of useful power conversion much higher. A device rated at 1MW would contain about 100 tonnes of rubber, making the Anaconda an exceptionally light wave energy converter for its power.When it comes to predictions, the Anaconda is like no other marine vessel or structure. It has some features in common with Pelamis, but it is much more compliant, has many more degrees of freedom, and does not necessarily follow the motion of the water surface. Our mathematical models of it are rather basic, and in many respects are not in very good agreement with laboratory measurements. The aim of this research is to develop a better understanding of the hydrodynamics of the device, and formulate a comprehensive and validated numerical with which to make more reliable estimates of full scale performance. Experiments will be carried out at scales of 1:28 and 1:14, with tubes of diameters 0.25m and 0.50m, at which rubber hysteresis losses will be proportionately much lower than at smaller scale. Three types of experiments are planned, to provide measurements of internal pressures, tube displacements, radiated waves, mooring forces, and absorber power:(1) measurements in still water with bulge waves generated mechanically at one end of the tube, and absorbed at the other,(2) measurements in regular and irregular waves,(3) measurements in extreme waves.The results will provide insights into the mechanics of the device and support the development of a numerical model that will for the first time include the effects of wave radiation and other factors so far neglected. Some features of the work will be relevant to other examples of wave interactions with compliant surfaces.