As a first stage in the analysis of storm surge risks to UK port infrastructure and supply chain operation, this project aims to improve the resilience of the port of Immingham and its critical biomass/coal transport link to power stations. The project includes the following three activities: WF1: To refine and operationalize an innovative artificial neural network (ANN) extreme sea-level prediction model (NE/M008150/1) for application at Immingham (with potential application for other UK ports, especially within estuaries). WF2: To translate predicted surge height and duration to risks to infrastructure (equipment, facilities) and operations (i.e. impacts on biomass/coal flows) through stakeholder engagement. WF3: Incorporate railway infrastructure and freight train movements to UCL's MARS model (used in NE/M008150/1) to predict the cascading impacts on the power sector.

This knowledge exchange project builds on the best science from three areas, firstly flood risk science and management, secondly catchment source control (runoff attenuation, SuDS and other green infrastructure) and thirdly ecosystem services assessment and payment for ecosystem services markets. It will be undertaken by the Centre for Floods, Communities and Resilience and the Centre for Transport & Society at UWE, Bristol in partnership with Network Rail, South Gloucestershire Council and Somerset Council. The primary objective is to assess the potential for catchment source control to reduce flooding impacts to the railway assets and therefore increase the resilience of the network. In order to explore the benefits of this approach an ecosystem services approach will be used to assess these services which will be contextualised in relation to a component of the study which assesses the direct and indirect costs of network disruption. The potential of a payment for ecosystem services market to fund the catchment intervention will be explored.

Structural application of fibre-reinforced polymer (FRP) composite materials is one of the key factors leading to technological innovations in aviation, chemical, offshore oil and gas, rail and marine sectors. Motivated by such successes, FRP shapes and systems are increasingly used in the construction sector, such as for bridges and small residential buildings. An obstacle to a wider use of FRP materials in structural engineering is the current lack of comprehensive design rules and design standards. While the preparation of design guidance for static actions is at an advanced stage in the USA and EU, the design against dynamic loading is underdeveloped, resulting in cautious and conservative structural design solutions. Knowledge on the dynamic properties (natural frequencies, modal damping ratios, modal masses and mode shapes of relevant vibration modes) of FRP structures and their performance under dynamic actions (such as pedestrian excitation, vehicle loading, wind and train buffeting) needs to be advanced if to achieve the full economic, architectural and engineering merits in having FRP components/structures in civil engineering works. This project will provide a step change to design practice by developing new procedures and recommendations for design against dynamic actions. This will be achieved by: 1) Developing an instrumented bridge structure at the University of Warwick campus that will provide unique insight into both static and dynamic performance over the course of the project, and beyond; 2) Providing novel experimental data on dynamic properties and in-service vibration response of ten full-scale FRP structures; and 3) Critical evaluation of the numerical modelling and current vibration serviceability design approaches. The data collected will be delivered in a systematic form and made available, via an open-access on-line database for rapid and easy dissemination, to academic and industrial beneficiaries, as well as to agencies supporting the preparation of institutional, national and international consensus design guidance. Outcomes from this project will provide the crucial missing information required for the reliable design of light-weight FRP structures, and pave the way towards this structural material becoming a 'material of choice' for future large-scale bridges and other dynamically loaded structures. This medium to longer-term impact is aligned with national plans for the UK having a sustainable and resilient built environment.

The vision for this Programme is to deliver the step changes in Robotics and Autonomous Systems (RAS) capability that are necessary to overcome crucial challenges facing the nuclear industry in the coming decades. The RAS challenges faced in the nuclear industry are extremely demanding and complex. Many nuclear installations, particularly the legacy facilities, present highly unstructured and uncertain environments. Additionally, these "high consequence" environments may contain radiological, chemical, thermal and other hazards. To minimise risks of contamination and radiological shine paths, many nuclear facilities have very small access ports (150 mm - 250 mm diameter), which prevent large robotic systems being deployed. Smaller robots have inherent limitations with power, sensing, communications and processing power, which remain unsolved. Thick concrete walls mean that communication bandwidths may be severely limited, necessitating increased levels of autonomy. Grasping and manipulation challenges, and the associated computer vision and perception challenges are profound; a huge variety of legacy waste materials must be sorted, segregated, and often also disrupted (cut or sheared). Some materials, such as plastic sheeting, contaminated suits/gloves/respirators, ropes, chains can be deformed and often present as chaotic self-occluding piles. Even known rigid objects (e.g. fuel rod casings) may present as partially visible or fragmented. Trivial tasks are complicated by the fact that the material properties of the waste, the dose rates and the layout of the facility within which the waste is stored may all be uncertain. It is therefore vital that any robotic solution be capable of robustly responding to uncertainties. The problems are compounded further by contamination risks, which typically mean that once deployed, human interaction with the robot will be limited at best, autonomy and fault tolerance are therefore important. The need for RAS in the nuclear industry is spread across the entire fuel cycle: reactor operations; new build reactors; decommissioning and waste storage and this Programme will address generic problems across all these areas. It is anticipated that the research will have a significant impact on many other areas of robotics: space, sub-sea, mining, bomb-disposal and health care, for example and cross sector initiatives will be pursued to ensure that there is a two-way transfer of knowledge and technology between these sectors, which have many challenges in common with the nuclear industry. The work will build on the robotics and nuclear engineering expertise available within the three academic organisations, who are each involved in cutting-edge, internationally leading research in relevant areas. This expertise will be complemented by the industrial and technology transfer experience and expertise of the National Nuclear Laboratory who have a proven track record of successfully delivering innovation in to the nuclear industry. The partners in the Programme will work jointly to develop new RAS related technologies (hardware and software), with delivery of nuclear focused demonstrators that will illustrate the successful outcomes of the Programme. Thus we will provide the nuclear supply chain and end-users with the confidence to apply RAS in the nuclear sector. To develop RAS technology that is suitable for the nuclear industry, it is essential that the partners work closely with the nuclear supply chain. To achieve this, the Programme will be based in west Cumbria, the centre of much of the UK's nuclear industry. Working with researchers at the home campuses of the academic institutions, the Programme will create a clear pipeline that propels early stage research from TRL 1 through to industrially relevant technology at TRL 3/4. Utilising the established mechanisms already available in west Cumbria, this technology can then be taken through to TRL 9 and commercial deployment.

Climate change is an important global challenge to be addressed in the coming years. Climate change can be considered as a long-term risk issue brought about by changes in the long-term average climate but also in the short-term extreme events. Transport infrastructure systems, which are designed to be operational over a long time period, are increasingly likely to experience the impact of climate change over their lifetime. Knowledge of future climatic conditions is essential in order to aid infrastructure owners manage the impact of climate change on both existing and planned infrastructure. There is a clear need to minimise the negative impacts arising from the changing climate and adapt to the changes expected in the future by introducing them into current design and assessment practice. In the long term, future load increases are likely to become significant as well. An improved and more reliable definition and estimation of the risk and costs of climate and increasing loading demand impacts on infrastructure should underpin this effort.The proposed project is an initiative to evaluate the potential significance of the anticipated changes to climate, weather as well as increasing load demand on bridges and to quantify the risks posed to the existing infrastructure in terms of bridge safety, expected failure costs and additional maintenance and adaptation expenses. The project will focus on failure modes associated with bridge scour, material deterioration, temperature stress cycling and movement and bearing deterioration. A novel methodology for estimating the risk of collapse of bridges under the effect of changing climate and increasing loading demands will be developed. The time evolution of risk will be captured through quantifying the probability of failure of the bridge over time for each of the above mentioned modes as well as quantification of the consequences of failure. A probabilistic framework, which is able to capture uncertainties, is essential towards quantifying the effects of climate change on the bridge infrastructure in terms of the increase in risk, i.e. reduction in safety, as well in terms of expected additional future costs arising from maintenance, replacements and adaptation plans. Case studies will at first focus on metallic bridges, though the framework could be adapted and applied to other bridge types such as concrete and masonry. The proposed methodology will have the potential to incorporate input in the form of local future climate change predictions and will offer the opportunity to establish a bridge risk ranking map for any given bridge population characterising the vulnerability of a bridge structure, depending on its location, to climate change and changing live load effects.The individual objectives of the proposed work are identified as follows:I. Development of a novel probabilistic methodology for the estimation of risk of collapse of bridges under changing environmental and load demand conditions.II. Evaluation of the effect of increased river flooding, arising from climate change, on the scour risk ranking and reliability of bridges.III. Evaluation of the effects of climate change and increasing live loading on material deterioration and bridge reliability.IV. Evaluation of the effects of temperature changes due to climate change on bridge thermal movements, stress cycling and bearing performance. V. Application of the developed methodology, in the form of case studies, for the estimation of the reliability and risk of collapse of a number of typical bridge types.The proposed work will benefit from collaboration with a mix of organisations i.e. Network Rail, TGP, HR Wallingford and TRL and will allow them to meet the future challenges associated with the long-term management of bridge infrastructure. This will allow diverse needs and opinions to be captured, and provides a powerful repository of knowledge/expertise that will be exploited by the project team.