Have you noticed that ever more wind turbines appear in the countryside? And more and more solar panels are installed on the houses on your route from work to home? All these are signs of the increasing uptake of micro-generation, whereby individuals or organisations install their own small-scale, renewables-based energy generators to produce and use energy. Presently, in the UK, they must sell the excess of their production back to the grid at a set price. Perhaps you yourself have installed some PV panels and have to sell the excess of your energy production back to the grid at a set price? And perhaps you would much rather contribute your excess generation free of charge to the nearby homeless shelter instead? Or sell it to someone else at a better price? Such free trade between micro-generators could become possible through a peer-to-peer (P2P) energy market. Similar 'sharing' platforms are already in place in other markets, e.g., via Airbnb in the hotel industry, or Uber in taxi hire (though both of these still impose substantial intermediation charges). But what would such a market democratisation entail for the energy sector? Is the infrastructure for P2P energy trading technically feasible? Who would provide it? What will be the role of the current major power producers (like British Gas and EDF Energy) in such a market? Could supply continuity be ensured under the fluctuating generation imposed by the nature of these energy sources? What factors will encourage households/groups to join this market? What regulatory changes are necessary for this market to function? These are the questions that the HoSEM project sets out to address. The key aim of this project is to research the feasibility of such democratised P2P energy market. To enable such a P2P energy market, this project will: 1. Develop a novel technical platform to support P2P household-level energy trading. Here all market participants must have read and write access to the records for the production, sale, and purchase of energy at low cost per transaction; each transaction must be accurately recorded, verifiable, and encryption-secured to guarantee accurate assignment of rights and responsibilities for trades and billing, allowing equal access to all interested participants. The distributed ledger technology uniquely meets all these domain requirements, providing an ideal technical tool for such a platform. The ledgers will also be available to 3rd party businesses that wish to provide new value added services for the energy market. 2. Establish a scientific basis for factors that would foster trust in households and organisations to participate in this market. Since prospective market participants will be acting as individuals or groups (e.g., likeminded "greens" or "profit seekers"), factors for both kinds of such participants will be researched. For instance, individuals may act upon trust in information and its sources, while a group member may follow what other members trust. 3. Research various possible configurations of such a P2P trading (e.g., where a few large groups are formed and influence the energy price, or each individual trades independently) along with algorithms for trade optimisation under each configuration (e.g., how to optimise own income and cut emissions as an individual, or minimising external energy dependency when trading as a community group). 4. Study the social, and economic implications of such a market: what will such a change imply for the current market participants, its impact on the energy supply chain, and how would this market affect everyday individual/community life? The DLT-enabled P2P energy trading has a strong disruptive potential, which could enable new business models and processes in energy sector. This project will help the businesses, regulators, and households gain an understanding of this potential, and get ready to transition into and engage with this changing market.

This project contributes substantially to enhancing the UK's resilience to climate variability and change through working with key stakeholders to ensure research is fit for purpose. This advance will be achieved by embedding a high qualified researcher in EDF to apply new modelling techniques that examine the vulnerability of their power stations to flooding and erosion from extreme rainfall. Embedded researchers play an important role in connecting businesses and environmental managers to current state-of-the-art in research approaches and techniques. By being embedded in EDF, the researcher will establish a good understanding of day-to-day working, drivers, decision-making contexts, and knowledge and information needs as well as the regulatory requirements for implementation. The researcher will establish an excellent understanding of both operational and planning requirements of flood risk assessment, and vulnerability thresholds for the associated hazard of erosion from surface water flows. The researcher will also identify the organizational mechanisms whereby this improved assessment is put into practice through planning, management and the implementation of the necessary mitigation measures. The researcher will, therefore, develop an intrinsic understanding of the problems due to flooding and erosion from extreme rainfall events, and then bring appropriate knowledge and innovative tools to bear on how these climate-related hazards are best predicted and communicated. Working with both EDF colleagues and University of Liverpool academics, the researcher will undertake assessments of flood and erosion risk that provide useful and usable information, "working collaboratively to generate new knowledge, synthesize and communicate findings to promote learning across relevant science and business domains." The risk modelling comprises models of flood and erosion hazard (probability of impact and extent) and damage (economic loss), the product of which are probability maps of buildings and structures at risk. A hydro-erosion model will be used to produce these maps, allowing the risk to nuclear power generation and decommissioning from extreme rainfall events to be assessed. This model predicts how much rainfall becomes runoff, how runoff is routed according to slope and relief, and how the resulting flows are then able to erode, transport and deposit sediment. Model outputs are fine scale maps of flooding, erosion and deposition, updated slope and relief, and runoff through time. To provide an assessment of erosion hazard from changing event intensity and frequency, UK Climate Change Projections will be used to generate rainfall depth duration frequency curves and river discharge time series for the next 60 years. To quantify the business impact of extreme rainfall and the vulnerability of assets, the project will forecast the economic loss caused by physical damage, judging the cost of mitigation measures against the associated economic benefits. Project outputs will be disseminated to energy sector stakeholders through workshops, conferences and webinars, showcasing how decision-relevant risk data can optimise the deployment of resources and reduce operational costs. This dissemination provides an opportunity to deliver a 'common language' for the communication of storm-related risk, and set an example of best practice in using risk-based analysis to inform operational decision-making. The outputs will include: - Scientific insights into the changing flood and erosion risk to nuclear power stations as a result of climate projections - How erosion hazards influence the vulnerability and resilience of these safety-critical assets to a changing climate - An integrated quantitative predictive modelling framework and decision-support tool that provides the much needed strong evidence base for sustainable, resilient decision making - Deepened engagement between scientists and stakeholders in the energy sector

The UK government considers nuclear energy to play an important role in the country's energy mix to establish a secure, environmentally friendly and diverse energy portfolio and meet the future energy demand. There are currently two reactors being built in the southwest of the UK and a number of others currently under development. In order to ensure nuclear energy safer and economically competitive, the Generation IV International Forum (GIF) has been formed, which has selected six advanced nuclear reactor designs to be the focus of the development by its member countries. Two of them use liquid metal as primary-circuit coolant, i.e., the sodium-cooled fast reactor (SFR) and the lead-cooled fast reactor (LFR). In the UK, BEIS has recently supported feasibility studies for eight advanced modular reactors (AMRs), three of which are Liquid Metal-cooled Fast Reactor (LMFRs). The knowledge gaps and modelling challenges in LMFR are broadly speaking related to two facts. Firstly, the heat transfer characteristic of liquid metal is markedly different from that of the conventional fluids (air and water) due to the extremely low Prandtl number, which makes the conventional turbulence models invalid under most conditions. Secondly, the special pool-type design gives rise to thermal hydraulic phenomena including natural circulation and stratification, which are unique for such reactors. Additionally, there is a lack of benchmarking data due to the difficulties associated with the measure of the flow and thermal fields in liquid metal. This proposal, developed in response to the EPSRC's collaborative research call on 'UK/US NEUP 2019', is aimed at addressing the above challenges. This joint research project will focus on developing instrumentation technology and associated modelling for liquid metal cooled fast reactor. The US partners will carry out experimental investigations, while the UK partners will develop computational tools for high fidelity modelling and conjugate heat transfer analysis. High fidelity large eddy simulation (LES) of stagnation and stratification flow of liquid metal will be carried out to complement physical experiment to provide valuable detailed data for turbulence and engineering model development, as well as to help in advancing the knowledge in such complex flow phenomena. This will be followed by refinement and validation of the 'conventional' CFD models using experimental and numerical data to develop new understanding of turbulent models and numerical methods for the simulation of liquid metal flows. Finally, a highly innovative conjugate heat transfer model of the sodium-to-supercritical-CO2 compact printed circuit heat exchanger (PCHE) will be developed based on the novel coarse-grid CFD recently developed and the immerse boundary method. If successful, they represent a major advancement in modelling of heat exchangers with highly complex geometry and physics and can be used to assist the design and optimisation of such systems effectively.

The High Temperature Gas-cooled Reactor (HTGR) design is one of the six advanced reactor types selected by the Generation IV International Forum (GIF) for development to be employed in the near future. It is the only design which allows the generation of hydrogen alongside the generation of electricity. HTGR is one of the key reactor designs that are currently supported in the US and a number of other countries. In the UK, the Department for Business, Energy and Industrial Strategy (BEIS) has recently supported feasibility studies for eight advanced modular reactors (AMRs), three of which are HTGRs, to facilitate the UK's engagement for the development of such advanced technologies. HTGRs are designed to avoid fission product release under any conditions, even beyond design basis accidents, by utilizing passive safety systems. However, the air ingress following the depressurization of an HTGR has been identified as an important risk to the core safety. Significant work has been carried out recently to investigate this phenomenon, but most have focused on the later stages of the process including the air-refill of the reactor building and air-ingress into the reactor pressure vessel. In contrast, the first stage, blowdown, has rarely been investigated in detail to date. This is a highly complex transient process, with the flow transitioning from a highly under-expanded supersonic jet, to a weakly under-expanded supersonic jet, and finally to complex natural circulation. This poses a huge challenge to modelling. This proposal and the associated US proposal are aimed at investigating the spatial distribution of air/oxygen and helium in each reactor building cavity during and after the blowdown phase. The objective of the proposed research by our partners in the US is to obtain experimental validation data on mixing of helium and air in reactor building cavities during and after blowdown in HTGRs such as a General Atomics 350 MWt MHTGR. The purpose of the proposed research in the UK is to carry out numerical simulations to complement the experimental endeavours carried out by the US partners. The UK work is organised into two work packages. Work Package 1 is aimed at developing and validating engineering Reynolds-Averaged Navier-Stokes (RANS)-based CFD models for the simulation of the full transient process during and after blowdown, from the initial pipe break to the time when equilibrium is reached and continuing to the following air-refill phase. This model will be one of the first to look at the complete transient process, and we aim to bring in innovative numerical methods to deal with the transition from compressible to incompressible flows. Work Package 2 is aimed at developing high fidelity CFD models based on well-resolved Large Eddy Simulation (LES) for the study of fundamental flow physics underpinning the air-ingress phenomena in a HTGR. This is to advance the understanding of such phenomena and provide detailed information and data, complementary to experiments, to support the development of engineering CFD models and correlations. In addition, effort will be made to compare computer codes used in the UK and the US to evaluate the consistency and discrepancies between them.

Due to climate change, extreme meteorological phenomena such as heavy precipitation, extreme temperature, strong winds and sea level rise, seem to be growing more severe and frequent, but the actual estimation of this evolution in extreme weather events remains subject to large uncertainty. For example, in December 2015 when storm Desmond hit the UK, several communities were badly affected by water level rises. Rainfall in this storm crept up to new record levels and provided us with critical lessons on how we can better prepare to withstand similar hazards. However, these lessons learned are in hindsight. When looking at the occurrence probability of such an extreme event that out-spans the range of previously recorded data, Extreme Value Theory (EVT) is the most appropriate branch of probability theory to be implemented as risk assessment and forecasting have a strong probabilistic foundation. In many operational settings, risk mitigation measures are required to balance costs with safety. For example, in insuring systems and infrastructure against extreme events, it might not be enough to sift through extreme record events that emerge from historical data, but it would also be nonsensical to channel most resources into a safety system so robust that it would spectacularly exceed the actual risk being protected against. EVT offers an appropriate statistical toolkit for forecasting extreme outcomes to a high degree of accuracy, thus providing critical evidence for assessing risk more accurately in preparing a proportionate response. There are varying layers of complexity in EVT enveloped in the recently introduced class of multivariate max-stable processes. These are promising models for the structural components that capture how extremes from multiple phenomena (hence the prefix multivariate) are likely to manifest themselves jointly across a certain region over time (hence the so-called space-time processes, also termed random fields). Real life applications abound in the multivariate infinite-dimensional max-stable processes frameworks. For example, the Fukushima nuclear disaster in 2011 was ignited by the combination of a huge earthquake followed by a tsunami. The main goal of this research proposal is to develop a general theory for multivariate infinite-dimensional extremes (extremes of two or more random fields) that will culminate in the development of statistical methodology for modelling interactions of two or more related extreme events. Recent studies have found that there exists significant long-term impact of climate change on storms that combine wind speed and precipitation, deeming it critically important that any fragility analysis be conducted in such a way as to ensure probabilistic safety levels of a nuclear power plant for extreme weather events. For example, the sting jet phenomena often unleashes very extreme local wind speeds, heavy rainfall and extreme temperatures on a nuclear plant. This is therefore the first application area of the developed statistical methodology. It is intended that this research programme will not only lead to improvement in safety standards and operational reliability of the nuclear energy fleet but also carries with it the potential of reducing costs in expensive overprotection measures that could run into millions of pounds. In addition to the nuclear energy sector other application areas will be explored. Energy supply and renewables power systems are so unwieldy that people are still trying to unravel some intriguing aspects of time dependent peak demands. The statistical methodology developed as part of this research programme will enable a better understanding to be gained of the characteristic features in smart-meter data, which will ultimately give people access to more affordable energy, providing more interaction and safety and thus more choice.