Public Funding for Edf Energy Nuclear Generation Limited

Next-generation Machinery Health State Detection (mSTATE) product - combining state-of-the-art digital signal processing hardware and novel mathematical algorithms for future net zero energy generation. This 18-month collaborative project will result in a step-change in the value of existing machinery protection systems through the development of innovative and adaptive machinery failure state detection processing and algorithmic technologies, to improve machine safety and reliability through earlier fault detection and avoidance of false alarms. The resulting diagnostics will permit enhanced decision-making, enabling meaningful and timely maintenance actions within industrial market sectors. The technology will be applicable for monitoring of all critical rotating machines where failure may impair safety, incur significant costs, adversely affect electricity supply or violate environmental standards. The consortium, led by Beran Instruments Ltd. (a UK-based SME), includes EDF Energy Nuclear Generation Ltd. and University of Bristol (UoB).

Structurally-critical components operating at high temperatures and in high pressure gaseous environments can display cracking behaviours that are not replicated using conventional mechanical testing methods which simulate the temperature but not the gas environment. Such behaviour appears to have been observed in both UK nuclear power stations and industrial gas turbines. This raises questions about using existing laboratory data for estimating the lifetime of in-service components. There is a need to confirm whether gas environment has a significant impact and develop a mechanical testing capability that better simulates these high temperature and pressure gaseous environments. This would provide a capability which is believed not to exist at any other facility world-wide, and is certainly not readily available. This project brings together a consortium of organisations to address this problem, from a user perspective and also in the provision of testing capability, with suitable instrumentation. Detailed microscopy will be undertaken to demonstrate the differences in behaviour seen between cracked ex-service components and cracks produced under current laboratory conditions. Alongside this, a facility will be designed and built to enable fatigue initiation, and fatigue and creep crack growth tests to be conducted in relevant environments for nuclear power stations and gas turbines. Initial trials in the pressurised gas facility will be undertaken to demonstrate its operation and provide an opportunity to determine the reproduction of ex-service behaviour.

The proposed work aims to improve the understanding of graphite fracture and irradiation creep behaviour by studying large specimens extracted from a reactor at end-of-service. This uniquely will enable valid fracture and creep data to be determined on material that had seen reactor conditions to high dose and weight loss conditions. Current data are determined on small specimens that are either unirradiated or irradiated in materials test reactors. In particular, the likely life-limiting failure mode is through a process known as keyway root cracking. Here a crack initiates at a sharp re-entrant corner; to study this failure mode in particular requires specimens of sufficient size to give a valid range of notch geometries. In addition, the relaxation of stress by irradiation creep is a key process to mitigate processes at sharp corners. No work on irradiation creep has been performed on corner geometries or at high tensile strain; both of these will be addressed in the current proposal. The results will allow the continued safe operation of reactors, enabling low carbon energy to be produced in the UK.

The advancement of reliable and effective health monitoring technologies for nuclear plant is dependent on collecting the right data at the right time. There is often insufficient data after an event to make an informed decision or develop robust health monitoring algorithms that can be relied upon to detect repeat occurrences. The goal of this collaborative project is to develop new Noise and Vibration Data Compression (NVCOMP) and smart data acquistion technologies, which will result in embeddable health monitoring solutions that can assist in the capture and replay of events in order to identify potential nuclear plant damage / deterioration. Critically, the new NVCOMP data acquisition and compression technologies will be deployable at the sensor / data acquisition node, greatly reducing the size of stored data, which opens new opportunities for monitoring items in a nuclear power station, which have previously not been cost-effective. The de-skilling of configuration of such equipment simplifies rapid deployment, and the reduction in reliance on high speed infrastructure communication allows simple installation in response to a potential noise or vibration issue.

A new methodology for assessing residual stresses using non-contact thermography is proposed. Residual stresses are stresses that are hidden in structures usually developed during manufacturing. The addition of the residual and service stresses can bring the material close to failure. The purpose of the research is to identify the residual stresses at welds in service components. Most portable residual stress measurement techniques are destructive. Other non-destructive residual stress measurement techniques are not portable. The thermography approach is non-destructive and portable, therefore offering a means to investigate components in service without costly plant down time. The proposed technique has been validated in a laboratory environment. There are still significant challenges to be addressed to bring the system to market, which will be dealt with in the planned research work by an expert consortium.

In this project, Cybula, a research intensive SME, will work with EDF's nuclear operating business in the UK and their R&D group in France to further develop and evaluate its' pattern recognition software methods for use as an alerting and diagnostic modelling system to monitor a range of assets. The proposed data modelling approach will use an abnormality detection system (AURAalert) which uses Cybula's optimised search engine to compare current performance of a continuously monitored system against large, reference data containing individual instances of normal performance. A proto-type system was developed as part of a previous TSB nuclear feasibility study. AURAalert will be linked to Cybula's SDE search software so that EDF can search for similar events in archived data across fleets of assets. The project aims to test the system on a range of assets.

Graphite is used as the moderator in EDF Energy nuclear Advanced Gas Cooled Reactors. It also plays a structural role and the integrity of graphite components has a high impact on plant lifetime economics. The aim of the project is to gain a good understanding and evaluation of fracture in irradiated graphite components by complementary numerical and experimental approaches. An advanced modelling tool allowing automatic simulation of crack propagation in graphite bricks will be developed. An innovative experimental method will be elaborated to validate these models. Uncertainties related to the whole core mechanical behaviour will also be assessed. By supporting the decisions regarding AGRs plant life extensions, it will participate to the security of low carbon electricity supply in the UK in the next years, at affordable and competitive costs.

Graphite has been used as the moderator within some designs of nuclear power station cores for over 50 years and is being considered for future High Temperature Reactor core designs due to its unique ability to withstand high temperatures and high levels of irradiation by fission neutrons. In some of these designs, the graphite also plays a structural role and the integrity of the graphite components has a considerable impact on plant lifetime economics. This project seeks to improve the understanding of irradiation-induced creep, which is a key process in the forecasts of structural integrity but is one where the underlying process is not presently fully understood. If successful, the project will contribute to security of low-carbon energy supply in the UK and the wider supply chain, whilst placing the UK at the forefront of research for the next generation nuclear plant.

Building on its successful feasibility study, where a potential 25% time-saving for machine fault diagnosis was demonstrated, the consortium aims to achieve Intelligent Condition Monitoring (ICM) for the Nuclear Power Industry. This project will enable Beran and EDF Energy to extend health monitoring to a wider range of machinery, structures and new civil nuclear plants. The technology adopted is derived from a physical understanding of non-linearities arising from degradation of components. Utilising expertise in prognostic algorithms from the University of Bristol, methods already used in the aerospace and medical sector will be adapted and developed for use within nuclear power plant systems. Industry benefits include increased accuracy, reliability and safety, greater availability of plant through predictive maintenance, improved operator intelligence, resulting in enhanced plant performance and reduced operating costs.

The fleet of Advanced Gas-cooled Reactor (AGR) nuclear power plants generate ~15% of the UK’s electricity power. The planned AGR closures between 2016 and 2024 are predicted to contribute to a shortage in UK electricity generation capacity. Therefore establishing safe lifetime extension of the AGRs is important for the UK. The degradation of high temperature stainless steel components through creep-fatigue processes is life limiting to the AGRs. New evidence suggests that there may be a synergistic interaction between the gas in which these components operate and the way they may fail, which is not fully understood. Lifetime extension may be impossible without accounting for this interaction. This project aims to understand this interaction between the environment and component degradation, enabling an assessment methodology to be developed which can establish the safety and extended lifetime of stainless steel components operating in the AGR reactors.