Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring

As the nuclear power plants within the UK age, there is an increased requirement for condition monitoring to ensure that the plants are still be able to operate safely. This paper describes the novel application of Intelligent Systems (IS) techniques to provide decision support to the condition monitoring of Nuclear Power Plant (NPP) reactor cores within the UK. The resulting system, BETA (British Energy Trace Analysis) is deployed within the UK’s nuclear operator and provides automated decision support for the analysis of refuelling data, a lead indicator of the health of AGR (Advanced Gas-cooled Reactor) nuclear power plant cores. The key contribution of this work is the improvement of existing manual, labour-intensive analysis through the application of IS techniques to provide decision support to NPP reactor core condition monitoring. This enables an existing source of condition monitoring data to be analysed in a rapid and repeatable manner, providing additional information relating to core health on a more regular basis than routine inspection data allows. The application of IS techniques addresses two issues with the existing manual interpretation of the data, namely the limited availability of expertise and the variability of assessment between different experts. Decision support is provided by four applications of intelligent systems techniques. Two instances of a rule-based expert system are deployed, the first to automatically identify key features within the refuelling data and the second to classify specific types of anomaly. Clustering techniques are applied to support the definition of benchmark behaviour, which is used to detect the presence of anomalies within the refuelling data. Finally data mining techniques are used to track the evolution of the normal benchmark behaviour over time. This results in a system that not only provides support for analysing new refuelling events but also provides the platform to allow future events to be analysed. The BETA system has been deployed within the nuclear operator in the UK and is used at both the engineering offices and on station to support the analysis of refuelling events from two AGR stations, with a view to expanding it to the rest of the fleet in the near future

WTEC panel report on European nuclear instrumentation and controls

Control and instrumentation systems might be called the 'brain' and 'senses' of a nuclear power plant. As such they become the key elements in the integrated operation of these plants. Recent developments in digital equipment have allowed a dramatic change in the design of these instrument and control (I&C) systems. New designs are evolving with cathode ray tube (CRT)-based control rooms, more automation, and better logical information for the human operators. As these new advanced systems are developed, various decisions must be made about the degree of automation and the human-to-machine interface. Different stages of the development of control automation and of advanced digital systems can be found in various countries. The purpose of this technology assessment is to make a comparative evaluation of the control and instrumentation systems that are being used for commercial nuclear power plants in Europe and the United States. This study is limited to pressurized water reactors (PWR's). Part of the evaluation includes comparisons with a previous similar study assessing Japanese technology

Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving

To take into account the experience feedback on solving complex problems in business is deemed as a way to improve the quality of products and processes. Only a few academic works, however, are concerned with the representation and the instrumentation of experience feedback systems. We propose, in this paper, a model of experiences and mechanisms to use these experiences. More specifically, we wish to encourage the reuse of already performed expert analysis to propose a priori analysis in the solving of a new problem. The proposal is based on a representation in the context of the experience of using a conceptual marker and an explicit representation of the analysis incorporating expert opinions and the fusion of these opinions. The experience feedback models and inference mechanisms are integrated in a commercial support tool for problem solving methodologies. The results obtained to this point have already led to the definition of the role of ‘‘Rex Manager’’ with principles of sustainable management for continuous improvement of industrial processes in companies

Monitoring and the Risk Governance of Repository Development and Staged Closure:Exploratory Engagement Activity in Three European Countries.

This report is the product of research activity within the EC Seventh Framework Programme “Monitoring Developments for Safe Repository Operation and Staged Closure” (MoDeRn) Project. This project aims to further develop understanding of the role of monitoring in staged implementation of geological disposal to a level of description that is closer to the actual implementation of monitoring. It focuses on monitoring conducted to confirm the basis of the long term safety case and on monitoring conducted to inform on options available to manage the stepwise disposal process from construction to closure (including e.g. the option of waste retrieval). This report investigates the potential of citizen stakeholder engagement in the identification of monitoring objectives and the development of monitoring strategies for geological disposal of high level waste (HLW) or spent nuclear fuel (SNF). It builds on an earlier MoDeRn report describing monitoring the safe disposal of radioactive waste as a socio-technical activity (Bergmans, Elam, Simmons and Sundqvist 2012)

Technology assessment between risk, uncertainty and ignorance

The use of most if not all technologies is accompanied by negative side effects, While we may profit from today’s technologies, it is most often future generations who bear most risks. Risk analysis therefore becomes a delicate issue, because future risks often cannot be assigned a meaningful occurance probability. This paper argues that technology assessement most often deal with uncertainty and ignorance rather than risk when we include future generations into our ethical, political or juridal thinking. This has serious implications as probabilistic decision approaches are not applicable anymore. I contend that a virtue ethical approach in which dianoetic virtues play a central role may supplement a welfare based ethics in order to overcome the difficulties in dealing with uncertainty and ignorance in technology assessement

Bayesian belief network model for the safety assessment of nuclear computer-based systems

The formalism of Bayesian Belief Networks (BBNs) is being increasingly applied to probabilistic modelling and decision problems in a widening variety of fields. This method provides the advantages of a formal probabilistic model, presented in an easily assimilated visual form, together with the ready availability of efficient computational methods and tools for exploring model consequences. Here we formulate one BBN model of a part of the safety assessment task for computer and software based nuclear systems important to safety. Our model is developed from the perspective of an independent safety assessor who is presented with the task of evaluating evidence from disparate sources: the requirement specification and verification documentation of the system licensee and of the system manufacturer; the previous reputation of the various participants in the design process; knowledge of commercial pressures;information about tools and resources used; and many other sources. Based on these multiple sources of evidence, the independent assessor is ultimately obliged to make a decision as to whether or not the system should be licensed for operation within a particular nuclear plant environment. Our BBN model is a contribution towards a formal model of this decision problem. We restrict attention to a part of this problem: the safety analysis of the Computer System Specification documentation. As with other BBN applications we see this modelling activity as having several potential benefits. It employs a rigorous formalism as a focus for examination, discussion, and criticism of arguments about safety. It obliges the modeller to be very explicit about assumptions concerning probabilistic dependencies, correlations, and causal relationships. It allows sensitivity analyses to be carried out. Ultimately we envisage this BBN, or some later development of it, forming part of a larger model, which might well take the form of a larger BBN model, covering all sources of evidence about pre-operational life-cycle stages. This could provide an integrated model of all aspects of the task of the independent assessor, leading up to the final judgement about system safety in a particular context. We expect to offer some results of this further work later in the DeVa project

Application of Artificial Intelligence in Detection and Mitigation of Human Factor Errors in Nuclear Power Plants: A Review

Human factors and ergonomics have played an essential role in increasing the safety and performance of operators in the nuclear energy industry. In this critical review, we examine how artificial intelligence (AI) technologies can be leveraged to mitigate human errors, thereby improving the safety and performance of operators in nuclear power plants (NPPs). First, we discuss the various causes of human errors in NPPs. Next, we examine the ways in which AI has been introduced to and incorporated into different types of operator support systems to mitigate these human errors. We specifically examine (1) operator support systems, including decision support systems, (2) sensor fault detection systems, (3) operation validation systems, (4) operator monitoring systems, (5) autonomous control systems, (6) predictive maintenance systems, (7) automated text analysis systems, and (8) safety assessment systems. Finally, we provide some of the shortcomings of the existing AI technologies and discuss the challenges still ahead for their further adoption and implementation to provide future research directions

Technological advances, human performance, and the operation of nuclear facilities

2017 Spring.Includes bibliographical references.Many unfortunate and unintended adverse industrial incidents occur across the United States each year, and the nuclear industry is no exception. Depending on their severity, these incidents can be problematic for people, the facilities, and surrounding environments. Human error is a contributing factor in many such incidents. This dissertation first explored the hypothesis that technological changes that affect how operators interact within the systems of the nuclear facilities exacerbate the cost of incidents caused by human error. I conducted a review of nuclear incidents in the United States from 1955 through 2010 that reached Level 3 (serious incident) or higher on the International Nuclear Events Scale (INES). The cost of each incident at facilities that had recently undergone technological changes affecting plant operators' jobs was compared to the cost of events at facilities that had not undergone changes. A t-test determined a statistically significant difference between the two groups, confirming the hypothesis. Next, I conducted a follow-on study to determine the impact of the incorporation of new technologies into nuclear facilities. The data indicated that spending more money on upgrades increased the facility's capacity as well as the number of incidents reported, but the incident severity was minor. Finally, I discuss the impact of human error on plant operations and the impact of evolving technology on the 21st-century operator, proposing a methodology to overcome these challenges by applying the systems engineering process

Supervisory Control System Architecture for Advanced Small Modular Reactors

This technical report was generated as a product of the Supervisory Control for Multi-Modular SMR Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (SMR) Research and Development Program of the U.S. Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular advanced SMR (AdvSMR) plants. This research activity advances the state-of-the art by incorporating decision making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides a brief history of hierarchical functional architectures and the current state-of-the-art, describes a reference AdvSMR to show the dependencies between systems, presents a hierarchical structure for supervisory control, indicates the importance of understanding trip setpoints, applies a new theoretic approach for comparing architectures, identifies cyber security controls that should be addressed early in system design, and describes ongoing work to develop system requirements and hardware/software configurations