Development of an integrated decision support system to aid cognitive activities of operators

As digital and computer technologies have grown, human-machine interfaces (HMIs) have evolved. In safety-critical systems, especially in nuclear power plants (NPPs), HMIs are important for reducing operational costs, the number of necessary operators, and the probability of accident occurrence. Efforts have been made to improve main control room (MCR) interface design and to develop automated or decision support systems to ensure convenient operation and maintenance. In this paper, an integrated decision support system to aid operator cognitive processes is proposed for advanced MCRs of future NPPs. This work suggests the design concept of a decision support system which accounts for an operator's cognitive processes. The proposed system supports not only a particular task, but also the entire operation process based on a human cognitive, process model. In this paper, the operator's operation processes are analyzed according to a human cognitive process model and appropriate support systems that support each cognitive process activity are suggestedclos

Design of an integrated operator support system for advanced NPP MCRs: issues and perspectives

Recently, human error has been highlighted as one of the main causes of accidents in nuclear power plants (NPPs). In order to prevent human errors during the main control room (MCR) operations, which are highly complex and mentally taxing activities, improved interfaces and operator support systems have been developed for advanced MCRs. Although operator support systems have the capability to improve the safety and reliability of an NPP, inappropriate designs can have adverse effects on the system safety. Designs based on systematic development frames and validation/verification of the systems are pivotal strategies to circumvent the negative effects of operator support systems. In this paper, an integrated operator support system designed to aid the cognitive activities of operators as well as theoretical and experimental evaluation methods of operator support systems are reviewed. From this review, it was concluded that not only issues about systems (e.g., the accuracy of the system outputs),but also issues about human operators who use the systems (for instance, information quality, the operator???s trust and dependency on support systems) should be considered in the design of efficient operator support systems

A neural network based operation guidance system for procedure presentation and operation validation in nuclear power plants

An operation guidance system (OGS) was developed to regulate and supervise operators' actions during abnormal environments in nuclear power plants (NPPs). The system integrated a primitive computerized procedures system (CPS) and ail operation validation system (OVS) imbedded in a virtual simulated operational environment. As the key component of the OGS, OVS provided two important functions for the operators: validated check of operations, and qualitative and quantitative effects analysis of operations. Each of operators' action was evaluated by the system and possible results were simulated by using artificial neural networks (ANN). Finally, corresponding suggestion or warning was provided to operators. This should reduce human errors during operation in emergency scenarios. (C) 2007 Elsevier Ltd. All rights reservedclos

A dynamic neural network aggregation model for transient diagnosis in nuclear power plants

A dynamic neural network aggregation (DNNA) model was proposed for transient detection, classification and prediction in nuclear power plants. Artificial neural networks (ANNs) have been widely used for surveillance, diagnosis and operation of nuclear power plants and their components. Most studies use a single general purpose neural networks for fault diagnostics with limited reliability and accuracy. The proposed system in this study uses a two level classifier architecture with a DNNA model instead of the conventional single general purpose neural network for fault diagnosis. Transients' type, severity and location were individually obtained by assigning neural networks for different purposes. The model gave satisfactory performance in the system tests and proved to be a better method from comparison. Few previous diagnostic systems focus on the prediction of transients' severity. The proposed system can provide more accurate numerical values other than qualitative approximation for transient's severity. (C) 2007 Elsevier Ltd. All rights reservedclos

An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network

The design of instrumentation and control (I&C) systems for nuclear power plants (NPPs) is rapidly moving towards fully digital I&C systems and is trending towards the introduction of modern computer techniques into the design of advanced main control rooms (MCRs) of NPPs. In the design of advanced MCRs, human-machine interfaces have improved and various types of decision support systems have been developed. It is important to design highly reliable decision support systems in order to adapt them in actual NPPs. In addition, to evaluate decision support systems in order to validate their efficiency is as important as to design highly reliable decision support systems. In this paper, an operation advisory system based on the human cognitive process is evaluated in order to estimate its effect. The Bayesian belief network model is used in the evaluation of the target system, and a model is constructed based on human reliability analysis event trees. In the evaluation results, a target system based on the operator's cognitive process showed better performance compared to independent decision support systems. (c) 2007 Elsevier Ltd. All rights reservedclos

Evaluation of availability of nuclear power plant dynamic systems using extended dynamic reliability graph with general gates (DRGGG)

To assess the availability of a nuclear power plant’s dynamic systems, it is necessary to consider the impact of dynamic interactions, such as components, software, and operating processes. However, there is currently no simple, easy-to-use tool for assessing the availability of these dynamic systems. The existing method, such as Markov chains, derives an accurate solution but has difficulty in modeling the system. When using conventional fault trees, the reliability of a system with dynamic characteristics cannot be evaluated accurately because the fault trees consider reliability of a specific operating configuration of the system. The dynamic reliability graph with general gates (DRGGG) allows an intuitive modeling similar to the actual system configuration, which can reduce the human errors that can occur during modeling of the target system. However, because the current DRGGG is able to evaluate the dynamic system in terms of only reliability without repair, a new evaluation method that can calculate the availability of the dynamic system with repair is proposed through this study. The proposed method extends the DRGGG by adding the repair condition to the dynamic gates. As a result of comparing the proposed method with Markov chains regarding a simple verification model, it is confirmed that the quantified value converges to the solution. Keywords: Dynamic system availability, Reliability graph with general gates, Extended dynamic gate

Conceptual Design of a Remote Monitoring and Control System for Nuclear Power Plants

Nuclear power plants (NPPs) will be highly connected network enabled systems in the future. Using the network and web enabled tools, NPPs will be remotely monitored by operators at any time from any place connected to the network via a general web browser. However, there will be two major issues associated with this implementation. The first is the security issue. Only the authorized persons need to be allowed to access the plant since NPP is a safety-critical system. However, the web technology is open to the public. The second is the network disturbance issue. If operators can not access the plant due to network disturbances, the plant will come into the out-of-control situation. Therefore, in this work, we performed a conceptual design of a web-based remote monitoring and control system (RMCS) considering these issues

Investigation on relationship between information flow rate and mental workload of accident diagnosis tasks in NPPs

The objective of this study is to investigate experimentally the relationship between an operator's mental workload and the information flow rate of accident diagnosis tasks and further to propose the information flow rate as an analytic method for measuring the mental workload. There are two types of mental workload in the advanced main control room of nuclear power plants: the information processing workload, which is the processing that the human operator must actually perform in order to complete the diagnosis task, and emotional stress workload experienced by the operator. In this study, the focus is on the former. Three kinds of methods are compared to measure the operator's workload: information flow rate, subjective methods, and physiological measures. Information flows for eight accident diagnosis tasks are modeled qualitatively using a stage model and are quantified using Conant's model. The information flow rate is obtained by imposing time limit restrictions for the tasks. National Aeronautics and Space Administration-Task Load Index (NASA-TLX) and Modified Cooper-Harper (MCH) scale are selected as subjective methods. For the physiological measurements, an eye tracking system analyzes eye movements related to the operator's blinking and fixation on regions of interests. Through the experiments, the relationship between the information flow rate of accident diagnosis tasks and the selected measures is investigated. Results indicate that the information flow rate of diagnosis tasks is in high agreement with both subjective rating scores and eye movement parameters related to blinking and fixation on the regions of interest. It appears, then, that information flow rate can be an alternative as an analytic approach for measuring mental workload. By using data on the information flow rate, we can predict the mental workload required for a task without performing experiments in advanceclos

Measuring Situation Awareness of Operating Team in Different Main Control Room Environments of Nuclear Power Plants

Environments in nuclear power plants (NPPs) are changing as the design of instrumentation and control systems for NPPs is rapidly moving toward fully digital instrumentation and control, and modern computer techniques are gradually introduced into main control rooms (MCRs). Within the context of these environmental changes, the level of performance of operators in a digital MCR is a major concern. Situation awareness (SA), which is used within human factors research to explain to what extent operators of safety-critical systems know what is transpiring in the system and the environment, is considered a prerequisite factor to guarantee the safe operation of NPPs. However, the safe operation of NPPs can be guaranteed through a team effort. In this regard, the operating team's SA in a conventional and digital MCR should be measured in order to assess whether the new design features implemented in a digital MCR affect this parameter. This paper explains the team SA measurement method used in this study and the results of applying this measurement method to operating teams in different MCR environments. The paper also discusses several empirical lessons learned from the results