Nuclear Power Plant Main Control Room Research Articles

Develop a framework of human reliability analysis to evaluate the human error probability in DMCR of NPPs

ABSTRACT Human reliability analysis (HRA) has an important effect on the safety of nuclear power plants (NPPs). However, the operating environment in the digital main control room of NPPs has changed with the application of digital interface. Therefore, this paper developed a framework of HRA to evaluate human error probability (HEP) under the condition of digital interface control. Firstly, the hierarchical task analysis method was used to decompose the task to determine a series of sub-tasks. Secondly, the HEPs of diagnosis and execution were calculated based on the standardized plant analysis risk-human reliability analysis method. Finally, the final HEP of task was calculated by considering the recovery failure probability of human error. The experimental results showed that the HEP evaluation result of the developed method was consistent with the statistical method result. It indicated that the developed HRA method can be used to evaluate the HEP of task.

A Fuzzy CREAM Method for Human Reliability Analysis in Digital Main Control Room of Nuclear Power Plants

Human error is an important factor leading to nuclear power plant (NPP) accidents. The increasing of the amount of information improves the operators’ human error probability (HEP) in the digital main control room of NPPs. Human reliability analysis (HRA) is considered to be an effective method to reduce human error. The Cognitive Reliability and Error Analysis Method (CREAM) is one of the widely accepted HRA methods. However, there are shortcomings that weaken the applicability of this method. Therefore, this research proposes a fuzzy CREAM method based on a combination of fuzzy logic theory and the CREAM method. The study considers the weight of common performance conditions (CPCs) and constructs a logical relationship between CPCs and control modes. Finally, the effectiveness of the proposed method is determined using a widely accepted method to validate the evaluation results. The validated results showed that the evaluation result has a consistency between the fuzzy CREAM method and the traditional CREAM method. They indicated that the fuzzy CREAM method can obtain reliable HEP.

Modeling digital main control room operator’s resilience under extreme conditions: An Experiment design scheme

Human reliability is one of the most important factors that make effects in nuclear power plant(NPP) operation. In advanced digital NPP main control room with high levels of automation, the systematic operation which require a sufficient mental workload to address those undesired events has become a critical challenge for operators. The aim of this research is to identify the operator’s reliability by developing a resilience model. In this work, a seven-stage technique framework is proposed, which includes the skeleton of theoretical analysis, experimental design and hardware setting to how to establish the model for NPP operator in a downsize main control room cabin. The resilience model for operators’ reliability via assessing their basic skill tasks performance and evaluating their cognitive workload in the framework hence can be used for assessing the level of training of the new employed operators as well as human reliability in other critical process industries.

Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks.

In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It is therefore necessary to check whether operators are sufficiently attentive either as supervisors or peers during reactor operation. Recently, digital control technologies have been introduced to the operating environment of an NPP MCR. These upgrades are expected to enhance plant and operator performance. At the same time, because personal computers are used in the advanced MCR, the operators perform more cognitive works than physical work. However, operators may not consciously check fellow operators' attention in this environment indicating potentially higher importance of the role of operator attention. Therefore, remote measurement of an operator's attention in real time would be a useful tool, providing feedback to supervisors. The objective of this study is to investigate the development of quantitative indicators that can identify an operator's attention, to diagnose or detect a lack of operator attention thus preventing potential human errors in advanced MCRs. To establish a robust baseline of operator attention, this study used two of the widely used biosignals: electroencephalography (EEG) and eye movement. We designed an experiment to collect EEG and eye movements of the subjects who were monitoring and diagnosing nuclear operator safety-relevant tasks. There was a statistically significant difference between biosignals with and without appropriate attention. Furthermore, an average classification accuracy of about 90% was obtained by the k-nearest neighbors and support vector machine classifiers with a few EEG and eye movements features. Potential applications of EEG and eye movement measures in monitoring and diagnosis tasks in an NPP MCR are also discussed.

A Comparison of Displays and Associated Workload on Nuclear Power Plants Tasks

Nuclear Power Plant (NPP) operators complete a variety of tasks to ensure the NPP is running safely and efficiently. However, the levels and types of workload associated with the different task types are not yet fully understood. The present investigation examined workload levels and types for three common NPP Main Control Room (MCR) tasks in a controlled experimental environment using a variety of subjective and performance measures of workload. The results suggest that the three task types differ in the levels and types of workload. These findings can be used to better understand the types of NPP tasks that induce workload and the type of workload they induce. The full results of these experiments will be captured in future articles and technical reports.

Human error and the associated recovery probabilities for soft control being used in the advanced MCRs of NPPs

Since the Three Mile Island (TMI)-2 accident, human error has been recognized as one of the main causes of Nuclear Power Plant (NPP) accidents, and numerous studies related to Human Reliability Analysis (HRA) have been carried out. Most of these studies were focused on considering the conventional Main Control Room (MCR) environment. However, the operating environment of MCRs in NPPs has changed with the adoption of new human-system interfaces (HSI) largely based on up-to-date digital technologies. The MCRs that include these digital and computer technologies, such as large display panels, computerized procedures, and soft controls, are called advanced MCRs. Among the many features of advanced MCRs, soft controls are a particularly important because operating actions in advanced MCRs are performed by soft control. Due to the difference in interfaces between soft control and hardwired conventional controls, different HEP should be used in the HRA for advanced MCRs. Unfortunately, most current HRA databases deal with operations in conventional MCRs and are not explicitly designed to deal with digital Human System Interface (HSI). For this reason, empirical human error and the associated error recovery probabilities were collected from the mockup of an advanced MCR equipped with soft controls. To this end, small-scaled experiments are conducted with 48 graduated students in the department of nuclear engineering in Korea Advanced Institute of Science and Technology (KAIST) are participated, and accident scenarios are designed with respect to the typical Design Basis Accidents (DBAs) in NPPs, such as Steam Generator Tube Rupture (SGTR), Loss of Coolant Accident (LOCA) and Excess Steam Demand Event (ESDE). After that, the Bayesian update is conducted in order to extract the 5% and 95% quantiles of empirical human error and the associated recovery failure probabilities.

Workload Associated with Nuclear Power Plant Main Control Room Tasks

Nuclear Power Plant (NPP) operators complete a variety of tasks to ensure the NPP is running safely and efficiently. However, the levels and types of workload associated with the different task types are not yet fully understood. The present investigation examined workload levels and types for three common NPP Main Control Room (MCR) tasks in a controlled experimental environment using a variety of subjective, physiological, and performance measures of workload. The results suggest that the three task types differ in the levels and types of workload. These findings can be used to better understand the types of NPP tasks that induce workload and the type of workload they induce. The full results of these experiments will be captured in future articles and technical reports.

Estimating the response times of human operators working in the main control room of nuclear power plants based on the context of a seismic event – A case study

After the Fukushima accident, a couple of novel issues have raised in terms of the safety assessment of nuclear power plants (NPPs). This means that the performance of human operators should be properly evaluated under an extreme event. However, it is unrealistic to collect a sufficient amount of human performance data from a real event, such as a great earthquake. As one of the promising solutions, a conceptual framework is suggested in this paper, which is helpful for estimating the response time data of human operators working in the main control room of NPPs under a seismic event. To this end, the four kinds of representative contexts that could be anticipated from seismic events are identified. Then the response times of human operators who are faced with similar contexts are reviewed from existing literatures and databases. As a result, a couple of rules that allow us to extrapolate the response times of human operators under seismic events are extracted. Although underlying rationales being used for determining these rules are still arguable, it is expected that response times under seismic events could be properly understood along with accumulating those of human operators against non-seismic conditions.

Interview to Questionnaire Comparison of Workload Measurement on Nuclear Power Plant Tasks

Nuclear Power Plant (NPP) Main Control Room (MCR) operators oversee proper functioning of the facilities, including the controls to maintain the nuclear reactor. At least three operators, two reactor operators (ROs) and one senior reactor operator (SROs), are required for safe operations. The level of detail involved in performing the duties required of a nuclear power plant operator can result in a considerable amount of workload. Given the responsibility for safe operations, it is critical that operator workload is understood to provide accurate information about potential errors. Workload is the perceived amount of demand associated with executing a given task [1]. In light of resource theory, workload is the amount of resources required to perform a task and generally, it is accepted that as workload increases, performance decreases, thus errors are more likely and safety can be jeopardized [2]. Systematic experimentation for identifying levels of workload associated with NPP MCR tasks has been limited and the studies conducted are not without their limitations [3–5]. To understand the level of workload experienced by NPP operators, an experiment was conducted using “experienced” participants. An experienced participant in the present discussion is one that completed a rigorous training curriculum for three common task types encountered during main control room operations. The task types as adapted from [6] were checking, response implementation, and detection [7]. Three experienced participants served in the role of an RO in the present experiment, participating in 27 sessions each, and completing the three task types during each session. Each task type consisted of a block of four tasks. The NASA-Task Load Index was administered after each task type block and interviews were conducted at a later time. Results indicated that the detection task was the most demanding. The implications of measurement fit for workload assessment in a nuclear power plant domain are discussed.

Investigating Workload Measures in the Nuclear Domain

Research into human-system interaction, specifically focusing on workload, has intensified in the nuclear domain. Past research on workload in the Nuclear Power Plant (NPP) domain has attempted to use both subjective and physiological measures of workload, yet the sensitivity of the workload measures used in past experiments is unknown. This initial experiment will guide future research in the NPP domain by identifying whether the NASA-TLX, EEG, and ECG are sensitive to detecting workload changes in common NPP Main Control Room (MCR) tasks. Results suggest the three workload measures did not reveal expected differences between task types in the NPP MCR context.

Development and validation of a heuristic model for evaluation of the team performance of operators in nuclear power plants

The global concerns about safety in the digital technology of the main control room (MCR) are growing as domestic and foreign nuclear power plants are developed with computerized control facilities and human–system interfaces. In a narrow space, the digital technology contributes to a control room environment, which can facilitate the acquisition of all the information needed for operation. Thus, although an individual performance of the advanced MCR can be further improved; there is a limit in expecting an improvement in team performance. The team performance depends on organic coherence as a whole team rather than on the knowledge and skill of an individual operator. Moreover, a good team performance improves communication between and within teams in an efficient manner, and then it can be conducive to addressing unsafe conditions. Respecting this, it is important and necessary to develop methodological technology for the evaluation of operators’ teamwork or collaboration, thus enhancing operational performance in nuclear power plant at the MCR. The objectives of this research are twofold: to develop a systematic methodology for evaluation of the team performance of MCR operators in consideration of advanced MCR characteristics, and to validate that the methodology is adaptable to the advanced MCR of nuclear power plants. In order to achieve these two objectives, first, team performance factors were extracted through literature reviews and methodological study concerning team performance theories. Second, the team performance factors were identified and behavior markers were deducted based on the factors. Lastly, an estimation model for the evaluation of team performance was developed, and the model thereon was validated. The estimation model consists of an evaluation of task characteristics, identification of team performance factors, evaluation of team performance, calculation of team performance, and analysis of team performance. The detailed contents and validations of the model are also presented in this paper.

Investigation of automation deployment in the main control room of nuclear power plants by using adaptive automation

AbstractRecently, with the progress of computer technology, the digitalization of human–system interface (HSI) in the main control room (MCR) of advanced nuclear power plants (NPPs) has become an important issue. A higher level of automation means that the computers execute the greater part of the task. The frequency, however, of automation‐induced system failures, including human errors, prompts us to more closely investigate the influences of automation. The objective of this study is to measure the effects of adaptive automation on the primary task performance, operator situation awareness (SA), and workload in an advanced MCR of an advanced NPP to reduce the number of failures and improve human performance. This study selects automatic mode and semi‐automatic mode to compose five different types of automation allocations. The experiment scenario is a reactor shutdown task. A personal computer transient analyzer (PCTran) is used to simulate the HSI of an MCR. Twelve participants are required to perform the experiment scenario on the automation allocation types. The dependent variables were the primary task performance; the subjective workload was measured using an NASA‐Task Load Index (NASA‐TLX) questionnaire; and three levels of SA were estimated by SA queries. Experimental results revealed that the automation allocations made up of higher ratio automatic modes led to superior primary task performance, lower operator workload, and lower frequency of human errors. In the high ratio automatic mode allocation, the operators have the lowest SA queries score. This study provides additional information for future digital HSI design in the MCRs of advanced NPPs. © 2011 Wiley Periodicals, Inc.

The research on extracting the information of human errors in the main control room of nuclear power plants by using Performance Evaluation Matrix

Digitalized nuclear instruments and control systems have been the main stream design for the main control room (MCR) of advanced nuclear power plants (NPPs) nowadays. Digitalization of human–system interface (HSI) could improve human performance and, on the other hand, could reduce operators’ situation awareness as well. It might cause that humans make wrong decision during an emergency unintentionally. Besides, digital HSI relies on computers to integrate system information automatically instead of human operation. It has changed the operator’s role from mainly relating operational activity to mainly relating monitoring. However, if the operators omit or misjudge the information on the video display units and wide display panel, the error of omission and error of commission may occur. This study applies Content Category Analysis (CCA) and Performance Evaluation Matrix (PEM) methods to explore the potential problems in the MCR of advanced NPPs which are caused by human errors. The results show that the potential problems that would probably contribute to the human performance of MCR in the advanced NPPs are multiple accidents, pressure level, number of operators, and other factors such as working environmental. The conclusions of this research may be considered to avoid and prevent human errors in the human factor related researches especially in the nuclear safety field.

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 suggested.