Main Control Room Operators Research Articles

Design challenges and response plans for intelligent decision support systems for Korean nuclear power plants under normal and abnormal conditions

In nuclear power plants (NPPs), an intelligent decision support system (IDSS) aids the decision-making process of main control room operators. It achieves this by monitoring and diagnosing conditions, predicting progress, and providing preventive advice during both normal and abnormal operations. Despite ongoing research in Korea, few IDSS for NPPs have been effectively applied and verified. Furthermore, established designs and validation guidelines for IDSSs for Korean NPPs remain lacking. To address this gap, this study systematically identifies problems and corresponding countermeasures for applying artificial intelligence-based design and validation technologies, while complying with licensing regulatory standards. The aim is to develop a practical and effective IDSS. This study identifies design challenges in the practical application of fundamental IDSS technology, outlining necessary design and validation technologies. Additionally, it suggests technology-specific response plans for the identified design challenges.

A Novel Communication Framework for Reduction of Staffs in Advanced MCRs of SMRs: A Prototype Development of a NLP-Based System

As small modular reactors are gaining attention as the future of nuclear energy, it has become increasingly imperative to minimize the number of required operators in order to improve economic competitiveness. Although the tasks of operators have changed and their workloads have been relatively reduced as digital technologies have been applied to advanced main control rooms (MCRs), no change in the number of operators has been made when compared to conventional MCRs in the Republic of Korea. As a solution, the introduction of natural language processing (NLP) technology to replace certain operator tasks in advanced MCRs can be a valuable means of reducing MCR staff. In this paper, we suggest a novel communication framework utilizing NLP technology to minimize the number of operators in advanced MCRs. To do this, we analyze operator tasks in advanced MCRs and select those that can be replaced by NLP technology. We then develop a prototype NLP-based system and analyze the process and characteristics of the suggested communication framework.

Research on modeling in operator mental workload based on VACP method

AbstractIn the context of the applications of higher automation and complex system configuration in nuclear power plants (NPPs), ensuring nuclear safety by maintaining the reliability of the operators in main control room is become more crucial than ever before. As an essential dimension of physiological indicator, human mental workload is widely used in evaluating human performance and reliability. This paper presents an approach to evaluate the mental workload of operators using multiple resources in Visual, Auditory, Cognitive, and Psychomotor (VACP) model, and takes time pressure (TP) as a critical index. We have performed the approach by a real case study and analyzed the relationship between the operator mental workload and TP, task type and the error probability during the Loss of Coolant Accident (LOCA) under full power operation. There are two operating phases in the workload has been analyzed. Moreover, the relationship between human‐error probability (HEP) and TP had been studied via volatility gain analysis for distinguishing which step of a task is of most important. The results shows that the fault remind (“informing LOCA”) is the first important fluctuation in the phase ignoring TP and HEP. On the other hand, the information validity (“ensuring control rods has been inserted to the bottom”) in the case considering TP is the most important. Because the high task load is positively correlated with human error, the research provides an important basis for preventing human errors in the phase of NPP designs, which will be especially useful in safety‐critical tasks.

An Approach to Analyze Diagnosis Errors in Advanced Main Control Room Operations Using the Cause-Based Decision Tree Method

Advancements in the nuclear industry have led to the development of fully digitized main control rooms (MCRs)—often termed advanced MCRs—for newly built nuclear power plants (NPPs). Diagnosis is a major part of the cognitive activity in NPP MCRs. Advanced MCRs are expected to improve the working environment and reduce human error, especially during the diagnosis of unexpected scenarios. However, with the introduction of new types of tasks and errors by digital MCRs, a new method to analyze the diagnosis errors in these new types of MCRs is required. Task analysis for operator diagnosis in an advanced MCR based on emergency operation was performed to determine the error modes. The cause-based decision tree (CBDT) method—originally developed for analog control rooms—was then revised to a modified CBDT (MCBDT) based on the error mode categorizations. This work examines the possible adoption of the MCBDT method for the evaluation of diagnosis errors in advanced MCRs. We have also provided examples of the application of the proposed method to some common human failure events in emergency operations. The results show that with some modifications of the CBDT method, the human reliability in advanced MCRs can be reasonably estimated.

Investigating the Effect of Task Complexity on the Occurrence of Human Errors observed in a Nuclear Power Plant Full-Scope Simulator

The task complexity (TACOM) measure was previously developed to quantify the complexity of the proceduralized tasks performed by nuclear power plant main control room operators, and its suitability has been verified by comparing TACOM scores with two different types of human performance data, response times and subjective workload scores. The full appropriateness of the measure has yet to be sufficiently validated though, because of a current lack of comparisons between TACOM scores and associated human errors. In this regard, the purpose of this study was to further confirm the appropriateness of the TACOM measure by comparing human error data collected from a full-scope simulator of a domestic Korean nuclear power plant with the associated TACOM scores. Results show that the number of human errors increases proportionally with an increase in TACOM score. This result strongly implies that the TACOM measure is suited for use as a tool to estimate the complexity of proceduralized tasks, which would act as a key indicator to identify the vulnerable points most likely to lead to operator performance degradation.

Evaluation of operation state for operators in NPP Main control room using human behavior recognition

The cognitive state of the main control room (MCR) operator is the state of cognitive progress. This paper proposes a video analysis method to assist in the analysis of the operation state. A behavioral coding method is presented for the feature extraction of the MCR operator, and the time-line analysis method is used to continuously sample the operator’s postures and actions. OpenPose algorithm and ST-GCN method are used for the recognition of the operator’s behavior. The level of consciousness and cognition is analyzed based on the operator’s body language and used to evaluate the level of mental stress in performance shaping factors (PSF). A case is presented for the feasibility analysis of the operation state evaluation method. The results of the video analysis help recognize the operator’s bad or error behavior and improve the operator’s operation state.

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.

INFORMATION PROCESSING IN THE REACTOR PROTECTION SYSTEMS OF HIGH TEMPERATURE GAS-COOLED REACTORS

Reactor protection systems (RPS) transform process variable signals from the sensors into initiation and actuation signals to trip the reactor if the signal's value exceeds the predefined trip setpoints of the RPS. Information on the current value of the process variables signals and the trip setpoint should be displayed properly on the visual display unit (VDU) in order to maintain the situation awareness of the operators in main control rooms (MCR). In addition, it is also helpful for them to investigate the cause of an accident after the reactor trip and to mitigate the accident based on the appropriate emergency operating procedures. This paper investigates how the information is processed in the RPS of Experimental Power Reactor (EPR) based on high temperature reactor (HTR) technology, and how the information is displayed on the human machine interface (HMI) of the MCR of the EPR. It is conducted by classifying the RPS into three layers based on its components and their functions, followed by the investigation of the type and the information processing in each layer. The results show that the form of the information has been changed throughout the RPS, started from the sensors and until it is displayed on the VDU. The results of the investigation are necessary to understand the concept of RPS, especially for new operators, and to prepare the mitigation actions based on the process variable that cause the reactor trip.Keywords: Experimental power reactor, Reactor protection system, Human machine interface, Information processing, Situation awareness

The effect of communication quality on team performance in digital main control room operations

A team of operators is required for nuclear power plant operation, and communication between the operators is an important aspect of the team's ability to successfully carry out tasks. It has been difficult to evaluate the quality of this communication though, and as the relationship between communication quality and team performance has yet to be clarified, it has not been applied to most human reliability analysis (HRA) methodologies. This study investigates the relationship between the quality of communication and team performance using data from a full-scope training simulator of a digital main control room (MCR). Two important characteristics of communication were considered to determine quality: each operator's ability to self-confirm the status of a given task in a digital MCR, and the type of communication, as divided into 1-way, 2-way, and 3-way between operators. To measure team performance, the concept of an unsafe act was employed, which is defined as a human error that has the potential to negatively affect plant safety. Analysis results showed that the communication quality and team performance were related to each other. With this more clearly defined relationship, the results of this study can be applied to related performance shaping factors to improve HRA.

Variability of plant risk due to variable operator allowable time for aggressive cooldown initiation

Abstract Recent analysis results with realistic assumptions provide the variability of operator allowable time for the initiation of aggressive cooldown under small break loss of coolant accident or steam generator tube rupture with total failure of high pressure safety injection. We investigated how plant risk may vary depending on the variability of operators’ failure probability of timely initiation of aggressive cooldown. Using a probabilistic safety assessment model of a nuclear power plant, we showed that plant risks had a linear relation with the failure probability of aggressive cooldown and could be reduced by up to 10% as aggressive cooldown is more reliably performed. For individual accident management, we found that core damage potential could be gradually reduced by up to 40.49% and 63.84% after a small break loss of coolant accident or a steam generator tube rupture, respectively. Based on the importance of timely initiation of aggressive cooldown by main control room operators within the success criteria, implications for improvement of emergency operating procedures are discussed. We recommend conducting further detailed analyses of aggressive cooldown, commensurate with its importance in reducing risks in nuclear power plants.

Design and Implementation of HuREX Analysis Supporting Interface for HRA Data Extraction

It is well-known that one of the main causes of problems affecting social-technical systems, including nuclear power plants (NPPs), is human error. For this reason, reducing human error through human reliability analysis (HRA) is important. Furthermore, sufficient and reliable human performance data collection is a prerequisite for ensuring the safety of NPPs. The Korea Atomic Energy Research Institute developed the Human Reliability data EXtraction (HuREX) framework to provide a standard guideline for the collection and analysis of human performance data from operators in main control rooms based on simulator training records of NPPs. To do this, the development of a computerized software interface is required to collect simulator-based human performance data systematically and then to enter/analyze/quantify the various forms of data obtained from the simulator. In addition, a HRA database is needed for the effective management of the data generated during this process. In this research, we develop an interface that supports HuREX analysis so that HRA practitioners can conduct more effective HRA data analyses by integrating various types of raw data (e.g., audiovisual records, plant parameters, and operator action logs) collected from simulators. In addition, we expand the OPERA database to store a standardized data structure for more effective analyses of unsafe acts via the HuREX data analyzer and the HuREX video analyzer.

Study on the passive refrigeration for main control room of nuclear power plant in power outage accident

High-pressure air with room temperature can be used for refrigeration through isentropic expansion or isenthalpic throttling process with no power supplying, which can also meet the demands of oxygen supplying for operators in the insulated situation. Two passive cooling strategies for high-pressure air are proposed: one is throttling refrigeration, and the other is expansion refrigeration, which can provide an effective method to ensure the safety of operators in main control room when an emergency occurs in nuclear power plant. Comparisons between the two passive cooling strategies are done by theoretical and experimental methods, and the cooling effects for both strategies are analyzed. The results show that the passive cooling strategy of isentropic expansion can meet the both requirements of cooling and clean air supplying for the main control room when emergencies occur in nuclear plants, with the minimum cooling capacity of 3000 W.

A framework to estimate probability of diagnosis error in NPP advanced MCR

Recently, a new type of main control room (MCR) has been adopted in nuclear power plants (NPPs). The new MCR, known as the advanced MCR, consists of digitalized human-system interfaces (HSIs), computer-based procedures (CPS), and soft controls while the conventional MCR includes many alarm tiles, analog indicators, hard-wired control devices, and paper-based procedures. These changes significantly affect the generic activities of the MCR operators, in relation to diagnostic activities. The aim of this paper is to suggest a framework to estimate the probabilities of diagnosis errors in the advanced MCR by updating a time reliability correlation (TRC) model. Using Bayesian inference, the TRC model was updated with the probabilities of diagnosis errors. Here, the diagnosis error data were collected from a full-scope simulator of the advanced MCR. To do this, diagnosis errors were determined based on an information processing model and their probabilities were calculated. However, these calculated probabilities of diagnosis errors were largely affected by context factors such as procedures, HSI, training, and others, known as PSFs (Performance Shaping Factors). In order to obtain the nominal diagnosis error probabilities, the weightings of PSFs were also evaluated. Then, with the nominal diagnosis error probabilities, the TRC model was updated. This led to the proposal of a framework to estimate the nominal probabilities of diagnosis errors in the advanced MCR.

Development of digital device based work verification system for cooperation between main control room operators and field workers in nuclear power plants

Digital technologies have been applied in the nuclear field to check task results, monitor events and accidents, and transmit/receive data. The results of using digital devices have proven that these devices can provide high accuracy and convenience for workers, allowing them to obtain obvious positive effects by reducing their workloads. In this study, as one step forward, a digital device-based cooperation support system, the nuclear cooperation support and mobile documentation system (Nu-COSMOS), is proposed to support communication between main control room (MCR) operators and field workers by verifying field workers’ work results in nuclear power plants (NPPs).The proposed system consists of a mobile based information storage system to support field workers by providing various functions to make workers more trusted by MCR operators; also to improve the efficiency of meeting, and a large screen based information sharing system supports meetings by allowing both sides to share one medium. The usability of this system was estimated by interviewing field operators working in nuclear power plants and experts who have experience working as operators.A survey to estimate the usability of the suggested system and the suitability of the functions of the system for field working was conducted for 35 subjects who have experience in field works or with support system development-related research. The usability test was conducted using the system usability scale (SUS), which is widely used in industrial usability evaluation. Using questionnaires made specifically for this test, a function suitability was evaluated to determine whether the system stores work results in sufficient detail, without any disadvantages for field workers.Based on the results of the questionnaires, it is expected that the functions of the cooperation and work verification support system will be useful for understanding field workers’ work results if the manual or the set of guidelines for using the suggested system is well constructed.

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

Abstract 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.

Study on dynamic evolution of operators’ behavior in digital nuclear power plant main control room – Part I: Qualitative analysis

Digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Many studies shows that the adoption of digital technology has brought some new risks for MCR operators, and whether the reliability of these technologies can meet safety and economic requirements has become one of the urgent problems that NPPs must solve. The study consists of two parts. In Part I, we investigated the dynamic evolution of operators’ four behaviors: monitoring and detection (MD), situation assessment (SA), response planning (RP), and response implementation (RI). This paper incorporates Boolean network (BN) analysis into the field of human reliability analysis (HRA), by applying semi-tensor product of matrix (STP), whereby the dynamics evolution of operators’ behavior can be expressed in an algebraic form. Utilizing this algebraic representation, a BN analysis model is proposed, on which we based a qualitative analysis. An illustrative example is given to show how to construct the BN model via experimental data. We also discuss the advantage of the proposed methodology, its feasibility and highlighting the future work remaining.

Methodology for analyzing the dependencies between human operators in digital control systems

In a digital control system, the dependency model between the actions of operators differs from that in a conventional control room because information sharing and the main control room (MCR) operations are team operations. Dependencies between the actions of operators are more common in a digital control system compared with a conventional control room because operators share the same information and MCR operations are directed by team decisions. Therefore, assessing the dependencies between operators is an important aspect of human reliability analysis. In this study, we use a fuzzy logic-based approach to evaluate the dependencies among the actions of operators in the present study. First, the factors that influence the dependency levels among the actions of operators are identified by analyzing the characteristic human factors in a digital control system and an analytical model of the dependencies is then constructed. Second, a method for analyzing the dependencies between the actions of operators is established based on a fuzzy logic approach. This method can simulate vague and uncertain knowledge, but it also provides a clear explanation of the origins of results and their reasoning process by tracing the steps in reasoning. Therefore, traceability and repeatability are characteristics of the proposed method. Third, we present a case study to demonstrate the proposed approach. Finally, we demonstrate that the results obtained are reasonable and that the established model is stable based on validations that involve data comparisons and a sensitivity analysis of the model.

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.

Comparing cultural profiles of MCR operators with those of non-MCR operators working in domestic Nuclear Power Plants

Operation experience of complex socio-technical systems such as Nuclear Power Plants (NPPs) shows that most significant events are attributable to human error. Thus, various kinds of Human Reliability Analysis (HRA) techniques were used to manage human error for safety-critical tasks. However, a lack of available HRA data is a critical issue in conducting an HRA. For this reason, many researchers have tried to provide HRA data extracted from simulated emergency conditions. Unfortunately, it is still doubtful to directly use these HRA data because different operational cultures may result in different human performances even under a similar task context. From this concern, previous studies claimed that Main Control Room (MCR) operators working in different NPPs share very similar cultural profile. In order to confirm this claim, the culture profiles of operating personnel (i.e., non-MCR and MCR operators) working in domestic NPPs are compared. As a result, although some discrepancies are observed, it is positive to say that operating personnel of NPPs share similar cultural profiles to some extent. This result can be regarded as the first step to provide technical underpinnings that are helpful for understanding human performance data collected from different countries.

Comparison between conventional and digital nuclear power plant main control rooms: A task complexity perspective, part I: Overall results and analysis

Digitalization is a trend in safety-critical complex systems. It changes the way human interacts with systems. We have less empirical knowledge about its potential negative effects on human. In our study, we compared conventional and digital main control rooms (MCRs) in nuclear power plants (NPPs) from a task complexity perspective. Complexity factors in MCRs were quantified in terms of three aspects, frequency of occurrence, complexity induced by their being, and impact caused by them. A total of 69 licensed operators participated in the study. The study consists of two parts. In Part I, overall results and analysis were reported. Generally, operators in digital MCRs perceived higher frequency and higher impact of complexity factors than those in conventional MCRs, no matter in abnormal/emergency or normal situations. Operators in digital MCRs perceived higher complexity than those in conventional MCRs in abnormal/emergency situations. These findings suggest that operators in digital MCRs experience higher complexity and workload which may reduce their reliability. These findings imply that we should caution the side-effects of ubiquitous digitalization in complex industrial systems. Relevance to industryDigital technologies are widely deployed in the nuclear industry. They change the working environments in which operators interact with NPP systems. There is insufficient research on operator experience on the changes brought by technological developments in NPP control rooms. Our findings imply that we should take care of the potential negative effect of digitalization on operator working environments.