Main Control Room Research Articles

Scrutinizing the effect of task complexity on operators’ task performance time in a digitalized main control room of a nuclear power plant

The TACOM (Task Complexity) measure was previously developed to quantify the complexity of tasks conducted by human operators in the main control room of nuclear power plants. The appropriateness of the TACOM measure was then confirmed in various validation studies mainly by comparing TACOM scores and operators’ task performance times in analog-type main control rooms. However, the suitability of the measure has not yet been validated using operators’ task performance times in digital-type main control rooms. This study aimed to further validate the suitability of the TACOM measure by analyzing task performance time data obtained from a digitalized full-scope simulator of a Korean domestic nuclear power plant and comparing the data with TACOM scores. The findings reveal a positive correlation between the task performance times in the digitalized main control room and the TACOM scores, meaning that the operators’ task performance time increases proportionally as the TACOM score increases. This strongly implies that the TACOM measure is also a reliable tool for predicting task complexity in a digitalized main control room.

Dynamic human reliability analysis method for nuclear power plant main control room based on SPAR-H and SD

Human reliability analysis (HRA) plays a vital role in probabilistic risk assessment (PRA) by quantifying the reliability and safety of complex technical systems through the estimation of human error probabilities (HEPs). Standardized plant analysis risk human (SPAR-H) reliability analysis is widely used for HRA; it adjusts the nominal HEP by assigning different multipliers to the performance shaping factors (PSFs). However, SPAR-H cannot capture the time-varying nature of HEPs; therefore, it cannot realistically respond to the accumulation and fluctuation of human risk factors across the mission. Hence, this study proposed a systematic method of dynamic HRA. It includes decision-making trial and evaluation laboratory-interpretative structural modeling (DEMATEL-ISM) to qualitatively and quantitatively analyze the hierarchical causality among the PSFs and their influence on each other based on their relative relationship in SPAR-H and construct hierarchical causality diagrams among the PSFs. Additionally, it uses a system dynamics method in conjunction with the analysis of time-dependent PSFs based on the hierarchical causality diagrams of PSFs to respond to the time-varying nature of HEPs. The simulation and rationale check results of the cases show that the proposed dynamic HRA method can realize a more realistic and dynamic estimation of HEPs.

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.

Identifying a probe to visualize the variability of operating teams for supporting the human reliability analysis of nuclear power plants: An explanatory study

Operating teams consisting of several team members still play a critical role in coping with off-normal conditions in socio-technical systems. Thus, various kinds of human reliability analysis methods have been suggested based on the consideration of diverse performance shaping factors that can affect the performance of team members. Unfortunately, since multiple performance shaping factors can vary across operating teams (i.e., crew-to-crew variability), it is crucial to figure out how to visualize this variability in a systematic way. In this regard, comparing the cultural characteristics of operating teams with their performance would be a good starting point. This study investigates how cultural characteristics can be correlated with the occurrence of unsafe acts based on empirical data collected from operating teams working in the main control room of Korean domestic nuclear power plants. The cultural characteristics of the operating teams were visualized using five Hofstede’s cultural indices and compared with the number of unsafe acts observed from simulated off-normal conditions. As a result, a statistically significant correlation is found between the occurrence of unsafe acts and one of the Hofstede’s indices. From this finding, it is expected that a relevant probe to scrutinize crew-to-crew variability could be soundly determined in future works.

Utility and Industry Perceptions of Control Room Modernization Over the Last 10 Years

Within the current U.S. nuclear power fleet, main control room modernization (CRM) is an important step toward cost savings. In recent decades, plants have been engaged in upgrades to varying degrees. This process requires a nuanced, balanced, and timely approach that ensures continued safety and long-term sustainability. In 2012, a survey was issued to individuals from the nuclear industry to learn their perspectives on a range of CRM issues. The survey targeted the benefits and challenges for utilities undertaking this process, including the main drivers and barriers to technology upgrades, regulatory compliance, and the effects these factors have on concepts of operations, strategic approaches, and staffing. In 2022, the survey was issued again to understand whether CRM perceptions had changed in the last 10 years. Our findings identify changes in industry thinking from a decade ago. We reveal perspective shifts that represent increased optimism, and in some instances, increased doubt regarding the opportunities and challenges inherent in CRM and implementation. We also report nuanced differences in CRM perspectives between utility and surrounding nonutility nuclear industry respondents.

Automating execution of surveillance procedures for NPP main control rooms

ABSTRACT For the past 30 years, progress in the automation of control processes in the nuclear industry has been much slower compared to other industries. In the same timeframe, other complex industrial and/or high-risk processes (e.g., aviation) have been revolutionized by the exponential increase of technology capability in computing and information systems. The reason for the relatively slow trickling of technology advancements in the nuclear field is multi-faceted: i) resistance to change from a traditionally proven solution (partially due to very specific regulation requirements); ii) the cost to adopt Computerized Procedure Systems for existing NPPs, without having a quantified and proven safety benefit; iii) relatively low number of new NPPs being built following the Chernobyl and Fukushima disasters; iv) possible negative impact on the human factors aspect. After a short introduction to automation in another high-risk industry (aviation), this paper focuses on the practical approach required for automating Surveillance Procedures, and at the same time taking into consideration the human factors impact of this approach.

Task reliability index for operator performance and failure probability assessment in control room simulators

Main control room simulators are an important information source for improving the empirical basis of human reliability analysis (HRA). Both quantitative and qualitative observations provide valuable insight on the operators’ ability to successfully perform their tasks. However, relevant portions of this evidence are not used in typical approaches for estimation of human error probabilities (HEP), which are based on failure counts. With small sample sizes and the operator performance levels representative for nuclear power plants, very little information enters the probability estimates. This paper presents a novel approach to formalize the collection and use of reliability-relevant evidence from simulators. The methodology treats task reliability with the plant-centred orientation characteristic of the systems or Probabilistic Safety Assessment (PSA) perspective as well as a human-centred view of task performance based in human factors engineering. These are combined to form a Task reliability index (TRI) able to distinguish finer performance variations and consider indications of potential failures. Bayesian updating of HEP distributions is suggested by translating the TRI data into pseudo-failures and trials, preserving the convenient coupling of Beta-Binomial distributions in the Bayesian analysis. The approach is demonstrated using data from the International HRA Empirical Study and is shown to produce results that are comparable to those obtained in the empirical study, which were based on comprehensive expert analyses.

Uncertainty-Based Validation Methodology and Experimental Analysis for External Control Room Human Performance Simulation: Application to Fire Probabilistic Risk Assessment of Nuclear Power Plants

In probabilistic risk assessment (PRA) of nuclear power plants (NPPs), human reliability analysis (HRA) is conducted to identify potential human failure events that could contribute to risk scenarios and estimate human error probabilities. Lessons learned from the 2011 Fukushima Daiichi NPP accident underscored that for PRA, it is critical to model external control room (Ex-CR) human actions. The state-of-practice HRA methods, historically developed for the main control room HRA, are limited in capturing the unique nature of Ex-CR human actions, such as location dependence (in addition to the time dependence) of human actions and spatiotemporal interactions of human performance with the surrounding physical environments, for instance, hazard propagation. To advance the Ex-CR HRA in the context of the fire PRA for NPPs, the authors’ team developed a simulation-based fire crew performance model using an agent-based modeling (ABM) technique. The ABM fire crew simulation was coupled with a fire progression model through a spatiotemporal interface using a geographic information system. This paper focuses on the validation of the ABM simulation, which is the key requirement for the simulation-based Ex-CR human performance model to be utilized in PRA. The existing validation approach, initially developed for physical models in the fire PRA of NPPs, is extended for validation of the simulation-based Ex-CR human performance model. Model uncertainty is used as a measure of model validity, which facilitates the incorporation of the validation result into the PRA. The degree of the model uncertainty is characterized by a lognormal error model whose parameters are quantified based on a pairwise comparison between empirical data and model predictions. The proposed validation approach is demonstrated using a case study of the fire PRA of NPPs. This study makes two research contributions: (1) it is the first to validate the simulation-based Ex-CR human performance model against empirical human performance data and incorporate the validation result into the PRA of NPPs, and (2) this study, for the first time, conducts a controlled experimental test to collect empirical data for fire crew performance at NPPs.

Method of estimating break size in piping loop systems

The approach for determining the break size of recirculation loops in a multiple-loop power plant in the event of a loss of coolant accident (LOCA) is presented in this study. In this study, the MAAP5 simulation program was used. An approach to measuring the size of a crack or break in the cooling system is the temperature difference between the recirculation loops. This method does not require any additional facilities; it compares the temperatures of the cooling loops to determine which one has a rupture. The best data source was the loop monitoring system, which sends temperature data for analysis to the main control room. A real operating power reactor training simulator and the FSAR are applied to evaluate MAAP5, the methodology's engine. The results of the MAAP5 simulation code were consistent with those of the power plant simulator. Therefore, MAAP5 could produce enough analytical data to create the relationship diagram between temperature difference and break size.The study hypothesized that there exists a maximum value of temperature difference corresponding to each break size and suggested that applying the absolute maximum temperature difference can aid in identifying the break size. This approach proposes an assistive method for determining the size of a fracture or break in the recirculation system by leveraging the temperature difference between each loop.This approach eliminates the need for additional facilities, as temperature data from the recirculation loops can be transmitted to the main control room. After the reactor scram, operators can monitor the maximum temperature differences at the inlet to estimate the break size. Although the fitting curve used to preliminary estimate the Large Break Loss of Coolant Accident break size may overestimate the break size, it still provides valuable insights. This novel tool offers a rapid and comprehensive method for detecting LOCA events in the recirculation loops.

Justification of fire protection measures in the NPP control room using CFD fire modeling

Introduction. The present paper provides justification of fire safety measures to protect systems of the main control room of NPP using computational fluid dynamics fire modeling.Aim. To develop fire protection measures for systems of the NPP control room using computational fluid dynamics model.Materials and methods. The study involved analysis into purpose and application scope of various methods for modeling dynamics of development and spread of fire hazards. The application of the computational fluid dynamics fire modeling for multifunctional premises was considered.Results. Following the analysis of different methods for modeling the dynamics of development and spread of fire hazards, the present paper introduces the potential of using various methods of fire modeling in the evaluation of fire hazards for main control room. The obtained computations show that the temperature at the reinforcement site remains below the critical value in the most dangerous fire development scenarios like ventilation controlled fire. Moreover, fire hazards fail to spread through the walls of an uninsulated room within three hours at any value of fire load in main control room.Conclusions. The study revealed a potential for using computational fluid dynamics fire modeling for evaluating fire hazards in various buildings and premises, as well as for justifying the sufficiency of fire resistance requirements established for building structures. This regularity is obtained under conditions of preventing the spread of fire beyond the fire zone within the estimated burnout time of the entire fire load. The results received for this particular type of premises (cable floor) indicate that the designed fire resistance of the barriers separating safety system premises and normal operation premises guarantees non-proliferation of fire. The obtained regularities can be used in the development/revision of regulatory documents on fire safety at operating NPPs and NPPs under construction

Electric Field Level Prediction in a Nuclear Power Plant's Main Control Room Using CNN Model

Electric Field Level Prediction in a Nuclear Power Plant's Main Control Room Using CNN Model

Design Change and Operational Consideration of the HVAC System during Nuclear Power Plant Decommissioning

The heating, ventilation, and air conditioning (HVAC) system plays a crucial role in ensuring the safety of workers and preventing the release of gaseous radioactive materials into the environment during the decommissioning of a nuclear power plant (NPP). To establish an HVAC operation strategy, decommissioning phases were divided into four stages, and the HVAC systems were reclassified. In addition, assumptions have been made regarding design modifications and maintenance for the reactor containment building (RCB) HVAC, fuel handling building (FHB) HVAC, and main control room (MCR) HVAC. Based on these, for RCB HVAC operation, natural ventilation and RCB purge operation during the transition period are proposed. In the decommissioning stage, recirculation operation, entire ventilation operation consisting of continuous operation and purge operation, and finally partial ventilation operation to purify local space were proposed. Moreover, during the transition period, the FHB HVAC was proposed to operate as normal NPP, and the MCR HVAC was suggested to operate with safety-related equipment removed.

Identification of primary input parameters affecting evacuation in ventilated main control room through CFAST simulations and application of a machine learning algorithm to replace CFAST model

Accurately predicting evacuation time in a ventilated main control room (MCR) during fire emergencies is crucial for ensuring the safety of personnel at nuclear power plants. This study proposes to use neural networks alongside consolidated fire and smoke transport (CFAST) simulations to serve as a surrogate model for physics-based simulation tools. Our neural networks can promptly predict the evacuation time in MCRs, proving to be a valuable asset in fire emergencies and eliminating the need for time-consuming rollouts of the CFAST simulations. The CFAST model simulates fire and evacuation scenarios in a ventilated MCR with variations in input parameters such as door conditions, ventilation flow rate, leakage area, and fire propagation time. Target output parameters, such as hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD), are used alongside standardized evacuation variables to train a machine learning model for predicting evacuation time. The findings suggest that high ventilation flow rates help to dilute smoke and discharge hot gas, leading to lower target output parameters and quicker evacuation. Standardized evacuation variables exceed the required abandonment criteria for all door conditions, indicating the importance of proper evacuation procedures. The results show that neural networks can generate evacuation times close to those obtained from CFAST simulations.

Novel Approach for Network Data Exchange Among Safety-Related Control Systems of Nuclear Reactors

Industrially mature digital networking technologies form the backbone of the distributed control architectures of nuclear reactors. Typically, hundreds of control systems responsible for assuring safer and secure plant operations are located in the field and interconnected via wired isolated local area networks, which are also connected to centralized servers and operating consoles located in the main control room. Many of such control systems require data processed by other systems situated far away in the plant, which mandates multiple concurrent reliable TCP sessions to be active or live for such field-level control systems. Multi-socket communication beyond 10 is practically difficult for embedded systems with limited memory and processing capabilities; hence, data accumulation, extraction, and routing are typically done with the help of commercially available high-performance servers and switches. The servers and operating consoles of a plant are generally Linux-based commercial-off-the-shelf (COTS) industrial computers, whose development lifecycle is not accessible for review and in accordance with safety guides; hence, qualifying such components for safety operations is extremely difficult. This paper presents a novel way of independently offloading safety-related data transactions from such COTS components (reducing dependency) with the help of very simple, reliable, and secure hardware, which is referred to as a data exchange and processing unit (DEPU). An approach is proposed to realize distributed control architecture with this proposed hardware (to simplify qualification tasks) along with existing servers and operating consoles without compromising powerful and convenient human-machine interface as well as the data logging capabilities of such components. Hardware and software design perspectives, performance characterization, and qualification testing of the DEPU in accordance with nuclear power plant instrumentation and control system design guidelines are also briefed in this paper.

Fire simulation in the main control room of Bushehr nuclear power plant using CFAST software

Fire simulation in the main control room of Bushehr nuclear power plant using CFAST software

Measuring team situation awareness through team communication: A study on nuclear main control room crews.

Situation awareness (SA) in complex socio-technical systems is considered a key cognitive activity, as control crews are often engaged in simultaneous task processes and are required to monitor and evaluate system parameters, making decisions and projections for the future accordingly. However, measuring SA at the team level is still a challenging area of research within the topic. In our research, we applied verbal protocol analysis as an alternative method to assess nuclear power plant control room crews' team SA. We conducted a study of 10 control room crews, examining their intrateam communication and its relatedness to team performance. We have found that communication categories related to the second and third levels of team SA increased significantly after the onset of an emergency event. Furthermore, while none of the team communication categories was related to team performance before the emergency event, all of them showed a strong positive correlation with team performance after the emergency situation occurred. Our results underline the importance of adequate verbalization of key information within the team, so as to support the rapid and accurate development of team SA during emergency situations.

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.

Collecting and Organizing the Influencing Factors of Team Communications to Handle Nuclear Power Plant Emergencies

A nuclear power plant (NPP), as a complex safety-critical system, requires qualified operators working in teams. Interactions between operators in the main control room (MCR) team are important to ensure safe operation. Since communication is the basis of the operators’ interactions, team communication is a significant factor affecting teamwork performance. Especially during NPP emergencies, poor team communication may lead to incorrect decisions and countermeasures, causing deterioration toward accidents. Moreover, in an emergency situation, emergency response teams are assembled. This multi-team and critical work condition further emphasizes the need for effective and accurate team communication. We collected the factors influencing team communication in NPP emergencies using a literature review combined with text mining. Our method for extracting the influencing factors consists of four steps; then, by applying topic modeling from text mining, we complemented the influencing factors. The resulting list of influencing factors of team communications for handling NPP emergencies is organized into five elements: individual, team, communication, NPP tasks, and external elements. Discussions on the team communication model, applicability, communication errors, and emergency response teams are also presented.

Numerical simulation of indoor air distribution and wall heat storage under accident conditiohs in a main control room

The main control room serves as a refuge for staff in a nuclear power plant in the event of an accident. To determine whether the control room can meet habitability requirements under accident conditions, this study utilized CFD methods to establish a habitability model of the main control room under such conditions. The changing trends of temperature and velocity near personnel were analyzed. The numerical results indicate that the building envelope significantly contributes to reducing the indoor temperature. The average wall temperature measured at 72 hours was 27?C, with an average temperature increase of 4?C. The highest average ambient temperature in the main control room occurred at 24 hours. At this time, the indoor ambient temperature reached approximately 34.62?C, with a temperature increase of 11.62?C, while the wind speed near the personnel remained below 0.2 m/s, meeting habitability requirements for personnel under extreme conditions.

Safety of Evacuation According to Habitability Criteria for Main Control Room of Nuclear Power Plant

The operator is always present in the main control room (MCR) of a nuclear power plant. However, when a fire occurs in an MCR, different conditions for operator habitability are proposed using various criteria, and various evacuation safety evaluation results can be obtained. In this study, fire and evacuation simulations of an MCR were performed to determine the available safe egress time and required safe egress time. In addition, the evacuation safety and habitability of the MCR were evaluated for various criteria.