Plant Main Control Research Articles

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.

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

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.

Transitioning Nuclear Power Plant Main Control Room From Paper Based Procedures to Computer Based Procedures

The United States (U.S.) has 99 operating Nuclear Power Plants (NPPs). The majority of these were designed and commissioned in the 1970s and 1980s. Plants are modernizing their control systems and main control rooms to be able to continue operating past their original 40-year license agreements. U.S. NPP main control rooms are migrating towards hybrid controls with both digital and analog systems. Digital upgrades, while costly, provide improved reliability, reduced maintenance cost, and the potential for fewer unplanned outages and fewer human errors. U.S. utilities have been slow to embrace computerized procedure system (CBP) research, even though CBPs demonstrate clear operational and human factors benefits. Most of the CBP research has been oriented to new reactor designs or full digital control rooms and is not applicable to the piecemeal modernization approach favored by U.S. plants. Research is needed to examine how CBPs impact operations in hybrid control rooms, and how current paper based procedures can be efficiently migrated to computerized platforms. Work is underway to develop tools and perform the obligatory research needed to design and validate CBPs for modernized U.S. nuclear control rooms.

Suggestion of Design Evaluation Plan based on Star Life Cycle to introduce the Information Minimalism Concept of KOREA Nuclear Plant

The design of Korea Nuclear Power Plant (NPP) main control rooms (MCR) has been changed to be fully digitalized. Five or six display devices are assigned to each operator in NPP MCR to provide the information of safety parameter and plant status, and various control functions by connecting computerized control devices. Under this circumstance, the distributed displays can induce a dispersion of the operators’ attention and increase the workload while conducting monitoring and control tasks efficiently. In addition, to support human operators to reduce their workload and increase the performance, the concepts of the ecological interface design (EID) and the operator-centered design were applied to the design HMI display. However these designs are applied to a limited set of screens and did not differ largely from the traditional HMI design in that the layout of the information is somewhere similar to P&IDs. In this paper, we propose a design evaluation plan based on star life cycle to introduce the information minimalism concept for designing an HMI display.

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.

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.

Reliability forecasting for operators’ situation assessment in digital nuclear power plant main control room based on dynamic network model

With the technical development of computer hardware and software, 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. Faced with these technical changes, operators need to continue improving their situation assessment (SA) reliability level. In addition to evaluate operators’ SA reliability, managers and shift supervisors also want to forecast their SA reliability level. There have been many studies with respect to operators’ SA, but most of them are static analysis method and cannot be applied to predict operators’ SA reliability. So, on the basis of different forecasting approaches and observation data, how to predict the operators’ SA reliability level has became a problem that many analyst interest in. In this paper, first we identified the influence factors associated with SA reliability, and then we developed the SA reliability model, finally we proposed a reliability forecasting model by integrating time series forecasting method with dynamic network model (DNM). Our experiment verification focused on steam generator tube rupture (SGTR) event, using the forecasting model, we demonstrated how to predict operators’ SA reliability during the course, and the prediction results are consistent with measurement results.

Establishing a Value Chain for Human Factors in Nuclear Power Plant Control Room Modernization

Commercial nuclear power plants in the United States (U.S.) have operated reliably and efficiently for decades. With a second 20-year life extension of operation beyond the plant's original operating licenses now being considered by many utilities, there are opportunities to achieve even greater efficiencies, while maintaining high operational reliabilities, through strategic, risk- and economically-informed, upgrades to plant systems and infrastructure. The U.S. Department of Energy's Light Water Reactor Sustainability (LWRS) program supports the commercial nuclear industry's modernization efforts through research and development (R&D) activities across many areas to help establish the technical and economic bases for modernization activities. The Advanced Instrumentation, Information, and Control Systems Technologies pathway is one R&D focus area for the LWRS program, and has researchers at Idaho National Laboratory working with select utility partners to use human factors and instrumentation and controls R&D to help modernize the plant's main control room. However, some in the nuclear industry have not been as enthusiastic about using human factors R&D to inform life extension decision-making. Part of the reason for this may stem from uncertainty decision-makers have regarding how human factors fits into the value chain for nuclear power plant control room modernization. This paper reviews past work that has attempted to demonstrate the value of human factors, and then describes the value chain concept, how it applies to control room modernization, and then makes a case for how and why human factors is an essential link in the modernization value chain.

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.

Comparison between conventional and digital nuclear power plant main control rooms: A task complexity perspective, Part II: Detailed results and analysis

Part II of this study aims to provide detailed, diagnostic information about the complexity difference between conventional and digital main control rooms (MCRs) in nuclear power plants. Complexity factors were classified according to task components and complexity dimensions. The effects of operator experience and plant type on complexity factors were statistically analyzed from three levels, i.e., task components, complexity dimensions, and individual factors. Interface management complexity factors were compared with other factors in digital MCRs. The results suggest that generally operator experience had effects on several task components and complexity dimensions only in abnormal/emergency situations. Plant type affected several task component and complexity dimensions in both abnormal/emergency and normal situations. Complexity factors in the affected task components and complexity dimensions had higher frequency, complexity, or impact in digital MCRs than those in conventional MCRs. Factors related to crew activity and the dimensions of overabundance, temporal demand, and variability had relatively high frequency, complexity, or impact. Compared with other factors, interface management complexity factors had marginally higher frequency, but significantly lower complexity and impact. Relevance to industryThis study quantitatively addresses the complexity difference between conventional and digital MCRs in detail. It may provide rich information for how to improve operator working environments in NPPs. It may also contribute to other applied domains, such as human reliability analysis and interface design.

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.

Effects of Information Organization and Presentation on Human Performance in Simulated Main Control Room Procedure Tasks

AbstractThe organization and presentation of information are critical in designing a display for industrial safety‐critical systems. How they affect human performance is not fully studied yet. Functional displays are newly proposed for nuclear power plant (NPP) main control rooms. The effect of functional organization and the choice of information presentation styles need to be examined. This study aims to explore the effects of information organization (process display vs. functional display), parameter presentation (text vs. bar chart), and component presentation (mimic vs. simplified graph) for better understanding the pros and cons of functional displays designed following function based task analysis (FBTA). Performance data were collected from simulated procedure tasks using eight (2 × 2 × 2) displays. The results indicate that the functional display based on FBTA was more effective than the process display, and this could be mainly attributed to its functional information organization rather than to its presentation styles of parameters and components.

The Influence of Individual and Team Cognitive Ability on Operators’ Task and Safety Performance: A Multilevel Field Study in Nuclear Power Plants

While much research has investigated the predictors of operators’ performance such as personality, attitudes and motivation in high-risk industries, its cognitive antecedents and boundary conditions have not been fully investigated. Based on a multilevel investigation of 312 nuclear power plant main control room operators from 50 shift teams, the present study investigated how general mental ability (GMA) at both individual and team level can influence task and safety performance. At the individual level, operators’ GMA was predictive of their task and safety performance and this trend became more significant as they accumulated more experience. At the team level, we found team GMA had positive influences on all three performance criteria. However, we also found a “big-fish-little-pond” effect insofar as team GMA had a relatively smaller effect and inhibited the contribution of individual GMA to workers’ extra-role behaviors (safety participation) compared to its clear beneficial influence on in-role behaviors (task performance and safety compliance). The possible mechanisms related to learning and social comparison processes are discussed.

A New Round Innovation of C-GIS

C-GIS is one of China's emerging medium - voltage electrical equipment packages. It is of small size, high reliability, adaptive advantages of diversity and changing environmental conditions. With the development of smart grid in China, C-GIS to the development of intelligent. According to relevant experts pointed out that the development of the intelligent switch cabinets along the two routes: First, the Device status response to the power plant main control the computer by remote control, implementation of intelligent switches and the entire system. This is the intelligent power plant level; Second, the intelligent switch ontology. The latter more acceptable to foreign and domestic manufacturers. Because intelligence is the most basic, most reliable of the components of intelligent, Mechanical by traditional mechanism to the electronic design of moving mechanism and innovation has put in front of our designers. The author from the perspective of institution design of the inflatable Cabinet (c-gis) technical aspects of design.

An empirical study on the relationships between functional performance measure and task performance measure in NPP MCR

In many industrial settings such as chemical plants and electrical power generating plants, operator performance measures have been used for multi-objectives such as control room design, human system interface evaluation, training and procedures. Because of multiple uses of performance measures, many methods and criteria for measuring human performance have been developed. Among these methods, functional performance measures and task performance measures are well known and widely used to measure human performance. Although these two methods are used independently for many industries, and most studies related to operators’ performance use one of these measures, there has been no research to directly identify the relationships between the two measures.In this paper, task performance and functional performance measures are compared and investigated in terms of whether they have any relationships under the same Interfacing System Loss of Coolant Accident (ISLOCA) scenario considered in the experiment. Furthermore, to gain realistic results, these two performance measures are applied to Nuclear Power Plant Main Control Room (NPP MCR) operators to measure their performances in a full-scope simulator. Finally, a regression line plotting the relation between task and functional performance score and the correlation of the two performance measures are investigated.

Advanced interaction media in nuclear power plant control rooms

The shift from analog to digital Instruments (related mainly to information visualization) and Controls in Nuclear Power Plant Main Control Rooms (NPP MCR) is a central current topic of investigation. In NPP MCR, digitalization was implemented gradually, analog and digital systems still coexisting for the two main systems related to safety--Safety Instruments and Control System (SICS) and Process Instruments and Controls System (PICS). My ongoing research focuses on the introduction of Advanced Interaction Media (AIM) such as stereoscopic 3D visualization and multi-touch surfaces in control rooms. This paper proposes a Safety-Centric approach for gathering the Design Rationale needed in the specification of such novel AIM concepts as well as their evaluation through user tests. Beyond methodological research, the final output of the current research is to build an experimental simulator aiming to enhance improvements in Human-Systems Integration (HSI). This paper provides an overview of the topics under consideration.

Mathematic Model Research on Panel Layout

The design criteria, operational frequency, operational order and compatibility are proposed and analyzed for nuclear power plant main control room. A layout optimization mathematic model is created based on these rules. Objective function of the mathematic model is developed, in which the distance of hands’ moving is added in order to measure the workload of operators. An example of 12 components on panel is implemented by particle swarm optimization.

Comparison between various control methods for thermal power plant main control system

In thermal power plants, it is important to improve the control accuracy of main steam pressure and temperature and so forth during load up/down. This paper focuses on temperature control, the most difficult aspect of control due to the nonlinearity and long dead time of power plants. We applied control methods such as MRAC, neural network, and long-range predictive control to the power plant main control system. Each method was evaluated by a simulator using detailed physical models that represent accurately the power plant dynamics. We confirmed that each method can provide proper control, but long-range predictive control is better than the two other methods. In addition, thermal power plants are so complex that further analysis (e.g., persistently exciting condition, learning method of neural networks) is necessary for the application of theoretical algorithms. © 1999 Scripta Technica, Electr Eng Jpn, 128(3): 72–81, 1999

New method of off-line adjustment of feed-forward control for fossil-fired plant main control system

In fossil-fired power plants, it is important to improve the control accuracy of, for example, main steam pressure and temperature during load increase/decrease. This paper focuses on temperature control, which is the most difficult control due to the nonlinearity and large dead time of power plants. First, we construct a simplified model of a power plant that has first-order lag and dead time. Second, a calculation method of feed-forward signal is proposed from the temperature measured during load increase/decrease. Optimal feed-forward signals were decided from various lead increase/decrease rates and load change widths, followed by generalization of feed-forward control at any rate and load change width. Neural network was applied for this generalization. The proposed method was evaluated by a detailed simulator that represents accurately the dynamics of power plants. © 1997 Scripta Technica, Inc. Electr Eng Jpn 119(1): 55–61, 1997