Power Plant Control Room Research Articles

Multi-Stage Evaluation Using GONUKE

Multi-stage validation (MSV) has become an important concept in nuclear power plant control room design and modernization. MSV consists of multiple stages of collecting evidence that establish reasonable confidence in the design. The Guideline for Operational Nuclear Usability and Knowledge Elicitation (GONUKE) was created as a framework to support different types of human factors evaluations across different stages of the design and development life cycle. The GONUKE framework did not originally address MSV, but it espoused safety case approaches that build different evidences toward design completion, which is a complementary approach to MSV. In this paper, we show how GONUKE specifically aligns to MSV. We then expand the discussion to include multi-stage evaluation. As defined in GONUKE, there are three types of evaluation. Validation is empirical evidence collected through human-in-the-loop studies, whereas verification is expert comparison of a design against formalized standards, and epistemiation is expert knowledge transfer to design.

Extended cognitive reliability and error analysis method for advanced control rooms of nuclear power plants

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

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 Reliable People Tracking in Nuclear Power Plant Control Room Monitoring System Using Particle Filter

A Reliable People Tracking in Nuclear Power Plant Control Room Monitoring System Using Particle Filter

Simulator Feature Framework: Requirements to Support Training, Research, and Education

There is an expansion of nuclear power plant control room simulator use beyond traditional operator training. Modern simulator designs require more robust capabilities to serve the diverse needs of multiple user groups including researchers and educators. A common framework for evaluating simulator features to support training, research, and education is critical to ensure future simulators enable research for immediate and future plant modernization and advanced reactor deployment needs. An initial framework comprised of 8 feature categories was developed by reviewing published simulator-based research and analyzing simulator features against research objectives and results. Future research will focus on evaluating the suitability of this framework in characterizing and differentiating simulators across training, research, and education use cases.

A Bayesian two-stage approach to integrate simulator data and expert judgment in human error probability estimation

With the ongoing efforts to collect new data for Human Reliability Analysis (HRA) (in particular, from nuclear power plant control room simulators), it becomes important that the coming data will be processed traceably, addressing its underlying variability, eventually in combination with expert judgment. In this direction, this work presents a two-stage Bayesian model to integrate expert-elicited probability estimates and empirical evidence from simulator data in the quantification of HEP values and of the associated variability distributions. The general aim is to provide a data aggregation framework able to mathematically combine diverse information sources throughout the HEP estimation process, in a systematic and reproducible way, contributing to strengthening the empirical basis of future HRA methods. The Bayesian model can be used to produce reference values and bounds for HRA methods as well as to improve the quality of plant-specific HEP estimates for use in Probabilistic Safety Assessment applications. The model is first verified with artificial data and then applied to quantify the HEP of human failure events from literature. Model sensitivity to biases in expert estimates is also investigated.

Regulatory Considerations for the Potential Use of a Multi-Stage Validation Testing Approach to Support Human Factors Engineering Technical Reviews for Proposed Nuclear Power Plant Control Room Design Modifications

Traditionally, integrated system validation (ISV) testing for proposed nuclear power plant control room design changes has been completed prior to the U.S. Nuclear Regulatory Commission (NRC) approving the proposed change. This, however, can pose scheduling challenges for proposed changes to operating facilities. The NRC is therefore considering possible alternatives for licensees to provide the human factors engineering validation information necessary to demonstrate reasonable assurance of safety for proposed design changes. One such alternative could be the use of early-stage testing results from a multi-stage validation (MSV) program. If early-stage results, along with other design considerations, can provide sufficient supporting information, the NRC may be able to make a safety determination for a proposed design change prior to the completion of ISV testing. Licensees proposing such an approach should consider available industry standards discussing MSV, in conjunction with existing NRC guidance where applicable, when developing their validation program and establishing success criteria. The NRC intends to engage in future discussions with stakeholders regarding the potential development of additional NRC-endorsed guidance on the use of MSV to support proposed changes to existing facilities, as well as designs for new reactor control facilities.

Dynamic thermal performance analysis for fin-concrete ceiling in main control rooms of passive nuclear power plants

The main control rooms of passive nuclear plants must maintain a habitable environment once station-blackout accidents occur. In this condition, the heavy fin-concrete ceiling on the room will remove heat from kind of heat sources and protect from overheating environment. However, the dynamic thermal process of finned concrete ceiling has not been studied in various passive cooling measures. In this study, an efficient parametric resistance–capacitance thermal network model is established to describe dynamic thermal responses of heavy fin-concrete layer, and validated by dynamic temperature change data of a hot-box experiment for 24 h. Series indicators were deduced by analytic solutions. Based on the validated model and indicators, factor analysis was conducted to obtain details of effect of finned-plate geometric parameters and heat source intensity. The results show that initial 2-h thermal process can be divided into two stage, “transient stage” and “quasi-stable stage”. The transient-stage thermal process is determined by source flux and finned coefficient of finned plate. The quasi-stable thermal process depends on thermal mass of the finned plate and heat source flux. Furthermore, there exists a linear relationship between air temperature and heat source flux. Finned plate layout can be design according to the factor assessment results.

Exploring Individual factors influencing human reliability among Control Room Operators: A qualitative study

: Identifying the individual factors is a major issue in determining the likelihood of human error and ultimately human reliability. in current human reliability assessment (HRA) methods this is determined based on a performance shaping factors(PSFs) list and experts’ judgment. This was a qualitative content analysis study, in which the participants were selected using purposive sampling from the combined cycle power plant control rooms. Semi-structured interviews were performed and collected data were analyzed. A total of 32 operators (20 Module controller, 8 head operators, and 4 managers) were interviewed. Five categories were extracted, namely “mental condition”, “consciousness at work”, “professional competence”, “communication skills”, and “quick reaction and decision making capabilities”. Accordingly, it is suggested to taken into account such factors as professional competence and speed of reactions and to pay more attention to their important factors in the reliability of operators in combined cycle power plant control rooms.

Impact of workload on cognitive performance of control room operators

Workload has long been considered as one of the important factors for personal functions and malfunctions, particularly in complex systems. Undertaking operations in workstations of such systems usually entails complex tasks and poor cognitive performance of their operators may contribute to human error and critical subsequent consequences. Although many studies have investigated the effects of workload on the cognitive performance, there is a gap for specific jobs and operations such as control room operation. This paper then aims to determine that what dimensions of the workload has more impact on cognitive performance of a combined cycle power plant (CCPP) Control room operators. Control room operators from two CCPPs participated (n = 95) in this study. Hierarchical task analysis (HTA) was employed to perform the job analysis. To assess the perceived workload, NASA Task Load Index (NASA-TLX) was performed at the end of the work shift. The participants were subjected to three cognitive performance tests including sustained attention, simple reaction and working memory at the beginning and end of the work shift. The values of mental demand on check and control tasks (92.17 ± 4.38), decisions about abnormal conditions (90.16 ± 5.71) and reporting (85.09 ± 3.25) were high. The task of communication and coordination in terms of temporal demand (71.66 ± 7.3) and performance (68.04 ± 4.92) had higher values compared to other tasks. The highest weighted workload (84.27 ± 6.48) was also attributed to the task of checking and controlling. Sustained attention and working memory were more susceptible to excessive workload among CCPP control room operators.

An experimental study on the effects of task complexity and knowledge and experience level on SA, TSA and workload

With the improvement of digital level of main control rooms (MCRs) of nuclear power plants (NPPs), the issue of situation awareness (SA) of operator becomes particularly prominent in NPP operations. More and more scholars have done some research on SA and team situation awareness (TSA). In order to explore the effects of performance shaping factors (PSFs) on SA, TSA and workload, the effects of task complexity and operators’ knowledge and experience level on operators’ SA, TSA and workload were studied through simulator experiments. The results show significant effects on the operators’ SA and TSA levels. The higher the complexity of task, the lower the level of operators’ SA and TSA; and the higher the level of knowledge and experience, the higher the level of operators’ SA and TSA. Experiments also show that task complexity and the level of knowledge and experience have a significant impact on the operator's workload. The higher the task complexity is, the higher the operator’s workload level is, and the higher the knowledge and experience level is, the lower the workload level of the operator is. The research results provide a theoretical basis for improving the level of SA and reducing workload, and provide theoretical and experimental guidance for identifying the impacts of PSF on SA, TSA and workload.

AI-Guided Reasoning-Based Operator Support System for the Nuclear Power Plant Management

The decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

Systems usability case in stepwise control room validation

We present a Systems Usability Case approach enabling a requirement-based human factors evaluation of complex socio-technical systems. The approach is especially suitable for stepwise verification and validation activities of nuclear power plant control-room systems. Systems Usability Case is based on the Safety Case approach and exploits the Systems Usability construct. Systems Usability Case is a conceptual procedure within which a reasoning process takes place that enables moving from abstract understanding of human performance and usability of complex tools, to concrete proof of a specific system, and finally to interpreting, in elaborated abstract terms, what is learned about the overall acceptability and level of Systems Usability of the targeted system. The paper introduces the Systems Usability Case approach and demonstrates an application of it to real data from a stepwise control room validation. The results suggest that Systems Usability Case has some advantages: it helps to conduct the validation activities in a more systematic fashion; it makes the reasoning process more explicit and transparent; we are able to build a longitudinal view of the progress of the design process; and constructing the Systems Usability Case enables monitoring of the fulfilment of the requirements from the human factors (i.e., Systems Usability) perspective.

An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

AbstractThe paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data.

Coordination breakdowns in nuclear power plant control rooms: cause identification and behaviour-sequence analysis

This study aims to identify the causes of coordination breakdowns among control crews and to understand their coordination-behaviour patterns during emergencies in nuclear power plants (NPPs). On the basis of in-depth interviews with 18 control-crew operators, we identified 25 causes of coordination breakdown related to work processes, personnel, and situation and organisation. In addition, we observed 12 control-crew training sessions that dealt with emergencies and conducted lag-sequential analysis. The levels of coordination effectiveness were evaluated using the proportion of coordination breakdowns and the anticipation ratio. We found that higher-performing teams exhibited more non-random coordination behavioural patterns than did lower-performing teams. Coordination-behaviour patterns specific to the higher-performing teams included adaptive workload management (from senior operators) and proactive seeking performance monitoring (from junior operators). The findings of the study enrich our understanding of the critical factors and processes that influence coordination effectiveness of NPP control crews. Practitioner summary: Causes of coordination breakdowns among control crews of NPPs were identified based on in-depth interviews with control-crew operators, and behavioural-pattern analysis of control crews in 12 training sessions were analysed to reveal the patterns that differentiate higher- and lower-performing teams. The findings of the study enrich our understanding of the critical factors and processes that influence the coordination effectiveness of NPP control crews. Abbreviations: NPP: nuclear power plant; RO: reactor operator; TO: turbine operator; CO: coordinator; SRO: senior reactor operator

Human reliability analysis for operators in the digital main control rooms of nuclear power plants

ABSTRACT As the main control room of nuclear power plants (NPPs) has been gradually digitized, new human reliability problems may emerge because of a series of new changes in the cognitive processes, behavioral patterns, and error mechanisms of operators. Aiming to address this situation, this paper proposes a method as guidance for human reliability analysis (HRA) of different cognitive Stages. This method first constructs the influencing factors of three cognitive processes, including monitoring, decision-making, and execution of actions, and then evaluates the weights of these influencing factors through an analytic hierarchy process (AHP). In this study, the parameters used in the proposed HRA method were determined by analyzing the test data obtained from a simulation model, and the results demonstrated the rationality and feasibility of the proposed method. A case example using this HRA method was given in which the human error probabilities at three stages in a nuclear power plant (NPP) steam generator tube ruptures (SGTR) accident were obtained. In summary, the proposed method is a simple and feasible HRA tool that can be applied in digital NPP main control rooms (MCRs).

Rigged hand model for the Blender Game Engine

In a lot of virtual reality applications, it is necessary to display and animate the user's hand in the virtual world. In game engines, armatures are often used for modeling parts or the whole of the human body. The process of creating the armature and assigning parts of the mesh representing flesh and skin to the “bones” of the armature is called rigging. After performing rigging, moving the armature will result in the movement of the mesh, thus the virtual hand (or other object) is animated. The Blender Game Engine (BGE) is one of the few open-source game engines available. The paper gives a detailed description of the process of successfully building a complex rigged hand model for the BGE and gives guidance for driving this hand model with input data from the Leap Motion hand movement detector. The rigged hand model has been implemented, using the hand mesh from the LibHand library and an armature specifically built to match the hand representation of the Leap Motion. The model will be used for navigation and interaction in the virtual model of a power plant control room.

Feasibility of methods for early formative control room system evaluation

In a nuclear power plant, human factors evaluation is an important activity in the design of the control room system to ensure safe operation. The purpose of this study was to test the feasibility of methods for early formative evaluation of nuclear power plant control room systems, that is to say assessment of more general design decisions. Two methods were chosen for the assessment, scenario-based talkthrough and heuristic evaluation, and they were tested in three nuclear power plant control room system modification projects. The two methods were found useful and suitable for early formative evaluation. The combination of the methods makes it possible to take advantage of the strengths of both methods. Using guidelines focuses the evaluation on identifying typical design problems, while using a scenario-based use-focused approach allows identifying problems less typical and more unique for the specific design being evaluated. Doing the latter thoroughly result in a recourse-intensive evaluation, but this can be countered by trading some of the thoroughness for efficiency by using guidelines in the evaluation. Proposals for future work include improving the method combination by providing better support for adapting the implementation of the methods, as well as for the practical execution of the evaluation activity. Future work should also include further investigation of the method combination's usefulness, for example in other domains.

Applying Human Factors Engineering Program to the Modernization Project of NPP Control Room in accordance with U.S.NRC and KTA Regulations

Application of Human Factors Engineering (HFE) in the design and implementation of such a project is essential to ensure that the new man-machine interface outcoming from the modernization does not have any negative impacts on human performance and plant safety. This paper analyzes the applicability of the Human Factors Engineering Program in the licensing and certification of Konvoi Nucleoelectric Power Plant Control Room modernization Project using digital instrumentation and control in accordance with U.S.NRC and KRA regulations. The results of the analyses show that although regulatory bodies adopt different methodology in the process of licensing the modernization of control rooms, the engineering aspects are being developed based on the principles of engineering.

Evaluation of ARIMA Models for Human–Machine Interface State Sequence Prediction

In this paper, auto-regressive integrated moving average (ARIMA) time-series data forecast models are evaluated to ascertain their feasibility in predicting human–machine interface (HMI) state transitions, which are modeled as multivariate time-series patterns. Human–machine interface states generally include changes in their visually displayed information brought about due to both process parameter changes and user actions. This approach has wide applications in industrial controls, such as nuclear power plant control rooms and transportation industry, such as aircraft cockpits, etc., to develop non-intrusive real-time monitoring solutions for human operator situational awareness and potentially predicting human-in-the-loop error trend precursors.