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Workload Associated with Nuclear Power Plant Main Control Room Tasks
Abstract
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.
... The participants had a greater workload in the identification task realm, not to mention that the mental demand was higher in those tasks. Meanwhile, according to NASA-TLX, the frustration scale and the total workload was at the highest point (Reinerman-Jones et al. 2015). ...
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.
Research into human-system interaction, specifically focusing on workload, has intensified in the nuclear domain. Past research on workload in the Nuclear Power Plant (NPP) domain has attempted to use both subjective and physiological measures of workload, yet the sensitivity of the workload measures used in past experiments is unknown. This initial experiment will guide future research in the NPP domain by identifying whether the NASA-TLX, EEG, and ECG are sensitive to detecting workload changes in common NPP Main Control Room (MCR) tasks. Results suggest the three workload measures did not reveal expected differences between task types in the NPP MCR context.
Diagnosis and monitoring are the major tasks of an operator in main control room of nuclear power plants (NPPs). The operator’s mental workload influences his/her performance, and furthermore, affects the system safety and operations. This study investigated the operator’s mental workload and work performance of the NPP in Taiwan. An experiment including primary and secondary tasks was designed to simulate the reactor shutdown procedure of the fourth nuclear power plant (FNPP). The performance of the secondary tasks (error rate), subjective mental workload (NASA Task Load Index, NASA-TLX) as well as seven physiological indices were assessed and measured. The group method of data handling (GMDH) was applied to integrate these physiological indices to develop a work performance predictive model. The validity of the proposed model is very well with R2 = 0.84 and its prediction capability is high (95% confidence interval). The proposed model is expected to provide control room operators a reference value of their work performance by giving physiological indices. Besides NPPs, the proposed model can be applied to many other fields, e.g. aviation, air transportation control, driving and radar vigilance, etc.
10 undergraduates performed a paced mental task at 3 levels of difficulty, while time-locked recordings of pupil diameter, heart rate, and skin resistance were made. A similar pattern of sympathetic-like increase was found in the 3 autonomic functions during information intake and processing, followed by a decrease during the report phase. The peak response in each measure was ordered as a function of task difficulty. (15 ref.)
Cardiac and electrodermal measures are regarded as indicators of user strain during computer work, not taking the possible influence of finger and hand movements on these measures into account. For the evaluation of such effects, motor demands and mental load were both varied as independent factors in two experiments. As a motor task, subjects had to produce compensatory keystrokes at different speed levels to keep a moving mark within a target area on the computer screen. Mental load was varied in experiment 1 by manipulation of keystroke synchronization accuracy, and in experiment 2 by manipulation of memory load. Physiological measures were affected by motor activity only at a very high typing speed. At lower levels of motor activity physiological effects were dependent exclusively on mental load. Frequency of skin conductance responses was the most sensitive indicator of the emotional consequences of mental load and mean heart period reflected its attentional aspects. The study supports the assumption that physiological effects of motor activity can be neglected during typical computer tasks, demanding keystrokes at intervals of 300 ms or longer.
Many of today’s most complicated systems are human-machine systems that involve extensive advanced technology and a team of highly trained operators. As these human-machine systems are so complex, it is important to understand the factors that influence operator performance, operator state (e.g., overloaded, underload, stress) and the types of errors that operators make. Thus, it is desirable to develop an experimental methodology for studying complex systems that involve team operations. This paper looks at Nuclear Power Plant (NPP) operations as a test case for building this methodology. The methodology will reference some aspects/details specific to NPPs, but the general principles are intended to extend to any complex system that involves team operations.
Automating tasks alleviates operator resources to be delegated to other demands, but the cost is often situation awareness. In contrast, complete manual control of a system opens the door for greater human error. Therefore, an ideal situation would require the development of an adaptive system in which automation can be triggered based on performance of a particular task, time spent on the task, or perhaps physiological response. The latter pertains to the goal for this particular study. Electroencephalogram (EEG), electrocardiogram (ECG), and eye tracking measures were recorded during six multi-tasking scenarios to assess if any one single measure is best suited for future implementation as an automation invocation. EEG showed the greatest potential for that purpose. Copyright 2010 by Human Factors and Ergonomics Society, Inc. All rights reserved.
This Nuclear Regulatory Commission (NRC) sponsored study has identified human-performance issues in new and advanced nuclear power plants. To identify the issues, current industry developments and trends were evaluated in the areas of reactor technology, instrumentation and control technology, human-system integration technology, and human factors engineering (HFE) methods and tools. The issues were organized into seven high-level HFE topic areas: Role of Personnel and Automation, Staffing and Training, Normal Operations Management, Disturbance and Emergency Management, Maintenance and Change Management, Plant Design and Construction, and HFE Methods and Tools. The issues where then prioritized into four categories using a 'Phenomena Identification and Ranking Table' methodology based on evaluations provided by 14 independent subject matter experts. The subject matter experts were knowledgeable in a variety of disciplines. Vendors, utilities, research organizations and regulators all participated. Twenty issues were categorized into the top priority category. This Brookhaven National Laboratory (BNL) technical report provides the detailed methodology, issue analysis, and results. A summary of the results of this study can be found in NUREG/CR-6947. The research performed for this project has identified a large number of human-performance issues for new control stations and new nuclear power plant designs. The information gathered in this project can serve as input to the development of a long-term strategy and plan for addressing human performance in these areas through regulatory research. Addressing human-performance issues will provide the technical basis from which regulatory review guidance can be developed to meet these challenges. The availability of this review guidance will help set clear expectations for how the NRC staff will evaluate new designs, reduce regulatory uncertainty, and provide a well-defined path to new nuclear power plant licensing.
Piloting an aircraft is a complex task that places demands on several aspects of a pilot's cognitive capabilities. Because of the multifaceted nature of flying, several measures are required to identify the effects of these demands on the pilot. Several psychophysiological measures were recorded so that a wider understanding of the effects of these demands could be achieved. Heart rate, heart rate variability, eye blinks, electrodermal activity, topographically recorded electrical brain activity, and subjective estimates of mental workload were recorded. Ten pilots flew an approximately 90-min scenario containing both visual and instrument flight conditions. To determine the reliability of the psychophysiological measures, the pilots flew the same scenario twice. The responses during the 2 flights were essentially identical. Cardiac and electrodermal measures were highly correlated and exhibited changes in response to the various demands of the flights. Heart rate variability was less sensitive than heart rate. Alpha and delta bands of the brain activity showed significant changes to the varying demands of the scenarios. Blink rates decreased during the more highly visually demanding segments of the flights.
NASA-TLX is a multi-dimensional scale designed to obtain workload estimates from one or more operators while they are performing a task or immediately afterwards. The years of research that preceded subscale selection and the weighted averaging approach resulted in a tool that has proven to be reasonably easy to use and reliably sensitive to experimentally important manipulations over the past 20 years. Its use has spread far beyond its original application (aviation), focus (crew complement), and language (English). This survey of 550 studies in which NASA-TLX was used or reviewed was undertaken to provide a resource for a new generation of users. The goal was to summarize the environments in which it has been applied, the types of activities the raters performed, other variables that were measured that did (or did not) covary, methodological issues, and lessons learned
This volume presents thoughts on measuring team performance written by experts currently working with teams in fields such as training, evaluation, and process consultation. The chapters are: (1) "An Overview of Team Performance Measurement" (Michael T. Brannick and Carolyn Prince); (2) "A Conceptual Framework for Teamwork Measurement" (Terry L. Dickinson and Robert M. McIntyre); (3) "A Framework for Developing Team Performance Measures in Training" (Janis A. Cannon-Bowers and Eduardo Salas); (4) "Conceptual Development and Empirical Evaluation of Measures of Shared Mental Models as Indicators of Team Effectiveness" (Kurt Kraiger and Lucy H. Wenzel); (5) "Team Workload: Its Meaning and Measurement" (Clint A. Bowers, Curt C. Braun, and Ben B. Morgan, Jr.); (6) "Team Decision-Making Accuracy under Difficult Conditions: Construct Validation of Potential Manipulations Using TIDE [squared] Simulation" (John R. Hollenbeck, Douglas J. Sego, Daniel R. Ilgen, Debra A. Major, Jennifer Hedlund, and Jean Phillips"; (7) "Team Performance Measurement in Distributed Environments: The TARGETs Methodology" (Daniel J. Dwyer, Jennifer E. Fowlkes, Randall L. Oser, Eduardo Salas, and Norman E. Lane); (8) "The Measurement of Team Performance with a Standardized Survey" (Glenn Hallam and David Campbell); (9) "Assessing Processes within and between Organizational Teams: A Nuclear Power Plant Example" (John E. Mathieu and David V. Day); (10) "Task and Aggregation Issues in the Analysis and Assessment of Team Performance" (Paul Tesluk, John E. Mathieu, Stephen J. Zaccaro, and Michelle Marks); (11) "Behind the Scenes: Fieldtesting a Measure of Effectiveness for Theater Teams" (Judith L. Komaki); (12) "Assessment of Nuclear Power Plant Crew Performance Variability" (Jody L. Toquam, Jennifer L. Macaulay, Curtis D. Westra, Yushi Fujita, and Susan E. Murphy); (13) "The Measurement of Team Process Behaviors in the Cockpit: Lessons Learned" (Ashley Prince, Michael T. Brannick, Carolyn Prince, and Eduardo Salas); (14) "Performance Measurement Tools for Enhancing Team Decision-Making Training" (Joan Hall Johnston, Kimberly A. Smith-Jentsch, and Janis A. Cannon-Bowers); and (15) "Principles for Measuring Teamwork: A Summary and Look toward the Future" (David P. Baker and Eduardo Salas). Each chapter contains references. (Contains 25 figures and 36 tables.) (SLD)
For al main control room (MCR) in advanced nuclear power plants (ANPPs), a team of three operators has been adopted to enhance the safety of all the operating conditions, including general, abnormal, and emergent. Therefore, to evaluate the workload of team operators in the MCR of NPPs would be one valuable issues in human factor engineering (HFE) research. The NASA Task Load Index (NASA-TLX) has been selected to measure the workload of operators in past studies. Some studies, however, indicated that the workload measured by the NASA-TLX did not have significant correlation with team performance. That is, assessing team workload using NASA-TLX alone may be a problem, and its sensitivity needs to be verified. In this study, a measurement called Team Workload Assessment (TWA) was developed to evaluate the team workload by characteristics of teamwork. The important characteristics of teamwork, including coordination, communication, support and leadership, and time sharing were developed in the questionnaire. Confirmatory factor analysis and Cronbach's α coefficient were used to examine the validity and reliability of the questionnaire. Finally, the team workload scores of the TWA were compared with the team workload scores of the NASA-TLX and the task performance was obtained from an experiment designed to verify the suitability of the TWA. As a result, it was found that the team workload scores of the TWA are more sensitive to task performance than are those of the NASA-TLX. Therefore, the TWA is available to measure the team workload in the MCR of NPPs. © 2011 Wiley Periodicals, Inc.
An accurate measure of mental workload in human operators is a critical element of monitoring and adaptive aiding systems that are designed to improve the efficiency and safety of human-machine systems during critical tasks. Functional near infrared (fNIR) spectroscopy is a field-deployable non-invasive optical brain monitoring technology that provides a measure of cerebral hemodynamics within the prefrontal cortex in response to sensory, motor, or cognitive activation. In this paper, we provide evidence from two studies that fNIR can be used in ecologically valid environments to assess the: 1) mental workload of operators performing standardized (n-back) and complex cognitive tasks (air traffic control--ATC), and 2) development of expertise during practice of complex cognitive and visuomotor tasks (piloting unmanned air vehicles--UAV). Results indicate that fNIR measures are sensitive to mental task load and practice level, and provide evidence of the fNIR deployment in the field for its ability to monitor hemodynamic changes that are associated with relative cognitive workload changes of operators. The methods reported here provide guidance for the development of strategic requirements necessary for the design of complex human-machine interface systems and assist with assessments of human operator performance criteria.
Instantaneous self-assessment (ISA) is a technique that has been developed as a measure of workload to provide immediate subjective ratings of work demands during the performance of primary work tasks such as air traffic control. This paper reports a study that compared the results of ISA with those gathered from other established workload evaluation techniques; subjective ratings collected at the end of the task, mean heart rate and heart rate variability, and error in the primary task of tracking. ISA ratings were found to be correlated significantly with the post-task ratings of workload, heart rate variability, and task performance. Generally each of the techniques was sensitive to variations in task difficulty. However, performance on the primary tracking task was found to be poorer during periods when ISA responses were required, regardless of whether they were spoken or manual responses. This finding suggests that the usefulness of the technique is limited in comparison to less intrusive measures of workload.
Human Mental Workload
- N Meshkati
- P Hancock
Investigating the universality and comprehensive ability of measures to assess the state of workload
- J I Abich