Modeling and simulation approaches to developing human performance measures in nuclear industry

Human performance is a key component to the safe operation of nuclear power plants. Further, human performance is quite variable, and while some variability may be random, much of it may be attributed to factors that are difficult to assess. There is a need to identify and assess aspects of human performance that relate to plant safety and to develop measures that can be used to successfully assess human performance for purposes of research that can lead to technical basis for developing human factors review criteria

Using Information from Operating Experience to Inform Human Reliability Analysis

This paper reports on efforts being sponsored by the U.S. NRC and performed by INEEL to develop a technical basis and perform work to extract information from sources for use in HRA. The objectives of this work are to: 1) develop a method for conducting risk-informed event analysis of human performance information that stems from operating experience at nuclear power plants and for compiling and documenting the results in a structured manner; 2) provide information from these analyses for use in risk-informed and performance-based regulatory activities; 3) create methods for information extraction and a repository for this information that, likewise, support HRA methods and their applications

MODELING HUMAN RELIABILITY ANALYSIS USING MIDAS

This paper summarizes an emerging collaboration between Idaho National Laboratory and NASA Ames Research Center regarding the utilization of high-fidelity MIDAS simulations for modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (i) the estimation of human error with novel control room equipment and configurations, (ii) the investigative determination of risk significance in recreating past event scenarios involving control room operating crews, and (iii) the certification of novel staffing levels in control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of risk in next generation control rooms

Joint System Prognostics For Increased Efficiency And Risk Mitigation In Advanced Nuclear Reactor Instrumentation and Control

The science of prognostics is analogous to a doctor who, based on a set of symptoms and patient tests, assesses a probable cause, the risk to the patient, and a course of action for recovery. While traditional prognostics research has focused on the aspect of hydraulic and mechanical systems and associated failures, this project will take a joint view in focusing not only on the digital I&C aspect of reliability and risk, but also on the risks associated with the human element. Model development will not only include an approximation of the control system physical degradation but also on human performance degradation. Thus the goal of the prognostic system is to evaluate control room operation; to identify and potentially take action when performance degradation reduces plant efficiency, reliability or safety

Human Factors Issues For Multi-Modular Reactor Units

Smaller and multi-modular reactor (MMR) will be highly technologically-advanced systems allowing more system flexibility to reactors configurations (e.g., addition/deletion of reactor units). While the technical and financial advantages of systems may be numerous, MMR presents many human factors challenges that may pose vulnerability to plant safety. An important human factors challenge in MMR operation and performance is the monitoring of data from multiple plants from centralized control rooms where human operators are responsible for interpreting, assessing, and responding to different system’s states and failures (e.g., simultaneously monitoring refueling at one plant while keeping an eye on another plant’s normal operating state). Furthermore, the operational, safety, and performance requirements for MMR can seriously change current staffing models and roles, the mode in which information is displayed, procedures and training to support and guide operators, and risk analysis. For these reasons, addressing human factors concerns in MMR are essential in reducing plant risk

Lessons Learned from Dependency Usage in HERA: Implications for THERP-Related HRA Methods

Dependency occurs when the probability of success or failure on one action changes the probability of success or failure on a subsequent action. Dependency may serve as a modifier on the human error probabilities (HEPs) for successive actions in human reliability analysis (HRA) models. Discretion should be employed when determining whether or not a dependency calculation is warranted: dependency should not be assigned without strongly grounded reasons. Human reliability analysts may sometimes assign dependency in cases where it is unwarranted. This inappropriate assignment is attributed to a lack of clear guidance to encompass the range of scenarios human reliability analysts are addressing. Inappropriate assignment of dependency produces inappropriately elevated HEP values. Lessons learned about dependency usage in the Human Event Repository and Analysis (HERA) system may provide clarification and guidance for analysts using first-generation HRA methods. This paper presents the HERA approach to dependency assessment and discusses considerations for dependency usage in HRA, including the cognitive basis for dependency, direction for determining when dependency should be assessed, considerations for determining the dependency level, temporal issues to consider when assessing dependency, (e.g., considering task sequence versus overall event sequence, and dependency over long periods of time), and diagnosis and action influences on dependency

Advantages and Disadvantages of Physiological Assessment For Next Generation Control Room Design

Abstract - We propose using non-obtrusive physiological assessment (e.g., eye tracking,) to assess human information processing errors (e.g., loss of vigilance) and limitations (e.g., workload) for advanced energy systems early in the design process. This physiological approach for assessing risk will circumvent many limitations of current risk methodologies such as subjective rating (e.g., rater’s biases) and performance modeling (e.g., risk assessment is scripted and is based upon the individual modeler’s judgment). Key uses will be to evaluate (early in the design process) novel control room equipment and configurations as well as newly developed automated systems that will inevitably place a high information load on operators. The physiological risk assessment tool will allow better precision in pinpointing problematic design issues and will provide a “real-time” assessment of risk. Furthermore, this physiological approach would extend the state-of-the-art of human reliability methods from a “static” measure to more “dynamic.” This paper will discuss a broad range of the current popular online performance gauges as well as its advantages and disadvantages for use in next generation control room

Modeling and Simulation Approaches to Developing Human Performance Measures in Nuclear Industry Joint Meeting and Conference of the Institute of Electrical and Electronics Engineers (IEEE) and Human Performance / Root Cause / Trending / Operating Experien

Abstract-Human performance is a key component to the safe operation of nuclear power plants. Further, human performance is quite variable, and while some variability may be random, much of it may be attributed to factors that are difficult to assess. There is a need to identify and assess aspects of human performance that relate to plant safety and to develop measures that can be used to successfully assess human performance for purposes of research that can lead to technical basis for developing human factors review criteria

Report from the Light Water Reactor Sustainability Workshop on Advanced Instrumentation, Information, and Control Systems and Human-System Interface Technologies

The Light Water Reactor Sustainability (LWRS) Program is a research and development (R&D) program sponsored by the U.S. Department of Energy (DOE). The program is operated in close collaboration with industry R&D programs to provide the technical foundations for licensing and managing the long-term, safe, and economical operation of Nuclear Power Plants that are currently in operation. The LWRS Program focus is on longer-term and higher-risk/reward research that contributes to the national policy objectives of energy and environmental security. Advanced instruments and control (I&C) technologies are needed to support the safe and reliable production of power from nuclear energy systems during sustained periods of operation up to and beyond their expected licensed lifetime. This requires that new capabilities to achieve process control be developed and eventually implemented in existing nuclear assets. It also requires that approaches be developed and proven to achieve sustainability of I&C systems throughout the period of extended operation. The strategic objective of the LWRS Program Advanced Instrumentation, Information, and Control Systems Technology R&D pathway is to establish a technical basis for new technologies needed to achieve safety and reliability of operating nuclear assets and to implement new technologies in nuclear energy systems. This will be achieved by carrying out a program of R&D to develop scientific knowledge in the areas of: • Sensors, diagnostics, and prognostics to support characterization and prediction of the effects of aging and degradation phenomena effects on critical systems, structures, and components (SSCs) • Online monitoring of SSCs and active components, generation of information, and methods to analyze and employ online monitoring information • New methods for visualization, integration, and information use to enhance state awareness and leverage expertise to achieve safer, more readily available electricity generation. As an initial step in accomplishing this effort, the Light Water Reactor Sustainability Workshop on Advanced Instrumentation, Information, and Control Systems and Human-System Interface Technologies was held March 20–21, 2009, in Columbus, Ohio, to enable industry stakeholders and researchers in identification of the nuclear industry’s needs in the areas of future I&C technologies and corresponding technology gaps and research capabilities. Approaches for collaboration to bridge or fill the technology gaps were presented and R&D activities and priorities recommended. This report documents the presentations and discussions of the workshop and is intended to serve as a basis for the plan under development to achieve the goals of the I&C research pathway

Lessons Learned from Dependency Usage in HERA: Implications for THERP-Related HRA Methods Joint 8th Annual Conference on Human Factors and Power Plants and the 13th Annual Workshop on Human Performance / Root Cause / Trending / Operating Experience / and

Abstract-Dependency occurs when the probability of success or failure on one action changes the probability of success or failure on a subsequent action. Dependency may serve as a modifier on the human error probabilities (HEPs) for successive actions in human reliability analysis (HRA) models. Discretion should be employed when determining whether or not a dependency calculation is warranted: dependency should not be assigned without strongly grounded reasons. Human reliability analysts may sometimes assign dependency in cases where it is unwarranted. This inappropriate assignment is attributed to a lack of clear guidance to encompass the range of scenarios human reliability analysts are addressing. Inappropriate assignment of dependency produces inappropriately elevated HEP values. Lessons learned about dependency usage in the Human Event Repository and Analysis (HERA) system may provide clarification and guidance for analysts using THERP-based dependency models. This paper presents the HERA approach to dependency assessment and discusses considerations for dependency usage in HRA, including the cognitive basis for dependency, direction for determining when dependency should be assessed, considerations for determining the dependency level, temporal issues to consider when assessing dependency, (e.g., considering task sequence versus overall event sequence, and dependency over long periods of time), and diagnosis and action influences on dependency