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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification are discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A Feasibility Study on the Integration of Human Performance Data From Diverse Sources Based on the Complexity of a Proceduralized Task

Securing the safety of socio-technical systems including nuclear facilities is the upmost goal to ensure their sustainability because historical records demonstrate that the performance degradation of human operators (e.g., human errors) is one of the crucial contributors to the occurrence of unexpected events resulting in extensive casualties and financial losses. This implies that the collection of human performance data in diverse conditions with which they could be faced during the operation of nuclear facilities. As this collection requires significant resources, it is necessary to resolve how to accomplish it with limited resources. To address this challenge, as suggested in the SHEEP framework, it is indispensable to extract valuable insights after integrating various kinds of human performance data obtained from different sources. However, a practical method to soundly integrate them seems to be still incomplete. Accordingly, the applicability of TACOM (Task Complexity) measure is investigated as a tool to identify useful information based on the integration of human performance data observed from different simulation conditions. As a result, it is expected that the TACOM measure would play an important role in addressing the technical challenge in securing human performance data.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation andits impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after exposure to stress, which may be expected based in part on rodent responses found afterexposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperilmission accomplishment. If mission-relevant animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗
NASA NTRSDate not supplied

Planned Investigations to Address Acute Central Nervous System Effects of Space Radiation Exposure with Human Performance Data

This work intends to generate evidence of acute, incremental human performance decrement similar to that due to space radiation and its impacts on the brain, to accompany ongoing human performance modeling work. The planned work will explore the boundaries of human behavioral and performance decrement after expo-sure to stress, which may be expected based in part on rodent responses found after exposure to ionizing radiation. The collection of evidence via simulation studies can characterize real human errors toward determining what stress levels lead to significantly-low levels of performance (below permissible outcome limits) which would imperil mission accomplishment. If mission-relevant yet animal-study-linked tasks are used, human and animal performance levels may be aligned to enable quantitative assignment of permissible exposure limits based on animal exposure studies. Ultimately, a transfer function between the performances of exposed rodents and humans under stress can be developed using shared impairment mechanisms.

human performance↗
NASA NTRSDate not supplied

Leveraging Human Performance Data to Change the Narrative that People are the Safety Problem

The study of errors and failure has a long and productive history in the behavioral sciences. By studying how systems fail, we rule out various mechanisms for how those systems might work, thereby refining our theories of how they actually work. Human performance, however, includes more than errors; human performance comprises both failures and successes. A systematic bias to collect and analyze data only on error affects the decisions we make as a community by promoting the narrative that “people are the safety problem.” This narrative manifests in both obvious and subtle ways in the design of systems intended for human use. When the only safety data that are available are about human failure, then “data-driven” designs can only consider that humans fail. Changing this narrative will depend on new data and new ways to examine data – specifically, data on the processes by which human create and contribute to safety. An alternate narrative is that people represent a primary source of safety, through their capability to anticipate, monitor for, respond to, and learn from expected and unexpected change. This presentation will describe research efforts to expand the range of safety-relevant events to include not just rare safety failures but frequent safety successes. These efforts include use of data from both operations and simulations to develop methods and metrics for learning from structured observation, self-report, and system data.

Jon Holbrook↗
NASA NTRS2015

Human Factors and Habitability Challenges for Mars Missions

As NASA is planning to send humans deeper into space than ever before, adequate crew health and performance will be critical for mission success. Within the NASA Human Research Program (HRP), the Space Human Factors and Habitability (SHFH) team is responsible for characterizing the risks associated with human capabilities and limitations with respect to long-duration spaceflight, and for providing mitigations (e.g., guidelines, technologies, and tools) to promote safe, reliable and productive missions. SHFH research includes three domains: Advanced Environmental Health (AEH), Advanced Food Technology (AFT), and Space Human Factors Engineering (SHFE). The AEH portfolio focuses on understanding the risk of microbial contamination of the spacecraft and on the development of standards for exposure to potential toxins such as chemicals, bacteria, fungus, and lunar/Martian dust. The two risks that the environmental health project focuses on are adverse health effects due to changes in host-microbe interactions, and risks associated with exposure to dust in planetary surface habitats. This portfolio also proposes countermeasures to these risks by making recommendations that relate to requirements for environmental quality, foods, and crew health on spacecraft and space missions. The AFT portfolio focuses on reducing the mass, volume, and waste of the entire integrated food system to be used in exploration missions, and investigating processing methods to extend the shelf life of food items up to five years, while assuring that exploration crews will have nutritious and palatable foods. The portfolio also delivers improvements in both the food itself and the technologies for storing and preparing it. SHFE sponsors research to establish human factors and habitability standards and guidelines in five risk areas, and provides improved design concepts for advanced crew interfaces and habitability systems. These risk areas include: Incompatible vehicle/habitat design, inadequate human-computer interaction, inadequate critical task design, inadequate human-automation/robotic interaction, and performance errors due to training deficiencies. To address the identified research gaps within each risk, SHFH's research plan includes studies in the laboratory, in analogs, and on International Space Station (ISS). In addition to establishing and maintaining the risk-based research portfolio, SHFH is also implementing a qualitative approach to determine how we at NASA evaluate human performance. Via interviews with experts, such as trainers, flight controllers, and flight surgeons, we are collecting the metrics by which they assess human performance, evidence of performance issues, and potential or actual consequences. The Human Performance Data Project will determine what human performance data have been collected in the past at NASA, and what data should be collected in the future in order to complete our knowledgebase and reduce risks related to human factors and habitability.

Whitmore, Mihriban↗
DOE OSTI2017

Utilizing the SACADA system to collect simulator training data to inform human reliability analyses - 169

Lack of appropriate human performance data for the development of human reliability analysis (HRA) methods has been identified as a key issue contributing to the method-to-method variability among the HRA methods. The United States Nuclear Regulatory Commission (NRC) worked with domain experts to develop the Scenario Authoring, Characterization, and Debriefing Application (SACADA) system to collect nuclear power plants' licensed operator simulator training and examination data to inform HRA. In the past two decades, significant improvements in understanding and modelling human performance in HRA have affected the perspectives of the types of data to be collected for HRA. A significant change is that human performance is strongly dependent on the context of the tasks to be performed. To incorporate this understanding, the SACADA data taxonomy collects the context and actual performance information of the training objective elements (TOEs) in nuclear plant operator simulator training. This provides a framework consistent with HRA to use context to estimate human error probabilities. It is recognized that measuring crew performance is equally important as improving operator training. SACADA is designed to support the nuclear trainers in capturing this important information that is used to identify training weaknesses and drive continuous improvement. This paper discusses the SACADA taxonomy, the SACADA system's functions, and the supporting software design to enable the SACADA system to be practically implemented in the nuclear power plants' operator simulator training program to collect data for tracking operator performance and HRA analysis. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2004

EVA Performance Prediction

Astronaut physical performance capabilities in micro gravity EV A or on planetary surfaces when encumbered by a life support suit and debilitated by a long exposure to micro gravity will be less than unencumbered pre flight capabilities. The big question addressed by human factors engineers is: what can the astronaut be expected to do on EVA or when we arrive at a planetary surface? A second question is: what aids to performance will be needed to enhance the human physical capability? These questions are important for a number of reasons. First it is necessary to carry out accurate planning of human physical demands to ensure that time and energy critical tasks can be carried out with confidence. Second it is important that the crew members (and their ground or planetary base monitors) have a realistic picture of their own capabilities, as excessive fatigue can lead to catastrophic failure. Third it is important to design appropriate equipment to enhance human sensory capabilities, locomotion, materials handling and manipulation. The evidence from physiological research points to musculoskeletal, cardiovascular and neurovestibular degradation during long duration exposure to micro gravity . The evidence from the biomechanics laboratory (and the Neutral Buoyancy Laboratory) points to a reduction in range of motion, strength and stamina when encumbered by a pressurized suit. The evidence from a long history of EVAs is that crewmembers are indeed restricted in their physical capabilities. There is a wealth of evidence in the literature on the causes and effects of degraded human performance in the laboratory, in sports and athletics, in industry and in other physically demanding jobs. One approach to this challenge is through biomechanical and performance modeling. Such models must be based on thorough task analysis, reliable human performance data from controlled studies, and functional extrapolations validated in analog contexts. The task analyses currently carried out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

Peacock, Brian↗
NASA NTRS2012

Model for Predicting the Performance of Planetary Suit Hip Bearing Designs

Designing a space suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. During the development period of the suit numerous design iterations need to occur before the hardware meets human performance requirements. Using computer models early in the design phase of hardware development is advantageous, by allowing virtual prototyping to take place. A virtual design environment allows designers to think creatively, exhaust design possibilities, and study design impacts on suit and human performance. A model of the rigid components of the Mark III Technology Demonstrator Suit (planetary-type space suit) and a human manikin were created and tested in a virtual environment. The performance of the Mark III hip bearing model was first developed and evaluated virtually by comparing the differences in mobility performance between the nominal bearing configurations and modified bearing configurations. Suited human performance was then simulated with the model and compared to actual suited human performance data using the same bearing configurations. The Mark III hip bearing model was able to visually represent complex bearing rotations and the theoretical volumetric ranges of motion in three dimensions. The model was also able to predict suited human hip flexion and abduction maximums to within 10% of the actual suited human subject data, except for one modified bearing condition in hip flexion which was off by 24%. Differences between the model predictions and the human subject performance data were attributed to the lack of joint moment limits in the model, human subject fitting issues, and the limited suit experience of some of the subjects. The results demonstrate that modeling space suit rigid segments is a feasible design tool for evaluating and optimizing suited human performance. Keywords: space suit, design, modeling, performance

Cowley, Matthew S.↗
DOE OSTI2022

Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)

Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2009

Human Factors Assessment of Vibration Effects on Visual Performance During Launch

The Human Factors Assessment of Vibration Effects on Visual Performance During Launch (Visual Performance) investigation will determine visual performance limits during operational vibration and g-loads on the Space Shuttle, specifically through the determination of minimum readable font size during ascent using planned Orion display formats. Research Summary: The aim of the Human Factors Assessment of Vibration Effects on Visual Performance during Launch (Visual Performance) investigation is to provide supplementary data to that collected by the Thrust Oscillation Seat Detailed Technical Objective (DTO) 695 (Crew Seat DTO) which will measure seat acceleration and vibration from one flight deck and two middeck seats during ascent. While the Crew Seat DTO data alone are important in terms of providing a measure of vibration and g-loading, human performance data are required to fully interpret the operational consequences of the vibration values collected during Space Shuttle ascent. During launch, crewmembers will be requested to view placards with varying font sizes and indicate the minimum readable size. In combination with the Crew Seat DTO, the Visual Performance investigation will: Provide flight-validated evidence that will be used to establish vibration limits for visual performance during combined vibration and linear g-loading. o Provide flight data as inputs to ongoing ground-based simulations, which will further validate crew visual performance under vibration loading in a controlled environment. o Provide vibration and performance metrics to help validate procedures for ground tests and analyses of seats, suits, displays and controls, and human-in-the-loop performance.

Kritina Holden↗
DOE OSTI2021

An Experimental Analysis on the CNS Simulator Comparing Human Performance between Operators and Students

This study, as a previous study of the SHEEP project, aims to identify differences in human performance data through experiments with students and operators using CNS (Compact Nuclear Simulator). To achieve this goal, this experiment seeks to analyze the correlation of measured human performance between students and operators through a randomized factorial experiment design. Five human performances are measured. In addition, several scenarios and related procedures have been developed for the CNS experiments.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

How Do Different Knowledge Frameworks Help Us Learn From Aviation Line Observations?

Human performance includes actions that increase safety, as well as actions that can reduce safety. Ensuring safety in complex dynamic operations like commercial aviation depends on the ability to institute appropriate responses based on what is learned from flightcrew performance and the contexts in which it occurs. To do this systemically at the organization level requires collecting data on flightcrew performance, developing effective approaches to analyzing those data, and understanding how to translate what has been learned into policies, procedures, and practice. Systematic observation of front-line operators is a vital source of human performance data. Much has been learned from such observations, including methodological principles. Most observations have been based on a framework focused on managing safety challenges and the ensuing unsafe events. A complementary perspective focuses on flexibility and actions that promote continued safe and effective operation. We consider lessons learned about observational methods from an established framework focused on undesired actions and how these might be extended for a framework focused on desired actions.

safety↗
DOE OSTI2017

Design and implementation of HuREX analysis supporting interface - 171

Human error is recognized as one of the main causes to affect to the socio-technical system including nuclear power plant. Therefore, reducing human error through human reliability analysis (HRA) is a critical issue. Moreover, sufficient and reliable human performance data collection is a prerequisite for ensuring the safety of nuclear power plants. Korea Atomic Energy Research Institute developed the HuREX (Human Reliability data Extraction) framework to collect and analyze the responses of human operators from simulator training records of nuclear power plant. Thus, the development and computer software interfaces of the database are essential to efficiently support human reliability analysis. In this study, OPERA database was developed in accordance with the following process. First, the essential data required for the HRA analysis (e.g., plant data, procedures, system and equipment info, operating crews, results of simulator experiments, and so forth) was stored in the database. In addition, standardized procedures and related items were stored in the database to support HRA quantification. A data structure was developed to store crew responses conducted by operators to cope with an emergency situation during simulator experiments. In addition, various interfaces that escalate efficiency of the HuREX applications were developed. The HuREX analysis support interface was developed with HuREX Video Analyzer for observation of simulator collection data (e.g., audio-visual records, plant parameters, operator's action logs) and HuREX Data Analyzer for analysis of operator's conducted task. By using the OPERA database and HuREX analysis support interface developed through this research, maximizing the efficiency of human reliability analysis based on simulator training data. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1985

Rule-based analysis of pilot decisions

The application of the rule identification technique to the analysis of human performance data is proposed. The relation between the language and identifiable consistencies is discussed. The advantages of production system models for the description of complex human behavior are studied. The use of a Monte Carlo significance testing procedure to assure the validity of the rule identification is examined. An example of the rule-based analysis of Palmer's (1983) data is presented.

Lewis, C. M.↗
NASA NTRS1985

Issues in rule identification and logical induction

The relationship between language and empirical fitting of data is discussed. The production system is presented as an appropriate description of human behavior in Man-Machine systems. Issues arising in the identification of rules from data are examined. Rules identified through logical generalization are shown to be equivocal. Difficulties arising from the use of logic-based procedures with human performance data containing errors are explored. Problems relating to rule sets which are not disjoint are discussed and a solution presented. Significant testing issues are raised for rule identification and a procedure based on controlling contrivedness is presented. A synthesis of data and knowledge-based approaches is suggested as a remedy to many of the difficulties discussed.

Lewis, C. M.↗
DOE OSTI2019

Development of a Fleet-Level Human Factors Engineering Program to Support the Digital Modernization of Multiple Turbine Control Systems

A number of years ago, Duke Energy and the United States (U.S.) Department of Energy (DOE) entered into a collaboration to support Duke’s digital upgrade activities for the main control rooms at three of their commercial nuclear power stations. The collaboration specifically focused on the human factors engineering (HFE) aspects of Duke’s plans to upgrade the legacy turbine control systems (TCS) at their Brunswick, Robinson, and Harris plants. This TSC upgrade involved installing a common digital control system (DCS), or distributed instrumentation and control (I&C) system platform, which multiple digital plant control systems can be integrated onto as the control rooms are modernized over time. Given the breadth and depth of the scope of this upgrade, DOE researchers at Idaho National Laboratory (INL) with expertise in human factors collaborated with Duke throughout the entire HFE life cycle to help ensure the upgrade was performed in a manner consistent with regulatory human factors review criteria, such as the U.S. Nuclear Regulatory Commission’s (NRC) Human Factors Engineering Program Review Model (NUREG 0711, 2012). This paper describes the HFE researchers performed through the early and middle phases of these TCS upgrades. Specific HFE activities include: 1) the development of a human factors program management plan, 2) performing an operational experience review, 3) evaluating the design human system interface while it was still in the early stages of development, and 4) developing a framework to help map these HFE activities to NUREG-0711 to help understand and catalog the value of different types and phases of human performance data collection. These four HFE activities are described in more detail below.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1991

Portable computers as companions in space

The paper describes a Space Shuttle Program payload that uses a Macintosh portable computer to gather human performance data for a cursor control device experiment and to test prototype software applications for the Space Station Freedom (SSF). The payload is the first phase of a NASA research and development project to operationally test human-computer interface requirements and crew support applications for an advanced portable computer for the SSF.

Microgravity↗