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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2020

INL Human Performance Improvement Guide, GDE-863

Guidance on Integrating Human Performance Improvement including guidance on Developing Area Specific Implementation Plans, Tool Usage, and Building the Capacity for Resiliency aka Failing Safely.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Integrating Mindfulness with Human Performance in High Complexity Environments - 19498

This paper includes a survey of both scientific and technical literature studies of mindfulness interventions in a variety of industries and populations and proposes potential applications in complex nuclear waste operations. Mindfulness training techniques have been utilized in various forms for decades in high consequence work in both public and private enterprise. The traditional safety nomenclature has simply used different words to describe many of the same concepts that mindfulness practice addresses. Historically, human performance improvement (HPI) has focused on task, mission and error-likely conditions. These safety programs recognize that human behavior is the source of most errors and focus on identification of specific error precursors (mind not on task, incorrect mental picture, etc.). Workers in nuclear and related industries have been trained to recognize these error precursors but have received little training on what to do about them. The techniques of mindfulness align well with HPI programs currently utilized in commercial and government nuclear operations. Indeed, Chapter 5 of the Department of Energy Human Performance Improvement Handbook (DOE-HDBK-1028-2009) includes a discussion of mindfulness with respect to human performance. Mindfulness training supplements current performance improvement efforts by giving workers the tools to not just recognize error-likely conditions within themselves, but also gives them methods to mitigate them. The mindfulness practices presented here focus on self-awareness rather than task-awareness. Workers can apply these techniques in all aspects of their lives which in turn addresses many of the distractions previously identified as error precursors (stress at home or at work, physical discomforts, mind not on task, etc.). The application of mindfulness techniques through integration with established Integrated Safety Management Systems (ISMS) has the potential to improve the safe performance of nuclear waste operations and increase the breadth of organizational safety culture. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Comparison of Human Performance between Operators and Students Using Rancor Microworld Simulator: A Preliminary Result

This paper describes an experiment using the Rancor Microworld simulator to probe into differences in human performance between students and actual operators. Six human performance measures – 1) time, 2) error, 3) workload, 4) situational awareness, 5) attention patterns, and 6) number of manipulations – are measured from experiments. The experiment has been conducted for 11 operators and 20 students so far. More experiments and analyses will be continued. Further experimental studies using Rancor Microworld are expected to be able to collect additional data that may be missing from full-scope studies and contribute to items that can support human reliability data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Savannah River Remediation Liquid Waste Operations Making the Workplace Safer - Lean and Human Performance Improvement Initiatives - 17244

The Savannah River Site, a U.S. Department of Energy facility, contracted Savannah River Remediation (SRR) to manage its liquid waste project, which is a unique, high hazard nuclear waste treatment and disposal facility consisting of 51, one million gallon underground waste tanks, a solvent extraction processing unit, a vitrification facility for the highest radioactive waste, and a grout solidification and disposal facility for a decontaminated salt solution. Our Project mission is to treat the nuclear waste and close the associated storage and treatment facilities, of which, 8 of the 51 tanks have been closed to date. Over the past three years, SRR implemented a Lean Business Management System to address site inefficiencies, aging infrastructure concerns and budget constraints. The Lean philosophy started with the work of W. Edwards Deming and his contemporaries. In more recent years the process has matured in the Toyota Production System and migrated into fields as diverse as services industries, health-care, and now the DOE complex. Like safety, continuous improvement is a fundamental core business value that starts at the top. The Lean Business System, led by our executive management team, drives quality, production and waste elimination by focusing on People using a structured Process that allows the workforce to identify and fix problems in their workplace. Many inefficiencies and quality related issues start with the desire to make systems fail-safe without defining the core requirements for which that process or program was created. This leads to added complexity and latent or inherent human performance issues embedded within our processes. While Lean can't fix all problems, a combination of strong nuclear safety culture, robust conduct of operations, active human performance improvement process, and a business practice of continuously looking for improvements leads to excellence across our industry and creates a culture that is worthy of promoting. Without strong management, our systems fail because no one sponsors or encourages those attributes we covet. Leadership starts at the top with our customer defining what provides 'value' to them, and filters down through to the organization and ultimately the workforce in day to day conduct of operations. It is imperative that our customer drives these desirable ideals through recognition and contractual requirements to encourage and support those behavioral traits that are critical to our ongoing success.This paper focuses on how the Lean Business Management System supports those attributes that we value: a strong nuclear safety culture; disciplined conduct of operations; and a culture of robust human performance and continuous improvement. These attributes in our daily work environment propel a safer, more consistent, more efficient workplace. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

An Experimental Investigation of Human Performance Differences Depending on Simulator Complexity

As a different approach to collect human reliability analysis (HRA) data compared to the full-scope simulator studies, Idaho National Laboratory (INL) has attempted to collect HRA data based on Simplified Human Error Experimental Program (SHEEP), which uses a simplified simulator and student participants. To date, INL has considered the SHEEP approach using simplified simulators such as Rancor Microworld and Compact Nuclear Simulator to complement – not replace – full-scope studies as well as to mainly collect HRA data for estimating nominal/basic human error probabilities (HEPs) needed in the HRA quantification process. This study is a part of the project aiming to suggest how to support full-scope data collection studies based on SHEEP. This paper first introduces major tasks within the SHEEP framework. Then, as one of the major tasks, why and how we have planned to experimentally investigate human performance differences depending on simulator complexity are mainly introduced in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

EFCOG Human Performance Improvement Task Group: Task 20-2, Asking Better Error Precursor Questions for Effective Job Planning, Pre-Job Briefs, and Event Investigations

The second principle of human performance states: “error-likely situations are predictable, manageable, and preventable.” An error-likely situation comes into play when task-related factors exceed the capabilities of the individual, creating a mismatch at the point when the individual is “touching” either the physical or the paper plant. The simple presence of adverse conditions cannot be error-likely unless a specific action is to occur within that set of adverse conditions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

A Multi-Methods Approach to HRA and Human Performance Modeling: A Field Assessment

The Advanced Test Reactor (ATR) is a research reactor at the Idaho National Laboratory is primarily designed and used to test materials to be used in other, larger-scale and prototype reactors. The reactor offers various specialized systems and allows certain experiments to be run at their own temperature and pressure. The ATR Canal temporarily stores completed experiments and used fuel. It also has facilities to conduct underwater operations such as experiment examination or removal. In reviewing the ATR safety basis, a number of concerns were identified involving the ATR canal. A brief study identified ergonomic issues involving the manual handling of fuel elements in the canal that may increase the probability of human error and possible unwanted acute physical outcomes to the operator. In response to this concern, that refined the previous HRA scoping analysis by determining the probability of the inadvertent exposure of a fuel element to the air during fuel movement and inspection was conducted. The HRA analysis employed the SPAR-H method and was supplemented by information gained from a detailed analysis of the fuel inspection and transfer tasks. This latter analysis included ergonomics, work cycles, task duration, and workload imposed by tool and workplace characteristics, personal protective clothing, and operational practices that have the potential to increase physical and mental workload. Part of this analysis consisted of NASA-TLX analyses, combined with operational sequence analysis, computational human performance analysis (CHPA), and 3D graphical modeling to determine task failures and precursors to such failures that have safety implications. Experience in applying multiple analysis techniques in support of HRA methods is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Efforts to enhance reproducibility in a human performance research project

Background: Ensuring the validity of results from funded programs is a critical concern for agencies that sponsor biological research. In recent years, the open science movement has sought to promote reproducibility by encouraging sharing not only of finished manuscripts but also of data and code supporting their findings. While these innovations have lent support to third-party efforts to replicate calculations underlying key results in the scientific literature, fields of inquiry where privacy considerations or other sensitivities preclude the broad distribution of raw data or analysis may require a more targeted approach to promote the quality of research output. Methods: We describe efforts oriented toward this goal that were implemented in one human performance research program, Measuring Biological Aptitude, organized by the Defense Advanced Research Project Agency's Biological Technologies Office. Our team implemented a four-pronged independent verification and validation (IV&V) strategy including 1) a centralized data storage and exchange platform, 2) quality assurance and quality control (QA/QC) of data collection, 3) test and evaluation of performer models, and 4) an archival software and data repository. Results: Our IV&V plan was carried out with assistance from both the funding agency and participating teams of researchers. QA/QC of data acquisition aided in process improvement and the flagging of experimental errors. Holdout validation set tests provided an independent gauge of model performance. Conclusions: In circumstances that do not support a fully open approach to scientific criticism, standing up independent teams to cross-check and validate the results generated by primary investigators can be an important tool to promote reproducibility of results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance

Picking foraminifera from sediment samples is an essential, but repetitive and low-reward task that is well-suited for automation. The first step toward building a picking robot is the development of an automated identification system. We use machine learning techniques to train convolutional neural networks (CNNs) to identify six species of extant planktic foraminifera that are widely used by paleoceanographers, and to distinguish the six species from other taxa. We employ CNNs that were previously built and trained for image classification. Foraminiferal training and identification use reflected light microscope digital images taken at 16 different illumination angles using a light-emitting diode (LED) ring. Overall machine accuracy, as a combination of precision and recall, is better than 80% even with limited training. We compare machine performance to that of human pickers (six experts and five novices) by tasking each with the identification of 540 specimens based on images. Experts achieved comparable precision but poorer recall relative to the machine, with an average accuracy of 63%. Novices scored lower than experts on both precision and recall, for an overall accuracy of 53%. The machine achieved fairly uniform performance across the six species, while participants' scores were strongly species-dependent, commensurate with their past experience and expertise. The machine was also less sensitive to specimen orientation (umbilical versus spiral views) than the humans. Finally, these results demonstrate that our approach can provide a versatile ‘brain’ for an eventual automated robotic picking system.

58 GEOSCIENCES↗
DOE OSTI2021

Human Performance Improvement Task Group Task 21-1 Best Practice: Using virtual capabilities or options for HPI application (to reduce errors, strengthening defenses, strengthening the organization, and/or increasing capacity)

In 2020 the world was impacted by COVID-19. How work is done was dramatically changed for a large portion of the workforce. Many have made the abrupt shift to working from their home while others have adapted to COVID protocols (such as social distancing and wearing facemasks). Fundamentally, Human and Organizational Performance Improvement concepts and science did not change – only the delivery method changed (in some cases). The primary effect has been to accelerate dynamics already present in society – from e-commerce to online education to remote healthcare. Change is never easy for humans. However, remote work should be viewed as an opportunity; not a fix to a problem. In this Best Practice paper, you’ll get practical suggestions to help you reduce errors and improve Human Performance in remote, socially-distanced “work-from-home” environments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Using recordings of brain activity to predict and improve human performance

This project investigated methods for using recordings of event-related potentials (ERPs) to predict and improve human memory performance. In a series of experiments, the ERPs related to good and poor memory performance were characterized and a computational model was developed in which the ERPs recorded while a person studied words were used to predict whether that person would be a high performer or a low performer on a subsequent memory test. These experiments provide the first demonstration of ERPs used to predict subsequent memory performance. Additional experiments investigated the effects of different types of memory training (learning a memory strategy such as mental imagery or increasing memory capacity through working memory training) on memory performance and the associated brain activity.

Matzen, Laura E.↗
DOE OSTI2012

The Use Of Computational Human Performance Modeling As Task Analysis Tool

During a review of the Advanced Test Reactor safety basis at the Idaho National Laboratory, human factors engineers identified ergonomic and human reliability risks involving the inadvertent exposure of a fuel element to the air during manual fuel movement and inspection in the canal. There were clear indications that these risks increased the probability of human error and possible severe physical outcomes to the operator. In response to this concern, a detailed study was conducted to determine the probability of the inadvertent exposure of a fuel element. Due to practical and safety constraints, the task network analysis technique was employed to study the work procedures at the canal. Discrete-event simulation software was used to model the entire procedure as well as the salient physical attributes of the task environment, such as distances walked, the effect of dropped tools, the effect of hazardous body postures, and physical exertion due to strenuous tool handling. The model also allowed analysis of the effect of cognitive processes such as visual perception demands, auditory information and verbal communication. The model made it possible to obtain reliable predictions of operator performance and workload estimates. It was also found that operator workload as well as the probability of human error in the fuel inspection and transfer task were influenced by the concurrent nature of certain phases of the task and the associated demand on cognitive and physical resources. More importantly, it was possible to determine with reasonable accuracy the stages as well as physical locations in the fuel handling task where operators would be most at risk of losing their balance and falling into the canal. The model also provided sufficient information for a human reliability analysis that indicated that the postulated fuel exposure accident was less than credible.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Materials and Fuels Complex Human Performance and Nuclear Safety Culture Pocket Guide

The facilities at the Materials and Fuels Complex (MFC) contain a diverse collection of nuclear research and development capabilities which enable experiments and engineering to drive the world’s nuclear energy future. It is our responsibility to ensure safe, efficient, and reliable operation of MFC facilities to support INL’s nuclear science and technology and national security missions. The MFC management plan makes it clear that safely achieving this takes the right people using good processes.

99 GENERAL AND MISCELLANEOUS↗