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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Practicing for Mars: The International Space Station (ISS) as a Testbed

Allows demonstration and development of exploration capabilities to help accomplish future missions sooner with less risk to crew and mission Characteristics of ISS as a testbed High fidelity human operations platform in LEO: Continuously operating habitat and active laboratory. High fidelity systems. Astronauts as test subjects. Highly experienced ground operations teams. Offers a controlled test environment.: Consequences to systems performance and decision making not offered in ground analogs International participation. Continuously improving system looking for new technology and ideas to improve operations. Technology Demos & Critical Systems Maturation. Human Health and Performance. Operations Simulations and Techniques. Exploration prep testing on ISS has been ongoing since 2012. Number of tests increasing with each ISS expedition. One Year Crew Expedition starting in Spring 2015. ROSCOSMOS and NASA are partnering on the Participating Crew are Mikhail Kornienko and Scott Kelly Majority of testing is an extension of current Human Biomedical Research investigations Plan for extending & expanding upon current operations techniques and tech demo studies ESA 10 Day Mission in Fall 2015 ESA astronaut focus on testing exploration technologies Many more opportunities throughout the life of ISS! 4/24/2014 david.h.korth@nasa.gov 4 Exploration testing

Korth, David H.↗
NASA NTRS2013

Predicting Operator Execution Times Using CogTool

Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

Santiago-Espada, Yamira↗
NASA NTRS1989

Expert systems should be more accurate than human experts - Evaluation procedures from human judgment and decisionmaking

Two procedures for the evaluation of the performance of expert systems are illustrated: one procedure evaluates predictive accuracy; the other procedure is complementary in that it uncovers the factors that contribute to predictive accuracy. Using these procedures, it is argued that expert systems should be more accurate than human experts in two senses. One sense is that expert systems must be more accurate to be cost-effective. Previous research is reviewed and original results are presented which show that simple statistical models typically perform better than human experts for the task of combining evidence from a given set of information sources. The results also suggest the second sense in which expert systems should be more accurate than human experts. They reveal that expert systems should share factors that contribute to human accuracy, but not factors that detract from human accuracy. Thus the thesis is that one should both require and expect systems to be more accurate than humans.

Levi, Keith↗
DOE OSTI2023

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Strategy for Developing Technologies for Megawatt-class Nuclear Electric Propulsion Systems

In late fiscal year 2020, the Space Nuclear Propulsion (SNP) project began the process of formulating an investment strategy to support development of the technologies required for a high-power (megawatt-class) nuclear electric propulsion (NEP) system capable of performing human-scale missions. This activity was initiated concurrent with several high-level studies and assessments were either under way or had just concluded. Studies of human-scale Mars missions have been performed several times over the past two decades. One of the most recent studies examined opposition-class human Mars missions to occur in the late 2030s timeframe [1,2]. The mission architecture assumed a hybrid NEP/chem-propelled vehicle that used a high specific impulse (Isp) NEP-system and a liquid oxygen (LOx)-liquid methane high thrust chemical stage (two 110 kN (25 klbf) thrust, 365 s Isp engines) for maneuvers performed to enter and exit gravity wells. Trajectory analyses performed in this study showed that such a mission could be performed with 2-4 MWe directed into the electric propulsion system (operating for 20,000+ hours), with the large range representing different opposition-class Mars mission opportunities and permutations on the trajectory design, concept of operations, and technology choices. In 2020, the NASA Engineering and Safety Center (NESC) performed a study to evaluate the maturity of the different technologies required for nuclear propulsion systems [3]. The executive summary of this report provided the following top-level conclusions: • “The majority of critical technologies for… NEP/Chem… systems are relatively immature” • “TRLs [technology readiness levels] in the literature are often overestimated” • “The majority of critical technologies… for NEP/Chem… systems are at a relatively high level of advancement degree of difficulty (AD2 > 4) for maturation, requiring a dual development approach” • “The proper assessment of baseline TRL and AD2 values and the estimation of requirements and resources required for advancement have been consistent issues for NEP,” • “Non-advocate reviews should occur at the start of a technology program and at all key milestones.” In 2021, the National Academies of Science, Engineering, and Medicine (NASEM) issued a separate report [4] identifying the “primary technical and programmatic challenges, merits, and risks for maturing space nuclear propulsion technologies of interest to a future human Mars exploration mission.” That work contained several important findings, including: • “Developing a MWe-class NEP system for the baseline mission would require increasing power by orders of magnitude relative to NEP system flight- or ground-based technology demonstrations completed to date.” • “Subscale in-space flight testing of NEP systems cannot address many of the risks and potential failure modes associated with the baseline mission NEP system. With sufficient M&S [modeling & simulation] and ground testing, including modular subsystem tests at full scale and power, flight qualification requirements can be met by the cargo missions that will precede the first crewed mission to Mars. Fully integrated ground testing may not be required.” • “As a result of low and intermittent investment over the past several decades, it is unclear if even an aggressive program would be able to develop an NEP system capable of executing the baseline mission in 2039.” These efforts motivated the SNP project to investigate the technologies available for a megawatt-class high power nuclear electric propulsion system. That system is illustrated schematically in Figure 1 and is comprised of five separate top-level critical technology elements (CTEs). 1. Nuclear Reactor – Thermal power source for the system, utilizing high-assay low enriched uranium (HALEU) as the nuclear fuel. Reactor radiation shielding is also included in this CTE. 2. Power Conversion – Operates as a thermodynamic cycle, accepting nuclear reactor thermal power as an input and converting it to mechanical power. 3. Power Management and Distribution (PMAD) – Accepts as an input mechanical power from the power conversion system, which is used to generate electrical power. The PMAD system also distributes the generated electrical power to all other parts of the spacecraft, including the high-power EP system. The PMAD system may also perform duties such as isolation, fault detection, and power transformation/rectification for different spacecraft systems, including the thrusters. 4. Electric Propulsion (EP) – Accepts as an input electrical power, which is used to accelerate a propellant to high speeds to produce thrust. This system includes the power processing unit (PPU), which converts the power it receives to the correct current and voltage required by the thrusters, and the propellant storage and feed systems, which contain and meter the flow of propellant to the thrusters. 5. Thermal Management (Radiators/Heat Rejection) – The cold side of the thermodynamic power conversion cycle, accepts thermal power from the power conversion system and radiatively rejects that heat to space. In this paper, we describe the SNP project formulation and investment strategy that aims to accomplish the research and development required to advance the technology readiness for each CTE. The strategy relies heavily upon experimental testing supported by modeling and simulation to yield realistic assessments of the technologies, which in turn will be used to inform future NEP system-level design decisions and any potential technology downselects.

Kurt A Polzin↗
NASA NTRS2015

NASA Lighting Research, Test, & Analysis

The Habitability and Human Factors Branch, at Johnson Space Center, in Houston, TX, provides technical guidance for the development of spaceflight lighting requirements, verification of light system performance, analysis of integrated environmental lighting systems, and research of lighting-related human performance issues. The Habitability & Human Factors Lighting Team maintains two physical facilities that are integrated to provide support. The Lighting Environment Test Facility (LETF) provides a controlled darkroom environment for physical verification of lighting systems with photometric and spetrographic measurement systems. The Graphics Research & Analysis Facility (GRAF) maintains the capability for computer-based analysis of operational lighting environments. The combined capabilities of the Lighting Team at Johnson Space Center have been used for a wide range of lighting-related issues.

Clark, Toni↗
NASA NTRS2012

SARDA HITL Simulations: System Performance Results

This presentation gives an overview of the 2012 SARDA human-in-the-loop simulation, and presents a summary of system performance results from the simulation, including delay, throughput and fuel consumption

Gupta, Gautam↗
NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗
NASA NTRS1990

A system performance throughput model applicable to advanced manned telescience systems

As automated space systems become more complex, autonomous, and opaque to the flight crew, it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed that are related to total system validation. An evaluative throughput model is presented which can be used to generate a human operator-related benchmark or figure of merit for a given system which involves humans at the input and output ends as well as other automated intelligent agents. The concept of sustained and accurate command/control data information transfer is introduced. The first two input parameters of the model involve nominal and off-nominal predicted events. The first of these calls for a detailed task analysis while the second is for a contingency event assessment. The last two required input parameters involving actual (measured) events, namely human performance and continuous semi-automated system performance. An expression combining these four parameters was found using digital simulations and identical, representative, random data to yield the smallest variance.

Haines, Richard F.↗
NASA NTRS2013

NextGen Operational Improvements: Will they Improve Human Performance

Modernization of the National Airspace System depends critically on the development of advanced technology, including cutting-edge automation, controller decision-support tools and integrated on-demand information. The Next Generation Air Transportation System national plan envisions air traffic control tower automation that proposes solutions for seven problems: 1) departure metering, 2) taxi routing, 3) taxi and runway scheduling, 4) departure runway assignments, 5) departure flow management, 6) integrated arrival and departure scheduling and 7) runway configuration management. Government, academia and industry are simultaneously pursuing the development of these tools. For each tool, the development process typically begins by assessing its potential benefits, and then progresses to designing preliminary versions of the tool, followed by testing the tool's strengths and weaknesses using computational modeling, human-in-the-loop simulation and/or field tests. We compiled the literature, evaluated the methodological rigor of the studies and served as referee for partisan conclusions that were sometimes overly optimistic. Here we provide the results of this review.

Beard, Bettina L.↗
NASA NTRSDate not supplied

The Exploration Crew Health and Performance System of the Future - A Shared Mental Model

The challenges involved in vehicle/habitat design and operation for long-duration deep space missions are complex, and the needs of a human crew must be considered in the context of all the system trades required to enable such missions. An exploration Crew Health and Performance (CHP) system complements all the other vehicle/habitat systems to achieve one specific and critical endpoint – ensuring that the astronauts can perform the job that they were sent into space to do. This includes accounting for all aspects of the physiological, psychological, medical, and environmental realities that the human crew must face in deep space. Along with this system complexity comes the additional need for increased autonomy of the crew due to the immense distance from Earth. The design of future systems must respect the real human capabilities and limitations within the context of a mission to the Moon or Mars. The NASA Moon to Mars Objectives document outlines the need for advanced CHP system designs: • Develop systems that monitor and maintain crew health and performance throughout all mission phases, including during communication delays to Earth, and in an environment that does not allow emergency evacuation or terrestrial medical assistance. • Evaluate and validate progressively Earth-independent crew health & performance systems and operations with mission durations representative of Mars-class missions. • Validate readiness of systems and operations to support crew health and performance for the initial human Mars exploration campaign. This presentation will outline the initial work that Exploration Medical Capability is leading on the development of a prototype design for an exploration Crew Health and Performance (CHP) system for future NASA human deep space long-duration missions. This effort will require commitment from all stakeholders to a shared mental model of what a future exploration CHP system should look like, one that will address the needs, goals, and objectives of the Agency and help to ensure mission success in deep space.

K R Lehnhardt↗
NASA NTRS2015

Identification and Evaluation of Integration and Cross Cutting Issues Across HRP Risks

The HRP Integrated Research Plan contains the research plans for the 32 risks requiring research to characterize and mitigate. These risks to human health and performance in spaceflight are identified by evidence and each one focuses on a single aspect of human physiology or performance. They are further categorized by aspects of the spaceflight environment, such as altered gravity or space radiation, that that play a major role in their likelihood and consequence. From its inception the "integrate" in the Research Plan has denoted the integrated nature of risks to human health and performance, the connectedness of physiological systems within the human body regardless of the spaceflight environment, and the integrated response of the human body to the spaceflight environment. Common characteristics of the spaceflight environment include altered gravity, atmospheres and light/dark cycles, space radiation, isolation, noise, and periods of high or low workload. Long term exposure to this unique environment produces a suite of physiological effects such as stress; vision, neurocognitive and anthropometric changes; circadian misalignment; fluid shifts, deconditioning; immune dysregulation; and altered nutritional requirements. Matrix diagraming was used to systematically identify, analyze and rate the many-to-many relationships between environmental characteristics and the suite of physiological effects. It was also to identify patterns in the relationships of common physiological effects to each other. Analyses of patterns or relationships in these diagrams help to identify issues that cut across multiple risks. Cross cutting issues benefit from a multidisciplinary approach that synthesizes concepts or data from two or more disciplines to identify and characterize risk factors or develop countermeasures relevant to multiple risks. They also help to illuminate possible problem areas that may arise when a countermeasure impacts risks other than those which it was developed to mitigate, or identify groupings of physiological changes that are likely to occur that may impact the overall risk posture.

Steinberg, S. L.↗
NASA NTRS1989

Learning in tele-autonomous systems using Soar

Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

Laird, John E.↗
NASA NTRS1995

Emulating the Lateral Dynamics of a Range of Vehicles Using a Four-Wheel-Steering Vehicle

The concept of Variable Dynamic Testbed Vehicle (VDTV) has been proposed as a tool to evaluate collision detection/avoidance systems, to perform vehicle-related human factors research, and to support other Automated HighWay System programs. The goal of this study is to analytically investigate to what extent a VDTV with four-wheel-steering can emulate the lateral dynamics of a broad range of vehicle models.

Four-wheel-steering varible dynamic testbed vehicl↗
NASA NTRS2022

Directed Acyclic Graphs: A Tool for Understanding the NASA Human Spaceflight System Risks - Human System Risk Board

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding of these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document is a sister document to NASA/TM 20220006812 Directed Acyclic Graph Guidance Documentation (1). In that document, the basic guidance for creating and standardizing directed acyclic graphs as tools for cross-risk analysis is provided. This document contains the initial configuration managed DAGs that were created as a result of applying those principles. These initial versions were accepted by the HSRB in January of 2022. Each of the Human System Risks are represented by a DAG that has been reviewed by the larger Human Health and Performance community at NASA including life scientists, physical scientists, physicians, nurses, pharmacists, exercise specialists and more. These results show the starting point for Human System Risk DAGs as shared mental models and communication aids across the boundaries of the various expertise needed to understand and mitigate the human risks in spaceflight. Because they are a starting point, each of these DAGs can be expected to change over time as new or refined evidence becomes available. The process for updating these DAGs can be found in the JSC-66705 Human System Risk Management Plan (2) that is publicly available on the NASA Technical Reports Server.

Erik L. Antonsen↗
NASA NTRS2017

Effects on Task Performance and Psychophysiological Measures of Performance During Normobaric Hypoxia Exposure

Human-autonomous systems have the potential to mitigate pilot cognitive impairment and improve aviation safety. A research team at NASA Langley conducted an experiment to study the impact of mild normobaric hypoxia induction on aircraft pilot performance and psychophysiological state. A within-subjects design involved non-hypoxic and hypoxic exposures while performing three 10-minute tasks. Results indicated the effect of 15,000 feet simulated altitude did not induce significant performance decrement but did produce increase in perceived workload. Analyses of psychophysiological responses evince the potential of biomarkers for hypoxia onset. This study represents on-going work at NASA intending to add to the current knowledge of psychophysiologically-based input to automation to increase aviation safety. Analyses involving coupling across physiological systems and wavelet transforms of cortical activity revealed patterns that can discern between the simulated altitude conditions. Specifically, multivariate entropy of ECG/Respiration components were found to be significant predictors (p< 0.02) of hypoxia. Furthermore, in EEG, there was a significant decrease in mid-level beta (15.19-18.37Hz) during the hypoxic condition in thirteen of sixteen sites across the scalp. Task performance was not appreciably impacted by the effect of 15,000 feet simulated altitude. Analyses of psychophysiological responses evince the potential of biomarkers for mild hypoxia onset.The potential for identifying shifts in underlying cortical and physiological systems could serve as a means to identify the onset of deteriorated cognitive state. Enabling such assessment in future flightdecks could permit increasingly autonomous systems-supported operations. Augmenting human operator through assessment of cognitive impairment has the potential to further improve operator performance and mitigate human error in safety critical contexts. This study represents ongoing work at NASA intending to add to the current knowledge of psychophysiologically-based input to automation to increase aviation safety.

Stephens, Chad↗
NASA NTRSDate not supplied

Expanding Our Understanding of What Constitutes a Safety-Relevant Occurrence

Focusing on undesired operator behaviors is pervasive in system design and safety management cultures. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. The study of human contributions to safety represents a vast and largely unexplored opportunity to learn. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform system design, safety-related decision making and policies depends upon identifying, collecting, and interpreting safety producing behaviors in addition to safety reducing behaviors.

Jon B Holbrook↗