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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

An Operational Concept for Flying FMS Trajectories in Center and TRACON Airspace

Current Flight Management Systems (FMS) do a good job of constructing and flying an optimal trajectory for a single aircraft. Unfortunately, flight crews are often unable to fly these FMS routes during arrivals at busy airports. The Center TRACON Automation System (CTAS) has been designed to aid Center and TRACON (Terminal Radar Approach Control) controllers in assigning runways, sequencing and vectoring all classes of aircraft. CTAS bases its advisories on trajectory predictions for arriving aircraft using algorithms very similar to those in airborne FMS systems. This paper presents near and far term operational concepts for how a ground ATM (air traffic management) automation system like CTAS could work more effectively with the airborne automation in FMS equipped aircraft. The concepts for a more compatible air-ground system include: 1) a common route databases for both CTAS and FMS; 2) datalink to downlink information on aircraft weight, final approach speed and trajectory intent and to uplink wind information; 3) new FMS functions to allow flight crews to easily update their FMS trajectory to match the trajectory suggested by the ground automation with voice clearances, and 4) in the far term, datalink to downlink user preferred trajectories and to uplink trajectory clearances in the terminal area. The paper analyses some of the human factors issues that may result in allowing aircraft to fly FMS routes during enroute descent and in the terminal area. A series of linked human in the loop flight deck and air traffic control simulations and a field test with the NASA 757 are being conducted at NASA's Ames and Langley Research Centers to address these issues and to evaluate the operational feasibility of these approaches to more efficient flight and increased airport throughput.

Palmer, Everett↗
NASA NTRS2018

Gene Expression of Pathogens in Simulated Microgravity

Extended exposure to radiation and microgravity in space has been linked to astronauts developing chronic diseases upon returning to Earth. The Gram-negative pathogen Serratia marcescens has been shown to potentially cause significant infections in humans and in insect models on Earth. Our recent findings also showed that S. marcescens shows an increase in virulence after a short period of growth in the spaceflight environment, which raises initiatives to find the correlation between space environment and the increased virulence. Because we know that the health of astronauts is immunocompromised in space, it is possible that the combination of increased bacterial virulence and the weakened immune system will cause astronauts to be more susceptible to chronic diseases in extended spaceflight. With 75% of human disease genes being conserved in the fruit fly Drosophila melanogaster, these insects act as an ideal model organism to study the human immune system. The high accessibility, low cost, high rate of reproductivity, and short lifespans of D. melanogaster facilitate efficient, high-quality research that seeks to understand altered virulence of this opportunistic pathogen. In this ground-based study, we will use a rotating wall vessel apparatus to simulate microgravity and determine how pathogenicity changes by evaluating differences in gene expression for S. marcescens between bacteria grown in simulated microgravity conditions and controls. We will compare the results of our findings to gene expression patterns in actual spaceflight samples of S. marcescens grown on the ISS (International Space Station) during a recent validation mission, to see if there are common mechanisms across our simulated microgravity and actual spaceflight microgravity samples that both show increased virulence in the fruit fly. With extended space travel in the foreseeable future, understanding how human physiology will be affected by these different factors will help mitigate risks and deaths.

spaceflight analogue↗
NASA NTRSDate not supplied

Impact of Simulated Galactic Cosmic Radiation and Hindlimb Unloading on the Mouse Adrenal Gland Morphology and Histology

Stress related impact of Galactic Cosmic Radiation (GCR) combined with microgravity in space are concerns for astronauts going beyond the Van Allen belts on their way to the Moon and Mars. The adrenal gland is the central endocrine tissue involved in stress management, adrenal hormones regulate the immune system, cellular and tissue metabolism, and glucose and sodium balances. Adult (6 m old) female (n=18) and male (n=18) C57BL/6J mice were divided evenly into 6 treatment groups (control, hindlimb unloading (HU), irradiated (IR), HU+IR, group house control, and group house IR). Adrenals were dissected and fixed for 24 h in 4% paraformaldehyde, followed by transfer to 70% EtOH, and shipment to KUMC. Adrenals were then embedded in paraffin and serial sectioned and 4 central sections from each were stained with H&E, prior to imaging on a Nikon 80i microscope. Whole adrenal cross section area, medullary area, and cortex area were determined. General adrenal gland morphology and histology did not appear to be affected by hindlimb unloading or GCR exposure. Total cross-sectional area, medullary region, and cortex of the adrenal were not different across treatment groups. Male adrenal cross-sectional areas are half the size of the female adrenals, due to a difference in cortex area. In conclusion, simulated microgravity and GCR did not dramatically affect the adrenal gland histology or size. Support from Accelerate Cancer Education Internship Program (KUCC) and KINBRE Summer Scholars Program (KUMC) and NASA Human Research Program (HRP) Human Factors Behavioral Performance Element Grant 18 18FLAG 2 0028

radiation↗
NASA NTRSDate not supplied

Modeling Distributed Situation Awareness in Resilience-Based Design of Complex Engineered Systems

Human operators play a major role in the resilience of complex systems–while human error is one of the biggest contributors to hazardous events, operators additionally play a critical role in mitigating hazardous events. A key factor underlying this operator resilience is situation awareness–the ability of operators to understand their environment and each other to achieve desired system functions. In contrast to situation awareness-related accident models in the literature, which are largely conceptual in nature, this work proposes the use of a dynamic simulation framework to concretely model both the effects of situation awareness-related human errors and situation awareness-related hazard-mitigating properties using the distributed situation awareness theory. This work then presents specialized model constructs to enable agents’ individual perceptions of the system state and transactions with other agents (and thus distributed situation awareness) to be represented in simulation. To demonstrate this framework, it is then adapted to an aircraft taxiway case study, where it is used to model aircraft conflicts due to lack of vision and poor communications from the air traffic controller. This demonstration shows the potential of using simulation models to rigorously understand situation awareness-related human errors and thus inform the design of resilience.

Resilience Modeling↗
NASA NTRSDate not supplied

Modeling Distributed Situation Awareness in Resilience-based Design of Complex Systems

Human operators play a major role in the resilience of complex systems–while human error is one of the biggest contributors to hazardous events, operators additionally play a critical role in mitigating hazardous events. A key factor underlying this operator resilience is situation awareness–the ability of operators to understand their environment and each other to achieve desired system functions. In contrast to situation awareness-related accident models in the literature, which are largely conceptual in nature, this work proposes the use of a dynamic simulation framework to concretely model both the effects of situation awareness-related human errors and situation awareness-related hazard-mitigating properties using the distributed situation awareness theory. This work then presents specialized model constructs to enable agents’ individual perceptions of the system state and transactions with other agents (and thus distributed situation awareness) to be represented in simulation. To demonstrate this framework, it is then adapted to an aircraft taxiway case study, where it is used to model aircraft conflicts due to lack of vision and poor communications from the air traffic controller. This demonstration shows the potential of using simulation models to rigorously understand situation awareness-related human errors and thus inform the design of resilience.

Resilience Modeling↗
NASA NTRSDate not supplied

Human placenta-derived stromal cells mitigate select immune responses to simulated weightlessness

Space flight presents unique risks to human health. Microgravity and social isolation are important space flight stressors which have vast impact on multiple systems such as the musculoskeletal, immune and central nervous system (CNS). To explore candidate countermeasures against tissue decrements caused by spaceflight, we performed a pilot study with PLacental-eXpanded stromal (PLX) cells. PLX cells secrete factors that modulate the immune system, but do not trigger host immune responses, enabling treatment in subjects that have intact immune systems. These cells had previous success in treating critical limb ischemia and acute radiation syndrome in murine models. In this study, 4-month-old female mice underwent 30 days of hindlimb unloading (HU) in single housing conditions to simulate long-term weightlessness and isolation. HU and normally ambulating controls were administered with PLX cells or sham-injected with Plasmalyte. We hypothesized that administration of PLX cells will mitigate some of the effects caused by prolonged HU. We found that treatment with PLX cells was well tolerated as indicated by body weights, circulating corticosterone levels and immune organ response to injection of the cells. HU led to the expected decreases in soleus muscle weights and bone loss. We did not observe any protective properties of the PLX cells in the musculoskeletal system but found that the cell treatment partially protected from a subset of HU-induced immune and CNS changes. In the hippocampus, protein levels of 9 of 44 cytokines were downregulated by HU. PLX administration mitigated changes in expression of 8 of these cytokines, including IL-2, IL-6 and MCP-1. To our knowledge, this is the first report on the protective effects of PLX-PAD against HU-induced changes in the cytokine milieu of the CNS. Our findings warrant further studies, which includes testing in actual spaceflight.

Microgravity↗
NASA NTRS1973

Introduction

The objective of the Skylab medical experiment altitude test was to provide a nearly full scale simulation of a 56-day Skylab mission for studying physiological changes produced in man by the long term exposure to space conditions. Evaluated in the altitude chamber tests were human cardiovascular/hemodynamic responses, musculoskeletal/metabolic effects, endocrine/electrode factors, and neurophysiological indices.

Johnston, R. S.↗
NASA NTRS1974

Simulators' validation study: Problem solution logic

A study was conducted to validate the ground based simulators used for aircraft environment in ride-quality research. The logic to the approach for solving this problem is developed. The overall problem solution flow chart is presented. The factors which could influence the human response to the environment on board the aircraft are analyzed. The mathematical models used in the study are explained. The steps which were followed in conducting the validation tests are outlined.

Schoultz, M. B.↗
NASA NTRS1999

In Vivo Noninvasive Analysis of Human Forearm Muscle Function and Fatigue: Applications to EVA Operations and Training Maneuvers

Forearm muscle fatigue is one of the major limiting factors affecting endurance during performance of deep-space extravehicular activity (EVA) by crew members. Magnetic resonance (MR) provides in vivo noninvasive analysis of tissue level metabolism and fluid exchange dynamics in exercised forearm muscles through the monitoring of proton magnetic resonance imaging (MRI) and phosphorus magnetic resonance spectroscopy (P-31-MRS) parameter variations. Using a space glove box and EVA simulation protocols, we conducted a preliminary MRS/MRI study in a small group of human test subjects during submaximal exercise and recovery and following exhaustive exercise. In assessing simulated EVA-related muscle fatigue and function, this pilot study revealed substantial changes in the MR image longitudinal relaxation times (T2) as an indicator of specific muscle activation and proton flux as well as changes in spectral phosphocreatine-to-phosphate (PCr/Pi) levels as a function of tissue bioenergetic potential.

Fotedar, L. K.↗
NASA NTRS1999

Interpretation of Lidar and Satellite Data Sets Using a Global Photochemical Model

A primary goal of the NASA Tropospheric Chemistry Program (TCP) is to "contribute substantially to scientific understanding of human impacts on the global troposphere". In order to analyze global or regional trends and factors of the troposphere chemistry, for example, its oxidation capacity or composition, a continuous global/regional data coverage as well as model simulations are needed. The Global Tropospheric Experiment (GTE), a major component of the TCP, provides data vital to these questions via aircraft measurement of key trace chemical species in various remote regions of the world. Another component in NASA's effort are satellite projects for exploration of tropospheric chemistry and dynamics. A unique data product is the Tropospheric Ozone Residual (TOR) utilizing global tropospheric ozone data. Another key research tool are simulation studies of atmospheric chemistry and dynamics for the theoretical understanding of the atmosphere, the extrapolation of observed trends, and for sensitivity studies assessing a changing anthropogenic impact to air chemistry and climate. In the context with model simulations, field data derived from satellites or (airborne) field missions are needed for two purposes: 1. To initialize and validate model simulations, and 2., to interpret field data by comparison to model simulation results in order to analyze global or regional trends and deviations from standard tropospheric chemistry and transport conditions as defined by the simulations. Currently, there is neither a sufficient global data coverage available nor are existing well established global circulation models. The NASA LARC CTM model is currently not yet in a state to accomplish a sufficient tropospheric chemistry simulation, so that the current research under this cooperative agreement focuses on utilizing field data products for direct interpretation. They will be also available for model testing and a later interpretation with a finally utilized model.

Zenker, Thomas↗
NASA NTRS2006

Behavioral Health Program Element

The project goal is to develop behavioral health prevention and maintenance system for continued crew health, safety, and performance for exploration missions. The basic scope includes a) Operationally-relevant research related to clinical cognitive and behavioral health of crewmembers; b) Ground-based studies using analog environments (Antarctic, NEEMO, simulations, and other testbeds; c) ISS studies (ISSMP) focusing on operational issues related to behavioral health outcomes and standards; d) Technology development activities for monitoring and diagnostic tools; and e) Cross-disciplinary research (e.g., human factors and habitability research, skeletal muscle, radiation).

Leveton, Lauren B.↗
NASA NTRS2026

Introduction to the Special Issue on Advanced Air Mobility Noise: Predictions, Measurements and Perception

This Special Issue focuses on noise associated with Advanced Air Mobility (AAM), an emerging class of predominantly electric distributed-propulsion aircraft designed for urban and regional transportation. As these vehicles move toward certification and deployment, noise has become a central challenge for regulatory approval and public acceptance, particularly due to operations in densely populated areas and at low altitudes. The 24 contributions in this issue address three key aspects of AAM noise: prediction, measurement, and human perception. Prediction studies span a wide range of modeling fidelities, from high-resolution simulations to improved semi-analytical approaches, and examine complex aeroacoustic mechanisms including rotor interactions, turbulence ingestion, and broadband noise generation. Measurement studies, largely at model scale, provide new insights into tonal and broadband noise characteristics across configurations and operating conditions, while supporting model validation. Perception-focused contributions investigate annoyance, sound quality metrics, and auralization, emphasizing the role of context and operational factors in shaping human response. Together, these works highlight the interdisciplinary nature of AAM noise research and the need for integrated approaches to enable quieter vehicle design.

Perception↗
NASA NTRS2002

Automated fault-management in a simulated spaceflight micro-world

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

NASA Discipline Space Human Factors↗
NASA NTRS1999

Transducer model produces facilitation from opposite-sign flanks

Small spots, lines and Gabor patterns can be easier to detect when they are superimposed upon similar spots, lines and Gabor patterns. Traditionally, such facilitation has been understood to be a consequence of nonlinear contrast transduction. Facilitation has also been reported to arise from non-overlapping patterns with opposite sign. We point out that this result does not preclude the traditional explanation for superimposed targets. Moreover, we find that facilitation from opposite-sign flanks is weaker than facilitation from same-sign flanks. Simulations with a transducer model produce opposite-sign facilitation.

NASA Discipline Space Human Factors↗
DOE OSTI2024

Identifying Climate Patterns Using Clustering Autoencoder Techniques

Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k -means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k -means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.

Kurihana, Takuya↗
NASA NTRS1990

Human factors issues in telerobotic systems for Space Station Freedom servicing

Requirements for Space Station Freedom servicing are described and the state-of-the-art for telerobotic system on-orbit servicing of spacecraft is defined. The projected requirements for the Space Station Flight Telerobotic Servicer (FTS) are identified. Finally, the human factors issues in telerobotic servicing are discussed. The human factors issues are basically three: the definition of the role of the human versus automation in system control; the identification of operator-device interface design requirements; and the requirements for development of an operator-machine interface simulation capability.

Malone, Thomas B.↗
NASA NTRS2005

Human Factors Assessment of Respiratory Support Pack (RSP) Cue Card

The Respiratory Support Pack (RSP) is a medical pack onboard the International Space Station (ISS) that contains much of the necessary equipment for providing aid to a conscious or unconscious crewmember in respiratory distress. Inside the RSP lid pocket is a 5.5 by 11 inch paper cue card, which is used by a Crew Medical Officer as the procedure to set up the equipment and deliver oxygen to a crewmember. In training, crewmembers expressed concerns about the readability and usability of the cue card; consequently, updating the cue card was prioritized as an activity to be completed prior to Space Shuttle return-to-flight. The Usability Testing and Analysis Facility at the Johnson Space Center evaluated the current layout of the cue card, and proposed several new cue card designs based on human factors principals. A series of three studies were performed in order to experimentally compare performance with each of the cue card designs. Nonmedically trained personnel used either a redesigned RSP cue card, or the original card to simulate resuscitation (using a mannequin along with the hardware). Time to completion, errors and subjective ratings were recorded. The addition of pictures, colors, borders, and simplification of the flow of information (making minimal changes to the actual procedure content) elicited great benefits during testing. Time to complete RSP procedures was reduced by as much as three minutes with the final cue card design. Detailed results from these studies, as well as general guidelines for cue card design will be discussed.

Whitmore, Mihriban↗