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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 NTRSDate not supplied

Lunar Surface Cargo Offloading Concepts

A sustainable presence on the lunar surface will serve as a vital training ground and technology demonstration test site in preparation for future human missions to Mars. Robotic lunar surface campaigns will focus on the exploration of resources providing information on the availability and extraction of usable resources, such as oxygen and water, and prepare the surface for a sustained human presence. Landers, outfitted with sensor packages, will be used to conduct risk-reduction activities and aid in the development of technologies prior to the crewed lunar missions that drive the need to for a logistics supply chain that requires offloading. A series of landers will be required on other planetary surfaces to build up the capabilities, capitalizing on those resources, required for sustained human presence. In each of those landers will be cargo including ascent vehicles, habitats, supplies, science packages, spare parts, fluids commodities for fuel and life support, and others varying in volume and ranging from mass in hundreds of kilograms to an estimated 6-14 metric tons to support Human Landing Systems and surface logistics requirements. This paper will examine the challenge of offloading examples of these cargo elements from different categories of landers on the lunar surface using a variety of methodologies. Challenges on the lunar surface arise with the conditions present (thermal, lighting, communications, regolith consistency), the desire to minimize mass of all landed systems, the desire to perform much of the activities with limited to minimal human interaction, and the overall configuration of the landers that are responsible for landing the cargo.

Lunar↗
NASA NTRS2017

Annoyance to Noise Produced by a Distributed Electric Propulsion High-Lift System

A psychoacoustic test was performed using simulated sounds from a distributed electric propulsion aircraft concept to help understand factors associated with human annoyance. A design space spanning the number of high-lift leading edge propellers and their relative operating speeds, inclusive of time varying effects associated with motor controller error and atmospheric turbulence, was considered. It was found that the mean annoyance response varies in a statistically significant manner with the number of propellers and with the inclusion of time varying effects, but does not differ significantly with the relative RPM between propellers. An annoyance model was developed, inclusive of confidence intervals, using the noise metrics of loudness, roughness, and tonality as predictors.

Rizzi, Stephen A.↗
NASA NTRS1999

Dose-response relationship between sleep duration and human psychomotor vigilance and subjective alertness

Although it has been well documented that sleep is required for human performance and alertness to recover from low levels after prolonged periods of wakefulness, it remains unclear whether they increase in a linear or asymptotic manner during sleep. It has been postulated that there is a relation between the rate of improvement in neurobehavioral functioning and rate of decline of slow-wave sleep and/or slow-wave activity (SWS/SWA) during sleep, but this has not been verified. Thus, a cross-study comparison was conducted in which dose-response curves (DRCs) were constructed for Stanford Sleepiness Scale (SSS) and Psychomotor Vigilance Task (PVT) tests taken at 1000 hours by subjects who had been allowed to sleep 0 hours, 2 hours, 5 hours or 8 hours the previous night. We found that the DRCs to each PVT metric improved in a saturating exponential manner, with recovery rates that were similar [time constant (T) approximately 2.14 hours] for all the metrics. This recovery rate was slightly faster than, though not statistically significantly different from, the reported rate of SWS/SWA decline (T approximately 2.7 hours). The DRC to the SSS improved much more slowly than psychomotor vigilance, so that it could be fit equally well by a linear function (slope = -0.26) or a saturating exponential function (T = 9.09 hours). We conclude that although SWS/SWA, subjective alertness, and a wide variety of psychomotor vigilance metrics may all change asymptotically during sleep, it remains to be determined whether the underlying physiologic processes governing their expression are different.

Non-NASA Center↗
NASA NTRS1996

Advanced Air Traffic Management Research (Human Factors and Automation): NASA Research Initiatives in Human-Centered Automation Design in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. The core processes of control and the distribution of decision making in that control are undergoing extensive analysis. From our perspective, the human operators and the procedures by which they interact are the fundamental determinants of the safe, efficient, and flexible operation of the system. In that perspective, we have begun to explore what our experience has taught will be the most challenging aspects of designing and integrating human-centered automation in the advanced system. We have performed a full mission simulation looking at the role shift to self-separation on board the aircraft with the rules of the air guiding behavior and the provision of a cockpit display of traffic information and an on-board traffic alert system that seamlessly integrates into the TCAS operations. We have performed and initial investigation of the operational impact of "Dynamic Density" metrics on controller relinquishing and reestablishing full separation authority. (We follow the assumption that responsibility at all times resides with the controller.) This presentation will describe those efforts as well as describe the process by which we will guide the development of error tolerant systems that are sensitive to shifts in operator work load levels and dynamic shifts in the operating point of air traffic management.

Corker, Kevin M.↗
NASA NTRS1992

Sonic boom acceptability studies

The determination of the magnitude of sonic boom exposure which would be acceptable to the general population requires, as a starting point, a method to assess and compare individual sonic booms. There is no consensus within the scientific and regulatory communities regarding an appropriate sonic boom assessment metric. Loudness, being a fundamental and well-understood attribute of human hearing was chosen as a means of comparing sonic booms of differing shapes and amplitudes. The figure illustrates the basic steps which yield a calculated value of loudness. Based upon the aircraft configuration and its operating conditions, the sonic boom pressure signature which reaches the ground is calculated. This pressure-time history is transformed to the frequency domain and converted into a one-third octave band spectrum. The essence of the loudness method is to account for the frequency response and integration characteristics of the auditory system. The result of the calculation procedure is a numerical description (perceived level, dB) which represents the loudness of the sonic boom waveform.

Shepherd, Kevin P.↗
DOE OSTI2023

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Soyuz Landing Reconstructions

Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.

Preston Greenhalgh↗
NASA NTRS2020

Dose-Dependent Sensorimotor Impairment in Human Ocular Tracking After Acute Low-Dose Alcohol Administration

Changes in oculomotor behaviours are often used as metrics of sensorimotor disruption due to ethanol (EtOH); however, previous studies have focused on deficits at blood-alcohol concentrations (BACs) above about 0.04%.We investigated the dose dependence of the impairment in oculomotor and ocular behaviours caused by EtOH administration across a range of ultra-low BACs (≤0.035%).We took repeated measures of oculomotor and ocular performance from sixteen participants, both pre- and post-EtOH administration. To assess the neurological impacts across a wide range of brain areas and pathways, our protocol measured 21 largely independent performance metrics extracted from a range of behavioural responses ranging from ocular tracking of radial step-ramp stimuli, to eccentric gaze holding, to pupillary responses evoked by light flashes. Our results show significant impairment of pursuit and visual motion processing at 0.015% BAC, reflecting degraded neural processing within extrastriate cortical pathways. However, catch-up saccades largely compensate for the tracking displacement shortfall caused by low pursuit gain, although there still is significant residual retinal slip and thus degraded dynamic acuity. Furthermore, although saccades are more frequent, their dynamics are more sluggish (i.e. show lower peak velocities) starting at BAC levels as low as 0.035%. Small effects in eccentric gaze holding and no effect in pupillary response dynamics were observed at levels below 0.07%, showing the higher sensitivity of the pursuit response to very low levels of blood alcohol, under the conditions of our study.

visual motion processing↗
NASA NTRS2005

NASA Intelligent Systems Project: Results, Accomplishments and Impact on Science Missions

The Intelligent Systems Project was responsible for much of NASA's programmatic investment in artificial intelligence and advanced information technologies. IS has completed three major project milestones which demonstrated increased capabilities in autonomy, human centered computing, and intelligent data understanding. Autonomy involves the ability of a robot to place an instrument on a remote surface with a single command cycle. Human centered computing supported a collaborative, mission centric data and planning system for the Mars Exploration Rovers and data understanding has produced key components of a terrestrial satellite observation system with automated modeling and data analysis capabilities. This paper summarizes the technology demonstrations and metrics which quantify and summarize these new technologies which are now available for future Nasa missions.

Coughlan, Joseph C.↗
DOE OSTI2020

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Cognition in Space Workshop: Metrics and Models - 1

"Cognition in Space Workshop I: Metrics and Models" was the first in a series of workshops sponsored by NASA to develop an integrated research and development plan supporting human cognition in space exploration. The workshop was held in Chandler, Arizona, October 25-27, 2004. The participants represented academia, government agencies, and medical centers. This workshop addressed the following goal of the NASA Human System Integration Program for Exploration: to develop a program to manage risks due to human performance and human error, specifically ones tied to cognition. Risks range from catastrophic error to degradation of efficiency and failure to accomplish mission goals. Cognition itself includes memory, decision making, initiation of motor responses, sensation, and perception. Four subgoals were also defined at the workshop as follows: (1) NASA needs to develop a human-centered design process that incorporates standards for human cognition, human performance, and assessment of human interfaces; (2) NASA needs to identify and assess factors that increase risks associated with cognition; (3) NASA needs to predict risks associated with cognition; and (4) NASA needs to mitigate risk, both prior to actual missions and in real time. This report develops the material relating to these four subgoals.

Woolford, Barbara↗
DOE OSTI2025

Benchmarking CO₂ storage simulations: Results from the 11 th Society of Petroleum Engineers Comparative Solution Project

The 11 th Society of Petroleum Engineers Comparative Solution Project (shortened SPE11 herein) benchmarked simulation tools for geological carbon dioxide (CO 2 ) storage. A total of 45 groups from leading research institutions and industry across the globe signed up to participate, with 18 ultimately contributing valid results that were included in the comparative study reported here. This paper summarizes the SPE11 results. A comprehensive introduction and qualitative discussion of the submitted data are provided, together with an overview of online resources for accessing the full depth of data. A global metric for analyzing the relative distance between submissions is proposed and used to conduct a quantitative analysis of the submissions. This analysis attempts to statistically resolve the key aspects influencing the variability between submissions. The study shows that the major qualitative variation between the submitted results is related to thermal effects, dissolution-driven convective mixing, and resolution of facies discontinuities. Moreover, a strong dependence on grid resolution is observed across all three versions of the SPE11. However, our quantitative analysis suggests that the observed variations are predominantly influenced by factors not documented in the technical responses provided by the participants. We therefore identify that unreported variations due to human choices within the process of setting up, conducting, and reporting on the simulations underlying each SPE11 submission are at least as impactful as the computational choices reported.

Nordbotten, Jan M. [Univ. of Bergen (Norway); Norw↗
NASA NTRS2022

Astronaut Kinematics and Injury Risk for Piloted Lunar Landings and Launches While Standing

During future lunar missions, astronauts may be required to pilot vehicles while standing, and the associated kinematic and injury response is not well understood. In this study we used human body modeling to predict unsuited astronaut kinematics and injury risk for piloted lunar launches and landings in the standing posture. Three pulses (2-5 g; 10–150 ms rise times) were applied in 10 directions (vertical; ± 10-degree offsets) for a total of 30 simulations. Across all simulations, motion envelopes were computed to quantify displacement of the astronaut’s head (max 9.0 cm forward, 7.0 cm backward, 2.1 cm upward, 7.3 cm downward, 2.4 cm lateral) and arms (max 25 cm forward, 35 cm backward, 15 cm upward, 20 cm downward, 20 cm lateral). All head, neck, lumbar, and lower extremity injury metrics were within NASA’s tolerance limits, except tibia compression forces (0–1543 N upper tibia; 0–1482 N lower tibia; tolerance—1350 N) and revised tibia index (0.04–0.58 upper tibia; 0.03–0.48 lower tibia; tolerance—0.43) for the 2.7 g/150 ms pulse. Pulse magnitude and duration contributed over 80% to the injury metric values, whereas loading direction contributed less than 3%. Overall, these simulations suggest piloting a lunar lander vehicle in the standing posture presents a low risk of injury to the astronaut, although risk of tibia injury is potentially outside NASA’s acceptance limits and warrants further investigation.

Mitesh Lalwala↗
DOE OSTI2022

Prevalence and scalable control of localized networks

The ability to control network dynamics is essential for ensuring desirable functionality of many technological, biological, and social systems. Such systems often consist of a large number of network elements, and controlling large-scale networks remains challenging because the computation and communication requirements increase prohibitively fast with network size. Here, we introduce a notion of network locality that can be exploited to make the control of networks scalable, even when the dynamics are nonlinear. We show that network locality is captured by an information metric and is almost universally observed across real and model networks. In localized networks, the optimal control actions and system responses are both shown to be necessarily concentrated in small neighborhoods induced by the information metric. This allows us to develop localized algorithms for determining network controllability and optimizing the placement of driver nodes. This also allows us to develop a localized algorithm for designing local feedback controllers that approach the performance of the corresponding best global controllers, while incurring a computational cost orders-of-magnitude lower. Here, we validate the locality, performance, and efficiency of the algorithms in Kuramoto oscillator networks, as well as three large empirical networks: synchronization dynamics in the Eastern US power grid, epidemic spreading mediated by the global air-transportation network, and Alzheimer’s disease dynamics in a human brain network. Taken together, our results establish that large networks can be controlled with computation and communication costs comparable to those for small networks.

42 ENGINEERING↗
NASA NTRS2020

Evaluation Issues for a Flight Deck Interface; CAST SE-210 Output 2: Report 4 of 6

This report is part of a series of reports that addresses flight deck design and evaluation, written as a response to loss of control accidents. In particular, this activity is directed at failures in airplane state awareness, in which the pilot loses awareness of the airplane’s energy state or attitude and enters an upset condition. Another report in this series of reports speaks directly to flight deck evaluation methods and metrics for the types of attention and awareness issues that were revealed from the airplane state awareness events. In this report, we describe a wide range of flight deck evaluation issues tied to flight crew performance. The objectives are to establish a framework for thinking about how the flight deck interface should support the performance of the flight crew, and to aid the Federal Aviation Administration (FAA) in identifying relevant human performance issues during the evaluation/certification process. Issues are broken out into sections that cover physical ergonomics, design for usability, data integration and display content, attention and task management, flight crew problem solving, and flight crew teaming. For each issue, we recommend specific ways that the flight deck interface should support the flight crew. For each, we also identify existing 14 CFR Part 25 rules and guidance that are relevant to the issue. This allows the FAA to determine what current regulatory materials can support them in raising the issue with the applicant.

commercial aviation↗
NASA NTRS2025

Time Course of Effects of Carbon Dioxide Exposure on Physical and Cognitive Performance in a Simulated Surface Extravehicular Activity Contingency Scenario

INTRODUCTION Carbon dioxide (CO 2 ) is a metabolic byproduct produced by humans that must be scrubbed from the atmosphere by environmental control and life support systems in space vehicles and spacesuits to prevent buildup. Current nominal CO 2 limits are set by NASA Standard 3001, however, limits during contingency situations are not specified. The purpose of this study was to characterize and quantify the physiological, cognitive, and self-assessed symptom and performance metrics as a function of inspired CO 2 (P I CO 2 ) during a simulated 1-hour contingency lunar EVA scenario in virtual reality (VR). METHODS Fifteen healthy subjects completed 7 simulated EVA scenarios walking on a passive treadmill for one hour breathing dry, ambient air mixed with added CO 2 in a blind, counterbalanced manner (P I CO 2 : 0, 5, 10, 15, 20, 25, 30 mmHg) simulating a 2.0 km contingency EVA walkback to a habitat on the lunar surface in the event of a CO 2 scrubber malfunction. Subjects were immersed in a Lunar VR environment and asked to maintain their walking speed between 2.1 km/h and an upper limit individually calibrated to a fixed metabolic workload of 1.3 L/min of O 2 consumption, and performed periodic cognitive tasks and continuous cardiopulmonary measurements. Self-assessments of symptoms and task performance were measured via verbal Likert-scale survey at the onset of the walkback and at 10-minute intervals thereafter. RESULTS The time course of cardiopulmonary, cognitive, and self-reported responses at each level of P I CO 2 will be presented. All 15 subjects were able to complete the 1-hr walk back task at all CO 2 levels. Physiological responses were rapid, typically within 1 to 5 minutes. No effects of time were detected for cognitive measures. Symptomatic ratings of headache, shortness of breath, and fatigue demonstrated a time-course development, reaching asymptote after 40 minutes of CO 2 exposure. DISCUSSION These findings will inform the posture of risk associated with CO 2 exposure on human health and performance during microgravity and planetary surface operations, This will help inform decisions related to space suit and environmental life support hardware requirements and EVA operational limits for contingency extravehicular activity (EVA) scenarios.

carbon dioxide↗
DOE OSTI2023

Deep Reinforcement Learning for Resilient Power and Energy Systems: Progress, Prospects, and Future Avenues

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗