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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Usability Evaluation of Indicators of Energy-Related Problems in Commercial Airline Flight Decks

A series of pilot-in-the-loop flight simulation studies were conducted at NASA Langley Research Center to evaluate indicators aimed at supporting the flight crew’s awareness of problems related to energy states. Indicators were evaluated utilizing state-of-the-art flight deck systems such as on commercial air transport aircraft. This paper presents results for four technologies: (1) conventional primary flight display speed cues, (2) an enhanced airspeed control indicator, (3) a synthetic vision baseline that provides a flight path vector, speed error, and an acceleration cue, and (4) an aural airspeed alert that triggers when current airspeed deviates beyond a specified threshold from the selected airspeed. Full-mission high-fidelity flight simulation studies were conducted using commercial airline crews. Crews were paired by airline for common crew resource management procedures and protocols. Scenarios spanned a range of complex conditions while emulating several causal factors reported in recent accidents involving loss of energy state awareness by pilots. Data collection included questionnaires administered at the completion of flight scenarios, aircraft state data, audio/video recordings of flight crew, eye tracking, pilot control inputs, and researcher observations. Questionnaire response data included subjective measures of workload, situation awareness, complexity, usability, and acceptability. This paper reports relevant findings derived from subjective measures as well as quantitative measures.

Evans, Emory T.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18834-DND

This presentation will give an overview of the 20-plus years of pulsed transmit laser development at NASA Langley Research Center (LaRC) to enable a coherent Doppler wind lidar to measure global winds from earth orbit. Our group at LaRC has been developing the pulsed laser and other coherent lidar technologies for the global wind mission since the late 1980s. The causal path followed has been from space mission requirements to coherent lidar requirements to component requirements to technology development and finally to ground and aircraft validation. We will describe the development and deployment of Doppler Aerosols Wind Lidar (DAWN) for airborne measurement of wind velocity and direction. The will also present the status of ongoing fully conductively-cooled 2-micron wind lidar transmitter for NASA 3-D winds mission.

Upendra N Singh↗
NASA NTRS2014

TPSAS-NF1676L-18905-DND

Aircraft loss of control is a leading cause of fatal accidents across all transport airplane and operational classes. Aircraft loss-of-control (LOC) accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents. This presentation will define LOC as a dynamics and control problem, summarize LOC accident analysis results, and discuss current NASA research that supports a holistic approach for significantly reducing aircraft LOC accidents for current and future aircraft. The approach includes onboard systems technologies for LOC prevention and recovery, as well as a parallel effort for their validation. The onboard systems technologies provide improved situational awareness, guidance, and control under realistic LOC hazards, and include: hazards effects detection and mitigation; upset detection, prevention and recovery; and multiple hazards mitigation. Validation technologies include analytical, simulation, and experimental methods, tools and testbeds as well as the development of a comprehensive set of realistic LOC test scenarios. Future research directions will also be discussed.

Christine Belcastro↗
NASA NTRSDate not supplied

A Statistical Analysis of Impact Ice Adhesion Strength Data Acquired with a Modified Lap Joint Test

Numerous methodologies have been utilized to measure the adhesion strength of impact ice, and the data reported in the literature varies significantly from method to method. In order to initiate an investigation to determine the cause of this disparity, a lap-joint shear test methodology that was recently developed was utilized in the Icing Research Tunnel at the NASA Glenn Research Center. Data was obtained while varying the temperature, test section velocity, liquid water content, and cloud droplet median volumetric diameter, among other parameters, over five campaigns. A new data set acquired using this new test method is presented. The results are analyzed with standard statistical methodologies and demonstrate a strong correlation between the apparent adhesion strength of ice and temperature, annealing time, and heating time. Observations during the test and analysis of the results suggest the presence of large residual stresses in the samples, which is in agreement with prior work. Due to the nature of the test methodology, and all known ice adhesion test methodologies, the measured, or apparent, adhesion strength is geometry dependent, a fact emphasized by the results presented here. The data was organized both cumulatively and independently by result code. Trends in the data are discussed in the context of causal physical mechanisms. The data shows the apparent adhesion strength was not linear with temperature, liquid water content, annealing time, and other variables. Short-term heating of the samples was shown to have negligible effect, and the apparent adhesion strength had a flat trend with velocity.

Ice Adhesion↗
NASA NTRSDate not supplied

Preliminary Design of an 'Autonomous Medical Response Agent' Interface Prototype for Long Duration Spaceflight

Major challenges for astronauts in future long-duration exploration missions (LDEMs) will be that crewmembers are not expected to be medical professionals, may be under high workload and stress, are facing physiological challenges caused by spaceflight, and will have limited, delayed voice communications with medical support from Earth. An autonomous medical response agent (AMRA) is envisioned to help astronauts address medical complaints, develop a differential diagnosis, and guide self-treatment until a healthy state is restored. AMRA develops a process of personalized diagnosis and treatment through a Bayesian predictive control system that recommends therapeutic control actions including diagnostic tests and treatments to crewmembers (Menon, 2020). The Human Computer Interaction (HCI) lab from NASA Ames Research Center’s Human Systems Integration Division (Code TH) has collaborated with Nahlia Inc in human-centered design augmentation research for AMRA. The project, titled Design of ‘Autonomous Medical Response Agent Interface Prototype for Long Duration Spaceflight, has been funded by the Translational Research Institute for Space Health (TRISH) and introduces an interactive user-interface prototype that guides astronauts through self-diagnosis, treatment, and rehabilitation while communicating with remote specialists in ground support (most notably a patient’s flight surgeon). Our project develops the interaction design for the crewmember using AMRA through user research, iterative design, and usability testing to evaluate the user interface and workflow designed. The interface design deliverable for this project, titled AMRA Aggregate Information Display (AMRA AID) is an integrated information display system for comprehensive autonomous medical guidance, diagnosis, and treatment of in-flight medical conditions experienced by crewmembers. AMRA AID demonstrates how we might ensure crew autonomy, increase the crew’s medical capabilities, and decrease cognitive burden within a front-end user interface. AMRA AID refrains from relying on input from ground or mission control for self-treatment of medical issues—though ground awareness and communication with ground is maintained as a means of ensuring trust between mission control and crew. AMRA AID demonstrates how the crew’s on-board medical system might integrate with information from vehicle monitoring and crew schedule, without assuming causal relationships. AMRA AID’s comprehensive view enables efficient information access for both crew and ground support, reducing cognitive burden in the event of an unplanned or emergency medical incident and enabling informed analytical decisions to be made based on both crew and vehicle health. Human-centered design augmentation advanced within the prototype included: enhanced workflow and treatment guidance for two medical scenarios for a non-specialist user base with various levels of medical training, interaction design which considered speech (conversational user interface) elements and on-screen interactions to be developed in future iterations of the project, communication design and functional requirements relevant to self-care versus caring for another astronaut, as well as user testing of the prototype with an international space medical community. This project arrives at critical findings regarding usability needs, communication requirements, and integrated information requirements for a future technology interface functioning to increase confidence between ground support and LDEM crewmembers.

TRISH↗
NASA NTRSDate not supplied

Predicting Cognitive States Using Machine Learning Fusion Paradigms to Reduce Model Uncertainty

The development of a synergetic system between humans and technology is a challenge that the scientific community has been facing for many years. Our aeronautic research aims to enhance this synergy between humans and machines through predictive human performance modeling for systems to mitigate high-risk situations. By being able to predict and anticipate human states, the crew monitoring system should be able to adjust and support the pilot for aviation safety. Our work focusing on attention-related human performance-limiting states (AHPLS) that impact a pilot’s performance and introduce high-risk catastrophic situations [1]. For example, AHPLS has been cited as a causal factor in more than 50% of all loss control in flight and thus contributes significantly toward commercial aviation fatalities [1, 2]. Cognitive state and its physiological fingerprint can be valuable information for this detecting AHPLS, but human cognitive state detection is still a major limitation for these crew monitoring systems.

machine learning↗
NASA NTRS2008

The impact of hydrogen contamination on the Total Dose Response of Linear Bipolar Microcircuits

Recent enhanced low dose rate sensitivity (ELDRS) investigations carried out by RLP Research, Crane, Arizona State University (ASU), and Jet Propulsion Laboratory (JPL) have shown significant differences in the degradation of bipolar microcircuits with total dose in the presence of molecular hydrogen (H2) in packages. This has a significant impact on radiation hardness assurance and opens up opportunity to improve device performance. The objectives of this program are 1) to investigate and confirm the causal relationship between packaging recipes, hydrogen contamination, and total dose response of linear bipolar microcircuits; and 2) to develop a guideline that will take into account these effects at the radiation level for future NASA space missions. This program is geared to benefit all future NASA space missions using bipolar or BiCMOS linear devices.

McClure, Steve S.↗
NASA NTRS1999

Constraint-free Theories of Gravitation

Lovelock actions (more precisely, extended Gauss-Bonnet forms) when varied as Cartan forms on subspaces of higher dimensional flat Riemannian manifolds, generate well set, causal exterior differential systems.

gravitation↗
NASA NTRS2020

Behavior modeling for cybersecurity

In this paper, we elaborate on the key actors within the context of the cyber world at the Jet Propulsion Laboratory and use Bayesian Belief Networks to represent the causal and probabilistic relationships between the various elements that affect an actor and the likelihood of exploits and adverse consequences that can occur due to an exploit. We assess the effectiveness of each of the mitigative methods and the sensitivity of the system to each of the aggravating as well as mitigative factors. We use a combination of objective incident data and Subject Matter Expert knowledge as input to these models.

King, James↗
NASA NTRSDate not supplied

An Approach for Identifying IASMS Services, Functions, and Capabilities From Data Sources

Assuring safety in the NAS with the inclusion of new entrants that are part of Advanced Air Mobility (AAM) will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using semi-autonomous/autonomous vehicles. Overcoming these AAM safety assurance challenges is the focus of the In-time Aviation Safety Management System (IASMS). The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs)designed to manage operational risks, identify unknown risks, and inform system design to mitigate risk. This paper describes a broad approach for identifying SFCs involving technology trends in research, assessment of known and unknown risks in safety reports, and causal and contributing factors in aviation accidents and incidents. This approach leverages these sources to identify potential SFCs that enable the Monitor, Assess, and Mitigate (M-A-M)functionality that represents the enabling framework of the IASMS.

Kyle Ellis↗
NASA NTRSDate not supplied

Calibration of Landsat 8 Aquatic Reflectance Band Data to Spatial Variations in Chlorophyll a, Suspended Sediment, N, and P in Coastal Estuaries of Southern Louisiana

Nutrient enrichment of coastal estuaries is a proven causal agent of harmful algal blooms, fish kills, and hypoxic zones. To enable regional mapping in coastal estuaries of southern Louisiana of Chlorophyll a, suspended sediment, N, and P concentrations, monthly water sample data collected at over 30 stations along a 129 km transect in the Barataria Basin by Turner et al. (2019) were correlated with Landsat 8 aquatic reflectance (ar) band 3 and 4 image data (2013-2016). Results showed significant non-linear correlations (R2 > 0.2) of Landsat ar band 4 values with measured concentrations of Chlorophyll a, total suspended sediment, N, and P. The strongest correlations were revealed between Landsat ar band 4 reflectances and total P concentrations, periodically at R2 values > 0.6. Landsat ar band images revealed detailed variations in total N and P concentrations that were consistent with the measured nutrient declines associated with dilution of freshwater as sampling locations progressed toward more coastal saline waters. Regional map images of ar band 4 in 2019 and 2020 confirmed that recent openings of Bonnet Carre Spillway could have resulted in damage to oyster beds in the brackish Gulf waters near Lake Borgne and the Mississippi River Delta, possibly due to reduced salinity levels and enhanced sediment deposition.

Calibration↗
NASA NTRSDate not supplied

The Sufficient Component Cause Model Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at low doses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗
NASA NTRSDate not supplied

NASA’s Identified Risks of Adverse Outcomes Due to Inadequate Human Systems Integration Architecture in Human Spaceflight

The NASA Human System Risk Board (HSRB) has the overall responsibility for tracking the evolution of the top ~30 human system risks that it has identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to mitigate those risks, and developing evidence-based risk posture recommendations. One of the identified risks is due to inadequate human systems integration architecture (HSIA) and a driving factor of this risk is that given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors. The HSRB uses Directed Acyclic Graphs (DAGs) as a communication tool for describing how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes and as the basis for understanding intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes. The HSIA risk DAG will be presented and described. Historically, critical malfunctions requiring Crew/MCC management occurred at a rate of 1.7 times per year for ISS averaged over the lifetime and 3-4 times per year in the burn in phase for the vehicle. These averages do not include EVA data, which greatly increases the incident rate. Prior experience from the Apollo program showed 10/11 crewed missions experienced significant anomalies where crew relied heavily on MCC expertise in real-time. These failure patterns are in line with those observed in other complex engineered systems (e.g., oil rigs, launch systems, commercial aviation, etc.) It is likely that general malfunction and error rates are > 10% for short duration missions (<30 days), based on past and current spaceflight operations data. Likelihood of adverse outcomes has the potential to increase as crew conduct work with new, complex systems and with less ground support. For Low Earth Orbit missions and Lunar missions less than 30 days, assuming minimal comm delays, disruptions and bandwidth limitations, malfunctions and errors can affect mission objectives and crew health but may be mitigated by ground support. For Lunar missions greater than 30 days and any potential Mars mission malfunctions and errors can have Loss of Crew and Loss of Mission consequences due to reduced ground support (communication delays, constraints and blackouts) for more complex operations, as well as reduced resupply and evacuation options.

Daniel M Buckland↗
NASA NTRS2022

In-Time Terminal Area Risk Management

In-Time Aviation Safety Management System (IASMS) for Commercial Operations Developing methods to Improve risk management and safety assurance processes by proactively identifying risks and causal factors before an accident/incident occurs.

Kyle Kent Edward Ellis↗
NASA NTRSDate not supplied

The Potential Outcome Model: Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at lowdoses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗
NASA NTRSDate not supplied

Lunar TLP's and the Tectonic Processes of the Earth and the Moon

We study the transient lunar phenomena (TLP) as an indicator of lunar tectonic. Seismic phenomena can be used as a direct indicator of some tectonic activities of the planets The Moon-Earth gravitational interaction has been studied extensively as a triggering mechanism to geodynamics. In this work, we study the reverse interaction Earth-Moon in relation to the TLP activities. The lunar outgassing potentially is the leading cause for TLP activities resulting from the lunar interior's dynamic mechanism. We have studied Earth venting and earthquakes processes and have found that radon was frequently activated before significant seismic events due to Moon-Sun interaction with Earth (Ouzounov et al., 2018). Earthquake lights, an associated phenomenon reported before some major earthquakes, are analog to TLP activities on the moon. In 1972, N. Kozyrev suggested a possible moon response to the significant seismic events on Earth. To understand whether TLP's activities have any possible connection with Earth geodynamics, we perform a statistical check between the significant seismic activities from the NEIC catalog and lunar TLPs for 1907-1977 for four lunar areas :Aristarchus, Plato, Gassendi, and Alphonsus. We use TLP compiled catalog based on Middlehurst et al. (1968), Cameron (2006a,b), and Crotts (2008) catalogs. Our results revealed a causal relationship between significant earthquakes and TLP events. However, this relation varies from the location and depth of the seismic events. Deformation triggers the degassing process, and TLPs are indicators for those underlying activities. Our work can provide new information about the origin of TLP and the existence of a possible relationship between the tectonic processes of Earth and the Moon.

D Ouzonov↗
NASA NTRSDate not supplied

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗
NASA NTRSDate not supplied

NASA's Identified Risk of Adverse Outcomes due to Inadequate Human Systems Integration Architecture

The NASA Human System Risk Board (HSRB) is responsible for tracking the evolution of the top ~30 human system risks identified to be associated with human spaceflight. As part of this process, the Board is charged with maintaining a consistent, integrated process to evaluate those risks and developing evidence-based risk posture recommendations. Risks are ranked by likelihood and consequence. Intermediate causal relationships between risk contributing factors and countermeasures that link hazards to outcomes are described using Directed Acyclic Graphs (DAGs). The DAGs are also useful for identifying common factors and countermeasures across the top 30 risks as well as communicating how astronaut exposure to spaceflight hazards leads to meaningful mission-level health and performance outcomes. One of the top risks tracked by the HSRB is The Risk of Adverse Outcomes Due to Inadequate Human-Systems Integration Architecture (HSIA). This risk captures the possibility that due to decreasing real-time ground support during missions beyond LEO, crew will be unable to adequately respond to unanticipated critical malfunctions or detect safety-critical procedural errors. The HSIA risk is ranked red (high) for Lunar surface and Mars missions due to the probability of Loss of Crew and Loss of Mission consequences. This paper describes the evidence that supports the HSIA risk ranking and presents the central narrative of the HSIA risk DAG-- i.e., anomaly detection, diagnosis, intervention, and task performance. Characterizations of the current state of practice for each of the DAG’s central nodes and the future tools needed for successful anomaly response are provided.

human-systems integration architecture↗