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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

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRS1983

Functional language and data flow architectures

This is a tutorial article about language and architecture approaches for highly concurrent computer systems based on the functional style of programming. The discussion concentrates on the basic aspects of functional languages, and sequencing models such as data-flow, demand-driven and reduction which are essential at the machine organization level. Several examples of highly concurrent machines are described.

Ercegovac, M. D.↗
NASA NTRS1988

Calibration support for the Earth Observing System Project

The Earth Observing System Project (EOS) program guidelines establishes significantly more stringent requirements on calibrations of instruments. This requirement is driven by the need for long-term continuity of acquired data sets and the use of measurements in interdisciplinary investigations. Personnel from the Standards and Calibration Office have been supporting the Program and Project in interpreting these goals into specific requirements. Contributions to EOS have included participation in the Panel of Experts which produced a list of consensus items necessary for accomplishing an accurate calibration and suggested EOS Project Calibration Policy, and drafting the announcement of opportunity and bidders information package positions on instrument calibration and data product validation. Technical staffing was provided to the NASA delegates to the Committee on Earth Orbiting Satellites (club of space-faring nations) for the standing working group on Calibration and Data Validation.

Guenther, B. W.↗
NASA NTRS1991

Macintosh II based space Telemetry and Command (MacTac) system

The general architecture and the principal functions of the Macintosh II based Telemetry and Command system, presently under development, are described, with attention given to custom telemetry cards, input/output interfaces, and the icon driven user interface. The MacTac is a low-cost, transportable, easy to use, compact system designed to meet the requirements specified by the Consultative Committeee for Space Data Systems while remaining flexible enough to support a wide variety of other user specific telemetry processing requirements, such as TDM data. In addition, the MacTac can accept or generate forward data (such as spacecraft commands), calculate and append a Polynomial Check Code, and output these data to NASCOM to provide full Telemetry and Command capability.

Dominy, Carol T.↗
NASA NTRS1992

Microstructural development during directional solidification of peritectic alloys

Despite the widespread commercial use of peritectic alloys (e.g., steels, brass, bronze, intermetallic compounds, Co based superalloys and A3B type superconductors), the characterization of the microstructural development during directional solidification of peritectics has historically lagged behind similar efforts directed towards other types of binary invariant reactions such as eutectic or monotectic. A wide variety of possible microstructures has been shown to form in peritectics depending upon the imposed temperature gradient, G, the solidification velocity, V, as well as the presence or absence of convection in the melt. This has important technological implications since many commercially important alloys exhibit peritectics and processing methods such as casting and welding often involve widely changing conditions. It has been the aim of this project to examine, in a systematic fashion, both experimentally and theoretically, the influence of gravitationally driven convection on segregation and microstructural development during solidification in peritectic systems under terrestrial conditions. The scientific results of the project will be used to establish ground based data in support of a meaningful microgravity flight experiment.

Lograsso, Thomas A.↗
NASA NTRS2012

Automation of Hubble Space Telescope Mission Operations

On June 13, 2011, after more than 21 years, 115 thousand orbits, and nearly 1 million exposures taken, the operation of the Hubble Space Telescope successfully transitioned from 24x7x365 staffing to 815 staffing. This required the automation of routine mission operations including telemetry and forward link acquisition, data dumping and solid-state recorder management, stored command loading, and health and safety monitoring of both the observatory and the HST Ground System. These changes were driven by budget reductions, and required ground system and onboard spacecraft enhancements across the entire operations spectrum, from planning and scheduling systems to payload flight software. Changes in personnel and staffing were required in order to adapt to the new roles and responsibilities required in the new automated operations era. This paper will provide a high level overview of the obstacles to automating nominal HST mission operations, both technical and cultural, and how those obstacles were overcome.

Burley, Richard↗
NASA NTRS2014

Validation of the 5th and 95th Percentile Hybrid III Anthropomorphic Test Device Finite Element Model

NASA spacecraft design requirements for occupant protection are a combination of the Brinkley criteria and injury metrics extracted from anthropomorphic test devices (ATD's). For the ATD injury metrics, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Furthermore, each of these ATD's is required to be fitted with an articulating pelvis and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. The requirements require that physical testing be performed with both ATD's to demonstrate compliance. Before compliance testing can be conducted, extensive modeling and simulation are required to determine appropriate test conditions, simulate conditions not feasible for testing, and assess design features to better ensure compliance testing is successful. While finite element (FE) models are currently available for many of the physical ATD's, currently there are no complete models for either the 5th percentile female or the 95th percentile male Hybrid III with a straight spine and articulating pelvis. The purpose of this work is to assess the accuracy of the existing Livermore Software Technology Corporation's FE models of the 5th and 95th percentile ATD's. To perform this assessment, a series of tests will be performed at Wright Patterson Air Force Research Lab using their horizontal impact accelerator sled test facility. The ATD's will be placed in the Orion seat with a modified-advanced-crew-escape-system (MACES) pressure suit and helmet, and driven with loadings similar to what is expected for the actual Orion vehicle during landing, launch abort, and chute deployment. Test data will be compared to analytical predictions and modelling uncertainty factors will be determined for each injury metric. Additionally, the test data will be used to further improve the FE model, particularly in the areas of the ATD neck components, harness, and suit and helmet effects.

Lawrence, C.↗
NASA NTRSDate not supplied

Solar Migrating Diurnal Tide in the Upper Mesosphere and Lower Thermosphere from SD-WACCM-X, Aura/MLS, and TIMED/SABER

Solar heating on the rotating Earth is a fundamental forcing of atmospheric tidal waves. The migrating diurnal tide, propagating from the troposphere to the upper mesosphere and lower thermosphere, is a large global disturbance that drives most of the daily variations in dynamics, thermal structures, chemistry, as well as atmospheric compositions. In this study, we present a comprehensive analysis of the (1,1) propagating diurnal tides derived from multi-year MLS and SABER observations, to characterize and better understand interannual and long-term tidal variability in the upper atmosphere. Although the (1,1) tide is driven by the solar heating, its interannual variations are largely determined by the internal variability of Earth’s climate system. The tidal amplitudes derived from MLS and SABER data agree well with each other in terms of monthly climatology and interannual variations, showing a consistent seasonal cycle and modulations from the Quasi Biennial Oscillation (QBO). The Ensemble Empirical Mode Decomposition (EEMD) analysis, employed to extract the low frequency variations, also reveals an ENSO-like (42 months) influence on tidal amplitudes in the upper mesosphere. While their (1,1) tidal amplitudes are less affected by the solar cycle, the mean mixing ratio of carbon monoxide (CO) and ozone (O3) is significantly modulated by the 11-year solar cycle due to their UV-dependent photochemistry.

mesosphere↗
NASA NTRS2019

Cognitive Communications for NASA Space Systems

The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗
NASA NTRS2011

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

clouds↗
NASA NTRS2009

The Interannual Stability of Cumulative Frequency Distributions for Convective System Size and Intensity

The characteristics of convective system populations in West Africa and the western Pacific tropical cyclone basin were analyzed to investigate whether interannual variability in convective activity in tropical continental and oceanic environments is driven by variations in the number of events during the wet season or by favoring large and/or intense convective systems. Convective systems were defined from Tropical Rainfall Measuring Mission (TRMM) data as a cluster of pixels with an 85-GHz polarization-corrected brightness temperature below 255 K and with an area of at least 64 square kilometers. The study database consisted of convective systems in West Africa from May to September 1998-2007, and in the western Pacific from May to November 1998-2007. Annual cumulative frequency distributions for system minimum brightness temperature and system area were constructed for both regions. For both regions, there were no statistically significant differences between the annual curves for system minimum brightness temperature. There were two groups of system area curves, split by the TRMM altitude boost in 2001. Within each set, there was no statistically significant interannual variability. Subsetting the database revealed some sensitivity in distribution shape to the size of the sampling area, the length of the sample period, and the climate zone. From a regional perspective, the stability of the cumulative frequency distributions implied that the probability that a convective system would attain a particular size or intensity does not change interannually. Variability in the number of convective events appeared to be more important in determining whether a year is either wetter or drier than normal.

Mohr, Karen I.↗
NASA NTRS2011

Planetary Education and Outreach Using the NOAA Science on a Sphere

Science On a Sphere (SOS) is a large visualization system, developed by the National Oceanic and Atmospheric Administration (NOAH), that uses computers running Redhat Linux and four video projectors to display animated data onto the outside of a sphere. Said another way, SOS is a stationary globe that can show dynamic, animated images in spherical form. Visualization of cylindrical data maps show planets, their atmosphere, oceans, and land, in very realistic form. The SOS system uses 4 video projectors to display images onto the sphere. Each projector is driven by a separate computer, and a fifth computer is used to control the operation of the display computers. Each computer is a relatively powerful PC with a high-end graphics card. The video projectors have native XGA resolution. The projectors are placed at the corners of a 30' x 30' square with a 68" carbon fiber sphere suspended in the center of the square. The equator of the sphere is typically located 86" off the floor. SOS uses common image formats such as JPEG, or TIFF in a very specific, but simple form; the images are plotted on an equatorial cylindrical equidistant projection, or as it is commonly known, a latitude/longitude grid, where the image is twice as wide as it is high (rectangular). 2048x] 024 is the minimum usable spatial resolution without some noticeable pixelation. Labels and text can be applied within the image, or using a timestamp-like feature within the SOS system software. There are two basic modes of operation for SOS: displaying a single image or an animated sequence of frames. The frame or frames can be setup to rotate or tilt, as in a planetary rotation. Sequences of images that animate through time produce a movie visualization, with or without an overlain soundtrack. After the images are processed, SOS will display the images in sequence and play them like a movie across the entire sphere surface. Movies can be of any arbitrary length, limited mainly by disk space and can be animated at frame rates up to 30 frames per second. Transitions, special effects, and other computer graphics techniques can be added to a sequence through the use of off-the-shelf software, like Final Cut Pro. However, one drawback is that the Sphere cannot be used in the same manner as a flat movie screen; images cannot be pushed to a "side", a highlighted area must be viewable to all sides of the room simultaneously, and some transitions do not work as well as others. We discuss these issues and workarounds in our poster.

Simon-Miller, A. A.↗
NASA NTRS2023

Robotic and Crewed Mars Missions Increasing the Demand for Planetary Protection Technology Needs

Planetary protection (PP) policy seeks to avoid harmful contamination by limiting biological and relevant organic contamination from spacecraft as well as preventing adverse changes to Earth’s biosphere when extraterrestial samples are brought back to Earth. The PP policy at NASA was updated in 2021 (NPR 8715.24) and 2022 (NASA-STD-8719.27) to enable missions by expanding the decades old prescriptive requirements to allow for an option of adopting performance-based requirements that are objectivesdriven, risk-informed and case-assured. In parallel, the final PP knowledge gap workshop was completed representing the international consensus on the key areas to be considered in developing crew PP policy. These knowledge gaps focused on key technology development areas in 1) microbial and human health monitoring, 2) technical and operations needed for contamination control and 3) natural transport of contamination on Mars. As robotic missions start to implement performance-based approaches and research and technology efforts commence to inform crew policy the demand for data quality driven verification and validation in relevant space environments. Examples of the types of testing that is envisioned includes test as you fly validation and verification of decontamination systems in a relevant on-orbit and Mars environment, developing lethality curves of terrestrial organisms to further our understanding of the biocidal impacts of Mars and the space environment, and particle transport model validation and verification. Thus, the PP discipline has identified the need for groundbased space environments to perform preliminary testing as validation and verification of flight systems and to advance the technology readiness level prior to further testing on-orbit or lunar environments to prepare for Mars.

J. Nick Benardini↗
NASA NTRSDate not supplied

Robotic and Crewed Mars Missions Increasing the Demand for Planetary Protection Technology Needs

Planetary protection (PP) policy seeks to avoid harmful contamination by limiting biological and relevant organic contamination from spacecraft as well as preventing adverse changes to Earth’s biosphere when extraterrestrial samples are brought back to Earth. The PP policy at NASA was updated in 2021 (NPR 8715.24) and 2022 (NASA-STD-8719.27) to enable missions by expanding the decades old prescriptive requirements to allow for an option of adopting performance-based requirements that are objectives-driven, risk-informed and case-assured. In parallel, the final PP knowledge gap workshop was completed representing the international consensus on the key areas to be considered in developing crew PP policy. These knowledge gaps focused on key technology development areas in 1) microbial and human health monitoring, 2) technical and operations needed for contamination control and 3) natural transport of contamination on Mars. As robotic missions start to implement performance-based approaches and research and technology efforts commence to inform crew policy the demand for data quality driven verification and validation in relevant space environments. Examples of the types of testing that is envisioned includes test as you fly validation and verification of decontamination systems in a relevant on-orbit and Mars environment, developing lethality curves of terrestrial organisms to further our understanding of the biocidal impacts of Mars and the space environment, and particle transport model validation and verification. Thus, the PP discipline has identified the need for ground-based space environments to perform preliminary testing as validation and verification of flight systems and to advance the technology readiness level prior to further testing on-orbit or lunar environments to prepare for Mars.

J Nick Benardini↗
NASA NTRS2019

Flash Drought as Captured by Reanalysis Data: Disentangling the Contributions of Precipitation Deficit and Excess Evapotranspiration

Flash droughts – uncharacteristically rapid dryings of the land system – are naturally associated with extreme precipitation deficits. Such precipitation deficits, however, do not tell the whole story, for land surface drying can be exacerbated by anomalously high evapotranspiration (ET) rates driven by anomalously high temperatures (e.g., during heatwaves), anomalously high incoming radiation (e.g., from reduced cloudiness), and other meteorological anomalies. In this study, the relative contributions of precipitation and ET anomalies to flash drought generation in the Northern Hemisphere are quantified through the analysis of diagnostic fields contained within the MERRA-2 reanalysis product. Unique to the approach is the explicit treatment of soil moisture impacts on ET through relationships diagnosed from the reanalysis data; under this treatment, an ET anomaly that is negative relative to the local long-term climatological mean is still considered positive in terms of its contribution to a flash drought if it is high for the concurrent value of soil moisture. Maps produced in the analysis show the fraction of flash drought production stemming specifically from ET anomalies and illustrate how ET anomalies for some droughts are related to temperature and radiation anomalies. While ET is found to have an important impact on flash drought production in the central US and in parts of Russia known from past studies to be prone to heatwave-related drought, and while this impact does appear stronger during the onset (first several days) of flash droughts, overall the contribution of ET to these droughts is small relative to the contribution of precipitation deficit.

R D Koster↗
NASA NTRS2010

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Narasimhan, Sriram↗