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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
DOE OSTI2022

FTICR-MS, Sensor, and Environmental Data from 5 Streams Impacted by the 2020 Holiday Farm Fire Associated with: "Spatiotemporal controls on the delivery of dissolved organic matter to streams following a wildfire"

This data package is associated with the publication "Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire" submitted to Geophysical Research Letters (Roebuck et al., 2022). The study aims to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples (24 samples in 1-hour intervals) were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. The samples were collected in November 2020 during the first major storm pulse following the conclusion of the wildfire. Samples were characterized for dissolved organic carbon, total dissolved nitrogen, and by ultra-high resolution mass spectrometry. In situ turbidity data also collected.This data package contains 4 primary folders that include the following: 1) Metadata, 2) EnvData (Environmental Data), 3) SensorData, and 4) FTICR_SupportingData. The package contains a single file-level metadata (flmd) file. Each primary folder also contains individual data dictionaries (dd) to define and provide descriptors of column/row headers and data flags. The FTICR_SupportingData, folder 4, contains raw, unprocessed FTICR-MS Data files in addition to a csv containing processed FTICR-MS data. This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development and Characterization of Cementitious Waste Forms for Immobilization of Granular Activated Carbon, Silver Mordenite, and HEPA Filter Media Solid Secondary Waste

At the Department of Energy’s Hanford site, over 53 million gallons of chemically complex and radioactive wastes have been stored in 177 underground tanks. The Hanford Tank Waste Treatment and Immobilization Plant (WTP) is under construction and is designed to treat and immobilize these wastes. During operations of WTP, solid secondary wastes (SSWs) will be generated as a result of waste treatment, vitrification, off-gas management, and supporting process activities. SSW treatment processes and resulting disposal pathways for the final disposition form of the SSW are needed to support direct feed low activity waste (DFLAW) operations and facilitate continued operation of WTP. The SSWs produced through WTP operations are expected to include used process equipment, contaminated tools and instruments, decontamination wastes, high-efficiency particulate air (HEPA) filters, carbon absorption beds (granular activated carbon, GAC), silver mordenite (AgM) and spent ion-exchange resins. These waste streams are planned to be immobilized in a cementitious waste form and disposed of either as stabilized/blended (non-debris) or encapsulated (debris) in a cementitious waste form. Accordingly, cementitious waste forms from these streams were included in the 2017 Integrated Disposal Facility (IDF) Performance Assessment (PA). The input data used to represent these SSW forms in the 2017 IDF PA involved many assumptions and associated uncertainties. This data limitation was due to the lack of material- and site-specific data available for representative SSW materials in cementitious matrices. To verify the assumed values used in the IDF PA and fill this limitation in available data, Washington River Protection Solutions, LLC (WRPS), has initiated a program targeted toward gathering site specific data relevant to Hanford SSW disposal. The work within this report is a continuation of this ongoing program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1995

An estimate of solar wind velocity profiles in an coronal hole and a coronal streamer area (6-40 solar radius)

Using the total electron content data obtained by the Ulysses Solar Corona Experiment during the superior solar conjunction in summer 1991, we selected two data sets, one associated with a coronal hole and the other one with coronal streamer crossings. By doing this data splitting, we find two entirely different density profiles varying as r(exp -2.7) and r(exp -2.3) for the coronal hole and coronal streamers, respectively. Assuming mass flux conservation from the inner corona to one AU, an estimate for the velocity profiles or acceleration in these two different regions can be determined. The more negative exponent of the coronal hole density profile indicates a more extended heating and acceleration region or more flaring, or both. Various possible explanations will be discussed.

Paetzold, M.↗
NASA NTRS1995

An Estimate of Solar Wind Velocity Profiles in a Coronal Hole and a Coronal Streamer Area (6-40 R(radius symbol)

Total electron content data obtained from the Ulysses Solar Corona Experiment (SCE) in 1991 were used to select two data sets, one associated with a coronal hole and the other with coronal streamer crossings. (This is largely equatorial data shortly after solar maximum.) The solar wind velocity profile is estimated for these areas.

solar corona solar wind coronal streamer Ulysses↗
DOE OSTI2025

Data from: “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”

This dataset is associated with the manuscript “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”. Bald cypress “knees” (aboveground woody roots) have been shown to contribute to wetland methane (CH4) efflux, with large variation within and between studies. To explain this variation, we investigated spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH4 fluxes from knees. Methane fluxes were collected from September 2022 to August 2024 at three locations in western Kentucky, USA, within the Mississippi Alluvial Valley: a main channel (semi-permanently flooded), side channel (seasonally flooded), and reservoir edge (artificially flooded). Knee CH4 fluxes (“Ross_et_al_Knee_Flux_Data.csv”) were measured from multiple heights on knees (20, 40, and 60 cm) of various sizes (knee straight height ranged from 24 to 93 cm) using a LiCOR LI-7810 CH4/CO2/H2O Trace Gas Analyzer. The dataset also includes environmental variables collected with each knee measurement, including water level adjusted for knee-to-knee elevational differences, subsurface and air temperature, and humidity. Soil CH4 fluxes (“Ross_et_al_Soil_Flux_Data.csv”) were also collected adjacent to knees (starting in April 2023) when water levels didn’t overtop soil collars, using a LiCOR Smart Chamber and calculated in SoilFluxPro software. The soil flux dataset includes associated variables collected by the Smart Chamber. Three separate files (“*_Water_Level.csv”) are included for water level and subsurface temperature data collected at each site using HOBO U20L barometric pressure loggers. Each file type (knee flux, soil flux, water level) has an associated data dictionary (“*_dd.csv”). For specifics on methodology used and calculations, see the associated manuscript. The R script includes code used for figures and analyses reported in the manuscript.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Dual S and Ku-band tracking feed for a TDRS reflector antenna

The results are presented of a trade study designed to identify a synchronous satellite antenna system suitable for receiving and transmitting data from lower orbiting satellites at both S- and K sub u-bands simultaneously as part of the Tracking and Data Relay Satellite System. All related problems associated with maintaining a data link between two satellites with a K sub u-band half-power beamwidth of 0.4 db are considered including data link maintenance techniques, beam pointing accuracies, gimbal and servo errors, solar heating, angle tracking schemes, acquisition problems and aids, tracking accuracies versus SNR, antenna feed designs, equipment designs, weight and power budgets, and detailed candidate antenna system designs.

Pullara, J. C.↗
NASA NTRS1982

Correlated Birkeland current signatures from the TRIAD and Magsat magnetic field data

Transverse magnetic disturbances associated with Birkeland currents have been measured by the Magsat and TRIAD spacecraft, whose orbits were nearly coplanar from November to mid-December, 1979. A comparison of data received when the satellites were over the TRIAD/Chatanika receiving station shows that 75% of magnetic disturbance measurements are similar in shape and magnitude, with TRIAD peak disturbances being on average 7% larger than those of Magsat. This discrepancy is lower than measurement uncertainties due to baselines and calibration. During periods of higher Kp, despite time separations of as much as 45 min, better agreement is found in the large-scale and well-defined field-aligned current signatures.

Zanetti, L. J.↗
NASA NTRS2011

EOS MLS Level 1B Data Processing Software

This software is an improvement on Version 2, which was described in EOS MLS Level 1B Data Processing, Version 2.2, NASA Tech Briefs, Vol. 33, No. 5 (May 2009), p. 34. It accepts the EOS MLS Level 0 science/engineering data, and the EOS Aura spacecraft ephemeris/attitude data, and produces calibrated instrument radiances and associated engineering and diagnostic data. This version makes the code more robust, improves calibration, provides more diagnostics outputs, defines the Galactic core more finely, and fixes the equator crossing. The Level 1 processing software manages several different tasks. It qualifies each data quantity using instrument configuration and checksum data, as well as data transmission quality flags. Statistical tests are applied for data quality and reasonableness. The instrument engineering data (e.g., voltages, currents, temperatures, and encoder angles) is calibrated by the software, and the filter channel space reference measurements are interpolated onto the times of each limb measurement with the interpolates being differenced from the measurements. Filter channel calibration target measurements are interpolated onto the times of each limb measurement, and are used to compute radiometric gain. The total signal power is determined and analyzed by each digital autocorrelator spectrometer (DACS) during each data integration. The software converts each DACS data integration from an autocorrelation measurement in the time domain into a spectral measurement in the frequency domain, and estimates separately the spectrally, smoothly varying and spectrally averaged components of the limb port signal arising from antenna emission and scattering effects. Limb radiances are also calibrated.

Perun, Vincent S.↗
NASA NTRS2020

TESS Data Release Notes: Sector 21 DR 29

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel les, light curve les, collateral pixel les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

Michael M. Fausnaugh↗
DOE OSTI2021

SFA-VirOmics

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information. PNNL’s Soil Microbiome SFA Virome Dataset Annotation page is an extension to the PNNL Soil Microbiome SFA repository on DataHub allows for exploring and downloading integrated experimental omics dataset annotations, associated experimental metadata, pre- and post-processed viral data files, and other associated materials directly related to experimental viral project data.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

Bosworth, Edward L., Jr.↗
DOE OSTI2020

My vehicle is a data mine

In this talk we explore how analysis of vehicle data provides information of individual vehicle behaviors, information of other vehicles in the flow of traffic, and insights into the behavior of drivers. Over the last two decades traditional passenger vehicles have been transformed from integrated two-port electrical nodes to cyber-physical systems of communicating computational nodes whose individual state and control variables are shared on a standard controller area network (CAN) bus. As driver assistance systems have crept into vehicles as safety features, driver behaviors can be observed through analysis of the data streams on the CAN bus as these new nodes communicate with one another. The properties of these data streams, as well as architectures and approaches to gather the data, are important to consider when drawing conclusions on the relevance of the data in making decisions at varying levels of the information hierarchy. We will demonstrate several technical challenges associated with these data collection processes, as well as preliminary results that demonstrate application relevance of the data to behavior, traffic, and systems domains.

42 ENGINEERING↗
DOE OSTI2020

Processor and method of weighted feature importance estimation

A method includes determining a feature importance ranking for each pair of clusters of a plurality of clusters to generate a first plurality of feature importance rankings. The method further includes determining a feature importance ranking between a particular data element and each cluster to generate a second plurality of feature importance rankings. A distance value associated with each pair of clusters of the plurality of clusters is determined to generate a plurality of distance values, and a probability value associated with each data element is determined to generate a plurality of probability values. The method further includes weighting the first plurality of feature importance rankings based on the plurality of distance values to determine a first plurality of weighted feature importance rankings and weighting the second plurality of feature importance rankings based on the plurality of probability values to determine a second plurality of weighted feature importance rankings.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

RadLab and the Environmental Data Application Dashboard: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Ionizing radiation in particular has been established in ground-based experiments as being correlated with increased risk of carcinogenesis and cardiovascular and neurological effects. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (osdr.nasa.gov) has developed two Web applications: the Environmental Data Application (EDA) and a radiation-specific RadLab. Each consists of an API (application programming interface) and an associated GUI (graphical user interface) that provide single points of access to the data. To date, OSDR has focused on the sensors from payloads and radiation detectors located on the ISS. The Web applications process telemetry information and associated data, such as spacecraft location and orientation, from multiple international databases. The applications’ request syntax enables users to interrogate these data by craft, sensor type, time range, radiation type (galactic cosmic rays, solar particle events, the contribution of the South Atlantic Anomaly), facilitating arbitrary comparisons of original source data at varying time resolutions. The applications provide programmatic access for use in computational pipelines and GUIs for data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗
NASA NTRS1978

Landsat spectral signatures - Studies with soil associations and vegetation

The effect of soils and vegetation upon Landsat spectral properties was investigated for a 12,950 hectare area. Six soil associations used for corn, small grains, and grass were analyzed for two dates during the 1974 growing season. Landsat scenes for April 19 and June 30 were studied to separate categories of agricultural land use and to assess the influence of soil association on the spectral signatures of vegetation and bare ground. The April 19 data were useful to separate cropland from grassland and to locate areas of open water. The June 30 data showed that soil associations could not consistently be separated within the data of a single vegetative type; however, the results showed that soils did influence all vegetative spectral reflectances to some degree. Because soils did influence vegetative spectral reflectance, a generalized training set containing data points from each of the six soil associations was used to separate four categories of agricultural land use in the 12,950 hectare test area. An accuracy of about 94% was obtained.

Westin, F. C.↗
NASA NTRS2009

Network device interface for digitally interfacing data channels to a controller via a network

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

Ellerbrock, Philip J.↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗