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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 1,441 records · Page 80

Data Validation Package - April and July 2015 Groundwater and Surface Water Sampling at the Gunnison, Colorado, Processing Site

This event included annual sampling of groundwater and surface water locations at the Gunnison, Colorado, Processing Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites. Samples were collected from 28 monitoring wells, three domestic wells, and six surface locations in April at the processing site as specified in the 2010 Ground Water Compliance Action Plan for the Gunnison, Colorado, Processing Site. Domestic wells 0476 and 0477 were sampled in July because the homes were unoccupied in April, and the wells were not in use. Duplicate samples were collected from locations 0113, 0248, and 0477. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. No issues were identified during the data validation process that requires additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package - June 2016 Groundwater and Surface Water Sampling at the Green River, Utah, Disposal Site

This event included annual sampling of groundwater and surface water locations at the Green River, Utah, Disposal Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for US. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lrnldownloads/sampling-and- analysis-plan-us-department-energy-office-legacy-management-sites). Samples were collected from 15 monitoring wells and two surface locations at the disposal site as specified in the draft 2011 Ground Water Compliance Action Plan for the Green River, Utah, Disposal Site. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. A duplicate sample was collected from location 0179. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. See Attachment 2, Trip Reports for additional details. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that requires additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package - July 2016 Groundwater Sampling at the Gunnison, Colorado, Disposal Site

Groundwater sampling at the Gunnison, Colorado, Disposal Site is conducted every 5 years to monitor disposal cell performance. During this event, samples were collected from eight monitoring wells as specified in the 1997 Long-Term Surveillance Plan for the Gunnison, Colorado, Disposal Site. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for US Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and­ analysis-plan-us-department-energy-office-legacy-management-sites). Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. A duplicate sample was collected from location 0723. Water levels were measured at all monitoring wells that were sampled and seven additional wells. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that require additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗

Framework for an adaptive integrated observation system using a hierarchy of machine learning approaches

Focal Area(s): 1. Data acquisition enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, and hardware-related efforts involving AI. 2. Insight gleaned from complex measurements using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI Science Challenge and Rationale: Atmospheric processes are stochastic, occur at scales from the micrometer to many kilometers, and are constantly changing over time. Characterizing these interactions and associated environmental conditions using traditional measurement techniques is difficult and can take years to build statistics on atmospheric phenomena that occurs episodically. Developing new innovative approaches to modify sampling strategies in real-time would enable the routine collection of targeted measurements focused on a specific set of science questions.

54 ENVIRONMENTAL SCIENCES↗

Strategic Petroleum Reserve Enhanced Monitoring Compendium - FY 2021

The Strategic Petroleum (SPR) is the world’s largest supply of crude oil. The reserve consists of fours sites in Louisiana and Texas. Each site stores crude in deep, underground salt caverns. It is the mission of the SPR’s Enhanced Monitoring Program to examine all available data to inform our understanding of each site. This report discusses the data, processes and results for each of the four sites.

02 PETROLEUM↗

Support for the Second MOSAiC Science Conference support (Final Report)

This is a final report for a conference support project. The US Department of Energy’s Atmospheric System Research Program provided funding support for the Second MOSAiC Science Conference. MOSAiC is the Multidisciplinary drifting Observatory for the Study of Arctic Climate, a yearlong, international expedition into the rapidly changing Arctic sea ice. The expedition collected measurements of the atmosphere, sea ice, and ocean to study coupled physical, chemical, and biological processes. The Second MOSAiC Science Conference provided an important opportunity to bring the MOSAiC-interested community together to discuss MOSAiC data, scientific analyses, synthesis, modeling activities, and more. Overall, the conference was a significant success and has motivated and facilitated a great deal of ongoing research. The support provide by this project was used along with support from other agencies to implement a participant support program that enabled participation in the conference by a diverse collection of researchers from many different countries and disciplines, 60% of whom were female. Most of these participants were Early Career Researchers. Participation by these researchers was vital to the overall success of the conference and has helped to build leadership and research skills for the participants that will serve both themselves and the broader scientific community in the future.

54 ENVIRONMENTAL SCIENCES↗

Colorado State University (CSU) X-Band Precipitation Radar Plan Position Indicator Data Processed with Corrected Moments in Antenna Coordinates (CMAC) Value-Added Product Report

In 2010 the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility procured 3- and 5-cm wavelength radars for documenting the macrophysical, microphysical, and dynamical structure of precipitating systems. To maximize the scientific impact, ARM supported the development of an application chain to correct for various phenomena in order to retrieve the “point” values of moments of the radar spectrum and polarimetric measurements. We have now used the lessons learned from the processing of the 3- and 5-cm wavelength radars obtained by ARM to help process X-band radar data from the Surface Atmospheric Integrated Field Laboratory (SAIL) field campaign. This report details the motivation, science, and progress to date as well as charting a path forward.

54 ENVIRONMENTAL SCIENCES↗

Iron-starvation induces photosystem I antenna remodeling in green algae

Dunaliella salina and Dunaliella tertiolecta are extremophile, marine algae that can survive in very low Fe conditions. In this study, we used TMT-proteomics to compare the Fe starvation responses to the Fe replete responses. Samples were digested with trypsin, labeled with TMT 10-Plex, then analyzed by LC-MS/MS. Data was searched with MS-GF+ using PNNL's DMS Processing pipeline.

59 BASIC BIOLOGICAL SCIENCES↗

2024 Standard Scenarios: A U.S. Electricity Sector Outlook

This data corresponds to the 2024 Standard Scenarios report, which contains a suite of forward-looking scenarios of the possible evolution of the U.S. electricity sector through 2050. These files contain modeled projections of the future. Although we strive to capture relevant phenomena as comprehensively as possible, the models used to create this data are unavoidably imperfect, and the future is highly uncertain. Consequentially, this data should not be the sole basis for making decisions. In addition to drawing from multiple scenarios within this set, we encourage analysts to also draw on projections from other sources, to benefit from diverse analytical frameworks and perspectives when forming their conclusions about the future of the power sector. For further discussions about the limitations of the models underlying this data, see section 1.4 of the "ReEDS Documentation" linked below. For scenario descriptions, input assumptions, and metric definitions for the data in these files, see the "2024 Standard Scenarios Report" linked below.

2050↗

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗

Graph-based featurization methods for classifying small molecule compounds

For over a decade, drug-induced liver injury (DILI) has posed significant drawbacks in the synthesis and development of drugs and remains a consequential concern. With finite success within the existing preclinical models, DILI is one of the main causes of drug withdrawal or termination from the market. Particularly, this withdrawal occurs during the late stages of drug development (Kullak-Ublick, 2017). Since DILI is difficult to diagnose and treat, it has become an obstacle in the drug production market that in turn affects clinicians, pharmaceutical companies, and consumers. We propose a method for learning features of DILI-positive drugs based on the graphical relationships and patterns they possess within a network of biological databases. We also train various statistical and machine learning models on these learned features in order to classify the drugs as DILI-positive or negative. Our methods include Random Forest, Neural networks, and logistic regression classification. We utilize labeled DILI-positive and DILI-negative datasets, which were developed by the FDA and the National center for toxicological research, as well as additional literature datasets (Thakkar, 2020) in order to validate our results and assess our featurization and model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Introducing the Video In Situ Snowfall Sensor (VISSS)

The open-source Video In Situ Snowfall Sensor (VISSS) is introduced as a novel instrument for the characterization of particle shape and size in snowfall. The VISSS consists of two cameras with LED backlights and telecentric lenses that allow accurate sizing and combine a large observation volume with relatively high pixel resolution and a design that limits wind disturbance. VISSS data products include various particle properties such as maximum extent, cross-sectional area, perimeter, complexity, and sedimentation velocity. Initial analysis shows that the VISSS provides robust statistics based on up to 10 000 unique particle observations per minute. Comparison of the VISSS with the collocated PIP (Precipitation Imaging Package) and Parsivel instruments at Hyytiälä, Finland, shows excellent agreement with the Parsivel but reveals some differences for the PIP that are likely related to PIP data processing and limitations of the PIP with respect to observing smaller particles. The open-source nature of the VISSS hardware plans, data acquisition software, and data processing libraries invites the community to contribute to the development of the instrument, which has many potential applications in atmospheric science and beyond.

54 ENVIRONMENTAL SCIENCES↗

Where on the moon - An Apollo systems engineering problem.

Approaches used in the selection of lunar landing sites are discussed, giving attention to a survey of major constraints affecting site selection. The science objectives of lunar exploration are considered, taking into account exploration goals, the acquisition of required data, mission science planning, orbital science, lunar surface traverse capability, the mare basalts, lunar interior composition, regolith, breccias, lunar chronology, lunar surface processes, and the origin of the moon. Subjects examined in connection with Apollo system capabilities include the Apollo missions, development missions, lunar exploration missions, mission design requirements, navigation, launch vehicle considerations, methods of determining accessibility, lunar module descent considerations, landing site redesignation, and questions of landability.

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Space Station Needs, Attributes and Architectural Options. Contractor orientation briefings

Requirements are considered for user missions involving life sciences; astrophysics, environmental observation; Earth and planetary exploration; materials processing; Spacelab payloads; technology development; and communications are analyzed. Plans to exchange data with potential cooperating nations and ESA are reviewed. The capability of the space shuttle to support space station activities are discussed. The status of the OAST space station technology study, conceptual architectures for a space station, elements of the space-based infrastructure, and the use of the shuttle external tank are also considered.

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Current status and future developments in radar remote sensing

Some of the major initiatives and directions of remote sensing using SAR (Synthetic Aperture Radar) data alone and in conjunction with other sensors for Earth science investigations are outlined. Specific emphasis is on areas key to global monitoring using SAR data from spaceborne platforms: calibration, geophysical processing, and generation of digital elevation models. Calibration as used here encompasses end to end system characterization over the life of a sensor and characterization of data products relative to past and future sensors. Geophysical processing is defined here to include any processing which results in derived geophysical units. An additional data type, topography, which is required to complete the three dimensional view of surface properties and correct for distortions inherent in SAR is discussed. Future challenges in radar remote sensing include development of strategies to extrapolate from regional to global scale models and development of new sensor technology.

Evans, Diane L.↗

Current status and future developments in radar remote sensing

Some of the major initiatives and directions of remote sensing using SAR (Synthetic Aperture Radar) data alone and in conjunction with other sensors for earth science investigations are outlined. Specific emphasis is on areas key to global monitoring using SAR data from spaceborne platforms: calibration, geophysical processing, and generation of digital elevation models. Calibration as used here encompasses end-to-end system characterization over the life of a sensor and characterization of data products relative to past and future sensors. Geophysical processing is defined here to include any processing which results in derived geophysical units. An additional data type, topography, which is required to complete the three-dimensional view of surface properties and correct for distortions inherent in SAR is discussed. Future challenges in radar remote sensing include development of strategies to extrapolate from regional to global scale models and development of new sensor technology.

Evans, Diane L.↗

R and T report: Goddard Space Flight Center

The 1993 Research and Technology Report for Goddard Space Flight Center is presented. Research covered areas such as (1) flight projects; (2) space sciences including cosmology, high energy, stars and galaxies, and the solar system; (3) earth sciences including process modeling, hydrology/cryology, atmospheres, biosphere, and solid earth; (4) networks, planning, and information systems including support for mission operations, data distribution, advanced software and systems engineering, and planning/scheduling; and (5) engineering and materials including spacecraft systems, material and testing, optics and photonics and robotics.

Soffen, Gerald A.↗

The Laboratory for Terrestrial Physics

The Laboratory for Terrestrial Physics is dedicated to the advancement of knowledge in Earth and planetary science, by conducting innovative research using space technology. The Laboratory's mission and activities support the work and new initiatives at NASA's Goddard Space Flight Center (GSFC). The Laboratory's success contributes to the Earth Science Directorate as a national resource for studies of Earth from Space. The Laboratory is part of the Earth Science Directorate based at the GSFC in Greenbelt, MD. The Directorate itself is comprised of the Global Change Data Center (GCDC), the Space Data and Computing Division (SDCD), and four science Laboratories, including Laboratory for Terrestrial Physics, Laboratory for Atmospheres, and Laboratory for Hydrospheric Processes all in Greenbelt, MD. The fourth research organization, Goddard Institute for Space Studies (GISS), is in New York, NY. Relevant to NASA's Strategic Plan, the Laboratory ensures that all work undertaken and completed is within the vision of GSFC. The philosophy of the Laboratory is to balance the completion of near term goals, while building on the Laboratory's achievements as a foundation for the scientific challenges in the future.

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