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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Electromagnetic pinned solitons for space debris detection

Electromagnetic “pinned” solitons in the form of stationary nonlinear waves are studied within the framework of an inertial magneto-hydrodynamic model. These structures, that can arise when a charged source moves in a magnetized plasma, have a velocity that is equal to the source velocity and, hence, appear as “pinned” structures that envelope the source. We investigate the excitation of such solitons in the Low Earth Orbit region due to the passage of charged orbital debris objects. The spatial size of these electromagnetic solitons, typically of the order of a few ion skin depths, can be very large in this region. Such solitons can be detected using a variety of ground- or orbit-based radio sounding techniques and may provide a convenient additional means of tracking small sized orbital debris objects that are difficult to spot optically.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗
DOE OSTI2021

SPRUCE Ground Observations of Phenology in Experimental Plots, 2020

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2020, the fifth full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2020 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) format containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2020. User note: Ground observations of phenology from 2016-2021 are available. SPRUCE Ground Observations of Phenology in Experimental Plots 2021, https://doi.org/10.25581/spruce.099/1874936 for the most recent data as well as links to all other ground phenology datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SPRUCE Ground Observations of Phenology in Experimental Plots, 2021

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2021, the sixth full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2021 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) format containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2021. User note: Ground observations of phenology from 2016-2020 are available. See the user guide for links to all other ground phenology datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SPRUCE Ground Observations of Phenology in Experimental Plots, 2022

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2022 (2022-03-28 to 2021-11-17), the seventh full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2022 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2022.

SPRUCE experiment, plant phenological phases, Spru↗
DOE OSTI2024

SPRUCE Ground Observations of Phenology in Experimental Plots, 2023

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2023 (2023-03-30 to 2023-11-29), the eighth full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2023 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2023.

Marcell Experimental Forest↗
DOE OSTI2025

SPRUCE Ground Observations of Phenology in Experimental Plots, 2024

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2024 (2025-03-06 to 2025-11-21), the ninth full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2024 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2024.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Townsend’s Ground Squirrel Conservation on the Hanford Site for Calendar Year 2022: Translocation to Support At-Risk Ground Squirrel Populations

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitat under DOE-RL stewardship at the Hanford Site required for accurate ecological impact assessment decision-making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). In addition, ecological monitoring helps ensure that DOE-RL, its contractors and other entities conducting activities on the Hanford Site are in compliance with the Hanford Site Comprehensive Land Use Plan (DOE/EIS-0222-F). DOE-RL places priority on monitoring those plant and animal species or habitats with specific regulatory protections or requirements; or that are rare and/or declining (federal or state listed endangered, threatened, or sensitive species); or of significant interest to federal, state, or tribal governments or the public.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ultrafast structural dynamics of UV photoexcited cis , cis -1,3-cyclooctadiene observed with time-resolved electron diffraction

Conjugated diene molecules are highly reactive upon photoexcitation and can relax through multiple reaction channels that depend on the position of the double bonds and the degree of molecular rigidity. Understanding the photoinduced dynamics of these molecules is crucial for establishing general rules governing the relaxation and product formation. Here, in this study, we investigate the femtosecond time-resolved photoinduced excited-state structural dynamics of cis,cis-1,3-cyclooctadiene, a large-flexible cyclic conjugated diene molecule, upon excitation with 200 nm using mega-electron-volt ultrafast electron diffraction and trajectory surface hopping dynamics simulations. We tracked the photoinduced structural changes from the Franck–Condon region through the conical intersection seam to the ground state. Our findings revealed a novel primary reaction coordinate involving ring distortion, where the ring stretches along one axis and compresses along the perpendicular axis. The nuclear wavepacket remains compact along this reaction coordinate until it reaches the conical intersection seam, and it rapidly spreads as it approaches the ground state, where multiple products are formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Deploying and Tracking Software with NCCS Software Provisioning

The National Center for Computational Sciences (NCCS) at Oak Ridge National Laboratory has a long history of deploying ground-breaking leadership-class supercomputers for the U.S. Department of Energy. The latest in this line of supercomputers is Frontier, the first supercomputer to break the exascale barrier (1018 floating-point operations per second) on the TOP500 list. Frontier serves a wide array of scientific domains, from traditional simulation-based workloads to newer AI and Machine Learning workloads. To best serve the NCCS user community, NCCS uses Spack to deploy a comprehensive software stack of scientific software packages, providing straightforward access to these packages through Lmod Environment Modules. Maintaining a large software stack while also including multiple new compiler releases each year is a very time-consuming task. Additionally, it is not straightforward to provide a software stack alongside existing vendor-provided software such as the HPE/Cray Programming Environment (CPE), and existing CPE, Spack, and Lmod integration does not allow for multiple versions of GPU libraries such as AMD’s ROCm to be used. To address these challenges and shortcomings, NCCS has developed the NCCS Software Provisioning tool (NSP)1, a tool for deploying and monitoring software stacks on HPC systems. NSP allows NCCS to quickly and effectively provision software stacks from the ground up using template-driven recipes and configuration files. NSP is successfully deployed on Frontier and several other NCCS clusters, enabling the NCCS software team to quickly deploy software stacks for newly-released compilers, expand current software offerings, better support GPU-based software, and monitor Lmod module usage to identify unused software packages that can be removed from the software stack. In this work, we discuss the shortcomings of the previous CPE, Spack, and Lmod usage at NCCS, provide further details on the implementation and structure of NSP, then discuss the benefits that NSP provides.

Rentschler, Asa [ORNL] (ORCID:0009000597694743)↗
DOE OSTI2020

Understanding the Spatial Organization of Simultaneous Heavy Precipitation Events Over the Conterminous United States

We introduce the idea of simultaneous heavy precipitation events (SHPEs) to understand whether extreme precipitation has a spatial organization manifested as specified tracks or contiguous fields with inherent scaling relationships. For this purpose, we created a database of SHPEs using ground-based precipitation observations recorded by the daily Global Historical Climatology Network across the conterminous United States during 1900–2014. SHPEs are examined for their seasonality, spatial manifestation, orientation, and areal extent. We quantified the spatial distribution of the centroids and principal axes of SHPEs and their quasi-elliptical manifestations, azimuthal orientations, and areal extents on the ground. Four seasons, December-January-February (DJF), March-April-May (MAM),June-July-August (JJA), and September-October-November (SON) are considered to examine the spatial patterns and associated large-scale atmospheric circulations. Results indicate that there are 54, 58, 103, and204 SHPEs in DJF, MAM, JJA, and SON seasons, and their longest stretches range on average between 650and 1,600, between 850 and 1,500, between 950 and 1,550, and between 750 and 1,450 km, respectively. SHPEs in the DJF, MAM, and JJA seasons occur mostly over the Pacific coast and central and midwestern United States, respectively. The atmospheric circulation patterns and mechanisms of precipitable water vapor and moisture transport in the atmosphere are also discussed in relation to these SHPEs. Power laws explain SHPEs' underlying area scaling behavior in all the four seasons, with stronger evidence in DJF and MAM. A seasonal spatial risk model is developed to predict the likelihood of SHPEs. Quantifying the characteristics of SHPEs and modeling their footprints can improve the projections of flood risk and understanding of damages to interconnected infrastructure systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NGEE Arctic Tram: Radiation and Environmental Measurements over Low- and High-Centered Polygon Vegetation Communities, Barrow, Alaska, 2014-2017

These data were generated from an observational platform (Tram), an automated cart carrying a suite of radiation and remote sensing instruments running on 68 meters of elevated track 1 to 1.5 meters above the surface of the vegetation communities of low- and high-centered polygon ground. The Tram is in the footprint of the NGEE Arctic/AmeriFlux eddy covariance flux tower (US-NGB) at the Barrow Environmental Observatory, Barrow, Alaska, and operated before, during, and after the growing seasons of 2014-2017. Dataset includes one user guide (*.pdf) with final and raw *.csv data files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Seismic Recovery of Acoustic Source Height During the OSIRIS-REx Sample Return Capsule Re-Entry

Controlled hypersonic reentries with well‐constrained trajectories are exceedingly rare, yet they provide valuable reference cases for validating geophysical source characterization methods applicable to bolides and space debris. The 24 September 2023 re‐entry of the OSIRIS‐REx Sample Return Capsule, the first interplanetary capsule to return over the contiguous United States in nearly two decades, presented such an opportunity. Here, we present seismic observations of this event recorded at 16 stations across three sites at ground distances of 7–20 km from the trajectory. Using eigenray tracing through ground‐to‐space atmospheric specifications, we invert picked acoustic‐to‐seismic travel times for effective shock‐generated acoustic source altitudes along the known trajectory. The method recovers source heights of 57.9–59.5 km with travel‐time residuals <1 s across all stations. The seismic‐derived source heights, when compared at their along‐track positions, fall within the range of previously published infrasound‐derived heights for the corresponding trajectory segment, with intermethod differences comparable with the timing‐based uncertainty. These results suggest that air‐to‐ground coupling does not introduce a resolvable systematic timing bias in the picked near‐field seismic arrivals, supporting seismic observations as a complementary tool for altitude estimation of bolides, re‐entry vehicles, and other hypersonic atmospheric sources.

Silber, Elizabeth Allaryce [Sandia National Labora↗
DOE OSTI2023

Hanford Site Ground Squirrel Monitoring Report for Calendar Year 2021

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing U.S. Department of Energy (DOE) activities. Ecological monitoring data provide baseline information about the plants, animals, and habitat under DOE-RL stewardship at the Hanford Site required for accurate ecological impact assessment decision making under the National Environmental Policy Act and Comprehensive Environmental Response, Compensation, and Liability Act. In addition, ecological monitoring helps ensure that DOE-RL, its contractors, and other entities conducting activities on the Hanford Site are in compliance with DOE/EIS- 0222-F, Hanford Site Comprehensive Land Use Plan (CLUP). DOE-RL places priority on monitoring those plant and animal species or habitats with specific regulatory protections or requirements; that are rare and/or declining (federal or state listed endangered, threatened, or sensitive species); or of significant interest to federal, state, or Tribal governments or the public.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, with impacts comparable to many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study presents an objective derecho detection approach capable of automatically identifying derechos through both observations and model results. The approach is grounded in a physically based definition of derechos and integrates three algorithms: (1) the Python Flexible Object Tracker (PyFLEXTRKR) algorithm to track mesoscale convective systems (MCSs), (2) a semantic segmentation convolutional neural network to identify bow echoes, and (3) a comprehensive classification algorithm to detect derechos within MCS life cycles and distinguish derecho-producing from non-derecho-producing MCSs. Using this approach, we developed a novel high-resolution (4 km and hourly) observational dataset of derechos and accompanying derecho-producing MCSs over the United States east of the Rocky Mountains from 2004 to 2021. The dataset consists of two subsets based on different gust speed data sources and is analyzed to document the climatology of derechos in the United States. On average, 12–15 derechos are identified per year, aligning with previous estimations (∼6–21 events annually). The spatial distribution and seasonal variation patterns are consistent with prior studies, showing peak occurrences in the Great Plains and the Midwest during the warm season. Additionally, during the study period, derechos account for approximately 3.1 % of measured damaging gusts (≥25.93 m s−1) over the eastern United States. The dataset is publicly available at https://doi.org/10.5281/zenodo.14835362 (Li et al., 2025).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Long-Term Photovoltaic System Performance in Cold, Snowy Climates

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize northern and alpine communities due to their scalability and affordability. However, a barrier to large-scale adoption of PV in cold climates is long-term performance uncertainty under snowfall, freeze-thaw cycles, low temperatures, and high winds. In this work, we provide a comprehensive review of published silicon degradation rates in cold Koppen-Geiger climate classifications of Dfb (humid continental), Dfc (subarctic), and ET (tundra). We first analyze the system degradation rates of three subarctic ground-mounted photovoltaic sites in North America using the RdTools year-on-year method: an Al-BSF double-axis tracking site in Fairbanks, Alaska (65degrees N); a PERC and silicon heterojunction bifacial vertical and south-tilted site in Fairbanks, Alaska; and a PERC south-facing fixed-tilt site in Fort Simpson, Northwest Territories (62degrees N). Degradation rates of these newly analyzed sites vary between -0.4%/year and -1.5%/year. Combining these data with previously reported cold climate degradation rates, we show that the distribution of cold climate degradation peaks at -0.1%/year to -0.2%/year but has a large tail with rates above -0.5%/year. The average reported cold climate degradation rate is -0.45%/year, whereas the median value is -0.33%/year. These results suggest that despite frequent freeze-thaw cycles and potential exposure to high wind and snow loads, PV systems in cold climates tend to degrade slower than PV systems in warmer climates. The limited sample size of reported degradation rates in cold climates (27) motivates the need for further data acquisition and monitoring efforts as new technologies are deployed.

14 SOLAR ENERGY↗
DOE OSTI2025

SSAPy - Space Situational Awareness for Python

SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from low-Earth into the cislunar regime. Orbits can be flexibly specified from common input formats such as Keplerian elements or two-line element (TLE) data files. SSAPy allows users to model satellites and specify parameters such as satellite area, mass, and drag coefficients. SSAPy includes a customizable force-propagation with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes use of various community integration methods and can calculate time-evolved orbital quantities, including satellite magnitudes and state vectors. Users can specify various space- and ground-based observation models with support for multiple coordinate and reference frames. SSAPy also supports orbit analysis and propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification. The majority of SSAPy’s methods are vectorized and parallelizable, allowing for effective use of high-performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to visualize orbits and trajectories. Examples are shown in Figure 1 and Figure 2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Novel Segmentation Algorithm for the ARM User Facility All-Sky Imagers Using Machine Learning Applications

Cloud cover plays a pivotal role in modulating the Earth's energy budget through the reflection of incoming solar radiation and the trapping of outgoing longwave radiation. Ground-based all-sky imagers offer an objective assessment of cloud cover that can be used to estimate solar irradiance, classify cloud types, track cloud movement, and serve as a benchmark 10 for the evaluation of satellite and reanalysis data products. The Atmospheric Radiation Measurement (ARM) user facility has utilized all-sky imagers for more than 25 years to monitor cloud cover and augment its comprehensive suite of atmospheric measurements. Following the retirement of its Total Sky Imager (TSI), ARM recently deployed the TSI’s successor, the All Sky Imager (ASI-16 camera systems). To provide a smooth transition and continuity to the vast amount of knowledge gathered by the TSI over the years, while addressing typical deployment issues, we developed a novel pixel segmentation algorithm, 15 the ASI Sky Cover (ASISKYCOVER). ASISKYCOVER builds on the different strengths and properties of the TSI processing algorithm while integrating machine learning techniques, ensuring data validity and accuracy across diverse atmospheric conditions. It enhances cloud cover characterization with new features such as artifact detection and uncertainty quantification. ASISKYCOVER also includes cloud cover estimates for near-zenith (narrow field-of-view) and reduces susceptibility to false detections. This study introduces ASISKYCOVER, details its algorithm framework, and demonstrates its capabilities using a 20 year-long dataset from the ARM Southern Great Plains site. Comparisons with co-located TSI data and other ARM measurements, such as zenith-pointing radars and lidars, are presented, underscoring the ASISKYCOVER’s potential to improve cloud cover analyses and data evaluation efforts, as well as to be integrated into higher-level data products that synergize instrument suites to generate new and insightful information

Silber, Israel↗