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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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335 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

UAS remote sensing (DJI Phantom 4 RTK platform): RGB orthomosaic, digital surface and canopy height models, plant functional type map, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using a DJI Phantom 4 RTK unoccupied aerial system (UAS) ? operated by the University of Maine Wheatland Geospatial Lab (https://wheatlandlab.org/). This package includes data from 17 flights flown over the NGEE-Arctic Council, Kougarok, Kougarok Mile80, Teller, and Teller Mile32 sites in July 2019. The Phantom 4 RTK is a drone platform that collects very high spatial resolution optical red/green/blue (RGB) imagery. Derived image products include point cloud, ortho-mosaiced RGB, a digital surface model (DSM) using the structure from motion (SfM) technique, and a canopy height model (CHM). Unprocessed and processed data products (1,000+ files) are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *hdr,), ENVI image file (*.dat), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. 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 OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance and normalized difference vegetation index, Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) – operated by the Terrestrial Ecosystem Science & Technology group https://www.bnl.gov/envsci/testgroup/ at Brookhaven National Laboratory. This package includes data from 19 flights flown over the NGEE-Arctic, Kougarok Mile Marker (MM) 80, Kougarok Fire Complex (KFC) and Teller MM 27 sites in July 2022. Derived image products include point cloud, ortho-mosaiced multispectral image, a digital surface model (DSM) using the structure from motion (SfM) technique, and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats.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 OSTI2025

The LSST Camera (LSSTCam)

The LSST Camera is the sole instrument for the NSF-DOE Vera C. Rubin Observatory and consists of a 3.2 gigapixel focal plane mosaic with in-vacuum controllers, dedicated guider and wavefront CCDs, a three-element corrector whose largest lens is 1.55m in diameter, six optical interference filters covering a 320-1050nm band pass with an out-of-plane filter exchange mechanism, and camera slow control and data acquisition systems capable of digitizing each image in 2 seconds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Reference Site Condition Datasets for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. Further information on the datasets and how they were created can be found in: Biglu, M., M. Hall, E. Lozon, S. Housner. 2024. Reference Site Conditions for Floating Wind Arrays in the United States. Golden, CO: National Renewable Energy Laboratory (NREL). NREL/TP-5000-89897. The data are also available at: https://github.com/FloatingArrayDesign/SiteConditions The content of each dataset is as follows: _NOW23_wind.txt: Hourly NOW-23 wind data up to a height of 400 meter. _metocean_1hr.txt: Hourly time series including wind, wave, surface current and temperature data. _Summary.xlsx: Metocean data, including extreme values, joint probability distributions and monthly statistics. _usSEABED_soil.csv: Extract of the usSEABED database for this specific site. _bathymetry_200m.txt (and 500m, 1000m): Gridded seabed depth data.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

A Novel Approach to Simulate Realistic Concrete Microstructures under Irradiation

The concrete biological shield of light water reactors is exposed to high neutron and gamma irradiation doses in the long term. Irradiation deteriorates the physical and mechanical properties of concrete. Such effects need to be investigated to predict the concrete’s performance in the event of a lifetime extension of a nuclear power plant. This work combines high-resolution characterization techniques with fast-Fourier transform (FFT)-based 2-D simulations to evaluate the radiation-induced volumetric expansion (RIVE) and damage in concrete microstructures under neutron irradiation. Two concrete microstructures from samples provided by the Japan Concrete Aging Management Program (JCAMP) were characterized using micro x-ray fluorescence (mXRF) to obtain elemental intensity maps, and energy-dispersive x-ray spectroscopy to complement mXRF with local elemental information for Na. Minerals and cement paste are then identified based on the elemental composition to produce high-resolution phase maps, resulting in a more accurate representation of the microstructures compared to previous work. Simulations of radiation-induced volumetric expansion (RIVE), creep, and damage in JCAMP concrete use the fast Fourier transform (FFT)-based code Microstructure Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) combined with the irradiated minerals, aggregates, and concrete (IMAC) database, which contains mineral-specific RIVE models. Overall, the simulation results are in fair agreement with experimental data.

Cheniour, Amani↗
DOE OSTI2020

Spatiotemporal variations of albedo in managed agricultural landscapes: inferences to global warming impacts (GWI)

Albedo can be used to quantify ecosystem and landscape contributions to local and global climate. Such contributions are conventionally expressed as radiative forcing (RF) and global warming impact (GWI). We contextualize our results within landscape carbon production and storage to highlight the importance of changes in albedo for landscape GWI from multiple causes, including net ecosystem production (NEP) and greenhouse gas (GHG) emissions. Objective To examine the spatiotemporal changes in albedo (Δα) in contrasting managed landscapes through calculations of albedo-induced RF (RF Δα ) and GWI (GWI Δα ) under different climatic conditions. Methods We selected five contrasting landscapes within the Kalamazoo River watershed in southern Michigan USA as proof of concept. The daily MCD43A3 MODIS (V006) product was used to analyze the inter- and intra-annual variations of growing season albedo. In addition, the variations of RF Δα and GWI Δα were computed based on landscape composition and climate. Results The RF Δα (-5.6 W m -2 ) and GWI Δα (-1.3 CO 2eq ha -1 year -1 ) were high in forest-dominated landscapes, indicating cooling effects and CO 2eq mitigation impacts similar to crops. The CO 2eq mitigation of cropland-dominated landscapes was on average 52% stronger than forest-dominated landscapes. In the landscape with the highest proportion of forest, under dry and wet conditions CO 2eq mitigation was reduced by up to 24% and ~ 30%, respectively; in one cropland-dominated landscape wet conditions reduced CO 2eq mitigation by 23%. Conclusions Findings demonstrate that quantifying spatiotemporal changes in albedo in managed landscapes and under different climatic conditions is essential to understand how landscape modification affects RF Δα and GWI Δα and thereby contributes to ecosystem-level GWI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Role of Non-Local Effects on Surface Sensible Heat Flux Under Different Types of Thermal Structures Over the Arctic Sea-Ice Surface

The effects of atmospheric thermal structure on the surface energy flux are poorly understood over the Arctic sea-ice surface. Here, we explore the mechanism of sensible heat exchange under different types of thermal structures over the Arctic sea-ice surface by using data collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition. The quadrant analysis indicates that strong surface temperature inversions below 100 m enhance non-local effects on the positive (upward) sensible heat flux ($\overline{w'θ'}$) through entrainment of large eddies from the convective boundary layer aloft. However, strong surface inversions restrict the contributions of large eddies to the negative (downward) $\overline{w'θ'}$ due to intensified surface stability. By inspecting the existing parameterization schemes, we found that the European Center for Medium-Range Weather Forecasts Integrated Forecasting System scheme fails to predict the impacts of non-local processes on the positive $\overline{w'θ'}$, and an adjustment term to correct the bias of parameterized $\overline{w'θ'}$ is proposed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tethered balloon measurements reveal enhanced aerosol occurrence aloft interacting with Arctic low-level clouds

Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N 12−150 ) and above 150 nm (N >150 ). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N 12−150 up to 3,000 cm −3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N >150 to 310 cm −3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N >150 by up to 100%, while the decrease in N 12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N 12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N 12−150 and N >150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ARM FY2025 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is dedicated to delivering high-quality radar data that significantly advance our understanding of cloud and precipitation processes, improving climate models. With radars operating across diverse frequencies, scanning modes, and global climate conditions, extensive staffing is essential for effective management. Due to current staffing constraints, achieving the expected level of operational excellence requires a more strategic approach. To address this challenge, ARM has developed an operational radar plan for the upcoming Fiscal Year 2025 (FY25) based on budget and staffing considerations. This report summarizes the Fiscal Year 2024 (FY24) ARM radar-related activities and outlines the strategic plan for FY25. It presents a comprehensive radar plan that includes detailed activities, priorities, and a projected timeline aligned with the ARM radar roadmap. Key tasks, detailed in Table 1, cover various radar operational stages and coordinated efforts among ARM teams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

arsclwacr1kolliasshp.c0

arsclwacr1kolliasshp provides cloud boundaries and best-estimate time-height fields of uncalibreated radar moments on a ship. The uncalibreated WACR measurements are combined with observations from the micropulse lidar, ceilometer. The asiarsclwacrbnd1kolliasM1.c0 datastream contains cloud base and cloud layer boundaries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

arsclwacrbnd1kolliasshp.c0

arsclwacrbnd1kolliasshp provides cloud boundaries of radar moments. The uncalibreated WACR measurements are combined with observations from the micropulse lidar, ceilometer. The asiarsclwacrbnd1kolliasM1.c0 datastream contains cloud base and cloud layer boundaries.

54 ENVIRONMENTAL SCIENCES↗